Assessment of Potential Mining Impacts on Salmon Ecosystems of Bristol Bay, Alaska (External Review Draft)

                              External Review Draft | EPA910-R-12-004c | May 2012
   United States
   Environmental Protection
   Agency
       An Assessment of Potential Mining Impacts
      on  Salmon Ecosystems of Bristol Bay, Alaska
                                          Volume 3 - Appendices E-l

U.S. Environmental Protection Agency, Seattle, WA
www.epa.gov/bristolbay
                  External Review Draft - Do Not Cite or Quote

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DRAFT                                                EPA910-R-12-004c
DO NOT CITE OR QUOTE                                     May 2012
                                                     External Review Draft
                                                     www.epa.gov/bristolbay
      An Assessment of Potential Mining Impacts on
         Salmon Ecosystems of Bristol Bay, Alaska

                   Volume 3 - Appendices E-l
                                NOTICE
     THIS DOCUMENT IS AN EXTERNAL REVIEW DRAFT. It has not been formally released by
     the U.S. Environmental Protection Agency and should not be construed to represent Agency
     policy. It is being circulated for comment on its technical accuracy and policy implications.
                       U.S. Environmental Protection Agency
                               Seattle, WA

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                                 DISCLAIMER

This document is distributed solely for the purpose of pre-dissemination peer review under
applicable information quality guidelines. It has not been formally disseminated by the U.S.
Environmental Protection Agency (USEPA). It does not represent and should not be
construed to represent any Agency determination or policy. Mention of trade names or
commercial products does not constitute endorsement or recommendation for use.

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                                  CONTENTS


VOLUME 1
An Assessment of Potential Mining Impacts on Salmon Ecosystems of Bristol Bay, Alaska


VOLUME 2
APPENDIX A: Fishery Resources of the Bristol Bay Region

APPENDIX B: Characterizations of Selected Non-Salmon Fishes Harvested in the Fresh
Waters of Bristol Bay

APPENDIX C: Wildlife Resources of the Nushagak and Kvichak River Watersheds

APPENDIX D: Ecological Knowledge and Cultures of the Nushagak and Kvichak Watersheds,
Alaska


VOLUME 3
APPENDIX E: Bristol Bay Wild Salmon Ecosystem Baseline Levels of Economic Activity and
Values

APPENDIX F: Biological Characterization: Bristol Bay Marine Estuarine Processes, Fish, and
Marine Mammal Assemblages

APPENDIX G: Foreseeable Environmental Impact of Potential Road and Pipeline
Development on Water Quality and Freshwater Fishery Resources of Bristol Bay, Alaska

APPENDIX H: Geologic and Environmental Characteristics of Porphyry Copper Deposits
with Emphasis on Potential Future Development in the Bristol Bay Watershed, Alaska

APPENDIX I: Conventional Water Quality Mitigation Practices for Mine Design,
Construction, Operation, and Closure

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                 Appendix E

Bristol Bay Wild Salmon Ecosystem Baseline Levels
        of Economic Activity and Values
                      E-l

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Bristol Bay Wild Salmon Ecosystem
Baseline Levels of Economic Activity and Values
John Duffield
Chris Neher
David Patterson
Bioeconomics, Inc. Mlssoula, MT

Gunnar Knapp
Institute of Social and Economic Research—University of Alaska
Anchorage

Tobias Schworer
Ginny Fay
Oliver Scott Goldsmith
Institute of Social and Economic Research
University of Alaska Anchorage
April 27, 2012
For:
NatureServe
Conservation Services Division
       U4A  Institute of Social
       and Economic Research
       UN rvRRsriT of Ai ASKA ANCHORAGE              BIOECONOMICS

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Contents
Contents	2
List of Tables	4
List of Figures	7
Executive Summary	9
  Subsistence and Village Economies	11
  Commercial Fisheries	14
  Recreation	17
  Summary of Economic Significance	17
  Net Economic Values	22
1.0 Introduction and Setting	28
  1.1 Study Objectives and Report Organization	28
  1.2 Definition of Study Area	29
  1.3 Focus of Study-Economic Uses	32
2.0 Bristol Bay Recreation and Subsistence Economics	35
  2.1 Bristol Bay Sportfishing Economics	35
  2.1.1 Bristol Bay Area Trip Characteristics and Angler Attitudes	35
  2.1.2 Bristol Bay Angler Expenditures	38
  2.1.3 Aggregate Direct Sport fishing Expenditures in Bristol Bay	40
2.2 Bristol Bay Subsistence Harvest Economics	42
2.3 Bristol Bay Sport Hunting and Non-consumptive Economics	47
  2.3.1 Sport Hunting	47
  2.3.2 Non-consumptive Wildlife Viewing / Tourism Economics	48
3.0 Bristol Bay Commercial Fisheries	51
  3.1 Introduction	51
  3.2 Overview of the Bristol Bay Salmon Industry	52
  3.3 Bristol Bay Salmon Harvests	57
  3.4 Bristol Bay Salmon Products and Markets	71
  3.5 Bristol Bay Salmon Prices	80
  3.6 Bristol Bay Salmon Ex-Vessel and Wholesale Value	92
  3.7 Bristol Bay Salmon Fishermen	96
  3.8 Bristol Bay Salmon Processors	105
  3.9 Bristol Bay Salmon Industry Employment	109
  3.10 Bristol Bay Salmon Industry Taxes	117
  3.11 Regional Distribution of Bristol Bay Permit Holders, Fishery Earnings, and Processing
  Employment	119
  3.12 Distribution of Salmon Permits and Earnings within The Bristol Bay Region	129
  3.13 Economic Measures of the Bristol Bay Salmon Industry	137
  3.14 Bristol Bay Commercial Fisheries: Summary	144
  3.15 Appendix:  Data Sources	153
4.0 Economic Significance of Healthy Salmon Ecosystems in the Bristol Bay Region: Summary
Findings	171
  4.1 Introduction	173
  4.2 Methods	174

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  4.3 Regional Economic Overview	178
  4.4 Commercial Salmon Fisheries	182
  4.5 Recreation	184
     4.5.1 Non-Consumptive Use	187
     4.5.2 Sport Fishing	188
     4.5.3 Sport Hunting	189
  4.6 Subsistence	190
  4.7 Conclusions	191
  4.8 Key Assumptions and Uncertainties	193
  4.9 Data Sources	196
5.0 Bristol Bay Net Economic Values	199
  5.1 Commercial Fisheries	199
  5.2 Subsistence Harvest	201
  5.3 Sport Fishing Net Economic Value	205
  5.4 Sport Hunting Net Economic Value	207
  5.5 Wildlife Viewing and Tourism Net Economic Value	208
  5.6 Total  Net Economic Value and Present Value and Inter-temporal Issues	208
References	214

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List of Tables

Table 1. Bristol Bay Area Communities, Populations, and Subsistence Harvest 12
Table 2. Selected Economic Measures of the Bristol Bay Commercial Salmon Industry, 2000-
2010 16
Table 3. Summary of Regional Economic Expenditures Based on Wild Salmon Ecosystem
Services (Million 2009 $) 18
Table 4. Total Estimated Recreational Direct Spending in Alaska Attributable to Bristol Bay
Wild Salmon Ecosystems, 2009 19
Table 5. Cash Economy Employment Count by Place of Work in the Bristol Bay Region, 200920
Table 6. Cash Economy Estimated Economic Significance of Bristol Bay Ecosystems 21
Table 7. Summary of Bristol Bay Wild Salmon Ecosystem Services, Net Economic Value per
Year (Million 2009 $) 27
Table 8. Estimated Net Present Value of Bristol Bay Ecosystem Net Economic Use Values and
Alternative Assumed Perpetual Discount Rates 27
Table 9. Demographic and Socioeconomic Characteristics of the Bristol Bay Region 29
Table 10. Bristol Bay Area Communities and Populations 30
Table 11: Types of Ecosystem Services 33
Table 12. Bristol Bay Angler Distribution across Trip Types, by Residency 36
Table 13: Bristol Bay Angler Trip Characteristics 37
Table 14: Bristol Bay Angler Survey, Targeted Species 37
Table 15: Bristol Bay Angler Rating of Selected Attributes of Fishing Trip 38
Table 16. Nonresident Trips to Bristol Bay Waters, Mean Expenditure Per Trip Estimates By
Trip Type 39
Table 17: Distribution of Trip Expenditures across Spending Categories, by Residency and Area
39
Table 18. Estimated 2009 Bristol Bay area angler trips, by Angler Residency 40
Table 19. Estimated Aggregate Spending Associated with Sportfishing in the Bristol Bay Region
(2009 dollars) 41
Table 20. Bristol Bay Sportfishing: Aggregate in and out of Region and State Spending (2009)41
Table 21. ADF&G Division of Subsistence Average Per Capita Subsistence Harvest for Bristol
Bay Communities 43
Table 22. Historical Subsistence Salmon Harvest for Bristol Bay, Alaska: 1975-2007 (ADF&G
Division of Subsistence ASFDB) 45
Table 23. Bristol Bay Subsistence Salmon Harvests by District and Location Fished, 2007 46
Table 24. Estimated Total Annual Bristol Bay Area Subsistence-Related Expenditures (2009 $)
47
Table 25. ADF&G Reported Big Game Hunting in Bristol Bay and Alaska Peninsula Game
Management Units 48
Table 26. Estimated annual big game hunting expenditures for Bristol Bay region 48
Table 27. Comparison of Bristol Bay Drift Gillnet and Set Gillnet Fisheries (2006-10 Average)
64
Table 28. Sales of Selected Sockeye Salmon Products 73
Table 29. Selected Indicators of Participation in 2009 Drift Gillnet Fishery 98
Table 30. Estimated Number of 2009 Drift Gillnet Permit Holders who Fished Alone, With
another Permit Holder, or Did Not Fish 99

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Table 31. Estimates of Bristol Bay Processor Costs, Prices and Profits 107
Table 32. Indicators and Estimates of Bristol Bay Salmon Industry Fishing Processing
Employment 112
Table 33. Monthly Employment in Food Manufacturing, by Borough or Census Area 116
Table 34. Selected Data and Estimates for Bristol Bay Salmon Taxes 118
Table 35. Comparison of Vessels Used in the Bristol Bay Drift Gillnet Fishery, by Residency of
Permit Holder 123
Table 36. Participation and Gross Earnings in Bristol Bay Salmon Fisheries 128
Table 37. Population, Permit Holders, and Salmon Earnings, by Community: 2000 & 2010 ... 130
Table 38. Salmon Permit Holders per 100 Residents, by Community 134
Table 39. Bristol Bay Salmon Fishery Earnings, by Community 136
Table 40. Economic Measures of Bristol Bay Salmon Industry: Sockeye Salmon Harvests 138
Table 41. Economic Measures of Bristol Bay Salmon Industry: Sockeye Value 139
Table 42. Economic Measures of the Bristol Bay Salmon Industry: Export Value 141
Table 43. Economic Measures of the Bristol Bay Salmon Industry: Employment 142
Table 44. Economic Measures of the Bristol Bay Salmon Industry: Permit Prices and Values. 143
Table 45. Distribution of Harvests for Bristol Bay Fishing Districts, 1986-2010 146
Table 46. Geographic Distribution of Bristol Bay Salmon Industry Employment and Earnings.
150
Table 47. Relative Indicators of 2010 Salmon Fishery Participation and Earnings 151
Table 48. Selected Economic Measures of the Bristol Bay Salmon Industry, 2000-2010 152
Table 49. Distribution of Selected Economic Measures for the Bristol Bay Commercial Salmon
Fishing Industry, 1980-2010 153
Table 50. Estimated Economic Significance of Bristol Bay Ecosystems 172
Table 51. Annual average jobs associated with $1 million in spending in each sector in
Southwest Alaska, 2009 176
Table 52. Annual payroll associated with $1 million in spending in each sector in Southwest
Alaska, 2009 177
Table 53. Employment Count by Place of Work in the Bristol Bay Region, 2009 179
Table 54. Federal Spending in the Bristol Bay Region, 2009 ($000) 179
Table 55. Estimated Residence of Workers in the Bristol Bay Region 2009 180
Table 56. Estimated Personal Income in the Bristol Bay Region, 2009 (000$) 181
Table 57. Estimated Economic Significance of Commercial Fishing 183
Table 58. Estimated Recreational Visitors and Expenditures in the Bristol Bay Region, 2009. 185
Table 59. Estimated Economic Significance of All Recreation 186
Table 60. Estimated Economic Significance of Non-Consumptive Use 187
Table 61. Estimated Economic Significance of Sport Fishing 188
Table 62. Estimated Economic Significance of Sport Hunting 189
Table 63. Estimated Economic Significance of Subsistence 190
Table 64. Estimated Economic Significance of Bristol Bay Ecosystems 192
Table 65. Current Bristol Bay Salmon Fishing Permit Numbers and sale prices, 2011 200
Table 66. Estimated Two-Stage Least Squares Wage Compensating Differential Model of
Subsistence Harvest in 90 Alaska Communities (Duffield 1997) 203
Table 67. Estimated Total Annual Bristol Bay Subsistence Harvest (usable pounds of harvest)
204
Table 68. Estimated Net Economic Annual Value of Bristol Bay Area Subsistence Harvest... 205

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Table 69. Responses to Current Trip Net Economic Value Question	206
Table 70: Estimated Mean Willingness to Pay for Anglers' Recent Trip to Bristol Bay	207
Table 71. Estimated Willingness to Pay for Sportfishing Fishing in the Bristol Bay Region.... 207
Table 72. Estimated annual big game hunting net economic value for Bristol Bay region	208
Table 73. Summary of Bristol Bay Wild Salmon Ecosystem Services, Net Economic Value per
Year (Million 2009 $)	211
Table 74. Estimated Net Present Value of Bristol Bay Ecosystem Net Economic Use Values and
Alternative Assumed Perpetual Discount Rates	213

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List of Figures

Figure 1. Map of Bristol Bay Study Area 11
Figure 2. Bristol Bay Area Location and Major Communities 13
Figure 3. Bristol Bay Area Commercial Salmon Fishery Management Districts 14
Figure 4. Selected Bristol Bay Salmon Processor Costs: 2001-2009 24
Figure 5. Flows of Ecosystem Services (adapted from (National Research Council 2005)) 25
Figure 6. Bristol Bay Area Location and Major Communities 30
Figure 7. Map of Bristol Bay Study Area 32
Figure 8. Comparison of Resident and Nonresident Bristol Bay Angler Trip Types 36
Figure 9. Distribution of Bristol Bay Subsistence Harvest 43
Figure 10. Major Bristol Bay River Systems 53
Figure 11. Bristol Bay Commercial Salmon Harvests 57
Figure 12. Bristol Bay Fishing Districts. Source: ADFG map posted at: 58
Figure 13. Bristol Bay Commercial Sockeye Salmon Harvests, by District 59
Figure 14. Share of Bristol Bay Commercial Sockeye Salmon Harvest, by District 60
Figure 15. Naknek-Kvichak District Sockeye Salmon Harvests, by River of Origin 61
Figure 16. Bristol Bay Salmon Harvests, by Fishery 65
Figure 17. World Sockeye Supply 66
Figure 18. Alaska Salmon Supply 67
Figure 19. World Salmon and Trout Supply 68
Figure 20. Bristol Bay Sockeye Preseason Projection and Actual Commercial Catch 69
Figure 21. Bristol Bay Salmon Harvests, 1985-2009 70
Figure 22. Bristol Bay Sockeye Salmon Production 72
Figure 23. Share of Sockeye Salmon Production in Bristol Bay 72
Figure 24. Bristol Bay Sockeye Salmon Harvests and Production 74
Figure 25. Monthly Sales Volume of Bristol Bay Salmon Products 75
Figure 26. Alaska Frozen Sockeye Production and U.S. Frozen Sockeye Exports 77
Figure 27. Estimated End-Markets for Alaska Frozen Sockeye Salmon 78
Figure 28. Alaska Canned Sockeye Production and U.S. Canned Sockeye Exports 79
Figure 29. Average Ex-Vessel Price of Bristol Bay Sockeye Salmon, 1975-2010 80
Figure 30. Average Wholesale and Ex-Vessel Prices of Bristol Bay Sockeye Salmon 81
Figure 31. Average Monthly First Wholesale Prices 83
Figure 32. Average Wholesale and Ex-Vessel Prices, Bristol Bay and Rest of Alaska 84
Figure 33. Average Ex-Vessel Prices of Sockeye Salmon, Selected Alaska Areas 84
Figure 34. Japanese Red-Fleshed Salmon Imports, May-April 85
Figure 35. Japanese Red-Fleshed Frozen Salmon Imports & Wild Sockeye Wholesale Price.... 86
Figure 36. Japanese Wholesale Prices and Bristol Bay Prices for Sockeye Salmon 87
Figure 37. Average United States Import Prices of Selected Farmed Salmon Products 88
Figure 38. U.S. Wholesale Prices for Selected Wild and Farmed Salmon Products 88
Figure 39. Monthly Average Wholesale Case Prices for Alaska Canned Sockeye Salmon 89
Figure 40. Estimated Chilled and Un-chilled Shares of Bristol Bay Salmon Harvests 91
Figure 41. Ex-Vessel and First Wholesale Value: 1984-2010 93
Figure 42. Distribution of Nominal Value of Bristol Bay Sockeye Salmon 94
Figure 43. Distribution of Value of Bristol Bay Sockeye Salmon 95
Figure 44. Number of Limited Entry Permits Issued and Fished in Bristol Bay 97

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Figure 45. Average Gross Earnings of Bristol Bay Drift Gillnet Permit Holders 100
Figure 46. Average Gross Earnings of Bristol Bay Set Gillnet Permit Holders 101
Figure 47. Average Prices Paid for Bristol Bay Limited Entry Permits 102
Figure 48. Average Permit Prices and Total Earnings: Bristol Bay Drift Gillnet Fishery 103
Figure 49. Average Prices and Earnings: Bristol Bay Set Gillnet Fishery 103
Figure 50. Northern Economies' Estimates of the Breakdown of Operating Costs 104
Figure 51. Number of Companies Reporting Salmon Production in Bristol Bay, by Product... 106
Figure 52. Selected Bristol Bay Salmon Processor Costs, 2001-2009 108
Figure 53. Selected Estimates of Bristol Bay Salmon Fishing and Processing Workers 113
Figure 54. Monthly Employment in Food Manufacturing, Bristol Bay Region 115
Figure 55. Bristol Bay Region Local Communities Source:
www.visitbristolbay.org/bbvc/images/bb map large.jpg 120
Figure 56. Number of Bristol Bay Permit Holders by Residency 121
Figure 57. Permit Holders Average Earnings, by Residency 122
Figure 58. Share of Total Earnings of Bristol Bay Drift Gillnet Permit Holders, by Residency 124
Figure 59. Share of Total Earnings of Bristol Bay Set Gillnet Permit Holders, by Residency.. 125
Figure 60. Share of Bristol Bay Seafood Processing Employment, by Residency 126
Figure 61. Local Bristol Bay Resident Share of Salmon Fisheries: Selected Measures 127
Figure 62. Estimated Bristol Bay Area Population, by Area 131
Figure 63. Estimated Population by Region 131
Figure 64. Number of Drift Gillnet Holders, by Region 132
Figure 65. Number of Drift Gillnet Holders per 100 Residents, by Region 132
Figure 66. Number of Set Gillnet Holders, by Region 133
Figure 67. Number of Set Gillnet Permit Holders per 100 Residents, by Region 133
Figure 68. Total Salmon Fishery Earnings, by Region 135
Figure 69. Per Capita Salmon Fisheries Earnings, by Region 135
Figure 70. Bristol Bay Commercial Salmon Harvests 138
Figure 71. Ex-Vessel and Wholesale Value of Bristol Bay Sockeye Salmon 140
Figure 72. Estimated Value of US Exports of Bristol Bay Salmon Products 141
Figure 73. Estimated Total Value of Bristol Bay Limited Entry Permits 144
Figure 74. Bristol Bay Commercial Salmon Harvests 145
Figure 75. Estimated Shares of Bristol Bay Sockeye Salmon Production, 2010 147
Figure 76. Average Ex-Vessel and Wholesale Prices of Bristol Bay Sockeye Salmon 148
Figure 77. Ex-Vessel and First Wholesale Value 1980-2010 149
Figure 78. Local Bristol Bay Resident Share of Bristol Bay Salmon Fisheries 150
Figure 79. Selected Bristol Bay Salmon Processor Costs: 2001-2009 209
Figure 80. Flows of Ecosystem Services (adapted from (National Research Council 2005)) ... 210

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Executive Summary

The objective of this report is to characterize the baseline levels of economic activity and related
ecosystem services values for the Bristol Bay wild salmon ecosystem. The overarching purpose
of this report is to provide baseline economic information to the Environmental Protection
Agency in order to inform review of mining proposals in the Nushugak and Kvichak drainages.
Both regional economic significance and social net economic accounting frameworks are
described in this report. This study reviews and summarizes existing economic research on the
key sectors in this area and reports findings based on original survey data on expenditures and
net benefits. This report combines efforts on the part of Bioeconomics, Inc. and the University
of Alaska Institute of Social and Economic Research. John Duffield and Chris Neher compiled
the report and authored the executive summary, Sections 1, 2, and 5. Gunnar Knap wrote
Section 3 (commercial fisheries), and Tobias Schworer, Ginny Fey and Scott Goldsmith wrote
Section 4.

The major components of the total value of the Bristol Bay area watersheds include subsistence
use, commercial fishing, sportfishing and other recreation, and the preservation values (or
indirect values) held by users and the U.S. resident population. The overall objectives of this
study is to estimate the share of the total regional economy (expenditures, income and jobs) that
is dependent on these essentially pristine wild salmon ecosystems, and to provide a preliminary
but relatively comprehensive estimate of the total economic value (from an applied welfare
economics perspective) that could be at risk from extractive resource development in the region.

It is important to note that while the geographic scope of this economic characterization report is
targeted to the Bristol Bay wild salmon ecosystem, the scope of the proposed mining activity is
somewhat narrower, including the Nushugak and Kvichak drainages. This report used existing
information and data to target this economic characterization report to ecosystem services and
associated economic activity and values, specific to the Bristol Bay Region. However, data on
different economic sectors vary in quality, and available data on some economic activities (such
as non-consumptive tourism) make it more difficult to identify activities and associated
economic values narrowly targeted to the Bristol Bay area. The overall intent of this report is to
provide a general picture of the full range of economic values associated with ecosystem services
supplied by the entire Bristol Bay region. Values tied to, and specific to, the proposed mining
activity (and discharges) in the Nushugak and Kvichak Drainages would be a subset of those
reported here, and have not been identified in this general characterization analysis.

Following this executive summary, the report is organized into five main sections. Section 1
provides a brief introduction to the report. Section 2 addresses economic visitation and
expenditures related to sportfishing, subsistence harvests, hunting, and non-consumptive
recreation. Section 3 focuses on commercial fishing. Section 4 combines the regional economic
activity associated with recreation and commercial fishing into an analysis of regional economic
significance of these activities. Finally, Section 5 focuses on the net economic values associated
with recreation and commercial fisheries in the Bristol Bay ecosystem.

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For purposes of a baseline year, the most recent generally available data year is used (2009).
Where available, (primarily in the commercial fisheries discussion) data on 2010 is also shown.
Summary values are presented for 2009 data and in 2009 dollars.

The rivers that flow into the Bristol Bay comprise some of the last great wild salmon ecosystems
in North America (Figure 1). The Kvichak River system supports the world's largest run of
sockeye salmon. While these are primarily sockeye systems, all five species of Pacific salmon
are abundant, and the rich salmon-based ecology also supports many other species, including
Alaska brown bears and healthy populations of rainbow trout. The Naknek, Nushugak, Kvichak,
Igushik, Egegik, Ugashik, and Togiak watersheds are all relatively pristine with very few roads
or extractive resource development. Additionally, these watersheds include several very large
and pristine lakes, including Lake Iliamna and Lake Becherof Lake Iliamna is one of only two
lakes in the world that supports a resident population of freshwater seals (the other is Lake
Baikal in Russia). The existing mainstays of the economy in this region are all wilderness-
compatible and sustainable in the long run: subsistence use, commercial fishing, and wilderness
sportfishing, hunting, and wildlife viewing and other non-consumptive recreation. The
commercial fishing is largely in the salt water outside of the rivers themselves and is closely
managed for sustainability. The subsistence, sportfish and other recreation sectors are relatively
low impact (primarily personal use and catch and release fishing, respectively). Additionally,
there are nationally-important public lands in the headwaters, including Lake Clark National
Park and Preserve, Katmai National Park and Preserve, Togiak National Wildlife Refuge, and
Wood-Tikchick State Park (the largest state park in the U.S.).
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                                                 Nushagak
                                                      Kvichak
Figure 1. Map of Bristol Bay Study Area


The current study focuses on an overview of values based on existing data and previous studies,
and estimation of both the regional economic significance (focusing on jobs and income) of
these ecosystems using an existing regional economic model, as well as total value in a social
benefit-cost framework. The objective is to provide a preliminary but relatively comprehensive
estimate of the range of fishery-related values in this region (Figure 1).

This summary provides a brief characterization of each of the major sectors, followed by the
primary economic findings.
Subsistence and Village Economies

The Bristol Bay economy is a mixed cash-subsistence economy. The primary features of these
socio-economic systems include use of a relatively large number of wild resources (on the order
of 70 to 80 specific resources in this area), a community-wide seasonal round of activities based
on the availability of wild resources, a domestic mode of production (households and close kin),
frequent and large scale noncommercial distribution and exchange of wild resources, traditional
systems of land use and occupancy based on customary use by kin groups and communities, and
a mixed economy relying on cash and subsistence activities (Wolfe and Ellanna, 1983; Wolfe et
al. 1984). The heart of this cash-subsistence economy is the resident population of 7,475
individuals located in 25 communities (Table 1) spread across this primarily un-roaded area
(Figure 2). Archeological evidence indicates that Bristol Bay has been continuously inhabited by
humans at least since the end of the last major glacial period about 10,000 years ago. Three
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primary indigenous cultures are represented here: Aleuts, Yupik Eskimos, and the Dena'ina
Athapaskan Indians. The share of the population that is Alaska Native is relatively high at 70
percent, compared to Alaska as a whole, with 16 percent.
Table 1. Bristol Bay Area Communities, Populations, and Subsistence Harvest
Bristol Bay Area
Community /year of
AKF&G survey
Aleknagik 2008
Clark's Point 2008
Dillingham 1984
Egegik 1984
Ekwok 1987
Igiugig2005
Iliamna 2004
King Salmon 2008
Kokhanok 2005
Koliganek 2005
Levelock 2005
Manokotak 2008
Naknek 2008
New Stuyahok 2005
Newhalen 2004
Nondalton 2004
Pedro Bay 2004
Pilot Point 1987
Port Alsworth 2004
Port Heiden 1987
South Naknek 2008
Ugashik 1987
Togiak City 2000
Twin Hills 2000
Un-surveyed communities
Total
Population
(2010 census)
219
62
2,329
109
115
50
109
374
170
209
69
442
544
510
190
164
42
68
159
102
79
12
817
74
457
7,475
Per Capita Harvest
(AKF&G Surveys)
296
1210
242
384
797
542
469
313
680
899
527
298
264
389
692
358
306
384
133
408
268
814
246
499

343
Total Annual
Harvest (Ibs)
64,824
75,020
563,618
41,856
91,655
27,100
51,121
117,062
115,600
187,891
36,363
131,716
143,616
198,390
131,480
58,712
12,852
26,112
21,147
41,616
21,172
9,768
200,982
36,926
-
2,563,313
% Native Population
(2000 census)
81.9%
90.7%
52.6%
57.8%
91.5%
71.7%
50.0%
29.0%
86.8%
87.4%
89.3%
94.7%
45.3%
92.8%
85.0%
89.1%
40.0%
86.0%
4.8%
65.6%
83.9%
72.7%
86.3%
84.1%


Sources: US Census Bureau (2010 census statistics), and ADF&G Division of Subsistence Community Profile Data Base; Personal Comm. David
Holen, ADF&G Oct 25, 2011.
Wild renewable resources are important to the people of this region and many residents rely on
wild fish, game and plants for food and other products for subsistence use. Total harvest for these
25 communities is on the order of 2.6 million pounds based largely on surveys undertaken from
the late 1980's through 2008, as summarized in the Alaska Division of Subsistence community
profile data base. A new round of surveys is now underway to update this data. Estimates for the
2004-2008 study years (Fall et al. 2006; 2008; 2009) are included in the data presented in Table
1.  Additionally, as yet unpublished data from 2009 for Alegnagik, Clarks Point and Manokotak
are included in the table (Per. Com. David Holen, ADF&G, Oct. 25, 2011). Per capita harvests
average about 343 pounds. Primary resources used include salmon, other freshwater fish,
caribou, and moose. Subsistence use continues to be very important for communities of this
region, based on these recent surveys, and participation in subsistence activity, including

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harvesting, processing, giving and receiving is quite high. Compared to other regions of Alaska,
the Bristol Bay area has some characteristic features, including the great time depth of its cultural
traditions, its high reliance on fish and game, the domination of the region's market economy by
the commercial salmon fishery, and the extensive land areas used by the region's population for
fishing, hunting, trapping and gathering. (Wright, Morris, and Schroeder, 1985; Fall, Krieg, and
Holen, 2009).
Pacific Ocean
Figure 2. Bristol Bay Area Location and Major Communities
The primary private source of cash employment for participants in Bristol Bay's mixed cash-
subsistence economy is the commercial salmon fishery. The compressed timing of this fishery's
harvesting activity makes it a good fit with subsistence in the overall Bristol Bay cash-
subsistence economy. Participation in the Bristol Bay salmon fishery is limited to holders of
limited entry permits and their crew. There are approximately 1,860 drift gillnet permits for
fishing from boats and approximately 1000 set net permits for fishing from the shore. The
driftnet fishery accounts for about 80% of the harvest. Most of the harvest is processed by about
ten large processing companies in both land-based and floating processing operations which
employ mostly non-resident seasonal workers.

Many commercial fishing permit holders and crew members, as well as some employees in the
processing sector, are residents of Bristol Bay's dominantly-native Alaskan villages. An
ADF&G summary of subsistence activity in Bristol Bay (Wright, Morris, and Schroeder 1985)

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noted that as of the mid-1980's traditional patterns of hunting, fishing, and gathering activities
had for the most part been retained, along with accommodations to participate in the commercial
fishery and other cash-generating activities. In the abstract to this 1985 paper, the authors
characterize the commercial salmon fishery as "a preferred source of cash income because of its
many similarities to traditional hunting and fishing, and because it is a short, intense venture that
causes little disruption in the traditional round of seasonal activities while offering the potential
for earning sufficient income for an entire year." Commercial fishing is a form of self
employment requiring many of the same skills, and allowing nearly the same freedom of choice
as traditional subsistence hunting and fishing. (Wright, Morris, Schroeder 1985; p. 89).
Brhtol Bay Area Commercial
Sfihnoii Fhfien' Management Districts

Alaska Department of Fish and Game
J.V.'S?31 of CST'ITl frcia! r<;k??ifS
Figure 3. Bristol Bay Area Commercial Salmon Fishery Management Districts
Commercial Fisheries

The Bristol Bay commercial salmon fishery harvests salmon which spawn in and return to
numerous rivers over a broad area. The Bristol Bay commercial fisheries management area
encompasses all coastal and inland waters east of a line from Cape Menshikof to Cape
Newhenham (Figure 3). This area includes eight major river systems: Naknek, Kvichak, Egegik,
Ugashik, Wood, Nushagak, Igushik and Togiak. Collectively these rivers support the largest
commercial sockeye salmon fishery in the world (ADF&G, 2005). This is an interesting and
unique fishery, both because of its scale and significance to the local economy, but also because
it is one of the very few major commercial fisheries in the world that has been managed on a
14

-------
sustainable basis. The substantial diversity in this system, both across species and within species
(population diversity), leads to relatively stable populations. Schindler (2010) estimated that
variability in annual Bristol Bay salmon runs is 2.2 times lower than if the system consisted of a
single population, and that a single homogeneous population of salmon would lead to 10 times
more frequent fisheries closures. These findings indicate the importance of maintaining
population diversity in order to protect the ecosystem and the economy that depends on it.

Catches in each district vary widely from year to year and over longer time periods of time,
reflecting wide variation in returns to river systems within each district. Currently there is
particular interest in the significance of fisheries resources of river systems in the Nushagak and
Kvichak districts, because of potential future resource development in these watersheds. Over
the period 1986-2010, the Naknek-Kvichak catches ranged from as low as 5% to as high as 52%
of total Bristol Bay catches; Nushagak district catches ranged from as low as 9% to as high as
45% of total Bristol Bay catches. For most of the past decade, the combined Nushagak and
Naknek-Kvichak districts have accounted for about 60% of the total Bristol Bay commercial
sockeye harvest.l

The five species of pacific salmon found in Bristol Bay are the focus of the major commercial
fisheries. Sockeye salmon account for about 94% of the volume of Bristol Bay salmon harvests
and an even greater share of the value.

The fishery is organized into five major districts (Figure 3) including Togiak, Nushagak,
Naknek-Kvichak, Egegik, and Ugashik. Management is focused on discrete stocks with harvests
directed at terminal areas at the mouths of the major river systems (ADF&G, 2005). The stocks
are managed to achieve an escapement goal based on maximum sustained yield. The returning
salmon are closely monitored and counted and the openings are adjusted on a daily basis to
achieve desired escapement. Having the fisheries near the mouths of the rivers controls the
harvest on each stock, which is a good strategy for protection of the discrete stocks and their
genetic resources. The trade-off is that the fishery is more congested and less orderly, and the
harvest is necessarily more of a short pulse fishery, with most activity in June and early July.
This has implications for the economic value of the fish harvest, both through effects on the
timing of supply, but also on the quality of the fish. Most fish are canned or frozen, rather than
sold fresh. Total catches vary widely from year to year. Between 1980 and 2010, Bristol Bay
sockeye salmon harvests ranged from as low as 10 million fish to as high as 44 million fish.
Harvests can vary widely from year to year. Annual pre-season forecasts are subject to a wide
margin of error.

Strong Japanese demand for frozen sockeye salmon drove a sharp rise in Bristol Bay salmon
prices during the 1980s. Competition from rapidly increasing farmed salmon production drove a
protracted and dramatic decline in prices between 1988 and 2001, which led to an economic
crisis in the industry. However, growing world salmon demand, a slowing of farmed salmon
production growth, diversification of Bristol Bay salmon products and markets, and
improvements in quality have driven a strong recovery in prices over the past decade. The real
1 Bristol Bay salmon harvest statistics can be found at
http://www.adfg.alaska.gov/index.cfm7adfg=commercialbyareabristolbay.salmon
15

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(2010 dollars) ex-vessel value paid to fishermen fell from $359 million in 1988 to $39 million in
2002, and rose to $181 million in 2010.2  The real first wholesale value of Bristol Bay salmon
production fell from $616 million in 1988 to $124 million in 2002, and then rose to $390 million
in 2010. In 2009, the ex-vessel value of Bristol Bay salmon harvest was approximately $300
million. Many other factors, such as changes in wild salmon harvests, exchange rates, diseases in
Chilean farmed salmon, and global economic conditions have also affected prices. In general,
changes in ex-vessel prices paid to fishermen have reflected changes in first wholesale prices
paid to processors.

There are many potential economic measures of the Bristol Bay salmon industry (Table 2).
Which measure is most useful depends upon the question being asked. For example, if we want
to know how the Bristol Bay salmon fishery compares in scale with other fisheries, we should
look at total harvests or ex-vessel or wholesale value. If we want to know how it affects the
United States balance of payments, we should look at estimated net exports attributable to the
fishery. If we want to know how much employment the industry provides for residents of the
local Bristol Bay region, Alaska or the United States, we should look at estimated employment in
fishing and processing for residents of these regions. If we want to know the net economic value
attributable to the fishery, we should look at estimated profits of Bristol Bay fishermen and
processors.  These different measures (Table 2) vary widely in units, in scale,  and in the measure
of how economically "important" the fishery is. For example, for the period 2000-2010, Bristol
Bay harvests were 62% of all Alaska sockeye salmon harvests and 45% of total world production
for the species.
Table 2. Selected Economic Measures of the Bristol Bay Commercial Salmon Industry,
2000-2010.
Measure
Sockeye Salmon Havests
Millions offish
Millions of pounds
Bristol Bay harvest
volume as a share of:
Alaska sockeye salmon
World sockeye salmon
Alaska wild salmon (all species)
World wild salmon (all species)
World wild & farmed salmon
(all species)
Gross Value ($ mllions)
Ex-vessel value
First wholesale value
Total value of US exports of
Bristol Bay salmon products
2000

21
125

61%
45%
18%
7%
3%

80
175
150
2001

14
96

56%
40%
12%
5%
2%

40
115
137
2002

11
65

48%
28%
10%
4%
1%

32
100
97
2003

15
93

50%
38%
13%
5%
2%

48
114
111
2004

26
152

59%
47%
19%
8%
3%

76
176
172
2005

25
155

58%
47%
16%
7%
3%

95
220
193
2006

28
165

69%
49%
22%
8%
3%

109
237
173
2007

30
173

62%
47%
18%
7%
3%

116
249
183
2008

28
160

71%
52%
23%
9%
3%

117
262
206
2009

31
183

71%
55%
25%
7%
3%

144
293
230
2010

29
170

74%





181
390
254
Avg.

23
140

62%
45%
18%
7%
2%

94
212
173
Range

11- 31
65 - 183

48% - 74%
28%- 55%
10%- 25%
4%- 9%
1%- 3%

32 - 181
100 - 390
97 - 254
 The ex-vessel value is the total post-season adjusted price paid to fishermen for the first purchase of commercial
harvest.
                                           16

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Recreation

Next to commercial fishing and processing, recreation is the most important private economic
sector in the Bristol Bay region. This recreational use includes sport fishing, sport hunting, and
other tourism/wildlife viewing recreational trips to the Bristol Bay Region. The 2005 Bristol
Bay Angler Survey (Duffield et al. 2007) confirmed that the fresh water rivers, streams, and
lakes of the region are a recreational resource equal or superior in quality to other world
renowned sport fisheries.

In survey responses Bristol Bay anglers consistently emphasize the importance of Bristol Bay's
un-crowded, remote, wild setting in their decisions to fish the area. Additionally, a significant
proportion of these anglers specifically traveled to the region to fish the world-class rainbow
fisheries. These findings indicate that Bristol Bay sport fishing is a relatively unique market
segment, paralleling the findings of Romberg (1999) and Duffield, Merritt and Neher (2002) that
angler motivation, characteristics, and values vary significantly across Alaska sport fisheries.

Recreational fishing use of the Bristol Bay region is roughly divided between 58% trips to the
area by Alaska residents and 42% trips by nonresidents. These nonresidents (approximately
12,500 trips in 2009 (personal communication, ADF&G, 2011)) account for the large majority of
total recreational fishing spending in the region. It is estimated that in 2009 approximately $50
million was spent in Alaska by nonresidents specifically for the purpose of fishing in the Bristol
Bay region. In total, it is estimated that $60 million was spent in Alaska in 2009 on Bristol Bay
fishing trips.

While sport fishing within the Bristol Bay region comprises a large and well recognized share of
recreational use and associated visitor expenditures, thousands of trips to the region each year are
also made for the primary purpose of sport hunting and wildlife viewing. Lake Clark and Katmai
National Parks are nationally significant protected lands and are important visitor destinations
attracting around 65,000 recreational visitors in 2010 (NFS public visitation statistics).
Additionally, rivers within Katmai NP provide the best locations in North America to view wild
brown bears.
Summary of Economic Significance

Table 3 through 7 detail the summary results of the analysis of economic values. Table 3 shows
estimated direct expenditures in Alaska related to harvest or use of Bristol Bay area renewable
resources. Total estimated direct expenditures (that drive the basic sector of the economy) were
estimated to be $479 million in 2009. The largest component is commercial fishing harvesting
and processing. These estimates were obtained from the Alaska Department of Revenue and the
Commercial Fishing Entry Commission. The next most significant component is wildlife
viewing/tourism at $104 million in 2009. Sport fishing is estimated to constitute another $60
million in spending. This estimate is derived from the 2005 Bristol Bay Angler survey data as
well as AK F&G use estimates. Sport hunting is less important economically.
17

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The direct economic spending and sales shown in part A of the table supports an estimated
14,200 direct full and part-time jobs in the Bristol Bay region during peak season.
Table 3. Summary of Regional Economic Expenditures Based on Wild Salmon Ecosystem
Services (Million 2009 $)
Ecosystem Service
Estimated direct expenditures / sales per year
(A) Direct Expenditures and Sales
Commercial fish wholesale value3
Sport fisheries
Sport hunting
Wildlife viewing / tourism
Subsistence harvest expenditures
Total direct annual economic impact
300.2
60.5
8.2
104.4
6.3
479.6
(B) Estimated Direct Full & Part-Time Jobs at Peak Season
Commercial fish Sector
Sport fisheries
Sport hunting
Wildlife viewing / tourism
Subsistence harvest expenditures
Total direct annual economic impact
11,572
854
132
1,669
Not Captured by the Market
14,227
Table 4 provides additional detail on recreation expenditures, including number of trips and
spending by residence of the participants. A large share of total recreation expenditures is by
nonresident anglers ($49.8 million) and nonresident non-consumptive (tourism/wildlife viewing)
visitors ($92.9 million). This reflects the high quality of this fishery and other recreational
opportunities in the region, in that the area is able to attract  participants from a considerable
distance in the lower 48 states as well as foreign countries.  Subsistence harvest expenditures are
based on limited data and are likely to be conservative. (Goldsmith, 1998)
3 Estimates of some year-specific commercial fishery total harvest and total sales vary slightly within this report.
This is due to differences in how these data are aggregated and reported by the Alaska Fish and Game, and the point
in time these statistics were accessed during the preparation of this report.
                                             18

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Table 4. Total Estimated Recreational Direct Spending in Alaska Attributable to Bristol
Bay Wild Salmon Ecosystems, 2009
                             Local       Non-local         Non-
                           residents       residents       residents
Visitors
Non-consumptive
Sport fishing
Sport hunting

4,506
13,076 3,827
1,319

36,458
12,464
1,323

40,964
29,367
2,642
  Total                     13,076          9,652           50,245           72,973

Spending per visitor
  Non-consumptive                -         $2,548           $2,548
  Sport fishing                 $373         $1,582           $3,995
  Sport hunting                    -         $1,068           $5,170
Spending (Sniillion)
Non-consumptive
Sport fishing
Sport hunting
Total

-
$4.9
-
$4.9

$11.5
$6.0
$1.4
$18.9

$92.9
$49.8
$6.8
$149.5

$104.4
$60.7
$8.2
$173.3
Table 5 summarizes the full time equivalent employment (annual average) for the cash
component of the economy associated with the major economic sectors of the Bristol Bay
economy, those dependent on wild salmon ecosystems—recreation, commercial fishing, and
subsistence, as well as other major employment sectors. The economy of the Bristol Bay Region
depends on three main activities or sectors—publicly funded services through government and
non-profits, commercial activity associated with the use of natural resources (mainly commercial
fishing and recreation), and subsistence. Subsistence is a non-market activity in the sense that
there is no exchange of money associated with the subsistence harvest. However, local
participants invest a significant portion of their income to participate in subsistence and the
harvest has considerable economic value and their expenditures have significant economic
effects.

Public services and commercial activities bring money into the economy (basic sectors) and
provide the basis for a modest support sector. The support sector (non-basic sector) consists of
local businesses that sell goods  and services to the basic sectors including the commercial fishing
industry, the recreation industry, the government and non-profit sectors. The support sector also
sells goods and services to participants in subsistence activities.

The relative importance of government, commercial  fishing and recreation, within the regional
economy can be measured by the annual average employment in each sector. In 2009, more than
two thousand jobs were directly associated with government spending from federal, state, and
local sources. Commercial fishing and recreation accounted for approximately three thousand or

                                           19

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57 percent of total basic sector jobs. Since much of the recreation is using public lands and
resources, a share of the government sector, for example administration of the federal and state
parks and wildlife refuges, is directly related to providing jobs and opportunities in the recreation
sector. Accordingly, the estimate of recreation-dependent jobs is conservative.

The support sector depends on money coming into the regional economy from outside mainly
through government, commercial fishing, and recreation. The relative dependence of the support
sector on the three main sectors is difficult to measure. One reason for this is that government
employment is stable throughout the year, while employment in commercial fisheries and
recreation vary seasonally. Due to the seasonal stability of government jobs, the payroll spending
of people employed in government is likely to contribute more to the stability of support sector
jobs in the region than their share of basic sector jobs indicates.
Table 5. Cash Economy Full-time Equivalent Employment Count by Place of Work in the
Bristol Bay Region, 2009

Total jobs count
Basic
Fish harvesting
Fish processing
Recreation
Government & Health
Mineral Exploration
Non-basic
Construction

Trade/Transportation/Leisure
Finance
Other wage & salary
Non-basic self employed
r^iiiiu
-------
Subsistence users are not the only hunter-gatherers in this economy. Essentially the entire private
economy is "following the game" (or in this case fish), with many commercial fishermen,
processors, sport anglers, sport hunters, and wildlife viewers coming from elsewhere in Alaska
or outside the state to be part of this unique economy at the time that fish and game are available.
The estimated earnings associated with the salmon ecosystem dependent jobs is shown in Table
6. The total of $283 million was divided among $78 million for residents of the Bristol Bay
region, $104 million to residents of the rest of Alaska, and $100 million to residents of other
states.

Table 6. Cash Economy Estimated Economic Significance of Bristol Bay Ecosystems

Direct jobs
Peak
Commercial fish
Recreation
Subsistence

Annual average
Commercial fish
Recreation
Subsistence

Multiplier Jobs
Total jobs
(annual average)
Direct wages
($000)
Commercial fish
Recreation
Subsistence

Multiplier wages
Total wages

Total
i Ul
-------
(besides those associated with expenditures for tools, equipment, and supplies in Table 3) can be
approximated through either a top-down or bottom-up estimation approach.

Population levels in Bristol Bay were 7,475 in 2010 (Table 1). Based on 2010 census counts, the
number of Bristol Bay residents aged 16 and over was 5,448. The cash economy and equivalent
full-time employment of Alaskans in the Bristol Bay region is estimated at 4,675 (Table 5). The
estimated cash economy employment for local Bristol Bay residents only is 2,032 (Table 6). By
not choosing to move elsewhere, Bristol Bay residents reveal their preference for the livelihood
presented by the mixed cash-subsistence economy. This is supported by the findings in Borass
(2011). For example, several local interviewees were quoted as saying "But I wouldn't trade this
place for anything. This is home; this is where I find clean water to drink." And "We love this
place. Moving is not an option to me." (Boraas (2011) p. 3.)

Data in Holen et al. (2011) indicate that for Bristol Bay communities participation in subsistence
activities is very high. In the towns of King Salmon, Naknek and South Naknek 90% or more of
residents reported participation in subsistence harvest activities (p. 20). One estimate of
participation (employment) in the subsistence livelihood (full-time equivalent jobs) would be to
attribute the residual of the adult (16 and over) population less the cash economy jobs (Table
5)—or around 3,400 jobs to this sector. Therefore, the non-cash economy jobs associated with
the subsistence sector may be roughly 3,400.

Another approach would be to examine the effort levels (days in subsistence activities) based on
subsistence fishing permit data. Fall et al. (2009) indicates that the harvest levels per day are
actually constrained not by potential daily harvest, but by the processing capacity of the family
unit (or extended family).

The total number of full-time equivalent jobs directly dependent on the wild salmon ecosystem is
the sum of the cash economy jobs (6,266) plus the subsistence sector livelihoods (roughly
estimated at (3,400 jobs), or about 9,600 jobs.
Net Economic Values

The preceding discussion has focused on a regional economic accounting framework and job and
wage-related measures of economic significance. This section introduces the net economic value
measures for evaluation of the renewable Bristol Bay resources. The framework for this
accounting perspective is the standard federal guidelines (Principles and Standards) for
estimating net economic benefits in a system of national accounts (U.S. Water Resources
Council 1985). EPA (2010) is a more recent and complementary set of guidelines.

22
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and often differ from preferences in mainstream society. Additionally, because these are highly
vertically integrated economies, substantial value-added may occur before final consumption
(such as drying, or smoking fish and meats). In their research on estimating the economic value
of subsistence harvests, Brown and Burch (1992) suggest that these subsistence harvests have
two components of value, a product value, and what they call an "activity value." The product
value is essentially the market value of replacing the raw subsistence harvest. The activity value
would primarily include the cultural value of participating in a subsistence livelihood. The
activity value component is also associated with the value of engaging in subsistence harvest and
food processing activities. This activity value would include maintaining cultural traditions
associated with a subsistence livelihood. Duffield (1997) estimated a hedonic model of
subsistence harvest of 90 Alaskan communities. This model estimated a total NEV per pound of
useable subsistence harvest of $32.89. ($75.58 based on 2009 Alaska income levels)

Based on an estimated 2.6 million pounds of subsistence harvest per year in the Bristol Bay
region, and valued at an estimated range of $32.89 to $75.58 per pound, this harvest results in an
estimated net economic value annually of subsistence harvest of between $84.3 and $193.7
million.

The net economic value of commercial fisheries is estimated based on data on Salmon fishery
permit sales prices for Bristol Bay. The Commercial Fish Entry Commission reports average
permit transfer prices annually (and monthly) for the Bristol Bay salmon fishery.4 Over the
period from 1991-2011 the average sales price for Bristol Bay drift net permits has been
$149,000 (in current dollars). The average price for set net permits over the same period has been
$42,200. The 95% confidence interval on the mean drift net price for this period is from
$105,500 to $192,700. For the set net permit transfers, the 95% C.I. on the mean sales price was
between $28,700 and $55,700.5 For both types of permits combined, it is estimated that the total
market value of the permits ranges from approximately $225 million to $414 million.

In order to be comparable to other annual net economic values in this analysis (such as sport
fishing or sport hunting) the net present value of commercial fishing permits must be converted
into an annual value reflecting expected annual permit net income The permit total value can be
annualized using an appropriate amortization (or discount) rate. The decision to sell a
commercial fishing permit at a given price is an individual (or private) decision. In deciding on
an acceptable sales price, a permit holder considers past profits from operating the permit, risk
associated with future operation of the permit (both physical and financial), and many other
factors. All these considerations weigh on how heavily a permit seller discounts (reduces)
potential future profits from fishing the permit in order to arrive at a lump-sum value for the
permit. Huppert et al. (1996) specifically looked at Alaska commercial salmon permit operations
and sales and estimated the individual discount rate on drift net permit sales in the Bristol Bay
and surrounding fisheries. This discount rate was estimated from both profitability and permit
sales price data. Huppert et al. estimated the implied discount rate appropriate for annualizing
permit sales prices in this setting at 13.52%. This estimate was consistent with previous
4 A long time series of monthly and annual permit transfer prices is continuously updated at,
http://www.cfec.state.ak.us/pmtvalue/mnusalm.htm
5 Over the period 1991-2011, a total of 3,246 Bristol Bay drift net salmon permits and 1,867 set net salmon permits
were reported sold by the Commercial Fish Entry Commission.

23
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estimates for the fishery. Use of the 13.52% discount rate from Huppert results in an estimated
average annual permit net income associated with Bristol Bay commercial salmon fishing of
between $30.4 million and $55.9 million.

Net income for the processing sector is more difficult to estimate. Relative to the fishing sector,
with ex-vessel value of $181 million in 2010, the processing sector provides an approximately
equal value added of $209 million in 2010 (first wholesale value of $390 million in 2010 less the
cost of buying fish at the ex-vessel cost of $181 million. (Figure 4) However, information on
profits or net income for this sector are difficult to obtain. As with permit prices, processor
profits are highly variable year-to-year. The average value added associated with salmon
processing for the Bristol Bay fishery is generally equal to or more than the ex-vessel value.
Salmon processors in the Bristol Bay fishery have an "oligopsony" market structure, in that a
small number of buyers of raw fish exist in the market. Additionally, these buyers are largely
"price makers" in that they set the price paid per pound to fishermen each season. Given the
unique relationship between fisherman that the small number of processors in the Bristol Bay, it
is estimated that processors derive profits (net economic value) equal to that earned by
fishermen. Therefore, for the purposes of this report it is estimated that the NEV for salmon
producers is equal to that for the fishing fleet.
Selected Bristol Bay Salmon Processor Costs, 2001-2009
300
250
200
150
100
I Other costs
and profits
ESCost of labor
(fish processing
earnings)
I Cost of fish
(ex-vessel
value)
Source: ADFG, ADLWD
Figure 4. Selected Bristol Bay Salmon Processor Costs: 2001-2009

The sportfish net economic values are angler recreational benefits (consumer surplus) in Duffield
et al. (2007). These estimates are consistent with values from the extensive economic literature
on the value of sportfishing trips (for example Duffield, Merritt and Neher 2002). Sport hunting
6 Huppert, Ellis and Nobel (1996) estimated the real discount rate associated with sales of Alaska drift gill-net
commercial permits of 13.52%. Karpoff (1984) estimated the discount rate from sales of Alaska limited entry
permits at 13.95%.
24
-------
values are based on studies conducted in Alaska McCollum and Miller (1994). In addition to
recreationist's net benefits, net income (producer's surplus) is recognized by the recreation and
tourism industry. This is a component that remains to be estimated. Direct use values for
recreation total from $167 million to $273 million per year.

Based on the National Research Council panel on guidelines for valuation of ecosystem services
(NRC 2005), it is important to include intrinsic or passive use values (aka "non-use" values) in
any net economic accounting of benefits (Figure 5).
ECOSYST :M
HUMAN ACTIONS
(PRIVATE/PUBLIC)
ECOSYSTEM GOODS
& SERVICES
Use vatues |
Pa;; iveUse Value;
tr y . criSefxe, spcocs prescnratoo.
nifcw* r*OTMt«
RJHjfif (rr>osfcn.
use
Q B
lndJn»ci
4- 9. UVB pr«KKn
flood CQDfjol, pokikn
Figure 5. Flows of Ecosystem Services (adapted from (National Research Council 2005))
A major unknown is the total value related to existence and bequest motivations for passive use
values. Goldsmith et al. (1998) estimated the existence and bequest value for the federal wildlife
refuges in Bristol Bay at $2.3 to $4.6 billion per year (1997 dollars). There is considerable
uncertainty in these estimates, as indicated by the large range of values. Goldsmith's estimates
25
-------
for the federal wildlife refuges are based on the economics literature concerning what resident
household populations in various areas (Alberta, Colorado) (Adamowicz et al. 1991; Walsh et al.
1984; Walsh et al. 1985) are willing to pay to protect substantial tracts of wilderness. Similar
literature related to rare and endangered fisheries, including salmon, could also be appealed to
here. It is possible that from a national perspective the Bristol Bay wild salmon ecosystems and
the associated economic and cultural uses are sufficiently unique and important to be valued as
highly as wilderness in other regions of the U.S. Goldsmith et al.'s (1998) estimates assume that
a significant share of U.S. households (91 million such households) would be willing to pay on
the order of $25 to $50 per year to protect the natural environment of the Bristol Bay federal
wildlife refuges. The number of these households is based on a willingness to pay study (the
specific methodology used was contingent valuation) conducted by the State of Alaska Trustees
in the Exxon Valdez oil spill case (Carson et al. 1992). The findings of this study were the basis
for the $1 billion settlement between the State and Exxon in this case. These methods are
somewhat controversial among economists, but when certain guidelines are followed, such
studies are recommended for use in natural resource damage regulations (for example, see Ward
and Duffield 1992). They have also been upheld in court (Ohio v. United States Department of
Interior, 880 F.2d 432-474 (D.C. Cir.1989)) and specifically endorsed by a NOAA-appointed
blue ribbon panel (led by several Nobel laureates in economics) (Arrow et al. 1993).

While the primary source of passive use values for Bristol Bay are likely to be with national
households (lower 48), it is important to note that the Alaska natives living in Bristol Bay also
likely have significant passive use values for the wild salmon ecosystem. For example, Boraas
(2011) quotes Bristol Bay natives in saying "We want to give to our children the fish, and we
want to keep the water clean for them... It was a gift to us from our ancestors, which will then be
given to our children.) (Boraas p. 33).

Goldsmith's estimates for just the federal refuges may be indicative of the range of passive use
values for the unprotected portions of the study area. However, there are several caveats to this
interpretation. First, Goldsmith et al. estimates are not based on any actual surveys to calculate
the contingent value specific to the resource at issue in Bristol Bay. Rather, they are based on
inferences from other studies (benefits transfer method). Second, these other studies date from
the 1980's and early 1990's and the implications of new literature and methods have not been
examined. Additionally, the assumptions used to make the benefits transfer for the wildlife
refuges may not be appropriate for the larger Bristol Bay study area which includes not only the
wildlife refuge, but also two large national parks. This topic is an area for future research.
26
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Table 7. Summary of Bristol Bay Wild Salmon Ecosystem Services, Net Economic Value
per Year (Million 2009 $)
Ecosystem Service
Commercial salmon fishery
Fishing Fleet
Fish Processing
Sport fishing
Sport hunting
Wildlife viewing / tourism
Subsistence harvest and activity
Total Direct Use Value
Low estimate

$30.4
$30.4
$12.2
$1.4
$8.1
$84.3
$166.80
High estimate

$55.9
$55.9
$12.2
$1.4
$8.1
$193.7
$327.20
Table 7 provides a summary of annual net economic values. Since these are values for renewable
resource services that in principle should be available in perpetuity, it is of interest to also
consider their present value (e.g. total discounted value of their use into the foreseeable future).
The controlling guidance document for discounting in cost benefit analysis, OMB Circular A-4
(2003), generally requires use of discount rates of 3% and 7%, but allows for lower, positive
consumption discount rates, perhaps in the 1 percent to 3 percent range, if there are important
intergenerational values. Weitzman, (who's work is cited both in the EPA guidance (EPA 2000)
and in OMB guidance (Circular A-4 (2003))) conducted an extensive survey of members of the
American Economic Association, and suggests a declining rate schedule, which may be on the
order of 4 percent (real) in the near term and declining to near zero in the long term. He suggests
a constant rate of 1.75% as an equivalent to his rate schedule. Table 8 shows the estimated net
present value in perpetuity of direct use values within the Bristol Bay Ecosystem. The table
shows a range of alternative discount rates from the standard "intragenerational" rates of 7% and
3% to the more appropriate "intergenerational" rates for the Bristol Bay case of 1.75% and 1.0%.
The entire range of NPV estimates in the table is from $2.4 to $32.7 billion. The range of
estimated direct use NPV of the resource using the more appropriate intergenerational discount
rates is from $9.6 to $32.7 billion. These estimates are likely quite conservative as they do not
include estimates of passive use values, but are limited to direct economic uses of the wild
salmon ecosystem services.
Table 8. Estimated Net Present Value of Bristol Bay Ecosystem Net Economic Use Values
and Alternative Assumed Perpetual Discount Rates
Estimate

Low Estimate
High Estimate
Net Present Value (million 2009 $)
Annual Value 7% Discount 3% Discount 1.75% Discount 1% Discount
$166.80
$327.20
$2,383
$4,674
$5,560
$10,907
$9,531
$18,697
$16,680
$32,720
27
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1.0 Introduction and Setting
This report provides information on the importance of wild fisheries and the natural environment
in the Bristol Bay region to the economies of the Bristol Bay region, the State of Alaska and the
U.S. as a whole.
1.1 Study Objectives and Report Organization

The primary purpose of this report is to estimate baseline levels of economic activity and values
associated with the current Bristol Bay Region wild salmon resource. This comprehensive report
includes and synthesizes individual reports on separate components of economic activity and
values linked to the Bristol Bay Ecosystem. Economic activity linked to Bristol Bay includes
sportfishing, subsistence harvest, sport hunting, and commercial fishing. Additionally, an
analysis of the structure of the Bristol Bay economy and the significance of these ecosystem-
related economic activities to the economy is presented.

This report on the baseline levels of economic activities (as of 2009) within the Bristol Bay
Ecosystem is organized as follows:

Section 1: Introduction and Setting
Section 2: Baseline Recreation and Subsistence Economics
Section 3: Baseline Commercial Fisheries Activity
Section 4: Economic Significance Analysis (Schworer et al.)
Section 5: Baseline Net Economic Values

The major components of the total value of the Bristol Bay area wild salmon ecosystems include
subsistence use, commercial fishing and processing, sportfishing, and the preservation values (or
indirect values) held by users and the U.S. resident population. The overall objectives of this
work are to estimate the share of the total regional economy (expenditures, income and jobs) that
is dependent on these essentially pristine wild salmon ecosystems, and to provide a preliminary
but relatively comprehensive estimate of the total economic value (from a benefit-cost
perspective) associated with the ecosystem.

28
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supplied by the entire Bristol Bay region. Values tied to, and specific to, the proposed mining
activity (and discharges) in the Nushugk and Kvichak Drainages would be a subset of those
reported here, and have not been identified in this general characterization analysis.
1.2 Definition of Study Area

The Bristol Bay region is located in southwestern Alaska. The region, which includes Bristol
Bay Borough, the Dillingham Census Area, and a large portion of Lake and Peninsula Borough,
contains a relatively small number of communities, the largest of which are shown in Figure 6.
The area is very sparsely populated and the large majority of its population is comprised of
Alaskan Natives (Table 9). Although median household income varies among census areas
within the region, outside of the relatively small Bristol Bay Borough, income is somewhat lower
than for the state of Alaska as a whole. As noted, Alaskan Natives make up over two-thirds of
the total population within the region as compared to approximately 15% for the entire state
(Table 9)

Table 9. Demographic and Socioeconomic Characteristics of the Bristol Bay Region
Area Population Percent Percent 18 Number of Median household
2010 Alaska or over households income 2009
Native
Bristol Bay Borough
Dillingham Census Area
Lake & Peninsula Borough
Total Bristol Bay Region
State of Alaska
997
4,847
1,631
7,745
710,231
48.2%
80.4%
74.6%
73.8%
14.8%
77.4%
67.1%
69.8%
66.7%
73.6%
423 $
1,563 $
553 $
2,539 $
234,779 $
64,418
46,580
42,234
48,010
66,712
Source: US Census Quickfacts. Quickfacts.census.gov
29
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Table 10. Bristol Bay Area Communities and Populations
Bristol Bay Area Community
Aleknagik
Clark's Point
Dillingham
Egegik
Ekwok
Igiugig
Iliamna
King Salmon
Kokhanok
Koliganek
Levelock
Manokotak
Naknek
New Stuyahok
Newhalen
Nondalton
Pedro Bay
Pilot Point
Port Alsworth
Port Heiden
South Naknek
Ugashik
Togiak City
Portage Creek
Twin Hills
Population
(2010 census)
219
62
2,329
109
115
50
109
374
170
209
69
442
544
510
190
164
42
68
159
102
79
12
817
2
74
Pacific Otean
Figure 6. Bristol Bay Area Location and Major Communities
30
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This study focuses on the economic contributions of the Bristol Bay ecosystem. The rivers that
flow into the Bristol Bay comprise some of the last great wild salmon ecosystems in North
America (Figure 7). All five species of Pacific salmon are abundant, and the rich salmon-based
ecology also supports many other fish species, including healthy populations of rainbow trout.
The Naknek, Nushagak-Mulchatna, and Kvichak-Lake Iliamna watersheds are relatively pristine
with very little reading or extractive resource development. The existing mainstays of the
economy in this region are all wilderness-compatible and sustainable in the long run: subsistence
use, commercial fishing, and wilderness sportfishing. Commercial fishing largely takes place in
the salt water outside of the rivers themselves and is closely managed for sustainability. The
subsistence and sportfish sectors are relatively low impact; primarily personal use and catch and
release fishing, respectively. Additionally, there are important public lands in the headwaters,
including Lake Clark National Park and Preserve, Katmai National Park and Preserve, and
Togiak National Wildlife Refuge.

The Bristol Bay area includes the political designations of Bristol Bay Borough, the Dillingham
census area, and most of Lake and Peninsula Borough. The largest town in the area is
Dillingham. In 2010 the Dillingham census area had an estimated population of 4,847 (US
Census, Quick Facts).
31
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Nushagak
Kviehak
Figure 7. Map of Bristol Bay Study Area
1.3 Focus of Study-Economic Uses

As noted, this report focuses on estimating baseline levels of ecosystem services provided by the
Bristol Bay Region. These services are broad and substantial and include, but are not limited to
commercial, aesthetic, recreational, cultural, natural history, wildlife and bird life, and ecosystem
services.

A primary dichotomy of economic value is the division of values into those that are, or can be
traded within existing economic markets, and those for which no developed market exists.
Examples of resource services specific to the Bristol Bay region that are traded in markets are
commercial fish harvests and guided fishing trips. While a number of services provided by
Bristol Bay natural resources can be classified as market services (with associated market-
derived values), there are many services provided by this area that are classified as non-market
services. These non-market resource services include noncommercial fishing, wildlife watching,
subsistence harvests, protection of cultural sites, and aesthetic services.

A second dichotomy of resource services and associated values is that of direct use and passive
use services and values. The most obvious type, direct use services, relates to direct onsite uses.
The second type of resource services are so-called passive use services. These services have
values that derive from a given resource and are not dependent on direct on-site use. Several of
the possible motives for passive use values were first described by Weisbrod (1964) and Krutilla
32
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(1967), and include existence and bequest values. Existence values can derive from merely
knowing that a given natural environment or population exists in a viable condition. For
example, if there were a proposal to significantly alter the Bristol Bay natural ecosystem, many
individuals could experience a real loss, even though they may have no expectation of ever
personally visiting the area.

While use services may or may not have associated developed markets for them, passive use
services are exclusively non-market services.

When passive use and use values are estimated together, the estimate is referred to as total
valuation. This concept was first introduced by Randall and Stoll (1983) and has been further
developed by Hoehn and Randall (1989).

The National Research Council in their 2005 publication "Valuing Ecosystem Services: Toward
Better Environmental Decision Making" provided an outline of ecosystem services. Table 11
provides an application of the NRC outline to Bristol Bay resources, and details examples of the
ecosystem services, both use and passive use, that are produced by natural resources such as
those found in the Bristol Bay region.
Table 11: Types of Ecosystem Services
Use Values
Nonuse Values
Direct

Commercial and recreational
fishing

Aquaculture

Transportation

Wild resources

Potable water

Recreation

Genetic material

Scientific and educational
opportunities
Indirect

Nutrient retention and cycling

Flood control

Storm protection

Habitat function

Shoreline and river bank
stabilization
Existence and Bequest
Values
Cultural heritage

Resources for future
generations

Existence of charismatic
species

Existence of wild places
A comprehensive economic evaluation of these Bristol Bay wild salmon ecosystems needs to
include two distinct accounting frameworks. One is regional economics or economic
significance, focused on identifying cash expenditures that drive income and job levels in the
33
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regional economy. The other is a net economic value framework that includes all potential costs
and benefits from a broader social perspective. The latter necessarily includes nonmarket and
indirect benefits, such as the benefits anglers derive from their recreational activity, over and
above their actual expenditure. Both perspectives are important for policy discussions and
generally both accounting frameworks are utilized in evaluating public decisions..
34
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2.0 Bristol Bay Recreation and Subsistence Economics

Section 2 of this report addresses the regional economic activity associated with the recreation
and subsistence sectors. Primary recreational activities examined include sportfishing, sport
hunting, and tourism/wildlife viewing.
2.1 Bristol Bay Sportfishing Economics

Sportfishing is a consistently economically significant economic activity in the Bristol Bay
Region. Information sources for this section are the Duffield et al. (2007) report on Bristol Bay
Salmon Ecosystem economics (referred to hereafter as the 2005 Bristol Bay Study), and Alaska
Department of Fish and Game estimates of the total populations of anglers fishing the Bristol
Bay Area waters, (pers. Comm. G. Jennings, August 2011)

The sport angler and trip characteristics, expenditures, and values are presented using several
sub-sample breakouts. Comparisons of sub-samples are presented to highlight similarities as
well as differences between sample groups. Primary sub-samples examined include non-resident
anglers, non-local Alaska resident anglers, and Bristol Bay resident anglers.

The 2005 Bristol Bay study examined angler responses to a wide range of questions on their
opinions, preferences, and experiences relating to fishing in the Bristol Bay area. The following
sportfishing results focus on key characteristics of Bristol Bay sportfishing. Estimates of angler
spending and net economic values have been adjusted from the original 2005 dollars to 2009
dollars using the Consumer Price Index-Urban (CPI-U).
2.1.1 Bristol Bay Area Trip Characteristics and Angler Attitudes

The 2005 Bristol Bay Study reported several differences between how nonresident anglers and
Alaska anglers access Bristol Bay fisheries and the types of accommodations they use when
there. For non-resident anglers the most common trip included staying at a remote lodge and
flying or boating with a guide (35.2%). Resident anglers accessed the Bristol Bay area with their
own plane or boat (49.9%), driving to area by motor vehicle (11.3%), and "other" type of trips
(24%). Those who reported driving to access Bristol Bay fisheries were primarily residents and
nonresidents staying in the King Salmon and Dillingham area, where a few local roads exist and
provide some access to nearby fisheries.
35
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Table 12. Bristol Bay Angler Distribution across Trip Types, by Residency
Trip Type
Stayed at a remote lodge and flew or boated with a guide to fishing
Stayed at a tent or cabin camp and fished waters accessible from camp
Hired other lodging in an area community and either fished on own or
contracted for travel on a daily basis
Floated a section of river with a guided party
Hired a drop-off service and fished and camped on our own
Accessed the area with my own airplane or boat
Drove to the area by motor vehicle
Other
Sample Size
Non-residents
(%)
35.2
23.7
6.4

3.9
4.3
8.3
4.3
14.0
246
Alaska
Residents (%)
-
7.8
4.2

2.8
2.2
49.9
11.3
24.0
55
Note: sample size for resident sample is not large enough to divide into local and non-local sub-samples

Other
Drove to area
Accessed area with own
boat or plane
Hired float, drop off, or
other lodging
Stayed at a tent or cabin
camp
Stayed at a remote
lodge

|11°/
1 4%

1 24%
4%
)

%
3%
I
1 8°
'o

0%
15%

1 24%

1 35%

0.00% 10.00%

50%

20.00% 30.00% 40.00% 50.00% 60.00%
Percent of respondents
D Nonresidents • Residents

Figure 8. Comparison of Resident and Nonresident Bristol Bay Angler Trip Types
Respondents to the 2005 Bristol Bay survey were asked what was the primary purpose of their
trip to the Bristol Bay area. A majority of nonresidents (73%) reported fishing as their major
purpose; 30% of resident anglers reported fishing as the main purpose of their most recent
Bristol Bay trip. Table 13 also shows that a much larger proportion of non-residents (45%) than
residents (11.4%) were on their first trip to their primary fishing destination.

36
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Table 13: Bristol Bay Angler Trip Characteristics.
Statistic
Major purpose of trip
was for fishing
Trip was first trip to
primary destination
Nonresidents
(sample size)
72.7%
(246)
45.2%
(245)
Alaska Residents
29.5%
(54)
1 1 .4%
(48)
Survey respondents in the 2005 study were asked what fish species they targeted on their most
recent trip to Bristol Bay. Table 14 reports these results. Overall, king salmon and rainbow trout
were the most frequently targeted species for both residents and non-residents.

Table 14: Bristol Bay Angler Survey, Targeted Species.

Primary species targeted on
trip / statistic
Rainbow Trout
King Salmon
Silver Salmon
Sockeye Salmon
Other Species
Sample size
Bristol Bay Anglers
Nonresidents
30.6%
35.2%
16.3%
9.1%
8.8%
235
Alaska Residents
31 .3%
29.8%
16.5%
0%
22.4%
48
Respondents to the 2005 Bristol Bay angler survey were presented with a series of statements
regarding fishing conditions on their Bristol Bay area trip. They were asked to indicate their
level of agreement or disagreement with each statement. Table 15 shows the percent of residents
and non-residents who either "agreed" or "strongly agreed" with each statement. Across all of
the statements presented in the survey, majorities of both resident and non-resident respondents
agreed with the positive statements about their fishing experience. The highest levels of
agreement for both nonresidents and Alaska resident anglers were with the statements "there was
a reasonable opportunity to catch fish", "there was minimal conflict with other anglers", and
"fishing was in a wilderness setting."
37
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Table 15: Bristol Bay Angler Rating of Selected Attributes of Fishing Trip
Statement
Fishing conditions were un-crowded
There was a reasonable opportunity to catch fish
There was minimal conflict with other anglers
Fishing was in a wilderness setting
There was opportunity to catch trophy-sized fish
There was opportunity to catch and release large # of fish
Sample Size
% of respondents who either
"agree" or "strongly agree"
Nonresidents Alaska Residents
87.2% 75.4%
96.5% 93.0%
93.3% 90.7%
92.4% 95.0%
81 .4% 70.0%
87.3% 76.6%
235 47
2.1.2 Bristol Bay Angler Expenditures

Respondents to the 2005 Bristol Bay angler survey were asked a series of questions relating to
the amount of money they spent on their fishing trips. Average spending per trip was estimated
for three types of anglers: local Bristol Bay Area residents, Alaska residents from outside the
Bristol Bay region, and nonresidents. Adjusted to 2009 price levels, nonresidents reported
spending the most for their sportfishing trips to Bristol Bay ($3,995). Alaska resident anglers,
those from outside Bristol Bay spent an average of $1,582 per trip and those living within the
Bristol Bay region reported spending an average of $373 per sportfishing trip.

Table 16 breaks out average expenditures by impact region and type of fishing trip for the
nonresident angler sample. Where money is spent on a trip determines local economic impacts.
For instance, a given amount of money spent within the very small Bristol Bay economy has a
much greater relative impact than the same amount of money spent in a larger economy, such as
Anchorage. Table 16 shows that the largest per-trip spending is made by nonresident anglers
who stay at a remote lodge with daily guiding services ($6,950/trip). This compares to the
lowest spending levels per trip of about $1,400 for driving to the fishing site, accessing the area
with own plane or boat, and hiring a drop-off service and fishing or camping on own.

The first two rows of Table 16 show that a large portion of Alaska trip costs for remote lodge or
tent or cabin camp trips is associated with the cost of a sport-fishing package or tour. This sport-
fishing package spending is assumed to be spent in the Bristol Bay region.
38
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Table 16. Nonresident Trips to Bristol Bay Waters, Mean Expenditure Per Trip Estimates
By Trip Type
Trip type
Stayed at a remote lodge and flew or boated with a
guide to fishing sites most days
Stayed at a tent or cabin camp and fished waters
accessible from this base camp
Hired other lodging in an area community and either
fished on own or contracted for travel on a daily
basis
Floated a section of river with a guided party
Hired a drop-off service and fished and camped on
our own
Accessed the area with my own airplane or boat
Drove to the area by motor vehicle
Other
Total Reported
Trip Spending

$6,950

$4,158

$2,643
$2,187

$1,515
$1,437
$1,453
$2,233
Bristol Bay
spending11

$1,900

$1,357

$1,818

$1,145
$1,291
$1,062
$1,047
Package sport-
fishing trip
spending

$6,089

$3,517

$2,576

$2,422
a all spending in Bristol Bay except package sportfishing trip expenditures (package trip expenditures are also assumed spent in
the Bristol Bay Region)
Note: cells with less than 5 observations are left blank. Category values are the average values for those respondents reporting an
expense in that category. Bristol Bay spending and Package sport-fishing tour spending will not necessarily sum to Total spending
due to varying sample sizes.
Table 17 details the distribution of Bristol Bay trip spending across expenditure categories. For
non-residents visitors, the largest three spending categories within the Bristol Bay area were for
commercial and air taxi service and for lodging or camping fees (totaling about 66% of all
spending in Bristol Bay). For non-local Alaska residents the three largest categories of spending
were "gas and other Alaska travel costs," camping fees, and commercial air travel (totaling about
58% of all Bristol Bay spending by non-local Alaska residents).
Table 17: Distribution of Trip Expenditures across Spending Categories, by Residency and
Area

Expenditure category
Commercial air travel
Air taxi service
Transportation by boat
Boat or vehicle rental
Gas or other travel costs in AK
Lodging or camping fees
food or beverages
Guide fees
Fishing supplies
Other non-fish package tours
Other
Nonresidents
In Bristol Bay
31.1%
20.5%
0.0%
5.3%
4.1%
13.9%
9.2%
6.2%
4.1%
0.1%
5.4%
In rest of AK
51 .9%
1.3%
0.0%
4.8%
1 .4%
1 1 .9%
19.3%
0.6%
5.2%
0.7%
2.9%
non-local AK
residents
In Bristol Bay
18.1%
11.1%
0.0%
7.5%
16.3%
23.6%
16.7%
0.0%
6.7%
0.0%
0.0%
39
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2.1.3 Aggregate Direct Sport fishing Expenditures in Bristol Bay

In order to derive estimated aggregate angler expenditures related to sportfishing in the Bristol
Bay region, two primary pieces of information were needed: 1) the number of angler trips per
year to the region by Alaska residents and nonresidents, and 2) the average spending per trip by
resident and nonresident anglers. A trip is defined here as a roundtrip visit from home, and
return. Estimates of the number of anglers who fished in the Bristol Bay region in 2009 were
derived by ADF&G staff (Table 18). The average number of trips per angler, estimated from
responses to the 2005 Bristol Bay angler survey, is also shown in Table 18. In total
approximately 29,000 sport fishing trips were taken in 2009 to Bristol Bay freshwater fisheries.
These trips are roughly split between 12,000 nonresident trips, 13,000 Bristol Bay resident trips,
and 4,000 trips by Alaskans living outside of the Bristol Bay area.
Table 18. Estimated 2009 Bristol Bay area angler trips, by Angler Residency
Statistic
Annual Anglers
fishing Bristol Bay
waters
Average trips per
angler for 2005
Estimated total
trips
Nonresidents Out-of-area AK
residents
9,572 2,561

1.30 1.49
12,464 3,827

BB Residents
1,133

11.54
13,076

Table 19 presents the aggregation of total angler expenditures within the Bristol Bay region.
This table shows average and aggregate estimated expenditures for three angler groups: 1)
nonresident anglers, 2) local-area resident anglers (those who live in the Bristol Bay area), and 3)
non-local resident anglers (those Alaska residents living outside of the Bristol Bay region). This
table also shows average and total annual spending by nonresident anglers for package
sportfishing trips in the Bristol Bay region.

Overall, the large majority of angler spending in the region is attributable to nonresident anglers.
Additionally, the majority of nonresident spending is due to the purchase of sportfishing
packages such as accommodation and angling at one of the areas remote fishing lodges.
Estimates of variability in the estimates were derived for average expenditure levels, and total
visitation estimates. It is estimated that annually Bristol Bay anglers spend approximately $58
million within the Bristol Bay economy. Given the variability in the components of this
estimate, the 95% confidence interval for Bristol Bay area spending by anglers from outside the
area ranges from $0 to $130 million annually. The vast majority of this spending (approximately
$47 million annually) is spent by nonresident anglers.

40
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Table 19. Estimated Aggregate Spending Associated with Sportfishing in the Bristol Bay
Region (2009 dollars)

Mean expenditures in Bristol
Bay region
Estimated trips
Total Bristol Bay direct
expenditures
Nonresidents
All Non Residents
$ 1,471
12,464
$ 18,333,187
Remote Lodge
Increment
$4,698
6,187
$ 29,068,303
out-of-area AK
residents

$ 1,582
3,827
$ 6,053,700
BB Residents

$ 373
13,076
$ 4,874,848
Total

29,367
$ 58,330,039
Table 20 presents total estimated direct angler expenditures by residency, and location of
spending. Again, among all direct spending related to Bristol Bay angling, the large majority is
associated with nonresidents traveling to Alaska. Additionally, the large majority of this
spending is reported to have occurred within the Bristol Bay economy. This table categorizes
spending by origin and destination. This classification is then used in the regional economic
significance analysis presented in Section 4.
Table 20. Bristol Bay Sportfishing: Aggregate in and out of Region and State Spending
(2009)
Population

NONRESIDENT Base trip spending
NONRESIDENT Sportfish package
spending
NONRESIDENT TOTAL
RESIDENTS
OUT-OF-BB RESIDENT base trip
spending
BB RESIDENT base trip spending
ALASKA RESIDENT TOTAL
TOTAL
In Bristol Bay Spending
Total spending in
Bristol Bay
$ 18,333,187
$ 29,068,303
$ 47,401,490

$ 6,053,700
$ 4,874,848
$ 10,928,549
S 58,330,039
Total spending
from outside
Bristol Bay
$ 18,333,187
$ 29,068,303
$ 47,401,490

$ 6,053,700
$
$ 6,053,700
S 53,455,190
In Alaska Spending
Total in- state
spending
$ 20,727,318
$ 29,068,303
$ 49,795,621

$ 6,053,700
$ 4,874,848
$ 10,928,549
S 60,724,170

Spending from
outside Alaska
$ 20,727,318
$ 29,068,303
$ 49,795,621

$
$
$
S 49,795,621
41
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2.2 Bristol Bay Subsistence Harvest Economics

The subsistence harvest within the Bristol Bay region generates regional economic impacts when
Alaskan households spend money on subsistence-related supplies. Goldsmith (1998) estimated
that Alaskan Native households that use Bristol Bay wildlife refuges for subsistence harvesting
spend an average of $2,300 per year on subsistence-related equipment to aid in their harvesting
activities. Additionally, Goldsmith estimated that Non-Native households spend $600 annually
for this purpose. Correcting for inflation from 1998 to 2009 implies annual spending for
subsistence harvest of about $3,054 for Native households and $796 for Non-Native
households.7

Figure 9 shows the general distribution of subsistence harvest by Bristol Bay residents. Overall,
salmon make up the largest share of all harvest (on a basis of usable pounds), and accounts for
over one-half of all harvest. Another nearly one third of harvest come from land mammals
(31%), and non-salmon fish comprise another 10% of harvest.
7 A 1998-99 survey of the village of Atyqasuk (North Slope Borough) found that 3 3% of households spent between
$4,000 and $10,000 on subsistence activities and 9% spent more than $10,000 per year (US DOI, BLM and MMS
2005). The simple parametric mean for this inland community that harvested no whales was $3,740 per year per
household (1999 dollars). The use of the adjusted Goldsmith estimates therefore likely provides a conservative
estimate of subsistence expenditures.

42
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Salmon
52% ~\
Land Mammals
31%
Non-Salmon
10%
I
Birds and Eggs
2% I
Vegetation
3%
\ ^Marine Invertebrates
\ 0%
Marine Mammals
2%
Figure 9. Distribution of Bristol Bay Subsistence Harvest
Table 21 shows average per capita and total estimated community subsistence harvest for the
Bristol Bay communities. In total, individuals in these Bristol Bay communities harvest about
2.6 million pounds of subsistence harvest per year for an average of 343 pounds per person
annually. Table 22 and Table 23 detail Bristol Bay area subsistence harvest by salmon species
and location.
Table 21. ADF&G Division of Subsistence Average Per Capita Subsistence Harvest for
Bristol Bay Communities
Bristol Bay Area Community /year
of AKF&G harvest data survey
Aleknagik 2008
Clark's Point 2008
Dillingham 1984
Egegik 1984
Population Per Capita Harvest Total Annual
(2010 census) (raw pounds of Harvest
harvest)(AKF&G
Subsistence
Surveys)
219 296 64,824
62 1210 75,020
2,329 242 563,618
109 384 41,856
43
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Ekwok 1987
Igiugig 2005
Iliamna 2004
King Salmon 2008
Kokhanok 2005
Koliganek 2005
Levelock 2005
Manokotak 2008
Naknek 2008
New Stuyahok 2005
Newhalen 2004
Nondalton 2004
Pedro Bay 2004
Pilot Point 1987
Port Alsworth 2004
Port Heiden 1987
South Naknek 2008
Ugashik 1987
Togiak City 2000
Twin Hills 2000
Total surveyed communities
Un-surveyed communities
Total including un-surveyed areas
115
50
109
374
170
209
69
442
544
510
190
164
42
68
159
102
79
12
817
74
7,018
457
7,475
797
542
469
313
680
899
527
298
264
389
692
358
306
384
133
408
268
814
246
499

343
91,655
27,100
51,121
117,062
115,600
187,891
36,363
131,716
143,616
198,390
131,480
58,712
12,852
26,112
21,147
41,616
21,172
9,768
200,982
36,926

-
2,563,313
44
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Table 22. Historical Subsistence Salmon Harvest for Bristol Bay, Alaska: 1975-2007
(ADF&G Division of Subsistence ASFDB)
Year
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Average
Permits
686
716
738
773
829
1,243
1,112
806
829
882
1,015
930
996
938
955
1,042
1,194
1,203
1,206
1,193
1,119
1,110
1,166
1,234
1,219
1,219
1,226
1,093
1,182
1,100
1,076
1,050
1,063
1,035
Number of Fish Harvested
Chinook
8,600
8,400
7,000
8,100
10,300
14,100
13,000
13,700
13,268
11,537
9,737
14,893
14,424
11,848
9,678
13,462
15,245
16,425
20,527
18,873
15,921
18,072
19,074
15,621
13,009
11,547
14,412
12,936
21,231
18,012
15,212
12,617
15,444
13,825
Sockeye
175,400
120,900
127,900
127,600
116,500
168,600
132,100
110,800
143,639
168,803
142,755
129,487
135,782
125,556
125,243
128,343
137,837
133,605
134,050
120,782
107,717
107,737
118,250
113,289
122,281
92,050
92,041
81,088
95,690
93,819
98,511
95,201
99,549
121,906
Coho
8,500
3,500
6,600
4,400
7,300
7,300
12,200
11,500
7,477
16,035
8,122
11,005
8,854
7,333
12,069
8,389
14,024
10,722
8,915
9,279
7,423
7,519
6,196
8,126
6,143
7,991
8,406
6,565
7,816
6,667
7,889
5,697
4,880
8,329
Chum
7,500
9,100
9,100
16,200
7,700
13,100
11,500
12,400
11,646
13,009
5,776
11,268
8,161
9,575
7,283
9,224
6,574
10,661
6,539
6,144
4,566
5,813
2,962
3,869
3,653
4,637
4,158
6,658
5,868
5,141
6,102
5,321
3,991
7,733
Pink
1,300
4,400
300
12,700
500
10,000
2,600
8,600
1,073
8,228
825
7,458
673
7,341
801
4,455
572
5,325
1,051
2,708
691
2,434
674
2,424
420
2,599
839
2,341
1,062
3,225
1,098
2,726
815
3,099
Total
192,700
137,900
143,900
160,900
132,000
199,000
158,400
143,300
177,104
217,612
167,215
174,112
167,894
161,652
155,074
163,874
174,251
176,739
171,082
157,787
136,319
141,575
147,156
143,330
145,506
118,824
119,856
109,587
131,667
126,865
128,812
121,564
124,679
152,371
Harvest
per permit
280.9
192.6
195
208.2
159.2
160.1
142.4
177.8
213.6
246.7
164.7
187.2
168.6
172.3
162.4
157.3
145.9
146.9
141.9
132.3
121.8
127.5
126.2
116.2
119.4
97.5
97.8
100.3
111.4
115.3
119.7
115.8
117.3
153
45
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Table 23. Bristol Bay Subsistence Salmon Harvests by District and Location Fished, 2007.
(Fall et al. 2009)
Area sod river srscem
Xaknek- &ichak District
Nakiiek Paver subdistrict
Kvicliak River- niamma Lake
subdistnct:
Chekok
IgillgJE
Hiamna Lake-general
Kijik
Kokhauok
Kvichak River
Lake Clark
Leveled;
Newhalen River
Pedro Bay
Sixniile Lake
Egegik District
Ugashik District
Nushagak District
Wood River
Niishagak River
Niishagak Bay
noncommercial
Niishagak Bay commercial
Igushik.''%iiake River
Niishagak. site unspecified
Togiak District
Total
Number of
permits
issued*
480
287
196

1
4
31
4
30
12
34
1
39
20
26
28
17
496
135
117
228
33
25
1
45
1J«
Estimated salmon harvest
Chinook
672
664
8

0
1
0
0
6
0
0
1
0
0
0
165
43
13,330
1.793
5,479
5,138
418
500
1
1,234
15,444
Sock eye
69,837
22.364
47,473

310
1,419
5,017
769
15,540
1,203
3,604
102
8,732
5.569
5,208
980
1,056
25,127
6,813
5.879
9,545
S87
2,000
3
2,548
99,549
Coho
L104
1.078
26

0
0
0
0
26
0
0
0
0
0
0
334
281
3.050
293
1,127
L467
113
36
15
110
4,880
Chum
405
375
30

*0
i
0
0
~>J
0
0
&
0
0
0
•Jl
88
3.006
249
1,572
1:009
119
'^~
0
420
3^91
Pick
262
260
1

0
0
0
0
1
0
0
0
0
0
0
26
70
430
36
213
163
12
6
0
19
815
Total
72.280
24.742
47.538

310
1.422
5.017
769
15,595
1.203
3.604
109
S.732
5.569
5,208
1.577
1.546
44.944
9.184
14.270
17.322
1.550
2.599
19
4.332
124,679
Notes Esrrests are extrapolated for all pemate issued, based on those retimied and on the ares £shed as reported on
the permit. Due to rounding, the sum of coiwnns and rows may not equal tie estimated total Of 1,063 permit;
issued for the management area. 917 were returned (86.3-?-o).
a. Sum of sites may exceed district totals, and ami of districts may excead area total, because permittees may xise
mole than one site.
Source ADF&G Division of Subsistence ASFDB.
46
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In 2010 the US Census reported an estimated 1,873 Native and 666 non-native households in the
Bristol Bay Region (Bristol Bay Borough, Lake and Peninsula Borough, and Dillingham). Based
on the Goldsmith (1998) estimate of direct expenditures related to subsistence harvest, this
implies an annual direct subsistence-related expenditure of approximately $6.3 million in the
Bristol Bay region.
Table 24. Estimated Total Annual Bristol Bay Area Subsistence-Related Expenditures
(2009 $)
Area
Bristol Bay Borough
Dillingham Census Area
Lake & Peninsula Borough
Total Bristol Bay Region
Annual Spending/ household
Total Estimated
Subsistence Spending
Total
Population
2010
997
4847
1631
7,475

Percent Alaska
native
48.2%
74.6%
80.4%
73.8%

Number of
households
423
553
1563
2539

Number of
Native
Households
204
413
1257
1873
$ 3,054
$ 5,720,054
Number of
non-native
Households
219
140
306
666
$ 796
$ 530,350
$ 6,250,404
2.3 Bristol Bay Sport Hunting and Non-consumptive
Economics
2.3.1 Sport Hunting

In addition to sport fishing, sport hunting also plays a significant (but smaller) role in the local
economy of the Bristol Bay region. While not a large share of the economy, sport hunting in the
Bristol Bay area offers high quality hunting opportunities for highly valued species. Bristol Bay
sport hunting provides hunting opportunities for caribou, moose, and brown bear, among other
species. Table 25 shows reported hunter numbers for the most recently reported representative
years for several species hunted in the region. The big game hunting numbers are reported for
the two Game Management Units (GMUs) that comprise the Bristol Bay Region. GMUs are
spatial areas delineated by AKF&G to more closely correspond to wildlife habitat and population
ranges than do other geographical or political boundaries.
47
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Table 25. ADF&G Reported Big Game Hunting in Bristol Bay and Alaska Peninsula Game
Management Units
Most recent Big
(Number of nun
Moose
Caribou
Brown bear
The caribou estii
Shaded cells
Sources: AKDF&C
Game Hunting Estimates from ADF&G Wildlife Management Reports
ters)
Alaska Peninsula
(GMU 9)
Non-local
Residents
91
0
600
691
Nonreside
nts
157
0
624
781
Bristol Bay
(GMU 17)
Non-local
Residents Nonresidents
200 195
311 230
117 117
628 542
nate for GMU 17 is for the Mulchatna herd and extends beyond GMU 17 borders
include both non-local residents and local residents
j Species-specific Wildlife Management Reports
Table 26 outlines the estimation of total annual expenditures for big game hunting within the
Bristol Bay region. These estimates are based on an assumption of one trip per hunter per year
for a species, and utilize estimates of hunter expenditures per trip developed by Miller and
McCollum (1994) adjusted to 2009 price levels.
Table 26. Estimated annual big game hunting expenditures for Bristol Bay region
Statistic
Non-local Residents
Nonresidents
Estimated trips
Expenditure per trip
Total estimated direct
expenditure
1,319
1,068

1,408,351
1,323
5,170

6,839,301
Total
$
8,247,652.52
In total, it is estimated that Bristol Bay area big game hunters living outside of the area spend
about $8.2 million per year in direct hunting-related expenditures. The expenditure estimate
above may include some caribou hunting of the Mulchatna herd outside of the closely defined
Bristol Bay region game management units, resulting in an overestimate of spending for hunting
this species.
2.3.2 Non-consumptive Wildlife Viewing / Tourism Economics

Many of the sport fishing and sport hunting visitors to the Bristol Bay region also engage in
other activities such as kayaking, canoeing, wildlife viewing or bird watching. These activities
48
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are typically referred to as non-consumptive because unlike hunting or fishing, no resource is
"consumed," rather the goal is to leave the resource (flora and fauna) unchanged.

The Bristol Bay region has a number of nationally recognized special management areas for
wildlife. These include Katmai and Lake Clark National Parks, the Togiak and Becherof
National Wildlife Refuges, and Wood-Tikchick State Park. The most accessible and popular
destination for visitors interested in non-consumptive recreation activities is Katmai National
Park, and in particular Brooks Camp on Naknek Lake which is world famous as a site for bear
viewing. The camp accommodates both day and overnight visitors who are there to view the
bears, as well as sport fishermen.

Information on the number of non-consumptive use visitors, their itineraries and activities while
in the region, and their expenditures is somewhat limited. Unlike sport fishing and sport hunting,
no license is required for these other activities so there is no consistent and comprehensive
record documenting these trips.

The visitation estimates that form the basis for the analysis of non-consumptive use in Southwest
Alaska are primarily based on McDowell Group's (2006) Alaska Visitor Statistics Program
(AVSP) estimate . The AVSP is a comprehensive State of Alaska research program initiated in
1982 and follows a strict and proven methodology. The methodology utilizes an exit survey to
intercept visitors. As a result of the concentration of visitors in urban parts of the state, the
survey method tends to oversample urban visitors and undersample rural visitors. Based on a
separate stratified rural sample conducted during the 2001 AVSP, it is known that the survey
methodology tends to underestimate visitation to remote rural parts of the state such as
Southwest Alaska. Thus, the overall visitation used for this analysis can be considered
conservative. In addition to McDowell Group (2006), Fay and Christensen (201 l)'s 2007
estimate of visitation to Katmai was utilized.

For this analysis non consumptive users are defined as those who reported wildlife viewing,
camping, kayaking, hiking, or photography as their primary purpose of their visit. We adjust the
most recent 2006 summer and winter visitor estimate for Southwest Alaska excluding Kodiak by
applying the 2006-2009 percent difference in air travelers for Alaska overall (McDowell Group,
2007a & 2007b). The trend in air travelers to Alaska serves as the best indicator for changes to
visitation in Southwest Alaska for two reasons. First, visitors to rural Alaska are mainly
independent travelers, and second they primarily arrive by air in comparison to the statewide
largest share of visitors who arrive by cruise ship. The Southwest Alaska region closely matches
the Bristol Bay study region with the exception of Kodiak and the Aleutian Islands. Our analysis
excludes Kodiak but includes an insignificant portion of visitors to the Aleutian Islands.

Since the Alaska Visitor Statistics Program counts out-of-state visitors only, we calculate visitor
volume originating within the state based on Littlejohn and Hollenhorst (2007) and Colt and
Dugan (2005) resident share of between ten and eleven percent. We treat visitation to Katmai
NPP separate from other areas of the Bristol Bay region. Visitor volume and expenditure for
Katmai NPP are from Fay and Christensen (2010) and for the remaining Bristol Bay area are
from McDowell Group (2007a). We net out sport fishing and hunting visitation in Katmai NPP
using Littlejohn and Hollenhorst (2007) and for the rest of the region by applying the McDowell

49
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Group (2007a and 2007b) estimate. We assume equal expenditures for residents and non-
residents because the non-resident per person expenditure estimate in both cases does not include
the cost of travel to and from Alaska. For most non-residents all in-state travel expenditures are
included, based on the assumption that the primary reason for the travel to Alaska is the visit the
Bristol Bay region. For all of these estimates, we paid special attention to the potential for double
counting and addressed those issues.

Based on the most recent studies of non-resident visitors to the state and two studies that
estimated visitation and economic impacts related to Katmai National Park and Preserve, we
estimate that on an annual basis including summer and winter visitation, approximately 2,300
residents and 18,900 non-residents visited Katmai NPP. Other areas in the Bristol Bay region
received approximately 2,300 resident visitors and 19,000 non-resident visitors. Note, these
estimates exclude visitation where sport fishing or sport hunting was in part or the primary
activity of choice. After adjusting the per capita expenditures to 2009 dollars we estimate per
person expenditures to amount to $2,245 annually for Katmai NPP and $2,873 per person
annually for visiting other destinations in the Bristol Bay region.

To be consistent with the expenditure data for sport fishing and hunting, we assume that the visit
to the Bristol Bay region was the primary reason for their visit to Alaska. Based on these
assumptions, 2009 total expenditure for this group is estimated to be $104.2 million.

It should be noted that an earlier estimate of Bristol Bay non-consumptive (wildlife watching)
visitor expenditures (Duffield et al. 2007) reported a much lower spending level by this group
($17.1 million). As noted in that report, the estimate was based on extremely limited and dated
information from one location within the region (Brooks Camp). The estimate was derived and
presented as an approximation, as was also noted in the report, "This is an approximate estimate
based on limited and outdated information, and is an area for further research."(Duffield et al.
2007, p. 91).

The estimates derived in this later, current report utilizes both visitation and expenditure
estimates that were not available when the earlier report was drafted.
50
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3.0 Bristol Bay Commercial Fisheries
3.1 Introduction

This section provides an economic overview of Alaska's Bristol Bay commercial salmon
industry. The report begins with a brief overview of the industry. Subsequent sections discuss
harvests, products and markets, prices, harvest and wholesale value, fishermen, processors,
employment, taxes, the regional distribution of permit holders, fishery earnings and processing
employment, and the role of the industry in the Bristol Bay regional economy. The final section
discusses selected economic measures of the Bristol Bay salmon industry.

A challenge in characterizing the Bristol Bay fishery is that there is wide variation from year to
year in catches, prices, earnings, employment and other measures of the fishery. No single
recent year or period is necessarily "representative" of the fishery or what it will look like in the
future. To illustrate the range of historical variation in the fishery, wherever possible this report
provides data or graphs for at least the years since 2000, and in many cases for longer periods.

This report focuses on the economic significance of the entire Bristol Bay commercial salmon
fishery. The fishery harvests salmon returning to several major river systems, including the
Nushagak and Kvichak. Currently, because of potential future resource development in these
watersheds, there is particular interest in the fisheries resources and economic significance of
these two river system. As discussed in greater below, historically the relative contribution of
these river systems to total Bristol Bay commercial salmon harvests has varied widely from year
to year and over longer-term periods. There is no simple way to characterize what share of the
Bristol Bay commercial fishery is attributable to the Nushagak and Kvichak river systems, or
what this share will be in the future.

Some of the prices and values presented in this report are presented as nominal prices and values
(not adjusted for inflation), and others are presented as real prices and values (adjusted for
inflation). In general, we used nominal prices where our primary purpose was to show actual
prices and values over time (and as they appeared to people over time), and we used real prices
where our primary purpose was to compare prices and values over time. Prices and values are
expressed in nominal dollars except where the report specifically notes that they are real dollars.
All real prices are expressed in 2010 dollars, as calculated using the Anchorage Consumer Price
Index. This is far from an ideal measure, but it is the only long-term measure of inflation
o
available for any Alaska location.
In theory, it may appear more technically accurate to express all prices in real dollars. In
practice, there are several reasons why nominal prices are preferable for much of the data
presented in this report. First, it is far from obvious what the measure of inflation should be:
while the Anchorage CPI is the best available measure, it is not necessarily a good
characterization of the inflation actually experienced by Bristol Bay fishermen or processors.
Secondly, when price or value data are converted to "real" values it is harder to compare them to
other data unless those data have been converted to real values for the same year. Data
converted to real dollars quickly use their utility as a reference source. Third, people familiar

51
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The report presents a wide variety of data for the Bristol Bay salmon industry in graphs and
tables as well as in the text of the report. Detailed information on the data sources for all graphs ,
tables and text are provided in the data appendix at the end of the report. The report is based on
data available as of October 2011.

We've included pictures in the report to help readers who haven't had the opportunity to visit
Bristol Bay to have a sense of what the industry looks like. Except where otherwise noted,
pictures in the report were taken by Gunnar Knapp.
3.2 Overview of the Bristol Bay Salmon Industry

The Bristol Bay salmon fishery is one of the world's largest and most valuable wild salmon
fisheries. Between 2006 and 2010, the Bristol Bay salmon industry averaged:

• Annual harvests of 31 million salmon (including 29 million sockeye salmon)
• 51% of world sockeye salmon harvests
• Annual "ex-vessel" value (the value earned by fishermen) of $129 million
• Annual first wholesale value after processing of $268 million.
• 26% of the "ex-vessel" value to fishermen of the entire Alaska salmon harvest.
• Seasonal employment of more than 6800 fishermen and 3700 processing workers.

Bristol Bay is located in southwestern Alaska. Each year tens of millions of sockeye salmon
return to the major river systems which flow into Bristol Bay, of which the most significant (in
numbers of returning salmon) are the Nushagak, Kvichak, Naknek and Egegik Rivers. Sockeye
salmon spend a year or more in freshwater lakes before migrating to saltwater. The large lakes
of the Bristol Bay region provide habitat for sockeye salmon during this life stage.
with the Bristol Bay fishing industry remember what fish and permit prices actually were in any
given year: it is harder for them to recognize and believe prices or values converted to real
dollars.

52
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1
Egegik
Figure 10. Major Bristol Bay River Systems
Map source: www.purebristolbay.com/images/layout/BBNC_Base_Map-800.jpg
Almost all Bristol Bay commercial fish harvests occur during a brief four-week season from
mid-June to mid-July. At the peak of the season, millions of salmon may be harvested in a single
day.
The Naknek River near King Salmon
53
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Two kinds of fishing gear are used in the Bristol Bay fishery: drift gillnets (operated from
fishing boats) and set gillnets (operated from shore). Drift gillnets account for most of the total
catch. Technically, the drift gillnet fishery and the set gillnet fishery are managed as separate
fisheries.

Both the drift gillnet fishery and the set gillnet fishery are managed under a "limited entry"
management system which was implemented for all of Alaska's twenty-seven salmon fisheries in
the mid-1970s. The basic purpose of the limited entry system is to limit the number of boats
fishing in each fishery, which makes it easier for managers to control the total fishing effort and
makes the fishery more profitable for participants than it would be if entry (participation) were
unrestricted and more boats could fish. Every drift gillnet fishing boat or set net operation must
have a permit holder on board or present—so the number of boats or set net operations cannot
exceed the number of permit holders. There are approximately 1860 drift gillnet permits and
approximately 1000 set net permits. Section 3.7 below (Bristol Bay Salmon Fishermen)
provides more details about the limited entry system and Bristol Bay management regulations.
Drift Gillnet Boats Fishing in the Naknek River
The Bristol Bay salmon harvest is processed by about 10 large processing companies and 20
smaller companies employing about 3700 processing workers at the peak of the season in both
land-based and floating processing operations. Most of the land-based processors operate only
during the short summer salmon season. Most of the workers are flown in from outside the
region; and live in bunkhouse facilities at the processing plants.
54
-------
The Ekuk Processing Plant in the Nushagak District near Dillingham, photographed at low tide. Extreme tides
complicate logistics for land processing facilities in Bristol Bay. At many plants, fish can be delivered only when
the tide is in.
Most Bristol Bay salmon is processed into either frozen headed and gutted salmon or canned
salmon. Formerly almost all Bristol Bay frozen salmon was exported to Japan. In recent years
exports to Japan have declined sharply while shipments to the U.S. domestic market have
increased and exports have increased to Europe and to China (for reprocessing into fillets sold in
Europe, Japan and the United States). Most canned salmon is exported, primarily to the United
Kingdom, Canada and other markets.
Fish on a Bristol Bay fishing boat
Photograph by Gabe Dunham
Bristol Bay salmon catches vary widely from year
to year and over longer periods of time. Catches
set all-time records in the early 1990s, fell sharply
after 1995, and then rose again after 2002. The
2011 catch was about 25% lower than the average
for the previous five years.

Wholesale prices for Bristol Bay salmon products
and "ex-vessel" prices paid to fishermen increased
during the 1980s, peaked in 1988, and then
declined dramatically during the 1990s. The main
cause of the decline in prices was competition in
world markets from dramatically increasing world
production of farmed salmon, although many
other factors also contributed. Since 2001,
wholesale and ex-vessel prices have been
increasing, as the growth of farmed salmon
production has slowed and new markets for
Bristol Bay sockeye salmon have been developed.

The decline in catches and prices during the 1990s
led to a drastic decline in value in the Bristol Bay
55
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salmon fishery. The ex-vessel value paid to fishermen fell from a peak of $214 million in 1990
to just $32 million in 2002. The loss in value led to a severe economic crisis in the Bristol Bay
salmon industry. Many land-based salmon processing operations closed and many floating
processors left Bristol Bay. Many fishing permit holders stopped fishing, and permit prices fell
drastically.

As catches and prices have improved since 2002, the Bristol Bay salmon industry has
experienced a significant economic recovery. The ex-vessel value paid to fishermen increased
to $149 million in 2010. Participation in the fishery has increased and permit prices have
strengthened. Among both fishermen and processors there is a renewed sense of optimism about
the economic future of the Bristol Bay salmon industry, taking advantage of growing world
demand for wild salmon. This optimism is tempered by recognition of the variability of harvests
and value associated with fluctuations in salmon returns and markets.
•rocessor, and freighter anchored in the Nushagak district
Photograph by Gabe Dunham
A Bristol Bay processing worker holding a sockeye salmon
Photograph by Gabe Dunham
-------
3.3 Bristol Bay Salmon Harvests

Although all five species of Pacific salmon are caught in Bristol Bay, commercial salmon
harvests are overwhelmingly sockeye salmon. Between 2001 and 2010, sockeye accounted for
94% of total Bristol Bay salmon catches. Except where otherwise noted, references in this report
to harvests, production, prices, etc. are specifically for Bristol Bay sockeye salmon.

Between 1975 and 2010, annual Bristol Bay commercial sockeye salmon harvests ranged from 5
million to 44 million fish, with an annual average of 22.5 million fish. Harvests increased from
depressed levels of less than 6 million fish in the mid-1970s to more than 15 million fish for
most of the 1980s and more than 25 million fish annually for the years 1989-1996. Sockeye
salmon harvests peaked at 44 million fish in 1995. Harvests then fell off sharply to lows of 10
million fish in 1998 and 2002 before rebounding to 29 million fish in 2007 and 31 million fish in
2009—the highest sockeye harvest since 1995. The 2011 harvest of 22 million fish was
significantly lower than the previous five years and the lowest since 2003.
Bristol Bay Commercial Salmon Harvests
^n
4R _
An
QR _
"S ^n
i^
M—
o
in 9R
C
0
r= on
E 20
m -
in
5 -
n

ml
in r-~ o> T-
r-~ r-~ r-~ oo
o> o> o> o>

ro in r^ o> T-
oo oo oo oo o>
o> o> o> o> o>

ro in r^ o>
o> o> o> o>
o> o> o> o>
Source: Commercial Fisheries Entry Commission; Alaska

D Other
Species
• Sockeye

T- ro in r^ 05 T-
0 0 0 0 0 T-
000000
CM CM CM CM CM CM
Department of Fish and Game
Figure 11. Bristol Bay Commercial Salmon Harvests.
57
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The average weight of a Bristol Bay sockeye salmon is typically about 6 pounds. Between 1975
and 2010 average weights varied from as low as 5.3 pounds to as high as 6.7 pounds. . There
was no significant trend in average fish weight over this period. Fish weight tended to be
slightly lower in years when more fish were harvested.9

Bristol Bay sockeye salmon harvests may be expressed either in fish, pounds, or metric tons.
Over the period 1975-2010, sockeye salmon harvests averaged:
22.7 million sockeye
133 million pounds
60,200 metric tons
@ average weight of 5.9 pounds per fish)
@ 2204.6 pounds per metric ton)
For commercial fishery management purposes, Bristol Bay is divided into five different fishing
districts: Naknek-Kvichak, Egegik, Nushagak, Ugashik, and Togiak, which correspond to
different major Bristol Bay river systems.
(1 ~
Numbers in boxes are average annual
harvests for each district in millions of
fish for the years 1991-2010
S9WN-
Naknek-Kvichak
57-0 C-N-
Figure 12. Bristol Bay Fishing Districts. Source: ADFG map posted at:
www. adfg. alaska.gov/index. cfm ?adfg=CommercialByFisherySalmon. salmonmaps_districts_bristolbay
The correlation between fish weight and the number of fish harvested was -.433, which is statistically significant at
the 1% level in a one-tailed t-test (N = 36).
58
-------
Annual harvests within each district vary widely from year to year, as does the relative share of
each district in the total catch. Most of the record Bristol Bay catches of the mid-1990s were
caught in the Naknek-Kvichak and Egegik districts. Similarly, most of the decline in catches
after the mid-1990s resulted from a decline in catches in these two districts—particularly the
Naknek-Kvichak. Most of the recovery in catches since 2002 has also occurred in these two
districts, as well as in the Nushagak district, where catches have been very strong.
Bristol Bay Commercial Sockeye Salmon Harvests, by District
•Naknek-
Kvichak

Egegik
~0~Ugashik
OOOOOOOOOOT-T-
000000000000
CNCNCNCNCNCNCNCNCNCNCNCN
Source: ADFG
Figure 13. Bristol Bay Commercial Sockeye Salmon Harvests, by District.
59
-------
Currently, there is particular interest in the fisheries resources and economic significance of the
Nushagak and Kvichak watersheds because of potential future resource development in these
watersheds, Given the wide variation in catches by district from year to year and over longer
time periods of time, there no obvious way to characterize the relative share of the Bristol Bay
commercial salmon fishery attributable to these river systems or to the rivers, streams and lakes
that make up each river system.

In general, over most of the past decade, the Nushagak and Naknek-Kvichak districts have
accounted for about 60% of the total Bristol Bay commercial sockeye harvest (Figure 14).
Share of Bristol Bay Commercial Sockeye Salmon Harvest, by District
100% -n-r -T
80%
60% -
40% -
20% -
IIIIIIIITogiak

SUgashik

li Egegik

0Nushagak
I Naknek-
Kvichak
cor^oocj)OT-r\iro'5]-incDr^oocj)OT-r\iro'5]-incDr^oocj)OT-
ooooooooa>a>a>a>a>a>a>a>a>a>oooooooooc>T-T-
a>a>a>a>a>a>a>a>a>a>a>a>a>a>oooooooooooo
T-T-T-T-T-T-T-T-T-T-T-T-T-T-CNCNCNCNCNCNCNCNCNCNCNCN
Source: ADFG
Figure 14. Share of Bristol Bay Commercial Sockeye Salmon Harvest, by District.
Note however that both districts include other major rivers beside the Nushagak and Kvijak
rivers. For example, the Kvichak River generally accounts for less than half of Naknek-Kvichak
district harvests (Figure 15).
60
-------
Naknek-Kwijak District Sockeye Salmon Harvests, by River of Origin
INaknek
River
Branch River
IKvichak
River
Source: ADFG
Figure 15. Naknek-Kvichak District Sockeye Salmon Harvests, by River of Origin.
As discussed more below, economic measures of the Bristol Bay commercial fishery are not
necessarily proportional to fish harvests. If total fish harvests were to change by a given
percentage, the value of the fishery, employment, and other measures would not change by the
same percentage amount.

Bristol Bay Gear Types

All Bristol Bay salmon are harvested using gillnets. Gillnets hang in the water perpendicular to
the direction in which returning salmon are swimming. The fish get their heads stuck in the nets
and are "picked" from the net as it is pulled from the water.

There are two types of gillnet fishing operations in Bristol Bay: drift gillnets and set gillnets.
Drift gillnets hang in the water behind the fishing boat. After a period of time, the nets are
pulled back into the boat for picking.
61
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Gillnetters catch salmon by setting curtain-like nets
perpendicular to the direction in which the fish are traveling
as they migrate along the coast toward their natal streams.
The net has afloat line on the top and a weighted lead line
on the bottom. The mesh openings are designed to be just
large enough to allow the . . . fish to get their heads stuck
("gilled") in the mesh. . . . Net retrieval is by hydraulic
power which turns the drum. Fish are removed from the net
by hand "picking" them from the mesh as the net is reeled
onboard.
Gillnetter.
Source: Alaska Department of Fish and
Game, "What kind of fishing boat is that? "
www. cf.adfg. state, ak. us/geninfo/pubs/fv_n_a
k/fv_aklpg.pdf.
Picking salmon from the net on a Bristol Bay drift gillnet boat
Bristol Bay fishing boats stored in a Naknek boatyard
for the winter
Most Bristol Bay drift gillnet fishing boats
are used only during the short, intense
summer salmon season (although some are
used to fish for herring in the spring) and are
stored in boat yards for the rest of the year.
The fact that fishing boats and processing
plants are idle for much of the year adds to
costs in the fishery.
62
-------
Crowded fishing near the boundary of a Bristol
' district
Photograph by Bart Eaton
Drift gillnet fishermen have the advantage of
being able to move to where the fishing is best—
and the disadvantage that other fishermen are
likely to want to fish in the same places. Bristol
Bay drift gillnet fishing boats are often crowded
along the "lines" which are the boundaries of
legal fishing districts, established by GPS
coordinates. Often fishing is best when fishermen
are able to place their nets along the line, catching
fish as they swim into the district.

Bristol Bay drift gillnet fishing boats are limited
to 32 feet in length. Over time, wider and taller
boats have been built as fishermen try to get more
working space and hold capacity.
Drift gillnet boats waiting for an opening in the Nushagak district
~ --' '
Photograph by Gabe Dunham
63
-------
In set gillnet fishing, one end of the net is attached to the shore, while the other is attached to an
anchor in the water. Fishermen pick the fish from a skiff or from the beach at low tide.
A set-net fishing operation on the Nushagak River
There are more drift gillnet permits
fished than set gillnet permits, and
average catches are higher for drift
gillnet permits than for set gillnet
permits. As a result, drift gillnet
permits account for about four-fifths of
the Bristol Bay sockeye salmon catch.
Table 27. Comparison of Bristol Bay Drift Gillnet and Set Gillnet Fisheries (2006-10
Average)
Comparison of Bristol Bay Drift Gillnet and Set Gillnet Fisheries (2006-10 Averages)

Total Permits Fished
Average Pounds
Total Pounds

Drift
Gillnet
1,470
102,109
150,053

Set
Gillnet
847
37,575
31,813

Total
2,317
139,684
181,866
Ratio,
Drift Gillnet
to Set Gillnet
1.7
2.7
4/7

Drift
Gillnet %
63%

83%

Set
Gillnet %
37%

17%
Source: Commercial Fisheries Entry Commission, Basic Information Tables.
64
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Bristol Bay Salmon Harvests, by Fishery
250
h-h-h-OOOOOOOOOOCDCDCDCDCDOOOOO
Source: CFEC Basic Information Tables
Figure 16. Bristol Bay Salmon Harvests, by Fishery
Relative Scale of Bristol Bay Sockeye Salmon Harvests

There are several ways to measure the relative scale of Bristol Bay sockeye salmon harvests in
comparison with other sources of supply, which are illustrated by the three graphs below:

Sockeye salmon fisheries. Bristol Bay is by far the largest sockeye salmon fishery in the world.
Between 1980 and 2009 Bristol Bay averaged 59% of total Alaska sockeye salmon supply and
44% of total world sockeye salmon supply.
65
-------
World Sockeye Salmon Supply
250,000
Uapan

I Lower 48

Canada

Russia

I Other
Alaska

I Bristol
Bay
OCNl'vJ-CDOOOCNl'vJ-CDOOOCNl'vJ-CDOO
oooooooooocncncncncnooooo
(J>(J>(J>O)O)O)O)O)OOOOO
•f-t-t-t-t-t-t-t-t-t-CNCNCNCNCN

Source: ADF&G, NMFS, FAO
Figure 17. World Sockeye Supply
Alaska salmon fisheries. In most years, Bristol Bay sockeye is the single largest fishery in

Alaska. Between 1980 and 2009, Bristol Bay sockeye salmon averaged 20% of Alaska salmon

supply for all species combined.
66
-------
Alaska Salmon Supply
500 -T
450

400 -i
U)
§ 350 n
^— »
£ 300
E 250
° 200
T3
S 150
CD ' ow
W
g 100
50
n

O C\l ^~

CD CO O CM -^- CD CO

O CM <* CD CO
000000000000^0^0^0^00000
O^ O^ O} O} O} O} O} O} O} O} ^D ^D ^D ^D ^D
• Total Alaska
coho &
chinook

• Total Alaska
chum

• Total Alaska
pink

• Other Alaska
sockeye

• Bristol Bay
sockeye

Source: ADF&G, FAO, NMFS
Figure 18. Alaska Salmon Supply
World salmon supply. World farmed salmon and trout production has grown extremely rapidly
since the early 1980s. As farmed salmon and trout production increased, Bristol Bay's share of
total world salmon supply fell from 11% in 1980 to just 3% in 2009.
Mending gillnets at the historic Peter Pan processing plant in Dillingham
67
-------
World Salmon and Trout Supply
„ ___

3,000

2cnn

C
Q
9 nnn

0)
^ 1 'snn -
T3
C
<5 1 nnn
0
500

Note: "Other wild

salmon" includes
Lower 48, Canada,
Russia R Japan

OCN-3-COOOOCN-3-CO

00 O CM -fr

CD 00

• Farmed trout

• Farmed
salmon

• Other wild
salmon

• Other
Alaska
salmon
• Bristol Bay
wild salmon

oooooooooorororororoooooo
O5O5O5O5O5O5O5O5O5O5OOOOO
Source: ADF&G, FAO, NMFS
Figure 19. World Salmon and Trout Supply
Future Bristol Bay Salmon Harvests

It is very difficult to predict how Bristol Bay salmon harvests may change in the future. Every
year the Alaska Department of Fish and Game, as well as the University of Washington Fisheries
Research Institute (FRI) make pre-season projections of how many salmon will return to Bristol
Bay and what the harvest will be. The projections are based on estimates for previous years of
escapements, the number of juvenile salmon entering saltwater, and the numbers of adult salmon
of different age classes which returned.

The pre-season projections provide at best a rough guide to what actual harvests will be.
Between 1990 and 2011, actual catches ranged from 51% below the Alaska Department of Fish
and Game's projections to 128% over the projections, with an average annual projection error of
31%.
68
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Bristol Bay Sockeye Salmon Preseason Projection and Actual Commercial Catch
o 25,000
a 20,000
in
Source: ADF&G
Figure 20. Bristol Bay Sockeye Preseason Projection and Actual Commercial Catch
There are no formal projections of how Bristol Bay salmon harvests may change over the longer
term future. As shown by the graph on the following page, historically harvests have varied
widely from decade to decade. Analysis of lake-bed sediments has also shown significant
historical variation in salmon returns in previous centuries prior to commercial harvesting.

Long-term changes in salmon returns have been shown to be associated with periodic changes in
ocean conditions such as water temperature and currents, known as "regime shifts." The much
lower average harvests from the 1950s through the 1970s are thought to have resulted in part
from a different ocean regime (although other factors, such as interceptions of Bristol Bay
salmon by foreign fishing fleets, likely also played a role).

The potential for significant future changes in ocean conditions associated with not only regime
shifts but also global climate change could significantly affect future Bristol Bay salmon returns
and harvests—but it is very difficult to predict what changes might occur or when they might
occur.
69
-------
Bristol Bay Sockeye Salmon Harvests, 1895-2009
.,000
Note: The black line
shows the average
annual catch for the
preceding 10-years.
tn
•fl
! 15,000
o
.c
10,000

5,000

0
LOOLOOLOOLOOLOOLOOl^)OLOOLOOLOOLOOLOO

OOO5O5O5O5O5O5O5O5O5O5O5O5O5O5O5O5O5O5O5O5OOO
Source: ADF&G
Figure 21. Bristol Bay Salmon Harvests, 1985-2009
Until the 1950s, only sailboats were allowed to harvest salmon in Bristol Bay
4 •'•SSi-^s
* *^va*s|
Source: "Sailing for Salmon " exhibition of historic Bristol Bay photographs
at Anchorage Museum, summer 2011 (http://www.anchoragemuseum.org)
70
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3.4 Bristol Bay Salmon Products and Markets

The major products produced from Bristol Bay sockeye salmon are canned salmon, frozen
headed and gutted (H&G) salmon, frozen salmon fillets, fresh H&G salmon, and salmon roe.
Frozen H&G salmon and canned salmon account for most of the product volume.
Bristol Bay canned salmon
Headed and gutted salmon on trays for freezin
Bristol Bay sockeye salmon fillet
Processing Bristol Bay sockeye salmon roe
For most of the more than one-hundred year history of the Bristol Bay salmon fishery,
production was overwhelmingly canned salmon. Processing plants were called "canneries" and
processing companies were called "canners."

However, in the 1970s frozen salmon production increased rapidly, as technologies for freezing
salmon and shipping frozen salmon developed, and as Japanese demand for frozen Bristol Bay
salmon expanded with the end of Japanese salmon fishing in international waters and within the
U.S. 200-mile limit. By the mid-1980s, more than 80% of Bristol Bay salmon production was
71
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frozen, almost entirely for export to Japan. The shares of different product forms in Bristol Bay
production over time reflect changes in changes in relative prices and total harvests. From the
mid-1990s to the mid-2000s, as frozen sockeye salmon prices fell due to increased competition
in the Japanese market from farmed salmon, and as harvest volumes fell, the frozen share of
production declined and the canned share increased. Since the mid-2000s, as frozen sockeye and
harvest volumes have increased, the frozen share of production has risen (Figure 22 and Figure
23).
Bristol Bay Sockeye Salmon Production
180
0.0
Source: ADFG Commercial Operator Annual Report database
Figure 22. Bristol Bay Sockeye Salmon Production
100% -
80% -
60% -

40% -
20% -
0% -
Share of Sockeye Salmon Production in Bristol Bay

1 1

I | 1 1 | I I

CM CM CM

CO O
CM CM

• Roe
Fresh
• Canned
• Frozen

Source: ADFG, COAR
Figure 23. Share of Sockeye Salmon Production in Bristol Bay

72
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Table 28 provides more detail about product forms for canned and frozen Bristol Bay salmon in
recent years. In 2010, about one-third of canned salmon production was "tails" (14.75 ounce
cans) and about two-thirds "halves" (7.5 ounce cans). Between 2006 and 2010, the share of
frozen fillets in total frozen production increased from about 6% to about 18%.
Table 28. Sales of Selected Sockeye Salmon Products.

Sales of Selected Sockeye Salmon Products
by Major Bristol Bay Salmon Processors (pounds)
Type
Canned
Frozen
Fresh
Roe
Form
Canned Halves
Canned Tails
Frozen Fillet
Frozen H&G
Fresh H&G
Roe
2006
23,349,893
*
3,939,220
61,270,959
2,958,201
2,902,082
2008
23,672,655
*
7,930,710
53,590,871
1,904,051
3,186,876
2010
23,486,265
10,592,344
13,788,359
63,720,557
*
3,657,859
* Not reported due to confidentiality restrictions
Note: Includes only sales reported by processors with more than 1 million pounds of sales of
salmon products in the previous year.
Source: Alaska Department of Revenue, Annual Salmon Price Reports
In any given year, the total volume of Bristol Bay salmon products is less than the annual harvest
volume, because part of the weight (25%-35%) is lost in processing as the fish heads and guts are
removed, and also because some fish are shipped to plants outside the Bristol Bay region for
processing. Between 1984 and 2010, the reported volume of processed salmon products sold by
Bristol Bay salmon processors, or production, averaged 67% of the volume of harvests, and
ranged from as low as 59% to as high as 75%. The annual variation in the ratio of production
weight to harvest weight results from several factors including changes in average fish size,
changes in the mix of products produced, and changes in the share of the catch shipped outside
the region for processing.
73
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Bristol Bay Sockeye Salmon Harvests and Production
300.0
250.0
0.0
-3-COOOOCN-3-COOOOCN-3-COOOO
O5O5O5O5O5O5O5O5OOOOOO
Source: CFEC, ADFG
Figure 24. Bristol Bay Sockeye Salmon Harvests and Production
74
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Monthly Sales Volume, Bristol Bay Frozen H&G Sockeye Salmon
20,000
5,000
May-08
May-09 May-10

Source: Alaska Department of Revenue Salmon Price Reports
May-11
Monthly Sales Volume, Bristo Bay Sockeye Sa

a.
T3

*
ft
vw ^

J
V

A
LA-v
w*
mon Fillets, Fresh & H&G and Roe
t

/
( Y\
\ Y V

-^^Frozen and
Fresh
Fillets
-O- Fresh H&G
— *— Roe

May-08 May-09 May-10 May-11
Source: Alaska Department of Revenue Salmon Price Reports
Monthly Sales Volume, Bristol Bay Canned Salmon
-Canned
Halves
-Canned
Tails
ay-08 May-09 May-10 May-11

Source: Alaska Department of Revenue Salmon Price Reports
Figure 25. Monthly Sales Volume of Bristol Bay Salmon Products
75
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The timing of processors' sales of Bristol Bay salmon reflects the highly seasonal character of
the industry. Sales of products for which storage costs are relatively high—including frozen
H&G salmon, frozen and fresh fillets, fresh H&G and roe—are concentrated in the summer in
the months during and immediately after the season. Sales of canned salmon are distributed
more evenly over the year. For some products, no data are available for sales for some months
(to preserve confidentiality, sales are only reported if at least three processors report sales).

Bristol Bay Salmon Markets

Data are not available on the end-markets to which Bristol Bay sockeye salmon products are
shipped. However, because Bristol Bay represents such a large share of Alaska and United
States sockeye salmon production, we can make reasonable inferences about end markets for
Bristol Bay sockeye salmon by comparing U.S. export data with Alaska statewide production
data.

Prior to about 1998, almost all U.S. frozen sockeye salmon production (including Bristol Bay
production) was exported, and almost all exports were to Japan. Beginning in about 1999, this
pattern changed in two important ways. First, exports declined relative to production—
indicating that significant volumes of Alaska frozen sockeye were beginning to be sold in the
U.S. market rather than exported. Secondly, significant volumes of frozen sockeye began to be
exported to countries other than Japan—particularly EU countries and China—substantially
reducing the Japanese share of U.S. sockeye salmon exports (Figure 26).

These two trends together resulted in a dramatic decline in the volume of Alaska sockeye salmon
shipped to Japan—from more than 100,000 metric tons in 1993 to 20,000 Ibs or less since
2006—and a corresponding dramatic decline in the dependence of Alaska (and Bristol Bay)
sockeye on the Japanese frozen salmon market.
76
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Alaska Frozen Sockeye Production & U.S. Frozen Sockeye Exports
120,000
Sources: ADFG COAR database; NMFS trade data
Note: Export data
are for the period
May of the
production year to
April of the
following year.
Figure 26. Alaska Frozen Sockeye Production and U.S. Frozen Sockeye Exports.
77
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The volume of Alaska frozen sockeye salmon sold to U.S. domestic markets may be estimated as
total production minus exports. This in turn allows estimation of the end-market shares of the
United States and export markets. End-market shares have changed dramatically from the early
1990s, when almost all production was estimated to Japan. Between 2006 and 2010, 27-39% of
production was exported to Japan, 20-31% was sold in the United States, 10-21% was exported
to China, 11-16% was exported to the European Union, and 7-13% was exported to other
countries.
Estimated End-Markets for Alaska Frozen Sockeye Salmon (%
100%
80% -
60% -
40% -
20% -
0%
Note: USA
estimated as
Alaska
production
minus exports.
o>
oo
o>
T- CO
O> O>
O> O)
LO h-
O) O)
O) O)
O)
O)
O)
O
O
CM
CO
O
O
CM
LO
O
O
CM
h-
O
O
CM
O)
O
O
CM
Figure 27. Estimated End-Markets for Alaska Frozen Sockeye Salmon
Note that most of the frozen sockeye exported to China are not consumed in China. Rather, they
are thawed and reprocessed—using much cheaper Chinese labor—into fillet and other value-
added products which are then re-exported to end-markets in Europe, the United States and
Japan. Thus the final end-market shares for Europe, the United States and Japan are larger than
are shown in the graph (but data are not available to indicate how much larger.)
78
-------
Boxes of frozen Bristol Bay sockeye in the cold storage
of a Chinese reprocessing plant, 2007
Most Alaska canned sockeye—including Bristol Bay canned sockeye—is exported. Total
reported U.S. exports are approximately equal to total Alaska production (Figure 28).10
Historically the United Kingdom was by far the most important market for canned sockeye.
recent years, exports of canned sockeye to Canada have grown dramatically—from which
significant volumes are likely re-exported to the UK and other markets.
In
Alaska Canned Sockeye Production & U.S. Canned Sockeye Exports
30,000
25,000
So o o
o o o
CM CM CM CM
Sources: ADFG COAR database; NMFS trade data
All other
exports
Exports to
Australia
Exports to
Canada
I Exports to
UK
-Alaska
canned
production
Wofe: Export data
are for the period
May of the
production year to
April of the
following year.
Figure 28. Alaska Canned Sockeye Production and U.S. Canned Sockeye Exports
10 In some years reported US exports of canned sockeye salmon exceed reported Alaska production. The reasons for
this are not entirely clear. One likely contributing factor is that in years of large sockeye production, significant
volumes may be kept in inventory and sold during a later year.
79
-------
Relatively small volumes of fresh salmon are produced in Bristol Bay. It is difficult for Bristol
Bay to compete with other areas of Alaska in supplying fresh markets because of the greater
distance and cost required to transport fish to the United States market.

Salmon roe accounts for a relatively small share of total Bristol Bay product volume—typically
less than 3%-but accounts for a higher share of product value because it commands a higher
price per pound than other product forms. Most Bristol Bay sockeye salmon roe is exported as
sujiko (roe in whole skeins) to Japan.
3.5 Bristol Bay Salmon Prices
Between the late 1980s and 2001, Bristol Bay fishermen and processors experienced a dramatic
decline in prices paid for Bristol Bay salmon. The "ex-vessel price" paid to fishermen fell from
a peak of $2.10/lb in 1988 to $.42/lb in 2001. After 2001 the ex-vessel price recovered gradually
to $.66/lb in 2006 and $.80/lb in 2009 and then rose sharply to $1.07/lb in 2010. Final data for
Bristol Bay ex-vessel prices in 2011 were not available when this report was prepared but were
expected to be similar to 2010.

In nominal terms 2010 ex-vessel prices were similar to prices for much of the 1990s. In "real"
prices adjusted for inflation they remained lower than any year except 1993.
Average Ex-Vessel Price of Bristol Bay Sockeye Salmon, 1975-2010
$3.50

$3.00

$2.50

$2.00

$1.50

$1.00

$0.50

$0.00
Real price
(adjusted for inflation,
expressed in 2010
dollars)
Nominal price
(not adjusted for inflation)
O5O5O5O5O5O5O5O5O5O5O5O5
i- co in r- CD
o o o o o
o o o o o
CM CM CM CM CM
Source: ADFG, Commercial Operator Annual Reports
Figure 29. Average Ex-Vessel Price of Bristol Bay Sockeye Salmon, 1975-2010
80
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Cannery at Clark's Point, Nushagak District
Photograph by Gabe Dunham
The decline in ex-vessel prices during the 1990s reflects a decline in first wholesale prices paid
to processors for both canned and frozen salmon. Similarly, the increase in ex-vessel prices after
2001 reflects in first wholesale prices for both canned and frozen salmon—particularly for frozen
salmon (Figure 30).
$6.00
$5.00
$0.00
Average Ex-Vessel and Wholesale Prices of Bristol Bay Sockeye Salmon
COCOCOG)G)G)G)G)OOO

T-T-T-T-T-T-T-T-CSICSICSI

Source: Alaska Department of Fish and Game
CD CO O
OOi-
000
(XI (SI (SI
•Frozen
wholesale
price

•Canned
wholesale
price

•Ex-vessel
price
Figure 30. Average Wholesale and Ex-Vessel Prices of Bristol Bay Sockeye Salmon

81
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A loaded Bristol Bay gillnetter
Photograph by Gabe Dunham
Monthly wholesale price data, available for years since 2001, provide more detail about
wholesale price trends. Wholesale prices may fluctuate widely over the course of a year due to
changes in supply and other market factors.

Wholesale prices for frozen headed and gutted (H&G) salmon increased from about $1.75/lb in
2001 to about $3.00/lb in early 2011. Wholesale prices for canned salmon halves increased from
an average of about $2.50/lb in 2001 to about $3.50/lb in early 2011. Wholesale prices for
canned salmon tails fell from an average of about $2.30/lb in 2001 to about $2.10/lb in 2005
before increasing to $3.30/lb in early 2011.
82
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Average Monthly First Wholesale Prices,
Bristol Bay Canned and Frozen H&G Sockeye Salmon
$4
-Canned
Halves
-Canned
Tails
•Frozen H&G
$0.00
May- May- May- May- May- May- May- May- May- May- May- May-
01 02 03 04 05 06 07 08 09 10 11 12
Source: Alaska Department of Revenue Salmon Price Reports
Figure 31. Average Monthly First Wholesale Prices.
In general, wholesale prices paid to processors for canned Bristol Bay sockeye salmon are
similar to wholesale prices for canned sockeye salmon from other regions of Alaska. In contrast,
wholesale prices paid to processors for frozen Bristol Bay sockeye salmon are typically lower
than wholesale prices for frozen sockeye salmon from other regions of Alaska (Figure 32). This
may reflect differences in product mix and/or differences in the perceived quality of Bristol Bay
frozen sockeye compared with frozen sockeye from other parts of Alaska.

In turn, Bristol Bay ex-vessel price for sockeye salmon are typically lower than ex-vessel prices
for sockeye salmon in southcentral and southeast Alaska (Figure 33). This may reflect the fact
that processors receive lower wholesale prices for frozen sockeye, as well as the fact that
processors face higher operating costs in Bristol Bay than in less remote regions of southcentral
and southeast Alaska, as well as generally higher costs for transporting products to market.
83
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.Q

5}
$6.00
$5.00
$4.00
$3.00
$2.00
$1.00 -
$0.00
Average Wholesale and Ex-Vessel Prices of Sockeye Salmon:
Bristol Bay and the Rest of Alaska
^r CD oo o CM ^r
oo oo oo o> o> o>
O5O5O5O5O5O5O5O5
--Q--Rest-of-Alaska
canned
wholesale

-•—Bristol Bay
canned
wholesale

••A--Rest-of-Alaska
frozen
wholesale

-A— Bristol Bay
frozen
wholesale

•* -Rest of Alaska
ex-vessel
•Bristol Bay ex-
vessel
Source: Alaska Department of Fish and Game
Figure 32. Average Wholesale and Ex-Vessel Prices, Bristol Bay and Rest of Alaska
Average Ex-Vessel Prices of Sockeye Salmon, Selected Alaska Areas
$2.50
$2.00
$1.50
.Q
Si $1.00
$0.50 -
$0.00
Prince
William
Sound

-Southeast
-Cook Inlet
•Kodiak
•Bristol Bay
CD r^ oo o
O) O) O) O)
O) O) O) O)
ot-r\ico^rLocDi^ooa>o
OOOOOOOOOOt-
ooooooooooo
C\IC\IC\IC\IC\IC\IC\IC\IC\IC\IC\I
Source: ADFG, 1984-2010 Salmon Exvessel Pice Time Series by Species
Figure 33. Average Ex-Vessel Prices of Sockeye Salmon, Selected Alaska Areas.

84
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Factors Affecting Bristol Bay Salmon Prices

Changes in Bristol Bay salmon prices over the past three decades reflect dramatic changes in
world salmon markets over this period. The most important change was a dramatic increase in
world salmon supply resulting from rapid growth in farmed salmon production, mostly in
Norway, Chile, the United Kingdom and Canada.

In particular, during the 1990s, Japan—where the market for "red-fleshed salmon has previously
been dominated by Alaska sockeye—began to import large volumes of farmed coho salmon
from Chile and farmed trout from Chile and Norway. This, together with lower Bristol Bay
salmon harvests, led to a dramatic decline in the share of Bristol Bay sockeye salmon in its most
important market.
Japanese "Red-Fleshed" Salmon Imports, May-April
250,000
I Frozen trout
fillets
00 Frozen trout
(excl. fillets)
I Frozen coho
I Frozen sockeye
ro
o
ooo
CM CM CM
Figure 34. Japanese Red-Fleshed Salmon Imports, May-April

The effects of growing supply were compounded by an economic recession in Japan, changes in
the Japanese fish distribution system which increased the market power of retailers, and long-
term changes in Japanese food consumption patterns. The combined result was a sharp decline
in Japanese wholesale prices paid for Bristol Bay sockeye salmon as well as farmed salmon
(Figure 35). This in turn was reflected in a sharp decline in prices paid to Alaska processors and
fishermen (Figure 36).
85
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Bristol Bay headed and suited sockeye salmon
Japanese "Red-Fleshed" Frozen Salmon Imports & Wild Sockeye Wholesale Price
250,000
Sockeye wholesale price
& trout imports
OOOOOOO)O)O)O)O)O)O)O)O)O)OOOOOO
oooooooocncncncncncncncncncnooooo
Figure 35. Japanese Red-Fleshed Frozen Salmon Imports & Wild Sockeye Wholesale Price
86
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Japanese Wholesale Prices and Bristol Bay Prices for Sockeye Salmon
$6.00
$5.00
$1.00
$0.00
•August
Japanese
wholesale
price, Bristol
Bay frozen
sockeye

•Average first
wholesale
price, Bristol
Bay frozen
sockeye
•Average
Bristol Bay ex-
vessel price
oo oo oo oo
88S8888S88?
O5O5O5O5O5O5O5O5O5O5OOOOOO
CM CM CM CM CM CM
Figure 36. Japanese Wholesale Prices and Bristol Bay Prices for Sockeye Salmon
Just as multiple factors contributed to the fall in Bristol Bay salmon prices during the 1990s,
multiple factors contributed to the recovery in prices after 2001. Probably the most important
factors was a strong recovery in world market prices for farmed salmon, driven by rapidly rising
world demand and a slowing of the growth in world salmon production (Figure III-9),
exacerbated by major disease problems in the Chilean salmon industry which greatly reduced
Chilean production. Prices of farmed Atlantic salmon in particular rose dramatically from 2002
through 2010 (Figure 37 and Figure 38).
87
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Average United States Import Prices of Selected Farmed Salmon Products$/lb)
$7.00
$6.00
$5.00
$4.00
$3.00
$2.00
$1.00
$0.00
-US average import
price, Canadian fresh
Atlantic fillets
-US average import
price, Chilean fresh
Atlantic fillets
-US average import
price,Chilean frozen
Atlantic fillets
Source: NMFS
Figure 37. Average United States Import Prices of Selected Farmed Salmon Products
U.S. Wholesale Prices for Selected Wild and Farmed Salmon Products
reported in Urner Barry's Seafood Price Current
— Fresh farmed Atlantic, pinbone-out fillets

-^-Frozen H&G wild sockeye
Fresh farmed Atlantic, whole fish
$6.00
03030303030303030303030303030303030303030303
$0.00
Source: Urner Barry Publications, Inc., Seafood Price Current.
Figure 38. U.S. Wholesale Prices for Selected Wild and Farmed Salmon Products
88
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Other factors which contributed to the increase in prices for Bristol Bay sockeye salmon after
2001 include the strengthening of exchange rates between the yen and the dollar and between the
euro and the dollar, diversification of markets for frozen sockeye, and the development of new
product forms, particularly fillets.

Unlike frozen salmon markets, canned salmon markets have not been directly affected by
competition from farmed salmon—because relatively little farmed salmon is canned. However,
canned salmon markets are influenced by frozen market conditions—and thus indirectly by
farmed salmon. When frozen prices are high, processors tend to freeze relatively more salmon
and can relatively less, which reduces the supply of canned salmon, causing canned salmon
prices to rise. When frozen prices are low, processors tend to freeze relatively less salmon and
can relatively more, which increases the supply of canned salmon, causing canned salmon prices
to fall. Put differently, the ability of processors to shift between freezing and canning salmon
causes frozen and canned salmon prices to tend to move together.

This can be seen in the decline in the downward trend in canned salmon prices in the early
1990s, and the upward trend since the early 2000s (Figure 37). However, many other factors
affect canned salmon prices, including in particular wild salmon harvests, exchange rates
between the dollar and the UK pound, and changing demand patterns for canned salmon.
Monthly Average Wholesale Case Prices for Alaska Canned Sockeye Salmon
0)
en
ro
o
$250
$200
$150
$100
$50
•48 tails
•48
halves
OOOOOOOOOOO)O)O)O)O)O)O)O)O)O)OOOOOOOOOO^— ^~
Source: Alaska Department of Revenue salmon price reports. Data prior to August 2000 are
statewide average canned sockeye prices; later data are average prices for Bristol Bay canned
sockeye.
Figure 39. Monthly Average Wholesale Case Prices for Alaska Canned Sockeye Salmon.
89
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Future Bristol Bay Salmon Prices
Since the beginning of 2011 prices of farmed Atlantic salmon have fallen sharply, in response to
oversupply of world markets as Chilean production has recovered (Figure 37 and Figure 38,
above). Of great importance for the Bristol Bay salmon industry will be the extent to which
prices of Bristol sockeye salmon remain high, or alternatively follow the recent downward trend
in farmed salmon prices. At the time this report was written, it was too soon to tell how deep or
long the decline in farmed salmon prices may be, or how much it may affect sockeye salmon
markets.

More generally, the future outlook for Bristol Bay salmon prices is promising but uncertain.
There are several reasons for optimism, including growing demand for wild sockeye salmon in
the United States and Europe, the development of new higher-valued product forms (particularly
fillets), and improvements in the quality of Bristol Bay salmon (discussed below). However, the
Bristol Bay salmon industry will face challenges in taking advantage of these new market
opportunities. These include continued competition from farmed salmon and other new farmed
species, the logistical difficulties of market development given the wide variation in annual
Bristol Bay catches, high costs of transportation and labor, and highly concentrated seasonal
production which adds to costs and makes it difficult to slow down production and improve
quality. These factors make it relatively easier for other regions of Alaska than for Bristol Bay to
take advantage of growing market opportunities for wild sockeye salmon.

Bristol Bay Salmon Quality

In an increasingly competitive world seafood industry, quality is of increasing importance. An
important challenge for the Bristol Bay salmon industry has been a reputation for quality
problems. Many people in the industry believe these problems have historically kept wholesale
and ex-vessel prices lower than they would have been with better quality—although it is difficult
to quantify how important the effect of quality on prices has been.

Quality problems in the Bristol Bay fishery derive in part from handling practices such as those
depicted in these pictures posted on the internet. During the short, hectic and fast-paced Bristol
Bay season, fishermen have historically been focused on catching large volumes offish fast than
on handling fish carefully. (In the highly quality-conscious salmon farming industry, it would be
unthinkable to step on fish.)
Source:
90
-------
Source: http://bbda. org/Stern_Load06.jpg
www. adn. com/static/includes/highliner/cowboys.jpg
Quality problems in the Bristol Bay fishery have been compounded by the absence of ice or
chilling capacity on many fishing boats; the logistics of tendering salmon long distances from
fishing grounds to processors, which makes it more difficult to separate fish which have been
handled carefully from those which have not (and to pay quality-conscious fisherman a
corresponding price premium); and the difficulty of processing salmon soon after they are
caught, especially during peak fishing periods.

Improving quality has been a primary focus of the Bristol Bay Regional Seafood Development
Association (BBRSDA), u a fishermen's marketing association for the drift gillnet fishery
financed by permit holders by means of a 1% assessment on the ex-vessel value of landings
(harvests). BBRDSA has undertaken a number of projects focused on encouraging chilling
(through icing and/or refrigerated sea water) as well as improved handling practices. Annual
processor surveys funded by BBRDSA suggest that the share offish which are delivered chilling
is increasing (Figure V-12).12
Estimated Chilled and Unchilled Shares of Bristol Bay Salmon Harvests
^Unchilled
I Chilled
2008 2009 2010
Source: Northern Economics, 2010 Bristol Bay Processor Survey
Figure 40. Estimated Chilled and Un-chilled Shares of Bristol Bay Salmon Harvests
11 BBRSDA was established in 2005. Fishermen voted for the 1% assessment in 2006. Information about
BBRSDA may be found at www.bbrsda.com.
12 Northern Economics, 2010 Bristol Bay Processor Survey. Prepared for Bristol Bay Regional Seafood
Development Association, February 2011. http://www.bbrsda.com/layouts/bbrsda/files/documents/
bbrsda_reports/BB-RSDA%202010%20Survey%20Final%20Report.pdf
91
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Bristol Bay fishing, boats waiting, to unload to a tender
Photograph by Gabe Dunham
3.6 Bristol Bay Salmon Ex-Vessel and Wholesale Value

The decline in catches and prices during the 1990s led to a drastic decline in value in the Bristol
Bay salmon fishery. The nominal ex-vessel value paid to fishermen fell from a peak of $214
million in 1989 to just $32 million in 2002—a decline of 86%. The inflation-adjusted "real"
value (expressed in 2010 dollars) fell by an even greater 89% from a 1989 value of $359 million
to $39 million in 2002.
92
-------
700
600
Ex-Vessel and First Wholesale Value of Bristol Bay Sockeye Salmon
Harvests and Production, 1984-2010
CD OO O
O O T-
O O O
CM CM CM
-Real first
wholesale value
(2010$)
•Nominal first
wholesale value
-0- Real ex-vessel
value (2010$)
•Nominal ex-
vessel value
Source: CFEC, ADFG
Figure 41. Ex-Vessel and First Wholesale Value: 1984-2010

As catches and prices have improved after 2002, the Bristol Bay salmon industry experienced a
significant economic recovery. Ex-vessel value increased to $181 million in 2010. However,
this was well below the inflation-adjusted "real" value of the highest-value years of the late
1980s and early 1990s.

The first wholesale value of Bristol Bay salmon production exhibited similar trends over time as
ex-vessel value. The nominal first wholesale value fell from a peak of $351 million in 1992 to
$100 million in 2002. As catches and prices improved, nominal wholesale value rose to a record
$390 million in 2010. Adjusted for inflation, however, the 2010 first wholesale value remained
well below the 1989 peak real wholesale value of $616 million.

The decline in value of the Bristol Bay fishery during the 1990s and the rise in value after 2002
was experienced by both processors and fishermen. Like the ex-vessel value to fishermen, the
value retained by processors after deducting payments to fishermen (sometimes called the
processors' margin) fell dramatically during the 1990s and rose dramatically after 2002 (Figure
42).
93
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Distribution of Nominal Value of Bristol Bay Sockeye Salmon
400.0
350.0
Source: CFEC, ADFG
•Total first
wholesale
value
• Ex-vessel
value received
by fishermen
•Value to
processors
after
deducting
payments to
fishermen
Figure 42. Distribution of Nominal Value of Bristol Bay Sockeye Salmon
The share of first wholesale value received by fishermen fell from 83% in 1988 to 32% in 2002
and then rose to 46% in 2010 (Figure 43).
94
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100% -
80% -
60% -
40% -

20% -
0% -
Distribution of Value of Bristol Bay Sockeye Salmon

^-CDOOOCM^TCDOOOCM^TCD
XJCOCOOOOOOOOOO
35O5O5O5O5O5O5O5OOOO
Source: CFEC, ADFG

oo o
O T-
o o
CM CM

ESValue to
processors after
deducting
payments to
fishermen

• Ex-vessel value
received by
fishermen

Figure 43. Distribution of Value of Bristol Bay Sockeye Salmon

The relative share of wholesale value received by fishermen and processors has been a subject of
contention between fishermen and processors.13 During the 1990s, fishermen argued that they
had experienced a disproportionate and unfair share of the decline in wholesale value. Note,
however, that there is no economic reason to expect fishermen or processors' shares of gross
wholesale value to remain constant over time. Regardless of wholesale value, processors must
cover the costs of processing—which account for a relatively larger share of wholesale value as
wholesale value declines.

The loss in value during the 1990s led to a severe economic crisis in the Bristol Bay salmon
industry. As discussed above, as the value of the fishery declined, the prices of limited entry
permits plummeted and many fishermen stopped fishing their permits. Similarly, many land-
based salmon processing operations closed and many floating processors left Bristol Bay.
13 The decline in the fishermen's share of ex-vessel value was a key issue in an unsuccessful class-action lawsuit
filed in 1995, in which Bristol Bay permit holders alleged that major processors and Japanese importers of Bristol
Bay salmon had conspired to fix prices paid to fishermen (Alakayak v. All Alaskan Seafoods, Inc). The author
served as an expert witness on behalf of the defendant processors and importers.
95
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3.7 Bristol Bay Salmon Fishermen

As discussed earlier, both the Bristol Bay drift gillnet fishery and the Bristol Bay set gillnet
fishery are managed under a "limited entry" management system which was implemented for all
of Alaska's twenty-seven salmon fisheries in the mid-1970s. The basic purpose and effect of the
limited entry system is to limit the number of boats fishing in each fishery, which makes it easier
for managers to control the total fishing effort and makes the fishery more profitable for
participants than it would be if entry (participation) were unrestricted and more boats could fish.

There are approximately 1860 drift gillnet permits and approximately 1000 set net permits.
Every drift gillnet fishing boat or set net operation must have a permit holder on board or present
while fishing—so the number of boats or set net operations cannot exceed the number of permit
holders.

A permit represents a right (legally a revocable privilege) to participate in a fishery. Unlike
individual fishing quota (IFQ) or catch-share systems which have been implemented in some
United States fisheries, a permit does not restrict a permit-holder to catching a specific number of
fish. Fishermen may catch as many fish as they can—as long as they follow the numerous
regulations which restrict when, where and how they may fish.

When limited entry management was implemented in 1975, permits were allocated for free to
individuals who had historically participated in the fishery. Permit holders may hold permits in
perpetuity, although they must renew their permits each year for a nominal administrative fee.
Persons without permits can acquire them only by gift, inheritance or by buying them from
existing permit holders.

Permit holders must register to fish in one of the five Bristol Bay fishing districts. They may
transfer to fish in another district, but must wait 48 hours before fishing in the new district.

A "permit stacking" regulation" implemented in 2004 for the drift gillnet fishery allows two
permit holders who opt to fish together on a single vessel to use 200 fathoms of drift gillnet gear
(an additional 50 fathoms more than the usual limit of 150 fathoms). The objective of the
regulation was to allow two permit holders to team up to reduce their combined harvesting costs
to create a more profitable operation.

In addition to permit holders, there are an average of about two crew members for each drift
gillnet fishing boat and about two crew members for each set gillnet site. Crew members are
usually paid a percentage share of gross earnings after deducting costs of food and fuel. A
typical drift gillnet crew share is about 10%.

The Commercial Fisheries Entry Commission (CFEC) maintains detailed public data about
salmon permit holders, including their names, addresses, and vessel information. It also
publishes annual data on the total number of permits fished, total pounds landed, total gross
earnings, and average prices paid for permits sold.14
14 The data may be found at the Commercial Fisheries Entry Commission website: http://www.cfec.state.ak.us/.

96
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In contrast, almost no data are available about Bristol Bay crew members. Although crew are
required to purchase an annual Alaska fishing crew license for a nominal fee, no data are
available about whether they participate in fishing, which fisheries they fish in, or how much
they earn. For this reason, most of the data presented in this section are about Bristol Bay permit
holders. But keep in mind that about two-thirds of the people working in Bristol Bay fish
harvesting are crew members.

Fishery Participation

Until the late 1990s, most Bristol Bay permits were fished (Figure 44). However, beginning in
the late 1990s, a growing number of permit holders stopped participating in the Bristol Bay
fishery, because they couldn't make enough money to cover their costs. In 2002—the lowest
year for Bristol Bay ex-vessel value since the start of the limited entry program in 1975—only
63% of drift gillnet permits and 66% of set gillnet permits were fished.

Since 2002, as the value of the fishery increased, fishery participation also increased, although
many permits remained unfished. In 2010, 80% of drift gillnet permits and 86% of set gillnet
permits were fished.
Number of Limited Entry Permits Issued and Fished in Bristol Bay
2000
CM CM CM CM CM CM
Source: CFEC Salmon Basic Information Tables
Figure 44. Number of Limited Entry Permits Issued and Fished in Bristol Bay

Understanding the extent of participation in the Bristol Bay drift gillnet fishery since 2004 is
complicated by the permit-stacking option for the drift gillnet fishery, under which two permit
holders may opt to fish together (with an additional 50 fathoms of gear) from a single boat.
97
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A CFEC analysis of the 2009 fishery, based on district registration data (both permit-holders in a
two-permit operation are required to register for fishing in that district) concluded that "for the
fishery as a whole, two-permit operations occurred on an estimated 20.9% (278) of the 1,331
vessels registered during the season and one-permit only operations occurred on 79.1% (1,053)
of the vessels. Of the 1,610 distinct permit holders who registered during the season, 34.7%
(558) were involved in a two-permit operation during the season, while 65.3% (1,052) were
involved in a one-permit operation only."15

Table 29 and Table 30 (on the following page) provides selected indicators of participation in the
Bristol Bay drift gillnet fishery in 2009, based on various measures reported by CFEC. A total
of 1863 permits were issued to 1838 permit holders. Of these, 1610 registered to fish during the
season in one or more of the Bristol Bay fishing districts. Of these an estimated 1052 fished
alone and 558 fished with another permit holder. Of those who fished with another permit
holder, an estimated 401 reported landings on their permits while 157 reported no landings on
their permits (all of the operation's landings were reported on the other permit holder's permit).

Thus the CFEC data for the "number of permits fished," shown in Figure 44 above (1453 in
2009), overstates the number of boats which fished (1331 in 2009), but understates the number
of permit holders who participated in the fishery (1610 in 2009).
Table 29. Selected Indicators of Participation in 2009 Drift Gillnet Fishery
Selected Indicators of Participation in the 2009 Bristol Bay Drift Gillnet Salmon Fishery
Row
1
2
o
3
4
5
6
7
8
9
10
Indicator
Total permits issued
Number of permit holders
Number of distinct permit holders who registered during the season
Estimated number involved in a one-permit operation only during the season
Estimated number involved in a two-permit operation during the season
Number of fishermen who fished (reported landings on their permits)
Total permits fished (with reported landings)
Number of vessels registered during the season
Estimated number on which only one-permit operations occurred
Estimated number on which two-permit operations occurred
Source
a,b
b
c
c
c
b
a,b
c
c
c
Number
1,863
1,838
1,610
1,052
558
1,453
1,444
1,331
1,053
278
(a) CFEC, Salmon Basic Informaton Tables, Bristol Bay Drift Gillnet Salmon Fishery,
http://www.cfec.state.ak. us/bit/X_S03T.HTM.
(b) CFEC, "Permit & Fishing Activity by Year, State, Census Area or City," data for "Grand Total: All
Fishermen Combined", http://www.cfec.state.ak.us/gpbycen/2009/00_ALL.htm.
(c) Schelle, K., N. Free-Sloan, and C. Farrington, "Bristol Bay Salmon Drift Gillnet Two-Permit
Operations: Preliminary Estimates from 2009 District Registration Data (CFEC Report No. 09-6N, 2009).
http://www.cfec.state.ak.us/RESEARCH/09-6N/bbr_final_v4_121409.pdf.
15 Schelle, K., N. Free-Sloan, and C. Farrington, "Bristol Bay Salmon Drift Gillnet Two-Permit Operations:
Preliminary Estimates from 2009 District Registration Data (CFEC Report No. 09-6N, 2009).
http://www.cfec. state.ak.us/RESEARCH/09-6N/bbr_final_v4_121409.pdf.

98
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Table 30. Estimated Number of 2009 Drift Gillnet Permit Holders who Fished Alone, With
another Permit Holder, or Did Not Fish
Estimated Numbers of 2009 Drift Gillnet Permit Holders Who Fished Alone,
Fished with Another Permit Holder, or Did Not Fish
Number of permit holders who:
Fished alone
Fished with another permit holder
Fished with another permit holder and reported landings
As the only permit holder who reported landings
With both reporting landings
Fished with another permit holder but did not report landings
Held permit but did not fish it
TOTAL NUMBER OF PERMIT HOLDERS
Estimates
1,052
558
401
722
279
157
228
1,838
How calculated*
4
5
5 - (3 - 6)
6-8
5 - (3 -6) - (6-8)
3 -6
2-3
2
*Numbers refer to rows in the previous table.

Distribution of Earnings

In both the drift gillnet and set gillnet fisheries, each year there is wide variation among permit
holders in average earnings, reflecting differences in vessel size, fishing style, fishing experience
and skill, how aggressively and for how long they fish, what fishing districts they choose to fish
in, and good or bad luck. These differences are reflected in average earnings among four
"quartile" groups of permit holders, each of which accounts for one quarter of total Bristol Bay
earnings.

In the drift gillnet fishery, typically, the first quartile has about one-third to one-fourth as many
fishermen as the fourth quartile, earning on average of about three to four times as much (Figure
45).
99
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Average Gross Earnings of Bristol Bay Drift Gillnet Permit Holders,
by Quartile
$250,000
O5O5O5O5O5O5O5O5O5O5O5O5O5OOOOO
•*- First
quartile

^^ Second
quartile

-•-Third
quartile

-*- Fourth
quartile
Source: Commercial Fisheries Entry Commission quartile tables
Figure 45. Average Gross Earnings of Bristol Bay Drift Gillnet Permit Holders

Average earnings in the set gillnet fishery are much lower than in the drift gillnet fishery. The
highest earning "first quartile" set gillnet permit holders earn about half as much as the "first
quartile" drift gillnet permit holders (Figure 46). There is a wider range of variation in earnings
of set net permit holders, reflecting in part wide differences in the number offish swimming past
set net sites in different Bristol Bay locations.
100
-------
Average Gross Earnings of Bristol Bay Set Gillnet Permit Holders,
by Quartile
$120,000
-•-First
quartile

^^ Second
quartile

-•-Third
quartile

-*-Fourth
quartile
O5O5O5O5O5O5O5O5O5O5O5O5O5
T- co LO h- a>
o o o o o
o o o o o
CM CM CM CM CM
Source: Commercial Fisheries Entry Commission quartile tables
Figure 46. Average Gross Earnings of Bristol Bay Set Gillnet Permit Holders
Permit Prices

The prices paid for Bristol Bay permits have fluctuated dramatically over time. Expressed in
nominal dollars, average prices paid for drift gillnet permits rose from $66,000 in 1980 to
$249,000 in 1989, fell to $20,000 in 2002, and rose again to $102,000 in 2010. Average prices
paid for set gillnet permits rose from $29,000 in 1980 to $65,000 in 1989, fell to $12,000 in
2002, and rose again to $29,000 in 2010.
101
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Average Prices Paid for Bristol Bay Limited Entry Permits
$250,000
CM "3" CD 00 O
O O O O
rorororororororororooooooo

Source: CFEC Salmon Basic Information Tables
Figure 47. Average Prices Paid for Bristol Bay Limited Entry Permits
Bristol Bay limited entry permit prices are clearly strongly related to total earnings in the fishery.
In both fisheries, trends over time in permit prices closely track trends over time in total earnings
(Figure 48 & Figure 49). Economic theory suggests that permit prices would be driven by
fishermen's expectations of future profits from the fishery. The close relationship between total
earnings and permit prices suggests that expectations of future profits are driven by trends in
average profits in recent years.

Costs of Fishing

Not all Bristol Bay permit holder earnings are profits, of course. Permit holders face significant
costs of fishing, some of which are relatively fixed regardless of the volume or value of their
catch—which makes fishing profits relatively more volatile than earnings.

No data are collected on a regular basis on the costs faced by Bristol Bay permit holders. From
time to time, studies have estimated costs of fishing based on surveys of Bristol Bay permit
holders. However, it is difficult to characterize fishing costs, for several reasons. First, costs
may vary widely between fishing operations, because of differences in factors such as vessel
size, number of crew, how and where permit holders fish, and where permit holders and crew
live. Second, costs may vary significantly from year to year due to changes in prices of fuel,
insurance and other inputs to fishing. Third, fixed costs such as vessel storage and insurance
may vary widely from year to year when expressed on a per-pound basis due to changes in
harvest volumes.
102
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Average Permit Prices and Total Earnings: Bristol Bay Drift Gillnet Fishery
•Average permit price ($)
-0- Total earnings ($ million)
$250,000
\
$200

- $180
$0
§CN"3-COOOOCN"3-COOOOCN"3-COOOO
ooooooooo)O)O)O)O)ooooo-<-
0)0)0)0)0)0)0)0)0)0)000000

Source: CFEC Salmon Basic Information Tables
Figure 48. Average Permit Prices and Total Earnings: Bristol Bay Drift Gillnet Fishery
Average Permit Prices and Total Earnings: Bristol Bay Set Gillnet Fishery
•Average permit price ($)
-0-Total earnings ($ million)
$70,000

$60,000

-------
Figure 50 summarizes the estimated 2008 fishery-wide distributions of operating costs and
incomes to Bristol Bay permit holders and crew reported by the Anchorage-based economic
consulting firm Northern Economics in a recent detailed study of the importance of Bristol Bay
salmon fisheries to the Bristol Bay region and its residents, conducted for the Bristol Bay
Economic Development Corporation. The estimates were based on updates of estimates of
previous analyses by CFEC and Northern Economics to account for changes in fuel prices and
other costs. A review of the details of how the estimates were prepared and their limitations is
beyond the scope of this report. We include them here as a general indicator of the kinds of costs
which are important in the fishery and their approximate magnitudes relative to 2008 earnings.
Note that operating costs in both fisheries include fuel and oil, net maintenance, gear, boat and
net storage, transportation, food, insurance, taxes, fees and services. Permit holders also face
costs of crew share payments (about 10% of gross earnings per crew member, after deducting
costs of fuel and food), as well as loan payments for permits and boats.
All Drift Net Vessels
Transports Food
6% Fuel & Oil
4%
Income to Crew&
Permit Holders (Incl.
Loan Payments)
74%
Maintenance Nets,
Gear& Storage
10%
Insurance. Taxes,
Fees, & Services
6%
All Set Net Vessels
Transports Food
5% Fuels, Oil
2%
Maintenance Nets,
Gears. Storage
10%
Insurance. Taxes,
Fees, & Services
3%
Income to Crews,
Permit Holders (Incl
Loan Payments)
80%
Figure 50. Northern Economies' Estimates of the Breakdown of Operating Costs
and Incomes to Crew and Permit Holders, Bristol Bay Salmon Fisheries, 2008
Source: Northern Economics, The Importance of the Bristol Bay Salmon Fisheries to the Region and its Residents
(report prepared for the Bristol Bay Economic Development Corporation, October 2009). Estimates based in part
on earlier analyses by Northern Economics and CFEC.
104
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3.8 Bristol Bay Salmon Processors

Fish processing is an integral part of the Bristol Bay commercial salmon industry, employing
approximately half as many people as fish harvesting and more than doubling the value of the
fish.

Bristol Bay salmon are processed in both land-based processing facilities and on floating
processors. Salmon are canned only in large land-based facilities, which also have salmon
freezing capacity. Floating processors produce only frozen salmon. As discussed, the Bristol
Bay salmon processing industry typically employs about 3000 to 4000 workers annually at the
height of the salmon processing season—depending upon the size of the harvest. Of these, fewer
than 5% are residents of the Bristol Bay region. Another 10% to 15% are residents of other parts
of Alaska, and about 75% to 80% are residents of other states or countries. Most are relatively
unskilled short-term workers: only about 20% work in Bristol Bay for more than five years.
Almost all live in bunkhouses provided by the processing companies.
Yardarm Knot Cannery, Naknek
Source: http://vw.yardarm.net/red%20salmon%20cannery/cannery%20home4Jiles/image301.jpg

Icicle Seafoods' Floating Processor Bering Star in the Nushagak River
(the ship on the left is a cargo vessel loading frozen salmon for shipment to Japan)
105
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In 2010, six companies operated salmon canning facilities in Bristol Bay. These included some
of the largest seafood processing companies operating in Alaska, such as Trident Seafoods,
Ocean Beauty Seafoods, Icicle Seafoods and Peter Pan Seafoods. Most of these companies have
both land-based and floating processing operations in many parts of Alaska, which process not
only salmon but other major Alaska species as well, such as pollock, crab and halibut. All large
processors have home offices in or near Seattle.

In 2010, all of the processors with canning facilities, and five other larger processors purchased
salmon in multiple Bristol Bay districts. There were twenty-five other buyers and smaller
processors who bought salmon in just one district.

Most of the land-based processing facilities in the Bristol Bay region are located in or near a
small number of communities with regularly-scheduled air transportation. The largest number of
processors are located in Naknek along the Naknek River. Most of the other land-based facilities
are in Dillingham, Egegik and Togiak.

Bristol Bay salmon processing is not an easy business. The list of companies buying and
processing salmon in Bristol Bay changes from year to year. The number of large processors
operating in Bristol Bay declined in the 1990s, reflecting consolidation in the industry forced by
harvest volumes and lower profits. Many land-based processing plants closed and the number of
floating processors brought into Bristol Bay each year to process salmon also declined sharply.
This consolidation helped to make the industry more efficient and more profitable.
Number of Companies Reporting Salmon Production in Bristol Bay,
by Product
00000000000005050505050505050505
O5O5O5O5O5O5O5O5O5O5O5O5O5O5O5O5
OOOOOOOOOO
00000000000
0101010101010101010101
Source: ADF&G Commercial Operator Annual Reports
Figure 51. Number of Companies Reporting Salmon Production in Bristol Bay, by Product
106
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Fish account for the largest share of costs of Bristol Bay processors. Other important costs
include labor, fish tendering, packaging (boxes and cans), transportation of products and
workers, utilities and taxes, maintenance, and costs of equipment and buildings.

Another important "cost" is the adjustment for the yield from the "round pound" weight offish
purchased from fishermen to the "processed pound" weight offish products. In effect, for any
given ex-vessel prices, the lower the yield, the higher the cost offish per pound of final product
weight.

Costs per pound vary between product forms and may also vary widely from year to year as
fixed costs are spread over different volumes of salmon. Table 31 provides rough estimates of
Bristol Bay salmon processing costs from an analysis for 1994 and 1995. Note that costs have
likely risen considerably since these estimates were prepared, due to changes in costs of labor,
energy and other factors.
Table 31. Estimates of Bristol Bay Processor Costs, Prices and Profits
Estimates of Bristol Bay Processor Costs, Prices, and Profits: Mid-Range Estimates for 1994 and 1995

Price paid to fishermen
+ Taxes and assessments
+ Tender cost
+ Costs of services to fishermen
= Fish cost per round Ib.
- Roe value per round Ib. (= roe yeild x roe price)
= Fish cost per round Ib., net of roe value
^ Processing yield
= Fish cost per processed Ib., net of roe value
+ Processing costs per processed Ib.
+ Transportation and storage costs before sale
+ Other costs
= Processor's total cost
Average price received by processor
Profit or loss (= average price - total cost)
per processed Ib.
per round Ib.
Frozen Dressed
1994 1995
$0.97 $0.75
$0.03 $0.02
$0.17 $0.17
$0.03 $0.03
$1.20 $0.97
$0.09 $0.09
$1.11 $0.88
740/0 74o/0
$1.51 $1.20
$0.60 $0.60
$0.00 $0.00
$0.10 $0.10
$2.21 $1.90
$2.45 $1.80
$0.24 -$0.10
$0.18 -$0.07
Frozen Round
1994 1995
$0.97 $0.75
$0.03 $0.02
$0.17 $0.17
$0.03 $0.03
$1.20 $0.97
$0.00 $0.00
$1.20 $0.97
97% 97%
$1.24 $1.00
$0.40 $0.40
$0.00 $0.00
$0.10 $0.10
$1.74 $1.50
$2.20 $1.00
$0.46 -$0.50
$0.45 -$0.49
Canned
1994 1995
$0.97 $0.75
$0.03 $0.02
$0.17 $0.17
$0.03 $0.03
$1.20 $0.97
$0.07 $0.07
$1.13 $0.90
59% 59%
$1.92 $1.53
$0.73 $0.73
$0.10 $0.10
$0.10 $0.10
$2.85 $2.46
$2.71 $2.80
-$0.14 $0.34
-$0.08 $0.20
Note: Costs and prices can vary widely between processors. Any given processor's profits or lesses could be higher or lower than showin in this table.
Source: Currents: A Journal of 'Salmon Market Trends, University of Alaska Anchorage, Salmon Market Information Service, December 1995.
107
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Selected Bristol Bay Salmon Processor Costs, 2001-2009
"o
T3
300
250
200
150
100
III
= 50
imini
I Other costs
and profits
0 Cost of labor
(fish processing
earnings)
I Cost of fish
(ex-vessel
value)
8
CM
CM
8
CM
CO
8
CM
8
CM
in
8
CM
CD
8
CM
8
CM
00
8
CM
O)
8
CM
Source: ADFG.ADLWD
Figure 52. Selected Bristol Bay Salmon Processor Costs, 2001-2009

Most larger Bristol Bay salmon processors contract with tender vessels to transport salmon from
fishing vessels at or near the best fishing areas to land-based or floating processing facilities.
Tendering represents a significant cost for the industry. Many tender vessels are larger vessels
used seasonally in other Alaska fisheries such as the Bering Sea crab fisheries. No data are
available on the number of tender vessels used in the Bristol Bay fishery. A rough guess is that
there are about fifty.
Fishermen delivering salmon to a tender. As fish are
caught, they are placed in broiler bags in the hold of
the fishing boat. Here, a broiler bag is being hoisted
aboard a tender, where the fish are kept in refrigerated
water during transport to the processor.
Fish are pumped from tenders into processing plants
Photograph by Gabe Dunham
Photograph by Gabe Dunham
108
-------
Sockeye salmon entering a processing plant
Workers cleaning, salmon
Packaging is an important cost offish processing
3.9 Bristol Bay Salmon Industry Employment

Challenges in Measuring Bristol Bay Salmon Industry Employment

Measuring employment in the Bristol Bay salmon industry is complicated by several factors.
First, no employment data are collected for commercial fishing comparable to the employment
data collected for most other industries. This is because commercial fishermen (both permit
holders and crew) are considered self-employed, and they do not pay unemployment insurance.
Employment data for most industries (including fish processing) are based on unemployment
insurance reporting forms filed by employers. To make up for this significant gap in Alaska
employment data, as discussed below, the Alaska Department of Labor and Workforce
Development (ADLWD) Research and Analysis Division estimates monthly commercial fishing
employment by multiplying the number of permits for which fish landings are reported each
month by assumed average employment per permit fished (crew factors).
109
-------
Second, the Bristol Bay salmon industry is highly seasonal. Most of the fishing and processing
occurs between the middle of June and the middle of July, with smaller numbers of fishermen
and processing workers engaged in smaller-scale fishing and processing as well as start-up and
close-down activities earlier and later in the year. Thus a Bristol Bay fishing or processing job
which typically lasts less than two months is not directly comparable to a year-round job in
another industry. As discussed below, to provide a basis for comparing employment in the
Bristol Bay salmon industry with year-round employment in other industries, we estimate
"annual average employment," calculated as the total number of months worked divided by 12.

Third, the "Bristol Bay Region" for which ADLWD reports fish processing employment and
estimated salmon fishing employment includes the Chignik salmon fishery—an important
Alaska salmon fishery although much smaller than the Bristol Bay fishery. By way of
comparison, between 2006 and 2010, expressed as a percentage of the Bristol Bay salmon
fisheries, total pounds landed in the Chignik salmon fishery were 7.7% of Bristol Bay, earnings
were 6.3% of Bristol Bay, and total permits fished were 2.4% of Bristol Bay. Thus ADLWD fish
harvesting and processing employment estimates and data for the "Bristol Bay region" slightly
overestimate employment for the Bristol Bay salmon fishery.

Fourth, estimates offish processing employment are not available by fishery—because in
reporting employment fish processing plants do not distinguish between the species offish that
their workers were processing during the reporting period. Thus fish processing employment
estimates for the Bristol Bay region include some employment in processing other species such
as herring. However, it is likely that fish processing employment data for the Bristol Bay region
are overwhelmingly dominated by Bristol Bay salmon. For a comparison of the relative scale of
the two fisheries, between 2006 and 2010, expressed as a percentage of the Bristol Bay salmon
fisheries, total pounds landed in the Bristol Bay (Togiak) herring seine and gillnet fisheries
22.6% of pounds landed in the Bristol Bay salmon fisheries, earnings were 2.1% of earnings in
the salmon fisheries, and the total permits fished were 2.6% of permits fished in the salmon
fisheries. Note also that Bristol Bay herring processing is much less labor intensive than salmon
processing because Bristol Bay herring are entirely frozen round for export.
Terminology for Measures of Employment

In the subsequent discussion, we use the following terms for different kinds of employment
estimates:

Jobs: The number of distinct work positions
Workers: The number of different individuals who worked
Annual average employment The number of months worked divided by 12

For example, suppose a permit holder fishes for two months with two crew members on board
his boat. After one month one crew member leaves and is replaced by another crew member.
The permit holder's operation would account for 3 jobs, 4 workers, and annual average
employment of 0.5 (3 jobs x 2 months = 6 job months which is 6/12 or 0.5 job years).
110
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Estimates of Bristol Bay Salmon Harvesting and Processing Employment

Table 32 (on the following page) summarizes available estimates of Bristol Bay salmon
harvesting and processing employment from several different sources calculated in several
different ways. Figure 53 (on the subsequent page) graphs several of the estimates shown in
Table 32.

Estimated fishing jobs based on salmon permits fished (Rows 1-4)

A simple way to estimate Bristol Bay salmon fishing jobs is from Commercial Fisheries Entry
Commission (CFEC) data for the number of permits fished and the Alaska Department of Labor
and Workforce Development (ADLWD) assumption of three jobs for each drift gillnet and each
setnet fishing operation.16 Based on this methodology, between 2000 and 2010, the number of
Bristol Bay salmon fishing jobs ranged between 5592 and 8232. The estimated number of jobs
varied from year to year because the number of permits fished varied from year to year.

A problem with this method of estimating fishing jobs is that since the introduction of "permit
stacking" in the drift gillnet fishery, there is no longer necessarily a direct relationship between
the number of permits fished and the number of vessels fished. As discussed, the number of
permits fished each year likely understates the number of permit holders who fished but likely
overstates the number of vessels which fished (since some permit holders fished together on the
same vessel).

CFEC reported that 1444 permits were fished in 2009, but only 1331 vessels were registered to
fish during the season. This would imply that the number of permits fished overstated that
number of vessels fished by 113, which would in turn imply that the estimates in Row 4
overstate the number of fishing jobs by 339. For the same reason, the estimates in rows 6 and 9-
12 of Table 32 (discussed below) may also slightly overestimate the number of fishing workers.
16 According to a table of crew factors provided to Gunnar Knapp by ADLWD in 2004 (crewfactor.xls), ADLWD
assumed crew factors of 3.0 for both the Bristol Bay drift gillnet and set gillnet fisheries.

Ill
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Table 32. Indicators and Estimates of Bristol Bay Salmon Industry Fishing Processing
Employment
Indicators and Estimates of Bristol Bay Salmon Industry Fishing and Processing Employment, 2000-2010
Measure
Estimated fishing jobs based on salmon
permits fished (a)
Permits fished, drift gillnet fishery
Permits fished, set gillnet fishery
Permits fished, total
Estimated number of fishing jobs (= permits
fished x 3 jobs/permit fished)
ADLWD estimates of Bristol Bay region
salmon fishing workers (b)
[ndivi duals who fished permits
Total estimated workforce
Ratio of estimated workforce to individuals
who fished permits
Estimated crew workers
ADLWD estimates of Bristol Bay region
salmon fishing workers by month (c)
June
July
August
September
Bristol Bay region fish processing workers,
all species (d)
Total worker count
Bristol Bay region food manufacturing
employment (e)
July
Annual average
Assumed total salmon industry workers
Fishing (July employment) (Row 10)
Processing (total worker count) (Row 13)
Total
Estimated annual average
salmon industry employment
Fishing
(= total months of employment / 12)
Fish processing (f)
Total
Row

1
2
3
4

5
6
7
8

9
10
11
12

13
14
15

16
17
18

19
20
21
2000

1,823
921
2,744
8,232

2001

1,566
834
2,400
7,200

2,412
6,969
2.89
4,557

6,771
7,098
276
0

2,862

7,098
2,862
9,960

1,179
475
1,654
2002

1,184
680
1,864
5,592

1,867
5,334
2.86
3,467

4,830
5,514
309
0

2,273
2,414
765

5,514
2,273
7,787

888
366
1,254
2003

1,424
761
2,185
6,555

2,196
6,324
2.88
4,128

6,045
6,465
249
0

2,484
3,026
992

6,465
2,484
8,949

1,063
409
1,472
2004

1,411
795
2,206
6,618

2,210
6,294
2.85
4,084

6,093
6,513
375
84

3,474
4,189
1,139

6,513
3,474
9,987

1,089
581
1,669
2005

1,447
829
2,276
6,828

2,286
6,444
2.82
4,158

6,135
6,750
279
15

3,272
3,946
1,147

6,750
3,272
10,022

1,098
532
1,631
2006

1,475
844
2,319
6,957

2,340
7,020
3.00
4,680

6,201
6,936
540
3

2,940
4,391
1,339

6,936
2,940
9,876

1,140
483
1,623
2007

1,468
835
2,303
6,909

2,239
6,717
3.00
4,478

5,982
6,891
444
0

3,512
4,480
1,385

6,891
3,512
10,403

1,110
566
1,675
2008

1,469
850
2,319
6,957

2,245
6,735
3.00
4,490

6,060
6,969
504
12

3,952

6,969
3,952
10,921

1,129
640
1,769
2009

1,444
843
2,287
6,861

2,309
9,236
4.00
6,927

6,393
6,768
504
54

4,522

6,768
4,522
11,290

1,143
764
1,907
2010

1,494
861
2,355
7,065

Sources and notes: (a) CFEC Salmon Basic Information Tables, http://www.cfec.state.ak.us/bit/MNUSALM.htm; (b) ADLWD, "Fish Harvesting Workforce and
Gross Earnings by Species, 2001 - 2009,"
http://www.labor.state.ak.us/research/seafood/BristolBay/BBFHVWrkrEmgSpec.pdf Estimated crew workers= Total estimated workforce - Individuals who
fished permits, (c) ADLWD, "Fish Harvesting Employment by Species and Month, 2000-2009, Bristol Bay Region,"
http://labor.alaska.gov/research/seafood/BristolBay/BBAvgMonthlyRegSpc.pdf; (d) ADLWD, "Bristol Bay Region Seafood Industry, 2003-2009, Processing,"
http://labor.alaska.gov/research/seafood/BristolBay/BBSFPOver.pdf 2001 & 2002 data are earlier estimates formerly posted at the same website; (e) ADLWD,
Quarterly Census of Employment and Wages Data, http://labor.alaska.gov/research/qcew/qcew.htm; (f) annual average fish processing employment estimated by
assuming the same ratio of annual average employment to total worker count as the ratio of estimated annual average fishing employment to July fishing
employment.

ADLWD estimates of Bristol Bay region salmon fishing workers (rows 5-8)

These are ADLWD estimates of the salmon harvesting workforce (number of workers) in the

Bristol Bay region for the years 2001-2009.1? Note that these include workers in the Chignik

salmon fishery. The total estimated workforce (row 6) was estimated by multiplying the number
The estimates are posted at http://labor.alaska.gov/research/seafood/BristolBav/BBFHVWrkrErngSpec.pdf. A
discussion of the methodology used to prepare the estimates is posted on the ADLWD website at:
112
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18
of individuals who fished permits (row 5) by assumed crew factors for each fishery. ° We
calculated estimated crew workers (row 8) by subtracting individuals who fished permits (Row
5) from the total estimated workforce (row 6).
Selected Estimates of Bristol Bay Salmon Fishing and Processing Workers
12,000
10,000
8,000
6,000
4,000
2,000
•Assumed total fishing and
processing workers
(Row 18)

- Estimated fishing jobs
(Row 4)
-Estimated July salmon fishing
workers
(row 10)

-Estimated fishing workforce
(Row 6)
-Food manufacturing July
employment
(Row 14)

-Fish processing worker count
(Row 13)
O T- CM
O O O
O O O
CM CM CM
o
O
CM
CD
O
O
CM
O
O
CM
OO O> O
O O T-
O O O
CM CM CM
Note: Row numbers
refer to previous table.
Figure 53. Selected Estimates of Bristol Bay Salmon Fishing and Processing Workers
ADLWD estimates of Bristol Bay region salmon fishing workers by month (Rows 9-12)

These are ADLWD estimates of the salmon harvesting workforce (number of workers) by month
in the Bristol Bay region for the years 2001-2009.19 The methodology used for these estimates
http://labor.alaska.gov/research/seafood/Methodologv.pdf. Additional discussion of the methodology is provided in
Josh Warren and Rob Kreiger, "Fish Harvesting in Alaska (Alaska Economic Trends, November 2011); Josh
Warren and Jeff Hadland, "Employment in Alaska's Seafood Industry" (Alaska Economic Trends, November 2009);
and Paul Olson and Dan Robinson, "Employment in the Alaska Fisheries: A special project estimates fish
harvesting jobs" (Alaska Economic Trends, December 2004), These articles are posted on the ADLWD website at
http://labor.alaska.gov/trends/.
18 No documentation was provided as to what crew factors were used for these estimates. The ratio of estimated
workforce to individuals who fished permits (Row 7) suggests that crew factors of 3.0 were used for the years 2006-
2009. It is not clear why the ratio was lower for the years 2001-2005 (between 2.82-2.89) and much higher for 2009
(4.00), suggesting that different crew factors were used for these years. The estimate for 2009, based on a 25%
higher crew factor of 4.0, is indicated with a dashed line inFigure IX-1.
19 The estimates are posted at http://labor.alaska.gov/research/seafood/BristolBay/BBAvgMonthlyRegSpc.pdf.
113
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was similar but not identical to that used to for the estimates of salmon fishing workers in rows
5-8), resulting in slightly higher estimates.20

Bristol Bay region fish processing workers, all species (Row 13)

These are ADLWD estimates of the total worker count for Bristol Bay region seafood
processing.21'22

Bristol Bay region food manufacturing employment (Rows 14 & 15)

These are the sum of ADLWD data for food manufacturing employment in Bristol Bay Borough,
Lake and Peninsula Borough, and the Dillingham Census Area (the ADLWD's Bristol Bay
region).23 Table IX-2 provides the same detail in more detail, by month. Presumably, almost all
food manufacturing in the Bristol Bay region is fish processing. It is not clear why the July food
manufacturing employment (Row 14) is considerably larger than the total worker count for fish
processing for the same region (Row 13).

Assumed total salmon industry workers (Rows 14 & 15)

For the purposes of this report, we assume that the total number of workers in the Bristol Bay
salmon industry is July salmon fishing workers (Row 10) and the ADLWD total worker count
(Row 13). The inconsistencies between the different estimates discussed above suggest that
while these should be considered reasonable indicators of the general magnitude of the number
rather than precise data. In general, it appears reasonable to assume that in recent years the total
number of workers in Bristol Bay salmon fishing and processing has exceeded 10,000.

Estimated annual average salmon industry employment (Rows 19-21)

These are estimates of salmon industry annual average employment, or job months / 12. Again,
these should be considered reasonable indicators of the general magnitude of annual average
employment rather than precisely accurate data. In general, it appears reasonable to assume that
in recent years average annual employment in Bristol Bay salmon fishing and processing has
exceeded 1600.
20 According to notes provided with the estimates, for these estimates "... the permit itself is considered the
employer. In other tables where a count of workers was estimated, the employer was considered to be the vessel, or
permit holders for fisheries that did not typically use vessels. This means that a permit holder who makes landings
under two different permits (in the same vessel) in the same month will generate two sets of jobs whereas for tables
where the vessel is the employer there would be only one set of workers."
21 The data are posted at http://labor.alaska.gov/research/seafood/BristolBay/BBSFPOver.pdf.
22 The only information about how the data source or methodology is the following: "The Alaska Department of
Labor and Workforce Development's Occupational Database (ODB) is the primary source of seafood processing
employment data. The ODB contains quarterly information for all Alaska workers covered by unemployment
insurance (UI)." (http://labor.alaska.gov/research/seafood/Methodology.pdf).
23Quarterly Census of Employment and Wages Data posted at http://labor.alaska.gov/research/qcew/qcew.htm.

114
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Seasonally of Bristol Bay Fish Processing Employment

ADLWD monthly data for Bristol Bay food manufacturing employment provide an indication of
the seasonality and geographic distribution of Bristol Bay salmon processing (Figure 54 and
Table 33). Presumably salmon processing accounts for most but not all of Bristol Bay region
food manufacturing employment. One indicator of this is that for the years 2001-2009, the total
fish harvesting workforce for other fisheries for which ADLWD reported Bristol Bay region
harvesting workforce estimates, expressed as a percentage of the salmon harvesting workforce
estimates, averaged 5.5% for herring, 2.1% for halibut and 0.4% for sablefish.24

Bristol Bay region food manufacturing employment peaks in July, and is generally much higher
during the months from May through September than at other times in the year. Note that a
significant part of the work in fish processing occurs before the season starts (getting ready for
processing) and after the season ends (closing down processing operations and preparing for the
next season). Some people are employed throughout the year in activities such as plant
maintenance and repair.
Monthly Employment in Food Manufacturing, Bristol Bay Region, 2002-2007
5,000
4,000
3,000
2,000
1,000
2007
2006
2005
2004
2003
2002
Source: Alaska Department of Labor and Workforce Development
Figure 54. Monthly Employment in Food Manufacturing, Bristol Bay Region
ADLWD, "Fish Harvesting Workforce and Gross Earnings by Species, 2001-2009, Bristol Bay Region,"
http://labor.alaska.gov/research/seafood/BristolBay/BBFHVWrkrErngSpec.pdf.
115
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Table 33. Monthly Employment in Food Manufacturing, by Borough or Census Area.
Monthly Employment in Food Manufacturing, by Borough or Census Area, Bristol Bay Region, 2002-2010
Area Month

Bristol Bay
Borough

i mgham

egion

Units reporting
January
February
March
April
May
June
July
August
September
October
November
December
Average
Units reporting
January
February
March
April
May
June
July
August
September
October
November
December
Average
Units reporting
January
February
March
April
May
June
July
August
September
October
November
December
Average
Units reporting
January
February
March
April
May
June
July
August
September
October
November
December
Average
2002
8
7
8
8
441
495
713
977
325
51
42
29
34
261
4
283
529
590
455
372
384
1,091
392
347
283
149
48
410
7
20
21
19
23
53
222
346
278
87
15
13
28
94
19
310
558
617
919
920
1,319
2,414
995
485
340
191
110
765
2003
9
52
56
57
197
464
1,115
1,915
1,291
728
41
49
22
499
3
124
512
495
373
390
339
775
544
618
270
260
84
399
j
10
34
11
40
53
191
336
329
90
14
10
8
94
17
186
602
563
610
907
1,645
3,026
2,164
1,436
325
319
114
992
2004
11
11
10
21
81
678
1,299
2,644
1,250
834
46
59
46
582
3
184
519
496
451
285
739
1,035
544
552
331
253
147
461
5
5
5
11
27
52
258
510
250
18
8
7
6
96
19
200
534
528
559
1,015
2,296
4,189
2,044
1,404
385
319
199
1,139
2005
14
11
12
19
81
818
1,365
2,663
1,424
847
68
72
51
619
4
123
543
507
377
392
799
1,057
694
567
306
257
82
475
4
4
4
5
9
38
171
226
135
17
11
9
10
53
22
138
559
531
467
1,248
2,335
3,946
2,253
1,431
385
338
143
1,147
2006
11
14
13
25
113
894
1,957
2,898
1,471
789
61
74
53
697
4
232
418
487
477
455
951
1,164
987
789
305
199
97
547
4
11
17
19
26
62
242
329
258
89
41
27
20
95
19
257
448
531
616
1,411
3,150
4,391
2,716
1,667
407
300
170
1,339
2007
11
12
11
19
73
651
1,635
3,018
1,661
826
671
504
188
772
3
332
259
366
326
338
760
1,162
901
1,040
293
315
167
522
4
10
15
17
25
61
197
300
215
97
66
59
24
91
18
354
285
402
424
1,050
2,592
4,480
2,777
1,963
1,030
878
379
1,385
2008
10

4
9
15
16
29
69
156
319
24
20
5
5
5
56
17
9
15
16
29
69
156
319
24
20
5
5
5
56
2009
12

2010
12
16
19
27
96
977
1,819
3,489
1,738
914
92
66
59
776
3

Source: Alaska Department of Labor and Workforce Development, Quarterly Census of Employment and Wages Data, historical data for 2002-
2010, Excel file annual.xls, http://labor.alaska.gov/research/qcew/qcew.htm, downloaded November 27, 2011. Blank cells indicate data were not
available.
116
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3.10 Bristol Bay Salmon Industry Taxes

The Bristol Bay salmon industry pays millions of dollars annually in state, local and federal
taxes. This section briefly describes these taxes and provides estimates, where available, of taxes
paid in recent years.

Alaska Fisheries Business Tax

The Alaska Fisheries Business Tax (AS 43.75.015) accounts for the largest share of local and
state taxes paid by the Bristol Bay salmon industry. Under the fisheries business tax, salmon
processors pay the state:

5.0% of the ex-vessel value of salmon processed on floating facilities

4.5% of the ex-vessel value of salmon canned at shore-based facilities

3.0% of the ex-vessel value of other salmon processed at shore-based facilities
(e.g. salmon processed frozen, fresh, or in other ways except for canning)

The State of Alaska does not publish data on fisheries business tax revenues for specific species
and regions. Rows 1-4 of Table 34 provide a lower-bound estimate of tax obligations (before
credits) of Bristol Bay salmon processors, assuming that processors pay a tax rate of 5.0% for a
share of ex-vessel value equivalent to the share of canned salmon production in total Bristol Bay
salmon production, and 3.0% of ex-vessel value on the remaining share of ex-vessel value. This
estimate suggests that during the period 2000-2010, fisheries business tax obligations ranged
from as low as $1.3 million in 2002 to $6.4 million. Fisheries business tax payments are directly
proportional to ex-vessel value and thus highly sensitive to the effects of changes in catches and
prices on ex-vessel value.

Actual tax obligations are likely higher than the lower-bound estimates in Row 4, since (a) the
estimates do not take account of the higher tax rate (5.0%) on salmon processed on floating
processing; and (b) the share of salmon which is canned is likely higher than the share of canned
production in total production, because average yields are lower for canning.

Processors are entitled to credits against Fisheries Business Tax obligations up to certain limits
for certain kinds of expenditures, including for example investments in salmon product
development (AS 43.75.035); investments to improve salmon utilization (AS 43.75.036), and
and contributions to the University of Alaska and other Alaska higher education institutions (AS
43.75.018). No data are available on the extent to which these tax credits reduce Bristol Bay
fisheries business tax revenues.
117
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Table 34. Selected Data and Estimates for Bristol Bay Salmon Taxes
Selected Data and Estimates for Bristol Bay Salmon Taxes

Simple lower-bound estimate of
fisheries business tax obligations
ix-vessel value of Bristol Bay salmon
harvests ($ 000)
Canned share
(assumed tax rate = 5.0%)
STon-canned share
( assumed tax rate = 3%)
^ower-bound estimate of fisheries tax
obligation ($ 000)
State of Alaska Shared Business Tax
Payments to Bristol Bay Boroughs
and Cities (S 000) (a)
3ristol Bay Borough
^ake and Peninsula Borough
Dillingham
Egegik
Total
Row

1
2
3
4

5
6
7
8
9
2000

$84,014
37%
63%
$3,145

$1,440
$357
$203
$30
$2,029
2001

$40,359
32/0
68%
$1,467

$918
$246
$176
$176
$1,517
2002

$31,898
49%
51%
$1,270

$494
$162
$49
$78
$784
2003

$46,684
39%
61%
$1,760

NA
NA
NA
NA
NA
2004

$76,461
34%
66%
$2,818

$451
$113
$100
$36
$700
2005

$94,556
32%
68%
$3,439

$835
$71
$154
$29
$1,089
2006

$108,570
34%
66%
$3,998

$1,178
$99
$148
$29
$1,454
2007

$115,763
35%
65%
$4,287

$1,296
$134
$184
$74
$1,687
2008

$116,717
28%
72%
$4,163

$1,564
$138
$176
$63
$1,941
2009

$144,200
25%
75%
$5,061

$1,543
$152
$187
$63
$1,944
2010

$180,81S
27%
73%
$6,383

$1,797
$215
$23?
$85
$2,335
(a) Source: Alaska Department of Revenue, Annual Shared Taxes and Fees Reports, www.tax.alaska.gov. NA: Not available.
Fisheries Business Tax Refunds

The State of Alaska "refunds" a major share of Fisheries Business Tax revenues to Alaska local
governments, as follows (AS 43.75.130):

Cities receive 50% of the tax revenues collected in unified municipalities and in
cities outside organized boroughs, and 25% of tax revenues collected in cities in
organized boroughs

Boroughs receive 50% of the tax revenues collected in areas of boroughs outside
cities and 25% of the tax revenues collected in cities inside Boroughs.

Rows 5-9 of Table X-l provide data on State of Alaska shared fisheries tax payments to Bristol
Bay boroughs and cities. In total, these payments ranged from $700 thousand in 2004 to $2.3
million in 2010.
Local Government Taxes

Several local governments in the Bristol Bay region impose taxes on the ex-vessel value of
salmon processed within their jurisdictions. In 2010, these included the following:
25
Bristol Bay Borough:
Egegik:
Lake and Peninsula Borough:
Pilot Point:
4% raw fish tax (?)
3% raw fish tax
2% raw fish tax
3% raw fish tax
25 Alaska Office of the State Assessor, 2010 Alaska Taxable, Table 2, Sales/Special Taxes and Revenues,
http://www.dced. state.ak.us/dca/osa/osa_summary.cfm.
118
-------
Local governments also impose property taxes on processing facilities. No data are published on
Bristol Bay local government fish taxes or property taxes. However, it is likely that these taxes
are comparable in magnitude to fisheries business taxes, and represent a major share of total
local government tax revenues.

Federal Government Taxes

Like all U.S. industries, the Bristol Bay salmon industry pays federal taxes including corporate
and individual income taxes paid by processing companies, processing workers, and fishermen.
No data are available on federal taxes specifically attributable to the Bristol Bay salmon industry,
although it is likely that they significantly exceed total taxes paid to the state and local
governments.
3.11 Regional Distribution of Bristol Bay Permit Holders, Fishery
Earnings, and Processing Employment

An important characteristic of the Bristol Bay commercial salmon industry is that shares of the
participants in the industry—both fishermen and processing workers—do not live in the Bristol
Bay region but rather in other parts of Alaska or other states and countries. In this section we
review available data on trends in the regional distribution of permit holdings, earnings and
processing employment between "local" residents of the Bristol Bay region, other Alaskans, and
non-Alaskans.

The Bristol Bay Region

There are twenty-six communities in the Bristol Bay region the Commercial Fisheries Entry
Commission (CFEC) considers "local" to the fishery for its analyses (Figure 55). Residents of
these villages are considered "Bristol Bay residents" for the CFEC data presented below on
permit holdings and earnings of Bristol Bay residents.

Residents of five additional villages on the south side of the Alaska Peninsula (Chignik City,
Chignik Lagoon, Chignik Lake, Perryville and Ivanof) are also considered "Bristol Bay
residents" for the Alaska Department of Labor and Workforce Development (ADLWD) data on
seafood processing employment.
119
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TogiakO
0Twfn Hilte
oKoliganek

New Stuyahoko
OBkwok
Alegniglko IgiuglgO
O Lovelock
NondaKono
Iliamna
o
Pedro Bay

OKokhanok
•
Marvokotak ODWingham
- J°. n QPortag® Creek
Clark's Pomtg...
oNakrwk
South NaknekO oK|ng galmon
OEgcgik
Bristol Bq)
Port Heid*
Figure 55. Bristol Bay Region Local Communities Source:
www. visitbristolbay. org/bbvc/images/bb_map_large.jpg
Regional Distribution of Permit Holders

Limited entry was implemented for most Alaska salmon fisheries in 1975, including the Bristol
Bay drift gillnet and set gillnet fisheries. The permits were initially issued for free to individuals
based on their degree of economic dependence upon the fishery and the extent of their past
participation in the fishery. The purpose and effect of this initial allocation system was to
ensure that significant numbers of rural local residents received permits in regions of Alaska with
limited other economic opportunities, such as Bristol Bay (Knapp, 2011).
120
-------
Number of Bristol Bay Drift Gillnet Permit Holders, by Residency
-Residents
of other
states
-Other
Alaska
residents
-Bristol Bay
residents
Number of Bristol Bay Set Gillnet Permit Holders, by Residency
Soon after the implementation of
limited entry a significant long-
term decline began in the share of
permits held by local residents in
the Bristol Bay fisheries and many
other rural Alaska fisheries. There
has been a corresponding increase
in the number of permits held by
other Alaska residents as well as
non-Alaska residents. This decline
in local permits has been an
important concern at both the
regional and state level.

Between 1978 and 2010, the
number of permits Bristol Bay
drift gillnet permits held by local
residents fell from 614 to 383
(Figure 56). The share of drift
gillnet permits held by local
residents fell from 36% to 21%.

Between 1978 and 2010, the
number of permits Bristol Bay set
gillnet permits held by local
residents fell from 530 to 353. The
share of permits held by local
residents fell from 59% to 36%.

The decline in local permit
ownership has come about as a
result of both net permit transfers
(sales and gifts) from residents of
the region to non-local residents, as well as migration of permit holders out of the region.
Initially net permit transfers played a far greater role, but migration of permit holders out of the
region has also played an important role in recent years.
Figure 56. Number of Bristol Bay Permit Holders by
Residency
121
-------
Regional Distribution of Fishery Earnings
Drift Gillnet Permit Holders Average Earnings Per Permit Fished, by Residency
$140,000
$120,000
Set Gillnet Permit Holders Average Earnings Per Permit Fished, by Residency
Historically, Bristol Bay
residents have had the
lowest average earnings
(gross revenues) per permit
fished, while residents of
other stages have had had
the highest average
earnings per permit fished.
For example, in 2007—the
latest year for which CFEC
earnings data by residency
are available, in the Bristol
Bay drift gillnet fishery,
average earnings per permit
fished were $44,604 for
Bristol Bay residents,
$66,191 for other Alaska
residents, and $73,391 for
non-Alaska residents
(Figure XI-4).

In the Bristol Bay set
gillnet fishery, average
earnings per permit fished
were $22,991 for Bristol
Bay residents, $23,259 for
other Alaska residents, and
$25,333 for non-Alaska
residents (Figure XI-5).

A variety of factors may
contribute to these
differences in average
earnings per permit fished
by residency. In the drift
gillnet fishery, the vessels operated by Bristol Bay residents tend to be older and smaller, with
lower average horsepower and fuel capacity than those of other Alaska residents or residents of
other states (Table 35). A much smaller share of the vessels operated by Bristol Bay residents
have refrigeration capacity. All of these differences may reflect less access to capital for Bristol
Bay residents than for other Alaska residents or residents of other states. However, the reasons
for differences in earnings between groups have not been studied in detail or conclusively
explained.
Figure 57. Permit Holders Average Earnings, by Residency
122
-------
Table 35. Comparison of Vessels Used in the Bristol Bay Drift Gillnet Fishery, by
Residency of Permit Holder
Comparison of Vessels Used in the Bristol Bay Drift Gillnet Fishery, by Residency of Permit Holder

Average age
of vessels
(years)
Average
lorsepower of
vessels
Average
displacement of
vessels
(gross tons)
Average fuel
capacity of
vessels (gallons)
3ercent of
vessels with
refrigeration
capacity
Group
Bristol Bay Residents
Other Alaska Residents
Residents of Other States
Average
Bristol Bay Residents
Other Alaska Residents
Residents of Other States
Average
Bristol Bay Residents
Other Alaska Residents
Residents of Other States
Average
Bristol Bay Residents
Other Alaska Residents
Residents of Other States
Average
Bristol Bay Residents
Other Alaska Residents
Residents of Other States
Average
1983
9
9
11
10
239
243
252
245
10
12
12
11
239
306
283
276
0.5%
1.3%
0.5%
0.8%
1988
11
11
12
11
279
271
286
278
12
13
12
12
288
334
311
311
0.5%
2.3%
2.0%
1.6%
1993
14
14
13
14
282
315
335
311
12
13
13
13
282
364
348
331
2.3%
7.5%
8.1%
6.0%
1998
18
17
16
17
294
345
368
336
12
13
14
13
294
357
352
335
4.5%
13.7%
15.5%
11.2%
2003
22
21
20
21
287
350
372
336
12
14
14
13
287
357
350
331
5.5%
15.3%
17.8%
12.9%
2008
26
24
24
25
337
373
382
364
12
15
14
14
299
360
364
341
7.7%
20.8%
22.2%
16.9%
Northern Economics. 2009. The Importance of the Bristol Bay Salmon Fisheries to the Region and its
Residents. Report prepared for the Bristol Bay Economic Development Corporation. 193 pages. Data are
from tables on pages 136 and 137 of report. Based on data provided by the Commercial Fisheries Entry
Commission.
123
-------
Share of Total Earnings of Bristol Bay Drift Gillnet Permit Holders, by Residency
70%
60%
50%
40%
O5O5O5O5O5O5O5O5O5O5O5O5O5OOOO
30%
20%
10%
-Residents of other
states

-Other Alaska
residents
•Bristol Bay
residents
Figure 58. Share of Total Earnings of Bristol Bay Drift Gillnet Permit Holders, by
Residency
Trends over time in the share of different groups in total earnings of Bristol Bay permit holders
represent the combined effects of trends over time in each group's share of permit holdings as
well as differences between groups in average earnings. In the drift gillnet fishery, the share of
Bristol residents in total earnings fell from about 35% in the late 1970s to just 15% in 2007. The
share of non-Alaska residents increased from less than 50% in the late 1970s to 60% in 2007
(Figure 58).
124
-------
Share of Total Earnings of Bristol Bay Set Gillnet Permit Holders, by Residency
70%
60%
50%
40%
30%
20%
10%
0%
- Residents of other
states

-Other Alaska
residents

•Bristol Bay
residents
§§§§§8888
CXI CXI CXI CXI
Figure 59. Share of Total Earnings of Bristol Bay Set Gillnet Permit Holders, by
Residency
In the set gillnet fishery, the share of Bristol residents in total earnings fell from about 63% in the
late 1970s to 35% in 2007. The share of non-Alaska residents increased from abouS 20% in the
late 1970s to 34% in 2007 (Figure 59).
Regional Distribution of Processing Employment

Employment in Bristol Bay seafood processing is overwhelmingly dominated by residents of
other states and countries. In 2009, according to Alaska Department of Labor and Workforce
Development data, Bristol Bay residents accounted for less than 2% of Bristol Bay processing
workers, and other Alaska residents accounted for only 12%. Residents of other states and
countries accounted for 87%. (Processing employment data by residency are only available for
the years 2004-2009).(Figure 59).
125
-------
Share of Bristol Bay Seafood Processing Employment, by Residency
mno/
QD% -
80% -
7C\Q/n
fino/*
^n% -
4n% -
30% -
9n%

1U/o -
0% -1

lr-____^r___- *- ^- —*- -^

0 »— _ ___ _^___ ft ^
• * « « ,
M- m CD h- oo CD
000000
000000
CM CM CM CM CM CM
Source: Alaska Department of Labor and Workforce Development, Research and Analysis Division

-A- Residents of other
states or countries
-0- Other Alaska
residents
•^- Bristol Bay
residents

Figure 60. Share of Bristol Bay Seafood Processing Employment, by Residency
A Primarily Non-Local Fishery—With Widely Distributed Benefits

As is clear from the preceding figures, local residents account for a relatively small and declining
share of the jobs and earnings in the Bristol Bay salmon industry (Figure 61). In contrast, non-
Alaska residents account for relatively large and growing share of the jobs and earnings.
126
-------
50%
40%
30%
20%
10%
Local Bristol Bay Resident Share of the Bristol Bay Salmon Fisheries:
Selected Measures
•Total
permits
held*
-A- Total
earnings*
-Processing
employment
OOOCN^COOOOCN'^-COOO
r^ooooooooooo>a>a>a>a>
a>a>a>a>a>a>a>a>a>a>a>
CD oo
oooooo
CM CM CM CM CM CM
Source: CFEC, Changes in the Distribution of Alaska's Commercial Fisheries Entry Permits,
1975-2010
*Shares for
both fisheries
combined.
Figure 61. Local Bristol Bay Resident Share of Salmon Fisheries: Selected Measures
This does not mean, of course, that the Bristol Bay salmon fishery is unimportant as a source of
jobs or income for local residents. As we discuss in greater detail previously, it remains very
important. However, it is not as important for local residents as it might appear if one were to
erroneously assume that all the jobs were held by local residents and all the income was earned
by local residents.
Bristol Bay processing worker from Turkey
127
-------
A different perspective is that the Bristol Bay fishery is not just economically important for a
remote region of southwestern Alaska. Rather, it is of major economic importance for other
parts of Alaska and other states, particularly the Pacific Northwest. Thousands of residents of
other parts of Alaska and other states work in and earn significant income from participating in
Bristol Bay fishing and processing. For example, as shown in Table 36, in 2010, 597 residents
of other parts of Alaska, 656 residents of Washington, 125 residents of Oregon and 119 residents
of California fished Bristol Bay salmon permits. They had gross earnings of $40 million (other
Alaskans), $59 million (Washington residents), $10 million (Oregon residents, and $9.5 million
(California residents).
Table 36. Participation and Gross Earnings in Bristol Bay Salmon Fisheries

Participation and Gross Earnings in Bristol Bay Salmon Fisheries, by Group, 2010

Group
Bristol Bay Residents, Total
Dillingham Census Area
Bristol Bay Borough
Lake and Peninsula Borough
Other Alaska Residents, Total
Anchorage
ECenai Peninsula Borough
Matanuska-Susitna Borough
Wrangell-Petersburg Census Area
ECodiak Island Borough
Other parts of Alaska
Alaska Residents, Total
Other States and Countries, Total
Washington
Oregon
California
Other States & Countries
TOTAL
Number of Fishermen Who Fished*
Drift gillnet
fishery
301
202
56
43
359
86
86
38
18
42
89
660
850
538
87
87
138
1510
Set gillnet
fishery
297
183
83
31
238
120
44
42

9
23
535
281
118
39
32
92
816
Total
598
385
139
74
597
206
130
80
18
51
112
1195
1131
656
126
119
230
2326
Estimated Gross Earnings ($1000)
Drift gillnet
fishery
18,250
11,170
4,227
2,854
31,215
6,479
7,968
3,593
2,445
3,951
6,780
49,466
84,671
55,342
8,383
8,058
12,888
134,137
Set gillnet
fishery
10,670
6,451
3,162
1,057
8,858
4,288
1,685
1,504
0
321
1,061
19,528
11,494
4,179
1,618
1,449
4,249
31,022
Total
28,920
17,620
7,389
3,911
40,074
10,767
9,652
5,097
2,445
4,272
7,841
68,994
96,165
59,521
10,001
9,507
17,136
165,159
*Number of fishermen who made at least one landing as a permit holder.
Source: Commercial Fisheries Entry Commission, Fishery Participation and Earnings Statistics, 2010:
http ://www.cfec. state, ak.us/gpbycen/2010/mnu.htm.
128
-------
3.12 Distribution of Salmon Permits and Earnings within The Bristol
Bay Region
Above, we discussed the distribution of Bristol Bay
salmon permits and earnings between local residents of
the Bristol Bay region and residents of other parts of
Alaska and other states. In this section, we discuss the
distribution of permits and earnings within the Bristol
Bay region.

For this analysis, we used the Commercial Fisheries
Entry Commission (CFEC) definition of the Bristol Bay
region as the twenty-six communities within the Bristol
Bay watershed. For the analysis in this section, we use
the Alaska Department of Labor and Workforce
Development (ADLWD) definition of the Bristol Bay
region as the Bristol Bay Borough, the Lake and
Peninsula Borough, and the Dillingham Census Area.
The ADLWD definition is slightly larger because it
includes five communities outside the Bristol Bay
watershed (Chignik City, Chignik Lagoon, Chignik
Lake, Perryville and Ivanof).
Source: Alaska Department of Labor and Workforce Development.
Research and Analysis Section
DILLINGHAM CENSUS AREA
Dillingham Region
DiKingham
Aleknagik
Clark's Point
Portage Creek
Ekuk
LAKE AND PENINSULA
BOROUGH
Upper Nushagak
Region
Koliganek
New Sluyahok
Ekwok
Togiak-Manokotak Region
Togiak
Twin Hills
Manokotak
BRISTOL BAY BOROUGH
King Salmon
Naknek
South Naknek
Chignik Region
Chignik City
Chignik Lagoon
Chignik Lake
Ivanov Bay
Perryville
South Bristol Bay Region
Egegik
Pilot Point
Ugashik
Port Heiden
We further divide the Bristol
Bay region into seven smaller
regions, consisting of the groups
of communities:

Bristol Bay Borough
Dillingham Region
Togiak-Manokotak Region
Upper Nushugak Region
Lake Region
South Bristol Bay Region
Chignik Region

We omit the Chignik Region
from the figures because
residents of the region have very
little involvement with the
Bristol Bay fishery.
Table 37 summarizes population, numbers of permit holders, and salmon fishery earnings for
each community and region in 2000 and 2010. These data were used to calculate per capita
129
-------
permit holdings and earnings shown in Table 38 and Table 39. We used similar data to calculate
Figure 62 through Figure 69 which show trends by region over time.
Table 37. Population, Permit Holders, and Salmon Earnings, by Community: 2000 & 2010

Population, Salmon Permit Holders, and Bristol Bay Salmon Earnings, by Community, 2000 & 2010

BRISTOL BAY BOROUGH
King Salmon
Naknek
South Naknek
DILLINGHAM CENSUS AREA
Dillingham Region
Aleknagik
Clarks Point
Dillingham
Ekuk
Portage Creek
Togiak-Manokotak Region
Manokotak
Togiak
Twin Hills
Upper Nushagak Region
Ekwok
Koliganek
New Stuyahok
LAKE AND PEN. BOROUGH
Lake Region
Igiugig
Iliamna
Kokhanok
Levelock
Newhalen
Nondalton
Pedro Bay
Port Alsworth
South Bristol Bay Region
Egegik
Pilot Point
Port Heiden
Ugashik
Chignik Region
Chignik
Chignik Lagoon
Chignik Lake
Ivanof Bay
Perryville
BRISTOL BAY, TOTAL (a)
BRISTOL BAY, TOTAL (b)
Population
2000
1257
442
678
137
4,922
2800
221
75
2,466
2
36
1277
399
809
69
783
130
182
471
1,823
986
53
102
174
122
160
221
50
104
346
116
100
119
11
456
79
103
145
22
107
8003
7547
2010
997
374
544
79
4,847
2614
219
62
2,329
2
2
1333
442
817
74
834
115
209
510
1,631
953
50
109
170
69
190
164
42
159
291
109
68
102
12
362
91
78
73
7
113
7475
7113
Drift gillnet
permit holders
2000
63
14
37
12
326
167
19
8
139
0
1
107
28
72
7
52
5
14
33
86
36
4
8
4
8
6
4
1
1
49
23
9
15
2
1
0
0
1
0
0
475
474
2010
63
15
38
10
262
142
15
7
120
0
0
80
24
53
3
40
3
16
21
57
28
3
9
3
4
6
2
0
1
28
10
8
8
2
1
0
0
1
0
0
382
381
Set gillnet
permit holders
2000
117
17
70
30
231
115
9
5
101
0
0
106
44
60
2
10
0
3
7
64
32
0
7
4
6
2
8
2
3
31
15
11
3
2
1
0
0
1
0
0
412
411
2010
101
17
69
15
199
97
6
4
87
0
0
97
35
62
0
5
0
2
3
45
27
1
6
6
2
4
4
3
1
17
7
5
3
2
1
0
0
1
0
0
345
344
Resident drift
gillnet earnings
($000)
2000
$1,939
$589
$1,120
$230
$10,287
$6,284
$530
$329
$5,425
-
-
$2,918
$847
$2,071
$0
$1,084
$117
$300
$667
$1,454
$371
-
$116
$76
$130
$49
-
-
-
$1,083
$494
$232
$357
-
-
-
-
-
-
-
$13,679
$13,679
2010
$4,227
$1,209
$2,695
$323
$10,913
$6,855
$752
$C
$6,103
-
-
$3,222
$696
$2,526
$C
$836
-
$456
$38C
$2,01S
$865
-
$45C
$C
$189
$226
-
-
-
$1,152
$468
$C
$684
-
-
-
-
-
-
-
$17,158
$17,158
Resident set
gillnet earnings
($000)
2000
$1,506
$291
$920
$295
$3,901
$2,005
$131
$68
$1,806
-
-
$1,811
$646
$1,165
$0
$85
-
-
$85
$436
$109
-
$51
$0
$0
$0
$57
-
-
$328
$222
$106
$0
-
-
-
-
-
-
-
$5,843
$5,843
2010
$3,162
$749
$2,184
$229
$6,246
$3,032
$174
$117
$2,742
-
-
$3,213
$1,547
$1,666
$C
$0
-
-
-
$599
$499
-
$215
$143
$C
$141
-
-
-
$100
$10C
$c
$c
-
-
-
-
-
-
-
$10,007
$10,007
(a) Total includes the Chignik Region; (b) Total excludes the Chignik Region. Note:
and not reported. Sources: U.S. Censuses, 2000 and 2010; CFEC.
"-" indicates that earnings data were confidential
130
-------
Estimated Bristol Bay Area Population, by Borough / Census Area
Bristol Bay Population Trends

Figure 62 and Figure 63 show population trends for the Bristol Bay region. Note that the
population data should be considered estimates rather than precise data. They are based on the
decennial United States censuses conducted in 1980, 1990, 2000 and 2010, and were estimated
for intervening years by the Alaska Department of Labor and Workforce Development. In
addition, given the
seasonality of the Bristol
Bay area employment and
the fact that much of the
workforce is non-resident,
it is difficult to define or
measure population
precisely. It is most
useful to focus on long-
term population trends
and relative populations of
different regions rather
than short-term changes
which may result from
changes in how the data
were estimated rather than
actual population changes.
In general, the population
of the Bristol Bay area
increased rapidly during
the 1980s, grew more
slowly during the 1990s,
and declined gradually
during the 2000s. The
total 2010 population was
about 7500.

Of the six regions within
the Bristol Bay area
(excluding Chignik) the
Dillingham Region has by
far the largest population
and the south Bristol Bay
region has by far the
smallest.
9000
8000
7000
6000
5000
4000
3000
2000
1000
Dillingham Census Area
and Lake & Peninsula
Borough Combined
T- CM CM CM CM CM CM
Figure 62. Estimated Bristol Bay Area Population, by Area
Estimated Population, by Region
3000
2500
2000
1500
1000
500
-»- Dillingham Region

-•-Togiak-Manokotak Region

-x- Bristol Bay Borough

-x-Lake Region

-*- Upper Nushagak Region

-©-South Bristol Bay Region
Figure 63. Estimated Population by Region
131
-------
Permit Holders
Figure 64 shows the number of drift gillnet permit holders by region for the years 1984-2010.
The number is highest for the Dillingham Region, followed by the Togiak-Manokotak Region.
The number of drift gillnet permit holders has declined in all regions since 1984. The rate of
decline has been somewhat less for the Bristol Bay Borough, particularly since 2000.
Figure 65 shows number
of drift gillnet permit
holders per 100 residents,
by region. This measure
is equal to per capita
permit holdings multiplied
by 100.
By adjusting for
differences in population
over time and between
regions, it provides a way
of comparing the relative
degree of participation by
residents in the drift
gillnet fishery over time
and between regions.

Because the Bristol Bay
population has grown over
time, permit holdings per
100 residents have
declined relatively more
sharply than total permit
holdings, and have fallen
by about half since 1984
in all regions except the
Bristol Bay Borough.

In 2010, the number of
permit holders per 100
residents was highest in
the South Bristol Bay
Region (10) and lowest in
the Lake Region (3).
Thus the degree of
participation in the drift
gillnet fishery varies
between these regions by
a factor of 3.
Number of Drift Gillnet Permit Holders, by Region
250
200
150
100
-»-Dillingham Region

-•-Togiak-Manokotak Region

-*- Bristol Bay Borough

-*- Upper Nushagak Region

-e- South Bristol Bay Region

-x-Lake Region
cncncncncncncncnoooooo
--------
Figure 64. Number of Drift Gillnet Holders, by Region
Number of Drift Gillnet Permit Holders per 100 Residents, by Region
-e-South Bristol Bay Region

-•-Togiak-Manokotak Region

-*- Bristol Bay Borough

-»-Dillingham Region

•^All Bristol Bay Regions

-*- Upper Nushagak Region

-x-Lake Region
CD CO O
Figure 65. Number of Drift Gillnet Holders per 100 Residents,
by Region
132
-------
Number of Set Gillnet Permit Holders, by Region
Figure 66 shows the number of set gillnet permit holders by region for the years 1984-2010.
number is highest for the Bristol Bay Borough, Togiak-Manokotak Region, and Dillingham
Region, and is much lower for the other three regions. Since 1984, the number of set gillnet
permit holders has declined in four regions (Bristol Bay Borough, Dillingham Region, Lake
Region, and South Bristol
Bay Region). However,
the declines have
generally not been as
steep as the declines in the
number of drift gillnet
permit holders. The
number of set gillnet
permit holders has stayed
about the same in the
Togi ak-Manakotak
Region. It is very small in
the Upper Nushagak
Region.
The
160
140
120
100
-*- Bristol Bay Borough
-Togiak-Manokotak Region
-Dillingham Region
-x-Lake Region
-e- South Bristol Bay Region
-Upper Nushagak Region
Figure 66. Number of Set Gillnet Holders, by Region
Number of Set Gillnet Permit Holders per 100 Residents, by Region
Figure 67 shows number
of set gillnet permit
holders per 100 residents,
by region. In general, the
number of set gillnet
permit holders per 100
residents has trended
downward in all regions
except for the Bristol Bay
Borough.

There is wide variation
between regions in the
degree of participation in
the set gillnet fishery,
from as high as 10 permit
holders per 100 residents
in the Bristol Bay
Borough to as low as 1 in
the Upper Nushagak
Region.

Just as there is wide
variation between regions
in the numbers of permit
holders per 100 residents, there is also wide variation between individual communities within
regions and within the Bristol Bay watershed as a whole (Table 38). In 2010, some
CM CM CM CM
Figure 67. Number of Set Gillnet Permit Holders per 100
Residents, by Region
133
-------
communities, such as Ekwok and Nondalton, had fewer than 5 permit holders (drift and set
gillnet combined) per 100 residents. Others communities, such as Naknek and South Naknek,
had 20 or more.
Table 38. Salmon Permit Holders per 100 Residents, by Community

Salmon Permit Holders Per Hundred Residents, by Community, 2000 & 2010

Figure 68 and Figure 69 show total and per capita salmon fishery earnings for Bristol Bay
regions. Note that trends in fishery earnings for each region, as well as differences between
regions, reflect the combined effects of three factors: (1) trends in overall catches, prices and
value of the fishery; (2) trends in the number of permit holders in each region; and (3) trends in
average catch shares of
permit holders within each
region.
Total Salmon Fishery Earnings, by Region
$25,000
-»-Dillingham Region

-*- Bristol Bay Borough

-•-Togiak-Manokotak Region

-e- South Bristol Bay Region

-x-Lake Region

-*- Upper Nushagak Region
cncncncncncncncnoooooo
--------
Figure 68. Total Salmon Fishery Earnings, by Region
Per Capita Salmon Fishery Earnings, by Region
The combined effect of
the decline in total value
of the fishery as well as a
decline in the number of
permit holders was a
dramatic decline in
salmon fishery earnings
and per capita earnings for
all regions between the
late 1990s and 2002. Note
that this effect would
appear even more
dramatic if adjusted for
the inflation which
occurred during this
period of time.

Between 2002 and 2010,
both earnings and per
capita earnings have
recovered significantly
in all regions. However,
except for the Bristol Bay
Borough, per capita
earnings were well below
the levels of the 1980s,
particularly for the Lake
Region and Upper
Nughagak Region.

Just as there is wide
variation between regions
in per capita salmon
fishery earnings, there is
also wide variation
between individual communities within regions and within the Bristol Bay watershed as a whole
$25,000
$20,000
$15,000
$10,000
$5,000
-e-South Bristol Bay Region

-*- Bristol Bay Borough

-•-Togiak-Manokotak Region

-»-Dillingham Region

-x-Lake Region

-*- Upper Nushagak Region
Figure 69. Per Capita Salmon Fisheries Earnings, by Region
135
-------
(Table 39). In 2010, per capita salmon fishery earnings in some communities, such as Kokhanok
and Newhalen, were less than $2000. Presumably they were much lower in other communities,
such as Nondalton and Ekwok, for which earnings data were confidential due to the small
number of permit holders. In other communities, such as Naknek, South Naknek, Hiamna and
Port Heiden, they per capita earnings exceeded $6000. Thus there is clearly wide variation
within the Bristol Bay watershed in the extent to which communities and regions participate in
and benefit economically from Bristol Bay salmon fisheries.
Table 39. Bristol Bay Salmon Fishery Earnings, by Community
Bristol Bay Salmon Fishery Per Capita Earnings, by Community, 2000 and 2010

$2,285
$2,123
$2,560
$0
$1,384
$900
$1,649
$1,416
$798
$377

$1,137
$435
$1,067
$309

$3,129
$4,261
$2,316
$2,998

$1,709
$1,813
2010
$4,240
$3,232
$4,954
$4,093
$2,252
$2,623
$3,435
$0
$2,620

$2,417
$1,576
$3,091
$0
$1,002

$2,182
$745
$1,237
$908

$4,127
$0
$2,743
$1,191

$3,960
$4,296
$0
$6,705

$2,295
$2,412
Set gillnet fishery per capita
earnings
2000
$1,198
$657
$1,357
$2,154
$793
$716
$591
$901
$733

$1,418
$1,619
$1,440
$0
$109

$181
$239
$110

$504
$0
$0
$0

$947
$1,911
$1,058
$0

$730
$774
2010
$3,172
$2,004
$4,015
$2,892
$1,289
$1,160
$794
$1,882
$1,177

$2,410
$3,500
$2,039
$0
$0

$367
$524

$1,975
$842
$0
$740

$343
$915
$0
$0

$1,339
$1,407
Total salmon fishing per
capita earnings
2000
$2,740
$1,991
$3,009
$3,829
$2,882
$2,960
$2,990
$5,286
$2,933

$3,703
$3,742
$4,000
$0
$1,494

$1,597
$1,037
$487

$1,640
$435
$1,067
$309

$4,076
$6,173
$3,375
$2,998

$2,439
$2,587
2010
$7,411
$5,236
$8,969
$6,986
$3,540
$3,783
$4,229
$1,882
$3,798

$4,828
$5,075
$5,131
$0
$1,002

$1,604
$1,432

$6,102
$842
$2,743
$1,931

$4,302
$5,211
$0
$6,705

$3,634
$3,819
(a) Total includes the Chignik Region;
confidential and not reported. Sources:
(b) Total excludes the Chignik Region. Blank cells indicate that earnings data were
U.S. Censuses, 2000 and 2010; CFEC.
136
-------
3.13 Economic Measures of the Bristol Bay Salmon Industry

There is no single or best economic measure for the Bristol Bay fishery. Which measure is
appropriate depends upon the question being asked.

For example, if we want to know how the Bristol Bay salmon fishery compares in scale with
other fisheries, we should look at total harvests or ex-vessel or wholesale value. If we want to
know how it affects the United States balance of payments, we should look at estimated net
exports attributable to the fishery. If we want to know how much employment the industry
provides for residents of the local Bristol Bay region, Alaska or the United States, we should
look at estimated employment in fishing and processing for residents of these regions. If we
want to know the net economic value attributable to the fishery, we should look at estimated
profits of Bristol Bay fishermen and processors. These different measures vary widely in units,
in scale, and how economically "important" they make the fishery appear.

In this section, we summarize selected economic measures of the Bristol Bay commercial fishery
for recent years. These include harvests, gross ex-vessel and wholesale value, estimated export
value, direct employment and earnings in fishing and processing by region of residency, and
limited entry prices and total estimated limited entry permit value. We present tables of each of
these measures for the years 2000-2010. Where data are available, we present graphs for longer
periods, showing dollar values in both nominal and real (inflation-adjusted) prices expressed in
2010 dollars. Blank cells in the tables indicate that data were not available as of November
2011. Refer to earlier sections in this report for more detailed discussions of each measure.

Harvests

The Bristol Bay salmon fishery is a world-scale commercial salmon fishery. Between 2000 and
2010, Bristol Bay averaged 60% of total Alaska sockeye salmon harvests (by volume), 45% of
world sockeye salmon harvests, 18% of all Alaska wild salmon harvests, 7% of all world wild
salmon harvests, and 2% of all world salmon production (wild and farmed combined).
137
-------
Table 40. Economic Measures of Bristol Bay Salmon Industry: Sockeye Salmon Harvests
Economic Measures of the Bristol Bay Salmon Industry: Sockeye Salmon Harvests
Measure
Harvests
Millions offish
Millions of pounds
Bristol Bay harvest
volume as a share of:
Alaska sockeye salmon
World sockeye salmon
Alaska wild salmon (all species)
World wild salmon (all species)
World wild & farmed salmon
(all species)
2000

21
125

61%
45%
18%
7%
3%
2001

14
96

56%
40%
12%
5%
2%
2002

11
65

48%
28%
10%
4%
1%
2003

15
93

50%
38%
13%
5%
2%
2004

26
152

59%
47%
19%
8%
3%
2005

25
155

58%
47%
16%
7%
3%
2006

28
165

69%
49%
22%
8%
3%
2007

30
173

62%
47%
18%
7%
3%
2008

28
160

71%
52%
23%
9%
3%
2009

31
183

71%
55%
25%
7%
3%
2010

29
170

74%

Avg.

23
140

62%
45%
18%
7%
2%
Range

11 - 31
65 - 183

48%- 74%
28%- 55%
10%- 25%
4%- 9%
1%- 3%
Sources: Alaska Department of Fish and Game, National Marine Fisheries Service, FAO.
Bristol Bay Commercial Salmon Harvests
^n
AE*
A.r\ -
Ti
"m ^n -
M—
M—
O
/n 9^
c
o
^ 9fl -
E Z(J
^^
^r\
5 -
n

ml
LO h- O> T-
h- h- h- OO
O) O) O) O)

co LO r*- o •<-
oo oo oo oo o
O) O) O) O) O)

CO LO Is- O5
O) O) O) O)
O) O) O) O)
Source: Commercial Fisheries Entry Com mission; Alaska

T- CO LO h-
o o o o
o o o o
CM CM CM CM
Department of Fish and C

D Other
Species

• Sockeye

O) T-
O T-
O O
CM CM
ame

Figure 70. Bristol Bay Commercial Salmon Harvests
138
-------
Gross Ex-Vessel Value and First Wholesale Value

During the period 2000-2010, Bristol Bay sockeye salmon harvests had an average annual real
ex-vessel value to fishermen of $101 million (expressed in 2010 $). During this period of time,
the value was generally increasing, from a low or $39 million in 2002 to $181 million in 2010.
The real first wholesale value of salmon products processed from Bristol Bay sockeye salmon in
Bristol Bay was more than twice as high as harvest value, averaging $234 million for the period
2000-2010, and increasing from $124 million in 2002 to $390 million in 2010.
Table 41. Economic Measures of Bristol Bay Salmon Industry: Sockeye Value

Economic Measures of the Bristol Bay Salmon Industry: Sockeye Salmon Ex-Vessel Value and First Wholesale Value
Measure
Ex -Vessel Value
($ Millions)
Nominal value (not inflation-adjusted)
Real value (inflation adjusted, 2010 $)
First wholesale value
Nominal value (not inflation-adjusted)
Real value (inflation adjusted, 2010 $)
Bristol Bay sockeye salmon
share of:
Alaska wild salmon ex- vessel value
(all species)
World wild salmon ex-vessel value
(all species) *
United States fish & shellfish
landed value (all species)
Rank of Naknek-King Salmon among
U.S. ports in annual landed value
2000

80
104

175
227

23%

12%

2%
21

2001

40
51

115
144

14%

1%
49

2002

32
39

100
124

16%

1%
87

2003

48
57

114
137

19%

1%
58

2004

76
90

176
206

24%

13%

2%
12

2005

95
107

220
250

24%

12%

2%
8

2006

109
119

237
261

28%

13%

2%
8

2007

116
125

249
268

24%

11%

2%
7

2008

117
120

262
270

22%

10%

2%
7

2009

144
147

293
298

29%

3%
4

2010

181
181

390
390

25%

3%
4

Avg.

94
104

212
234

23%

10%

2%
24

Range

32 - 181
39 - 181

100 - 390
124 - 390

14% - 29%

6% - 13%

1% - 3%
87 - 4

* Valued at average prices of Alaska wild salmon, by species.

Sources: Alaska Department of Fish and Game, National Marine Fisheries Service, FAO.
139
-------
Ex-Vessel and Wholesale Value of Bristol Bay Sockeye Salmon
700
600
Note: Real (inflation-
adjusted) values are
expressed in 2010
dollars
i"~i"~i-~cocococococncncncncnooooo
-A- Real first
wholesale
value
•Nominal
first
wholesale
value

- Real ex-
vessel
value
•Nominal
ex-vessel
value
(S|(S|(S|(S|(S|

Source: Alaska Department of Fish and Game
Figure 71. Ex-Vessel and Wholesale Value of Bristol Bay Sockeye Salmon
Between 2000 and 2010, Bristol Bay averaged 23% of the ex-vessel for all Alaska wild salmon,
an estimated 10% of the harvest value of world wild salmon harvests, and 2% of the value of
U.S. fish and shellfish landings of all species combined.

As ex-vessel value increased dramatically between 2003 and 2010, the Bristol Bay port of
Naknek-King Salmon rose from a rank of 87th to 4th among all U.S. ports in annual landed
value (ex-vessel value, or value paid to fishermen, offish landed in the port).
Export Value of Bristol Bay Salmon Products

During the period 2000-2010, the value of Bristol Bay salmon products exported from the United
States averaged $173 million for the years 2000-2010, and was $254 million in 2010.
140
-------
Table 42. Economic Measures of the Bristol Bay Salmon Industry: Export Value.

Economic Measures of the Bristol Bay Salmon Industry: Estimated Export Value of Bristol Bay Sockeye Salmon Products
Measure
Nominal value of exports
(millions of dollars)
Canned
Frozen
Fresh
Roe
Total
Real value of exports
(millions of 2010 $)
Canned
Frozen
Fresh
Roe
Total
2000

44
8
87
11
150

57
11
112
14
193
2001

49
3
76
8
137

62
4
96
11
173
2002

41
11
40
5
97

50
14
49
6
120
2003

45
10
48
7
111

54
12
58
8
133
2004

68
13
82
8
172

80
15
96
9
201
2005

65
10
105
13
193

74
11
119
14
219
2006

79
5
80
9
173

86
6
88
10
191
2007

79
8
82
14
183

85
9
89
15
197
2008

84
8
92
22
206

86
8
94
23
212
2009

86
8
113
24
230

87
8
115
24
234
2010

80
8
146
20
254

80
8
146
20
254
Avg.

65
8
87
13
173

73
10
97
14
193
Range

41 -86
3 -13
40 - 146
5 -24
97 - 254

50 -87
4 -15
49 - 146
6 -24
120 -254
Note: The value oTUS exports oTBristol Bay sockeye salmon products was estimated as the total value oTUS sockeye salmon exports
multiplied by the share oTBristol Bay sockeye in total Alaska sockeye salmon havests. The value oTBristol Bay sockeye salmon roe exports
was assumed to be equal to the first wholesale value oT sockeye salmon roe production. The data source Tor US exports was the National
Marine Fisheries Serivce Foreign Trade in Fisheries Products website.
Estimated Value of US Exports of Bristol Bay Salmon Products
$300,000
$250,000
$200,000
"5
T3
$150,000
$100,000
$50,000
I Roe
Fresh
I Canned
I Frozen
-0-Real total
export value
(2010 dollars)

•^—Nominal total
export value
Source: NMFS trade data, ADFG COAR data for roe production value
Figure 72. Estimated Value of US Exports of Bristol Bay Salmon Products
141
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Employment

During the period 2001-2009, estimated peak employment in the Bristol Bay salmon industry
averaged 6,656 fishermen and 3,255 processing workers, for average total peak employment of
9,911.

Because the fishery occurs almost entirely in June and July, estimated annual average
employment is only about one-sixth as high as peak employment. During the period 2001-2009,
estimated annual average employment averaged 1,093 in fishing and 535 in processing, for a
total of 1,628 annual average jobs.

During this period Bristol Bay salmon annual average fishing employment averaged 15% of
Alaska statewide annual average fishing employment. Peak Bristol Bay commercial fishing
employment averaged 33% of peak statewide Alaska commercial fishing employment. Put
differently, in July—the busiest month for Alaska commercial fishing—about one third of all the
people fishing commercially in Alaska were fishing in Bristol Bay. Bristol Bay fish processing
accounted for an average of 14% of the individuals who worked in Alaska fish processing.
Table 43. Economic Measures of the Bristol Bay Salmon Industry: Employment

Economic Measures of the Bristol Bay Salmon Industry: Employment
Measure
Estimated peak employment or
number of workers
Peak (July) fishing employment
Number offish processing workers
Total
Estimated annual average
employment
Fishing
Fish processing
Total
Bristol Bay share of estimated Alaska
total
Annual average fishing employment
Peak (July) employment in fishing
Number offish processing workers
2001

7,098
2,862
9,960

1,179
475
1,654

15%
33%
13%
2002

5,514
2,273
7,787

888
366
1,254

12%
30%
11%
2003

6,465
2,484
8,949

1,063
409
1,472

14%
33%
11%
2004

6,513
3,474
9,987

1,089
581
1,669

15%
33%
16%
2005

6,750
3,272
10,022

1,098
532
1,631

15%
33%
15%
2006

6,936
2,940
9,876

1,140
483
1,623

16%
35%
13%
2007

6,891
3,512
10,403

1,110
566
1,675

15%
34%
15%
2008

6,969
3,952
10,921

1,129
640
1,769

16%
34%
17%
2009

6,768
4,522
11,290

1,143
764
1,907

16%
34%
19%
Avg.

6,656
3,255
9,911

1,093
535
1,628

15%
33%
14%
Range

5,514 -7,098
2,273 - 4,522
7,787 - 11,290

888 - 1,179
366 - 764
1,254 - 1,907

12% - 16%
30% - 35%
11% - 19%
Source: Alaska Department of Labor and Workforce Development, Research and Analysis Division.
142
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Limited Entry Permit Prices and Values

Limited entry permit prices provide a measure of the value to the marginal permit holder of the
present and future right to participate in the fishery. Economic theory suggests that this will be
the marginal permit holder's present discounted present value of expected future profits from the
fishery. During the period 2002-2010 Bristol Bay permit prices increased from $19,700 to
$102,100 for drift gillnet permits and from $11,900 to $28,700 for set gillnet permits. The
dramatic recovery in permit prices reflects a dramatic increase in profitability of the fishery and
expectations of continued profitability.

The total value of Bristol Bay permits—calculated as the number of permits multiplied by the
permit price—provides an estimate of the total present discounted value of expected future
profits from the fishery. During the period 2000-2010 the estimated total value of Bristol Bay
permits (both fisheries combined) ranged from $48 million to $218 million.

Multiplying the total value of a permit by the rate of return a permit holder demands on a permit
investment provides a measure of the annual profit permit holders expect to earn. We do not
know the rate of return demanded by permit holders. However, it is likely that it is between 5%
and 20%. This suggests that in 2010 annual expected profits from Bristol Bay commercial
fishing between $10.9 million and $43.7 million. Note that this does not include expected profits
from fish processing.

Table 44. Economic Measures of the Bristol Bay Salmon Industry: Permit Prices and
Values.
Economic Measures of the Bristol Bay Salmon Industry: Permits Prices and Values
Vleasure
V umber of permanent permits
issued
Drift gillnet fishery
Set gillnet fishery
Total
Average nominal permit price
($)
Drift gillnet fishery
Set gillnet fishery
Estimated total nominal value
($ millions) (a)
Drift gillnet fishery
Set gillnet fishery
Total
Implied annual nominal
profits ($ millions) (b)
assuming permit holders
demand a rate of return of:
5%
10%
15%
20%
2000

1858
1,007
1,007

80,500
32,400

149.6
32.6
182.2

9.1
18.2
27.3
36.4
2001

1,861
1,008
2,869

34,700
25,300

64.6
25.5
90.1

4.5
9.0
13.5
18.0
2002

1,863
1,004
2,867

19,700
11,900

36.7
11.9
48.6

2.4
4.9
7.3
9.7
2003

1,861
999
2,860

29,300
12,600

54.5
12.6
67.1

3.4
6.7
10.1
13.4
2004

1,857
988
2,845

37,000
14,700

68.7
14.5
83.2

4.2
8.3
12.5
16.6
2005

1,859
988
2,847

51,200
15,100

95.2
14.9
110.1

5.5
11.0
16.5
22.0
2006

1,859
985
2,844

75,000
22,400

139.4
22.1
161.5

8.1
16.1
24.2
32.3
2007

1,861
983
2,844

79,400
24,000

147.8
23.6
171.4

8.6
17.1
25.7
34.3
2008

1,863
979
2,842

89,800
27,400

167.3
26.8
194.1

9.7
19.4
29.1
38.8
2009

1,863
982
2,845

78,300
28,200

145.9
27.7
173.6

8.7
17.4
26.0
34.7
20K

1,863
982
2,845

102, IOC
28,70C

190.2
28.2
218/

10.9
21.8
32.8
43.7
Avg.

1,861
991
2,683

61,545
22,064

114.5
21.9
136.4

6.8
13.6
20.5
27.3
Range

1,857 - 1,863
979 - 1,008
1,007 - 2,869

19,700 - 102,100
11,900 - 32,400

36.7 - 190.2
11.9 - 32.6
48.6 - 218.4

2.4 - 10.9
4.9 - 21.8
7.3 - 32.8
9.7 - 43.7
(a) Calculated as average permit price x number of permanent permits issued, (b) Estimated total value x assumed rate of return demanded. Source: Commercial
Fisheries Entry Commission, Salmon Basic Information Tables.
143
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Estimated Total Value of Bristol Bay Limited Entry Permits
900
•Real
(2010)
dollars
•Nominal
dollars
r^ooooooooooa>a>a>a>a>
O5O5O5O5O5O5O5O5O5O5O5
O CM •* CD OO O
O O O O O T-
O O O O O O
CM CM CM CM CM CM
Source: Estimated from CFEC Salmon Basic Information Tables
Figure 73. Estimated Total Value of Bristol Bay Limited Entry Permits
3.14 Bristol Bay Commercial Fisheries: Summary
The Bristol Bay sockeye salmon fishery is one of the world's largest and most valuable wild
salmon fisheries. Between 2006 and 2010, the Bristol Bay salmon industry averaged:

• Annual harvests of 31 million salmon (including 29 million sockeye salmon)
• 51% of world sockeye salmon harvests
• Annual "ex-vessel" value to fishermen of $129 million
• Annual first wholesale value after processing of $268 million.
• 26% of the "ex-vessel" value to fishermen of the entire Alaska salmon harvest.
• Seasonal employment of more than 6800 fishermen and 3700 processing workers.

Participation in the Bristol Bay salmon fishery is limited to holders of limited entry permits and
their crew. There are approximately 1860 drift gillnet permits for fishing from boats and
approximately 1000 set net permits for fishing from the shore. The driftnet fishery accounts for
about 80% of the harvest. Most of the harvest is processed by about ten large processing
144
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companies in both land-based and floating processing operations which employ mostly non-
resident seasonal workers.

Bristol Bay Salmon Harvests

Sockeye salmon account for about 94% of the volume of Bristol Bay salmon harvests and an
even greater share of the value. Total catches vary widely from year to year. Between 1980 and
2010, Bristol Bay sockeye salmon harvests ranged from as low as 10 million fish to as high as 44
million fish. Harvests can vary widely from year to year. Annual pre-season forecasts are
subject to a wide margin of error.
Bristol Bay Commercial Salmon Harvests

•5
g
E

ml
& & & §

X) CO CO CO Cn
7) Cn Cn O5 O)

ro ID h- en
en en en en
en en en en

D Other
Species
• Sockeye

T- c^ LO h- en T-
888885
Source: Commercial F sheries Entry Commission; Alaska Department of F sh and Game

Figure 74. Bristol Bay Commercial Salmon Harvests

There are no formal long-term forecasts of future Bristol Bay harvests. The variability and
uncertainty of annual salmon returns are important factors influencing how the fishery is
managed and how fish are harvested, processed and marketed.

The Bristol Bay commercial salmon fishery harvests salmon which spawn in and return to
numerous rivers over a broad area. For management purposes, the fishery is divided into five
fishing districts. Catches in each district vary widely from year to year and over longer time
periods of time, reflecting wide variation in returns to river systems within each district (Table ).
There is no obvious way to characterize the relative share of the Bristol Bay commercial salmon
fishery attributable to particular river systems or to the individual streams and lakes that make up
each river system.
145
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Table 45. Distribution of Harvests for Bristol Bay Fishing Districts, 1986-2010

Distribution of Harvests for Bristol Bay Fishing Districts, 1986-2010
Measure
Harvests
(millions of
fish)
Share of total
harvests (%)
District
Naknek-Kvichak
Nushagak
Egegik
Ugashik
Togiak
Naknek-Kvichak
Nushagak
Egegik
Ugashik
Togiak
Minimum
0.6
1.7
2.3
0.5
0.1
5%
9%
16%
3%
0%
10th
percentile
2.7
2.7
4.0
1.5
0.2
18%
10%
21%
7%
1%
Mean
8.0
5.1
8.3
2.8
0.5
30%
22%
34%
11%
2%
90th
percentile
15.3
8.0
13.3
4.5
0.8
46%
32%
48%
15%
4%
Maximum
20.3
11.1
21.6
5.0
0.8
52%
45%
62%
32%
6%
Standard
deviation
5.0
2.3
4.3
1.3
0.2
11%
10%
11%
5%
1%
Source: Alaska Department of Fish and Game, Bristol Bay Annual Management Reports

Currently there is particular interest in the significance of fisheries resources of river systems in
the Nushagak and Kvichak districts, because of potential future resource development in these
watersheds. Over the period 1986-2010, the Naknek-Kvichak catches ranged from as low as 5%
to as high as 52% of total Bristol Bay catches; Nushagak district catches ranged form as low as
9% to as high as 45% of total Bristol Bay catches. For most of the past decade, the combined
Nushagak and Naknek-Kvichak districts have accounted for about 60% of the total Bristol Bay
commercial sockeye harvest.

In general, a decline in salmon returns associated with any particular river system might have a
relatively small effect on average catches over a long period of time in the Bristol Bay fishery.
But it might have a much larger effect on catches in those years when the river system would
have contributed a relatively larger share of total harvests. For example, if a particular river
system accounts for an average of 1% of the return on average but 10% of the return in some
years, the loss of that system would reduce catches by only 1% on average but would reduce
catches in some years by 10%. Put differently, a decline in catches from any particular river
system would increase the variability in catches in the fishery and the overall economic risk
associated with the fishery.

An inherent question here is whether 51% of the world's sockeye are caught in Bristol Bay
because that is where the fish are or because that is where the boats go? One could envision
circumstances where the boats prefer to go to areas that are more safe/convenient (more
sheltered, closer to port, etc.) and there are enough fish available there that they don't need to go
elsewhere. Is it possible that severe pollution in Bristol Bay might not necessarily result in the
total loss of 51% of the world's harvest, but rather displace it to other areas (possibly even in
another area of AK)?
146
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Bristol Bay Salmon Production and Markets

Most Bristol Bay salmon is processed into either frozen or canned salmon. Traditionally most
frozen salmon has been frozen headed and gutted (H&G) for further processing elsewhere,
particularly in Japan. However, in recent years production of frozen salmon fillets in the Bristol
Bay region has increased.

Formerly almost all Bristol Bay frozen salmon was exported to Japan as frozen headed and
gutted salmon. Over the past decade exports of frozen head and gutted salmon to Japan have
declined while exports have increased to Europe and to China (for reprocessing into fillets).
Most Bristol Bay canned salmon is exported, primarily to the United Kingdom and Canada.
Estimated Shares of Bristol Bay Sockeye Salmon Production, 2010
Fresh
10%
Canned
Roe tails
2% 6%
Frozen
fillets
12%
Canned
halves
14%
Frozen H&G
56%
Source: Estimated
from ADFG COAR
data and ADOR
Annual Alaska Salmon
Price Report data
Figure 15. Estimated Shares of Bristol Bay Sockeye Salmon Production, 2010
Bristol Bay Salmon Prices and Value

Ex-vessel prices paid to fishermen and first wholesale prices received by processors in the
Bristol Bay salmon fishery have varied widely over the past three decades, reflecting dramatic
changes in world salmon markets during this period.
147
-------
Average Ex-Vessel and Wholesale Prices of Bristol Bay Sockeye Salmon
$6.00
$0.00
Source: Alaska Department of Fish and Game
Figure 76. Average Ex-Vessel and Wholesale Prices of Bristol Bay Sockeye Salmon

Strong Japanese demand from frozen sockeye salmon drove a sharp rise in Bristol Bay salmon
prices during the 1980s. Competition from rapidly increasing farmed salmon production drove a
protracted and dramatic decline in prices between 1988 and 2001, which led to an economic
crisis in the industry. Growing world salmon demand, a slowing of farmed salmon production
growth, diversification of Bristol Bay salmon products and markets, and improvements in quality
have driven a strong recovery in prices over the past decade. Many other factors, such as
changes in wild salmon harvests, exchange rates, and global economic conditions have also
affected prices. In general, changes in ex-vessel prices paid to fishermen have reflected changes
in first wholesale prices paid to processors.

Changes in prices, harvests and production have combined to drive dramatic changes in the ex-
vessel and first wholesale value of Bristol Bay salmon over the past three decades . Adjusted for
inflation (expressed in 2010 $), the real ex-vessel value paid to fishermen fell from $359 million
in 1988 to $39 million in 2002, and rose to $181 million in 2010. The real first wholesale value
of Bristol Bay salmon production fell from $616 million in 1988 to $124 million in 2002, and
then rose to $390 million in 2010.
148
-------
700
600
Ex-Vessel and First Wholesale Value of Bristol Bay Sockeye Salmon
Harvests and Production, 1980-2010
-A-Real first
wholesale value
(2010$)
-Nominal first
wholesale value
-0-Real ex-vessel
value (2010$)
•Nominal ex-
vessel value
OOOOOOO)O)O)O)O)
O)O)O)O)O)O)O)O)
CM CM CM CM CM CM
Source: CFEC, ADFG
Figure 77. Ex-Vessel and First Wholesale Value 1980-2010
Bristol Bay Salmon Industry Employment

The number of Bristol Bay permits fished each year has varied over time depending on economic
conditions in the fishery. Over the past decades, between about 1200 and 1500 drift gillnet
permits and between about 700 and 900 set gillnet permits were fished each year.

On average, for each permit fished, about three people were engaged in fishing (the permit
holder and two crew members). The estimated total number of people working in fishing during
the Bristol Bay season ranged from about 5500 to 7100. Because most of the commercial
harvest occurs within a period of a few weeks in late June and early July, annual average
employment in the fishery is much smaller than peak employment, ranging from about 900 to
1200 over the past decade.

Over the past decade Bristol Bay fish processors employed between about 2300 and 4500
workers, with annual average employment ranging from about 360 to 760. Together, about
7,800-11,300 people worked seasonally in fishing and processing, for combined annual average
employment of 1200 to 1900.
149
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Geographic Distribution of Bristol Bay Salmon Fishery Participation and Earnings

Local residents of the Bristol Bay region account for a relatively small and declining share of
employment and earnings in the Bristol Bay salmon industry. Non-Alaska residents account for
a relatively large and growing share of employment and earnings.
Table 46. Geographic Distribution of Bristol Bay Salmon Industry Employment and
Earnings.
Geographic Distribution of Bristol Bay Salmon Industry Employment and Earnings: Selected Measures

Measure
Permit holders, drift gillnet fishery
Permit holders, set gillnet fishery
Permit holders, total
Earnings, drift gillnet fishery (2007) ($000)
Earnings, set gillnet fishery (2007) ($000)
Earnings, total (2007) ($000)
Processing workers (2009)
Processing workers' earnings (2009) ($000)
Measure by Residency
Bristol Bay
region
residents
383
353
736
$14,273
$6,989
$21,262
76
$1,000
Other
Alaska
residents
471
311
782
$25,020
$6,071
$31,091
529
$3,025
Residents
of other
states or
countries
1,009
317
1,326
$58,821
$6,840
$65,661
3,916
$27,162
Total
1,863
982
2,845
$98,115
$19,900
$118,014
4,521
$31,187
Share of Total
Bristol Bay
region
residents
21%
36%
26%
15%
35%
18%
2%
3%
Other
Alaska
residents
25%
32%
27%
26%
31%
26%
12%
10%
Residents
of other
states or
countries
54%
32%
47%
60%
34%
56%
87%
87%
Sources: Gho, Marcus, K. Iverson, C. Farrington, and N. Free-Sloan, "Changes in the Distribution of Alaska's Commercial
Fisheries Entry Permits, 1975 - 2010," CFEC Report 11-3N (2011); Permit holder earnings: Iverson, Kurt, "Permit Holdings,
Harvests, and Estimated Gross Earnings by Resident Type in the Bristol Bay Salmon Gillnet Fisheries," CFEC Rpt 09-IN (2009);
Processing workers and earnings: Alaska Department of Labor and Workforce Development estimates,
http://labor.alaska.gov/research/seafood/seafoodbristol.htm.
50%
40%
30%
Local Bristol Bay Resident Share of the Bristol Bay Salmon Fisheries:
Selected Measures
O
-------
This does not mean, of course, that the Bristol Bay salmon fishery is unimportant as a source of
jobs or income for local residents. It remains very important—but not as important as it would
be if all the jobs were held by local residents and all the income were earned by local residents.

A different perspective is that the Bristol Bay fishery is not just economically important for a
remote region of southwestern Alaska. Rather, it is of major economic importance for other
parts of Alaska and other states, particularly the Pacific Northwest. Thousands of residents of
other parts of Alaska and other states work in and earn significant income from participating in
Bristol Bay fishing and processing.

Distribution of Salmon Permits and Earnings within the Bristol Bay Region

Within the Bristol Bay region, there is wide variation in the extent to which residents of different
communities participate in and derive income from the Bristol Bay salmon fisheries. In 2010,
the number of permits held per 100 residents ranged from as high as 16 in the Bristol Bay
Borough to as low as 5 in the Upper Nushagak Region. Per capita salmon fishery earnings
ranged from more than $7000 in the Bristol Bay Borough to only $1000 in the Upper Nushagak
Region.
Table 47. Relative Indicators of 2010 Salmon Fishery Participation and Earnings.

Relative Indicators of 2010 Salmon Fishery Participation and Earnings, Bristol Bay Watershed Regions

Bristol Bay Borough
Togiak-Manokotak Region
South Bristol Bay Region
Dillingham Region
Lake Region
Upper Nushagak Region
Bristol Bay Watershed
Number of permit holders per 100 residents
Drift gillnet
fishery
6
6
10
5
3
5
5
Set gillnet
fishery
10
7
6
4
o
5
i
5
Combined
fisheries
16
13
15
9
6
5
10
Per capita salmon fishery earnings
Drift gillnet
fishery
$4,240
$2,417
$3,960
$2,623
$908
$1,002
$2,412
Set gillnet
fishery
$3,172
$2,410
$343
$1,160
$524
*
$1,407
Combined
fisheries
$7,411
$4,828
$4,302
$3,783
$1,432
$1,002
$3,819
* Confidential. Sources: U.S. Censuses, 2000 and 2010; CFEC.
Economic Measures of the Bristol Bay Salmon Industry

There are many potential economic measures of the Bristol Bay salmon industry. Which
measure is most useful depends upon the question being asked. For example, if we want to know
how the Bristol Bay salmon fishery compares in scale with other fisheries, we should look at
total harvests or ex-vessel or wholesale value. If we want to know how it affects the United
States balance of payments, we should look at estimated net exports attributable to the fishery. If
we want to know how much employment the industry provides for residents of the local Bristol
Bay region, Alaska or the United States, we should look at estimated employment in fishing and
151
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processing for residents of these regions. If we want to know the net economic value attributable
to the fishery, we should look at estimated profits of Bristol Bay fishermen and processors.
These different measures vary widely in units, in scale, and how economically "important" they
make the fishery appear.
Table 48. Selected Economic Measures of the Bristol Bay Salmon Industry, 2000-2010.

Selected Economic Measures of the Bristol Bay Salmon Industry, 2000-2010
Measure
Sockeye Salmon Havests
Millions offish
Millions of pounds
Bristol Bay harvest
volume as a share of:
Alaska sockeye salmon
World sockeye salmon
Alaska wild salmon (all species)
World wild salmon (all species)
World wild & farmed salmon
(all species)
Gross Value ($ mllions)
Ex -vessel value
First wholesale value
Total value of US exports of
Bristol Bay salmon products
Workers
Peak (July) fishing employment
Number offish processing
workers
Total
Estimated annual average
employment
Fishing
Fish processing
Total
Average permit price (S 000)
Drift gillnet fishery
Set gillnet fishery
Estimated total permit value ($
millions)
Drift gillnet fishery
Set gillnet fishery
Total
2000

21
125

61%
45%
18%
7%
3%

80
175
150

81
32

149.6
32.6
182.2
2001

14
96

56%
40%
12%
5%
2%

40
115
137

7,098
2,862
9,960

1,179
475
1,654

35
25

64.6
25.5
90.1
2002

11
65

48%
28%
10%
4%
1%

32
100
97

5,514
2,273
7,787

888
366
1,254

20
12

36.7
11.9
48.6
2003

15
93

50%
38%
13%
5%
2%

48
114
111

6,465
2,484
8,949

1,063
409
1,472

29
13

54.5
12.6
67.1
2004

26
152

59%
47%
19%
8%
3%

76
176
172

6,513
3,474
9,987

1,089
581
1,669

37
15

68.7
14.5
83.2
2005

25
155

58%
47%
16%
7%
3%

95
220
193

6,750
3,272
10,022

1,098
532
1,631

51
15

95.2
14.9
110.1
2006

28
165

69%
49%
22%
8%
3%

109
237
173

6,936
2,940
9,876

1,140
483
1,623

75
22

139.4
22.1
161.5
2007

30
173

62%
47%
18%
7%
3%

116
249
183

6,891
3,512
10,403

1,110
566
1,675

79
24

147.8
23.6
171.4
2008

28
160

71%
52%
23%
9%
3%

117
262
206

6,969
3,952
10,921

1,129
640
1,769

90
27

167.3
26.8
194.1
2009

31
183

71%
55%
25%
7%
3%

144
293
230

6,768
4,522
11,290

1,143
764
1,907

78
28

145.9
27.7
173.6
2010

29
170

74%

181
390
254

102
29

190.2
28.2
218.4
Avg.

23
140

62%
45%
18%
7%
2%

94
212
173

6,656
3,255
9,911

1,093
535
1,628

62
22

114.5
21.9
136.4
Range

11 - 31
65 - 183

48%- 74%
28%- 55%
10%- 25%
4%- 9%
1%- 3%

32 - 181
100 - 390
97 -254

5,514 -7,098
2,273 - 4,522
7,787 - 11,290

888 - 1,179
366 - 764
1,254 - 1,907

20 - 102
12 - 32

36.7 - 190.2
11.9 - 32.6
48.6 - 218.4
Economic impacts and net economic value of the Bristol Bay salmon industry are not necessarily
proportional to harvests or gross value, particularly in the short run. Put differently, economic
impacts and net economic value are disproportionately affected by changes in value. A 1%
change in harvests results in less than a 1% change in fishing and processing employment—
particularly if it is unexpected. In contrast, because many of the costs of the fishery are fixed, a
1% change in value results in more than a 1% change in profits and net economic value. For
these reasons, short term changes in future fish harvests would likely have less-than-proportional
or greater-than-proportional economic effects. Longer-term changes in fish harvests would tend
to have proportional economic effects as the scale of the fishing and processing industry changed
over time.
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Future Economic Importance of the Bristol Bay Salmon Industry

It is impossible to predict the future economic importance of the Bristol Bay salmon industry
with certainty. Historically, catches, prices and value have varied dramatically both from year to
year and over longer-term periods of time. They are likely to continue to vary.

No particular recent year or period is necessarily a good indicator of future Bristol Bay catches
and value. However, it seems likely that future catches, prices and values will fall within the
wide range experienced between 1980 and 2010.
Table 49. Distribution of Selected Economic Measures for the Bristol Bay Commercial
Salmon Fishing Industry, 1980-2010

Distribution of Selected Economic Measures for the Bristol Bay Commercial Salmon Fishing Industry, 1980-2010
Measure
Total sockeye salmon harvest (million fish)
Total sockeye salmon harvest (million pounds)
Ex-vessel price paid to fishermn ($/lb)
Average first wholesale price, frozen H&G salmon ($/lb)
Average first wholesale price, canned salmon ($/lb)
Total ex-vessel value ($ millions)
Total first wholesale value ($ millions)
Drift gillnet permit price ($ thousands)
Set gillnet permit price ($ thousands)
Estimated total permit value ($ millions)
Minimum
10.0
57.7
$0.53
$1.48
S2.21
39.3
123.9
24.3
14.7
60.0
10th
percentile
14.0
87.8
$0.61
SI. 64
$2.32
89.5
160.8
43.6
17.2
113.3
Mean
24.8
145.6
$1.31
S2.18
$3.05
184.0
324.8
180.5
54.2
375.6
90th
percentile
35.2
195.5
$2.18
$2.73
$3.86
311.8
486.2
311.6
83.6
623.6
Maximum
44.2
243.6
$3.79
$3.77
$5.72
359.2
616.5
434.7
107.2
879.5
Standard
deviation
8.8
48.8
$0.70
$0.54
$0.76
90.5
131.2
106.1
27.0
212.0
Note: All prices and values are adjusted for inflation to real 2010 dollars. 10th and 90th percentiles are interpolated. Estimated
total permit value calculated by mulltiplying average permit prices by the number of permanent permits renewed. First wholesale
prices and values are for the years 1984-2010. Data are from Alaska Department of Fish and Game and Commercial Fisheries
Entry Commission.
3.15 Appendix: Data Sources

A rich variety of data exists for the Bristol Bay commercial salmon fishery. However, the data
can be difficult and confusing to work with, for a number of reasons. Some data are not
published, and are available only upon request from Alaska state government agencies. Many
data series are available only for limited periods of time: some have been discontinued and are
not available for recent years; others have been collected or published only beginning relatively
recently and are not available for earlier years. Many data series are inconsistent: reports
published by the same agency in different years may provide different data for the same series.
Preliminary data (particularly for prices and values) are often revised later, sometimes
substantially. Some kinds of data are confidential except when aggregated for minimum
threshold numbers of permit holders, processors or other firms. Some kinds of data are
proprietary (particularly price data gathered by private market information services). Most
importantly, what data mean, how they were collected or estimated, and how reliable they are is
often unclear. For all these reasons, pulling together the variety of data presented in this report
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was a significant task, building on a variety of research conducted over many years, much of it
devoted to finding data sources and learning what they meant (and didn't mean).

The purpose of this appendix is to document, as best practical, the sources for the analysis, both
for the benefit of readers and for other researchers. The appendix provides details on the data
sources for all of the text references, graphs and tables in this report, except where the source is
obvious or reported in detail in the text.

The appendix begins with a description of the major data sources for this report (those used
multiple times), listed in alphabetical order of the names used to refer to them.

The appendix then describes the sources for all data provided in the report, text, figures and
tables, except where the source information is provided in the report or is otherwise clear. These
are listed in the chronological order in which they appear in the report.

The final section of the appendix provides the price index data used to convert selected prices
and values in the report from "nominal" dollars (not adjusted for inflation) to "real" dollars
(adjusted for inflation).

Researchers wishing more detailed information about data sources may contact Gunnar Knapp at
Gunnar.Knapp@uaa.alaska.edu or 907-786-7717.

Major Data Sources for This Report

Below are descriptions of the major data sources used in this report (those used multiple times),
listed in alphabetical order of the names used to refer to them (shown in bold font). Website
addresses were current as of October 2011 for all data found online.

ADFG Annual Run Forecasts and Harvest Projections. Each year the Alaska Department of
Fish and Game publishes a report on "Run Forecasts and Harvests Projections for Alaska Salmon
Fisheries" for the current year, which also includes a review of the salmon fisheries for the
previous season. This report includes forecasts for the coming season of commercial sockeye
salmon harvests in Bristol Bay. The reports for the most recent years are available at the
"Commercial Salmon Fisheries Forecasts" website:

http://www.adfg.alaska.gov/index.cfm?adfg=commercialbvfisherysalmon.salmonforecast

Reports for earlier years available on the Alaska Department of Fish and Game "Fishing and
Subsistence" Publications Searchable Database at:

http ://www. adfg. alaska. gov/sf/publications/

To find them, search for the following: Report = All Reports; Field = Title; Operator =
Contains; Search String = Forecast. Then scroll through several pages out output until you
come to "Commercial Fisheries Reports."
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ADFG Bristol Bay Annual Management Reports. These are detailed reports for each salmon
season compiled by Alaska Department of Fish and Game Division of Commercial Fisheries
Bristol Bay area management staff. Each report also contains an extensive data appendix with
dozens of tables of catches and escapements by district, day, gear type, etc. The reports are
available on the Alaska Department of Fish and Game "Fishing and Subsistence" Publications
Searchable Database at:

http ://www. adfg. alaska. gov/sf/publications/

To find them, search for the following: Report = Commercial Fisheries Annual Management
Reports; Field = Title; Operator = Contains; Search String = Bristol Bay.

ADFG Bristol Bay Salmon Season Summaries. These are news releases prepared by compiled
by Alaska Department of Fish and Game Division of Commercial Fisheries Bristol Bay area
management staff after each Bristol Bay salmon season after each salmon season which
summarize catches and preliminary ex-vessel price information. The news releases are available
on the ADFG Bristol Bay website at:

http://www.cf.adfg.state.ak.us/region2/fmfish/salmon/salmhom2.php

ADFG Commercial Operator Annual Report (COAR) Data. In April of every year, all
Alaska fish processors are required to submit "Commercial Operator Annual Reports" to the
Alaska Department of Fish and Game. In these reports they are required to report the total
volume offish purchased, by species and area; the total amount paid for fish purchased, by
species and area; the total volume (weight) of production, by product, species and area; and the
total first wholesale value of production. Information about the COAR reporting forms is at:

http://www.adfg.alaska.gov/index.cfm?adfg=fishlicense.coar

The COAR data are not posted on the internet or published regularly by ADF&G (which is
unfortunate), but are available by special request from ADF&G. The data used for this report
were provided on August 2, 2011 to Gunnar Knapp and were saved as Excel file "Statewide and
regional COAR production 1984-2011 provided by ADFG 8-2-1 l.xls." Average "first wholesale
prices" were calculated by dividing first wholesale value by production volume.

ADFG Alaska Commercial Salmon Harvests and Exvessel Values Reports. These reports
provide summary annual data for each of 11 Alaska salmon harvest areas. The data include
average fish weight, average price per pound, numbers offish, harvest volume in pounds, and
estimated value in dollars. Prices for the most recent year are generally preliminary estimates
based on fish tickets and reports from area managers. Prices for earlier years are generally based
on "Commercial Operators Annual Report and area staff reports." The reports are available at:

http://www.adfg.alaska.gov/index.cfm?adfg=commercialbyfisherysalmon.salmoncatch

ADFG Salmon Ex-Vessel Price Time Series by Species 1984-2008. This is a two-page table
of ex-vessel prices by species, 1984-2008, for the following areas: Cook Inlet, Kodiak, Alaska

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Peninsula, Bristol Bay, Prince William Sound, Southeast, and Statewide. Original source is cited
as the Commercial Operator Annual Reports database.
http ://www. cf. adfg. state. ak.us/geninfo/fmfish/salmon/catchval/blusheet/84-08exvl .pdf

ADLWD Bristol Bay Region Fishing and Seafood Industry Data. The Alaska Department of
Labor and Workforce Development (ADLWD) Research and Analysis Division posts a variety
of economic information for the Bristol Bay Seafood Industry on its "Bristol Bay Region Fishing
and Seafood Industry Data" website at:

http://labor.alaska.gov/research/seafood/seafoodbristol.htm.

ADOR Annual Salmon Price Reports. Every year, "large" Alaska salmon processors (those
with sales exceeding 1 million pounds in the previous calendar year) are required to report sales
volumes and first wholesale values for major salmon product categories to the Alaska
Department of Revenue. Annual statewide summary reports of these data are available on the
Alaska Department of Revenue's Tax Division Reports website at:

http://www.tax.alaska.gOv//programs/reports.aspx

Once on this page, click on "Alaska Salmon Price/Production." Note that the "Annual Salmon
Price Reports" differ from (and sometimes are inconsistent with the "Annual Salmon Production
Reports" and "Monthly Salmon Price Reports" which are also available at the same website.

ADOR Canned Salmon Wholesale Price Reports. For many years prior to 2001, the Alaska
Department of Revenue prepared "Canned Salmon Average Wholesale Reports." These reported
monthly statewide average prices for canned salmon, by species, compiled from information
reported by Alaska salmon processors. The University of Alaska Anchorage Institute of Social
and Economic Research (ISER) maintains a collection of these reports beginning with the period
April l-September30, 1983.

ADOR Monthly Salmon Price Reports. Every four months, "large" Alaska salmon processors
(those with sales exceeding 1 million pounds in the previous calendar year) are required to
submit salmon price reports to the Alaska Department of Revenue for the following four-month
periods: January-April, May-August, and September-December.
The reports include sales volumes and first wholesale values for major salmon product, by area
and month. Summaries of the data from these reports, for each four-month period, are available
on the Alaska Department of Revenue's Tax Division Reports website at:

http://www.tax.alaska.gOv//programs/reports.aspx.

Once at this page, click on "Alaska Salmon Price/Production." Note that these "Monthly Salmon
Price Report" differ from (and sometimes are inconsistent with the "Annual Salmon Price
Reports" and the "Annual Salmon Production Reports" which are also available at the same
website. Data are not reported for product-area-month combinations for which fewer than three
processors reported sales.
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CFEC Basic Information Tables. The Commercial Fisheries Entry Commission (CFEC) posts
"Basic Information Tables" for each Alaska salmon fishery on its website at:

http ://www. cfec. state. ak.us/bit/MNUS ALM.htm

These tables provide a useful summary of trends since 1975 in each salmon fishery for numbers
of permits issued/renewed, numbers of permits fished, total pounds harvested, average pound
harvested, gross earnings, average earnings, and average annual permit prices. The most recent
data currently available are for 2010.

CFEC Data for Alaska Salmon Harvests 1980-2005. 1980-2005: CFEC Alaska Salmon
Summary Data 1980-2005 061113. These are Commercial Fisheries Entry Commission data for
Alaska commercial salmon harvest (number offish, pounds, earnings, and price), by species, for
the years 1980-2005. This file was prepared by the Commercial Fisheries Entry Commission on
March 31, 2005 in response to a request by Professor Gunnar Knapp of the University of Alaska
Anchorage Institute of Social and Economic Research (ISER). The data was provided as an
Excel file named SWPrices.xls, containing the worksheet of this file named "Original data."
Professor Knapp maintains a copy of the file named "CFEC_Alaska_Salmon_Summary_Data
_1980-2005.xls." The data were calculated from CFEC fish ticket database. The harvest and
earnings figures include set and drift gill net, test fishing, confiscated and educational permit
harvests, and any other harvest where the product was sold.

CFEC Data for Bristol Bay Salmon Harvests 1975-2003. These are Commercial Fisheries
Entry Commission data for Bristol Bay commercial salmon harvests for the years 1975-2003,
provided by Kurt Iverson, June 9, 2004, as file BBayEarnHarvl.xls. The data were calculated
from CFEC fish ticket database. The harvest and earnings figures include set and drift gill net,
test fishing, confiscated and educational permit harvests, and any other harvest where the product
was sold.

CFEC Quartile Tables. The Commercial Fisheries Entry Commission (CFEC) posts annual
"Quartile Tables" for each Alaska salmon fishery on its website at:

http://www.cfec.state.ak.us/quartile/mnusalm.htm

These tables show the number of permit holders and average earnings per permit holder in each
"quartile group"—calculated by ranking permit holdings in each year by earnings, and then
dividing them into four "quartile" groups with equal total earnings. The first quartile has the
smallest number of permit holders with the highest average earnings; the fourth quartile has the
highest number of permit holders with the lowest average earnings.

CFEC Permit and Fishing Activity Data. The Commercial Fisheries Entry Commission
(CFEC) posts annual data on permit and fishing activity by year, state, census area and Alaska
city on its website at:

http://www.cfec.state.ak.us/fishery statistics/earnings.htm
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For each state, census area and city in which permit holders reside, and for each fishery for
which residents held permits, data include the number of permits issued, number of permit
holders, number of permits with recorded landings, total pounds landed and estimated gross
earnings. Earnings data are confidential for fisheries in which fewer than four permit holders in a
census area or community had landings.

FAO FishstatJ Database. FAO FishstatJ is software for fishery statistical time series developed
by the Food and Agricultural Organization of the United Nations (FAO) Fisheries and
Aquaculture Department, based in Rome. The software is designed to be used with global
datasets for capture (wild) fisheries catches and aquaculture production, by species, country and
year. The software and the global datasets can be downloaded from the FAO Fisheries and
Aquaculture Department website at:

http://www.fao.org/fi shery/stati stics/software/fi shstatj /en

NMFS Commercial Fishery Landings Database. The National Marine Fisheries Service
(NMFS) Office of Science and Technology maintains an online database of US Commercial
Fishery Landings (volume and value) by state, species and year. Customized datasets for Alaska
and other states may be downloaded from NMFS Commercial Fishery Landings webite at:

http://www.st.nmfs.noaa.gov/stl/commercial/index.html

NMFS Foreign Trade in Fisheries Products Data. The National Marine Fisheries Service
posts very detailed data online about U.S. exports and imports of fisheries products at:

http://www.st.nmfs.noaa.gov/stl/trade/

The export data in this report were calculated from the "Monthly Trade Data by Product,
Country/Association" option at this website.

NMFS Major Ports Data. The National Marine Fisheries Service publishes an annual report
entitled Fisheries of the United States which provides a wide variety of useful data on United
States fisheries. A regular table in this report (on page 7 in recent years), entitled "Commercial
Fishery Landings and Value at Major U.S. Ports," lists the value and volume of landings for the
top 50 United States ports (ranked by value). The Fisheries of the United States reports are
available at:

http://www.st.nmfs.noaa.gov/stl/publications.html

Data Sources for Report Text, Figures and Tables

Below are descriptions of the sources for data provided in the report text, figures and tables.
Except where text sources are given below, the data in the text is from the same sources as the
adjacent figures and tables in the same sections of the report. Except where text sources are
given below, all of the material discussed in the "Overview" and "Summary" sections of the
report is discussed in greater detail in corresponding sections of the report. Refer to the body of

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the report for more details as well as sources for information presented in the "Overview" and
"Summary" sections.

Page 52. "Annual harvests of 31 million salmon ..." Source: ADFG Alaska Commercial
Salmon Harvests and Exvessel Values Reports.

Page 52. "57% of world sockeye salmon harvests. " Source: See discussion below of sources
for Figure 22 (World Sockeye Supply).

Page 52. "Annual ex-vessel" value to fishermen of $129 million. " Source: ADFG Alaska
Commercial Salmon Harvests and Exvessel Values Reports.

Page 52. "Annual first wholesale value . . . of $268 million." ADFG Commercial Operator
Annual Report (COAR) Data.

Page 52. "26% of the ex-vessel value ..." Source: ADFG Alaska Commercial Salmon
Harvests and Exvessel Values Reports.

Page 52. "Seasonal employment of more than 6800 fishermen and 3 700 processing workers. "
Source: See sources for Table 36, page 112.

Figure 11. Bristol Bay Commercial Salmon Harvests. Sources: 1975-2003: CFEC Data for
Bristol Bay Salmon Harvests; 2004-2010: ADFG Alaska Commercial Salmon Harvests and
Exvessel Values Reports; 2011: ADFG 2011 Bristol Bay Salmon Season Summary (9/26/2011).

Page 57. "The average weight of a Bristol Bay sockeye salmon is typically about 6 pounds. . . .
average weights varied from as low as 5.3 pounds to as high as 6.7 pounds. " Data sources are
the same as for Figure 11.

Figure 12. Bristol Bay Fishing Districts. Average annual harvests for the years 1991-2010 were
calculated from the same data used for Figure 13.

Figure 13. Bristol Bay Commercial Sockeye Salmon Harvests, by District. Sources: 1986-1989:
ADFG Bristol Bay Annual Salmon Management Report, 2006, Appendix A3 .-Sockeye salmon
commercial catch by district, in numbers offish, Bristol Bay, 1990-2010; 1990-2010: ADFG
Bristol Bay Annual Salmon Management Report, 2010, Appendix A3.-Sockeye salmon
commercial catch by district, in numbers offish, Bristol Bay, 1990-2010. 2011: ADFG Bristol
Bay Salmon Season Summary, 2011.

Figure 14. Share of Bristol Bay Commercial Sockeye Salmon Harvest, by District. Same
sources as for Figure 13.

Figure 15. Naknek-Kvichak District Sockeye Salmon Harvests, by River of Origin. Compiled
from ADFG Bristol Bay Annual Management Reports for each year (usually tables 18, 19 or 20).
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Table 27. Comparison of Bristol Bay Drift Gillnet and Set Gillnet Fisheries (2006-10 Averages).
Source: CFEC Basic Information Tables.

Figure 16. Bristol Bay Salmon Harvests, by Fishery. Source: CFEC Basic Information Tables.

Figure 17. World Sockeye Salmon Supply. Bristol Bay: Sources are the same as for Figure 16.
Other Alaska: Calculated by subtracting Bristol Bay data from Alaska data. Alaska data: 1980-
2005: CFEC Data for Alaska Salmon Harvests 1980-2005; 2006-2009: ADFG Alaska
Commercial Salmon Harvests and Exvessel Values Reports. Lower 48: NMFS Commercial
Fishery Landings Database, data for Washington, Oregon and California; Canada, Russia and
Japan: FAO FishstatJ Database.

Figure 18. Alaska Salmon Supply. Bristol Bay sockeye: Sources are the same as for Figure 11.
Other Alaska sockeye: Calculated by subtracting Bristol Bay data from Total Alaska data. Total
Alaska data: 1980-2005: CFEC Data for Alaska Salmon Harvests 1980-2005; 2006-2009:
ADFG Alaska Commercial Salmon Harvests and Exvessel Values Reports.

Figure 19 World Salmon and Trout Supply. Wild salmon: Sources are the same as for Figure 17.
Farmed salmon and farmed trout: FAO FishstatJ Database. Includes only farmed production of
Atlantic, Coho and Chinook salmon. Includes only farmed rainbow trout farmed in a
"mariculture" (saltwater) environment.

Figure 20. Bristol Bay Sockeye Preseason Projection and Annual Commercial Catch. Preseaon
Projections: 1990-2005: ADFG Bristol Bay Annual Management Reports; Beginning 2006:
ADFG Annual Run Forecasts and Harvest Projections. Actual harvests: same sources for Figure
11.

Figure 21 Bristol Bay Sockeye Salmon Harvests, 1895-2009. 1893:-1997: Byerly, Mike;
Beatrice Brooks, Bruce Simonson, Herman Savikko and Harold Geiger. 1999. Alaska
Commercial Salmon Catches, 1878-1997. Alaska Department of Fish and Game Regional
Information Report No. 5 J99-05. March 1999. 1998-2003: CFEC Data for Bristol Bay Salmon
Harvests 1975-2003. 2004-2011: ADFG Alaska Commercial Salmon Harvests and Exvessel
Values Reports.

Figure 22. Bristol Bay Sockeye Salmon Production. ADFG Commercial Operator Annual Report
(COAR) Data.

Figure 23. Share of Sockeye Salmon Production in Bristol Bay. ADFG Commercial Operator
Annual Report (COAR) Data.

Table 28. Sales of Selected Sockeye Salmon Products by Major Bristol Bay Salmon Processors.
ADOR Annual Salmon Price Reports.

Figure 24. Bristol Bay Sockeye Salmon Harvests and Production. Harvests: See sources for
Figure 11. Production: ADFG Commercial Operator Annual Report (COAR) Data.
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Figure 25. Monthly Sale Volume of Bristol Bay Salmon Products. ADOR Monthly Salmon
Reports

Figure 26. Alaska Frozen Sockeye Production and U.S. Frozen Sockeye Exports. ADFG
Commercial Operator Annual Report (COAR) Data; NMFS Foreign Trade in Fisheries Products
Data.

Figure 27. Estimated End-Markets for Alaska Frozen Sockeye Salmon. Sources: ADFG
Commercial Operator Annual Report (COAR) Data; NMFS Foreign Trade in Fisheries Products
Data. The estimates for the "USA" were calculated by subtracting exports from Alaska
production as reported in the COAR data. For the years 1989-1992 reported exports exceeded
reported Alaska production. The estimate for the USA was assumed to be zero for these years.
This is almost certainly an underestimate. In reality, some frozen sockeye production
undoubtedly went to the US market, but the production and export data suggest that the amount
going to the US market was relatively low, with most of the production being exported.

Figure 28. Alaska Canned Sockeye Production and U.S. Canned Sockeye Exports. Sources:
ADFG Commercial Operator Annual Report (COAR) Data; NMFS Foreign Trade in Fisheries
Products Data.

Figure 29. Average Ex-Vessel Price of Bristol Bay Sockeye Salmon. See data sources for Figure
11. Real prices calculated using Anchorage CPI, as discussed below.

Figure 30. Average Wholesale and Ex-Vessel Prices of Bristol Bay Sockeye Salmon. Ex-vessel
prices: See data sources for Figure 11. Wholesale Prices: ADFG Commercial Operator Annual
Report (COAR) Data.

Figure 31. Average Monthly First Wholesale Prices. Sources: ADOR Monthly Salmon Price
Reports

Figure 32. Average Wholesale and Ex-Vessel Prices, Bristol Bay and Rest of Alaska. Rest-of-
Alaska wholesale and ex-vessel prices were calculated by dividing Rest -of -Alaska value by
Rest-of-Alaska volume. Rest-of-Alaska wholesale value and volume were calculated by
subtracting Bristol Bay wholesale value and volume from total Alaska wholesale value and
volume, as reported in ADFG Commercial Operator Annual Report (COAR) Data. Rest-of-
Alaska ex-vessel value and volume were calculated by subtracting Bristol Bay ex-vessel value
and volume (from sources for Figure 16, page 61) from total Alaska ex-vessel value and volume.
Sources for total Alaska ex-vessel value and volume were: 1980-2005: CFEC Data for Alaska
Salmon Harvests 1980-2005; 2006-2009: ADFG Alaska Commercial Salmon Harvests and Ex
vessel Values Reports.

Figure 33. Average Ex-Vessel Prices of Sockeye Salmon, Selected Alaska Areas. Sources:
ADFG Alaska Commercial Salmon Harvests and Exvessel Values Reports.

Figure 34. Japanese Red-Fleshed Salmon Imports, May-April. Sources: Japanese monthly
import data reported in Bill Atkinson's News Report (a weekly compilation of articles and

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information from the Japanese seafood industry press, translated into English, published until
2006 by industry analyst Bill Atkinson) and Japanese import data reported on the National
Marine Fisheries Service "Fishery Market News" website at:
http ://www. st. nmfs .noaa. gov/st 1/market_news/index .html.

Figure 35. Japanese Red-Fleshed Frozen Salmon Imports & Wild Sockeye Wholesale Prices.
Japanese red-fleshed salmon imports are data for May-April, from the same sources as for Figure
34. Sockeye wholesale price data are average prices for the period May-April, from the same
sources as for Figure 36.

Figure 36. Japanese Wholesale Prices and Bristol Bay Prices for Sockeye Salmon. Source for
ex-vessel price: see sources for Figure 11. Source for average first wholesale price: ADFG
Commercial Operator Annual Report (COAR) Data. Sources for Japanese monthly wholesale
prices: January 1980-December 1989: Tokyo Central Wholesale Market reports, average price
for all frozen sockeye. January 1990-April 2002. Suisan Tsushin (Seafood News), Marine
Products Power Data Book, 2002. Beginning May 2002: Japanese frozen market salmon prices
posted on www.fis.com and the predecessor "Seaworld" website (data are prices reported for the
first day of the month). Monthly wholesale prices in yen/kilo converted to prices in $/lb using
monthly Japanese exchange rate data reported on the website of the Federal Reserve Bank of St.
Louis (series EXJPUS, available at: http://research.stlouisfed.org/fred2/series/EXJPUS).

Figure 37. Average United States Import Prices of Selected Farmed Salmon Products. Source:
NMFS Foreign Trade in Fisheries Products data.

Figure 38. U.S. Wholesale Prices for Selected Wild and Farmed Salmon Products. Prices are
from Urner Barry's Seafood Price-Current, a twice-weekly market report for U.S. seafood
wholesale prices. Data shown in the figure are "low" reported prices for the first reporting date
of the month. Products are as follows: "Fresh farmed Atlantic, whole fish": Northeast,
Domestic and Canadian Atlantic, 6-8 Ibs; "Fresh farmed Atlantic, pinbone-out fillets": Fob
Miami, Chilean Atlantic Fillets, Scale-on/Standard, C Trim/Premium,Pinbone out, 2-3 Ibs;
"Frozen H&G wild sockeye": Red/Sockeye, Gillnet, 4-6 Ibs. Information on Seafood Price-
Current is at www.urnerbarry.com.

Figure 39. Monthly Average Wholesale Case Prices for Alaska Canned Sockeye Salmon. Data
through August 2000: ADOR Canned Salmon Wholesale Price Reports (statewide data for
canned sockeye salmon). Data beginning September 2000: ADOR Monthly Salmon Price
Reports (data for Bristol Bay canned sockeye salmon).

Figure 40. Estimated Chilled and Unchilled Shares of Bristol Bay Salmon Harvests. Northern
Economics, 2010 Bristol Bay Processor Survey. Prepared for Bristol Bay Regional Seafood
Development Association, February 2011. Available at:
http://www.bbrsda.com/layouts/bbrsda/files/documents/
bbrsda_reports/BB-RSDA%202010%20Survey%20Final%20Report.pdf
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Figure 41. Ex-Vessel and First Wholesale Value of Bristol Bay Sockeye Salmon Harvests and
Production, 1984-2010. Ex-vessel value: Same data sources as for Figure 11. Wholesale value:
ADFG Commercial Operator Annual Report (COAR) Data.

Figure 42. Distribution of Nominal Value of Bristol Bay Sockeye Salmon. Sources for ex-vessel
value and wholesale value are the same as for Figure 46, page 94. Value to processors after
deducting payments to fishermen was calculated by subtracting ex-vessel value from wholesale
value.

Figure 43. Distribution of Value of Bristol Bay Sockeye Salmon. Calculated from data used for
Figure 42.

Figure 44. Number of Limited Entry Permits Issued and Fished in Bristol Bay. Source: CFEC
Basic Information Tables.

Figure 45. Average Gross Earnings of Bristol Bay Drift Gillnet Permit Holders, by Quartile.
Source: CFEC Quartile Tables.

Figure 46. Average Gross Earnings of Bristol Bay Set Gillnet Permit Holders, by Quartile.
Source: CFEC Quartile Tables.

Figure 47. Average Prices Paid for Bristol Bay Limited Entry Permits. Source: CFEC Basic
Information Tables.

Figure 48. Average Permit Prices and Total Earnings: Bristol Bay Drift Gillnet Fishery. Source:
CFEC Basic Information Tables.

Figure 49. Average Permit Prices and Total Earnings: Bristol Bay Drift Gillnet Fishery. Source:
CFEC Basic Information Tables.

Figure 51. Number of Companies Reporting Salmon Production in Bristol Bay, by Product.
Source: ADFG Commercial Operator Annual Report (COAR) Data.

Figure 52. Selected Bristol Bay Salmon Processor Costs, 2001-2009. "Cost of labor" data are
ADLWD Bristol Bay Region Fishing and Seafood Industry Data. They are from the column
titled "Seafood Processing Wages" in a table named "Bristol Bay Region Seafood Industry 2003-
2009" (as well as earlier versions of the same table no longer posted online) posted at:

http://labor.alaska.gov/research/seafood/BristolBay/BBoverall.pdf

The data are also accessible by clicking on "Harvesting and Processing Workers and Wages" at
the ADLWD Bristol Bay Region Fishing and Seafood Industry Data website. "Cost offish" are
ex-vessel values from the same data sources as Figure 11. "Other costs and profits" were
calculated by subtracting "cost of labor" and "cost offish" from wholesale value, as reported in
ADFG Commercial Operator Annual Report (COAR) Data.
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Figure 54. Monthly Employment in Food Manufacturing, Bristol Bay Region, 2002-2007.
Alaska Department of Labor and Workforce Development, Quarterly Census of Employment
and Wages Data, historical data for 2002-2010, Excel file annual.xls, downloaded November 27,
2011 from:

http://labor.alaska.gov/research/qcew/qcew.htm

Table 34. Selected Data and Estimates for Bristol Bay Taxes. Ex-vessel value of Bristol Bay
salmon harvests: see data sources for Figure 11. Canned and non-canned share of production:
ADFG Commercial Operator Annual Report (COAR) Data.

Figure 56. Number of Bristol Bay Permit Holders by Residency. Source: Gho, Marcus, K.
Iverson, C. Farrington, and N. Free-Sloan, Changes in the Distribution of Alaska's Commercial
Fisheries Entry Permits, 1975 - 2010, CFEC Report 11-3N (2011), Appendix C. Available at:

http://www.cfec.state.ak.us/RESEARCH/12-lN/12-lN.htm

Figure 57. Permit Holders Average Earnings, by Residency. Source: Kurt Iverson, CFEC
Permit Holdings, Harvests, and Estimated Gross Earnings by Resident Type in the Bristol Bay
Salmon Gillnet Fisheries, CFEC Report 09-IN (February, 2009). Available at:

http://www.cfec.state.ak.us/RESEARCH/09 IN/09 IN.pdf.

Figure 58. Share of Total Earnings of Bristol Bay Drift Gillnet Permit Holders, by Residency.
Same source as for Figure 57.

Figure 58. Share of Total Earnings of Bristol Bay Set Gillnet Permit Holders, by Residency.
Same source as for Figure 57.

Figure 60. Share of Bristol Bay Seafood Processing Employment, by Residency. Source:
ADLWD Bristol Bay Region Fishing and Seafood Industry Data, posted at:

http://labor.alaska.gov/research/seafood/seafoodbristol.htm

In particular, see the following tables:

(A) "Bristol Bay Region Seafood Industry, 2003-2009, Processing" at:
http://labor.alaska.gov/research/seafood/BristolBay/BBSFPOver.pdf

(B) "Local Seafood Processing Workforce, 2003-2009, Bristol Bay Region" at:
http://labor.alaska.gov/research/seafood/BristolBay/BBSFPLocal.pdf

The number and percentage of residents of other states or countries was calculated from data in
(A). The number and percentage of Bristol Bay residents was calculated from data in (B). The
share of "Other Alaska residents" was calculated as the residual.
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Figure 61. Local Bristol Bay Resident Share of Salmon Fisheries: Selected Measures. Source
for local resident share of total permits held: Gho, Marcus, K. Iverson, C. Farrington, and N.
Free-Sloan, Changes in the Distribution of Alaska's Commercial Fisheries Entry Permits, 1975 -
2010, CFEC Report 11-3N (2011), Appendix C. Available at:

http://www.cfec.state.ak.us/RESEARCH/12-lN/12-lN.htm

Source for local resident share of total earnings: Iverson, Kurt, CFEC Permit Holdings,
Harvests, and Estimated Gross Earnings by Resident Type in the Bristol Bay Salmon Gillnet
Fisheries, CFEC Report 09-1N (2009). Available at:

http://www.cfec.state.ak.us/RESEARCH/09 IN/09 IN.pdf

Source for local resident share of processing employment: Alaska Department of Labor and
Workforce Development, "Local Seafood Processing Workforce, 2003-2009, Bristol Bay
Region," available at:

http://labor.alaska.gov/research/seafood/BristolBay/BBSFPLocal.pdf
Table 37. Population, Permit Holders, and Salmon Earnings, by Community: 2000 & 2010.
Source for population: U.S. Census, 2000 and 2010, in "Alaska Population Estimates by
Borough, Census Area, City and Census Designated Place (CDP), 2000-2011," Excel
spreadsheet available on website of Alaska Department of Labor and Workforce Development,
Research and Analysis Division at:

http://labor.alaska.gov/research/pop/popest.htm

Source for numbers of permit holders and earnings: CFEC Permit and Fishing Activity Data.

Figure 63. Estimated Bristol Bay Population, by Area and Region. Data for 2000-2010 are from
"Alaska Population Estimates by Borough, Census Area, City and Census Designated Place
(CDP), 2000-2011," Excel spreadsheet available on website of Alaska Department of Labor and
Workforce Development, Research and Analysis Division, at:

http://labor.alaska.gov/research/pop/popest.htm

Data for 1984-1999 are from Northern Economics, The Importance of the Bristol Bay Salmon
Fisheries to the Region and its Residents, Report prepared for the Bristol Bay Economic
Development Corporation (October 2009), Tables A1-A12.

Figure 63 [TOP FIGURE]. Estimated Bristol Bay Population, by Area. Data for 2000-2010 are
from "Alaska Population Estimates by Borough, Census Area, City and Census Designated Place
(CDP), 2000-2011," Excel spreadsheet available on website of Alaska Department of Labor and
Workforce Development, Research and Analysis Division. Data for 1984-1999 are from
Northern Economics, The Importance of the Bristol Bay Salmon Fisheries to the Region and its
Residents, Report prepared for the Bristol Bay Economic Development Corporation (2009),
Tables A1-A12.
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Figure 63 [BOTTOM FIGURE]. Estimated Population by Region. Data for 2000-2010 are from
"Alaska Population Estimates by Borough, Census Area, City and Census Designated Place
(CDP), 2000-2011," Excel spreadsheet available on website of Alaska Department of Labor and
Workforce Development, Research and Analysis Division. Data for 1984-1999 are from
Northern Economics, The Importance of the Bristol Bay Salmon Fisheries to the Region and its
Residents, Report prepared for the Bristol Bay Economic Development Corporation (2009),
Tables A1-A12.

Figure 65 [TOP FIGURE]. Number of Drift Gillnet Holders, by Region. Source: CFEC Permit
and Fishing Activity Data.

Figure 65 [BOTTOM FIGURE]. Number of Drift Gillnet Holders per 100 Residents, by Region.
Calculated by dividing data for number of drift gillnet holders, shown in Figure 65 [TOP
FIGURE], by data for estimated population by region, from the same sources as for Figure 63
[BOTTOM FIGURE].

Figure 67 [TOP FIGURE]. Number of Set Gillnet Holders, by Region. Source: CFEC Permit
and Fishing Activity Data.

Figure 67 [BOTTOM FIGURE]. Number of Set Gillnet Holders per 100 Residents, by Region.
Calculated by dividing data for number of set gillnet holders, shown in Figure 67 [TOP
FIGURE], by data for estimated population by region, from the same sources as for Figure 63
[BOTTOM FIGURE].

Table 38. Salmon Permit Holders per 100 Residents, by Community. Calculated by dividing
data for number of permit holders by community, from CFEC Permit and Fishing Activity Data,
by data for population by community, from the same sources as for Figure 63 [BOTTOM
FIGURE].

Figure 69 [TOP FIGURE]. Total Salmon Fishery Earnings, by Region. Source: CFEC Permit
and Fishing Activity Data.

Figure 69 [BOTTOM FIGURE]. Per Capita Salmon Fisheries Earnings, by Region. Calculated
by dividing data for total salmon fisheries earnings, shown in Figure 69 [TOP FIGURE], by data
for estimated population by region, from the same sources as for Figure 63 [BOTTOM
FIGURE].

Table 39. Bristol Bay Salmon Fishery Earnings, by Community, 2000 and 2010. Calculated by
dividing data for salmon fishery earnings by community, from CFEC Permit and Fishing
Activity Data, by data for population by community, from the same sources as for Figure 63
[BOTTOM FIGURE].

Table 40. Economic Measures of Bristol Bay Salmon Industry: Sockeye Salmon Harvests.
Same sources as for Figure 11, Figure 17, Figure 18 and Figure 19.
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Figure 70. Bristol Bay Commercial Salmon Harvests. Same sources as for Figure 16.

Table 41. Economic Measures of Bristol Bay Salmon Industry: Sockeye Value. Source for ex-
vessel value is the same as for Figure 11. Source for first wholesale value is ADFG Commercial
Operator Annual Report (COAR) Data. Source for Bristol Bay ex-value used in calculation of
Bristol Bay sockeye salmon shares of value is the same as for Figure 11. Source of Alaska wild
salmon ex-vessel value used to calculate Bristol Bay share of Alaska wild salmon ex-vessel
value is the same as for Alaska data for Figure 17. World wild salmon harvest value estimated
by multiplying world wild salmon harvests (from the same sources as for Figure 17) by Alaska
average ex-vessel prices (from the same sources as for Figure 17). Source for United States Fish
and Shellfish Landed Value is NMFS, Fisheries of the United States, various years, available at:

http://www.st.nmfs.noaa.gov/stl/publications.html

Source for "Rank of Naknek-King Salmon among U.S. ports in annual landed value" is NMFS
Major Ports Data.

Figure 71. Ex-Vessel and Wholesale Value of Bristol Bay Sockeye Salmon. Same sources as
for Figure 46.

Table 41. Economic Measures of the Bristol Bay Salmon Industry: Export Value. Source for
U.S. export value is NMFS Foreign Trade in Fisheries Products Data. Source for estimated share
of Bristol Bay sockeye in total Alaska sockeye salmon harvests is the same as for Figure 18.
Source for first wholesale value of sockeye salmon roe production is ADFG Commercial
Operator Annual Report (COAR) Data.

Figure 72. Estimated Value of US Exports of Bristol Bay Salmon Products. Same sources as for
Table 41.

Table 43. Economic Measures of the Bristol Bay Salmon Industry: Employment. Source for
estimated peak employment and estimated annual average employment is Table 43. Source for
Alaska totals used to calculate Bristol Bay share is the Alaska Department of Labor and
Workforce Development (ADLWD) Research and Analysis Division website for "Statewide
Data, Fishing and Seafood Industry" at:

http://labor.alaska.gov/research/seafood/seafoodstatewide.htm

Table 44. Economic Measures of the Bristol Bay Salmon Industry: Permit Prices and Values.
Source for permits issued and permit prices is CFEC Basic Information Tables.

Figure 74. Bristol Bay Commercial Salmon Harvests. Same sources as for Figure 11.

Table 45. Distribution of Harvests for Bristol Bay Fishing Districts. See the data sources for
Figure 13 for the sources for harvests by district used to calculate the distribution data shown in
the table.
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Figure 75. Estimated Shares of Bristol Bay Sockeye Salmon Production, 2010. Frozen, Canned,
Fresh and Roe share estimated from ADFG Commercial Operator Annual Report (COAR) Data.
Frozen fillet and frozen H&G shares and canned tails and canned halves shares estimated from
the shares of these products in frozen production and canned production reported in ADOR
Annual Salmon Price Reports.

Figure 76. Average Ex-Vessel and Wholesale Prices of Bristol Bay Sockeye Salmon. Same
sources as for Figure 30.

Figure 77. Ex-Vessel and First Wholesale Value of Bristol Bay Sockeye Salmon Production,
1980-2010. Same sources as for Figure 41.

Figure 78. Local Bristol Bay Resident Share of Bristol Bay Salmon Fisheries: Selected
Measures. Same sources as for Figure 61.

Table 47. Relative Indicators of 2010 Salmon Fishery Participation and Earnings, Bristol Bay
Watershed Region. Calculated from data in Table 37.

Table 48. Selected Economic Measures of the Bristol Bay Salmon Industry. Selected data from
Table 40-Table 44.

Table 49. Distribution of Selected Economic Measures for the Bristol Bay Commercial Salmon
Fishing Industry. Sources for distribution calculations are as follows: Harvest, ex-vessel price,
and ex-vessel value: Same data sources as for Figure 11. First wholesale prices and first
wholesale value: ADFG Commercial Operator Annual Report (COAR) Data. Permit prices and
estimated permit value: CFEC Basic Information Tables.
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Price Index Data for Converting from Nominal Dollars to Real Dollars

The Anchorage Consumer Price Index (CPI) was used to convert selected "nominal" price and
value data (not adjusted for inflation) presented in this report to "real" price and value data
(adjusted for inflation).

Anchorage and US Consumer Price Indexes
Year
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
Anchorage CPI
85.500
92.400
97.400
99.200
103.300
105.800
107.800
108.200
108.600
111.700
118.600
124.000
128.200
132.200
135.000
138.900
142.700
144.800
146.900
148.400
150.900
155.200
158.200
162.500
166.700
171.800
177.300
181.237
189.497
191.744
195.144
201.427

US CPI
82.400
90.900
96.500
99.600
103.900
107.600
109.600
113.600
118.300
124.000
130.700
136.200
140.300
144.500
148.200
152.400
156.900
160.500
163.000
166.600
172.200
177.100
179.900
184.000
188.900
195.300
201.600
207.342
215.303
214.537
218.056
224.939
Adjustment factor to convert to
2010 dollars using:
Anchorage CPI
2.282
2.112
2.004
1.967
1.889
1.844
1.810
1.804
1.797
1.747
1.645
1.574
1.522
1.476
1.446
1.405
1.368
1.348
1.328
1.315
1.293
1.257
1.234
1.201
1.171
1.136
1.101
1.077
1.030
1.018
1.000
0.969
US CPI
2.646
2.399
2.260
2.189
2.099
2.027
1.990
1.920
1.843
1.759
1.668
1.601
1.554
1.509
1.471
1.431
1.390
1.359
1.338
1.309
1.266
1.231
1.212
1.185
1.154
1.117
1.082
1.052
1.013
1.016
1.000
0.969
(a) Anchorage CPI: Consumer Price Index for Anchorage Municipality; (b) US CPI:
United States Consumer Price Index, All Urban Consumers. Source: U.S. Dept. of
Labor, Bureau of Labor Statistics (BLS), downloaded March 15, 2012 from Alaska
Department of Labor & Workforce Development website:
http://labor.alaska.gov/research/cpi/cpi.htm.

For any given year, the adjustment factor to convert from nominal dollars to real dollars is the
Anchorage CPI for 2010 (195.144) divided by the Anchorage CPI for the year. For example, a
nominal price of $1.00 in 1990 would have a "real" 2010 value of (195.144 / 118.600) x $1.00 =
1.645 x $1.00 = $1.64.
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This report uses the Anchorage CPI rather than the US CPI because it is the only available
measure of inflation for Alaska, and it is the most appropriate measure for accounting for the
effects of inflation for Alaskans. The table above also shows the corresponding alternative
adjustment factors using the US CPI. In practice, using the US CPI would have resulted in very
similar "real" prices and values, and would not have resulted in any meaningful changes in any
of the analysis or conclusions of this report. The source for both the Anchorage CPI and the US
CPI was the U.S. Dept. of Labor, Bureau of Labor Statistics (BLS). These data are available on
the Alaska Department of Labor & Workforce Development website at
http://labor.alaska.gov/research/cpi/cpi.htm.
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4.0 Economic Significance of Healthy Salmon Ecosystems in
the Bristol Bay Region: Summary Findings

This study is part of an economic analysis of the Bristol Bay watershed, which is in turn part of a
larger interdisciplinary watershed analysis for Bristol Bay that is being conducted by the
Environmental Protection Agency. The purpose of this study is to assess the economic
significance of commercial activities that are dependent on ecosystems in the Bristol Bay
watershed and important to the regional economy and to the state economy of Alaska. The study
region consists of the Bristol Bay Borough, the Dillingham Census Area, and the Lake and
Peninsula Borough. This economic significance analysis measures how many annual average
jobs and how much personal income was generated in Alaska by expenditures associated with
the Bristol Bay commercial salmon industry, subsistence activities, as well as various types of
recreational activities dependent on Bristol Bay salmon ecosystems. We divide recreation into
sport fishing, sport hunting, and non-consumptive use, based on the primary activity reported by
visitors to the Bristol Bay region.

For 2009, we estimate that about 6,300 annual average jobs are attributable to the wild salmon
ecosystem in the Bristol Bay region. Residents of Alaska hold more than 80 percent of all jobs.
About 60 percent of all Alaskans working in the Bristol Bay region live in other parts of Alaska.
About 20 percent of all jobs are held by non-residents from outside Alaska. At the peak of the
summer season, there are almost 15,000 jobs in the Bristol Bay region associated with the
commercial salmon fishery and recreation industries. In 2009, the total payroll traceable to this
economic activity amounts to more than $282 million of which $182 million went to Alaska
residents, and more than $100 million was received by non-residents from outside Alaska
working seasonally in the commercial salmon fishery, recreation industries, or service providing
industries. About $77 million went to local residents of the Bristol Bay region.

The commercial fishing industry provides the biggest contribution to the economic significance
of the Bristol Bay ecosystem. In terms of the overall direct employment in the region, half of all
jobs are in the fishing industry, followed by government (32 percent), recreation (15 percent),
and mineral exploration (3 percent). The largest recreation related contributor of direct jobs in
the region is the non-consumptive recreational use sector providing 9 percent of the overall
employment followed by sport fishing (5 percent) and sport hunting (1 percent).
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Table 50. Estimated Economic Significance of Bristol Bay Ecosystems

Direct jobs
Peak
Commercial fish
Recreation
Subsistence
Annual average
Commercial fish
Recreation
Subsistence
Multiplier Jobs
Total jobs
(annual average)
Direct wages
($000)
Commercial fish
Recreation
Subsistence
Multiplier wages
Total wages
Total
14,227
11,572
2,655
non-mkt.
2,811
1,897
914
non-mkt.
3,455
6,266
$166,632
$134,539
$32,093
non-mkt.
$115,976
$282,608
Non-local
4,365
3,257
1,114
non-mkt.
914
530
384
non-mkt.
2,008
2,922
$40,149
$22,698
$12,451
non-mkt.
$69,250
$104,399
Residents
Local
2,273
1,089
1,184
non-mkt.
585
177
408
non-mkt.
1,447
2,032
$31,048
$17,608
$13,440
non-mkt.
$46,724
$77,772
Total
6,639
4,341
2,298
non-mkt.
1,499
707
792
non-mkt.
3,455
4,954
$66,199
$40,307
$25,892
non-mkt.
$115,976
$182,175
Non-
Residents
7,587
7,237
356
non-mkt.
1,313
1,190
123
non-mkt.
-
1,313
$100,435
$94,233
$6,202
non-mkt.
-
$100,435
Note, table does not include jobs related to mineral exploration, commercial trapping, commercial fisheries other
than salmon, or government.
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4.11ntroduction

This study is part of an economic analysis of the Bristol Bay watershed, which is in turn part of a
larger interdisciplinary watershed analysis for Bristol Bay that is being conducted by the
Environmental Protection Agency. The purpose of this study is to assess the economic
significance of commercial activities that are dependent on ecosystems in the Bristol Bay
watershed and important to the regional economy and to the state economy of Alaska.
"Economic significance" refers to how many annual average jobs and how much personal
income was generated in Alaska by expenditures associated with the Bristol Bay commercial
salmon industry as well as various types of recreational activities and subsistence activities
dependent on Bristol Bay salmon ecosystems. Thus it represents the jobs and income lost would
the commercial fishing industry, tourism industry, and subsistence activities go away entirely.
The study region consists of the Bristol Bay Borough, the Dillingham Census Area, and the Lake
and Peninsula Borough.

Note the following important limitations of this study. First, the study does not measure the net
economic value of the natural resources occurring in the Bristol Bay region to Alaska and/or the
U.S. as a whole. For example, we do not measure the economic value visitors and non-visitors to
the region place on preservation offish, wildlife, and wilderness within the Bristol Bay region.
Second, an economic significance analysis is different from an economic impact analysis that
quantifies the change in management policy or some factor influencing the use of natural
resources in the region. For example, the construction of roads would result in marginal changes
to the current condition of natural resources in the region. The economic impacts associated with
these changes would not necessarily be proportional to the change in the scale of commercial
fishing or other fisheries-dependent activities they might affect. More specifically, we assume
that changes to final demand result in linear effects even though in reality change effect
relationships are often non-linear in nature.

Third, the analysis shows the contributions to the regional economy of Bristol Bay and the rest of
Alaska but excludes the contributions occurring in other states of the U.S. or other parts of the
world. Fourth, the model shows only a one-year-snapshot of the economy. The analysis is based
on data sources of earlier years that have been adjusted to reflect 2009 conditions or they are
based on 2009 data. Given the large annual variations that occur in catches for the commercial
salmon fishery and for visitation and expenditures related to tourism, the estimated economic
significance for 2009 is not necessarily representative of historical or future economic
significance.

The following sections of the report first describe the methods used to quantify the economic
significance of economic activity in the Bristol Bay region. We then provide a brief regional
economic overview followed by the multiplier results for each economic activity. The
appendixes discuss the rationale and uncertainties related to assumptions relevant for the analysis
and provide information about all data sources used.

Except where noted, all values are expressed in 2009 dollars and where necessary were adjusted
using the Anchorage Consumer Price Index, the only available measure of inflation for Alaska.

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We report employment estimates for residents of three different regions: the local Bristol Bay
region (local), other parts of Alaska (non-local residents), and residents of other states or
countries (non-residents).

Note, for the purpose of this study, we report peak employment as a point estimate of the
maximum count of workers observed, and state all other employment estimates (including
multiplier jobs) in terms of annual average jobs. For example, six jobs held for 2 month of the
year in commercial salmon fishing would result in one annual average job.
4.2 Methods

An economic significance analysis measures the importance of economic activity occurring in a
region to the regional and statewide economies. We use jobs and income as two measures to
show this significance. To conduct this analysis, we first identify the expenditures and jobs
directly associated with the primary economic activity of the region including commercial
fishing, recreation, and subsistence. We then calculate the additional expenditures, annual
average jobs, and payroll generated by dollars re-circulating through the economy to support
industries located in the region and elsewhere in Alaska. These effects are commonly referred to
as multiplier effects.

The process by which purchases by an industry or by households stimulate purchases by other
businesses and households is known as the multiplier effect. For this study, we measure
multiplier effects for indirect and induced employment and wages. Indirect effects occur when
primary industry purchases inputs to their operation from support sectors. For example, fishing
boat captains purchase diesel fuel from local gas stations. Induced effects consist of the
additional jobs and payroll created when employees of the primary and support industries spend
their personal income on consumer goods and services. For example, the manager of the local
gas station, where the fishermen bought fuel from, buys bread from the local bakery.

In order to appropriately calculate the effects of re-circulating dollars through the economy, we
use a regional Input-Output model developed by University of Alaska Anchorage Economics
Professor Scott Goldsmith for the state of Alaska. We refer to the model as the 'ISER Input-
Output model" (Goldsmith, 2000). The model reflects the economic structure of the Alaska
economy, consisting of four regions with the Southwest region encompassing the Bristol Bay
study area. Since the model represents the structure of the entire region of Southwest Alaska, it is
dominated by the larger urban area (Kodiak and Dutch Harbor), where most of the jobs are
located. Other more rural communities such as those of the Bristol Bay region have a more
rudimentary market economy. As a consequence, the Input-Output model may overstate the local
economic activity in a rural area compared to what that spending may actually generate. In other
words, in rural areas, the local jobs multiplier tends to be overstated.

Similarly to variation of economic activity within a region, there is also variation among regions.
For example, Anchorage serves as the trade and service center for the state. Thus, any spending
occurring in rural parts of the state has economic effects in the rural region and in the
Southcentral region, where Anchorage is located. An important feature of the ISER Input-Output

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model is that wages paid in Anchorage can be attributed back to expenditures made in rural
areas.

Another important characteristic of the ISER Input-Output model is that it establishes supply
constraints. In Alaska, inter-industry purchases mainly occur with services and raw materials that
are supply constrained due to resource scarcity and the limited availability of capital and labor to
extract the raw materials. "Off-the-shelf Input-Output models developed primarily for other less
resource-dependent states, such as IMPLAN, do not take this characteristic into account, and
potentially overestimate multiplier effects within Alaska (MIG, 2011). Another important
attribute of the Alaska economy is that inter-industry purchases are less important in Alaska
compared to more mature economies. The absence of a developed manufacturing sector in
Alaska means that most goods must be purchased outside the state, creating large leakages and
small indirect multiplier effects.

Despite the outlined advantages of the ISER Input-Output model, there remain many challenges
to the analysis. One of these challenges is that the economic structure depends in large part on
determining where the workers reside when they are not working. Many workers, particularly in
the commercial fishing industry don't live in the Bristol Bay region. They only come to the
region for a two to four months long period in the summer but live elsewhere the rest of the year.
The appendixes further discuss data sources used and the implications of assumptions made on
overall results. Due to a lack of certain kinds of data and other sources of uncertainty further
discussed in the appendix, the reader should interpret the estimated impacts as suggestive rather
than definitive.

The following two tables show how many jobs and income are associated with $1 million in
2009 spending in Southwest Alaska. For example, $1 million dollars of in-state spending on air
transportation in Southwest Alaska creates approximately six jobs in Southwest Alaska and one
job in Southcentral Alaska (Table 51). In addition, this spending generates $344,000 in payroll in
Southwest Alaska and $54,000 in payroll in Southcentral Alaska (Table 52).
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Table 51. Annual average jobs associated with $1 million in spending in each sector in
Southwest Alaska, 2009

SOUTH SOUTH SOUTH NORTH STATE
EAST CENTRAL WEST TOTAL
I II III IV
Agriculture and AFF Services
Forestry
Fishing
Crude Petroleum and Natural Gas
Other Mining
New Construction
Maintenance and Repair
Food and Kindred Products
Paper and Allied Products
Chemicals and Petroleum Processing
Lumber and Wood Products
Other Manufacturing
Railroads
Local and Interurban Transit
Motor Freight and Warehousing
Water Transportation
Air Transportation
Pipelines
Transportation Services
Communication
Electric, Gas, Water, and Sanitary
Wholesale Trade
Retail Trade
Finance
Insurance
Real Estate
Hotels, Lodging, Amusements
Personal Services
Business Services
Eating and Drinking
Health Services
Miscellaneous Services
Federal Government Ent
State & Local Government Ent
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.9
0.3
0.2
0.9
0.9
0.0
4.0
0.2
0.0
0.1
0.0
0.4
0.2
0.2
1.1
0.3
1.0
0.1
0.3
1.3
0.8
4.6
12.3
4.0
2.1
0.9
1.9
2.0
6.4
8.5
4.8
4.6
0.4
0.1
5.5
4.2
4.2
0.6
4.2
4.1
10.2
5.3
5.0
1.1
5.6
8.4
4.1
11.7
10.2
4.4
6.4
3.7
6.8
6.1
2.7
10.0
30.4
9.2
8.9
0.7
15.0
24.2
20.2
26.8
18.8
15.1
6.3
8.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
6.3
4.4
4.3
1.5
5.1
4.1
14.1
5.5
5.0
1.2
5.7
8.8
4.3
12.0
11.2
4.7
7.4
3.8
7.2
7.4
3.5
14.6
42.7
13.2
11.0
1.6
16.9
26.3
26.6
35.3
23.6
19.7
6.7
8.4
176
-------
Table 52. Annual payroll associated with $1 million in spending in each sector in Southwest
Alaska, 2009
Agriculture and AFF Services
Forestry
Fishing
Crude Petroleum and Natural Gas
Other Mining
New Construction
Maintenance and Repair
Food and Kindred Products
Paper and Allied Products
Chemicals and Petroleum Processing
Lumber and Wood Products
Other Manufacturing
Railroads
Local and Interurban Transit
Motor Freight and Warehousing
Water Transportation
Air Transportation
Pipelines
Transportation Services
Communication
Electric, Gas, Water, and Sanitary
Wholes ale Trade
Retail Trade
Finance
Insurance
Real Estate
Hotels, Lodging, Amusements
Personal Services
Business Services
Eating and Drinking
Health Services
Miscellaneous Services
Federal Government Ent
State & Local Government Ent
Households $

Source: ISER Input-Output Model (Goldsmith, 2000).
SOUTH SOUTH
EAST CENTRAL
1 II
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
43,276
13,755
8,821
150,128
72,014
254
243,764
7,446
524
12,003
1,092
15,244
16,082
5,409
35,723
21,311
54,410
4,718
14,772
87,937
55,677
227,652
365,739
206,101
108,765
29,189
46,021
44,267
298,171
151,775
197,932
172,055
25,818
5,415
SOUTH
WEST
III
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
274,635
209,563
209,563
92,746
326,900
254,526
626,678
181,843
165,218
97,505
211,898
299,200
296,407
269,956
336,974
316,516
344,270
268,972
296,132
423,144
186,376
494,997
904,797
476,973
463,912
23,538
360,382
526,104
940,459
479,206
785,286
565,071
403,554
360,384
NORTH
IV
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
_
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
9,129 $ 22,931 $
177
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4.3 Regional Economic Overview

The economy of the Bristol Bay Region depends on three main activities (basic sectors)—
publicly funded services through government and non-profits, commercial activity associated
with the use of natural resources (mainly commercial fishing and recreation), and subsistence.
Subsistence is a non-market activity in the sense that there is no exchange of money associated
with the subsistence harvest. However, local participants invest a significant portion of their
income to participate in subsistence and the harvest has considerable economic value and their
expenditures have significant economic effects.

Public services and commercial activities bring money into the economy (basic sectors) and
provide the basis for a modest support sector. The support sector (non-basic sector) consists of
local businesses that sell goods and services to the basic sectors including the commercial fishing
industry, the recreation industry, the government and non-profit sectors. The support sector also
sells goods and services to participants in subsistence activities.

The relative importance of government, commercial fishing and recreation, within the regional
economy can be measured by the annual average employment in each sector. In 2009, more than
two thousand jobs were directly associated with government spending from federal, state, and
local sources. Commercial fishing and recreation accounted for approximately three thousand or
57 percent of total basic sector jobs (Table 53).

The annual spending of federal dollars in the region serves as an indicator of the importance of
the government sector in the region. Table 54 shows that in 2009, $119 million in federal
spending flowed into the three labor market areas of the Bristol Bay region.
178
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Table 53. Employment Count by Place of Work in the Bristol Bay Region, 2009

Total jobs count
Basic
Fish harvesting
Fish processing
Recreation
Government & Health
Mineral Exploration
Non-basic
Construction

Trade/Transportation/Leisure
Finance
Other wage & salary
Non-basic self employed
Resident jobs count
.niiiiuai
Average
6,648
5,490
1,409
1,374
432
2,039
197
1,406
61
634

155
239
317
4,675
Summer
16,386
14,877
6,909
4,480
1,297
1,712
450
1,509
92
717

142
241
317
10,351
Winter
3,792
2,430
-
354
-
2,056
70
1,362
55
593

162
235
317
3,225
Swing
12,594
12,447
6,909
4,126
1,297
(344)
380
147
37
124

(20)
6
-
7,126
Note, estimates based on ISER Input-Output Model (Goldsmith, 2000).
Note, fish harvesting and processing include other fisheries but salmon, thus employment numbers cannot
be compared with other tables shown in this report. Summer and winter employment shown, are point
estimates that either show the maximum or minimum job count. Swing refers to the difference between
maximum and minimum. See Appendix B for sources used.
Table 54. Federal Spending in the Bristol Bay Region, 2009 ($000)

Total
Retirement
Other direct to individuals
Grants
Procurement
Wages
Bristol Bay
$49,600
$6,934
$1,930
$32,867
$4,440
$3,430
Dillingham
$54,345
$6,764
$10,235
$32,467
$1,005
$3,874
Lake & Pen
$16,013
$545
$4,799
$7,878
$857
$1,934
Total
$119,958
$14,243
$16,964
$73,212
$6,302
$9,238
Source: U.S. Department of Commerce (2009).
179
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Table 55. Estimated Residence of Workers in the Bristol Bay Region 2009
T . Other Outside „ .
Local ... ... Total
Alaska Alaska

Bristol Bay
State government 24 14 9 47
Local government 126 12 18 156
Private sector 273 332 1,916 2,521
Sum 423 358 1,943 2,724
Dillingham
State government
Local government
Private sector

90
877
1,033

24
66
270

8
94
728

122
1,037
2,031
Sum 2,000 360 830 3,190

Lake & Pen
State government 7 7 3 17
Local government 417 105 66 588
Private sector 179 322 685 1,186
Sum 603 434 754 1,791

Total Private 1,485 924 3,329 5,738
Share 26% 16% 58% 100%

Source: ADOL (2009). Note, this is a count of workers (unique individuals) and not a measure of Full
Time Equivalent or annual average jobs. Also, the table includes processing workers but excludes
harvesters in the commercial fishery (private sector).
The estimated personal income in the region varies by borough/census area. The Bureau of
Economic Analysis (BEA) reports more than $58,000 as the 2009 per capita personal income for
the Bristol Bay Borough. Per capital personal income in the Lake and Peninsula Borough or in
the Dillingham Census Area is approximately equal to $35,000 (Table 56). For comparison, the
2009 per capita personal income in Anchorage amounts to $48,598.

The commercial salmon fishery provides above average income to seasonal workers and
residents of the region. Because of the large amounts of income received by seasonal workers
that do not reside in the Bristol Bay region, BEA applies the Alaskan seasonal worker
adjustment. This residence adjustment lowers the income generated in the region by the amount
that's believed to be received by people working in Bristol Bay but not residing in the region. In
part, it is a subjective measure for the amount of income flowing out of the Bristol Bay Borough
to other areas of Alaska and to Washington State, Oregon, and California (BEA, 2007). Thus, the
per capita income measures stated in are uncertain and should be viewed as suggestive rather
than definitive.

180
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Table 56. Estimated Personal Income in the Bristol Bay Region, 2009 (000$)
Bristol Bay Dillingham Lake & Pen
Total
Wages $57,018 $96,654 $27,551 $181,223
+ Supplements to wages $16,694 $28,021 $9,164 $53,879
+ Proprietor income $9,421 $16,194 $2,605 $28,220
= Earnings by place of work $83,133 $140,869 $39,320 $263,322
- Contributions for government $8,799 $14,820 $3,736 $27355
social insurance
+ Residence adjustment -$39,175 -$4,530 -$1,055 -$44,760

= Net earnings by place of $35,159 $121,519 $34,529 $191,207
residence
+ Dividends $7,382 $20,314 $7,980 $35,676
+ Transfers $9,189 $35,764 $11,981 $56,934

= Personal Income $51,730 $177,597 $54,490 $283,817
Population 881 4,957 1,485 7,323
Per Capita Income $58,717 $35,828 $36,694 $38,757
Source: BEA (2009).
181
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4.4 Commercial Salmon Fisheries

The largest share of jobs and income generated in the Bristol Bay region comes from commercial
salmon fishing, including drift gillnet and set gillnet fisheries. The commercial salmon fishery is
described in detail in Section 3 of this report prepared as part of the EPA studies by University of
Alaska Professor Gunnar Knapp, on "An Economic Overview of the Bristol Bay Commercial
Salmon Industry." Here we provide a brief summary description prior to presenting estimates of
the economic significance of the industry.

The number of commercial fishing jobs and income varies from year to year due to the varying
size and value of the salmon harvest. For example, the ex-vessel value paid to fishermen fell
from a peak of $214 million in 1989 to $32 million in 2002, and recovered to $148 million in
2009. The 2009 harvest was 192 million pounds. The whole sale value of these fish amounted to
$300.2 million.26

At the peak of the 2009 commercial salmon fishery, about 1,000 local residents and 6,000
seasonal workers from outside the region participated in the commercial salmon fishery's
harvest. In addition, approximately 4,500 non-local processing workers came to the Bristol Bay
region. At the peak of the season approximately 11,500 workers had jobs in harvesting and
processing combined. About 4,300 of these workers were Alaska residents and approximately
7,200 came from outside the state.

We estimate that total income to harvesters in 2009 was approximately $103 million of which
permit holders received $72 million (70 percent) and $31 million went to crew members.
Alaskans participating directly in harvesting and processing earned approximately $40 million
amounting to 42 percent of total direct wages. Local residents of the Bristol Bay region earned
$17.6 million (12 percent) of total direct income in processing and harvesting combined.
The commercial salmon season is highly seasonal. Almost all fishing and processing activity
occurs between June and August. For the purpose of our analysis, we assume that each seasonal
fishing job lasts two months. Therefore, six seasonal jobs equate to one annual average job.

The in-state spending by harvesters, processors, and workers in the region and in other places of
Alaska created additional jobs in other sectors of the economy through the multiplier effect. We
estimate that on an annual average basis, 1,586 additional jobs (754 locally and 832 in the rest of
Alaska) and $54.7 million in indirect wages were traceable to commercial fisheries. These jobs
were in the trade, service, finance, and other support industries. Jobs created outside of the state
are not included in these estimates.

In 2009, the total income traceable to commercial salmon fishing in Bristol Bay equaled $189
million. Accounting for the short two months summer season in commercial salmon fishing, the
11,500 direct commercial salmon fishing jobs translate to approximately 1,900 jobs on an annual
26 Estimates of some year-specific commercial fishery total harvest and total sales vary slightly within this report.
This is due to differences in how these data are aggregated and reported by the Alaska Fish and Game, and the point
in time these statistics were accessed during the preparation of this report.

182
-------
average basis. With the addition of multiplier jobs, about 3,500 annual average jobs would be
attributable to the commercial salmon fishing industry (Table 57).
Table 57. Estimated Economic Significance of Commercial Fishing

Direct jobs
Peak
Harvesting
Processing
Annual average
Harvesting
Processing
Multiplier Jobs
Total jobs
(annual average)
Direct wages
($000)
Harvesting
Processing
Multiplier wages
Total wages
Total
11,572
7,050
4,522
1,897
1,143
754
1,586
3,483
$134,539
$103,354
$31,185
$54,705
$189,244
Non-local
3,251
2,694
557
530
437
93
832
1,362
$22,698
$19,645
$3,053
$28,101
$50,799
Residents
Local
1,089
1,013
76
111
164
13
754
931
$17,608
$16,609
$999
$26,604
$44,212
Total
4,341
3, 708
633
707
601
106
1,586
2,293
$40,307
$36,255
$4,052
$54,705
$95,012
Non-
Residents
7,231
3,342
3,889
1,190
542
648
-
1,190
$94,233
$67,100
$27,133
-
$94,233
Note, estimates based on ISER Input-Output Model (Goldsmith, 2000).
183
-------
4.5 Recreation

The second largest portion of jobs and income generated by spending dependent on Bristol Bay
salmon resources comes from the recreation sector which directly employs approximately 2,600
workers during peak season translating to about 900 annual average jobs with an annual payroll
of more than $32 million. Most recreational visits occur during the summer months, creating a
peak in economic activity that largely coincides with the peak of the commercial salmon fishery.
Recreational activity concentrates in Katmai National Park and Preserve, Lake Clark National
Park and Preserve as well as the National Wildlife Refuges: Alaska Peninsula/Becharof,
Ixembek, and Togiak. Sport fishing activity occurs mainly in the Nushagak and Naknek River
watersheds, whereas sport hunting occurs predominately in the Mulchatna River watershed.
Visitors travel to Alaska by air, ferry, highway, and cruise ship. Each of these travel markets has
distinct visitor attributes, demographics and regional impacts. Visitation to Southwest Alaska is
primarily driven by independent travelers who predominately arrive by air. Statewide visitation
declined 5.8 percent between 2008 and 2009 as a result of the recession following the collapse of
financial markets in late 2008. Cruise passenger volume remained essentially the same in 2009
because ship deployment decisions take a longer lead time than air. In contrast, air visitor traffic
decreased by 15 percent in 2009.

The rebound in Alaska visitation in 2010 was led by independent travelers arriving by air, and to
a lesser extent, road, ferry, and international visitors. This rebound is expected to continue in
2011 and again be comprised primarily of independent travelers. These independent visitors
tend to visit Alaska's more remote regions, while cruise visitors primarily visit the marine
accessible Southeast region and the Southcentral and Interior regions including Denali National
Park and Preserve. Katmai National Park and Preserve in Southwest Alaska showed a rebound in
visitor numbers in 2010 after declines in 2008 and 2009, based on National Park Service
Commercial Use Authorization permit report data. Among those that reported boosts in
independent-visitor traffic are lodges, tour operators, and campgrounds, according to the Alaska
Travel Industry Association.

We estimate that there were approximately 40,964 non-consumptive recreation visitors to
Southwest Alaska in 2009 of which approximately 10 percent were Alaska residents. Visitor
related spending amounted to approximately $173.3 million in 2009. The average spending per
visitor and the average length of stay are higher in Southwest Alaska compared to respective
statewide averages. Based on the Alaska Visitor Statistics Program, non-residents visiting
Southwest Alaska spent $2,873 per visitor and stayed 12.9 nights whereas the statewide average
visitor spent $992 and stayed 9.1 nights. Fay and Christensen estimate per visitor spending in
Katmai to amount to $2,332. Also, recreational expenditures occurring inside Katmai NPP are
relatively high for a remote Alaska park because of the location of Brooks Camp and concession
businesses located inside the park. Based on the visitor spending reported by the Alaska Visitor
Statistics Program and Fay and Christensen, we estimate non-consumptive visitor spending in
the Bristol Bay region to equal $2,548 per visitor and year.

Among all recreational users of the region, non-residents spent the largest amount, equaling
$149.5 million or 86 percent of total spending. Alaskans from outside the region spent an
estimated $18.9 million, whereas locals had the smallest amount equaling $4.9 million in

184
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recreation related expenditures. The per-visitor expenditures to destinations in Southwest Alaska
are higher compared to other locations in Southcentral Alaska because most travelers go by air to
the more remote locations such as Bristol Bay, whereas the largest portion of visitors to
Southcentral Alaska come to Alaska by cruise ship.
Table 58. Estimated Recreational Visitors and Expenditures in the Bristol Bay Region,
2009
Local Non-local Non-
residents residents residents
Visitors
Non-consumptive
Sport fishing
Sport hunting

4,506
13,076 3,827
1,319

36,458
12,464
1,323

40,964
29,367
2,642
Total 13,076 9,652 50,245 72,973

Spending per visitor
Non-consumptive - $2,548 $2,548
Sport fishing $373 $1,582 $3,995
Sport hunting - $1,068 $5,170

Spending (Sniillion)
Non-consumptive - $11.5 $92.9 $104.4
Sport fishing $4.9 $6.0 $49.8 $60.7
Sport hunting - $1.4 $6.8 $8.2
Total $4.9 $18.9 $149.5 $173.3

Note, some visitors combine fishing with non-consumptive use activities. These visitors are included here
in sport fishing. Cost of travel to Alaska for non-residents not shown. Annual spending per non-
consumptive visitor is the weighted average of visitor spending related to Katmai and other locations in
the Bristol Bay Region.
The local economic impact of visitor spending occurs primarily through local purchases of goods
and services. This effect is captured in the multiplier jobs and wages in . The multiplier jobs are
held in the transportation, accommodation, and trade sectors of the economy. A large share of
these jobs is located outside the Bristol Bay region in Southcentral Alaska where most of the
goods and services originate from. The jobs in these sectors are more likely to be filled by
Alaska residents who live where they work, and they are more likely year-round rather than
seasonal jobs.

For 2009, we estimate the total annual average number of jobs that are traceable to recreational
visits to the Bristol Bay region to equal 2,715 with total payroll of $90.8 million. On an annual
average basis, the majority (44 percent) of the 914 direct jobs were held by local residents of the
region followed by other Alaska residents (384 jobs). Other Alaskans either moved into the

185
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region to fill a job during the summer season, or their job was located in Anchorage and
attributable to recreation occurring in the Bristol Bay region. A smaller share of total jobs (13
percent) was taken by non-residents. Also, some of the indirect jobs in transportation, trade, and
accommodations were probably filled by non-residents rather than residents. Important to note is
that due to a lack of data, the distribution of jobs and income by residency is uncertain. However,
total employment and total income estimates are more robust measures.

Note, since many of the goods and services consumed in Alaska, are produced outside of Alaska
and consequently have economic effects elsewhere, these spillover effects are not part of this
economic analysis.
Table 59. Estimated Economic Significance of All Recreation

Direct jobs
Peak
Non-cons.
Sport Fish
Sport Hunt
Annual average
Non-cons.
Sport Fish
Sport Hunt
Multiplier Jobs
Total jobs
(annual average)
Direct wages
($000)
Non-cons.
Sport Fish
Sport Hunt
Multiplier wages
Total wages

Total
i Ul
-------
4.5.1 Non-Consumptive Use

Most of recreational spending in the Bristol Bay region is related to non-consumptive use, for
example wildlife viewing of coastal brown bears and bird species, or kayaking and camping
activities. For this part of the analysis we estimate visitation based on the most recent studies of
non-resident visitors to the state and two studies that estimated visitation and economic impacts
related to Katmai National Park and Preserve. On an annual basis including summer and winter
visitation, approximately 2,300 residents and 18,900 non-residents visited Katmai NPP. Other
areas in the Bristol Bay region received approximately 2,300 resident visitors and 19,000 non-
resident visitors. Note, these estimates exclude visitation where sport fishing or sport hunting
was in part or the primary activity of choice. After adjusting the per capita expenditures to 2009
dollars we estimate per person expenditures to amount to $2,245 annually for Katmai NPP and
$2,873 per person annually for visiting other destinations in the Bristol Bay region.

To be consistent with the expenditure data for sport fishing and hunting, we assume that the visit
to the Bristol Bay region was the primary reason for their visit to Alaska. For these visitors we
include all their instate spending in the calculation of multiplier jobs and income.

We estimate a total of 1,681 annual average jobs to be attributable to non-consumptive use of
natural resources in the Bristol Bay region with a payroll of $54.8 million. The main proportion
(57 percent) of jobs are held by residents of Alaska that don't live in the Bristol Bay region either
because they move to Bristol Bay for the summer months to fill a seasonal job or because they
work in Anchorage for a supplier of goods and services to the Bristol Bay region. The total
income generated in 2009 for residents of Alaska amounted to $51.4 million.
Table 60. Estimated Economic Significance of Non-Consumptive Use
Total
Non-local
Residents
Local
Total
Non-
Residents
Direct jobs
Peak
Annual average
Multiplier Jobs
Total jobs
(annual average)
Direct wages
($000)
Multiplier wages
Total wages
1,669
575
1,106
1,681
$19,107
$35,668
$54,775
735
253
703
956
$7,823
$24,059
$31,882
741
255
403
658
$7,925
$11,608
$19,533
1,475
509
1,106
1,615
$15,748
$35,668
$51,416
193
67
-
67
$3,359
$3,359
Note, estimates based on ISER Input-Output Model (Goldsmith, 2000). All direct jobs are in the Bristol
Bay region.
187
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4.5.2 Sport Fishing

The second largest share of total recreational expenditures in the Bristol Bay region is associated
with sport fishing, either as the only or as the primary activity of the visitor. Non-residents
account for 53 percent of visitors that fish in the region and spend 82 percent of total sport fish
related expenditures attributable to the region, excluding travel to Alaska. Non-residents are
most likely to hire guides and stay at local lodges. Alaska residents account for 47 percent of
visitation and spend 10 percent of total sport-fish-related expenditures. We also include spending
on sport fishing by local residents, even though that spending does not bring in money from
outside the region to the Bristol Bay region. If there would not be any sport fishing opportunities
in the region, that local spending could likely shift to other areas outside the region and thus
provides the rationale for including it in our calculations.

At the peak of the fishing season in July, employment in sport fishing reaches 854 direct
seasonal jobs. The annual average employment traceable to sport fishing in the region amounts
to approximately 300 annual average jobs, of which almost half are taken by local residents. The
total estimated payroll attributable to sport fishing activities in the Bristol Bay region amounts to
$31.4 million in 2009. We estimate that about a third of total payroll went to local residents of
the Bristol Bay region. After counting for multiplier jobs, more than 900 annual average jobs are
traceable to sport fishing occurring in the Bristol Bay region.
Table 61. Estimated Economic Significance of Sport Fishing
Residents
Non-local Local
Total
Total
Non-
Residents
Direct jobs
Peak
Annual average
Multiplier Jobs
Total jobs
(annual average)
Direct wages
($000)
Multiplier wages
Total wages
854
294
608
902
$11,279
$20,118
$31,397
328
113
371
484
$4,020
$13,339
$17,359
383
132
237
368
$4,777
$6,779
$11,556
712
245
608
853
$8,797
$20,118
$28,915
142
49
-
49
$2,482
$2,482
Note, estimates based on ISER Input-Output Model (Goldsmith, 2000). All direct jobs are in the Bristol
Bay region.
188
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4.5.3 Sport Hunting

Compared to other recreation activities, sport hunting accounts for the smallest share of total
recreational expenditures (3 percent) and the fewest visitors overall (5 percent) (Table 58). The
larger per person expenditure of $3,122 per visitor is related to higher travel costs. In addition,
non-residents are by law required to hire local guide services which adds to the cost for hunting
including air service to remote hunting locations. In addition, sport hunters are more likely to
hire commercial operators for sport hunting. Of the 125 total annual average jobs in Alaska
attributable to sport hunting, most are taken by residents of the state with the majority of workers
residing outside the Bristol Bay region. The total payroll attributable to spending traceable to
sport hunting in the Bristol Bay region is more than $4 million, with the majority going to non-
local residents of Alaska residing in the Southcentral region of Alaska.
Table 62. Estimated Economic Significance of Sport Hunting
Residents
Non-local Local
Total
Total
Non-
Residents
Direct jobs
Peak
Annual average
Multiplier Jobs
Total jobs
(annual average)
Direct wages
($000)
Multiplier wages
Total wages
132
45
87
132
$1,707
$2,886
$4,593
51
18
55
73
$608
$1,982
$2,590
60
21
32
53
$738
$903
$1,641
111
38
87
125
$1,347
$2,886
$4,233
21
7
-
7
$361
$361
Note, estimates based on ISER Input-Output Model (Goldsmith, 2000). All direct jobs are in the Bristol
Bay region.
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4.6 Subsistence

Subsistence is an important component of the regional economy even though it is not part of the
market economy. Consequently there is no official measure for employment or the amount of
payroll associated with the pursuit of subsistence resources. However, there remains a link
between subsistence and the market economy in form of equipment, goods, and services
purchased by households participating in subsistence. Typically these purchases include boats,
rifles, nets, snow mobiles, and fuel used exclusively to take part in subsistence activities.
Publically available data on expenditures related to subsistence activities in the Bristol Bay
region is not publically available. . Our estimate of $3,054 per household relies on data from a
survey conducted in 1993 in the North Slope Borough (North Slope Borough, 1993; Goldsmith,
1998). Although, income, employment opportunities, and subsistence methods used in the North
Slope Borough are different, there is evidence that suggests the estimate is justified. In the 1980s,
results of a subsistence survey in Western Alaska communities are consistent with the 1993
North Slope estimate (Peterson et al., 1992).
A large share of the 68 multiplier jobs occurs in the Southcentral region (47 jobs) with more than
$1.8 million in payroll. Local multiplier jobs amount to approximately 16 and an annual payroll
of $830,000. The small number of multiplier jobs that are generated by households' spending on
equipment also depends on the limited capacity of local businesses to supply goods and services.
Table 63. Estimated Economic Significance of Subsistence
Residents Non-
Non-local Local Total Residents

Direct jobs
Peak Non- Non-mkt. Non-mkt. Non-mkt. Non-mkt.
mkt.
Annual average
Multiplier Jobs
Total jobs
(annual average)
Direct wages
($000)
Multiplier wages
Total wages

68
68
Non-
mkt.
$2,599
$2,599

47
47
Non-mkt.
$1,769
$1,769

21
21
Non-mkt.
$830
$830

68
68
Non-mkt.
$2,599
$2,599

-
-
Non-mkt.
-
Note, estimates based on ISER Input-Output Model (Goldsmith, 2000). All direct jobs are in the Bristol
Bay region.
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4.7 Conclusions

In 2009, the Bristol Bay salmon ecosystem supported more than 6,000 annual average jobs with
a payroll of $282 million. Non-residents of Alaska held one fifth of all jobs and received one
third of all income generated, about $100 million. Alaskans held approximately 5,000 jobs (80
percent of all jobs) and earned $182 million, one third of total income. Local residents of the
Bristol Bay region held about a third of all jobs and earned almost $78 million (28 percent) of
total income traceable to the Bristol Bay salmon ecosystem (Table 64).

The majority of jobs held by Alaskans are taken by residents from other regions of Alaska,
particularly by harvesters in the commercial salmon fishery. More than half of all jobs are held
by workers in the support industries for commercial fishing and recreation, which are mainly
located in Southcentral Alaska. Multiplier wages amount to about a third of total income
generated.

The regional economy is primarily driven by the commercial salmon industry, followed by
tourism and participation in subsistence, considered to be a non-market economic activity. The
economy of the Bristol Bay is a mixed cash-subsistence economy, where subsistence activity
requires labor inputs without exchange of money for the labor performed. Subsistence creates
non-cash jobs to local residents of the region who are pursuing subsistence activities to support
their families' need for food. The subsistence economy provides a direct link between the health
of the Bristol Bay salmon ecosystem and human well-being. Subsistence is integral to the local
way of life in the Bristol Bay region. However, even though it is an important part of the regional
economy, work related to subsistence similar to household work, is not officially measured and
neither is it subject to an exchange of money for the work performed. Thus, in the context of this
study which is solely focused on market values, we are unable to quantify the economic
significance of subsistence in the sense of direct jobs and income. Thus we present these jobs as
non-market jobs. However, we present multiplier jobs resulting from subsistence-related
spending on capital equipment and gasoline for example. These expenditures are necessary
inputs to participating in subsistence activities and are included under multiplier jobs and wages
(Table 64).
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Table 64. Estimated Economic Significance of Bristol Bay Ecosystems

Direct jobs
Peak
Commercial fish
Recreation
Subsistence

Annual average
Commercial fish
Recreation
Subsistence

Multiplier Jobs
Total jobs
(annual average)
Direct wages
($000)
Commercial fish
Recreation
Subsistence

Multiplier wages
Total wages
Total
14,227
11,572
2,655
non-mkt.

2,811
1,897
914
non-mkt.

3,455
6,266
$166,632
$134,539
$32,093
non-mkt.

$115,976
$282,608
Non-local
4,365
3,257
1,114
non-mkt.

914
530
384
non-mkt.

2,008
2,922
$40,149
$22,698
$12,451
non-mkt.

$69,250
$104,399
Residents
Local
2,273
1,089
1,184
non-mkt.

585
177
408
non-mkt.

1,447
2,032
$31,048
$17,608
$13,440
non-mkt.

$46,724
$77,772
Total
6,639
4,341
2,298
non-
mkt.
1,499
707
792
non-
mkt.
3,455
4,954
$66,199
$40,307
$25,892
non-
mkt.
$115,976
$182,175
Non-
Residents
7,587
7,237
356
non-mkt.

1,313
1,190
123
non-mkt.

-
1,313
$100,435
$94,233
$6,202
non-mkt.

-
$100,435
Note, estimates based on ISER Input-Output Model (Goldsmith, 2000). All direct jobs are in the Bristol
Bay region.
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4.8 Key Assumptions and Uncertainties
Description
Potential Bias
Sensitivity
relative to
overall
results
GENERAL
The ISER Alaska Input-
Output model consists of four
regions. The Bristol Bay
region is only part of one of
these regions, the Southwest
region. Larger communities
outside Bristol Bay such as
Kodiak and Dutch Harbor are
part of the Southwest region.
The expenditures related to economic activity in
the Bristol Bay region overestimate the
employment generated in the region and
underestimate the employment generated in other
regions. The bias in overall Alaska economic
impact is unknown.
Moderate
The commodity by industry
matrix is part of the Input-
Output model and allocates
commodity expenditures
among costs of goods,
transportation margins, trade
margins, and to industries,
based on statewide averages.
Transportation and trade margins may be higher
for purchases made in small, rural parts of Alaska
than for the state as a whole. This would result in
an underestimate of the transportation and trade
share of the total economic impact. Bias in
overall Alaska economic impact is unknown.
Moderate
Composition of household
expenditures is based on
statewide averages.
The composition of rural household expenditures
may be different from the state average, which is
heavily weighted by urban households. Bias in
overall Alaska economic impact is unknown.
Moderate
COMMERCIAL FISHING
Unrepresentative base year for
harvest and ex-vessel value
estimates
Given the large annual variations that occur in
catches for the commercial salmon fishery the
estimated economic significance for 2009 is not
necessarily representative of historical or future
economic significance.
High
Assumptions about the level
of expenditures per harvester
and processor
Unknown
Moderate
Assumptions about the
composition of harvester and
processor purchases
Unknown
Moderate
Assumption about the regional
allocation of expenditures by
Unknown
Moderate
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harvesters and processors
Assumption about the
residence of harvesters and
processor employees
Unknown
Moderate
Description
Potential Bias
Sensitivity
relative to
overall
results
Travel cost related to non-
residents and Alaska residents
travel between place of
residence and place of work in
Bristol Bay.
While we consider the in-state economic impact
of all earnings for harvesters' and processors'
earnings, we ignore the in-state cost of travel
between place of residency and place of work for
participants in the commercial fishing industry.
Negligible
RECREATION: NON-CONSUMPTIVE USE
Assumptions about the
number of local resident
visitors, non-local residents,
and non-residents
Underestimate due to the potentially higher
number of resident visitors (Fix, 2010).
Moderate
Assumptions about the level
of expenditures per trip
Underestimate. Other sources state higher per trip
expenditures for Southwest Alaska destinations
ranging from $3,068 to $3,760 per person and
trip (Colt and Dugan, 2005; Littlejohn and
Hollenhorst, 2007).
Moderate
Regional allocation of non-
consumptive expenditures
Unknown
Negligible
Assumption about the regional
allocation of guide, charter,
and lodge purchases.
Unknown
Negligible
Assumption about the
residence of guide, charter,
and lodge employees
Unknown
Negligible
RECREATION: SPORT FISHING & HUNTING
Assumptions about the
number of trips by local
residents, non-local residents,
and non-residents
Given the annual variations that occur in the
number of visitors to Southwest Alaska the
estimated economic significance for 2009 is not
necessarily representative of historical or future
economic significance.
Moderate
Assumptions about the level
of expenditures per trip
Given the national recession and worldwide
economic slump the annual variations in visitor
expenditures, the estimated economic
significance for 2009 is not necessarily
representative of historical or future economic
Moderate
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Regional allocation of sport
fishing and sport hunting
expenditures
Assumption about the regional
allocation of guide, charter,
and lodge purchases.
Assumption about the
residence of guide, charter,
and lodge employees
Description
Capital expenditures related to
residents' boats, cabins, and
other equipment
significance.
Unknown
Unknown
Unknown
Potential Bias
We ignore capital expenditures related to
equipment due to the difficulty of apportioning a
usage-share to specifically sport fishing or
hunting in the Bristol Bay region.

Negligible
Negligible
Negligible
Sensitivity
relative to
overall
results
Moderate
SUBSISTENCE
Assumption of number of
households engaged in
subsistence activities
Assumption about the level of
expenditures on subsistence
per household
Assumptions about the
composition of subsistence
related expenditures
Assumption about the regional
allocation of subsistence-
related expenditures
Unknown
Unknown. Estimate is from the North Slope of
Alaska where there is a different subsistence
culture compared to Bristol Bay. Similar
subsistence surveys in Western Alaska indicate
that the estimate used is justified. The direction
of bias is unknown.
Unknown
Unknown
Moderate
Moderate
Negligible
Negligible
Source: adapted from Goldsmith et al. (1998).
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4.9 Data Sources

(Methods).
Expenditures that are excluded from the Input-Output modeling exercise are tax revenues
generated through locally occurring economic activity, expenditures associated with natural
resource management, and the commercial trapping industry. In addition, the study excludes the
economic importance of herring fisheries in the Bristol Bay region. Compared to salmon, herring
fisheries in Bristol Bay are much smaller amounting to $2.5 million in ex-vessel value in 2009
compared to salmon with $148 million (CFEC, 2009). We also do not count mineral exploration
because it is not dependent on healthy ecosystems in the Bristol Bay region.

(Regional Economic Overview). There are three data sources related to jobs reported in the
Bristol Bay region. The Alaska Department of Labor and Workforce Development offers annual
average employment for wage earners (ADOL, 2009e) and information on participation in the
commercial fisheries such as crew shares and processor employment (ADOL, 2009a-c). The
third data source is an annual count of proprietors provided by the U.S. Bureau of Economic
Analysis (BEA, 2009). Data from ADOL does not include fishing employment, but BEA
provides an estimate of proprietors (including fish harvesters and other proprietors) in the region.
Since ADOL data is measured in annual average jobs and the BEA data is a count of workers,
we adjust the proprietor data to reflect seasonality assuming a six week harvesting season.
Proprietors include local resident crew and local resident captains which are based on crew
factors from ADOL (2004) and resident share of crew from ADOL (2009c). In addition, we use
information on the number of local permits fished from CFEC (2009) to get an estimate of the
number of local captains participating in the fishery. It is important to note that the ADOL data
only provides employment estimates by place of work. The BEA proprietor data is based on
income tax returns, thus the BEA proprietors counted in our analysis are only the ones that show
a business address in the Bristol Bay region. Our analysis does not include businesses registered
elsewhere in Alaska or out of state. Consequently, the proprietor data used in this study and
shown in Table 2 is an underestimate of the jobs that likely exist. For this reason, employment
estimates in Table 2 are not comparable to employment estimates elsewhere in the report.

(Commercial fisheries). For this study we divide the commercial fisheries sector into harvesting
and processing. For the harvest sector, harvest data by residency of permit holder came from the
Commercial Fisheries Entry Commission's Basic Information Tables (CFEC, 2009). Residency
of captains is based on Iverson (2009). Residency of crew is unknown but was inferred from
crew license data available at ADOL (2009a) for all commercial fisheries in the Bristol Bay
region. ADOL (2009a) shows that local captains hire 1.46 local crew in all of Bristol Bay's
commercial fisheries. Since the salmon fisheries are by far the largest fisheries in the region we
assume that each local captain hires 1.46 local crew with the remainder of crew members coming
from other places in Alaska. Non-local captains are assumed to hire exclusively non-local crew
and non-resident captains exclusively non-resident crew. The crew size for Bristol Bay
commercial salmon fisheries amounts to three including the skipper and is the same in the set net
and drift gill net fisheries (ADOL 2004). Crew shares for the set net and drift gill net fisheries
are based on a ten year average proportion of crew shares to gross earnings as stated in Schelle et
al. (2004). In addition, Schelle et al. (2004) provides expenditure categories for harvesters for

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the drift gillnet fishery. Due to a lack of data on expenditures in the set gill net fishery, we
assume costs to be about half of what they are in the drift gill net fishery with lower insurance,
moorage and storage and other boat related expenses due to the much smaller boats being used
for set net operations. We further allocate these expenditures within a commodity by industry
matrix to form a final demand vector that's passed to the ISERI-O Model following Goldsmith
(2000). For the processing sector, we assume that 95 percent of the harvest is processed in the
Bristol Bay region, including on-shore and off-shore processing. For simplicity, the Input-Output
model assumes processor expenditures for off-shore processing to be similar to on-shore
processing. Residency of processing workers is from ADOL (2009). Wholesale value for salmon
roe and non-roe combined are from ADF&G (2009). Average processor yield is calculated based
on the combined net product weight stated in ADF&G (2009) and pounds harvested (CFEC,
2009). Note, all direct jobs are in the Bristol Bay region. Multiplier jobs are divided between
Bristol Bay and Southcentral Alaska. Multiplier jobs are assumed to be all taken by residents of
the region where they occur. Peak and annual average direct wages are assumed to be equal.

(Recreation).
No comprehensive analysis has been completed on the economic significance of recreation and
tourism in Southwest Alaska. One of the greatest challenges is estimating visitor volume for
residents and non-residents. A number of separate studies provide some indication of pertinent
levels and patterns of visitation activities. Non-resident visitation, length of stay, and expenditure
per visitor to Southwest Alaska are from McDowell Group ( 2007a). Bluemink (2010) and the
Alaska Travel Industry Association provided information on current trends in visitation and so
did the National Park Service Commercial Use Authorization permit report data (National Park
Service, 2010).

For this study we separated visitor impacts by residency and by type of activity. For sport
fishing and sport hunting, Duffield and Neher, estimated visitor volume and expenditures for
sport fishing and sport hunting based on license data and visitor specific expenditure data from
ADF&G (2009b). In addition, Duffield et al. (2007) conducted a lodge survey in the Bristol Bay
region that offered detailed angler expenditure categories by residency, as well as expenditure
detail for lodges and guiding outfits. After adjusting for inflation, we develop separate final
demand vectors for sport hunting and fishing by residency. The analysis follows Goldsmith
(2000) and Duffield et al. (2007). According to ADF&G's hunting regulations, the sport hunting
season for moose, caribou and bear is mainly in the fall months and varies by area. For the
calculation of annual average jobs, we assume the main season for sport hunting to be three
months long (ADF&G, 2011).

We define non-consumptive users as those who reported wildlife viewing, camping, kayaking,
hiking, or photography as their primary purpose of their visit. We adjust the most recent 2006
summer and winter visitor estimate for Southwest Alaska excluding Kodiak by applying the
2006-2009 percent difference in air travelers for Alaska overall (McDowell Group, 2007a &
2007b). The trend in air travelers to Alaska serves as the best indicator for changes to visitation
in Southwest Alaska for two reasons. First, visitors to rural Alaska are mainly independent
travelers, and second they primarily arrive by air in comparison to the statewide largest share of
visitors who arrive by cruise ship. The Southwest Alaska region closely matches the Bristol Bay
197
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study region with the exception of Kodiak and the Aleutian Islands. Our analysis excludes
Kodiak but includes an insignificant portion of visitors to the Aleutian Islands.
Since Alaska Visitor Statistics Program counts out-of-state visitors only, we calculate visitor
volume originating within the state based on Littlejohn and Hollenhorst (2007) and Colt and
Dugan (2005) resident share of between ten and eleven percent. We treat visitation to Katmai
NPP separate from other areas of the Bristol Bay region. Visitor volume and expenditure for
Katmai NPP are from Fay and Christensen (2010) and for the remaining Bristol Bay area are
from McDowell Group (2007a). We net out sport fishing and hunting visitation in Katmai NPP
using Littlejohn and Hollenhorst (2007) and for the rest of the region by applying the McDowell
Group (2007a and 2007b) estimate. We assume equal expenditures for residents and non-
residents because the non-resident per person expenditure estimate in both cases does not include
the cost of travel to and from Alaska. For the expenditure categories associated with non-
consumptive use, we modeled the final demand vector based on Fay and Christensen (2010).
These expenditures categories include transportation within Alaska, food, lodging, guiding
services, supplies, licenses, etc. For most non-residents all in-state travel expenditures are
included, based on the assumption that the primary reason for the travel to Alaska is the visit the
Bristol Bay region. We allocated these expenditures within a commodity by industry matrix to
form the final demand vector that's then passed to the ISERI-O Model developed by Goldsmith
(2000). For all of these estimates, we paid special attention to the potential for double counting
and addressed those issues.

Note, all direct jobs are in the Bristol Bay region but the residency of workers and the location
where these workers spend their income is difficult to trace. Multiplier jobs are divided between
Bristol Bay and Southcentral Alaska. Multiplier jobs are assumed to be all taken by residents of
the region where they occur. Peak and annual average direct wages are assumed to be equal.

(Subsistence).
We estimate annual expenditures related to subsistence activities for households based on the
only publically available source (North Slope Borough, 1993) and adjust for inflation to 2009$.
This estimate is justified as results from similar subsistence surveys are similar (Peterson et al.,
1992). We assume that every household in the region participates in subsistence activities with
varying degrees of involvement and expense. We assume Native households to be participating
in subsistence extensively resulting in the entire per household expenditure, whereas Non-Native
households are assumed to be less involved with about a quarter of expenditures related to
subsistence activities compared to Native households as indicated by North Slope Borough
(1993). Due to the lack of data, the economic significance is quite small if compared to
commercial fishing or non-consumptive use, both in terms of the market jobs and the payroll
generated. For the expenditure categories related to subsistence, we assume maintenance and
repair of boats and trucks to amount to 10% of total annual expense each, purchase of boats and
trucks (10% each), hunting equipment (7%), fuel, repair, and parts (13% each).

Note, all direct jobs are in the Bristol Bay region. Multiplier jobs are divided between Bristol
Bay and Southcentral Alaska. Multiplier jobs are assumed to be all taken by residents of the
region where they occur. Peak and annual average direct wages are assumed to be equal.
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5.0 Bristol Bay Net Economic Values

The second general accounting framework under which ecosystem services can be measured is
the Net Economic Value framework. Net economic value is the value of a resource or activity
that is over and above regular expenditures associated with engaging in an activity or visiting a
resource area. The framework for this accounting perspective is the standard federal guidelines
(Principles and Standards) for estimating net economic benefits in a system of national accounts
(U.S. Water Resources Council 1985). EPA (2010) is a more recent and complementary set of
guidelines.
5.1 Commercial Fisheries

In addition to the regional economic impact of commercial fish harvest in the Bristol Bay, the
commercial fishery has a net economic value related to the expected differences over time
between the ex vessel revenues and the costs of participating in this fishery. One method for
estimating this value is to look at the market prices for commercial fishing permits in the Bristol
Bay. Bristol Bay commercial fishing permits are of two types, drift net permits and set net
permits. Regulations closely control many aspects of this permitted commercial harvest,
including types of nets, size of boats, areas fished, and start and end dates of season. The value
of holding one of these perpetual commercial permits is reflected in the prices that these permits
command when they are transferred between owners. These market prices reflect the value that
commercial operators place on their right to fish the region. That value in turn is a judgment of
the value of the net income stream that would reasonably be expected from operating the permit
given current and expected future salmon harvest levels and salmon prices.

In 2011, there were 1,862 salmon drift net permits in the Bristol Bay fishery and 981 salmon set
net permits in the fishery. Every year a portion of these permits are sold and change hands.
Since 1991, an average of 155 drift net permits and 89 set net permits have been sold and
changed hands in the Bristol Bay fishery.27 Permit transfers each year generally account for
approximately 8% to 10% of issued salmon permits in the fishery.

The Commercial Fish Entry Commission also reports average permit transfer prices annually
(and monthly) for the Bristol Bay salmon fishery.28 Over the period from 1991-2011 the average
sales price for Bristol Bay drift net permits has been $149,000 (in constant 2011 dollars). The
average price for set net permits over the same period has been $42,200. The 95% confidence
interval on the mean drift net price for this period is from $105,500 to $192,700. For the set net
permit transfers, the 95% C.I. on the mean sales price was between $28,700 and $55,700.29
Table 65 presents the estimated 95% C.I. range of total Bristol Bay drift and set net salmon
permit value based on the 1991-2011 permit transfer data. For both types of permits it is
27 The Alaska Fish and Game Commercial Fish Entry Commission publishes annual data on permit transfers at,
http://www.cfec.state.ak.us/RESEARCH/12-lN/12-lN.htm
28 A long time series of monthly and annual permit transfer prices is continuously updated at,
http://www.cfec.state.ak.us/pmtvalue/mnusalm.htm
29 Over the period 1991-2011, a total of 3,246 Bristol Bay drift net salmon permits and 1,867 set net salmon permits
were reported sold by the Commercial Fish Entry Commission.

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estimated that the total value of the permits ranges from approximately $225 million to $414
million.

In order to be comparable to other annual net economic values in this analysis (such as sport
fishing or sport hunting) the total value of commercial fishing permits must be converted into an
annual value reflecting expected annual permit-related net income. The market value of the
permits can be annualized using an appropriate amortization (or discount) rate. The decision to
sell a commercial fishing permit at a given price is an individual (or private) decision. In
deciding on an acceptable sales price, a permit holder considers past profits from operating the
permit, risk associated with future operation of the permit (both physical and financial), and
many other factors. All these considerations weigh on how heavily a permit seller discounts
(reduces) potential future profits from fishing the permit in order to arrive at a lump-sum value
for the permit. Huppert et al. (1996) specifically looked at Alaska commercial salmon permit
operations and sales and estimated the individual discount rate on drift net permit sales in the
Bristol Bay and surrounding fisheries. This discount rate was estimated from both profitability
and permit sales price data. Huppert et al. estimated the implied discount rate appropriate for
annualizing permit sales prices in this setting at 13.52%. This estimate was consistent with
previous estimates for the fishery.30 Use of the 13.52% discount rate from Huppert results in an
estimated annual permit net profit or net income associated with Bristol Bay commercial salmon
fishing of between $30.4 million and $55.9 million.
Table 65. Current Bristol Bay Salmon Fishing Permit Numbers and sale prices, 2011
Permit type

Salmon (Drift net)
Salmon (Set net)
Total
Number of
permits

1862
981
Current market value
Lower 95%
Confidence
Interval
105,500
28,700

Estimated annual net income
(at 13.52% real discount rate)
Upper 95%
Confidence
Interval
192,700
55,700

Total
Lower 95%
Confidence
Interval
196,500,000
28,100,000
224,600,000
$30,400,000
Upper 95%
Confidence Interval
358,800,000
54,700,000
413,500,000
$55,900,000
Just as there is an implied net economic value associated with the fishing aspect of the Bristol
Bay commercial salmon fishery, as outlined above, there is also a net economic value associated
with expected future profits from investments in fish processing facilities in the region. Data on
Bristol Bay salmon processor average aggregate profit levels is not published. Table 31, above,
shows estimated profit (loss) margins for two years. Clearly, as with permit prices, processor
profits are highly variable year-to-year. The average value added associated with salmon
processing for the Bristol Bay fishery is generally equal to or more than the ex-vessel value.
30 Huppert, Ellis and Nobel (1996) estimated the real discount rate associated with sales of Alaska drift gill-net
commercial permits of 13.52%. Karpoff (1984) estimated the discount rate from sales of Alaska limited entry
permits at 13.95%.
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Salmon processors in the Bristol Bay fishery have an "oligopsony" market structure, in that a
small number of buyers of raw fish exist in the market. Additionally, these buyers are largely
"price makers" in that they set the price paid per pound to fishermen each season. Given the
unique relationship between fisherman that the small number of processors in the Bristol Bay, it
is estimated that processors derive profits (net economic value) equal to that earned by
fishermen. Therefore, for the purposes of this report it is estimated that the NEV for salmon
producers is equal to that for the fishing fleet.
5.2 Subsistence Harvest

The Alaska Department of Fish and Wildlife, Division of Subsistence reports that most rural
families in Alaska depend on subsistence fishing and hunting. ADF&G surveys of rural
communities find that from 92% to 100% of sampled households used fish, 79% to 92% used
wildlife, 75% to 98% harvested fish, and 48% to 70% harvested wildlife. Because subsistence
foods are widely shared, most residents of rural communities make use of subsistence foods
during the course of the year. The subsistence food harvest in rural areas constitutes about 2% of
the fish and game harvested annually in Alaska. Commercial fisheries harvest about 97% of the
statewide harvest, while sport fishing and hunting take about 1%. Though relatively small in the
statewide picture, subsistence fishing and hunting provide a major part of the food supply of
rural Alaska (Subsistence in Alaska, a 2000 Update
http://www.subsistence.adfg.state.ak.us/download/subupdOO.pdf).

The Alaskan subsistence harvest is not traditionally valued in the marketplace. Because the
subsistence resources are not sold, no price exists to reveal the value placed on these resources
within the subsistence economy. The prices in external markets, such as Anchorage, are not
really relevant measures of subsistence harvest value. The supply/demand conditions are unique
to the villages, many of which are quite isolated. Native preferences for food are strongly held
and often differ from preferences in mainstream society. Additionally, because these are highly
vertically integrated economies, substantial value-added may occur before final consumption
(such as drying, or smoking fish and meats). In their research on estimating the economic value
of subsistence harvests, Brown and Burch (1992) suggest that these subsistence harvests have
two components of value, a product value, and what they call an "activity value." The product
value is essentially the market value of replacing the raw subsistence harvest. The activity value
would primarily include the cultural value of participating in a subsistence livelihood. The
activity value component is also associated with the value of engaging in subsistence harvest and
food processing activities. This activity value would include maintaining cultural traditions
associated with a subsistence livelihood.

Duffield (1997) estimated the value per pound of Alaskan subsistence harvest though use of a
cross-sectional hedonic model of community-specific harvest per capita and community per
capita income levels. This "wage-compensating differential model" essentially estimates the
average tradeoff across communities between per-capita subsistence harvest (in pounds of usable
harvest) and per capita income levels. In essence, residents of rural Alaskan communities
tradeoff the opportunity to have higher income in a less rural environment with the opportunity
to harvest larger amounts of subsistence resources in more rural communities.

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There is a substantial economics literature that utilizes the hedonic wage, or wage compensating
differential model. For example, estimates of the trade-off of wages and workplace risk of
mortality are the basis of the statistical value of life estimates widely used in regulatory analysis
of ambient air and other standards (EPA 2008). There is also a literature that relates wages and
amenity values as revealed through choice of location (e.g. Henderson 1982, Clark and Khan
1988). These later models are generally applied to intercity data sets, such as across U.S.
SMSAs. These models are also used to estimate the benefits and costs of climate change (e.g.
Maddison and Bigano 2003).

The application of a compensating wage model to a cross-section of Alaska Villages and towns
is consistent with the view that these Alaska cash-subsistence economies are not just a transitory
phase in economic development. Rather the village economies represent an equilibrium that is a
function of individual choice of where to live and work (Wolfe and Walker 1987; Kruse 1991).

Wolfe and Walker (1987) were the first to estimate a statistical relationship between wage
income and subsistence livelihoods using harvested usable pounds as a measure of subsistence
productivity. Wolfe and Walker were interested in factors that influenced subsistence
productivity, including construction of roads, settlement activity and income. The data was
based on extensive surveys of Alaska villages undertaken by the applied anthropology group at
Alaska Fish and Game, Division of Subsistence. Duffield (1997) used the Wolfe and Walker 98
village dataset in a compensating wage specification to inform subsistence harvest valuation in
the context of the Exxon Valdez oil spill litigation. Hausman (1993), who represented the
defendant in the case (Exxon) also estimated a compensating wage model using the Wolfe and
Walker dataset. Hausman introduced the use of applying an instrumental variable approach to
estimating the model, since wages and subsistence harvests are jointly determined.

Hausman's (1993) estimate of the value of subsistence harvests (1982 dollars) was $33.60 per
pound and Duffield's (1997) was quite similar at $32.46. Table 66 reports an estimated wage
compensating model with a slightly revised dataset to correct for rounding error. This model is
almost identical to the earlier Hausman (1993) and Duffield (1997) estimates at $32.89 per
pound (1982 dollars).

The estimated wage compensating differential model shown in Table 66 uses a two-stage least
squares methodology and a linear specification. The two-stage least squares method is used to
statistically address the fact that income and harvest levels in the communities are at least partly
co-determined. The first stage of the model uses an instrumental variable (the percent of adults
in each community with 4 or more years of college education) along with the remaining regional
indicator variables to predict adjusted gross income per capita for each community. This
predicted income level then was used in the second stage regression. The model explains 70% of
the observed variation in harvest levels across communities, and only two of the 14 explanatory
variables are not significant at the 90% level of confidence or greater. The implied value per
pound of subsistence harvest is calculated from the parameter estimate for Adjusted Gross
Income Per Capita. The implied value per pound is the negative inverse of the income parameter
(-0.05351) times the average cost of living adjustment for the villages compared to Anchorage
(1.7598). [(1/-0.0531)*-! = $18.83 *1.7598 = $32.89]

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The estimated harvest income model is based on now 30 year-old data. Indexing these results
using average Alaska personal income per capita suggests that were this same relationship to
hold today, total subsistence harvest NEV would be on the order of $75.58 per pound. For
purposes of this report, a range of values in the following analysis uses both the estimated $32.89
value, based on the original dataset and specification, and the inflation adjusted value of $75.58
per pound.
Table 66. Estimated Two-Stage Least Squares Wage Compensating Differential Model of Subsistence
Harvest in 90 Alaska Communities (Duffield 1997).
Variable
Intercept
Adjusted Gross Income
Per Capita
Alaska Peninsula
Copper Basin
Kenai Peninsula
Kodiak
North Slope
NW Arctic
N Cook Inlet
Prince William Sound
South East
South West
Upper Xanana
Urban
West
Observations
R-Squared
Endogenous Variable
Instrumental Variable
Parameter
Estimate
1165.956
-0.05351
-549.018
-622.873
-564.685
-388.762
-401.538
-108.213
-629.667
-565.038
-504.528
-257.009
-632.759
-326.635
-201.926
Standard Error
161.4796
0.030018
97.51753
104.9037
177.5385
108.8402
169.0253
203.9510
203.2403
157.4034
137.8750
91.52865
117.6974
336.9811
92.04808
t Value
7.22
-1.78
-5.63
-5.94
-3.18
-3.57
-2.38
-0.53
-3.10
-3.59
-3.66
-2.81
-5.38
-0.97
-2.19
90
0.704
Adjusted Gross Income Per Capita (adjusted to Anchorage dollars using cost-of-
living index)
% of adults with 4 or more years of college (plus region indicator variables)
Based on both the Hausman (1993) and Duffield (1997) analyses, the correct in principle way to
value subsistence harvests is to use the compensating wage differential approach. With reference
to the Brown and Burch (1992) perspective, the compensating wage estimate includes both
product and activity value. Duffield (1997) also reports a replacement cost estimate of just
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product values for subsistence harvests at $13.28 per pound.
value is estimated at $18.86 per pound.32
31
In 2009 dollars, this product
Table 67 shows the accounting of ADF&G Division of Subsistence estimates of total annual
subsistence harvest in most communities in Bristol Bay. This total has been adjusted to include
population in the region not included in the ADF&G subsistence harvest estimates. In total, we
estimate that about 2.6 million usable pounds of subsistence harvest per year occur in the Bristol
Bay region. Valued at an estimated range of $32.89 to $75.58 per pound, this harvest results in
an estimated net economic value annually of subsistence harvest of between $84.3 and $193.7
million (Table 68).

Table 67. Estimated Total Annual Bristol Bay Subsistence Harvest (usable pounds of harvest)
Bristol Bay Area Community /year of harvest
data
Aleknagik 1989
Clark's Point 1989
Dillingham 1984
Egegik 1984
Ekwok 1987
Igiugig 2005
Iliamna 2004
King Salmon 2008
Kokhanok 2005
Koliganek 2005
Levelock 2005
Manokotak 2000
Naknek 2008
New Stuyahok 2005
Newhalen 2004
Nondalton 2004
Pedro Bay 2004
Pilot Point 1987
Port Alsworth 2004
Port Heiden 1987
South Naknek 2008
Ugashik 1987
Togiak City 2000
Twin Hills 2000
Total surveyed communities
Un-surveyed communities (estimated)
Total including un-surveyed areas
Total Usable Pounds Raw Subsistence
Harvest
64,824
75,020
563,618
41,856
91,655
27,100
51,121
117,062
115,600
187,891
36,363
131,716
143,616
198,390
131,480
58,712
12,852
26,112
21,147
41,616
21,172
9,768
200,982
36,926
2,406,599
156,714
2,563,313
Source: Estimates of community-specific subsistence harvest levels are contained within the Subsistence Technical
Report Series, available at, http://www.adfg.alaska.gov/sf/publications/
31 This value is the simple average of the replacement cost of lost harvest between two definitions of households in
the Duffield (1997) paper, p. 109, Table 4.
32 It should be noted that a significant component of subsistence harvest in some communities is marine mammals, a
resource with a very high market replacement cost.

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It should be noted that although the total annual value of subsistence harvests implied by the
wage compensating differential model is large, simply the market replacement cost of these
resources is fully 57% of the lower-bound estimate and 25% of the upper-bound estimate. In
addition to simply procuring the usable pounds of raw subsistence harvest, many of these
resources have substantial value-added in the form of processing by drying, smoking, or other
preserving, cleaning, or other processing methods. This value-added is also captured within the
context of the wage compensating differential model.

Another perspective on the revealed economic significance of subsistence harvests in Bristol Bay
is seen by comparing the implied NEV associated with subsistence activities and reported per
capita income in the region. For the 7,475 Bristol Bay residents (74% of who are Native
Alaskan) subsistence harvests valued at $32.89 per pound imply that the value of these harvests
are about 22% of their total combined per capita 2009 personal income (as reported by BEA) and
subsistence value. Valued at $75.74 per pound, subsistence harvest value is about 39% of total
income and subsistence value. Yet another perspective on the subsistence harvest value is the
relative effort or allocation of time put into the subsistence sector versus the cash income sector.
The effort put into the subsistence sector is estimated to be the same or more than the full-time
equivalent jobs included in the cash sector.
Table 68. Estimated Net Economic Annual Value of Bristol Bay Area Subsistence Harvest
Estimates of Subsistence Value
Value based on Harvested Product
Value
Value based on Wage Compensating
Differential Approach (Unadjusted 1982
Model)
Value based on Wage Compensating
Differential Approach (1982 results
indexed to 2009 $ using Alaska Per
Capita Personal Income )33
Per Pound
Value
$18.86
$32.89
$75.58
Total
Subsistence
Harvest
2,563,313
2,563,313
2,563,313
Total Annual Value
(Million 2009 $)
$48.3
$84.3
$193.7
5.3 Sport Fishing Net Economic Value

In addition to the direct expenditures that Bristol Bay area sport anglers make each year, there is
substantial net economic value attached to the trips these anglers take to the region. The 2005
Bristol Bay angler survey asked respondents a series of questions relating to what they spent on
their fishing trip, and how much, if any, more they would have been willing to spend to have the
same experience. Respondents were presented with a set of amounts ranging from $0 to $2,000,
1 http://www.bea.gov/iTable/index regional.cfm (accessed 4/25/12)

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and asked to mark the greatest additional increase in spending they would have made to take the
same trip. Table 71 shows the mean willingness to pay estimate for the two groups. The net
economic value from the survey data was estimated using an interval estimation model.
A measure of the net economic value of sport fishing trips is the amount anglers are willing to
pay over and above the costs of their trips. This willingness to pay is also referred to as net
economic benefit. There is a large economics literature on estimating sport fishing net economic
benefits (Rosenberger and Loomis 2001). The method for estimating these benefits here is
contingent valuation using the so called "payment card" question format.

Following questions on their trip expenditures, survey respondents were asked whether they felt
their trip was worth more than the amount they actually spent. Those who answered "yes" were
then asked, "What is the largest increase over and above your actual costs that you would have
paid to be able to fish your primary destination?" Respondents were presented with a series of
dollar amounts ranging from $10 to $2,000. Table 69 shows the percentage of both resident and
nonresident Bristol Bay anglers who responded that they would have paid the various additional
amounts to take their Bristol Bay fishing trip.
Table 69. Responses to Current Trip Net Economic Value Question

Willing to Pay More
$ 10
$ 25
$ 50
$ 100
$ 250
$ 500
$ 750
$ 1,000
$ 1,500
$ 2,000
Other amount
NONRESIDENTS
Percent
63.0%
1.1%
0.3%
0.2%
6.2%
16.2%
15.9%
2.5%
9.1%
3.7%
2.3%
4.3%
RESIDENTS
Percent
73.3%
0%
2.1%
3.6%
16.5%
20.5%
7.5%
3.6%
0%
0%
3.6%
15.7%
The estimates of willingness to pay models based on the Table 69 data were developed using a
maximum likelihood interval approach (Welsh and Poe 1998). As noted, respondents were
asked to choose the highest amount he or she was willing to pay from a list of possible amounts.
It was inferred that the respondent's true willingness to pay was some amount located in the
interval between the amount the respondent chose and the next highest amount presented. The
SAS statistical procedure LIFEREG was used to estimate the parametric model of willingness to
pay based on the underlying payment card responses.

Table 70 shows the estimated parametric willingness to pay for trips to Bristol Bay fisheries.
Nonresident anglers state their trip was worth approximately $450 more, on average, than they
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actually paid. Resident Bristol Bay anglers stated they were willing on average to pay an
additional $320 for their most recent trip. These estimates are similar to other estimates for
Alaska sport fishing (Duffield et al. 2002; Jones and Stokes 1987).
Table 70: Estimated Mean Willingness to Pay for Anglers' Recent Trip to Bristol Bay
Statistic
Estimated mean willingness to pay in addition to trip
costs for those willing to pay more
Percent of respondents willing to pay more for their
trip
Net willingness to pay for Bristol Bay fishing trips for
all anglers
Non-residents
$793
63.0%
$500
Residents
$480
73.3%
$352
The net economic value per trip estimates shown in Table 70 were calculated from the results of
a bivariate statistical model of the payment card response data using a variant of survival
analysis to examine censored interval data. The chi-square test of significance for the key
parameters from these models show the estimated coefficients to be statistically significant.

Based on an estimated annual use level of 12,464 trips for nonresidents, and 16,903 trips for
Alaska residents, we estimate that the annual net economic value of fishing trips in the Bristol
Bay region is approximately $12.2 million.
Table 71. Estimated Willingness to Pay for Sportfishing Fishing in the Bristol Bay Region

Estimated mean net willingness to pay
Estimated number of trips/year
Total estimated Net Economic Value
Total annual value
Residents
$ 352
16,903
$5,950,093
Nonresidents
$ 500
12,464
$6,228,350
$12,178,443
5.4 Sport Hunting Net Economic Value

As in the case of sport fishing, there is additional value associated with sport hunting, above
what is actually spent on the activity. Table 72 details the estimation of annual net economic
value of big game hunting in the Bristol Bay region. Table 72 utilizes ADF&G estimates of
hunter numbers in the game management units associated with the Bristol Bay area, and on
estimates of net willingness to pay per trip for hunting (from Miller and McCollum 1994,
adjusted to current, 2009 dollars). It is estimated that nonresident net economic value of Bristol
Bay hunting is approximately $1 million annually. The annual net economic value of big game
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hunting in the Bristol Bay region for Alaska residents is estimated at about $380,000. Therefore
the total annual estimated net economic value of big game hunting in this region is $1.4 million.

Table 72. Estimated annual big game hunting net economic value for Bristol Bay region
Species / Statistic

Moose
Caribou
Brown bear

trips
352
230
741
Total
Nonresidents
Value/ trip
$581
$640
$897

Non-local residents
NEV
$ 204,549
$ 147,298
$ 665,028
$ 1,017,000
Trips
291
311
717

Value/ trip
$268
$250
$307

NEV
$ 77,998
$ 77,892
$ 220,535
$ 376,000
5.5 Wildlife Viewing and Tourism Net Economic Value

The 1991 study by McCollum and Miller estimated the net economic value of wildlife watching
trips in Alaska. These values adjusted to current dollars results in an estimated value per trip of
$199. Using the 40,164 visitor trips to the region we estimate a 2009 net economic value of
wildlife watching of about $8.1 million.
5.6 Total Net Economic Value and Present Value and Inter-temporal
Issues
Commercial salmon fishery net economic values for fishermen are derived by annualizing the
total value of the perpetual permits to fish the Bristol Bay waters held by fishermen. The value of
these permits is reflected in the prices paid for them when they are exchanged in an open market
and reported by the Commercial Fish Entry Commission. These are on the order of $156,000 for
a drift gillnet permit in 2011, and have been as high as $200,000 as recently as 1993.

The total value of Bristol Bay permits—calculated as the number of permits multiplied by the
permit price—provides an estimate of the total present discounted value of expected future
profits from the fishery. Based on 1991-2011 average permit sales prices (in constant 2011
dollars) the estimated 95% confidence interval on the total value of Bristol Bay permits (both
drift net and set net fisheries combined) was between $224.6 million and $413.5 million.

Multiplying the total value of a permit by the rate of return a permit holder demands on a permit
investment provides a measure of the annual profit permit holders expect to earn. Using a
13.52% amortization (or discount) rate estimated by Huppert et al. (1996) suggests that annual
expected profits (net economic value) from Bristol Bay commercial fishing is currently between
$30.4 million and $55.9 million. Note that this does not include expected profits from fish

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processing. Subsistence harvests are valued based on the willingness-to-pay revealed through
tradeoffs of income and harvest in choice of residence location (Duffield 1997).

Source: ADFG.ADLWD
a
Figure 79. Selected Bristol Bay Salmon Processor Costs: 2001-2009
The sportfish net economic values are angler recreational benefits (consumer surplus) in Duffield
et al. (2007). These estimates are consistent with values from the extensive economic literature
on the value of sportfishing trips (for example Duffield, Merritt and Neher 2002). Sport hunting
values are based on studies conducted in Alaska by McCollum and Miller (1994). In addition to
recreationist's net benefits, net income (producer's surplus) is recognized by the recreation and
tourism industry. This is a component that remains to be estimated. Annual direct use net
economic values for recreation use of the Bristol Bay area is estimated to be $22.1 million,
including $12.2 million for sport fishing, $1.8 million for sport hunting, and $8.1 million for
wildlife viewing and other tourism.
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Based on the National Research Council panel on guidelines for valuation of ecosystem services
(NRC 2005), it is important to include intrinsic or passive use values (aka "non-use" values) in
any net economic accounting of benefits (Figure 80).
ECOSYSTEM
HUMAN ACTIONS
(PRIVATBFUBLIC)
ECOSYSTEM GOODS
& SERVICES
J
L
Use values I
Pa;; ijeU;e Value;
L* y. cci&rco,
Figure 80. Flows of Ecosystem Services (adapted from (National Research Council 2005))
A major unknown is the total value related to existence and bequest motivations for passive use
values. Goldsmith et al. (1998) estimated the existence and bequest value for the federal wildlife
refuges in Bristol Bay at $2.3 to $4.6 billion per year (1997 dollars). There is considerable
uncertainty in these estimates, as indicated by the large range of values. Goldsmith's estimates
for the federal wildlife refuges are based on the economics literature concerning what resident
household populations in various areas (Alberta, Colorado) (Adamowicz et al. 1991; Walsh et al.
1984; Walsh et al. 1985) are willing to pay to protect substantial tracts of wilderness. Similar
literature related to rare and endangered fisheries, including salmon, could also be appealed to
here. It is possible that from a national perspective the Bristol Bay wild salmon ecosystems and
the associated economic and cultural uses are sufficiently unique and important to be valued as
highly as wilderness in other regions of the U.S. Goldsmith et al.'s (1998) estimates assume that
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a significant share of U.S. households (91 million such households) would be willing to pay on
the order of $25 to $50 per year to protect the natural environment of the Bristol Bay federal
wildlife refuges. The number of these households is based on a willingness to pay study (the
specific methodology used was contingent valuation) conducted by the State of Alaska Trustees
in the Exxon Valdez oil spill case (Carson et al. 1992). The findings of this study were the basis
for the $1 billion settlement between the State and Exxon in this case. These methods are
somewhat controversial among economists, but when certain guidelines are followed, such
studies are recommended for use in natural resource damage regulations (for example, see Ward
and Duffield 1992). They have also been upheld in court (Ohio v. United States Department of
Interior, 880 F.2d 432-474 (D.C. Cir.1989)) and specifically endorsed by a NOAA-appointed
blue ribbon panel (led by several Nobel laureates in economics) (Arrow et al. 1993).

While the primary source of passive use values for Bristol Bay are likely to be with national
households (lower 48), it is important to note that the Alaska natives living in Bristol Bay also
likely have significant passive use values for the wild salmon ecosystem. For example, Boraas
(2011) quotes Bristol Bay natives in saying "We want to give to our children the fish, and we
want to keep the water clean for them.. .It was a gift to us from our ancestors, which will then be
given to our children.) (Boraas p. 33).

Goldsmith's estimates for just the federal refuges may be indicative of the range of passive use
values for the unprotected portions of the study area. However, there are several caveats to this
interpretation. First, Goldsmith et al. estimates are not based on any actual surveys to calculate
the contingent value specific to the resource at issue in Bristol Bay. Rather, they are based on
inferences from other studies (benefits transfer method). Second, these other studies date from
the 1980's and early 1990's and the implications of new literature and methods have not been
examined. Additionally, the assumptions used to make the benefits transfer for the wildlife
refuges may not be appropriate for the larger Bristol Bay study area which includes not only the
wildlife refuge, but also two large national parks. This topic is an area for future research.
Table 73. Summary of Bristol Bay Wild Salmon Ecosystem Services, Net Economic Value
per Year (Million 2009 $)
Ecosystem Service
Commercial salmon fishery
Fishing Fleet
Fish Processing
Sport fishing
Sport hunting
Wildlife viewing / tourism
Subsistence harvest
Total Direct Use Value
Low estimate

$30.4
$30.4
$12.2
$1.4
$8.1
$84.3
$166.80
High estimate

$55.9
$55.9
$12.2
$1.4
$8.1
$193.7
$327.20
Table 73 details the estimates of annual net economic values for the major sectors tied to the
Bristol Bay Ecosystem. The scope of this characterization report is to use existing data,
information, and estimates to provide a comprehensive picture of the economic structure and
associated values related to the Bristol Bay Ecosystem. The estimates shown in the table are

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based on a variety of sources and methods, and based on data and estimates from a range of
years. These estimates have been presented in constant 2009 dollars. Where possible, a range of
estimates has been presented.

Differences in net economic values across sectors are driven by several factors, including the
number of individuals impacted, the type of market structure, and the scope of resources and
resource services included in the estimates. For instance, the estimates for subsistence NEV are
between 38% and 73% higher than for the commercial salmon fishery (and processing) sectors.
These two sectors have several key differences, however. The market for commercial salmon is
highly competitive, with other fisheries (as well as farmed salmon) providing strong price
competition and thus keeping profits and implied NEV low in the sector. Additionally, the
estimates of commercial fishery NEV are based on commercial fishing permit sales prices.
These sales of generally less than 10% of active permits in a given year represent "marginal"
prices, rather than the "average permit value" to all permit holders. Those permit holders who do
not sell value their permits more highly than those who do. The commercial fishery NEV
estimates, therefore, are based on conservative marginal values while the subsistence values are
less conservative "average" values. A third difference between these estimates is that the
commercial fishery NEV is narrowly tailored to salmon fishing and processing, while the
subsistence harvest NEV includes all resources used (including land and marine mammals, fish,
shellfish, and plants). Salmon harvest only accounts for about one-half of all Bristol Bay
subsistence harvest (in usable raw harvest weight).

The estimates in Table 73 are for annual net economic values. Since these are values for
renewable resource services that in principle should be available in perpetuity, it is of interest to
also consider their present value (e.g. total discounted value of their use into the foreseeable
future). Recent literature (OMB 2003; EPA 2010; Weitzman 2001) provides some guidance on
the use of social discount rates for long term (intergenerational) economic comparisons.

The controlling guidance document for discounting in Federal cost benefit analysis, OMB
Circular A-4 (2003), generally requires use of discount rates of 3% and 7%, but allows for lower,
positive consumption discount rates, perhaps in the 1 percent to 3 percent range, if there are
important intergenerational values. The circular states,

"Special ethical considerations arise when comparing benefits and costs across generations.
Although most people demonstrate time preference in their own consumption behavior, it
may not be appropriate for society to demonstrate a similar preference when deciding
between the well-being of current and future generations. Future citizens who are affected by
such choices cannot take part in making them, and today's society must act with some
consideration of their interest.

One way to do this would be to follow the same discounting techniques described above and
supplement the analysis with an explicit discussion of the intergenerational concerns (how
future generations will be affected by the regulatory decision). Policymakers would be
provided with this additional information without changing the general approach to
discounting.
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Using the same discount rate across generations has the advantage of preventing time-
inconsistency problems. For example, if one uses a lower discount rate for future generations,
then the evaluation of a rule that has short-term costs and long-term benefits would become
more favorable merely by waiting a year to do the analysis. Further, using the same discount
rate across generations is attractive from an ethical standpoint. If one expects future
generations to be better off, then giving them the advantage of a lower discount rate would in
effect transfer resources from poorer people today to richer people tomorrow.

Some believe, however, that it is ethically impermissible to discount the utility of future
generations. That is, government should treat all generations equally. Even under this
approach, it would still be correct to discount future costs and consumption benefits generally
(perhaps at a lower rate than for intragenerational analysis), due to the expectation that future
generations will be wealthier and thus will value a marginal dollar of benefits or costs by less
than those alive today. Therefore, it is appropriate to discount future benefits and costs
relative to current benefits and costs, even if the welfare of future generations is not being
discounted. Estimates of the appropriate discount rate appropriate in this case, from the
1990s, ranged from 1 to 3 percent per annum." p. 35.

The key question in deciding on an appropriate discount rate or range of rates for analysis is
whether the Bristol Bay ecosystem is a resource of intergenerational significance. Clearly, this
resource base and ecosystem that has been relied on for thousands of years by Alaska natives,
and now has a long-term significance to a growing number of nonnatives, is the very definition
of an intergenerational resource.

Weitzman, (who's work is cited both in the EPA guidance (EPA 2000) and in OMB guidance
(Circular A-4 (2003))) conducted an extensive survey of members of the American Economic
Association, and suggests a declining rate schedule, which may be on the order of 4 percent
(real) in the near term and declining to near zero in the long term. He suggests a constant rate of
1.75% as an equivalent to his rate schedule. Table 74 shows the estimated net present value in
perpetuity of direct use values within the Bristol Bay Ecosystem. The table shows a range of
alternative discount rates from the standard "intragenerational" rates of 7% and 3% to the more
appropriate "intergenerational" rates for the Bristol Bay case of 1.75% and 1.0%. The entire
range of NPV estimates in the table is from $2.4 to $32.7 billion. The range of estimated direct
use NPV of the resource using the more appropriate intergenerational discount rates is from $9.5
to $32.7 billion. These estimates are likely quite conservative as they do not include estimates
of passive use values held by those living outside the Bristol Bay Region, but are limited to
direct economic uses of the wild salmon ecosystem services.

Table 74. Estimated Net Present Value of Bristol Bay Ecosystem Net Economic Use Values
and Alternative Assumed Perpetual Discount Rates
Estimate
Low Estimate
High Estimate
Net Present Value (million 2009 $)
Annual Value
$166.80
$327.20
7% Discount
$2,383
$4,674
3% Discount
$5,560
$10,907
1.75% Discount
$9,531
$18,697
1% Discount
$16,680
$32,720
213
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Appendix F

Biological Characterization:
Bristol Bay Marine Estuarine Processes,
Fish and Marine Mammal Assemblages
F-l
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Biological Characterization:

Bristol Bay Marine Estuarine Processes,

Fish and Marine Mammal Assemblages

March 2012
Prepared for

U.S. Environmental Protection Agency, Region 10

1200 6th Avenue, Seattle Washington, 98101

Prepared by

National Oceanic and Atmospheric Administration

Habitat Conservation Division, National Marine Fisheries Service

222 West 7th Avenue Anchorage, Alaska 99513-7577
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Acknowledgements

This report was compiled and written by Douglas Limpinsel, NOAA, Habitat Conservation
Division, Alaska Region. Acknowledgements should be extended to all of the following people
for verbal or literary contributions, direction and content of the discussion, wholly or in part. In
alphabetical order by affiliation and last name.

Alaska Department of Fish and Game: Timothy Baker, Lowell Fair, Laura Jemison, Lori
Quakenbush

Bristol Bay Native Community and Associates: Robert Andrew, Gregory Andrew, Peter
Andrew, Daniel Chythlook, Susan Flensburg, Tina Tinker

NOAA/NMFS - Alaska Fisheries Science Center and National Marine Mammal Lab:
Robin Angliss, Kerim Aydin, Steve Barbeaux, Troy Buckley, Daniel Cooper, Keith Cox,
Douglas Demaster, Edward Farley, Robert Foy, Sarah Gaichas, Jeffry Guyon, Paula Johnson,
Sonja Kromann, Robert Lauth, Robert McConnaughey, Jamal Moss, Philip Mundy, James
Murphy, Daniel Nichol, Olav Ormseth, Elizabeth Sinclair, Thomas Wilderbuer

NOAA/NMFS - Alaska Region, Habitat Conservation Division: Matthew Eagleton, Jeanne
Hanson, Jon Kurland, Brian Lance, John Olson, Eric Rothwell

NOAA/NMFS - Alaska Region, Protected Resources Division: Michael Williams

University of Alaska - Fairbanks and Bristol Bay Campus: Ken Coyle, Todd Radenbaugh

University of Washington - School of Fisheries and Joint Institute for the Study of the
Atmosphere and Ocean: Nancy Kachel, Katherine Myers (retired), Thomas Quinn, Daniel
Schindler.
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IV
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ABSTRACT

Bristol Bay is characterized as a large shallow sub-arctic marine estuary with distinct inner and
outer bay processes. The bay lies within the coastal or inner domain. The outer bay is heavily
influenced by marine currents, tides and oceanic processes from the Southeastern Bering Sea.
Nushagak and Kvichak bays, waters between Cape Constantine in the north and Ugashik Bay in
the south, comprise much of the inner bay complex. These inner bays are heavily influenced by
high volumes of fresh water discharge from several river systems. This fresh water influence
dominates the head of Bristol Bay and much of the Togiak Bay nearshore zone. Nearshore
currents in the larger bay generally follow a counter clock wise gyre, moving East along the
Alaska Peninsula before moving north and eventually west around Cape Newenham. Species
assemblage and trophic interaction between marine invertebrates, forage, anadromous and
groundfish species is complex and interrelated. Walleye pollock, yellowfin and rock sole, and
red king crab represent marine species that in larval and juvenile phases are transported along
currents into nearshore estuarine nursery habitat. Recent studies suggest complex predator prey
assemblages in nutrient rich convergence zones between the inner and outer bay complex and
along the northern nearshore zone. All five species of Pacific salmon are well established in
these waters with historically stable and productive populations. Salmon, a unique keystone
species, facilitate energy and nutrient transfer across multiple trophic levels from terrestrial head
waters through pelagic marine ecosystems. Out bound migrations of billions of salmon smolt
provide nutrition to numerous trophic levels and marine species. As juveniles, salmon smolt are
recognized as a forage fish species. In their returning adult phase, they provide a valuable
nutrient source to marine mammals and subsidize watersheds in the form of Marine Derived
Nutrient (MDN). Outwelling MDN flushed into estuaries has recently been recognized to further
contribute nutrient to estuarine processes. The range and distribution of Bristol Bay salmon has
been documented throughout the Bering sea, as far north as the Chukchi Sea and south into the
North Pacific and Gulf of Alaska. Several marine mammal species such as killer and beluga
whales, and seals and Steller sealion are known not only to inhabit Bristol Bay, but pursue both
juvenile and adult salmon up rivers in the region.
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VI
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Table of Contents

BRISTOL BAY 1

Estuarine Processes - Marine Influence 2

Estuarine Processes - Terrestrial Influence 2

Bristol Bay Marine Fish Assemblages 4

Inner Estuarine Fish Assemblage 4

Nearshore Fish Assemblages 4

Offshore Fish Assemblages 5

Bristol Bay Salmon 6

Range and Distribution 7

Salmon Contribution to Trophic Levels 8

Bristol Bay - Marine Mammals 9

Pinnipeds 10

Whales: Toothed Whales - Ondontocetes 11

Whales: Baleen Whales - Baleenotropha 12

Bibliography: By Section 13

Bristol Bay Marine and Estuarine Processes 13

Bristol Bay Fish Assemblages 15

Bristol Bay Salmon 18

Bristol Bay Marine Mammals 22

Tables 29

Table 1. Fish and Invertebrate Species List 29

Table 2. Marine Mammals Species List 39
VII
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VIII
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BRISTOL BAY
For the purpose of this discussion, Bristol Bay is the marine water east of the 162 longitude line,
including the contiguous shoreline (Fig 1). In this context, Bristol Bay contains approximately
1,300 kilometers of linear shoreline and nearly 65,400 sq kilometers of semi pelagic, nearshore,
and estuarine habitat.

Bristol Bay is characterized as a sub-arctic marine estuary of large size and shallow depth, with
distinct inner and outer bay processes. The inner bay processes are continuously fed large
volumes of fresh water from several watersheds and river systems, with salinity gradients
increasing toward the 162 line. The benthic topography is essentially flat (average gradient of
0.02 percent) with minimal variations in relief toward the continental slope. Within this gentle
contour Bristol Bay achieves an approximate maximum depth of 70m (Moore 1964, Buck et al.
1974).
[Mlliiujhnm

NushagakBay
KvichakBay
SOUTH EAST
BERING SEA
Figl. Bristol Bay: Showing general current patterns (green arrows), benthic contour lines (50 and 100m
blue dash), 162° longitude line (brown dash), and significant land marks as reference (labeled).

Historically, Bristol Bay has been identified as having two relatively distinct current zones
referred to as inner and outer bays. Currents were generally characterized as moving in a counter
1
-------
clockwise gyre under the influence of 3-23 foot tides (Buck et al. 1974, Straty 1977, Straty and
Jaenicke 1980). Recent investigations describe three current driven domains essentially based on
depth: coastal or inner domain (0-50 m depth), a middle domain (50-100 m depth), and an outer
or shelf domain (100-200 m) (Kinder and Coachman 1978, Kinder and Schumacher 1981,
Coachman 1986, Schumacher and Stabeno 1998, Stabeno et al. 2001).

Though distinction in physical properties can be documented (salinity, temperature, turbidity),
any boundary between these zones is always moving, shifting and waning under constantly
changing seasonal weather patterns and marine influence of tides and currents. Earlier
descriptions of the inner and outer bay complexes lie within these more recent descriptions of the
coastal and inner domain. Bristol Bay and associated marine and estuarine processes are heavily
influenced by often severe Eastern Bering Sea (EBS) and Arctic weather.

Estuarine Processes - Marine Influence

Outer Bristol Bay is essentially an extension of the EBS. Flood tides from the North Pacific
enter the EBS through several Aleutian Island passes contributing to the Aleutian North Shore
Current (ANSC) (Schumacher et al. 1979, Reed and Stabeno 1994, Stabeno et al. 2002 and
Stabeno et al. 2005). To the east of Unimak Pass, the remnant of this current continues as the
Bering Coastal Current (BCC), moving northeasterly along the Alaska Peninsula toward Bristol
Bay (Kachel 2011, pers. comm.). Much of this current diverts north along the 50 meter contour
forming a subtle, always shifting boundary between inner and outer bay waters (Coachman
1986). These currents eventually flow north and west around Cape Newenham toward Nunivak
and Pribilof Islands. Seasonal levels of upwelling marine nitrates, carbon, phosphates and silica
are quite high throughout the estuaries' inner domain contributing to the complexity of Bristol
Bay (Buck et al. 1974, Stockwell et al. 2001, Kachel et al. 2002, Coyle and Pinchuk 2002,
Stabeno and Hunt 2002, Ladd et al. 2005). Considerable mixing occurs at the convergence of
the inner and outer bay waters, often the area between Cape Constantine and Cape Newenham.
Benthic substrate in the outer bay generally consists of silts and mud to vast aggregates of sand,
gravel, cobble, and boulder (Sharma et al. 1972, NOAA 1987, Smith and McConnaughey 1999).

Estuarine Processes - Terrestrial Influence

Marine characteristics of the inner bay are heavily influenced by continual terrestrial freshwater
runoff from several river systems (Straty 1977, Straty and Jaenicke 1980). Four large rivers flow
into Nushagak Bay: the Igushik, Snake, Wood-Tikchik and Nushagak, and three rivers flow into
Kvichak Bay: the Naknak, Alagnak, and Kvichak.

The contributing discharge was once cited as 112x10 9 cu. m of fresh water annually (-125,400-
cfs annual average) contributed to the inner bay and estuary complex (Buck et al. 1974). The
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Nushagak and Kvichak Rivers drain 22,172 square miles (14,190,134 acres) of watershed
(USGS 2011). The Nushagak River has a mean annual discharge of 28,468 cfs, based on the
summation of the Nushagak River gage (USGS No. 15302500, 23,645 cfs) and the Wood River
gage (USGS No. 15303000, 4,823 cfs). The Kvichak River USGS gage (15300500) located at
Iguigig (the outlet of Lake Iliamna) has an average annual flow of 17,855 cfs. Assuming these
three gauges represent an accurate estimate, that total discharge is 46,323 cfs, or approximately
33,536,000-ac-ft per year1. There are other sources of fresh water contribution not monitored or
included in this estimate.

This fresh water influence dominates the head of the bay between April and November. Out-
welling water contributions are significantly higher in the summer than winter due to freezing
surface water conditions in the watersheds. As a result, summer ebb tide currents often
considerably exceed the flood tides. Discharge from these watersheds keep the inner bay waters
colder than the outer bay in early spring and summer; however, by mid-summer these
temperature regimes reverse with much warmer terrestrial discharges (Buck et al. 1974).
Additionally, the counter-clockwise gyre of the inner bay concentrates these freshwater
discharges in Nushagak Bay and maintains lower salinity compared to Kvichik bay. The highest
recorded sea surface salinity measurement in the middle estuary of the Nushagak is 10 parts per
thousand (ppt), compared to 20ppt in the Kvichik (Radenbaugh 2011, pers. comm.).

The inner Bristol Bay coastal domain exhibits the least saline though greatest temperature
fluctuation of the three domains due to tremendous terrestrial freshwater influences (Straty and
Jaenicke 1980). Earlier studies characterizing temperature and salinity gradients illustrate
differences in salinity and temperature regime between the innermost bay (salinity 28.9% and
temp 11.4°C) and the outermost bay (salinity 32.7% and temp 7.4°C) (Buck et al. 1974, NOAA
1987). Recent analysis of oceanographic currents, condition, and nutrients of the inner domain
(inner and outer bay) confirms generally shallow, wind-driven, well-mixed, homogenous,
nutrient-laden waters (Coyle and Pinchuk 2002, Kachel et al. 2002, Stabeno and Hunt 2002).
Benthic substrate in the inner bay consists of mostly a composite of mud, silts, sands, and patchy
gravels (Sharma et al. 1972, NOAA 1987, Smith and McConnaughey 1999).
The total discharge for the three river systems calculated as the annual sum of the daily mean discharges for respective periods of record.
Kvichak River 1967-1987, Nushagak River 1977-1993, Wood River 1957-1970.
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Bristol Bay Marine Fish Assemblages

Inner Estuarine Fish Assemblage

Recent biological survey efforts in the Nushagak Bay estuary indicate that the dominant species
in numbers and biomass include bay shrimp (Crangon alaskensis\ Gammarid amphipods and
mysiids (Gammarus sp.) (Radenbaugh 2010, pers. corns.). Walleye pollock (Theragra
chalcogramma), generally recognized as a semi pelagic species, have been identified in these
nearshore surveys between Protection and Etolin Points. Flatfish species (Pleuronectiform.es)
such as yellowfm sole (Limanda asperd) have also been confirmed in nearshore habitats.
Numerous other fish and invertebrate species are also abundant.

Nearshore surveys conducted by NOAA's Alaska Fisheries Science Center (NOAA-AFSC) in
Nushagak and Togiak bays further illustrate biodiversity of nearshore fish and invertebrate
species (Olmseth 2009). Over 40 fish and invertebrate species were encountered. Most captured
individuals were less than 20 cm in length. Of these species, shrimp (Crangonidae) and rainbow
smelt (Osmerus mordax) were the most abundant species encountered occurring in almost every
trawl and beach seine. The dominance of these species in catches was especially high in very
shallow water with mud and silt bottoms. Forage fish species identified were salmon smolt
(Salmonidae), capelin (Mallotus villosus) and herring (Clupea pallasii), as well as poachers
(Agonidae), sculpin (Cottoided), flatfish (Pleuronectiformes), and greenling (Hexagraaidae).

Nearshore Fish Assemblages

The importance and contribution of forage fish populations to marine trophic levels and
ecosystems are widely recognized. Forage fish species such as Pacific herring, eulachon
(Thaleichthyspacificus)., capelin, and rainbow smelt are all well documented in different
nearshore zones of Bristol Bay (Warner and Shafford 1981, Mecklenburg et al. 2002, Bernard
2010). Pacific herring are known to spawn in nearshore waters of Togiak and along the northern
shoreline of the Alaska Penninsula (Bernard 2010). Sand lance (Ammodytes hexapterus) have
been found in particular abundance in these nearshore waters of the Alaska Peninsula (McGurk
and Warburton 1992). Even Bristol Bay salmon smolt are recognized within the forage fish
guild (Gaichas and Ay din 2010).

Surveys conducted primarily to characterize the presence and distribution of forage fish species
(sand lance and rainbow smelt) in Bristol Bay nearshore waters also identified several species of
groundfish, Pacific cod (Gadus macrocephalus) and walleye pollock, as well as juvenile sockeye
salmon (Oncorhynchus nerkd) (Isakson et al. 1986, Houghton 1987). In one phase of this survey
effort, juvenile sockeye salmon were more abundant than any forage fish or juvenile ground fish
species encountered. Present again, though in lesser numbers, were Pacific herring, capelin,
pond and surf smelt, and eulachon. The presence, abundance, and biodiversity of these species
4
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in Bristol Bay estuaries and nearshore habitat reflect our current understanding of these areas as
nutrient rich fish nurseries.

Similar surveys of nearshore habitat conducted in neighboring Alaskan waters further illustrate
the complexity and diversity offish and invertebrate assemblages (Norcross et al. 1995,
Abookire et al. 2000, Abookire and Piatt 2005, Arimitsu and Piatt 2008, Thedinga et al. 2008,
Johnson et al. 2010). Anadromous species, as well as groundfish, forage fish and invertabrate
species are all well represented in many of these nearshore and estuarine areas in a variety of
different habitat and substrate types throughout Alaskan nearshore and estuarine zones.

Offshore Fish Assemblages

NOAA-AFSC has conducted annual surveys of the BBS offshore and outer Bristol Bay waters
since 1982. These surveys provide a representation of the numerous groundfish species that
inhabit the BBS and Bristol Bay deeper than the 15-20m contour (Lauth 2010). Data from these
surveys are used to monitor status of stocks, assist in establishing annual commercial catch
limits, and are used to evaluate trends in ecosystem and trophic level complexity.

Hundreds offish and invertebrate species inhabit Bristol Bay waters and contribute to countless
trophic levels at various life stages. Description of all known species is beyond the scope of this
discussion. However, all species ever identified in these surveys are listed to provide some
context (Table 1). To summarize the more commonly recognized species, represented are cod
and pollock (Gadidae\ fifteen species of flatfish (Pleuronectiformes\ and forage fish species
such as herring, eulachon, capelin, smelts, sand lance and sandfish. Dozens of other species of
skate (Rajidae\ poachers (Psychrolutidae\ greenling (Hexagrammos), rockfish (Scorpaenidae\
sculpin (Cottidae), crab (Cancer), and salmon are also well represented.

The transport and distribution of larval marine fish and invertebrate species from offshore to
nearshore nursery areas is widely recognized (Norcross et al. 1984, Lanksbury et al. 2007). This
relationship between oceanic and estuarine processes and species presence is represented in
Bristol Bay in the life histories of species such as walleye pollock, red king crab (Paralithodes
camtschaticus), and yellow fin and rock sole. Larval forms of each species are advected
(transported) and concentrated in nutrient rich nearshore and estuarine habitat in the inner bay.

Walleye pollock are a semi pelagic species spawning in open marine waters (Bailey et al. 1999).
As Coyle discussed (2002), pollock in their larval and juvenile forms are also known to be
advected into nearshore nursery zones.

"The presence of pollock eggs and larvae along the north shore of the Alaska Peninsula is
apparently fairly common (Bailey et al., 1999). Prevailing currents are northward, along
5
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the eastern shore of Bristol Bay (Napp et al., 2000). The eggs and larvae from the Alaska
Peninsula region are apparently transported northward by the current and by August-
September the zero year class juveniles are observed off Cape Newenham and Nunivak
Island (Bailey et al., 1999; this study)".

The trophic relationship between fish (predator) and invertebrate (prey) species is intuitive. A
recent investigation of trophic interactions using stable isotopes provides further explanation and
a stronger correlation between pollock and euphasiid populations near the convergence zone of
the inner and outer bay complex, within the inner domain (Aydin 2010). Pollock, found in
northern nearshore zones feed on mysiids showing "a higher 515N ratio than pollock in the
southwest along the Alaska Peninsula." Mysiids are more abundant in the diets of pollock in the
northern near shore zones than deepwater forage fish. These findings again substantiate our
understanding of nearshore and estuarine zones as nutrient rich fish nursery areas.

The second-largest population of red king crab is located in Bristol Bay (Dew and
McConnaughey 2005, Chilton et al. 2010). Although red king crab of both genders and several
stages of maturity are identified throughout central Bristol Bay, immature larvae and juveniles
are often concentrated along nearshore areas in the inner bay depending on environmental
influences. A key habitat feature supporting this life history strategy is the "unbroken coastal
shelf and longshore current" which transports larval king crab from the BBS and outer Bristol
Bay to the inner bay complex. As previously discussed, this current is driven by the ANSC and
BCC currents. As a result of nektonic and planktonic drift through the Bristol Bay gyre, larval
red king crab settle in cobble and gravel substrates of Kvichak Bay (Loher et al. 1998), and are
present along nearshore zone in the Togiak district (Olmseth 2009).

The nearshore benthic substrates of inner and outer Bristol Bay are optimal habitat for several
species of flatfish and invertebrates that inhabit the BBS (McConnaughey and Smith 2000).
Flatfish species are well represented in this nearshore coastal domain as well (Lauth 2010 -
Table 1). Life histories of several flatfish species, specifically yellowfin and rock sole, take
advantage of similar current mechanisms that advect larvae into favorable nursery areas (Nichol
1998, Wilderbuer et al. 2002, Norcross and Holladay 2005, Lanksbury et al. 2007, Cooper et al.
2011). Larval and juvenile yellowfin sole are present (Olmseth 2010) and abundant in shallow
nearshore areas along the northern shore and Togiak Bay (Nichol 1998, Wilderbuer et al. 2002).

Bristol Bay Salmon

The ecological role and contribution of Bristol Bay salmon is complex. Salmon facilitate energy
and nutrient exchange across multiple trophic levels from terrestrial headwaters through marine
ecosystems. Each species migrates through these ecotones at slightly different times depending
on life history and watershed of origin. Bristol Bay sockeye salmon, because of their abundance,
6
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distribution, and overall economic importance have been more extensively studied than other
salmonids in the region. Generally, once in marine waters juvenile salmon spend their first
summer in relatively shallow waters on the southeastern Bering Sea shelf, feeding, growing and
eventually moving offshore into the Bering Sea basin and North Pacific Ocean (Meyers et al.
2007, Farley et al. 2011, Farley 2012, pers. comms.).

Range and Distribution

Essential Fish Habitat (EFH) for all juvenile salmon, because of their broad range and
distribution, is generally defined as all marine waters over the continental shelf within the Bering
Sea extending north to the Chukchi Sea, and over the continental shelf throughout the Gulf of
Alaska and within the inside waters of the Alexander Archipelago (Echave et al. 2011). EFH for
immature and mature Pacific salmon includes nearshore and oceanic waters, often extending
well beyond the shelf break, with fewer areas within the Alexander Archipelago (Echave et al.
2011). The Magnuson-Stevens Fisheries Conservation and Management Act (MSFCMA)
defines EFH as waters and substrate necessary to fish for spawning, breeding, feeding, or growth
to maturity. For salmon, EFH are those fresh and marine waters needed to support healthy
stocks in order to provide long-term sustainable salmon fisheries (Eagleton 2012, pers. comms.).

In their emigration phase, anadromous juvenile salmon occupy shallows of estuaries and
nearshore zones though timing, duration, and abundance vary throughout the year depending on
species, stock, and life history stage (Groot and Margolis 1991, Quinn 2005). Nearshore and
estuary habitats act as a physiologic transition zone supporting the smoltification process and
osmoregulatory changes between fresh and saltwater ecotones (Hoar 1976 and 1988, Clarke and
Hirano 1995, Dickhoff et al. 1997). Some sub-yearling salmon (Northwest stocks) have been
shown to repeatedly move through zones of low and high salinity (Healey 1982, Levings 1994,
Levings and Jamieson 2001). These habitats and associated processes are integral to the survival
and growth of salmonid (Simenstad et al. 1982, Simenstad 1983, Thorn 1987).

The EBS shelf is important nursery grounds for juvenile Bristol Bay sockeye salmon (Farley et
al. 2009). Early models of EBS and North Pacific salmon stocks describe migrations and broad
distributions to the south and east in winter and spring, and to the north and west in summer and
fall (French et al. 1975, French et al. 1976, Rogers 1987, Burgner 1991, Shuntov et al. 1993).
These studies were the first to suggest population migrations crossed the Aleutian Island chain
into the North Pacific (Meyers et al. 1996, Myers 2011 pers. comms.). Recent investigations
incorporating genetic (DNA) and scale pattern analysis validate these observations (Bugaev
2005, Farley et al. 2005, Habicht et al. 2005, Habicht et al. 2007, Myers et al. 2007).
Investigations conducted in the autumn 2008 and winter 2009 substantiate the migration of
juvenile Bristol Bay sockeye salmon from the EBS shelf to the North Pacific, south of the
Aleutian Island chain (Habitch et al. 2010, Farley et al. 2011, Seeb et al. 2011).
7
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"In their first oceanic summer and fall, juveniles are distributed on the eastern Bering Sea
shelf, and by the following spring immature salmon are distributed across a broad region
of the central and eastern North Pacific. In their second summer and fall, immature fish
migrate to the west in a band along the south side of the Aleutian chain and northward
through the Aleutian passes into the Bering Sea. In subsequent years, immature fish
migrate between their summer/fall feeding grounds in the Aleutians and Bering Sea and
their winter habitat in the North Pacific. In their last spring, maturing fish migrate across
a broad, east-west front from their winter/spring feeding grounds in the North Pacific,
northward through the Aleutian passes into the Bering Sea, and eastward to Bristol Bay"
(Farley 2011).

More than 55% of ocean age-1 sockeye salmon sampled during those winter surveys in the North
Pacific were from Bristol Bay stocks. These broad seasonal shifts in distribution likely reflect
both genetic adaptations and behavioral responses to environmental cues (e.g., prey availability
and water temperature) that are mediated by bioenergetic constraints (Farley et al. 2011).

Salmon Contribution to Trophic Levels

A recent evaluation was conducted by the NOAA-AFSC Ecosystem Modeling Team to assess
the contribution of Nushagak and Kvichak river sockeye salmon to trophic dynamics to the BBS
shelf and North Pacific ecosystems (Gaichas and Aydin 2010). Using estimates of outbound
salmon smolt survival and adult returns, these two rivers account for nearly 70% (56,000 of
81,100 tons) of adult salmon biomass in the BBS. Depending on environmental influences and
number of out migrating and surviving smolt, juvenile sockeye salmon from these two river
systems may rank among the top ten forage groups. When compared with only single species
stock groups, they rank between fifth and seventh in importance, comparable to Pacific herring
or eulachon. In the open ocean, sockeye salmon represent 47% of total estimated salmon
biomass present in the eastern subarctic gyre (Aydin et al. 2003). Bristol Bay sockeye salmon
from the Nushagak and Kvichak river systems comprise 26% of total sockeye salmon biomass,
and 12% of total salmonid biomass in the entire eastern subarctic gyre. The Nushagak and
Kvichak river systems produce a significant portion of all salmon in offshore marine ecosystems,
the majority of salmon on the BBS shelf and represent the majority of juvenile and returning
adult salmon biomass (Gaichas and Aydin 2010). This evaluation provides additional insight
into the role and contribution of outbound salmon smolt to Bristol Bay and BBS trophic
interactions. Results from an unrelated study indicate outbound salmon smolt may export more
nitrogen and phosphorus than adult salmon transported into watersheds from the ocean (Moore
and Schindler 2004).
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It is well documented that returning adult salmon subsidize watersheds in the form of salmon
derived or Marine Derived Nutrients (MDN) (Gende et al. 2002, Schindler et al. 2003, Wilson et
al. 2004). The contribution of out-welling MDN, mass transport of nutrient back to estuarine
processes, further expands upon this concept. Nutrient transport is facilitated in the form of
partial and whole salmon carcasses, or particulates and dissolved nutrients (carbon, nitrogen and
phosphorous) moving from watersheds back to estuaries. Early studies identified the flow of
salmon carcasses out of the coastal watersheds into marine estuaries as a result of high
precipitation events (Brickell and Goering 1970, Richey et al. 1975). Salmon-derived nutrients
stimulate primary production in estuaries where nitrogen and phosphorus are often limiting
nutrients (Rice and Ferguson 1975). Estuarine algae use dissolved MDN, in turn feeding
copepods which feed juvenile salmon (Fujiwara and Highsmith 1997). One investigation
identified several species of marine invertebrates feeding on salmon carcasses (Reimchen 1994).
Stationary whole salmon carcasses were completely consumed in a week. Gende (2004)
estimated that 43% of the tagged salmon carcasses washed into the study estuary within days.
More recent investigations conducted in Alaskan waters estimate that the contribution of MDN
to marine estuarine processes may be as high as 60%, or two thirds of potential nutrient
transported back to the estuary (Johnston et al. 2004, Mitchell and Lamberti 2005).

In the Nushagak and Kvichak Bays, MDNs liberated from tens of millions of decomposing adult
salmon likely have a significant influence on trophic interactions and biodiversity. Estuarine
processes such as primary and secondary production and countless marine fish and invertebrate
species benefit from this mass transport. These and a multitude of similar studies indicate
marine and estuarine vegetation, and larval and juvenile invertebrate and fish populations benefit
from outwelling MDN washed back into estuaries.

Bristol Bay - Marine Mammals

The EBS supports numerous species of marine mammals including whales (Cetacea) of the
suborders Odontoceti (toothed whales and porpoise) and Mysticeti (baleen whales). Several
species of seals (pinnipeds) are also represented (Otariidae, Phocidae, and Odobenidae) in these
waters (Allen and Angliss 2010). Of marine mammals present in the EBS, twenty species occur
in Bristol Bay waters in significant numbers and regularity to be distinguished in this discussion
(Table 2). Three species of baleen whale (fin, right and humpback whales) and one pinniped
species (Western DPS Steller sea lion) found in Bristol Bay are recognized by federal or state
agencies as threatened, endangered, or listed as species of concern.

Within Bristol Bay, the presence of marine mammal and prey species is highly variable
depending on seasonality or waters of residency. For example, variability in seasonal range of
sea lions or fur seals, rookery vs oceanic phase or migratory patterns of prey species, introduces
ambiguity in accurately identifying annual presence and feeding habitats. Less is known about
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pinniped prey selection in the open ocean phase because scat and stomach content studies are
only conducted while specimens are on the rookery. Thus, the only prey species represented in
dietary analysis are prey species available in proximity to the rookeries.

Some marine mammal diet data show seasonal dependence on salmon. Several studies
demonstrate that salmon are well represented as a nutritional source in several marine mammal
species (Pauly et al. 1998a). Many marine mammals, especially pinniped and ondontocete
species, prey on adult and juvenile salmon in nearshore zones.

Pinnipeds

Sea lion predation on salmon has been confirmed by data from scat and stomach content studies
from which researchers have estimated the level of consumption and frequency of occurrence
(NMFS 1992, Merrick 1995, Merrick et al. 1997, Sinclair and Zeppelin 2002, Trites and
Donnelly 2003, Jemison 2011, pers. comms.). Depending on seasonal range and migratory
patterns, salmon ranked high as a selected prey species in Steller sea lion diets (Sinclair and
Zeppelin 2002). The endangered western stock of Steller sea lions relies on salmon during
summer; salmon rank second in frequency of occurrence in summer diets in all regions between
1990 and 1998 (Sinclair and Zeppelin 2002). These regions include the Bering Sea shelf and
waters surrounding the Aleutian Islands, where salmon were noted to increase in diets during
winter due to out-migrating juvenile Bristol Bay salmon (Sinclair and Zeppelin 2002).

An investigation was conducted to determine prey species of northern fur seals in the Pribilof
Islands (Sinclair et al. 2008). Salmon composed part of the diet of fur seals on St. George and
St. Paul Islands. Pacific salmon (Oncorhynchus spp.) had a mean annual frequency of
occurrence of 14.4%, and 10% in any 1 year on St. George and St. Paul Islands respectively. In
similar nutrition studies of BBS northern fur seals, salmon rank second among fish in frequency
of occurrence for animals on both Pribilof Islands from late July though September, 1990-2000
(Gudmundson et al. 2006). Another study indicates salmon comprise a portion of fur seal diets
throughout the Pacific, from California to their western Alaskan range (Perez and Bigg 1986).

Harbor seal are found throughout Bristol Bay and the BBS and also prey upon species of Pacific
salmon (Jemison et al. 2000, Small et al. 2003, Hauser et al. 2008, Allen and Angliss 2010,
Jemison 2011, pers. comms.). Lake Illiamna supports one of two recognized fresh water
populations of harbor seals (Smith et al. 1996). This population is defined as relatively small
with maximum aerial counts of hauled-out harbor seals ranging from 137 to 321. These counts
do not reflect absolute abundance (Mathisen and Cline 1992, Small 2001). Though this
population has colonized Lake Iliamna from Bristol Bay via the Kvichak River, there is no
evidence that populations move to and from the salt water estuary to the fresh water lake
(Mathisen and Kline 1992, Hauser et al. 2008). Current information indicates the Lake Illiamna
10
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population is resident. Harbor seals have also been identified in the Nushagak and Wood river
systems. In the Wood river system, Harbor seals are observed in Lake Aleknagik (B. Andrew
2011, pers. comms., Chythlook 2011, pers. comms., Tinker 2011, pers. comms.). Spotted seals
tagged in both Alaskan and Russian sectors of the Bering Sea showed clear seasonal preference
for nearshore habitat and associated fisheries. These populations fed mostly on fishes, such as
salmon (Onchorhynchus spp.), saffron cod (Eleginus gracilus), and herring (Burkanov 1989,
Lowery et al. 2000).

Whales: Toothed Whales - Ondontocetes

Beluga whales are abundant in Bristol Bay waters primarily from spring through fall, near the
mouths of the Kvichak, Nushagak, Wood and Igushik rivers. Earlier studies document the
importance and contribution of sockeye salmon in beluga nutrition (Brooks 1955). Lensink
(1961) noted that belugas fare poorly in Bristol Bay when migratory (anadromous) fish are not
available. In addition to following the general movements of its prey, belugas appear to feed
specifically where its prey species are most concentrated. The frequency of occurrence of
salmon species in beluga stomachs is correlated with the abundance of each species during their
respective migrations (Brooks 1955). Studies conducted by Brooks in the 1950s further indicate
that belugas feed on both juvenile and adult salmon, as well as on several other forage fish and
invertebrate species (Klinkhart 1966).

From 1993 to 2005, the beluga population increased in abundance by 4.8% per year, and while
thresholds of prey abundance needed for belugas to thrive are not fully understood, the larger
size of red salmon runs before and during the period covered by aerial surveys may partially
explain the increased beluga numbers (Lowry et al. 2008). Belugas are well known to travel up
these rivers in pursuit of salmon. They have been seen feeding on salmon in the Kvichak river
past Levelock to the Igiugig Flats (Cythlook and Coiley 1994, G. Andrew 2011, pers. comms.).
In summer, belugas are routinely observed in the Nushagak river (P. Andrew 2011, pers.
comms.). In the Wood river system, belugas have been observed in Lake Aleknagik (Fried et al.
1979, B. Andrew, 2011, pers. comms., Tinker 2011, pers. comms.).

Killer whales also inhabit Bristol Bay waters. They have been seen in nearshore waters and
frequent the lower river reaches chasing and preying upon salmon and beluga whales (Frost and
Lowry 1981, Frost et al. 1992, Allen and Angliss 2010, Quakenbush 2011, pers. comms.). In a
recent observation (July 17, 2002), killer whales displayed cooperative feeding behaviors near
the Nushagak spit. A pod formed a circle with their tails facing toward the center, fluke slapping
on the surface of the water. A male killer whale emerged through the center of the circle with a
mouth full of salmon (Tinker 2011, pers. comms.). In the Nushagak river, killer whales have
been observed chasing both belugas and coho salmon (Cythlook 2011, pers. comms.). In late

11
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fall, in the absence of beluga whales, killer whales pursue late run and fall coho up the Nushagak
river (P. Andrew 2011, pers. comms.).

Though opportunistic feeders, fish eating killer whales show an affinity to salmon. In Prince
William Sound, the results of a 14 year study of the diet and feeding habits of killer whales
identify two non-associating groups of killer whale, termed resident and transient (Bigg et al.
1987). The resident group (fish eaters) appear to prey principally on salmon, preferring coho (O.
kisutch) over other more abundant salmon species (Saulitis et al. 2000). Another distinct
population of Alaskan fish eating killer whales off the coast of British Columbia move
seasonally to target salmon populations (Nichol and Shackleton 1996). Field observations of
predation and stomach content analysis of stranded killer whales collected over a 20 year period
document 22 species offish and 1 species of squid dominated the diet offish eating resident-
type killer whales (Ford et al. 1998). Despite the diversity offish species taken in these studies,
fish eating resident killer whales showed a clear preference for salmon: 96% offish taken were
salmonids. Of the six salmonid species identified, by far the most common was chinook,
representing 65% of the total sample. The second most common was pink at 17%, followed by
chum (6%), coho (6%), sockeye (4%), and steelhead (2%) (Ford et al. 1998). Though likely a
separate population, Bristol Bay killer whales likely exhibit similar feeding behaviors.

Sperm whales, another species of toothed whales not identified in Bristol Bay waters as defined
in this discussion, have been known to prey upon salmon in the BBS. Though feeding primarily
on mesopelagic squid in the North Pacific, the species has also been documented as consuming
salmon as well as several other species offish (Tomilin 1967, Kawakami 1980).

Whales: Baleen Whales - Baleenotropha

Investigations of baleen whale food habits in the North Pacific and Bering Sea have documented
species such as humpbacks targeting small schooling fish populations. Salmon were among
numerous species offish identified (Nemoto 1959, Tomilin 1967, Kawamura, 1980). More
recently, humpback whales have been observed off Cape Constantine in the spring of year,
presumably feeding on schooling herring and possibly outmigrating salmon smolts (Cythlook
2011, pers. comms.). In southeast Alaska humpback whales have been observed preying upon
both wild and hatchery out bound salmon smolts as well as adult pink salmon (Straley et al.
2010, Straley 2011, pers. comms.). Humpback whales have been shown to exhibit site fidelity to
feeding areas, and return year after year to the same feeding locations (Baker et al. 1987,
Clapham et al. 1997). There is very little interchange between feeding areas (Baker et al. 1986,
Calambokidis et al. 2001, Waite et al. 1999, Urban et al. 2000).
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Bibliography: By Section

Bristol Bay Marine and Estuarine Processes

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26
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27
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S. Baker. 2000. Migratory destinations of humpback whales wintering in the Mexican
Pacific. Journal of Cetacean Research and Management 2:101-110.
28
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Tables
Table 1: Fish and Invertebrate Species - Species listed have been identified in the NOAA-
AFSC Bering Sea Trawl Surveys between 1982-2010 (Lauth 2010). Caveats: All species found,
1) east of the 162 line, 2) deeper than 15-20m, 3) seasonality of surveys and species presence do
not represent complete species diversity, 4) standardized trawl gear mesh is size selective,
juvenile and larval specimens of a species may not be well represented, 5) salmon species at any
life stage may not be well represented due to seasonality of surveys and migration.
FISH SPECIES
Common Name
Scientific Name
Chinook salmon
Chum salmon
Steelhead
Salmonidae
Oncorhynchus tshcnvytscha
Oncorhynchus keta
Oncorhynchus mykiss
Pacific cod
Walleye pollock
Arctic cod
Saffron cod
Gadidae
Gadus macrocephalus
Theragra chalcogramma
Boreogadus saida
Eleginus gracilis
Sablefish
Anoplopomatidae
Anoplopoma fimbria
Eulachon
Capelin
Rainbow smelt
Smelt unident
Osmeridae
Thaleichthys pacificus
Mallotus villosus
Osmerus mordax
Osmeridae
Pacific herring
Clupeidae
Clupea pallasi
Pacific sand lance
Ammodytidae
Ammodytes hexapterus
Pacific sandfish
Trich odontidae
Trichodon trichodon
29
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Pacific halibut
Yellowfin sole
Northern rock sole
Rock sole unident.
Flathead sole
Dover sole
Rex sole
Butter sole
Sand sole
Starry flounder
Alaska plaice
Arrowtooth flounder
Kamchatka flounder
Longhead dab
Sanddab unident.
Pleuronectidae
Hippoglossus stenolepis
Limanda aspera
Lepidopsetta polyxystra
Lepidopsetta sp.
Hippoglossoides elassodon
Microstomus pacificus
Glyptocephalus zachirus
Isopsetta isolepis
Psettichthys melanostictus
Platichthys stellatus
Pleuronectes quadrituberculatus
Atheresthes stomias
Atheresthes evermanni
Limanda proboscidea
Citharichthys sp.
Northern rockfish
Scorpaenidae
Sebastes polyspinis
Big skate
Bering skate
Starry skate
Alaska skate
Aleutian skate
Rajidae
Raja binoculata
Bathyraja intermpta
Raja stellulata
Bathyraja parmifera
Bathyraja aleutica
Whitespotted greenling
Rock greenling
Kelp greenling
Smooth lumpsucker
Greenling unident.
Hexagrammos
Hexagrammos stelleri
Hexagrammos lagocephalus
Hexagrammos decagrammus
Aptocyclus ventricosus
Hexagrammidae
Sawback poacher
Gray starsnout
Sturgeon poacher
Aleutian alligatorfish
Arctic alligatorfish
Psychrolutidae
Leptagonus frenatus
Bathyagonus alascanus
Podothecus accipenserinus
Aspidophoroides bartoni
Ulcina olrikii
30
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Warty poacher
Bering poacher
Chesnonia verrucosa
Occella dodecaedron
Wolf-eel
Bering wolffish
Anarhichadidae
Anarrhichthys ocellatus
Anarhichas orientalis
Threaded sculpin
Arctic staghorn sculpin
Armorhead sculpin
Northern sculpin
Sculpin unident.
Gymnocanthus sp.
Gymnocanthus pistilliger
Gymnocanthus tricuspis
Gymnocanthus galeatus
Icelinus borealis
Cottidae
Hookhorn sculpin
Irish lord
Red Irish lord
Yellow Irish lord
Artediellus sp.
Artediellus pacificus
Hemilepidotus sp.
Hemilepidotus hemilepidotus
Hemilepidotus jordani
Ribbed sculpin
Brightbelly sculpin
Warty sculpin
Great sculpin
Plain sculpin
Triglops sp.
Triglops pingeli
Microcottus sellaris
Myoxocephalus verrucosus
Myoxocephalus polyacanthocephalus
Myoxocephalus jaok
Pacific staghorn sculpin
Antlered sculpin
Spiny head sculpin
Crested sculpin
Eyeshade sculpin
Sailfin sculpin
Bigmouth sculpin
Thorny sculpin
Spatulate sculpin
Myoxocephalus sp.
Leptocottus armatus
Enophrys diceraus
Dasycottus setiger
Blepsias bilobus
Nautichthys pribilovius
Nautichthys oculofasciatus
Hemitripterus bolini
Icelus spiniger
Icelus spatula
Variegated snailfish
Liparis sp.
Liparis gibbus
31
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Snailfish unident.
Liparidinae
Daubed shanny
Snake prickleback
Decorated warbonnet
Bearded warbonnet
Polar eelpout
Stichaeidae
Lumpenus maculatus
Lumpenus sagitta
Chirolophis decoratus
Chirolophis snyderi
Lycodes turneri
Giant wrymouth
Cryptacanth odidae
Cryptacanthodes giganteus
INVERTEBRATE SPECIES
Common Name
Scientific Name
Octopus

Common Octopus
Eastern Pacific bobtail
Octopodidae sp.
Octopoda
Rossia pacifica
Crab

Oregon rock crab
Graceful decorator crab
Tanner crab
Circumboreal toad crab
Pacific lyre crab
Snow crab
Hybrid tanner crab
Helmet crab
Hermit crab unident.

Sponge hermit
Aleutian hermit
Splendid hermit
Knobbyhand hermit
Fuzzy hermit crab
Bering hermit
Alaskan hermit
Longfinger hermit
Cancer sp.
Cancer oregonensis
Oregonia gracilis
Chionoecetes bairdi
Hyas coarctatus
Hyas lyratus
Chionoecetes opilio
Chionoecetes hybrid
Telmessus cheiragonus
Paguridae
Pagurus sp.
Pagurus brandti
Pagurus aleuticus
Labidochirus splendescens
Pagurus confragosus
Pagurus trigonocheirus
Pagurus beringanus
Pagurus ochotensis
Pagurus rathbuni
32
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Wideband hermit crab
Hairy hermit crab
Purple hermit
Wrinkled crab

Fuzzy crab
Red king crab
Horsehair crab
Elassochims tenuimanus
Pagurus capillatus
Elassochims cavimanus
Dermaturus mandtii
Hapalogaster sp.
Hapalogaster grebnitzkii
Paralithodes camtschaticus
Erimacrus isenbeckii
Shrimp

Ocean shrimp
Alaskan pink shrimp
Humpy shrimp
Shrimp unident.

Spiny lebbeid

Abyssal crangon
Twospine crangon
Ridged crangon
Sevenspine bay shrimp
Crangonid shrimp unident.

Arctic argid

Sculptured shrimp
Kuro argid
Pandalus sp.
Pandalus jordani
Pandalus eous
Pandalus goniurus
Hippolytidae
Lebbeus sp.
Lebbeus groenlandicus
Crangon sp.
Crangon abyssorum
Crangon communis
Crangon dalli
Crangon septemspinosa
Crangonidae
Argis sp.
Argis dentata
Sclerocrangon sp.
Sclerocrangon boreas
Argis lar
Clams, Mussels, Scallop, Cockles

Northern horse mussel

Blue mussel
Weathervane scallop
Arctic hiatella
Arctic roughmya

Crisscrossed yoldia
Northern yoldia
Mytilidae sp.
Modiolus modiolus
Mytilus sp.
Mytilus edulis
Patinopecten caurinus
Hiatella arctica
Panomya norvegica
Yoldia sp.
Yoldia seminuda
Yoldia hyperborea
33
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Discordant mussel
Boreal astarte
Many-rib cyclocardia

Arctic surfclam

Alaska great-tellin

Bent-nose macoma

Pacific razor
Alaska razor

Softshell clam
Alaska falsej ingle (soft oyster)
Soft shell unident.

Hairy cockle
California cockle

Greenland cockle
Broad cockle
Coral, Soft coral

Sea raspberry

Sea pen (sea whip)

Snail, snails, welk

Aleutian moonsnail
Rusty moonsnail
Pale moonsnail
Great slippersnail
Moonsnail eggs unident

Warped whelk
Musculus discors
Astarte borealis
Cyclocardia crebricostata
Mactromeris sp.
Mactromeris polynyma
Tellina sp.
Tellina lutea
Macoma sp.
Macoma nasuta
Siliqua sp.
Siliqua patula
Siliqua alta
My asp.
Mya arenaria
Pododesmus macrochisma
Anomiidae
Ciliatum sp.
Clinocardium ciliatum
Clinocardium californiense
Serripes sp.
Serripes groenlandicus
Serripes laperousii
Cyclocardia sp.
Clinocardium sp.
Gersemia sp.
Gersemia rubiformis
Gorgonacea sp.
Pennatulacea
Natica clausa sp.
Cryptonatica aleutica
Cryptonatica russa
Euspira pallida
Crepidula grandis
Naticidae eggs
Volutopsius sp.
Pyrulofusus deformis
34
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Pribilof whelk

Lyre whelk
Fat whelk

Helmet whelk

Oregon triton

Rosy tritonia

Angular whelk
Sinuous whelk
Ladder whelk
Polar whelk
Smooth lamellaria

Snail eggs
Snail eggs unident.
Beringius sp.
Beringius kennicottii
Beringius beringii
Neptunea sp.
Neptunea pribiloffensis
Neptunea borealis
Neptunea lyrata
Neptunea ventricosa
Neptunea heros
Clinopegma magnum
Plicifusus kroyeri
Neptunea sp.
Fusitriton oregonensis
Tritonia sp.
Tritonia diomedea
Buccinum sp.
Buccinum angulosum
Buccinum plectrum
Buccinum scalariforme
Buccinum polare
Velutina velutina
Hyas sp.
Gastropod eggs
Neptunea sp. eggs
Barnacles

Giant barnacle
Beaked barnacle
Barnacle unident.
Balanus sp.
Balanus evermanni
Balanus rostratus
Thoracica
Anemone

Sea anemone unident.

Clonal plumose anemone
Gigantic anemone
Halipteris sp.
Actiniaria
Metridium sp.
Metridium senile
Metridium farcimen (=Metridium
giganteum)
Stomphia sp.
Urticina sp.
35
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Mottled anemone
Chevron-tentacled anemone
Tentacle-shedding anemone
Stony coral unident.
Urticina crassicornis
Cribrinopsis fernaldi
Liponema brevicornis
Scleractinia
Star fish, sea star

Mottled sea star
Giant sea star

Blackspined sea star

Blood sea star
Tumid sea star
Grooved sea star
Rose sea star

Purple-orange sea star
Brittlestarfish unident.
Basketstar
Notched brittlestar
Evasterias sp.
Evasterias troschelii
Evasterias echinosoma
Leptasterias groenlandica
Lethasterias nanimensis
Henricia sp.
Henricia leviuscula
Henricia tumida
Leptasterias polaris
Leptasterias katharinae
Leptasterias arctica
Leptasterias sp.
Crossaster sp.
Crossaster borealis
Crossaster papposus
Asterias sp.
Asterias amurensis
Ophiuroidea
Gorgonocephalus eucnemis
Ophiura sarsi
Sea urchin
Green sea urchin
Sand dollar
Echinacea sp.
Strongylocentrotus droebachiensis
Strongylocentrotus sp.
Strongylocentrotus poly acanthus
Echinarachnius parma
Sponges

Stone sponge
Clay pipe sponge
Barrel sponge
Stelletta sp.
Suberites ficus
Aphrocallistes vastus
Halichondria panicea
36
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Sponge

Jelly fish

Jelly Fish
Lion's mane
Chrysaora jellyfish
Jellyfish unident.
Comb jelly unident.
Suberites sp.
Porifera
Amphilaphis sp.
Chrysaora melanaster
Cyanea capillata
Chrysaora sp.
Scyphozoa
Ctenophora
Miscellaneous Invertabrate Species
Worm

Giant scale worm
Depressed scale worm
Striped sea leech
Echiuroid worm unident.
Cat worm unident.
Scale worm unident.
Peanut worm unident.
Tube worm unident.
Polychaeta
Eunoe nodosa
Eunoe depressa
Notostomobdella cyclostoma
Echiura
Nephtyidae
Polynoidae
Sipuncula
Hydroids

Bryozoans
Feathery bryozoan
Leafy bryozoan

Ribbed bryozoan
Bryozoan unident.

Sea Cucumbers

Sea football
Sea cucumber

Foraminiferan unident.
Abietinaria sp.

Eucratea loricata
Flustra sermlata
Alcyonidium pedunculatum
Rhamphostomella costata
Bryozoa
Cucumaria sp.
Cucumaria fallax
Holothuroidea
Cucumaria frondosa
Psolus sp.
Foraminifera
37
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Ascidians
Orange sea glob Aplidium sp.
Sea pork Aplidium californicum
Molgula sp.
Sea grape Molgula grifithsii
Sea clod Molgula retortiformis
38
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Table 2: Marine Mammals Species List - Marine mammal species listed have been identified
from several sources (Allen 2010, ADFG 2010, BBESI2001, BB-CRSA 2009).
MARINE MAMMALS
Common Name Scientific Name
Toothed Whales
Beluga whale
Killer whale
Pacific white-sided dolphin
Harbor porpoise
Ball's porpoise
Baird's beaked whale
Cetaceans - Ondontocetes
Delphinaptems leucas
Orcinus orca
Lagenorhynchus obliquidens
Phocoena phocoena
Phocoenoides dalli
Berardius bairdii
Baleen Whales
Cetaceans - Balenotropha
Gray whale
Humpback whale
Fin whale
Minke whale
Bowhead whale
Eschrichtius robustus
Megaptera novaeangliae
Balaenoptera physalus
Balaenoptera acutorostrata
Balaena mysticetus
Sealion
Pinnipeds - Otariidae
Steller sea lion (Eastern)
Northern fur seal (Eastern)
Eumetopiasjubatus
Callorhinus ursinus
Seals
Pinnipeds - Phocidae
Harbor seal
Spotted seal
Bearded seal
Ringed seal
Ribbon seal
Phoca vitulina
Phoca largha
Erignathus barbatus
Pusa hispida
Histriophoca fasciata
Walrus
Pinnipeds - Odobenidae
Odobenus rosmarus
Mustelidae - Lutrinae
Northern Sea Otter
Enhydra lutris kenyoni
39
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Appendix G

Foreseeable Environmental Impact of
Potential Road and Pipeline Development on
Water Quality and Freshwater Fishery Resources
of Bristol Bay, Alaska
G-l
-------
Foreseeable Environmental Impact of
Potential Road and Pipeline Development on
Water Quality and Freshwater Fishery Resources
of Bristol Bay, Alaska
By
Christopher A. Frissell, Ph.D.
Pacific Rivers Council
PMB 219, 48901 Highway 93, Suite A
Poison, MT 59860
chris@pacificrivers.org
phone 406-471-3167

Maps and Spatial Analysis contributed by
Rebecca Shaftel
Alaska Natural Heritage Program
University of Alaska Anchorage
Beatrice McDonald Hall, Suite 106
rsshaftel@uaa.alaska.edu
Report prepared for
University of Alaska Anchorage
Environment and Natural Resources Institute
And Alaska Natural Heritage Program
Daniel Rinella, Project Leader
rinella@uaa.alaska.edu
FINAL 31 January 2011
-------
ABSTRACT
While Pacific salmon fishery resources have diminished around the Pacific Rim for more
than a century, the Bristol Bay region of Alaska supports a globally unique, robust,
productive, and sustainable salmon fishery associated with extremely high quality waters
and high integrity freshwater ecosystems. The Bristol Bay watershed has seen a bare
minimum of road development to date. However, State of Alaska long range plans
envision a future of extensive inter-community transportation routes, including both
highways and pipelines. Other developments being considered for the area would also
require an infrastructure of roads and pipelines that would traverse previously roadless
areas of the Kvichak and Nushagak river drainages. As a plausible example of such
potential infrastructure, this report uses the 138-km-long access road and four pipelines
likely to be part of Northern Dynasty Minerals' Pebble Mine, should the company elect
to pursue development of that prospect. It reviews the known physical and biological
effects of road and pipeline development on streams, rivers, lakes, and wetlands. The
report identifies two key conditions in the Bristol Bay ecosystem that particularly
contribute to its water quality and biological productivity and resilience: 1) a geologic
and geomorphic template that provides abundant shallow groundwater resources and
strong vertical linkage between surface waters and groundwater, across all stream sizes
and wetland types; and 2) the lack of past industrial disturbance, including road
development across most of the Bristol Bay watershed. The example Pebble Mine
transportation corridor would bisect this landscape with the potential to shape the
hydrology, water quality and fish habitat integrity of many of the Kvichak and Nushagak
river drainages. Drawing from the literature that conceptualizes how to spatially project
risk-impact footprints from road designs and landscape and stream network data, the
report maps the spatial extent of potential harm from construction, operation, accidents
and accidents response on the Pebble transportation corridor. At least twelve percent and
possibly upwards of twenty percent of the road corridor would intersect or closely
approach known wetlands. More than 30 large streams and rivers known to support
spawning salmon would intersect with the proposed transportation corridor, potentially
affecting between twenty and thirty percent of known spawning populations of sockeye
salmon in the Hiamna Lake system. The eastern half of Iliamna Lake supports the highest
concentrations of rearing sockeye salmon and would also be very close to the road and
pipeline corridor. The corridor would also bisect or closely approach more then 70
streams known to support resident fishes such as dolly varden, arctic graying, and others.
The report also assesses potential mitigation measures and identifies practices that could
potentially reduce the risk of impact to water quality, freshwater ecosystem function, and
Bristol Bay fishery resources should the corridor be developed.
-------
I. INTRODUCTION AND SCOPE OF THIS REPORT

While Pacific salmon fishery resources have diminished around the Pacific Rim to the
point that many populations are managed as endangered or threatened species, the Bristol
Bay region of Alaska supports a globally unique, robust and productive salmon fishery
(Burgner 1991, Schindler et al. 2010). Commercial fishers harvest five Pacific salmon
species in Bristol Bay, including a sockeye salmon landing of over 29 million fish in
2010 (ADFG 2010). Bristol Bay's wild rivers support sport fisheries likely exceeding
90,000 angler days and millions of dollars in related expenditures (Duffield et al. 2007,
Duffield 2011, personal communication).

Hilborn et al. (2003) identified key factors sustaining the productivity and resilience of
Bristol Bay, specifically, 1) a highly accountable system of fishery regulation, 2)
favorable ocean conditions in recent years, and 3) a stock complex sustained by variable
production from an abundance and high diversity of freshwater and estuarine habitats.,
Salmon production in different Bristol Bay rivers and lakes, in their current, largely
natural and undeveloped condition, varies independently over time spans of decades.
Despite the local variability, the system sustains a high overall fishery production
because at any given time, a collection of extremely high-quality habitats contributes
extraordinarily high abundance and production of fishes. These same factors (i.e.,
diversity and high quality of interconnected habitats) likely confer to Bristol Bay a degree
of resilience in the face of future climate and environmental change (Hilborn et al. 2003,
Woody and O'Neal 2010, Schindler et al. 2010).

Although some planners have projected extensive highways and industrial development
in the Bristol Bay region (BBAP 2005), the Pebble Mine is the most likely large-scale
development to be proposed in the near future. Development of the Pebble project would
include a major 138-km-long access road, pipeline, and electric utility corridor between
the mine site, north of Lake Diamna, and a deepwater port on Cook Inlet, to the east
(Ghaffari et al. 2011) (Figure 1). This corridor would cross many tributaries of the of the
Kvichak and Nushagak Rivers, including tributaries of Diamna lake, as well as bisecting
numerous wetlands and groundwater-rich areas that connect to and sustain the water
quantity and quality in those fish habitats.
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- AD OT majo r ro ad s

- ADNR secondary roads

Proposed infrastructure corridor

;] Pebble deposit

I Bristol Baywater shed boundary
25 60
100 Kilometers
Figure 1. Existing roads in the Bristol Bay region, and the proposed routed of the Pebble
Mine transportation corridor. Mapped by Rebecca Shaftel (Alaska Natural Heritage
Program, Anchorage) based on dat from Alaska Department of Transporation and Alaska
Department of Natural Resources (Anchorage).
Through its contractor for this report, NatureServe, U.S. Environmental Protection
Agency charged the author with providing a review of: 1) relevant literature and expert
input on the risks, threats, and stressors to Bristol Bay area water quality and salmon
resources associated with the construction, operation, and maintenance of reasonably
foreseeable roads in the region; and 2) mitigation practices used to abate such impacts,
including both commonly used and available, but uncommonly used practices.

Accordingly, after a brief review of known consequences of road and pipeline
development on streams, rivers, and lakes, this report will assess the scope of likely and
possible environmental impacts on the water quality and fishery resources of the Bristol
Bay region from development of the potential Pebble Mine Transportation Corridor
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II. THE BRISTOL BAY ECOSYSTEM

Bristol Bay is one of the worlds few remaining, large virtually roadless near-costal
regions. There are but a few short segments of state highway and road, and no railroads,
pipelines, or other major industrial transportation infrastructure. Roadways presently link
Iliamna Lake to Cook Inlet and the Iliamna area north to the village of Nondalton, at the
south end of the Lake Clark system, and other short road segments connect Dillingham
to Aleknagik and Naknek to King (Figure 1).

Glacial landforms dominate much of Bristol Bay's surface geology and geormorphology
and include extensive glacial outwash glacial till mantles on hillslopes, expansive,
interbedded glacial lake deposits, and glacial and periglacial stream deposits (Hamilton
2007). These landforms, and more specifically, the extensive, interconnected surface and
near-surface groundwater systems resulting from them, are one of the two factors that
principally account for Bristol Bay's high productivity for salmon. (The other key factor
is the dearth of industrial and commercial development in the basin.)

Most available information on fish distribution and abundance in the Bristol Bay region
focuses on large rivers (in part because they can be surveyed from the air, at least for
sockeye salmon). However, a myriad of smaller streams and wetlands also provide high-
quality habitat for coho salmon, dolly varden, rainbow trout, and arctic grayling, as well
as other species including round whitefish, pond smelt, lamprey, slimy sculpin, northern
pike, sticklebacks and burbot (Rinella and Shaftel 2011, personal communcation). In the
most comprehensive published field inventory, Woody and O'Neal (2010) reported
detection of one or more of these species from 96 percent of the 108 small waters they
sampled in the vicinity of the projected site of Pebble prospect in the Nushagak and
Kvichak River drainages. They summarize:

Small headwater streams are often assumed not to be important
salmon producing habitats in Alaska, although collectively they
produce millions of salmon and determine water flow and
chemistry of larger rivers. As illustrated by this and numerous
other studies, headwaters comprise a significant proportion of
essential spawning and rearing habitat for salmon and non-salmon
species all of which are important to subsistence users in the
region.
III. ROADS AND PIPELINES PROPOSED OR FORESEEABLE IN BRISTOL BAY

In evaluating the environmental impact of any road, it is important to recognize that the
development of a new road is often only the first step toward industrial or commercial
development of the landscape in general, including the proliferation of additional roads
(Trombulak and Frissell 2000, Angermeier et al. 2004). Additional large-scale landscape
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development, facilitated by the initial road, is a reasonably foreseeable impact of road
construction in a roadless area. Essentially, finance and construction of the initial road
subsidizes future developments that rely on that road to route traffic, particularly when
that initial road connects to a possible trade hub, such as a deepwater port. The
environmental impact of the ensuing development can dwarf by orders of magnitude the
direct, local effects of constructing the initial road segment (Angermeier at al. 2004).

That there is some interest in industrialization of Bristol Bay beyond the Pebble Mine is
evident in various State of Alaska sources. The ADNR's Bristol Bay Area Plan from the
(BBAP 2005, citing the ADOT's Southwest Alaska Transportation Plan, November
2002), lays out an ambitious long-range vision for future development of a network of
roads and highways in the Bristol Bay region (Figure 2). The roads, highways, and
related infrastructure envisioned by the BBAP include "regional transportation corridors"
that would connect Cook Inlet to the area of the Pebble prospect, as well as Aleknagik
(already connected by road to Dillingham), King Salmon, Naknek, Egegik, and Port
Heiden, and finally, to Chignik and Perryville, on the southern Alaska Peninsula. The
State also foresees other "community transportation projects" that involve extensions,
improvements, or new roads within or adjacent to Bristol Bay watershed (Chigniks Road
Intertie, King Cove-Cold Bay Connection, Newhalen River Bridge, Iliamna-Nondalton
Road Intertie, and Naknek-South Naknek Bridge and Intertie). The plans also identify
three potential "Trans-Peninsula transportation corridors" (Wide Bay/Ugashik Bay,
Kuiulik Bay/Port Heiden, and Balboa Bay/Herendeen Bay,) routes that could serve for
roads, oil and gas pipelines or other utilities as needed (BBAP 2005, Figure 2.5).
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;
Legend
BristoJ Bay Area Plan boundary
BBM> Regions
DOT Transportation Comdofs
Trans-Peninsula Transportation CorrdKxs

Figure 2. Roads and transportation corridors envisioned in the Bristol Bay Area Plan
(BBAP 2005, Figure 2.5).

Several other large ore bodies and at least seven different complexes of mineral claims lie
within a roughly concentric 24-km radius around the existing Pebble Prospect,
encompassing a vast swath of the Bristol Bay watershed north of Iliamna Lake (Ghaffari
et al. 2011, The Nature Conservancy 2010). The area spans the headwaters of the
Koktuli, Stuyahok, and Newhalen Rivers, as well as Kaskanak, and both Lower and
Upper Tularik Creeks. There are other large mineral leases farther afield within Bristol
Bay, including tracts north and west of the Nushagak and Mulchatna Rivers. Although
they are at various stages of exploration, these prospects could yield future mine
proposals, particularly if road and other transportation improvements completed for
Pebble Mine provided a transportation stepping stone to them.
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IV. EFFECTS OF ROADS AND PIPELINES ON WATER AND FISH HABITAT

Roads have persistent multifaceted impacts on ecosystems and can strongly affect water
quality and fish habitat. Several authors have reviewed the suite and scope of
environmental impacts from roads (e.g., Forman and Alexander 1998, Trombulak and
Frissell 2000, Gucinski et al. 2001) with particular focus on water quality and fish habitat
impacts found in sources such as Furniss et al. (1991), Jones et al. (2000), and
Angermeier et al. (2004). The increasing presence of roads in the developed and
developing world has been identified as a threat to native freshwater species and water
quality alike. Czech et al. (2000), for example, identified roads as a likely contributing
factor in the local extinction and endangerment of 94 taxa across the U.S.

Road construction causes mortality and injury of stationary and slow-moving organisms
both within and adjacent to the construction footprint and alters the physical conditions in
the area, as well (Trombulak and Frissell 2000), often including direct conversion of
habitat to non-habitat within and adjacent to the footprint (Forman 2004). Behavior
modification depends on species and road size/type. Voluntary modification ranges from
use of the road corridor to avoidance; involuntary modification may result when a road
completely blocks the movement of organisms, resulting in fragmentation or isolation of
populations, often with negative demographic and genetic effects and with potential
consequences as grave as local population or species extinction and loss of biodiversity
(Forman 2004, Gucinski et al. 2001, Trombulak and Frissell 2000). Truncation offish
migrations due to passage barriers created by roads is one example of involuntary
behavioral alterations that compromise survival and productivity. Other behavior
modifications include changes in home range, reproductive success, escape response,
and/or physiological state (Forman and Alexander 1998, Trombulak and Frissell 2000).

Roads can create long-term, local changes in soil density, temperature, and water content,
light, dust, and/or surface water levels, and flow, runoff, erosion, and/or sedimentation
patterns, as well as adding heavy metals, deicing salts, organic molecules, ozone, and
nutrients to roadside environments (Forman 2004, Gucinski et al. 2001, Trombulak and
Frissell 2000, Forman and Deblinger 2000). When delivered to streams, road-derived
pollutants directly and indirectly impact water quality. The extension of natural stream
networks to integrate eroding road surfaces can cause sustained delivery of fine
sediments that alter bed texture and reduce the permability of streambed gravels (Furniss
et al. 1995, Wemple et al. 1996, Jones et al. 2000, Angermier et al. 2004). Increased
loading of fine sediments has been linked to adverse impacts on fish though several, often
co-occurring biological mechanisms, including decreased fry emergence, decreased
juvenile densities, loss of winter carrying capacity, increased predation on fish, and
reduced benthic organism populations and algal production (Newcombe and MacDonald
1991, Newcombe and Jensen 1996, Gucinski et al. 2001, Angermier et al. 2004, Suttle et
al. 2004, and many others). In steeper terrain, roads greatly increase the frequency of
slope failure and debris flow, with the resulting episodic sediment delivery to streams and
rivers (Montgomery 1994, Jones et al. 2000, Gucinski et al. 2001). Roads often promote
the dispersal of exotic species and pathogens by altering habitats, stressing native species,
and providing corridors and vehicle transport for seed/organism dispersal (Forman 2004,
8
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Trombulak and Frissell 2000, Gucinski et al. 2001). So long as they remain accessible
and passable enough to facilitate human use, roads also lead to increased hunting, fishing,
poaching, fish and wildlife harassment, use conflicts, lost soil productivity, fires,
landscape modifications, and decreased opportunities for solitude (Forman 2004,
Gucinski et al. 2001, Trombulak and Frissell 2000, Angermeier et al. 2004). Although
impacts to water and fish are the primary focus of this report, the direct and indirect
impacts of roads on other resources and their use should also be recognized.
Immediate Effects of Construction versus Long-term Impact of Use and Maintenance

Following Angermeier et al. (2004), the effects of roads are distributed across scales of
space and time in three discernible quanta. The first is the immediate and site-specific
effect from the construction of a new road. Many of these impacts are either transient or
are acute only during and shortly after initial construction. An example is the delivery of
large pulses of sediment to streams during runoff events after placement of fill or maj or
ground disturbance by heavy equipment. The second quantum is the suite of effects
caused by sustained operation, maintenance, and/or mere existence of the roadway.
Examples include seasonal runoff of pollutants such as deicing salts into nearby streams,
transport of wind-eroded dust from road surfaces to adjacent areas, chronic delivery of
sediment from erosion of road surfaces, ditches, and cut slopes, and the alteration or
sustained displacement of natural vegetation in the footprint and influence zone of the
road. Finally, often the greatest impact of road development is the ancillary
development of the landscape, or change in the pattern of human habitation, resource
extraction, and land and water use of a region, that the road in some way facilitates. The
remainder of this report focuses on the first two quanta, while acknowledging that the
third class of impacts is likely the most significant for Bristol Bay.
The hydrologic and biological effects of roads are generally similar in nature for
wetlands, streams, rivers, and lakes. Darnell et al. (1976, see especially pp. 129-136)
identified basic construction activities typically associated with industrial projects,
including roads and pipelines:

1) Clearing and grubbing;
2) Disposition of materials;
3) Excavation;
4) Sub-grade and slope/cut stabilization, including riprap;
5) Placement of fill;
6) Aggregate production;
7) Paving;
8) Equipment staging;
9) Borrow pits;
10) Landfills (disposal sites of excess excavated material).
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The authors summarized the categories of possible or likely impact from such projects
and activities on adjoining aquatic areas as follows:

1) Loss of natural vegetation;
2) Loss of topsoil;
3) Change of water table elevation;
4) Increased erosion;
5) Leaching of soil minerals from exposed and eroding soil surfaces;
6) Fluctuations in streamflow;
7) Fluctuations in surface water levels;
8) Increased downstream and upstream flooding;
9) Increased sediment load;
10) Increased sedimentation;
11) Increased turbidity;
12) Changes in water temperature;
13) Changes in pH;
14) Changes in chemical composition of soils and waters;
15) Leaching of pollutants from pavement;
16) Introduction of hydrocarbons to soils and waters;
17) Addition of heavy metals;
18) Addition of asbestos fibers (dispersed from industrial or natural sources); and
19) Increased oxygen demand (caused by organic matter export to and
accumulation in waterways).

These various alterations interact in complex cause-and-effect chains. Although
recognizing that long-term consequences of these alterations are to a significant degree
dependent on local circumstances, Darnell et al. (1976) nevertheless identified common,
general long-term outcomes that include 1) permanent loss of natural habitat; 2) increased
surface runoff and reduced groundwater flow; 3) channelization or structural
simplification of streams and hydrologic connectivity; and 4) persistent changes in the
chemical composition of water and soil.

Three other categories of impact common to roads have been identified in more recent
literature (Trombulak and Frissell 2000, Forman 2004): 1) disruption of movements of
animals, including fishes and other freshwater species; 2) aerial transport of pollutants
via road dust; and 3) disruption of near-surface groundwater processes, including
interception or re-routing of hyporheic flows, and conversion of subsurface slope
groundwater to surface flows. Because of their potential importance in the Bristol Bay
region, are further described in the following section.
Connectivity and Barriers to Fish Movement

Because roads alter surface drainage, and their stream crossing structures can either by
design or by subsequent alteration by erosion or plugging with debris, roads can form
barriers to the movement of freshwater organisms (Roeloffs et al. 1991, Trombulak and
10
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Frissell 2000, Gucinski et al. 2001.) Barriers to upstream passage into headwater streams
are most common. Pipelines may or may not have similar effects, depending on their
crossing design and association with access and maintenance roads.

Small headwater streams are the lifeblood of rivers and lakes; they sustain processes and
natural communities that are critically and inextricably linked to water quality, habitat
and ecosystem processes that sustain downstream resources (Lowe and Likens 2005).
The direct dependence of some fish on headwater streams for habitat is just one example
of these linkages. When road crossings block fish passage—as they often do (Flanders
Cariello 2000, Harper and Quigley 2000, Gucinski et al. 2001, FSSSWP 2008), the
isolated population(s) immediately lose migratory (anadromous or freshwater migrant)
species and life history types. Resident species that remain are also at risk of permanent
extirpation because barriers can hinder their dispersal and natural recolonization after
floods, drought, or other disturbances.

Bryant et al. (2009) found in southeast Alaska that Dolly Varden charr moved upstream
into very small streams primarily in fall, and coastal cutthroat trout primarily in spring.
Both species moved upstream just prior to their spawning season, but during low water
intervals, not during high-runoff events. Wigington et al. (2006) developed clear
quantitative evidence that free access to spawning and early rearing habitat in small
headwater streams is critical for sustaining coho salmon in an Oregon river. Culverts
and other road crossing structures not designed, constructed, and maintained to provide
free passage of such species can curtail migration, isolate these species from their
spawning and nursery habitats, and fragment populations into small demographic isolates
that are vulnerable to extinction (Hilderbrand and Kirshner 2000, Young et al. 2004).
Drawing inference from natural long-term isolates of coastal cutthroat trout and Dolly
Varden in Southeast Alaska, Hastings (2005) found that About 5.5 km length of perennial
flow headwater stream habitat supporting a census population size of greater than 2000
adults is required for a high likelihood of long-term population persistence. Beyond
diminishing potential survival and reproduction, barriers to movement can truncate life
history and genetic diversity of populations, reducing resilience and increasing their
vulnerability to environmental variability and change (Hilborn et al. 2003, Bottom et al.
2009).

The loss of some fish species due to road blockages and other barriers can bring
cascading ecological effects by altering key biological interactions. For example, the
blockage of anadromous salmon from headwater streams could trigger declines in food
web productivity caused by loss of marine-derived nutrients that originate from carcasses
and gametes of spawning salmon (Bilby et al. 1996, Wipfli and Baxter 2010).
Dust and Its Impact

Previous syntheses of the impacts of roads have not sufficiently addressed the effects of
road dust. Dust results from traffic operating on unpaved roads in dry weather, grinding
and breaking down road materials into fine particles (Reid and Dunne 1984). The
11
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resulting fines either transport aerially in the dry season or are mobilized by water in the
wet season. The dust particles may also include trace contaminants including deicing
salts, hydrocarbons, and a variety of industrial substances used in construction or
maintenance, or that are dispersed intentionally or unintentionally by vehicles on the road
(e.g., heavy metals or cyanide from transported mining waste, or asbestos fibers in some
mine and treatment projects). Especially after initial suspension by vehicle traffic, aerial
transport by wind spreads dust over varying terrain and long distances, meaning that it
can reach surface waters that are otherwise buffered from sediment delivery via aqueous
overland flow. Walker and Everett (1987) evaluated the impacts of road dust generated
in particular from traffic on the Dalton Highway and Prudhoe Bay Spine Road in
northern Alaska. Dust deposition altered the albedo of snow cover, causing earlier (and
presumably more rapid) snowmelt up to 100 meters from the road margin, as well as
increased depth of thaw in roadside soils. The authors also associated dust with loss of
lichens, sphagnum and other mosses, and a reduction of plant cover (Walker and Everett
1987). Loss of near-roadway vegetation has important implications for water quality, as
that vegetation is a major contributor to filtration of sediment from road runoff. Hence,
dust deposition not only contributes to stored sediment that will mobilize to surface
waters in wet weather, but can also reduce the capacity of roadside landscapes to filter
that sediment.
Near-Surface Groundwater and Hyporheic Flows

The potential Pebble Mine transportation corridor would have a high frequency of
crossings of streams, wetlands, and areas of shallow groundwater. These groundwater
systems include extensive hyporheic flow networks that connect surface waters through
shallow, subsurface flow paths. In the Bristol Bay watershed, they appear to be
especially associated with alluvial, glado-fluvial and glacio-lacustrine deposits, but also
locally with slope-mantling till and other locally porous deposits. Existing research sheds
relatively little light on the crucial subject of the impacts of road development on shallow
groundwater and the connectivity to surface water habitats important to fish. Due to the
apparent large extent and hydrologic importance of sub surface-to-surf ace hydrologic
connectivity to streams, lakes and wetlands in Bristol Bay (e.g., Woody and Higman
2011, Woody and O'Neal 2010), and to the recognized importance of groundwater-fed
habitats for northern latitude fishes (e.g., Cunjak 1996, Power et al. 1999, Malcom et al.
2004), this review pays particular attention to those linkages and how they can be
impacted by roads.

Rudimentary groundwater studies at roads traversing moderate slopes of conifer forest
and muskeg in southeast Alaska (Kahklen and Moll 1999) revealed there could be either
a bulge or a drawdown in groundwater level near the upslope ditch, while immediately
downslope of the road the water table was most often depressed. These effects appeared
for distances between 5 and 10 meters on each side of the road prism. The effect of
observed water table deformation on the downslope flux of groundwater remains
unknown.
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The distance to which a road influences subsurface flow paths may be considerably
greater in gently sloping alluvial and glaciolacustrine terrain, typically characterized by
shallower, porous zones of subsurface hyporheic or channeled subsurface flow that roads
can unearth or compact (Jones et al. 2000). It is well-recognized that management of
roads in such terrain types can be unpredictable and challenging, in part because it is very
difficult to anticipate the extent and nature of disruption to subsurface flow paths, large
volumes of water may be involved, and with low gradients, the effects of water table
deformation can project hundreds of meters from the road itself. (Darnell et al. 1976).

The high incidence of seeps and springs noted in glaciolacustrine, alluvial, and slope till
deposits within the Pebble prospect area (Hamilton 2007, Woody and O'Neal 2010)
testifies to the pervasiveness of shallow subsurface flow processes and inherent high
connectivity between groundwater and surface water systems in the terrain that would be
affected by the transportation corridor. Construction and operation of roadways and
pipelines can fundamentally alter the intricate connections between shallow aquifers and
surface channels and ponds, leading to further impacts on surface water hydrology, water
quality, and fish habitat (Darnell et al. 1976, Stanford and Ward 1993, Forman and
Alexander 1998, Hancock 2002). In wetlands, for example, hydrologic disruptions from
roads, by altering hydrology, mobilizing minerals and stored organic carbon, and
exposing soils to new wetting and drying and leaching regimes, can lead to changes in
vegetation, nutrient and salt concentrations, and reduced water quality (e.g., Ehrenfeld
and Schneider 1991). Hyporheic exchange processes may be further altered by changes
in sediment supply, both positive and negative, which alter infiltration, porosity, and
exfiltration of subsurface flow paths, as well as affecting mixing of upwelled and surface
water (Hancock 2002, Kondolf et al. 2002). Roads can either reduce sediment supply by
blocking downslope or downstream sediment transport or increase sediment supply by
creating a new source of eroded material (e.g., road fills, cuts, landslides), often
exacerbated by stream diversions that result in more erosive flows (Montgomery 1994).

Ground disturbance and catchment alteration by roads and other land use practices
generally increases erosion and sediment delivery to streams. In the Bristol Bay region,
many streams and rivers connect, directly or indirectly, to lakes. Of particular regard to
Pebble project is Lake Iliamna, which supports abundant and diverse sockeye salmon and
other species (Schindler et al. 2010). Accelerated sedimentation and accompanying
phosphorus deposition in lakes, as well as mobilization of dissolved and particulate
carbon and nitrogen result from shoreline and catchment disturbance (Birch et al. 1980,
Stendera and Johnson 2006), and these inputs can, in turn, trigger profound changes in
lake trophic status and food webs that could result in harmful effects on production of
sockeye salmon and other lake-dwelling species (Schindler and Scheurell 2002).
Nutrient delivery from road runoff and other road-related hydrologic alterations differs in
seasonal timing, quantity, and chemical makeup from nutrients delivered to streams and
lakes by anadromous fishes that die after spawning, hence it may have different
ecoystem-level effects. For example, road-associated runoff commonly combines inputs
of carbon, phosphorus, and nitrogen with suspended sediments, and the physical and
light-reducing properties of the sediments can profoundly impact the processing of those
nutrients by microbial films, plants, and filter feeders (Newcombe and Jensen 1996,
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Donohue and Molinos 2009). While the most profound and detectable physical and
biological effects occur in littoral zones and deltas, where sediments and nutrients are
directly delivered (and where sockeye spawning is often concentrated, [Woody 2007]),
suspended sediment and accelerated nutrient delivery can produce lake-wide effects
(Schindler and Scheurell 2002, Stendera and Johnson 2006, Donohue and Molinos 2009,
Ask et al. 2009). Ultraoligotrophic lakes (nutrient concentrations in both the water
column and lake sediments are extremely low) such as Iliamna can be among the most
vulnerable to major changes in lake status and function in response to increases in
nutrient or sediment inputs (e.g., Ramstack et al. 2004, Bradshaw et al. 2005).
Relationship of Road Density and Roadless Condition to Salmon

Across many studies in North America, higher abundances and more robust populations
of native salmonids typically correlate to areas of relatively low road density or large
roadless blocks (e.g., Baxter et al. 1999, Trombulak and Frissell 2000, Gucinski et al.
2001). One study from Alberta documented that bull trout occur at substantially reduced
abundance when even limited road development (road density of less than one mile per
square mile) occurs in the local catchment, compared to their typical abundance in
roadless areas (Ripley et al. 2005). In Montana, Hitt et al. (2003) found the incidence of
hybridization that threatens the westslope cutthroat trout within its native range increased
with increasing catchment road density. However consistent the correlations, the specific
causal links between roads and harm to fish are complex and manifold, and seldom laid
clear in existing research.

Nevertheless, in light of the already dramatic and widespread influence of roads in North
America (Forman 2000), protection of remaining roadless areas has been identified as a
potentially crucial and fiscally sound step for effective regional conservation offish and
wildlife (Trombulak and Frissell 2000, Gucinski et al. 2001).
Pipeline Spills

Pipelines have similar environmental effects as roads, with the primary difference being
that pipelines constantly or semi-continuously transport potentially toxic or harmful
materials that are only intermittently transported on roadways. In contrast to vehicle
transport, pipeline transport is often remote from direct oversight by human operators,
putting heavy reliance on remote leak detection. As a consequence, accidents with
pipelines can lead to dramatically larger spills than roadway accidents. Beyond pipeline
design, effective leak detection systems and inspection protocols are crucial for reducing
risk of leaks and spills, particularly in a relatively active seismic zone such as the Pebble
Mine area. However, in a review of recent pipeline spills in North America, Levy (2009)
finds that existing technology and contemporary practice does not provide firm assurance
against catastrophic spills.
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Pipeline crossings of streams are an obvious source of direct channel disturbance and
sediment entry, and as a result they have received considerable study (e.g., Lawrence and
Campbell 1980, Levesque and Dube 2007, Levy 2009). Pipeline installation can avoid or
reduce direct disturbance to channels by building full-span pipeline bridges over
waterways (at less expense than road bridges), or by boring underneath the streambed.

In addition to the access road, Ghaffari et al. (2011) describes a transportation corridor
(Figure 3) with four pipelines:

1) An 8-inch diameter steel pipeline to transport a slurry of copper-molybdenum
concentrate from the mine site to the port site, with one pump station at the mine
end of the line and a choke station at the port terminal;
2) A 7-inch diameter steel line returning reclaimed filtrate water (remaining after
extraction of the concentrate) to the mine site, fed from a pump station at the port
site;
3) A 5-inch diameter steel pipeline for pumping diesel fuel from the port site to the
mine site;
4) An 8-inch diameter pipeline for delivering natural gas from the port site to the
mine site (specifics of design not yet released).

All four lines would be contained in close proximity, for an unspecific portion of the
distance buried about five feet below the ground surface in a common trench, either
adjacent to or—in steeper terrain—beneath the road surface. The combined lines would
cross streams via either subsurface borings or suspended bridges, apparently with all
pipes encased in a secondary containment pipe, although the specific circumstances that
would receive secondary containment and what the containment design would be are not
available. In the design presented in Ghaffari et al. (2011, p. 336), there would be no
secondary encasement of the pipelines away from stream crossings

Available documents do not discuss the composition or potential toxicity of the mineral
slurry concentrate. However, it is likely that such a slurry would be toxic to some
organisms and that, due to its concentrated, aqueous form, it would readily transport
downstream or downslope of a spill site, and deposited materials on terrestrial surfaces
could generate leachate that enters groundwater systems. Projected chemical
composition of the returned slurry filtrate is also not available, but it is likely that this
water would have toxic levels of acidity and/or metals. As for the third line, diesel fuel
has known toxicity, with both acute and chronic effects on fish and other organisms
(Levy 2009 and elsewhere).

Liquified natural gas, the product that the fourth line would carry, consists primarily of
methane, which dissipates rapidly when released into water or the air, and is considered
non-toxic in those circumstances (Levy 2009). Large-scale explosions of natural gas
pipelines have occurred as a result of the accumulation of gas from slow leaks. Such an
explosion could pose a major risk of damaging or destroying the other pipelines in the
Pebble Mine corridor, disabling electronic leak detection and severing road access
necessary for emergency shut-offs or repairs. Containing all four pipelines, the primary
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access road, and the utility lines in a single narrow corridor, while reducing spatial
footprint impacts like erosion and sedimentation, would also bring the consequence,
albeit a low-probability one, of compounding the risk and potential scope of
environmental impact from a catastrophic event such as a methane explosion.
Proposed infrastructure corridor
Pebble deposit
Figure 3. Anticipated location of the road, pipeline, and utility transmission corridor for
Pebble Mine (Ghaffari et al. 2011, p. 326). The road would connect the Pebble Mine
operations with a new seaport on Cook Inlet. Not shown is an existing north-south
connecting tie road from near Nondalton to the Hiamna area. A segment from Cook Inlet
west to near Lake Iliamna would be reconstructed over an existing lower-standard
roadway.
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V. IMPACT FOOTPRINT OF THE PROPOSED PEBBLE MINE TRANSPORTATION
CORRIDOR ON WATER AND FISH

The Preliminary Assessment of the Pebble Project produced for Northern Dynasty
Minerals, Ltd. (Ghaffari et al. 2011) included a map and moderately detailed description
of the route of the potential Pebble Mine transportation corridor (see Fig. 3). The
following summary relies on that source for road location, while noting the caveat cited
in the document that the project ultimately proposed may be different.

According to Ghaffari et al. (2011), the proposed access road and pipelines would
provide for the basic infrastructural and transportation needs of the mine and its products
and have a fifty-year design life, consistent with the anticipated operating life of the
mine. The 86-mile corridor would contain an all-weather road with a two-lane, 30-foot
wide gravel driving surface. The road would link with the Hiamna airfield, as well as a
new deepwater port on Cook Inlet, from which ships would transport ore elsewhere for
processing. Northern Dynasty anticipates that the route would require twenty bridges,
ranging from 40 to 600 feet in total span, as well as 1,880 feet of causeway passing over
the upper end of Iliamna Bay and five miles of fill embankment along the shorelines of
Iliamna and Iniskin Bays.

The route of the transportation corridor stays south of the Lake Clark National Park
boundary. About eighty percent of the potential alignment is on private land held by
Alaska Native Village Corporations and other corporate landowners, with the rest owned
by the State of Alaska (Ghaffari et al. 2011). The route was reportedly selected with
regard to transportation and environmental concern in mind, but also with regard to
avoiding parcels of private land held by individuals (Ghaffari et al. 2011).

The Preliminary Assessment (Pp. 326-328) characterizes the proposed route as amenable
to road and pipeline construction with

. ...terrain favourable for road development. In general, soils are good to
excellent; where rock is encountered, it is fairly competent, useable for
construction material and amenable to reasonable slope development. The
numerous stream crossings appear to have favourable conditions for
abutment foundations. There are no significant occurrences of permafrost
or areas of extensive wetlands. Where the terrain is challenging, the rock
or soil conditions are generally favourable. In intertidal areas, subsurface
conditions appear favourable for placement of rock to create the required
road embankment

A comparison of the route to National Wetlands Inventory (NWI) data available for the
middle portions indicates that while the proposed route might avoid areas of particularly
extensive wetlands, nevertheless the route intersects or closely approaches a large number
of mapped wetlands (Figure 4 and Table 1). The route also crosses a great number of
mapped (and likely many more unmapped) tributary streams to Iliamna Lake on its 86-
mile traverse. The Preliminary Assessment does not identify alternative routes that
17
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would avoid or reduce impacts to wetlands, streams or shorelines.

Summarizing the account of Ghaffari et al. (2011, pp. 327-329), traveling eastward from
the Pebble Mine site, north of Hiamna Lake, the proposed transportation corridor passes
through diverse terrain and climatic zones. From the mine site, at an elevation of 1,100
feet above mean sea level, the road traverses variably sloping upland terrain over glacial
drift before descending to the Newhalen River valley, 11 kilometers north of Hiamna
Lake. From there, the route crosses variable terrain of dry, open tundra until approaching
Roadhouse Mountain, about 8 kilometers east of the river. The terrain and climatic
conditions of this western portion of the route are typical of western interior Alaska, with
relatively light precipitation, mild summers and winters with windblown snow. East of
Roadhouse Mountain, the route parallels the shoreline of Hiamna Lake apparently at a
distance of about five to eight kilometers from the shoreline, spanning a transitional
landscape of increasing snowpack and extensive spruce-hardwood forest cover. Roughly
20 kilometers west of Pedro Bay, the route approaches and occupies the shoreline of
Hiamna Lake, traversing the steep escarpment of Knutson Mountain, an area vulnerable
to avalanches, debris flows, and other high-energy montane processes. After skirting the
face of Knutson Mountain above the lakeshore, the route traverses an extensive outwash
plain northeast of Hiamna Lake, then ascends rugged terrain to cross Iliamna Pass and
wends its way some 32 kilometers through rugged terrain and increasingly warmer and
wetter Maritime climatic conditions until descending to the Iniskin Bay port site on Cook
Inlet.

Figures 4 through 8c and Table 1 provide a quantitative conceptualization of the potential
impact footprint of the Pebble Mine transportation corridor on the following known
resources:

1) Wetlands (Figure 4, Table 1);
2) Anadromous fish-bearing streams (Figures 5a and 5b);
3) Sockeye salmon spawning (Figure 6) and rearing (Figure 7) areas in the
Iliamna Lake system; and
4) Resident fish (Dolly Varden, arctic graying, rainbow trout, three-spine
stickleback, nine-spine stickleback, northern pike, and slimy sculpin; Figures
8a, 8b, and 8c).
18
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Proposed m&astnicture corridor

National Hydro graphyDataset streams
Figure 4. Overlay of the potential Pebble Mine transportation corridor1 on National
Wetlands Inventory (NWI) wetlands (U.S. Fish and Wildlife Service 2009). Digitized
NWI coverage is presently available only for the central portion of the corridor, from the
Newhalen River to Pile Bay (U.S. Geological Survey Quadrangles Iliamna D-3, D-4 and
D-5).
2 3
1 As mapped in Ghaffari et al. 2011.

2 NOTE the NWI map coding includes lakes and ponds that are not considered by
EPA to be classified as wetlands; however herein lakes and ponds are included in
this map as per the NWI; the map codes green mapped water bodies other than
streams.

3 In this area of Alaska, NWI mapping commonly underestimates actual field extent of
wetlands by as much as 50% (Gracz et al. 2008, Shaftel 201 Ipersonal communication).
19
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Table 1. NWI-mapped wetlands within and near the potential Pebble Mine
transportation corridor4 (U.S. Fish and Wildlife Service 2009). 5

Wetland Types

Wetlands
crossed by
alignment
m

Proportion of
mapped area
%

Wetlands crossed by corridor
m2 acres
Freshwater Emergent Wetland
2,555
3.8
1,135,667
281
Freshwater Forested/Shrub Wetland
2,800
4.2
1,356,058
335
Freshwater Pond
247
0.4
146,301
36
Lake
1,969
2.9
854,861
211
Other
122
0.2
38,671
10
Riverine
449
0.7
254,005
63
Total wetlands
8,142
12.2
3,785,563
935
Upland
58,676
87.8
33,676,263
8,322
Corridor not covered by NWI mapping
53,999
44.7
27,039,645
6,682
Total corridor
120,817
68,287,034
16,874
4 As mapped in Ghaffari et al. (2011}

5 "Crossed by alignment" refers to cumulative length of corridor median line that passes
through mapped wetlands of the various types. "Proportion" applies only to the corridor
within the area with digital NWI mapping (see Figure 4). "Crossed by Corridor" is the
area of wetlands within the corridor, using a fixed 500-meter width to capture the zone of
greatest direct and indirect influence and to account for uncertainties of actual location of
the road, pipelines and other corridor features.
20
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Figure 5a. Anadromous fish-bearing streams (documented to support at least one
species of salmon) crossed by the eastern half of the potential Pebble Mine transportation
corridor (Chekok Creek east to Y Valley Creek).6 Map compiled from Alaska
Department of Fish and Game (ADFG) catalog sources (Johnson and Blanche 201 la,
201 lb)7, supplemented with additional spawner count data (Morstad 2011, personal
communication. Compiled data on species present and available estimates of sockeye
spawning population size in each stream are provided in Appendix A.
6 Median alignment of the corridor was defined by scanning and geo-referencing the
Pebble transportation corridor route map from Ghaffari et al. (2011. Figure 1.9.2, p.57).

7 Field surveys indicate that ADFG Catalog (Johnson and Blanche 201 la, 201 lb)
under-represents the actual extent of salmon spawning (Woody and O'Neal 2010],
although these figures do reflect some updates based on recent surveys.
21
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\ 'V/1
Ml

Anadromous Waters Catalog streams

National Hydrography Dataset stream
r&

Ci
> \,J<
/ S ] ^j
J *~ *ri. m
Figure 5b. Anadromous fish-bearing streams (documented to support at least one
species of salmon) crossed by the western half of the potential Pebble Mine
transportation corridor (Upper Talarik Creek east to Canyon Creek).8 Map compiled
from Alaska Department of Fish and Game (ADFG) catalog sources (Johnson and
Blanche 201 la, 201 lb)9, supplemented with additional spawner count data (Morstad
2011, personal communication. Compiled data on species present and available
estimates of sockeye spawning population size in each stream are provided in
Appendix A.
8 Median alignment of the corridor was defined by scanning and geo-referencing the
Pebble transportation corridor route map from Ghaffari et al. (2011. Figure 1.9.2, p.57).

9 Field surveys indicate that ADFG Catalog (Johnson and Blanche 201 la, 201 lb)
under-represents the actual extent of salmon spawning (Woody and O'Neal 2010],
although these figures do reflect updates based on recent surveys.
22
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Sockeye spawning densities. 1955-2011
SO-4200
• 4 200 -12,200

12200-26,000

26.000-72.800
Figure 6. Pattern in abundance of spawning sockeye salmon in Iliamna Lake and
tributary streams relative to the potential Pebble Mine transportation corridor. A general
concentration of sockeye spawning is apparent in the northeast portion of Iliamna Lake.
Spawner density data compiled from Johnson and Blanche (201 la, 201 Ib, as average
counts collected with varying regularity between 1955-2011).
10
10 Morstad (2003) and Morstad (2011, personal communication), with additional
information on sampling locations from Rich (2011, personal communication).; summary
data presented in Appendix A)
23
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Figure 7. Uiamna Lake juvenile sockeye catches in tow-net sampling, 1961-1976,
relative to the potential Pebble Mine transportation corridor. High-density rearing sites
are concentrated in the eastern half of the lake, where the transportation corridor comes
closest to the lakeshore and intersects with numerous tributaries. Compiled from data
provided by Rich (2011, personal communication).n
11 Sampling methods for these data are described in Rich (2006).
24
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Freshwater Fish Inventory data points Proposed infrastructure corridor
— Anadromous Waters Catalog streams 62 streams crossed by corridor
National Hydrography Dataset streams
12
Figure 8a. Resident or nonadromous fish streams crossed or potentially affected by the
eastern one-third of the potential Pebble Mine transportation corridor. 3 Data compiled
and mapped from ADFG (2011) and Buckwalter (2011, personal communication).
Stream names and fish species known present are summarized in Appendix B.
12 Secondary tributaries entering trunk streams downstream of the transportation
corridor are indicated because they could be isolated and freshwater migrant life
histories harmed by spills affecting the trunk stream.

13 Median alignment of the corridor was defined by scanning and geo-referencing the
Pebble transportation corridor route map from Ghaffari et al. (2011).
25
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0 £
10 Kilometers
Freshwater Fish Inventory data points Proposed infrastructure corridor
• Anadromous Waters Catalog streams 62 streams crossed by corridor
National Hydrography Dataset streams
14
Figure 8b. Resident or nonadromous fish streams crossed or potentially affected by the
central one-third of the potential Pebble Mine transportation corridor.15 Data compiled
and mapped from ADFG (2011) and Buckwalter (2011, personal communication).
Stream names and fish species known present are summarized in Appendix B.
14 Secondary tributaries entering trunk streams downstream of the transportation
corridor are indicated because they could be isolated and freshwater migrant life
histories harmed by spills affecting the trunk stream.

15 Median alignment of the corridor was defined by scanning and geo-referencing the
Pebble transportation corridor route map from Ghaffari et al. (2011).
26
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Freshwater Fisn Inventory data points Proposed infrastructure corridor
— Anadromous Waters Catalog streams 62 streams crossed by corridor
National Hydrography Dataset streams B@£@j Pebble deposit
16
Figure 8c. Resident or nonadromous streams crossed or potentially affected by the
western one-third of the potential Pebble Mine transportation corridor.1? Data compiled
and mapped from ADFG (2011) and Buckwalter (2011, personal communication).
Stream names and fish species known present are summarized in Appendix B.
16 Secondary tributaries entering trunks downstream of the transportation corridor
are indicated because they could be isolated and freshwater migrant life histories
harmed by spills affecting the trunk stream.

17 Median alignment of the corridor was defined by scanning and geo-referencing the
Pebble transportation corridor route map from Ghaffari et al. (2011).
27
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Drawing on published conceptualizations that plot the extent of environmental and
ecological influences of roads as a spatial footprint (Forman 2000, Forman and Deblinger
2000, Trombulak and Frissell 2000, Jones et al. 2000), Figures 5 through 8 illustrate that
the potential Pebble transportation corridor could have widespread regional effect on the
aquatic ecosystems that feed Iliamna Lake. Figures 8a, 8b, and 8c identify both upstream
and downstream habitat that is susceptible to loss or degradation due to structural
failures, spills, sedimentation, or other impacts originating in the transportation corridor.
Through hydrological dispersion of sediment or toxicants, the maps illustrate that a large
proportion of Iliamna Lake salmon habitat would be vulnerable to indirect impact, or
direct impact at a point removed from the origin of a spill, either through potential
exposure to pollutants downstream of the transportation corridor or blockage of migration
to spawning and nursery habitats upstream.

A significant fraction of Iliamna Lake's sockeye salmon resource would be vulnerable to
impacts from the Pebble transportation corridor. Migration and spawning in these streams
could be compromised below the corridor crossing by sedimentation or contamination
from spills, and habitat upstream from the crossings could be cut off from access by spills
or structural failures. To roughly estimate the proportion at risk, Shaftel (2011, personal
communication) adjusted the stream length potentially affected by the transportation
corridor in each system by the average surveyed spawner density for that system (Figure
6, Appendix A). This analysis suggests that about twenty percent of known stream
spawning populations of Iliamna system sockeye reproduces in streams and rivers
intersected by the Pebble corridor (R, Shaftel, 2011 personal communication). Moreover,
Shaftel reports that many principal sockeye fluvial spawning areas lie in close proximity
to road and pipeline crossing sites. In addition, a major sockeye salmon beach spawning
site is located at the mouth of Knutsen Creek (Rich 2006, 2011), a stream that the Pebble
transportation corridor would cross, making its delta vulnerable to impacts from
upstream. If the Knutsen Creek delta spawning population is included in the tally of
potentially affected waters, roughly thirty percent of known Iliamna Lake sockeye
spawners could be at risk. A similar analysis from the University of Washington
Fisheries Research Institute came to a similar conclusion (Rich 2011, personal
communication).

Available data show that rearing sockeye salmon are most concentrated in the eastern
half of the lake (Figure 7), where the Pebble transportation corridor would intersect with
numerous direct tributaries to the lake and for some distance would occupy the lakeshore
itself, posing a high risk, if not a certainty of affecting Iliamna Lake habitats.
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VI. MITIGATION MEASURES AND LIKELY EFFICACY

It is commonly recognized that the environmental impact of a major construction project
like a road or major pipeline corridor can never be fully mitigated (Trombulak and
Frissell 2000). Indeed, inherent to the underlying purpose of road projects (i.e., to alter
natural conditions so that vehicle transportation is possible where it was physically
impossible before) are changes to landscape structure that not only irretrievably alter
ecosystem and biological conditions within the construction footprint, but also interrupt
or modify the natural flux of water, sediment, nutrients, and biota across the ecosystem,
usually permanently (Darnell et al. 1976, Rhodes et al. 1994, Forman and Alexander
1998, Forman 2000, Forman and Deblinger 2000, Trombulak and Frissell 2000).
Moreover, engineering or implementation failures, unanticipated field conditions, and/or
unforeseen environmental events inevitably test and compromise the effectiveness of
mitigation measures applied in large projects (e.g., Espinosa et al. 1997, Levy 2009). The
only sure way to avoid impacts to a freshwater ecosystem from a large road or pipeline
project is to refrain from building such a project in that ecosystem (Frissell and Bean
2009).

Unfortunately the scientific and professional literature on the subject of the effectiveness
of environmental mitigation measures for water and fish is sparse and poorly synthesized.
There are lists of standard practices and there are a scattering of short-term, site-specific
studies of efficacy of mitigation measures for roads and pipelines (e.g., assessment of
mitigation of the delivery of sediment and its local impact on biota). Some report
showing adverse impact, or ineffectiveness of mitigation measures, and others report not
detecting adverse effects, which is often taken as circumstantial evidence that mitigation
measures were effective. Exceedingly few of these studies extend to medium- or long-
term evaluation of mitigation effectiveness, and fewer still have been published in
accessible peer-reviewed forums. Therefore, evaluating the effectiveness of proposed
mitigation measures remains a process of best professional judgment and logical
evaluation of premises, specific environmental context, and likely operational
circumstances. The release of the Preliminary Assessment for the Pebble project this
year (Ghaffari et al. 2011) allows some specific analysis of the potential transportation
corridor.

A few synthesis documents also provide some guidance (e.g., Rhodes et al. 1994), but the
over-arching theme is that implementation of site-specific mitigation measures is fraught
with uncertainty and risk and that, overall, mitigation has proven to be ineffective in fully
protecting water quality and conserving freshwater fishery resources (Esiponsa et al.
1997).
29
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Mitigation Measures for Pebble Road

In the following section I cite mitigation measures identified in Ghaffari et al. (2011) for
the Bristol Bay transportation corridor and briefly assess 1) their likely effectiveness to
avoid or prevent harm to Bristol Bay water quality and fishery values, 2) possible adverse
side effects of applying the mitigation measure, and 3) alternative mitigation measures
that could be more effective, given the project is assumed to proceed.

As far as practicable, minimize areas of disturbances (Ghaffari et al. 2011, p. 3 29). This
means restricting the footprint of construction activities and the final footprint of the
project to the minimum practical surface area (for example, by stacking the road and
pipelines in a single corridor). The effectiveness of this measure depends on the location
of disturbance relative to resources at risk. Even a small footprint that involves
permanent alteration of soils, vegetation, and hydrology can have significant adverse
effects that propagate across the landscape by hydrologic and other vectors. This
measure must be practiced in the context of measures to avoid sensitive locations to be
effective. Secondly, the effectiveness of this measure depends on how other project
parameters, including capital cost, delimit what is "practicable." Limiting the area
disturbed can often involve expensive practices such as long-distance hauling of waste
material in preference to onsite storage. Finally, it is important to reiterate there are
potential risks associated with minimizing the footprint of the transportation corridor by
"stacking" the road and pipelines closely together. A pipeline failure or gas explosion
could sever the sole available route for ground transportation of equipment and personnel
to take emergency remedial measures.

As far as practicable, minimize stream crossings and avoid anadromous streams
(Ghaffari et al. 2011, p.329). This mitigation measure can be effective if three conditions
are met: 1) the landscape structure supports a route that avoids and is buffered from
strong interaction with streams, wetlands, and areas of near-surface groundwater; 2)
implementation does not result in a route so long and tortuous that it encumbers
additional environmental risk (e.g., to upland vegetation and wildlife), 3) resources are
sufficient to ensure that costly but environmentally sounder locations and possibly longer
routes are "practicable." Ghaffari et al. (2011, pp. 329-330) lists several other criteria
that constrain choice of road location, such as:

1) Avoiding certain "unfavorable" land ownerships;
2) Avoiding potential (albeit unspecified) geologic hazards;
3) Keeping road gradients under 8 percent;
4) Maintaining minimum curvature and design speeds;
5) Facilitating high axle loads for transporting assembled mine equipment;
6) Optimizing crossings of soils suitable to maintaining roadway structure and
stability;
7) Optimizing access to sources of construction and surfacing rock;
8) Incorporating minimum 2.5-foot (76 centimeter) ditches (possibly necessary
for maintaining subgrade stability in many wet or seasonally wet areas); and
9) Minimizing area of disturbance.
30
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These competing objectives for the roadway, coupled with the large number of streams in
the landscape between the Pebble Mine site and Cook Inlet serve to limit the
effectiveness of this measure. To be most effective, minimizing stream crossings must
take primacy above other objectives of economic or operational convenience in project
siting and route location. However, even in then, one potential side effect of basing
route selection on minimization of stream crossings in a stream-rich landscape would
likely be a route that is tortuous, countervailing the preceding mitigation measure of
minimizing area of disturbance. Hence the two most potentially effective mitigation
measures can stand in opposition to each other, especially in landscapes of relatively high
stream density.

Appropriate Best Management Practices (BMPs) will be utilized for the maintenance of
the road during operations and construction. Ghaffari et al. (2011, p. 370). The
Preliminary Assessment does not identify the appropriate practices for road maintenance
and construction, so it is not possible to specifically address their likely effectiveness at
reducing water quality and fisheries impacts. Specifically with regard to maintenance,
BMPs should include a strict prohibition on the disposal of material generated from
grading and snow removal into surface waters, and should specify grading practices that
retain a local road contour necessary to disperse road surface drainage away from
streams, rivers, Iliamna Lake and areas that drain to those waterways (Weaver and
Hagans 1994, Wemple et al. 1999, Furniss et al. 1991, Moll 1999). Construction
specifications should also designate sites for waste rock disposal and temporary materials
storage and stipulate that they be in locations with minimum risk of subsequent transport
of material to streams, rivers, or Iliamna Lake, whether by water, wind, or mass failure
(Weaver and Hagans 1994). These practices pose minimal risk of environmental side
effects, though they may increases annual operational costs. However, because these
practices are also effective at reducing roadway harm from erosion, over years they may
reduce maintenance and repair costs of the roadway.

Road dust abatement measures. Ghaffari et al. (2011, p. 458) mentions dust suppression
as a generic need, but the only allusion to specific mitigation regards procurement of a
water spreading truck (Ghaffari et al. 2011, p. 313). The Preliminary Assessment
mentions developing a dust dispersion model as part of the permitting process for air
emissions (Ghaffari et al. 2011, p. 458), but it does not address dust impacts to surface
waters. Depending on mineralogy, water application can be effective at reducing dust
transport, if application is frequent and of appropriately limited volume (USDA Forest
Service 1999). There are, however, offsetting factors: moderate or heavy application of
water that exceeds the very low infiltration capacity of the road surface mobilizes dust in
fluid runoff instead of aerial deposition. Wherever a road is in close proximity to surface
waters, such runoff can deliver suspended sediments, perhaps quite frequently, to
locations where., or at seasons when., they are otherwise virtually nonexistent. Loss of
fines from the road rock matrix can contribute to breakdown and accelerated erosion of
the road surface (USDA Forest Service 1999). On the other hand under-application of
water fails to fully abate dust generation.
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Dust abatement measures can bring unintended side effects. Even when dust abatement
is effective in retaining fines within the road rock matrix during the dry season, these
fines are simply mobilized by water and transported to the surrounding landscape in wet
season runoff (Reid and Dunne 1984). The fine sediments are not eliminated—merely
reallocated. Other dust controls, including chloride salts, clays, lignosulfanate or other
organic compounds, and petroleum distillates (Hoover 1981) bring risk of toxic effects
when they run off and enter surface waters, though little research is available to assess
their environmental risks or safe conditions of application (USDA Forest Service 1999).
In the case of chloride salts, one recommendation is to avoid application within 8 meters
of surface waters or anywhere groundwater is near the surface (USDA Forest Service
1999). Adverse biological effects are likely to be particularly discernible in naturally
low-conductivity waters like those of Bristol Bay, although research is needed to
substantiate this speculation. The best practice to minimize dust pollution is to avoid
road construction; the next most effective mitigation is surfacing all roadways with high-
grade asphalt pavement, with diligent maintenance of the paved road surfaces.

Paving can measurably reduce (though not eliminate) the chronic generation and delivery
of both wet-weather surface-erosion and dust (Furniss et al. 1991, Weaver and Hagans
1994). However, asphalt production, deposition, and weathering generates hydrocarbons
that may, in some circumstances, be harmful to aquatic life (Spellerberg 1998,
Trombulak and Frissell 2000). In addition, off-site transfer of heavy metals and other
contaminants from road treatments such as deicing salts could be more rapid and direct
from paved road surfaces. Moreover, in the case of the potential Pebble transportation
corridor, pavement could complicate excavation needed to access pipelines buried under
the road for visual inspection or repairs of leaks.
River and stream crossing structures have been designed to minimize the impact of the
project on areas of sensitive habitat (Ghaffari et al. 2011, p. 370). The Preliminary
Assessment further specifies that structural elements, including foundation elements, will
be designed to comply with a Memorandum of Agreement between ADOT and ADFG
regarding the design of culverts for fish passage and habitat protection. Wherever
culverts are not "suitable," Ghaffari et al. state the road would incorporate single- or
multiple-span bridges, with specifications based on "hydrological considerations, local
topography and fish passage requirements." Although criteria for determining crossing
structure type are not provided, the Preliminary Assessment identifies thirteen possible
multi-span bridge crossings, at "major" rivers, including 600-foot spans both at the
Newhalen River and across tidal flats at Iliamna Bay (Ghaffarri et al. 2011, p. 332).

Road crossing designs are much improved over historic practice, but where rivers are
wide and river or stream channels shift location frequently, any crossing structure short of
fully spanning the channel migration or flood-prone valley width can prove problematic.
Because of the nature of design structures and geomorphic setting, crossings of small
streams (under about 3 meters in width) pose greater risk of causing barriers to animal
migration and movement of sediment and natural debris, whereas crossings of larger
streams pose risk of erosion, sedimentation, channel and floodplain alteration, and
32
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delivery of pollutants from spills. The importance of small streams in Bristol Bay for
Dolly Varden and other fish species (Woody and O'Neal 2010) underscores the need for
culverts to provide fish passage and maintain fish habitat, even where salmon are absent.
Numerous studies also document that connectivity between small headwater streams
(including streams with intermittent or seasonal flow) and downstream habitats is
important and, in some cases, critical for productivity and survival of salmonids (e.g.,
Hilderbrand and Kirshner 2000, Young et al. 2004, Fausch et al. 2002, Hastings 2005,
Wigington et al. 2006, Bryant et al. 2009).

In general, culvert crossings of small streams remain problematic, even under
contemporary standards and practices as applied by state highway departments and land
management agencies. Flanders and Cariello (2000) reported that 66 percent of the
culverts on salmon streams and 78 percent of the culverts on non-anadromous trout
streams in the Tongass National Forest in southeast Alaska were inadequately designed
and maintained for fish passage. Gibson et al. (2005) surveyed a 210-kilometer segment
of the Trans-Labrador highway, newly constructed under prevailing Canadian
government and provincial regulations for fish protection, and found that more than half
of the culverts posed fish passage problems due to inadequate design or poor installation.
Chestnut (2002), in a survey of stream crossings in Kamloops, British Columbia, found
that out of 31 culverts assessed, all but one failed to meet Department of Fisheries and
Oceans objectives for juvenile fish passage and maintenance offish habitat. In an audit
of two other Provincial Forest Districts in British Columbia, Harper and Quigley (2000)
concluded about a third of road culverts blocked fish passage to upstream habitat.

In small streams without significant near-surface groundwater associations, the
effectiveness of different stream crossing structures depends on the geomorphic setting,
including stream gradient and channel stability, road slope and angle of interception,
flashiness of water and sediment flows, and abundance and size range of wood and other
waterborne debris. In small prairie streams, for example, Bouska et al. (2010) found that
large box culverts were less disruptive of stream morphology and hydrodynamics than
were low water crossings and corrugated metal culverts. Large-width, bottomless arch or
"squashed design" culverts that preserve or restore a natural channel bed material train
through the length of the culvert are the current standard norm for stream crossings to
maintain both physical and biological connectivity (Weaver and Hagans 1994, FSSSWG
2008). In recent years, the US Forest Service has worked to reduce risk of failure and
improve passage offish and other biota at road at road crossings using a new so-called
"Stream Simulation" design protocol for culvert crossings of small streams that
emphasizes dramatically wider, open-bottom arch stream crossing designs that strive to
maintain both geomorphic and biological continuity through the crossing (FSSSWG
2008). Greater expense of initial design and installation may be compensated by longer
life spans (round corrugated steel culverts commonly have a functional life span of 20
years, if properly functioning) and fewer emergency maintenance and repair costs
(Weaver and Hagans 1994).

Effective mitigation of adverse roadway impacts to streams must account explicitly not
just for the passage offish and surface waters; in ecosystems like Bristol Bay that are rich
33
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in shallow groundwater, roadways must also avoid disrupting or obstructing hyporheic
flow paths and shallow aquifers. Short of not building new roads altogether, the most
effective practice to avoid alteration of hydrology and hydrologic connectivity is to locate
the route well away from streams, wetlands, springs, seeps, areas of near-surface
groundwater, pond and lake shorelines, and alluvial fans and glacio-alluvial valley trains
where frequently shifting stream courses are present. Due to the number and density of
streams, zones of near-surf ace groundwater, and associated wetlands in the area of the
potential transportation corridor (Hamilton 2007), complete avoidance of "sensitive
habitat" would be exceedingly difficult. If avoidance of these sensitive hydrologic
features is impossible, the next best mitigation is bridge the roadway across them,
completely spanning the area of both surface water and near-surface groundwater,
thereby reducing direct physical intersection of the roadway and water features. At
streams, crossings should occur only where channels are stable, not migrating and not
branching. Where long suspensions are necessary to bridge multiple or coextensive
hydrologic features, special engineering is required to manage stormwater drainage that
accrues on the extensive suspended roadway and route and disperse this discharge to
areas well away from surface waters.

Where spanning extensive areas of shallow groundwater is impracticable (e.g., due to
expense), the next most effective mitigation would be to "lift" the road surface over them
by use of porous fills. Porous fills (commonly large, angular open-framework rock
capped by a surface of mixed material) can provide a stable road prism and support heavy
vehicle loads, while passing overland or sheet flow with limited concentration and
maximum dispersion of water, thereby reducing erosive forces and impacts to local
hydrology (Moll 1999). Nevertheless, porous fills do partly obstruct surface drainage,
blocking the movement of sediment, debris, and aquatic organisms and despite some
filtering capacity, they do not fully control delivery of sediment and other pollutants from
the road surface into surface waters. Under heavy tire loads, porous fill road beds may,
over time, subside into subsurface soils and alluvial deposits, allowing native fines to
enter and clog the porous matrix, eventually making it a barrier to subsurface flow.
Burial in a common trench. (Ghaffari et al. 2011, p. 336). Burial aids in insulation of the
pipeline. It also can reduce pipeline impact on wildlife movements, and in steep,
mountainous terrain, it can partially protect pipelines from damage and potential spills
caused by surface processes like avalanches, landslides and debris flows (Levy 2010).
Equally important, clustering of pipelines reduces the direct spatial footprint of
disturbance to habitat by concentrating construction and maintenance activity. The
smaller footprint, in turn, minimizes the area destabilized by excavation and backfill, thus
reducing impacts to water quality from construction site runoff. The downsides of
pipeline burial are that: 1) it prevents visual inspection of the lines for leakage and visual
monitoring of spilled materials; 2) it typically does not incorporate secondary
containment measures for spills and leaks; and 3) it can disrupt subsurface hydrology by
severing, damming, or capturing buried flow paths. Visual inspection is a vital backup to
electronic leak detection systems and may be the only sure way to detect some chronic,
slow leaks. Finally, buried pipelines are still vulnerable to stress and rupture from
34
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subsurface processes, such as earthflows, slumps, and seismic shocks.

Secondary containment of buried lines, using an impermeable lining for the trench, could
help limit the discharge of material in the event of leaks or spills, but would have the
opposing effect of causing greater distortion of natural subsurface flow paths. By acting
as a subsurface dam, a lined trench could not only disrupt natural hydrology patterns, but
by obstructing subsurface water flow, belowground containment structures could
complicate the management of drainage that is necessary to maintain the road surface
and the trench itself. From the standpoint of the protection of water quality and fish
resources, ideal mitigation measures could include: 1) keeping the pipelines above
ground and visible (except where landslide and avalanche risks are moderate to high); 2)
incorporating some means of secondary containment for spills and leaks; 3) installing
manual shutoff valves at either side of all surface water crossings and all locations
vulnerable to damaging landslides or avalanches; and 4) implementing robust plans for
both very frequent or full-time visual inspection for leaks, and rapid response for
containment, shutdown, repair, and disposal of contaminated material when leaks do
occur. Note that these measures may have adverse side effects; for example, elevated
pipelines may be more disruptive of wildlife movements, such as caribou migrations.

There is another drawback of clustering that the above mitigation measures would not
resolve. With common proximity of the lines, there might be some risk that natural gas
leakage and subsequent explosion could both damage the other lines and hinder rapid
response to repair damage and contain spills (due to damage to the road). This risk bears
close examination by appropriate experts.

Boringpiplines under stream (Ghaffari et al. 2011, p.337). Horizontal boring of a
pipeline under stream crossings can reduce much of the channel disruption, erosion and
sedimentation associated with trenching and exposed line surface crossings. However,
the method suffers from the same drawbacks identified above under Burial in a common
trench. In particular, leakage of the lines under the stream course could result in
undetected contamination of hyporheic, thence surface waters. To reduce impacts to fish
and water quality, the most effective mitigation measure likely would include suspending
pipelines (along with road crossings) on full-span bridges that minimize disturbance to
surface water, as well as containing the pipelines in a secondary pipe designed for and
operated under a plan that includes frequent visual inspection and robust spill response
procedures. Burial—with secondary containment—could be appropriate for unavoidable
crossings of areas with unstable slopes prone to landslides and avalanches. Note that
these measures may have adverse side effects; for example, elevated pipelines may be
more disruptive of wildlife movements.

Secondary containment pipe ("encased in a protective layer") for overhead stream
crossings on bridges (Ghaffari et al. 2011, p. 337). Secondary containment is a
particularly important measure for isolating and managing leaks or spills wherever the
pipeline is directly above surface water. Ideally, some form of secondary containment
should extend to other locations where leaks or spills could reach and contaminate
surface or subsurface waters. There also should be specific procedures and requirements
35
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for response and materials handling in the event of leaks or spills into the containment
system, to prevent secondary pollution from leaching or spill of contaminated materials.
Advance designation and preparation of an array of well-distributed storage pads for
contaminated soils at dry, stable sites far removed from surface waters or shallow
groundwater would be among the needs to implement this measure effectively. These
precautionary structural measures are likely to be costly.
Manual isolation valves on either side of major river crossings (Ghaffari et al. 2011, p.
376). The Preliminary Assessment does not define "major" river crossings, but they
would presumably include multi-span crossings such as that of the Newhalen River. The
effectiveness of manual closure correlates directly to the effectiveness of leak detection
and rapid response. Coupled with full-time, fully redundant electronic and visual leak
detection systems and valve locations as suggested above, manual valves could
considerably improve the odds of successful stream protection from leaks and spills.
Again, the surveillance and logistical measures needed to support a rapid response to
accidents can be costly.

Electronic Leak Detection Systems (Ghaffari et al. 2011, p. 376). The Preliminary
Assessment discusses implementing an electronic leak detection system for the pipelines,
using pressure transmitters located along the length of the lines. It also specifies a
SCADA (Supervisory Control and Data Acquisition) system for monitoring and control
of the pumping stations, with fiber optic communications between the concentrator and
the port site tying the detection systems together. The most effective approach to leak
detection includes redundant systems for each separate pipeline. However, the proposed
approach appears to tie leak detection for all four systems to a single fiber optic line.
Coupled with the close proximity of the four pipelines, a single communications line
increases the chance that leak detection could be disrupted by the same event that
triggered a leak (e.g., a seismic dislocation, lake seiche wave, or large landslide). As
suggested above, providing for rigorous visual inspection would further increase the
effectiveness of electronic leak detection and reduce the risk of undetected spills.
VII. CONCLUSIONS

• Bristol Bay's robust and resilient salmon fishery is in part associated with the
watershed's extremely high quality waters and high integrity freshwater
ecosystems, minimally impacted by roads and industrial development.

• A second major contributor to the Bristol Bay watershed's productivity for
salmon is its abundant and extensive near-surface groundwater and strong vertical
linkage between surface waters and groundwaters, across a wide range of stream
sizes and landscape conditions.
36
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• Any environmental analysis and planning of a road project such as the Pebble
Mine road must consider the significance of initial road development as an
economic and social stepping stone to future roads and developments.

• Roads, in particular can foster the incremental decline of salmon and other native
fishes by their own direct environmental impact, but equally important is that
roads facilitate a variety of human activities that bring their own suite of impacts.
including increased access to primitive lands, increasing legal and illegal hunting
and fishing, use of off-highway vehicles, increased mineral prospecting, and
others.

• For the Pebble road corridor, each stream or wetland crossing has the potential for
impacts to not just to salmon populations in the stream itself, but also
downstream in Iliamna Lake, which is in close proximity.

• The Pebble transportation corridor poses risks of direct and acute impacts to
salmonids, including possible loss of populations due to blocking of migration
pathways from spills or from stream crossing dysfunctions. Like any such
development, it will certainly cause chronic, pervasive "press disturbances"
(sensu Niemi et al. 1990) all along its length and for its entire existence,
contributing to deterioration of quality of spawning habitats, reduced habitat
diversity, disrupted groundwater hydrology, alteration of roadside vegetation, and
related impacts that stem from construction, operation and maintenance.

• Many environmental mitigation measures identified for the Pebble Project suffer
from being mutually exclusive or offsetting, from being superseded or limited by
fiscal or operational concerns, or are likely to be ineffective given the
hydrogeomorphology and inherent sensitivity of the environment in Bristol Bay
watershed.
37
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ACKNOWLEDGMENTS

Rebecca Shaftel of the Alaska Natural Heritage Program, Anchorage contributed
immensely to the analytic and graphical content of this report; she prepared all the maps.
We thank Harry Rich and Dr. Thomas Quinn of the University of Washington School of
Fisheries and Aquatic Sciences for critical data and analytic leadership in the assessment
of risk to sockeye salmon and other fishery resources.
38
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Appendix A. Numbers of sockeye salmon estimated in Lake Clark and Lake Iliamna
spawning areas.

Complied from ADFG (2011) spawner survey data from 1955-2011, with additional data
from Rich (2011, personal communication), by
Rebecca Shaftel (Alaska Natural Heritage Program, Anchorage).
Stream Name1
Length of anadromous Average no. of spawners,
stream (km) Species present 1 955-201 12
upstream downstream (no.
Upper Talarik Creek
Newhalen River
Roadhouse Creek
Hudson's Ponds
NW Eagle Bay Creek
NE Eagle Bay Creek
324-10-10150-2249
Young's Creek, mainstem
Young's Creek, east branch
Chekok Creek, west branch
Chekok Creek, mainstem
Canyon Creek
Wolf Creek
Mink Creek
Knutsen Creek
324-10-10150-2307
Pedro Creek and ponds
Russian Creek
324-10-10150-2333
Pile River
Iliamna River
Chinkelyes Creek
Y-Valley Creek
47.80
258.68
0.00
0.00
0.22
4.08
0.00
7.37
5.56
3.82
25.74
3.97
0.00
0.00
0.28
0.00
0.00
0.00
0.19
13.23
41.20
0.00
5.47
74.59 coho, Chinook, chum, sockeye
arctic char, coho, Chinook,
28.13 sockeye
10.85 sockeye
2.43 sockeye
1 1 .41 arctic char, sockeye
1 1 .28 arctic char, sockeye
3.95 arctic char, sockeye
8.88 arctic char, coho, sockeye
2.76 arctic char, coho, sockeye
4.83 arctic char, coho, sockeye
5.58 arctic char, sockeye
5.89 arctic char, sockeye
3.73 arctic char, sockeye
1 .69 arctic char, sockeye
2.90 arctic char, sockeye
1.31 sockeye
1.87 sockeye
3.15 sockeye
1.46 sockeye
4.73 arctic char, sockeye
Chinook, chum, coho, Dolly
1 7.49 Varden, pink, sockeye
5.60 Dolly Varden, sockeye
arctic char, Chinook, chum,
0.00 coho, pink, sockeye
Total anadromous streams crossed by road corridor:
Total
number of spawning salmon associated with stream crossings:
of vears counted)
7,021 (49)
84,933 (34)
1,052 (28)
1,342 (25)
1,649(32)
3,416(38)
NA
3,532(38)
10,882 (38)
8,015 (38)
4,469 (26)
1,144(35)
1,548 (41)
NA
4,259 (48)
2,263(17)

6,431 (38)
101,306(53)
9,128(46)
NA
15
252,390
' Stream names and codes are from the Anadromous Waters Catalog (AWC) or Morstad 2003.
8 Pers. comm. Steve Morstad 2011, methods in Morstad 2003.
47
-------
Appendix B (following two pages). Resident fish streams potentially affected, crossed
or closely approached by the potential Pebble Mine transportation corridor.
Compiled from the Alaska Freshwater Fish Inventory Database (Johnson and Blanche
201 la and 201 Ib, additional information provided by Buckwalter 2011, personal
communication).
48
-------
Stream No.
{ww* to east) Stream Name
1
2
3 Upp*r Tatar &k Creek
4
5
6
7
8
9
10
11
12 Newhaien Rivet
13
14
15
16
17
18
19
20 Roadbousc Creek
21 NW Cjgle 6*y Cr«tit
22
23
24
25
26 NE E^gle 8«y Creefc
27 Y-ftut^s Gfiwk, nwmrem
2S Yous^'s C*eek, east branch
29 Chekok Creek, west branch
30 the&£Qk Creek,, mai^stem
31 Canyon Cree^n
32
33
3-S
35
36
37
38
39
40
41
42
43
44
45
46
47
48 Knufs-on Creek
49
SO Pedro Greek
Si Russcan Geek
S2
S3
54
55
56
57 Pile Rsver
NHD Reach Code Stream of dec
19030206007351 first
19030206007)54 first
19Q30206GG?01$ fourth
190J02G6G07IS9 firs!
19030206007*75 fins?
19030205007587 4«»nd
19030205007593 second
19QJ020$(30?$9g 5«ond
19GJQ2QSG076Q6 second
19030205007602 second
19QJ02Q5G07615 SKond
190JQ2Q5QOQOQ2 fifth or higter
1903020501 3&b9 third
19Q302Q$G1JO$S second
19Q302QSG13057 first
190J020501J041 Mxond
190 J020601 0623 fir^t
190J020€»01062S ftfi£
19010206010629 ftrst
190302060W71? ftr^E
19QJ02060O&678 i«'0nd
190J02060O&677 firiS
190J0206tK^644 second
190J020600&671 second
190302060O6663 second
19G3Q2Q6Q06654 fin(
190M2060O&S98 thrtd
1903O206CK)6553 thifd
!90Ki2060C*S33 second
190J02060328S4 third
190M206CO63S9 third
19030206006336 fir^s
19030206005337 fim
1903O206QO6236 ftrsS
19030206006331 first
19030206006329 firs*
1903020600632? firs!
19QJ020&G0&325 ftnt
190302Q6C06322 fir^t
190J0206G06320 first
19030206006321 first
190i02060O631S fim
19030206006337 firs?
19Q3020SQO&35G fin?
190302060O&J15 firii
190i0206GO&3l'S first
190302060O62S1 firsE
190302060062SS fourth
190302Q6CQ628Q firsE
19030206QO6239 firs!
19G1G2060Q6248 first
19030206006231 firs?
19010206006230 first
39Q30206GQ&2.2S fir«
190KI2060O6227 first
190i0206Q06222 first
190J0206M0474 third
Resident fch
Ooliy Vardert, rainbow trout, skmv
scyipm
Oolfy Vardcn, ilimy vcuSpin
Arctk gf^'ng, Dolly Udrden, ninmpint?
ustcklebdck, rainbow trout, ilimy
sculp'fn, threespiine stickleback
coho salmon
Ooliy Varden, ninespine sttcicfebMk,
fiorthern pike, rainbow trout, slimy
SGu!pinr threespme stictkiebflck
furte'iptne $Hc*:l(?t?iKk. ^Eimy Ku^pin
Doll-y V,iJde«
Ooliy Vafde^
slimy icul-pie
slimy scuipin
Arctic graying, longnose iuck^r
Arctic RfaySing, hympback whitefi'sh,
longnovi; iuf^er, rjintKJw irwit, rounrf
whitefuh, s-cuipin
HQ data
No data
J*o data
Ho data
No d»1«
to dsta
^o data
5^imy scu^pift
Dolly Vwden
mtiesgirie 4ticil«ba'£k,j^rrry tculpin
Dolty Vafders
Ool^y Varde?i, einespine stickleback
Ooliy ViHdeiri, nine-spine sticMcback
Binespine sticfckback., rainbow trcMjt,
shmy wulpin
f^^f)t>ow UtHit, ilimy K'otpm
Dolty Vardsn, Miti&o* ?rout, slffjsy
sc«lpm
to data
fasnbcc* trout, slimy sculpin
Ooliy Vardee, slimy s-cuipini
m$zu
b$o data
r^o data
to data
to data
to data
to data
to d*u
to data
to data
to data
to data
to dirt a
to data
to data
to data
Dolfy Varden, s!imy scu^pin
CkilEy Uardefi, sEimy scuSpif*
to data
to data
to d3t»
to data
to sSAta
Ooliy Va*de*x, slimy KuSpis^
to data
slimy &c;ufpin, thre«spine stickleback
Anarffomous
fish
coho
coho
ChiAOD*:, ^hum,
coho, sockeye

arctic char,
ChiTvoc*, CO^o,
swkeye

arctic char,
IOC !«?¥«•

arctic char,
5
-------
Appendix B, second of two pages
Stream No.
(west to east} Stream Name
36
37
38
39
40
41
42
43
44
45
46
47
48 Knytson Creek
49
50 Pedro Creek
51 Russian Creek
52
53
54
55
56
57 Pile River
NHO Reach Code Stream order
19030206006329 first
19030206006327 first
19030206006325 first
19030206006322 first
19Q3Q206QG6320 first
19030206006321 first
19030206006318 first
19030206006317 first
19030206006316 first
19030206006315 first
19030206006314 first
19030206006251 first
190302060062S5 fourth
19030206006280 first
19030206006239 first
19030206006248 first
19030206006231 first
19030206006230 first
19030206006228 first
19030206006227 first
19030206006222 first
19030206000474 third
Resident fish
No data
No data
No data
No data
Ho data
Mo data
No data
No data
No data
No data
No data
No data
Dolly Varden, slimy sculpin
Doily Varden, slimy scoSpin
No data
No data
No data
No data
No data
Doily Varden, slimy scoSpin
No data
slimy sculpin, threespirse stickleback
Anadromous
fish In AWC?
N
N
N
N
N
N
N
N
N
N
N
N
arctic char,
sockeye Y
N
N
N
P4
N
sockeye Y
N
N
arctic char,
sockeye Y
19030206010632 first

59 liiamna River
60
61
62
63
64 Cfoinkelyes Creek
65
66
67
68

69 y-Valley Creek
70

19030206000033 fourth
19030206005773 first
19030206005761 second
19030206005759 first
19030206005754 second
19030206005737 second (at crossing)
19020602004863 first
19020602004864 first
19020602004865 first
19020602004866 first

19020602004867 second
19020602004882 first

Dolly Varden, slimy sculpin
No data
Dolly Varden, slimy scylpie
No data
No data
slimy sculpin
No data
No data
No data
No data

Dolly Varden
No fish recorded or observed.
Chinook, chum.
coho, Dolly
Varden, pink,
sockeye

arctic char.
Chinook, chum.
coho, pink.
sockeye

y
N
N
N
N
N
N
N
N
N

y
N
Stream names from the Alaska Freshwater Fish Inventory Database (ADFG 2011)
50
-------
Appendix H

Geologic and Environmental Characteristics of
Porphyry Copper Deposits with
Emphasis on Potential Future Development
in the Bristol Bay Watershed, Alaska
H-l
-------
2 USGS
science for a changing world
Geologic and Environmental Characteristics of Porphyry

Copper Deposits with Emphasis on Potential Future

Development in the Bristol Bay Watershed, Alaska
By Robert R. Seal, II
U.S. Department of the Interior
U.S. Geological Survey
-------
Geologic and Environmental Characteristics of Porphyry Copper Deposits -April 2012
Contents
Introduction 1
Geologic Characteristics of Porphyry Copper Deposits 2
Geologic Setting of the Bristol Bay Watershed 2
Mineral Resource Potential of the Nushagakand Kvichak Watersheds 2
General Characteristics of Porphyry Copper Deposits 4
Geologic Features: 4
Economic Characteristics: 5
Geology of Bristol Bay Porphyry Copper Deposits: 6
Mining and Beneficiation Considerations: 9
Environmental Characteristics of Porphyry Copper Deposits 10
Overview 10
Acid-Generating Potential 10
Waste Rock 13
Tailings 17
Copper Concentrate 22
Summary 24
References Cited 26
Figures
Figure 1. Generalized geologic map of the central part of the Bristol Bay watershed showing the general locations
of the Pebble, Humble, and Big Chunk prospects 3
Figure 2. Map showing location of Phanerozoic porphyry deposits with representative deposits labeled 5
11
-------
Geologic and Environmental Characteristics of Porphyry Copper Deposits -April 2012

Figure 3. Idealized cross section through a porphyry copper deposit showing the relationship of the ore zone to

various alteration types 6

Figure 4. Grade-tonnage characteristics of the Pebble deposit compared to other porphyry-type deposits 8

Figure 5. Plot of neutralizing potential (NP) and acid-generating potential (AP) for mineralized rock types at the

Bingham Canyon porphyry copper deposit, Utah 11

Figure 6. Plan view of the distribution of net-neutralization potential (NNP) values at the Bingham Canyon porphyry

copper deposit, Utah 12

Figure 7. Dissolved copper concentrations and water hardness values for various potential end-members waters

around the Pebble site in the Bristol Bay watershed associated with waste-rock piles 16

Figure 8. Dissolved copper concentrations and water hardness values for various potential end-members waters

around the Pebble site in the Bristol Bay watershed associated with a tailings impoundment 22

Tables

Table 1. Deposit types with significant resource potential for large scale mining in the Nushagak and Kvichak

watersheds 4

Table 2. Global grade and tonnage summary statistics for porphyry copper deposits (n = 256; Model 17, Singer

and others, 2008) compared to the Pebble deposit 7

Table 3. Annual consumption of copper, molybdenum and gold compared to the Pebble deposit 7

Table 4. Summary of geochemical results from humidity-cell tests on waste-rock samples conducted by the

Pebble Partnership (2011) 15

Table 5. Geochemical composition of porphyry copper tailing samples 18

Tables. Geochemical composition of test tailings samples from the Pebble deposit f 19

Table 7. Summary of geochemical results from humidity-cell tests on tailing samples and the supernatant solution

from metallurgical testing conducted by the Pebble Partnership 21

iii
-------
Geologic and Environmental Characteristics of Porphyry Copper Deposits -April 2012

Table 8. Geochemical analysis of the copper concentrate from the Aitik porphyry copper mine, Sweden 23

Table 9. Geochemical analyses of dissolved constituents in leachates from tailings and copper concentrate from

the Aitik Mine, Sweden 25
IV
-------
Geologic and Environmental Characteristics of Porphyry Copper Deposits -April 2012
Geologic and Environmental Characteristics of Porphyry

Copper Deposits with Emphasis on Potential Future

Development in the Bristol Bay Watershed, Alaska
By Robert R. Seal, II
US Geological Survey
954 National Center
12201 Sunrise Valley Drive
Reston,VA20192

Introduction

This report is prepared in cooperation with the Bristol Bay Watershed Assessment being conducted by the U.S.
Environmental Protection Agency. The goal of the assessment is to help understand how future large-scale
development in this watershed may affect water quality and the salmon fishery. Mining has been identified as a
potential source of future large scale development in the region, especially because of the advanced stage of
activity at the Pebble prospect. The goal of this report is to summarize the geologic and environmental
characteristics of porphyry copper deposits in general, largely on the basis of literature review. Data reported in the
Pebble Project Environmental Baseline Document, released by the Pebble Limited Partnership in 2011, are used to
enhance the relevance of this report to the Bristol Bay watershed.
The geologic characteristics of mineral deposits are paramount to determining their geochemical signatures in
the environment. The geologic characteristics of mineral deposits are reflected in the mineralogy of the
mineralization and alteration assemblages; geochemical associations of elements, including the commodities being
sought; the grade and tonnage of the deposit; the likely mining and ore-processing methods used; the
environmental attributes of the deposit, such as acid-generating and acid-neutralizing potentials of geologic
materials; and the susceptibility of the surrounding ecosystem to various stressors related to the deposit and its
mining, among other features (Seal and Hammarstrom, 2003). Within the Bristol Bay watershed, or more
specifically the Nushagak and Kvichak watersheds, the geologic setting is permissive for the occurrence of several
mineral deposit types that are amenable for large-scale development. Of these deposit types, porphyry copper
deposits (e.g., Pebble) and intrusion-related gold deposits (e.g., Shotgun) are the most important on the basis of
the current maturity of exploration activities by the mining industry. The Pebble deposit sits astride the drainage
divide between the Nushagak and Kvichak watersheds, whereas the Humble, Big Chunk, and Shotgun deposits
are within the Nushagak watershed. The Humble and Big Chunk prospects are geophysical anomalies that exhibit
some characteristics similar to those found at Pebble. Humble was drilled previously in 1958 and 1959 as an iron
prospect on the basis of an airborne magnetic anomaly. Humble is approximately 85 miles (137 km) west of
-------
Geologic and Environmental Characteristics of Porphyry Copper Deposits -April 2012

Pebble; Big Chunk is approximately 30 miles (48 km) north-northwest of Pebble; and Shotgun is approximately 110
miles (177 km) northwest of Pebble. The H and D Block prospects, west of Pebble, represent additional porphyry
copper exploration targets in the watershed.

Geologic Characteristics of Porphyry Copper Deposits

Geologic Setting of the Bristol Bay Watershed
The Nushagak and Kvichak watersheds are characterized by a complex geologic history. The history, going
back at least 100 million years, has been dominated by northward movement and subduction of the oceanic crust
beneath the Alaskan continental landmass, which continues today. The northward subduction of oceanic crust led
to the accretion of island land masses to the Alaskan mainland. The divide between the Nushagak and Kvichak
watersheds is near the geologic boundary between the Peninsular Terrane to the southeast and the Kahiltna
Terrane to the northwest (Decker and others, 1994; Nokleberg and others, 1994). The Peninsular Terrane consists
of Permian limestone, Triassic limestone, chert, and volcanic rocks, Jurassic volcanic and plutonic rocks, and
Jurassic to Cretaceous clastic sedimentary rocks.
The Pebble porphyry copper deposit and the Humble and Big Chunk prospects are located within the southern
Kahiltna Terrane (Fig. 1). The southern Kahiltna Terrane consists of a deformed sequence of Triassic to Jurassic
basalt, andesite, tuff, chert, and minor limestone of the Chilikadrotna Greenstone, which is overlain by the Jurassic
to Cretaceous Koksetna River sequence comprising turbiditic sandstones, siltstone, and shales (Wallace and
others, 1989). The area was intruded by Cretaceous to Tertiary plutons, which include those associated with the
Pebble deposit. The area also was partially covered by Tertiary to Quaternary volcanic rocks and varying
thicknesses of glacial deposits (Detterman and Reed, 1980; Bouley and others, 1995).
The underlying geology can exert a significant influence on water chemistry, and therefore the possible toxicity
of trace elements to aquatic organisms. The presence or absence of carbonate minerals and pyrite is the most
significant influences on water chemistry in terms of pH, hardness, and alkalinity. Carbonate minerals such as
calcite - the main constituent of limestone - can raise the pH and increase water hardness and alkalinity.
Limestone, dolomite, and siltstone with abundant calcareous concretions are the most common hosts of carbonate
minerals and are most abundant in Kvichak watershed in the vicinity of Lake Clark (Detterman and Reed, 1980;
Bouley and others, 1995). Pyrite, a potential source of acid, can be a minor constituent of turbiditic sediments such
those found in the Koksetna River sequence, northeast of Pebble. Hydrothermal activity associated with the
formation of mineral deposits, discussed below, also can introduce significant amounts of both pyrite and carbonate
minerals.

Mineral Resource Potential of the Nushagak and Kvichak Watersheds
The geologic setting of the Nushagak and Kvichak watersheds has characteristics that indicate that the region
is favorable for several different mineral-deposit types (Schmidt and others, 2007). These deposit types include
porphyry copper deposits, copper and iron skarn deposits, intrusion-related gold deposits, epithermal gold-silver
vein deposits, hot spring mercury deposits, placer gold deposits, and sand and gravel deposits (Table 1). Of these
deposit types, porphyry copper deposits and intrusion-related gold deposits are represented by prospects within the
area that could prompt large-scale development. Copper skarn deposits hold less potential, in the absence of
infrastructure from other mine development in the region, because of their typical smaller size (John and others,
2010). Significant exploration activity associated with porphyry copper deposits is currently being done at the
Pebble prospect, and to a lesser extent the Humble and Big Chunk prospects. Several other porphyry copper
prospects are immediately adjacent to Pebble, including the H Block and D Block prospects. Notable exploration
also is being done in the watershed at several gold properties including Shotgun, Kisa, and Bonanza Hills.
-------
,: * xS» T^onn
.A-^^ffl.a -M ^

-* • PebWe

*>>
OT»

•fcu I Tcm«>
Tnaak -U u. mtk>

^^1 VUV.

TTOC! \-rU
.[.. .. ^tebK MdiaMVUr* Rxi.»
nxi>
pMitu. nxli
MII«»M|*II n.ii
Figure 1. Generalized geologic map of the central part of the Bristol Bay watershed showing the general locations of the Pebble, Humble, and Big

Chunk prospects. Adapted from Wilson and others (2006). Map was made by Keith Labay (USGS).
-------
Geologic and Environmental Characteristics of Porphyry Copper Deposits -April 2012
The Pebble deposit is the most advanced among the mining prospects in the Bristol Bay watershed in terms of
exploration and preparation for the submission of mine permit applications. Therefore, the potential for large-scale
mining development within the watershed in the near future is greatest for porphyry copper deposits. Accordingly,
the remainder of the report will focus exclusively on this deposit type - porphyry copper deposits.

Table 1. Deposit types with significant resource potential for large-scale mining in the Nushagak and Kvichak
watersheds.
Deposit type
Porphyry copper

Intrusion-related gold

Copper(-iron-gold) skarn
Commodities Examples
References
Cu, Mo, Au, Pebble, Big Chunk, Schmidt and others (2007); Bouley
Ag Kijik River and others (1995)

Au, Ag Shotgun/Winchester. Schmidt and others (2007);
Kisa, Bonanza Hills Rombach and Newberry (2001)

Cu, Au, Fe Kasna Creek, Lake Schmidt and others (2007),
Clark Cu, Iliamna Newberry and others (1997)
Fe, Lake Clark
General Characteristics of Porphyry Copper Deposits

Geologic Features:
The geological characteristics of porphyry copper deposits recently have been reviewed by John and others
(2010), Sinclair (2007), and Seedorff and others (2005). Therefore, only salient features are summarized here.
Porphyry copper deposits are found around the world, most commonly in areas with active or ancient volcanism
(Fig. 2). The economic viability of porphyry copper deposits is dictated by the economy of scale - they typically are
low grade (average 0.44 % copper in 2008), large tonnage (typically hundreds of millions to billions of metric tonnes
of ore) deposits that are exploited by bulk mining techniques (John and others, 2010). Because of their large size,
their mine lives typically span decades.
Primary (hypogene) ore minerals found in porphyry copper deposits are structurally controlled and genetically
associated with felsic to intermediate composition, porphyritic intrusions that typically were emplaced at shallow
levels in the crust. Mineralization typically forms both within the associated intrusions and in the surrounding wall
rocks. The distribution of primary minerals is structurally controlled, filling veins, veinlets, stockworks and breccias.
Pyrite (FeS2) is typically the most abundant sulfide mineral. The main copper sulfide ore minerals are chalcopyrite
(CuFeS2) and bornite (CusFeS^. A number of other minor copper sulfide minerals are commonly found; most
notable from an environmental perspective is the arsenic-bearing mineral enargite (CusAsS^. Molybdenite (MoS2)
is the main molybdenum mineral. Gold in porphyry copper deposits can be associated in appreciable amounts with
bornite, chalcopyrite, and pyrite; the gold may occur as a trace element within these sulfide minerals or as
micrometer-scale grains of native gold (Kesler and others, 2002).
Hydrothermal mineralization events produce hydrothermal alteration haloes that are much larger than the
actual ore deposit. The classic alteration zonation includes a potassium feldspar-biotite rich core, surrounded by a
muscovite/illite sericitic (phyllic) alteration zone, which is surrounded by a clay-rich argillic alteration zone and finally
by a chlorite-epidote rich propylitic zone (Fig. 3; Lowell and Gilbert, 1970). The ore zones generally coincide with
the potassic and sericitic alteration zones. From an environmental perspective, the importance of these alteration
-------
Geologic and Environmental Characteristics of Porphyry Copper Deposits -April 2012

zones is that the sericitic and argillic alteration tends to destroy the acid-neutralizing potential of the rock, while
enhancing the acid-generating potential through the addition of pyrite. In contrast, the outer portion of the propylitic
zone tends to have enhanced acid-neutralizing potential due to the introduction of trace amounts of carbonate
minerals.
-60°N

Mt Policy /^*\
- Valley Copper '% ^
Yerington/Ann-Mason "5 «
— Resolution ~O~~
Morenci -•"
Cananea
,?__..?•-, ea^>
Far South East
Chuquicamata
La Escondida
El Salvador
Refugio-ro
ElTeniente -
Phanerozoic Igneous Provinces
Porphyry Deposit
-60°S
I
0 2,500 5,000
I I I120"WI
i 1
6°w
J L
I I
60"E
J L
120"E
60°S-
Figure 2. Map showing location of Phanerozoic porphyry deposits with representative deposits labeled.
Modified from Seedorff and others (2005) and John and others (2010).

Supergene (weathering) processes, which occur long after the initial hydrothermal mineralizing events, can
lead to zones of supergene enrichment near the tops of these deposits (John and others, 2010). The supergene
enrichment zones can be either oxide- or sulfide-dominated depending on the prevailing oxidation state at the site
of formation, the depth of the water table, and climate. Mined material from the oxide enrichment zone is amenable
to a heap-leaching method of ore processing known as "solvent-extraction - electrowinning" (SX-EW; Jergensen,
1999). However, supergene ores are likely to be minor in Alaska due to recent glaciation.
Porphyry copper deposits can be divided into three subtypes on the basis of Au (g/t)/Mo (%) ratios: porphyry
Cu, porphyry Cu-Mo, and porphyry Cu-Au deposits, where Cu-Au deposits have Au/Mo ratios greater than or equal
to 30, Cu-Mo deposits have Au/Mo ratios less than or equal to 3, and Cu deposits are all other deposits not within
these bounds (Sinclair, 2007; Singer and others, 2008). On the basis of these criteria, the Pebble deposit would be
classified as a porphyry Cu deposit.

Economic Characteristics:
Porphyry copper deposits are important sources of copper, molybdenum, gold, and silver; they also can supply
significant amounts of byproduct rhenium, tellurium, and platinum group elements. Porphyry copper deposits
supply over 60 percent of the copper for global copper production and together with porphyry molybdenum
deposits, account for over 95 percent of the molybdenum production (Sinclair, 2007; John and others, 2010). In
2010, the United States consumed 1,730,000 tonnes of copper, of which 30 percent was imported, chiefly from
Chile, Canada, and Peru. In the same year, the United States consumed 48,000 tonnes of molybdenum, and was
a net exporter. In 2010, the United States consumed 380 tonnes of gold of which 33 percent was imported,
-------
Geologic and Environmental Characteristics of Porphyry Copper Deposits -April 2012

primarily from Canada, Mexico, Peru, and Chile. These commodities serve myriad uses (U.S. Geological Survey,
2011). Copper is used primarily in building construction (wiring and pipes; 49 %), electric and electronic products
(20 %), vehicles (12 %), consumer products (10 %), and industrial machinery and equipment (9 %). Molybdenum
is primarily used as a steel alloy (75 %). Gold is used mainly for jewelry (69 %), and electrical and electronic
products (9 %). Silver is used for a variety of applications including industrial and medical uses, electronics, coins
and silverware, and photography (albeit a declining application). Rhenium is principally used as an alloy in turbine
engines (70 %) and for petroleum refining (20 %). Tellurium is primarily used as an alloy with steel, iron, and lead,
but increasingly is being used in solar cells. Platinum-groups metals (platinum, palladium, rhodium, ruthenium,
iridium, and osmium) principally are used in vehicle catalytic converters, as catalysts for chemical manufacturing, in
electronics and in emerging applications to fuel cells.
ADVANCED
ARGILLIC
Q-Kaol-Alun
PERIPHERAL
cp-gal-sl-Au-Ag
PYRITE SHELL
\ py10%
V,cp.01-3%
s\

\
ORE
^^-T- SHELL
-""" py1%
cp 1-3%
mb .003%
1
i

EXPLANATION:
Chi - Chlorite
Epi - Epidote
Garb - Carbonate
Q - Quartz
Ser - Sericite
K-feld - Potassium
Feldspar
Bi - Biotile
Anh - Anhydrite
py - pyritc

Kaol - Kaolinite
Alun - Alunite
cp - Copper
gal - Galena
si - Sulfide
Au - Gold
Ag - Silver
mb- molybdenite

mag
py
A Chl-Ser-Epi-mag
Figure 3. Idealized cross section through a porphyry copper deposit showing the relationship of the ore zone to
various alteration types. A. Distribution of alteration types; B. Distribution of ore mineral assemblages. The
causative intrusion corresponds to the potassic alteration zone. From John and others (2010) and modified from
Lowell and Guilbert (1970).

The grade and tonnage of porphyry copper deposits vary widely (Singer and others, 2008). Summary statistics
compiled for 256 porphyry copper deposits are presented in Table 2, and in Figure 4. For total tonnage of ore,
Pebble is in the upper 5th percentile, lower 50th percentile for copper grade, upper 10th percentile for molybdenum
grade, and upper 10th percentile for gold grade. The amount of metal contained in the Pebble deposit corresponds
to a 21 -year supply of copper for the United States, a 53-year supply of molybdenum, and a 9-year supply of gold,
based on 2010 consumption statistics (Table 3). From the perspective of future discoveries in the watershed, it is
therefore highly unlikely that new deposits will approach the size of Pebble, but instead will be considerably
smaller.

Geology of Bristol Bay Porphyry Copper Deposits:
Several porphyry copper prospects within the Bristol Bay watershed are being explored, and include Pebble,
Humble, and Big Chunk. The Pebble deposit is the only one with a significant published description of its geology
(Bouley and others, 1995; Kelley and others, 2010). The deposit is controlled by the Pebble Limited Partnership -
a joint venture between Northern Dynasty Minerals, Ltd., and Anglo American. The Pebble deposit may be viewed
-------
Geologic and Environmental Characteristics of Porphyry Copper Deposits -April 2012

as consisting of two contiguous ore bodies: Pebble West and Pebble East, with the buried Pebble East having the
higher ore grades. Pebble West was discovered in 1989 at the surface, and delineation drilling in 2005 resulted in
discovery of Pebble East beneath a 300 to 600 m thick cover of Tertiary volcanic rocks. The deposit has been
explored extensively with more than 1,150 drill holes that total greater than 949,000 feet (289,250 m) (Northern
Dynasty Minerals, 2011).

Table 2. Global grade and tonnage summary statistics for porphyry copper deposits (n = 256; Model 17, Singer
and others, 2008) compared to the Pebble deposit.
Parameter
Tonnage (Mt)
Cu grade (%)
Mo grade (%)
Ag grade (g/t)
Au grade (g/t)
10thPercentile
1,400
0.73
0.023
3.0
0.20
50th Percentile
250
0.44
0.004
0.0
0.0
90th Percentile
30
0.26
0.0
0.0
0.0
Pebble1
10,777
0.34
0.023
unknown
0.31
Sources: 1PLP (0.3 % Cu cut-off grade), includes measured, indicated, and inferred resources (http://www.pebblepartnership.com/)
Table 3. Annual consumption of copper, molybdenum and gold compared to the Pebble deposit.
Commodity
Copper (tonnes)
Molybdenum (tonnes)
Gold (tonnes)
US Annual Consumption (201 0)1
1,730,000
48,000
380
Pebble Resource2
36,636,364
2,531,818
3,337
Years of 2010
Consumption
21
53
9
Sources: 1U.S. Geological Survey (2011); 2PLP (0.3 % Cu cut-off grade), includes measured, indicated, and inferred resources
(http://www.pebblepartnership.com/}

The oldest rocks in the vicinity of the deposit are Jurassic to Cretaceous (ca. 150 Ma) clastic sedimentary rocks
(i.e., mudstone, siltstone, and sandstone), which were intruded by dominantly granitic plutons from 100 to 90 Ma;
granodiorite stocks and sills, spatially and genetically related to the Cu-Au-Mo mineralization, were intruded about
90 Ma (Kelley and others, 2010). Intrusion of these granodiorite bodies resulted in hydrothermal activity that
produced the mineralization and associated alteration of the intrusions and surrounding rocks. The Pebble West
deposit extends from the surface to a depth of about 500 m and encompasses roughly 6 square kilometers on the
surface. Pebble East is covered by a wedge of post-mineralization Tertiary volcanic rocks that exceeds 600 m in
thickness towards the east. The eastern end of the deposit is truncated by a high-angle fault that offsets the
deposit 600 to 900 m down to the east (Kelley and others, 2010). Early copper mineralization was dominated by
pyrite, chalcopyrite, and gold, which was overprinted by pyrite, bornite, digenite, covellite, and minor enargite,
followed by quartz-molybdenite veinlets (Bouley and others, 1995; Kelley and others, 2010).
Geologic information on the Humble prospect (previously known as Kemuk) is limited to the details found on
the Millrock Resources, Inc. website (http://www.millrockresources.com/projects/huinble/). The prospect is covered
by glacio-fluvial gravels and sands 30 to greater than 140 m thick. The site was identified on the basis of the
presence of an airborne geophysical (magnetic) anomaly and the presence of igneous rocks similar to those found
at Pebble. The Humble Oil Company drilled the property in 1958 and 1959 as an iron prospect. No mention is
made of Cu-Au-Mo mineralization from the 1950s drilling, and there are no recent data available. Information on
the Big Chunk Super project is limited to details on the Liberty Start Uranium and Metals Corporation website
-------
Geologic and Environmental Characteristics of Porphyry Copper Deposits -April 2012
(http://www.libertystaruranium.com/www/projects/big-chunk-super-project). Current exploration efforts are focused
on six to seven airborne electromagnetic geophysical anomalies from data collected in 2009 that are consistent
with porphyry-style mineralization. Although exploratory drilling is mentioned on the web site, no results are
discussed.
10.0
_ 1-0
ZJ
o
0.1
0.01
1.0
0.1
0.01
0.001
. - . 'j, Highland \
''.," Island''-., ValleV
Copper «,
• \
10 100 1,000 10.000 100.000
Tonnage (106t)
0.0001
'Cu
• CU-MO
i Cu-Au
\
'Island
Copper
'%, \ CS
X
"i
Bingham El Teniente
• "\ V?
• \ Chuquicamata

\ >
\
1 10 100 1.000 10,000 100,000
Tonnage (1Q6t)
10.0
^ 1-°
3
^

0.1
0.01
i Cu
• Cu-Mo
i Cu-Au
•v. v •»•«.. .
W-*
" "
\

\ \
Grasberg \
, 7 Binsham Pebble''-?-
\ Island
''-Copped
•\
\ "Hucklebeny"'. ,
v. *•&.
10 100 1.000 10,000 100,000
Tonnage (106t)
Figure 4. Grade-tonnage characteristics of the Pebble deposit compared to other porphyry-type deposits. A.
Copper; B. Molybdenum; C. Gold. The Pebble deposit is shown as the yellow star. Selected, noteworthy
deposits are labeled. Pebble is classified as a porphyry Cu deposit (red squares). The dashed diagonal lines
represent the total contained metal. Modified from Sinclair (2007).
-------
Geologic and Environmental Characteristics of Porphyry Copper Deposits -April 2012

Mining and Beneficiation Considerations:
Mining and ore-processing methods can vary based on whether or not parts of the ore are weathered, and on
the commodities being extracted. Due to their large size and low grades, porphyry copper deposits are mined by
bulk mining methods such as open-pit mining for deposits near the surface, and block caving for deposits at depth.
Because the copper ore grades are generally less than 2 percent, greater than 98 percent of the material mined
ends up as waste. The beneficiation of the ore is distinctly different between hypogene (primary) sulfide ores and
supergene (secondary) oxide ores. Mining begins with the removal of waste rock, which may or may not be acid-
generating. Country rocks that host the mineralization are commonly acid-generating due to the presence of
hydrothermal pyrite formed during the mineralizing event. These rocks may be classified as subeconomic ore and
may be stockpiled separately from barren waste rock. The processing of subeconomic ore commonly is prompted
by either an increase in metal prices making the material economically viable, or if a high-grade zone is
encountered during mining, the subeconomic ore may be mixed with high-grade ore to ensure that an appropriate
grade of material is being fed to the mill. In either case, subeconomic ore generally is handled in a similar fashion
to that of waste rock during mine operations because of its acid-generating potential.
The primary (hypogene) sulfide ore is crushed to sand or silt size prior to ore concentrate separation using the
froth flotation method (Fuerstenau and others, 2007). For porphyry copper deposits, such as Pebble, separate
concentrates for copper and molybdenum generally are produced. The gold in porphyry copper deposits can be
partitioned variably among the copper-sulfide minerals (chalcopyrite, bornite, chalcocite, digenite, and covellite),
pyrite, and free gold (Kesler and others, 2002). Gold associated with the copper minerals remains with the copper
concentrate and is recovered at an off-site smelter. Gold associated with pyrite will end up in the tailings, unless a
separate pyrite concentrate is produced. Pyrite concentrates can be produced during the froth flotation process for
the recovery of gold or to more effectively manage the high acid-generating potential of this material. Gold
commonly is recovered by cyanidation, but gold recovery from sulfide-rich material is poor (Marsden and House,
2006). To improve gold recovery, pyritic material typically is oxidized by various means including high-temperature
(pyrometallurgical) roasting; low-temperature, pressurized autoclaving; or bio-oxidation using bacteria. Following
oxidation, the material then is leached with cyanide, typically in a vat to recover gold (Marsden and House, 2006).
The resulting spent iron oxides generally are disposed with the tailings. Autoclaving is probably the most likely
option in southwest Alaska because cyanide can be managed effectively in a vat-leaching operation. High-
temperature roasting is energy intensive and presents additional challenges with respect to stack emissions.
Bioleaching may be more difficult because of the cold climate and slow biotic oxidation rates at lower temperatures.
Tellurium generally is recovered from the copper anode slimes at the refinery (John and others, 2010).
Rhenium is recovered as a byproduct of the roasting of the molybdenum concentrate at the refinery (U.S.
Geological Survey, 2011). The platinum-group metals generally are associated with copper concentrates (Tarkian
and Stribrny, 1999) and thus, would not be recovered on site at Pebble. Thus, the recovery of tellurium and
platinum-group elements from Pebble or other porphyry copper deposits in the watershed would likely be an activity
conducted off-site when ore concentrates are further processed.
Supergene (secondary) oxide ores commonly are beneficiated using a heap-leach method known as solvent
extraction-electrowinning (SX-EW). This process involves placing coarsely crushed ore on a lined pad and
applying sulfuric acid to leach copper from the ore. The pregnant leach solution is collected and the copper is
removed from the leachate electrolytically (Jergensen, 1999). The supergene enrichment zone at Pebble is poorly
developed and dominated by the secondary copper sulfide minerals covellite (CuS), digenite (Cui-xS), and
chalcocite (Cu2S), in part due to recent glaciation (Bouley and others, 1995). Therefore, processing of oxide ore is
unlikely at Pebble or geologically similar deposits within the watershed.
-------
Geologic and Environmental Characteristics of Porphyry Copper Deposits -April 2012

Environmental Characteristics of Porphyry Copper Deposits

Overview
Porphyry copper deposits can pose geochemical risks to aquatic and terrestrial ecosystems, and to human
health. The risks can range from nil to significant and depend upon a variety of factors. Factors that influence the
environmental characteristics of mineral deposits range from geologic setting (both local and regional), hydrologic
setting, climatic settings, and mining methods, to ore beneficiation methods. The sources of the risk can be
considered in the broad categories of acid-generating potential, trace element associations, mining and ore
beneficiation methods, and waste disposal practices. The significance of these sources of risk will vary from
deposit to deposit, but some generalizations can be made for porphyry copper deposits as a whole.

Acid-Generating Potential
Acid generation can be considered a "master variable" for aqueous risks. Metals and other cations are more
soluble at low pH as compared to neutral or high pH. Therefore, the acid-generating or acid-neutralizing potentials
of the waste rock, tailings, and mine walls are of prime importance in identifying the potential environmental risks
associated with mining and ore beneficiation.
The acid-generating or acid-neutralizing character of a rock or mine waste material is evaluated in terms of an
"acid-base account". Acid-base accounting uses static tests to assess maximum acid-generating potential. Static
tests are based on a single analysis of waste material and therefore are independent of rates of reactions. In
contrast to static tests, kinetic tests expose mine waste samples for weeks, months, or years. Most proposed
mining projects take a staged approach to evaluating acid-generating potential starting with acid-base accounting
data to screen numerous samples, which are followed by the more laborious kinetic testing process on fewer,
carefully selected samples.
The acid-generating potential of rocks and mine waste samples can be evaluated using a variety of techniques
(Price, 2009; INAP, 2011). In North America, one of the most common techniques investigates the difference or
ratio of the acid-generating and acid-neutralizing potential of the sample. Theoretically, a sample with an acid-
neutralizing potential (NP) equal to its acid-generating potential (AP) is "net neutral", meaning that its acid-
neutralizing potential (NP) should theoretically cancel (or neutralize) its acid-generating potential (AP).
Numerically, this is expressed as a "net neutralizing potential" (NNP) of zero, where

NNP = NP-AP

Values for AP, NP, and NNP are typically expressed in the units of kilograms of calcium carbonate per tonne of
waste material (kg CaCOs/t), such that the amount of calcium carbonate amendment that would be needed to
achieve "net neutrality" is readily apparent. The AP values are generally based on an analysis of the sulfide-sulfur
content of the sample, and the NP values are based on either an analysis of the carbonate content of the sample or
by leaching of the sample followed by a wet chemical titration of the resulting leachate. NNP values that are
greater than zero are "net alkaline" and those below zero are "net acidic". Alternatively, the acid-base account of a
sample also can be expressed in terms of its neutralizing potential ratio (NPR), which is simply the ratio of its NP to
itsAP:

NPR= NP/AP

Thus, a sample with a NPR equal to one is net neutral, greater than one is net alkaline, and less than one is net
acidic. Current industry standards generally divide rocks and mine waste samples into three distinct categories
based on the NPR values: potentially acidic drainage generating (PAG) for NPR less than 1; uncertain (possibly)
10
-------
Geologic and Environmental Characteristics of Porphyry Copper Deposits -April 2012

acidic drainage generating for NPR between 1 and 2; and non-potentially acidic drainage generating (non-
PAG)(INAP, 2011). Note that the requirement that non-PAG material have a NPR value greater than 2 represents
twice the amount of alkalinity needed for net neutrality under equilibrium conditions. In practice, kinetic
considerations are important, which is why a NPR greater than 2 is desirable.
The rocks associated with porphyry copper deposits, in general, tend to straddle the boundary between being
"net acidic" and "net alkaline". This aspect is illustrated well by the study of Borden (2003) on the Bingham porphyry
copper deposit in Utah (Figures 5 and 6), which shares many similar geologic features with the Pebble deposit.
The AP values for porphyry copper deposits approximately reflect the distribution of pyrite. The distribution of acid-
generating and non-acid-generating material in plan view at the Bingham mine matches well with the idealized
cross section of porphyry copper deposits shown in Figure 3B. The pyrite-poor, low-grade core corresponds to the
central part of the Bingham Canyon deposit where NNP values are greater than 0. The progression out to the ore
shell and pyrite shell with their increasing abundance of pyrite in these areas is reflected in the progressively more
negative NNP values.
1,000
5
f
10
Uncertain
non-PAG
PAG

.<*
++
'
I MM -If—I—H-
10 100
AP (kg CaCCyt)
1,000
Figure 5. Plot of neutralizing potential (NP) and acid-generating potential (AP) for mineralized rock types at the
Bingham Canyon porphyry copper deposit, Utah. Modified from Borden (2003).

During mining of porphyry copper deposits, a variety of materials with differing NNP values may be
encountered. The low NNP, largely barren pyrite shell likely represents waste rock that may need to be removed to
access the ore (Fig. 3B). The boundary between the ore shell and the pyrite shell is cryptic and typically is defined
operationally on the basis of a cut-off copper grade. Therefore, some of the "waste" material with significant,
subeconomic copper grades could be stockpiled for potential future beneficiation. The intrusions that produce
11
-------
Geologic and Environmental Characteristics of Porphyry Copper Deposits -April 2012

porphyry copper deposits can intrude any rock type. Therefore, the NNP values of the country rock of
undiscovered deposits cannot be predicted reliably. Likewise, geologic events following ore formation could
juxtapose a variety of rock types against an ore deposit, which can have a range of NNP values. In the case of
Pebble, subsequent volcanic activity after mineralization covered the eastern part of the deposit with material that
lacks acid-generating potential (Kelley and others, 2010; Pebble Partnership, 2011).
NNP(kgCaCO3/t)

Q^| Oto-25
| | -2510-50
^H <-50
500 m
Figure 6. Plan view of the distribution of net neutralizinig potential (NNP) values at the Bingham Canyon
porphyry copper deposit, Utah. NNP values above zero are "net alkaline"; those below zero are "net acid".
Modified from Borden (2003).
The mining method will influence the amount of waste rock removed. Open pit mining can require the removal
of large volumes of potentially acid-generating material. A waste-to-ore ratio of 2:1, meaning that two tonnes of
waste are removed for each tonne of ore, is not uncommon for porphyry copper deposits (Porter and Bleiwas,
2003). Underground block caving of ore requires that a shaft or decline be sunk to facilitate mining. The amount of
waste rock removed for block caving is much less than that removed in a typical open pit operation. In the specific
case of Pebble, the volcanic rocks overlaying Pebble East are devoid of pyrite and are generally classified as non-
PAG material, which would not require special handling to mitigate acidic drainage (Pebble Partnership, 2011). In
fact, this material could be used for a variety of construction projects on site (e.g., road fill, tailings dam
construction). In contrast, the pre-Tertiary rocks at Pebble are generally classified as PAG, with some samples
having uncertain potential for generating acid and fewer with no potential for generating acid (non-PAG). During
mining, some of this rock will be waste rock removed to access the ore, and some of it will be ore that will be
processed to extract mineral concentrates.
The most profound influence that beneficiation of ore can have on mine tailings derived from froth flotation
centers on the fate of pyrite (Fuerstenau and others, 2007). At many porphyry copper mines, the pyrite is
discharged with the waste tailings, thereby contributing to the acid-generating potential of the tailings. However,
12
-------
Geologic and Environmental Characteristics of Porphyry Copper Deposits -April 2012

the option exists to produce a pyrite concentrate to manage more effectively the acid-generation risks associated
with tailings, to extract gold associated with the pyrite, or both. The production of a pyrite concentrate will decrease
the acid-generating potential of the tailings.

Waste Rock
Waste rock associated with porphyry copper deposits reflects the geologic history of the deposit. Because
porphyry copper deposits are associated with igneous rocks intruded into shallow levels of the Earth's crust, the
geochemical properties of the country rocks can vary widely, particularly in terms of their acid-base accounting
properties and their trace element compositions. The hydrothermal activity that forms the ore deposits introduces
sulfur, which commonly forms sulfide minerals such as pyrite, and a variety of trace elements. Introduced sulfur
may also occur as the sulfate minerals anhydrite (CaS04), or barite (BaSCU), which are environmentally benign
with respect to acid-generating potential. In fact, for acid-base accounting, the portion of sulfur that occurs as
sulfate should be subtracted from the total amount of sulfur present to accurately estimate acid-generating potential
(Price, 2009). The hydrothermal alteration haloes around these deposits are significantly more extensive than the
ores themselves (Fig. 3) and commonly represent waste rock with significant associated environmental risks.
Rocks that form after the mineralization event, and not affected by supergene processes, are devoid of these
hydrothermal overprints of sulfur and trace elements.
An early step in mining is to remove the waste rock to access the ore. For open pit mines, waste to ore
(stripping) ratios commonly can exceed 2:1 (Porter and Bleiwas, 2003). As discussed in the previous section, the
acid-generating potential of the waste rock can span the range from potentially acid-drainage generating (PAG) to
non-PAG. The ability of leachate generated from waste rock to mobilize metals and oxyanions will vary, depending
in part, on the pH of the resulting solution, which largely is a function of the pyrite content of the waste rock.
The primary environmental risk associated with waste rock is through the oxidation of waste-rock material,
which may result in contamination of either groundwater or surface water. The oxidation of sulfide minerals such
as pyrite produce sulfuric acid, which then can dissolve metals and related elements from associated sulfide,
silicate, and carbonate minerals. The magnitude of this risk will depend upon waste management practices and
whether or not drainage is treated.
The geochemical characteristics of waste-rock dump drainage have been investigated by several studies. Day
and Rees (2006) conducted a study of dump seepage associated with several operating or recently closed
porphyry copper and porphyry molybdenum mines in British Columbia, many of which are located in the Fraser
River watershed. Porphyry copper mines included in their study were Gibraltar, Huckleberry, Island Copper, and
Mount Polley; the data from Huckleberry were from laboratory column tests only. These deposits fell into two
groups: those that produced low pH drainage and those that did not. The pH of waste-dump drainage from
Gibraltar and Huckleberry ranged from neutral down to approximately 2, whereas drainage from Island Copper only
reached a low of approximately 4.5. In contrast, the pH of waste-rock drainage at Mount Polley ranged between 7
and 8.5. The concentrations of sulfate and metals were negatively correlated with pH. The maximum
concentrations of sulfate (<30,000 mg/L), Al (< 1,000 mg/L), Mn (< 100 mg/L), and Cu (< 1,000 mg/L) were all
highest from Gibraltar; the highest concentrations of Zn (< 100 mg/L) were found in the Huckleberry column tests
(Day and Rees, 2006). For comparison, Lister and others (1993) found that 41 percent of the NPR values for
waste rock at Island Copper were below 1, 23 percent were between 1 and 3, and 36 percent were above 3, which
is consistent with the range of pH values, from 4.5 to 8, observed by Day and Rees (2003). Khorasanipour and
others (2011) found similar geochemical trends, but in a more arid environment, for drainage associated with
waste-rock dumps at the Sarcheshmeh mine in southeastern Iran. The pH ranged between 3.1 and 6.3, specific
conductance between 0.72 and 2.25 mS/cm, sulfate between 365 and 1,590 g/L, Al between < 0.05 and 60 mg/L,
Mn between 14.6 and 95.8 mg/L, Cu between 2.15 and 70 mg/L, and Zn between 2.4 and 27.4 mg/L.
13
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Geologic and Environmental Characteristics of Porphyry Copper Deposits -April 2012

In the vicinity of the proposed Pebble mine, the best insights into the potential behavior of waste rock come
from the humidity-cell tests being conducted by the Pebble Limited Partnership, and its contractors (Pebble
Partnership, 2011). Management of waste rock during mine operation typically involves placing waste rock in
subaerial piles on site. This configuration is similar to the conditions of humidity-cell tests where samples are
exposed to a weathering protocol under unsaturated conditions (Price, 2009). Standard procedures require that
rock be crushed to less than 6 mm, placed in cylinders, cycled through moist and dry air for six days, and leached
on the seventh day, all at room temperature. This requirement produces a material that has significantly more
surface area than waste rock produced during mining, which makes the test material more reactive than the actual
material. As such, this approach does not incorporate the temperature and precipitation variations encountered on
site, or the heterogeneous grain size of typical waste rock. "Barrel" kinetic tests were conducted also, where rather
than weathering samples in the laboratory, larger volumes of material were placed in barrels in the field and the
samples were exposed to site conditions. The goal of barrel testing is to scale-up laboratory results to conditions
that are more representative of the site in terms of amount and seasonality of precipitation and temperature
variations. The barrel test results are not discussed in this report. However, despite these caveats, the humidity-
cell results presented by the Pebble Partnership (2011) provide relevant information.
Pebble Partnership (2011) has divided material at the site into several different groups, for both Pebble West
and Pebble East: pre-Tertiary sedimentary and volcano-sedimentary units, Pre-Tertiary plutonic units, and Tertiary
volcanic units. In general, results from the pre-Tertiary rocks from Pebble West and Pebble East were not
significantly different. The pre-Tertiary rocks were present at the time of mineralization and therefore have the
potential to be significantly mineralized. The Tertiary volcanic rocks were deposited after mineralization, and
therefore should be lacking sulfide minerals as a source of acidity and metals.
The results of the Pebble Partnership (2011) humidity-cell tests are summarized in Table 4. Table 4 presents
the mean composition of leachate from these tests divided into three groups: Tertiary rocks, hydrothermally altered
pre-Tertiary rocks (undifferentiated) from Pebble West, and hydrothermally altered pre-Tertiary rocks
(undifferentiated) from Pebble East. The results from the variety of pre-Tertiary rock types were grouped together
here with the assumption that individual waste-rock types would not be selectively removed during mining. The
concentration of constituents in the leachate was calculated from the average release rate data presented by the
Pebble Partnership using the formula:

Concentration (mg/L) = [Release (mg/kg/week) x Mass of Sample (kg)]/Leachate Recovered (L),

where the average release rate, the mass of the solid sample, and amount of leachate recovered are provided in
the Pebble Partnership (2011) report. The results from Pebble include a number of parameters (Pebble
Partnership, 2011): pH, conductivity, acidity, alkalinity, total dissolved solids, hardness, F, Cl, SCU, Al, Sb, As, Ba,
Be, Bi, B, Cd, Ca, Cr, Co, Cu, Fe, Pb, Mg, Mn, Hg, Mo, Ni, K, Se, Si02, Ag, Na, Tl, Sn, V, and Zn. The present
discussion focuses on pH, sulfate, Cu, Mo, As, and Zn. The pH of a solution is a master variable that controls the
solubility of most elements. Sulfate is a proxy for pyrite oxidation, which produces the acid in acid-mine drainage.
Copper is a cationic species, and the most likely inorganic ecologic stressor expected at the site, especially for
aquatic organisms. Zinc commonly occurs in base-metal hydrothermal systems, but typically not in economic
concentrations in porphyry copper deposits. Arsenic and molybdenum are oxyanion species; arsenic is a
potentially significant stressor, especially with respect to drinking water contamination, whereas molybdenum is an
important ore constituent with less potential to be an environmental stressor.
14
-------
Geologic and Environmental Characteristics of Porphyry Copper Deposits -April 2012

Table 4. Summary of geochemical results from humidity-cell tests on waste-rock samples conducted by the Pebble
Partnership (2011).
Parameter

Pebble
Partnership
(2011) Source
PH
Alkalinity
Hardness
Cl
F
S04
Ag
Al
As
B
Ba
Be
Bi
Ca
Cd
Co
Cr
Cu
Fe
Hg
K
Mg
Mn
Mo
Na
Ni
Pb
Sb
Se
Sn
Tl
V
Zn
Units

S.U.
mg/L CaCOs
mg/L CaCOs
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
Tertiary Waste Rock
Mean

Table 11 -31
(calc);
Appendix
11C(pH)
7.2
65.9
74.0
0.53
0.06
28.0
0.000011
0.08
0.0027
0.0177
0.0572
0.0003
0.0005
21.3
0.0002
0.0039
0.0006
0.0032
0.140
0.000010
1.85
5.06
0.1015
0.0063
7.21
0.0044
0.0001
0.0021
0.0019
0.0013
0.00007
0.0018
0.0159
Standard
Deviation
Table 11 -31
(calc);
Appendix 1 1C
(PH)
1.3
51.0
88.1
0.11
0.09
83.8
0.000003
0.21
0.0042
0.0122
0.0824
0.0005
0.0002
31.6
0.0006
0.0157
0.0002
0.0061
0.484
0.000001
2.24
7.49
0.3990
0.0138
12.46
0.0165
0.0002
0.0019
0.0020
0.0015
0.00003
0.0022
0.0500
Pebble West Pre-Tertiary
Waste Rock
Mean

Table 11 -21
(calc);
Appendix 1 1C
(PH)
6.6
18.5
59.2
0.52
0.12
60.8
0.000027
0.32
0.0015
0.0159
0.0136
0.0003
0.0007
12.7
0.0004
0.0070
0.0007
1.5989
1.671
0.000011
1.41
6.69
0.7289
0.0018
2.05
0.0068
0.0002
0.0031
0.0038
0.0001
0.00041
0.0007
0.0556
Standard
Deviation
Table 11 -21
(calc);
Appendix 1 1C
(PH)
1.7
16.4
51.9
0.01
0.12
68.4
0.000044
0.85
0.0018
0.0085
0.0087
0.0003
0.0004
8.9
0.0007
0.0146
0.0004
3.2469
6.042
0.000002
0.72
8.68
1.5653
0.0018
0.03
0.0143
0.0003
0.0018
0.0057
0.0001
0.00098
0.0004
0.1080
Pebble East Pre-Tertiary Waste
Rock
Mean

Table 11 -21
(calc);
Appendix 1 1C
(PH)
4.8
9.9
21.9
0.91
0.11
51.9
0.000019
0.38
0.0080
0.0125
0.0045
0.0006
0.0006
6.3
0.0032
0.0097
0.0016
1.4162
10.195
0.000010
0.96
1.50
0.3386
0.0043
2.07
0.0105
0.0004
0.0008
0.0032
0.0019
0.00009
0.0024
0.4786
Standard
Deviation
Table 11 -21
(calc);
Appendix 1 1C
(PH)
1.9
14.1
23.1
0.91
0.16
52.0
0.000013
0.58
0.0189
0.0052
0.0056
0.0006
0.0003
5.3
0.0083
0.0120
0.0023
2.1609
16.051
0.000001
0.69
3.40
1.0745
0.0070
0.06
0.0168
0.0004
0.0018
0.0024
0.0022
0.00010
0.0056
1.3618
15
-------
Geologic and Environmental Characteristics of Porphyry Copper Deposits -April 2012
The pre-Tertiary rocks show a range of responses in the humidity-cell tests as reflected by the significant
standard deviations associated with their mean leachate concentrations (Table 4). The leachates from the pre-
Tertiary rocks are characterized by neutral to acidic pH values. As expected from the role of pyrite oxidation in acid
generation, the samples that generated the lowest pH values had the higher sulfate concentrations and lower
alkalinity values. For example, the mean pH for humidity-cell leachates for Pebble East was 4.8 ± 1.9 compared to
6.6 ± 1.7 for Pebble West, presumably reflecting the higher grade and pyrite content of Pebble East. The pH of the
samples correlated negatively with the alkalinity of the leachates. Copper concentrations generally correlate with
sulfate concentrations and low pH, as would be expected from the higher solubility of metals with acidic pH
conditions. The mean concentrations of copper in humidity-cell leachates from both Pebble West and Pebble East
were high compared to other metals and exceeded 1 mg/L. The mean zinc concentration reached 0.5 mg/L. In
contrast, the highest mean molybdenum concentration was less than 0.005 mg/L and the highest mean arsenic
concentration was 0.008 mg/L. The high standard deviations associated with all parameters in the leachate
chemistry from pre-Tertiary waste-rock types underscore the challenges associated with predicting waste-rock
seepage chemistry with a high level of confidence. At an operating mine, the drainage from waste-rock piles will be
a mixture of direct leachates from the waste rock and local ambient surface water and precipitation. The relative
proportion of these sources will depend upon local climatic conditions, the natural topography, alterations to the
natural topography made during mine construction, and engineering controls put in place during mine construction
to manage surface water. The range of potential compositions of seepage is shown in Figure 7.
100000
10000 i
CUO
Q.
O
QJ

~0
to
to
1000 -.
100 -.
10 -.
1 i
0.1
PEZ
HCT
PWZ
Barrel
pre-Tertiary Waste
Rock
North Fork Koktuli
River
10 100 1000

Hardness mg/L CaC03
10000
Figure 7. Dissolved copper concentrations and water hardness values for various potential end-member waters
around the Pebble site in the Bristol Bay watershed associated with waste-rock piles. The humidity-cell test
concentrations are from Table 4. The barrel-test results and the mean concentration for the North Fork of the
Koktuli River are from Pebble Partnership (2011). The triangle represents the range of potential compositions
that could be expected for seepage from Pebble West and Pebble East waste rock piles and the dashed line
represents the range of potential compositions that could be expected from piles of Tertiary waste rock (see text).
Abbreviations: PWZ, Pebble West Zone; PEZ, Pebble East Zone; HCT, Humidity-Cell Test.
16
-------
Geologic and Environmental Characteristics of Porphyry Copper Deposits -April 2012

The humidity-cell test results for the Tertiary volcanic rocks yielded more coherent results than did the pre-
Tertiary rocks discussed above. Invariably, the humidity-cell test results show no ability to generate acid with all pH
values ranging between 7 and 9 with a mean pH 7.2 ± 1.3. Sulfate concentrations generally range between 1 and
100 mg/L with a mean concentration of 28.0 mg/L, but the lack of correlation with pH suggests that the resulting
sulfate may be derived from benign sulfate minerals rather than acid-generating iron sulfide minerals. Copper
concentrations were low and generally correlated with sulfate concentrations.

Tailings
Mill tailings are the waste products from froth flotation, a process used to produce concentrates of economic
minerals. The specific minerals separated greatly influence the character of the waste material. For porphyry
copper deposits, it is typical to separate the copper-sulfide minerals [chalcopyrite (CuFeS2) and bornite (CusFeS^]
as a copper concentrate, and the molybdenum-sulfide mineral, molybdenite (MoS2) as a molybdenum concentrate
(Fuerstenau and others, 2007). Gold commonly is associated with the copper sulfide minerals or pyrite. The gold
associated with the copper concentrate will be recovered during smelting, typically conducted off-site. Gold
associated with pyrite will require additional processing commonly on-site, as described above, to recover the gold.
Thus, pyrite, the main source of acid-mine drainage, can be disposed with the tailings or it can be separated as a
concentrate to either recover gold or to more effectively manage acid-generation risks. Therefore, the acid-
generating potential and mobility of trace metals will be affected by whether or not pyrite is separated from tailings
prior to disposal.
A greater number of environmental risks are associated with tailings due to their finer grain size compared to
waste rock. Like waste rock, tailings can weather and the associated leachate can contaminate surface water and
groundwater (Stollenwerk, 1994; Brown and others, 1998; Khorasanipour and others, 2011). Furthermore,
because of the sand to silt size grains, tailings are prone to be transported by waters, especially in the case of
tailings dam failure, and wind. Thus, they present additional potential risks to aquatic organisms through sediment
contamination.
A compilation of geochemical analyses of "pristine", unoxidized tailings from porphyry copper deposits is
presented in Table 5. These data include analyses of tailings from the Aitik mine, Sweden (R. Seal, unpublished
data), the El Teniente mine, Chile (Smuda and others, 2008; Dold and Fontbote, 2001), the Andina mine, Chile
(Dold and Fontbote, 2001), the El Salvador mine, Chile (Dold and Fontbote, 2001), and the Sarcheshmeh mine,
Iran (Khorasanipour and others, 2011). It is important to note that none of these tailings had a pyrite concentrate
removed.
A summary of the geochemistry of tailings derived from metallurgical testing of drill core from the Pebble
deposit is summarized in Table 6 from the PLP Environmental Baseline Document (Pebble Partnership, 2011).
That report presents data from three sample sets, 2004, 2005, and 2008, which were used in the humidity-cell tests
described below. The 2004 and 2005 samples were from Pebble West. The 2008 samples were from Pebble West
and Pebble East. The analyses for all sets included acid-base accounting analyses. The analyses for the 2004
and 2005 samples focused on a more restricted group of analytes, limited mostly to elements for which regulatory
guidance exists (Ag, As, Cd, Co, Cr, Cu, Hg, Mn, Mo, Ni, Pb, Sb, Se, Tl, and Zn). The analyses for the 2008
samples included a larger group of analytes (Ag, Al, As, Au, B, Ba, Be, Bi, Ca, Cd, Ce, Co, Cr, Cs, Cu, Fe, Ga, Ge,
Hf, Hg, In, K, La, Li, Mg, Mn, Mo, Na, Nb, Ni, P, Pb, Rb, Re, S, Sb, Sc, Se, Sn, Sr, Ta, Te, Th, Ti, Tl, U, V, W, Y,
Zn, and Zr. The table includes average values, the standard deviation for the average, and the low and high
values. For the entire dataset, paste pH values are near neutral, ranging from 6.6 to 8.9. The NP/AP ratio ranges
from 0.1 to 9.0, corresponding to probably acidic drainage generating values (PAG; net acidic) to not probably
acidic drainage generating (non-PAG; net alkaline), with the average being 2.7 (non-PAG; net alkaline). None of
17
-------
Geologic and Environmental Characteristics of Porphyry Copper Deposits -April 2012
Table 5. Geochemical composition of porphyry copper tailing samples from the literature and unpublished USGS
studies.
Mine
Country
Sample No.
Source
AI203
CaO
Fe203
K20
MgO
MnO
Na20
P205
Si02
Ti02
As
Ba
Be
Bi
Cd
Co
Cr
Cu
Mn
Mo
Ni
Pb
Sb
U
V
Zn
S
Carbonate C
Total C
LOI
NNP
Unit

%
%
%
%
%
%
%
%
%
%
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
%
%
%
%
kg CaCOs/t
Aitik El Teniente El Teniente
Sweden Chile Chile
Aitik 1 Channel Sediment
average average
1 2 2
15.65
3.425
10.3
4.775
2.185
0.32
2.36
0.64
54.4
0.74
3.50 33.0 36.0
930.5 382 384
1.55
1.505
<0.01
61.45
20 67 64
478 1035 921
2165 358 376
11.75 89 101
14.15 23 23
9.85
2.77
4.45
155.5 243 230
74 62 58
2.64 3.62 3.43
0.01
0.01
3.55
-74.3
Cauquenes-
Teniente
Chile
T1 average
3

92.9
470.3

29.4
3037
334.5
108.5

208.9
92.94

-18.2
Piquenes-
Andina
Chile
A2 average
3

62.0
721.3

14.4
2515.2
592.3
53

36.9

125.5
208.98

-28.3
El Salvador
Chile
E2 average
3

136.3
418.3

8.5
5091 .2
67.3
234.6

22.5

139.9
42.9

-101.6
Sarcheshmeh
Iran
S6/S7 average
4

18.5

27.6
53
1205
700.5
96.7
40
46.0

210

Sources: 1. This study; 2. Smuda and others (2008); 3. Dold and Fonbote (2001); 4. Khorasanipour and others (2011)
the tailing samples presented in Table 5 had pyrite separated; all of their NNP values are negative, indicating a net
acidic character, unlike the Pebble tailings, which had pyrite removed. Otherwise, the overall chemistry of the
tailing samples in Tables 5 and 6 compares favorably in terms of the range of values. It is worth noting that the
2005 LT C2 Combined Pre-Cleaner Tailings sample (Table 11-46 of the Pebble Project Environmental Baseline
Document) has a copper concentration (2,050 mg/kg) that is 68 percent of the 0.3 percent cut-off grade, a
molybdenum concentration (188 mg/kg) that 80 percent of the published resource molybdenum grade, and one of
the lowest NNP values (-30 kgCaCOs/t). Further metallurgical testing presumably will seek to improve copper and
18
-------
Geologic and Environmental Characteristics of Porphyry Copper Deposits -April 2012

molybdenum recovery, which also will improve the separation of sulfide minerals and increase NNP of the resulting
tailings.
Table 6. Geochemical composition of test tailings samples from the Pebble deposit from the Pebble Project
Environmental Baseline Document. Summary statistics include all samples presented in Tables 11 -46 and 11-47 in
Pebble Partnership (2011).
Parameter
Ag
As
Ba
Be
Bi
Cd
Co
Cr
Cu
Hg
Mn
Mo
Ni
Pb
Sb
Se
Tl
U
V
Zn
Paste pH
Total S
Sulfate
Sulfide
AP
TIC
TIC
NP (Modified)
NP/AP
NNP
Units
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
Standard Unit
%
%
%
kg CaCOa/t
%
kg CaCOa/t
kg CaCOa/t
ratio
kg CaCOa/t
Average
0.7
25.2
30.0
0.3
0.6
0.1
8.1
149.9
682.9
0.1
359.9
51.9
67.7
15.0
1.0
1.8
0.3
0.4
87.3
87.4
8.2
0.5
0.0
0.5
14.2
0.3
22.6
13.5
2.7
-0.5
Standard
Deviation
0.5
31.6
10.6
0.1
0.5
0.1
10.2
177.3
414.0
0.1
201.4
35.1
111.6
16.6
1.0
2.0
0.2
0.2
36.0
66.3
0.4
0.9
0.0
0.9
27.8
0.2
15.5
6.9
1.9
27.2
Low
0.23
4.2
20
0.18
0.2
0.03
2.2
6
142
<0.01
84
10.5
6.3
3.3
0.2
0.4
0.07
0.17
36
29
6.6
0.09
-0.01
0.05
1.56
0.05
4.5
4.6
0.1
-110.2
High
2.17
169
50
0.64
1.98
0.4
45.9
748
2050
0.56
880
188
452
88.4
5.41
8.8
1.2
0.87
149
267
8.9
4.19
0.2
4.12
128.8
0.75
62.5
25.9
9
22.4
Additional insights into aquatic risks associated with tailings can be found in case studies from mines. The
geochemical characteristics of tailings seepage have been investigated by several studies. Smuda and others
19
-------
Geologic and Environmental Characteristics of Porphyry Copper Deposits -April 2012

(2008) investigated the geochemical environment associated with tailings at the El Teniente porphyry copper
deposit, Chile. They found a range of values for various water-quality parameters associated with the tailings pond.
These parameters included pH (7.2-10.2), sulfate (1556-5574 mg/L), Fe (1.44-8.59 mg/L), Al (below detection -
0.886 mg/L), Mn (0.001-20.1 mg/L), Ni (0.008-0.393 mg/L), Cu (0.003-0.250 mg/L), Zn (0.007-130 mg/L), Mo
(0.033-13.2 mg/L), and As (below detection - 0.345 mg/L). Khorasanipour and others (2011) studied the
geochemical environment associated with tailings at the Sarcheshmeh mine, Iran. They too found a range of
values for water-quality parameters such as pH (3.6-7.9),sulfate (1348-4479 mg/L), Fe (<0.01-19.3 mg/L), Al (<0.5-
154 mg/L), Mn (5.6-73.7 mg/L), Ni (0.088-1.74 mg/L), Cu (< 0.002-149.9 mg/L), Zn (0.094-20.3 mg/L), Mo (0.027-
2.9 mg/L), and As (< 0.005-0.04 mg/L).
Morin and Hutt (2001) compared predictions for tailing leachate chemistry with actual drainage chemistry at the
Bell mine in British Columbia on the basis of samples collected seven years after closure. The predictions
indicated that drainage from the tailing piles would start at near neutral pH conditions, but would turn acidic over the
course of several decades. Their post-closure sampling results indicated that acid generation is roughly 100 times
less than predicted. The authors attributed this discrepancy to basing prediction on an insufficient number of
humidity-cell tests and incorrect assumptions about the rate of sulfide oxidation. Weibel and others (2011) found
similar results in studies of a porphyry copper mine in Chile.
As with the waste rock at Pebble, the best insights into the potential behavior of mill tailings come from the
humidity-cell tests being conducted by the Pebble Limited Partnership and its contractors (Pebble Partnership,
2011). The Pebble Partnership initiated two sets of humidity-cell tests on tailings derived from preliminary
metallurgical testing: one set in 2005 and one set in 2008 (Pebble Partnership, 2011). Humidity-cell tests represent
one of the best predictors of long-term weathering of tailings in an aerobic environment (Price, 2009). The test
conditions are most representative of unsaturated tailings exposed at the surface of a pile. The geochemical
environment found at depth in the saturated zone is typically quite different (Blowes and others, 2003). The 2005
tailings samples originated from a relatively simple set of metallurgical methods, whereas the 2008 samples
originated from a greater variety of metallurgical processing methods. The humidity-cell tests for the tailings
samples were conducted using standard procedures, as described above for the waste-rock samples (Price, 2009).
However, the grain size of the tailings is well below the 6 mm maximum size of waste-rock samples, which means
that the tailings should be more reactive than were the waste-rock samples in humidity-cell tests. The results
included the same set of parameters as with the waste-rock testing. As for the waste-rock samples, the following
discussion focuses on pH, sulfate, copper, zinc, molybdenum, and arsenic.
The humidity-cell results were similar for both the 2005 and 2008 sets of tailings (Pebble Partnership, 2011).
Both sets had pH values ranging between 7 and 8.5 in experiments lasting up to 5 years for the 2005 samples and
for more than one year for the 2008 samples (Table 7). Sulfate concentrations for both sets generally are below 40
mg/L after the initial flush of soluble sulfate salts. The mean sulfate release concentration was 17.4 ± 8.0 mg/L.
The mean copper (5.3 ± 2.2 pg/L), and zinc (3.2 ± 1.7 pg/L) concentrations were less than those from the waste-
rock samples, whereas the molybdenum (33.5 ± 23.7 pg/L), and arsenic (5.5 ± 8.4 pg/L) concentrations were
higher (Table 4).
The chemical composition of the pond on top of the tailing impoundment is difficult to estimate, but bounds can
be placed on its composition. During mine operation, the water should represent a mixture of the supernatant
solution from the mill that is pumped with the tailings slurry to the impoundment, solutes derived from aerobic
leaching of the tailings material, which can be limited by the average humidity-cell results from tailings, and ambient
surface water and precipitation, which can be approximated by the mean composition of the North Fork of the
Koktuli River. The range of potential compositions is shown in Figure 8 by the triangle, which limits the range from
these three sources in terms of dissolved copper concentration and water hardness. The supernatant solution has
the highest copper concentration and water hardness of the three end members.
20
-------
Geologic and Environmental Characteristics of Porphyry Copper Deposits -April 2012
Table 7. Summary of geochemical results from humidity-cell tests on tailing samples and the supernatant solution
from metallurgical testing conducted by the Pebble Partnership (2011)
Parameter
Pebble Partnership
(2011) Source
pH
Alkalinity
Hardness
Cl
F
S04
Thiosalts (8203)
Ag
Al
As
B
Ba
Be
Bi
Ca
Cd
Co
Cr
Cu
Fe
Hg
K
Mg
Mn
Mo
Na
Ni
Pb
Sb
Se
Sn
Tl
V
Zn
Units

S.U.
mg/L CaCOs
mg/L CaCOs
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
Tailings Humidity Cell
Average Standard Deviation
Table11-49(calc);
Appendix 11L(pH)
7.8
59.7
66.8
0.52
0.451
17.4
nr
0.00001
0.02
0.0055
0.0107
0.0092
0.0002
0.0005
22.6
0.00001
0.0002
0.0005
0.0053
0.03
0.000010
4.02
2.55
0.0441
0.0335
2.10
0.0005
0.00006
0.0018
0.0015
0.0029
0.00005
0.0008
0.0032
Table11-49(calc);
Appendix 11L(pH)
0.2
15.5
13.6
0.08
0.440
8.0
nr
0.00000
0.03
0.0084
0.0010
0.0050
0.0000
0.0000
3.9
0.00000
0.0002
0.0000
0.0022
0.00
0.000000
1.69
2.07
0.0224
0.0237
0.26
0.0001
0.00001
0.0017
0.0006
0.0040
0.00000
0.0008
0.0017
Supernatant
Average Standard Deviation
Table 11 -48
7.9
74.8
322.8
nr
nr
318.7
44.1
0.00002
0.07
0.0172
nr
nr
nr
nr
116.0
-0.00008
-0.0001
-0.0010
0.0078
0.02
-0.000037
25.95
8.00
0.0719
0.0697
43.78
-0.0008
0.00023
0.0060
0.0076
nr
0.00002
nr
0.0043
Table 11 -48
0.3
20.4
254.8
nr
nr
372.1
156.1
0.00025
0.08
0.0212
nr
nr
nr
nr
101.2
0.00018
0.0004
0.0012
0.0049
0.32
0.000103
8.16
5.53
0.0631
0.0560
132.40
0.0018
0.00062
0.0058
0.0062
nr
0.00022
nr
0.0080
nr: not reported
21
-------
Geologic and Environmental Characteristics of Porphyry Copper Deposits -April 2012
The composition of water potentially seeping from the base of tailing piles is more problematic to estimate. At
depth in the saturated zone in tailing piles, dissolved oxygen is rapidly removed by reaction with trace amounts of
sulfide minerals, which limits the ability to generate acid during further interaction with tailings material. In these
acid-limited environments, silicate minerals such as feldspars and trace amounts of carbonate minerals can
effectively neutralize acid and restrict the ability of groundwater to dissolve additional metals and other trace
elements (Blowes and others, 2003). Under these conditions, the chemical composition of seepage from a tailings
pile should fall along the join between the average humidity-cell test composition and ambient surface water and
groundwater (Figure 8).
10
CUO
OJ
Q_
Q.
O
QJ

~0
to
to
8 -
6 -
2 -
• North ForkKoktuli River

• Tailings Average HCT

^Supernatant Average
50 100 150 200 250

Hardness mg/L CaC03
300
350
Figure 8. Dissolved copper concentrations and water hardness values for various potential end-member waters
around the Pebble site in the Bristol Bay watershed associated with a tailings impoundment. The humidity-cell
test concentrations are from Table 7. The mean concentrations for the North Fork of the Koktuli River are from
Pebble Partnership (2011). The triangle represents the range of potential compositions that could be expected
for a tailing pond during mine operation; after closure, once ore processing has ceased, the join between the
North Fork and the Tailings Average HCT compositions may be more representative of the range of potential
compositions (see text). Abbreviations: HCT, Humidity-Cell Test.

Copper Concentrate
Limited data are available on the geochemistry of copper concentrates from porphyry copper deposits. The
geochemical analysis by USGS laboratories of a single sample of a copper concentrate from the Aitik porphyry
copper deposit is presented in Table 8. X-ray diffraction analysis indicates that the sample is dominated by
22
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Geologic and Environmental Characteristics of Porphyry Copper Deposits -April 2012

chalcopyrite with trace amounts of pyrite, quartz, and possibly molybdenite. The ideal composition of chalcopyrite
is 34.6 weight percent Cu, 30.4 weight percent Fe, and 34.9 weight percent S. For the analysis presented in Table
8, the Cu concentration is above the upper detection limit. However, the analyzed concentration of S (33.4 wt. %)
indicates that the sample is greater than 95 percent chalcopyrite, whereas that of Fe (25.8 wt. %) indicates
approximately 85 percent chalcopyrite. The most notable trace elements in this concentrate are Zn (2190 mg/kg),
presumably reflecting the presence of minor sphalerite, Mo (1100 mg/kg), presumably reflecting the presence of
molybdenite, and Mn (346 mg/kg), likely hosted by sphalerite or traces of the Fe-carbonate mineral siderite.
Table 8. Geochemical analysis of the copper concentrate (Aitik 2) from the Aitik porphyry copper mine, Sweden
Element
Al
Ca
Fe
K
Mg
Na
Ti
Ag
As
Ba
Bi
Cd
Co
Cu
Ga
In
Mn
Mo
Ni
Pb
Sb
Te
Th
TI
U
V
Zn
S
Units
%
%
%
%
%
%
%
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
mg/kg
%
Concentration
0.98
0.32
25.8
0.49
0.11
0.19
0.05
>10
12
59
44.9
2.4
53.9
>10000
0.88
2.35
345
1100
72.1
64.9
43.4
4.1
1.5
0.2
2.2
23
2190
33.4
The solution chemistry associated with the transport of concentrate as a slurry in a pipeline can be assessed
by conducting leaching experiments on the Aitik copper concentrate sample described above, which is
mineralogically similar to copper concentrates from most porphyry copper mines. In flotation circuits, chalcopyrite
is not especially sensitive to pH, but pH may be adjusted to alkaline values to separate molybdenite or pyrite
(Fuerstenau and others, 2007).

23
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Geologic and Environmental Characteristics of Porphyry Copper Deposits -April 2012

The leachability of elements from copper concentrate was evaluated using the Synthetic Precipitation Leaching
Procedure (USEPA Method 1312), and a modification of this protocol. The standard procedure reacts a sample in
a 20:1 (solution: sample) ratio with a weak acidic solution (pH 5), made of a mixture of sulfuric and nitric acids,
under continuous agitation for 18 hours, after which the solution is sampled. Additional leaching experiments were
conducted in which the copper concentrate sample was leached following the same procedure except that the
starting leaching solution was either distilled water + NaOH solutions (pH 6, 7, 8, 9), or distilled water + Na2C03
solutions (pH 7, 9) adjusted to various starting pH values. The purpose of these experiments was to evaluate the
range of starting pH values that may be associated with a copper-concentrate slurry discharged from a mill to a
pipeline.
The results of the leaching experiments on the copper concentrate are presented in Table 9. Results from a
copper tailings sample from Aitik are also presented in Table 9. One of the most striking features of these
experiments using the copper concentrate is that regardless of the starting pH (pH = 5 to 9), the final pH after 18
hours for all experiments ended up between 4.1 and 4.2. Equally striking was the fact that dissolved copper
concentrations in the leachate ranged between 15,300 and 16,800 pg/L, dissolved iron concentrations ranged
between 5,480 and 10,200 pg/L, and dissolved sulfate ranged between 183.7 and 208.8 mg/L.

Summary

The Pebble deposit in the Bristol Bay watershed, southwestern Alaska, shares many geologic attributes with
typical porphyry copper deposits throughout the world. These features include: (1) its spatial association with
coeval granitic intrusions; (2) its large tonnage of ore and its low grade, although the size of Pebble places it in the
upper 5 percent of porphyry copper deposits globally; (3) the association of copper, molybdenum, and gold; (4) the
style of mineralization as veinlets, stockworks, and disseminations with igneous and sedimentary host rocks; and
(5) its zoned ore-mineral and alteration assemblages. From an environmental perspective, the acid-generating
potential of Pebble is similar to that found at other porphyry copper deposits: waste rock and tailings span the
range from potentially acidic drainage generating to non-potentially acidic drainage generating due to the low
contents of pyrite and other sulfide minerals as potential sources of acid, and the presence of silicate minerals such
as feldspars and trace amounts of carbonate minerals to neutralize acid. Humidity-cell tests by Pebble Partnership
(2011) indicate that drainage associated with pre-Tertiary waste rocks is likely to have higher concentrations of
solutes and lower pH than drainage associated with mine tailings. Solutions associated with a copper concentrate
slurry are likely to be weakly acidic and have high concentrations of dissolved copper and zinc.
24
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Geologic and Environmental Characteristics of Porphyry Copper Deposits -April 2012

Table 9. Geochemical analyses of dissolved constituents (< 0.45 pm) in leachates from tailings and copper
concentrate from the Aitik Mine, Sweden, using USEPA Method 1312 and a modified leaching method.
Field No.
Base (Acid)
Starting pH
Final pH
Spec.
Cond.
DO
T
Alkalinity

Ag
Al
As
Ba
Ca
Cd
Co
Cr
Cu
Fe
K
Mg
Mn
Mo
Na
Ni
Pb
Sb
Se
Si02
U
Zn
Cl
F
N03
S04
Units
S.U.
s.u.
pS/cm

mg/L
°C
mg/L
CaC03
M9/L
M9/L
M9/L
M9/L
mg/L
M9/L
M9/L
M9/L
M9/L
M9/L
mg/L
mg/L
M9/L
ug/L
mg/L
M9/L
M9/L
M9/L
M9/L
mg/L
M9/L
M9/L
mg/L
mg/L
mg/L
mg/L
Tailings
WSP*
5
7.3
133

10
22.6
9.3

<1
158
<1
50.5
16
O.02
0.43
<1
0.8
<50
2.15
0.38
20
<2
4.67
<0.4
<0.05
0.47
<1
1.8
<0.1
0.6
0.8
0.2
0.7
43.6
Copper Concentrate
WSP*
5
4.2
349

<10
1,910
<10
38.6
30
6.3
157
<1
16,500
7,940
3.4
5.5
931
<20
0.41
634
6.16
17.4
<10
<2
33.7
2,040
2.6
1.4
0.4
192.6
NaOH
6
4.2
362

<10
1,820
<10
39.2
28.9
6
151
<1
16,300
9,190
3.7
5.2
887
<20
0.52
607
6.93
13.4
<10
<2
33.8
1,920
2.6
1.5
O.08
200.8
NaOH
7
4.2
350

<10
1,790
<10
40
29
5.9
152
<1
15,400
7,440
3.4
5.3
891
<20
0.84
613
6.15
16.6
<10
<2
31.2
1,950
2.8
1.5
O.08
191.4
NaOH
8
4.2
345

<10
1,770
<10
40.7
28.5
5.9
151
<1
15,300
7,070
3.4
5.3
880
<20
0.89
609
6.08
16.2
<10
<2
31.9
1,940
2.6
1.5
O.08
185.1
NaOH
9
4.1
372

<10
1,850
<10
38.5
28.7
6
151
<1
16,800
10,200
3.8
5.2
883
<20
1
607
7.92
14.7
<10
<2
34
1,940
2.6
1.5
O.08
208.8
Na2C03
7
4.2
340

<10
1,950
<10
37.9
28.2
6.3
154
<1
16,300
5,560
3
5.5
918
<20
0.87
620
5.36
16.8
<10
<2
34.8
2,040
2.6
1.6
O.08
183.7
Na2C03
9
4.2
340

<10
1,870
<10
36.2
28.3
6
152
<1
15,600
5,480
3.1
5.4
899
<20
1.5
612
5.55
16.6
<10
<2
33
1,980
2.5
1.5
O.08
184.5
*WSP: Mixture of H2S04 and HMOs with pH = 5.0 in accordance with EPA Method 1312.
25
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Geologic and Environmental Characteristics of Porphyry Copper Deposits -April 2012

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28
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Appendix I

Conventional Water Quality Mitigation
Practices for Mine Design,
Construction, Operation, and Closure
1-1
-------
DRAFT May 2012
DO NOT CITE OR QUOTE External Review Draft
Conventional Water Quality Mitigation
Practices for Mine Design, Construction,
Operation, and Closure
Barbara A. Butler, Ph.D.
U.S. EPA Office of Research and Development
National Risk Management Research Laboratory
Land Remediation and Pollution Control Division
Remediation and Redevelopment Branch
NOTICE

THIS DOCUMENT IS A PRELIMINARY DRAFT. It has not been formally
released by the U.S. Environmental Protection Agency and should not be
construed to represent Agency policy. It is being circulated for comment on its
technical accuracy and policy implications.
Office of Research and Development
U.S. Environmental Protection Agency
Washington, DC
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***internal deliberative materials-do not cite, quote, or distribute***

Mitigation includes the steps needed to avoid, minimize, or compensate for any
potential adverse impacts on the environment from a given activity (Hough and
Robertson, 2009). Hardrock metal mining is an activity that provides metals for
numerous purposes, but it has the potential to have adverse effects on nearby aquatic
environments. Many mitigation measures developed to avoid or minimize impacts to
water quality and aquatic ecosystems have become current industry practice and
several of these are presented in this document for selected waste streams associated
with mining, along with discussions of accidents and failures associated with storage of
waste rock and tailings. Also briefly discussed is compensatory mitigation, which may
be required under Section 404 of the Clean Water Act (CWA) when there are
unavoidable impacts anticipated to lead to the loss of wetland, stream, or other aquatic
resource.

The most important aspects of mitigation for any mining site are proper planning,
design, construction, operation, management, and closure of waste and water
containment and treatment facilities, and monitoring and maintenance over all mine-
life phases, including following closure. Planning for design and construction must
consider site-specific factors such as climate, topography, hydrology, geology, seismicity,
and waste material specific factors such as geochemistry, mineralogy, particle size, and
presence of process chemicals. These factors should be based upon conservative
estimates of future conditions to minimize potential for failure overtime. In addition,
the planning and design should incorporate considerations for the land's use following
closure of mining operations.
1. WASTE ROCK

Overburden is unconsolidated surface material that would be removed to expose the
ore/waste rock zone and often comprises alluvium, colluvium, glacial tills, or other soils;
overburden may be stockpiled separately for later use in reclamation. Waste rock
includes rock that is removed above the ore and rock that is removed along with the
ore, but cannot be mined economically at the time of mining (sub-economic ore). The
particle size distribution of waste rock may vary from sand-sized fines to large boulders,
with the quantity in a given particle size class dependent upon the site geology and the
specifics of the method(s) in which it was extracted (e.g., blasting strength). The sources
of potential environmental influence to surface water from waste rock piles include
sediment loading due to erosion and deposition of fugitive dusts, and contaminant
loading due to leaching of acidity and inorganic contaminants, such as metals and
metalloids, contained in the waste rock. Precipitation and surface water run-on can
lead to weathering and erosion of materials into runoff (dissolved and particulate)
transported to surface water. Percolation and infiltration that lead to leaching and
transport of ions through seepage of the leachate to groundwater may occur also, as
may seepage through sloped pervious material to a surface water body. Additional
routes of environmental exposure include movement of material mass (e.g., through
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***internal deliberative materials-do not cite, quote, or distribute***

rockslides due to physical instability) into a water body and wind erosion carrying finer
particles (dust) through the air.

Waste rock, and other mining materials may be classified as potentially acid-generating
(PAG) or non-acid generating (NAG, also called non-PAG); this distinction is determined
through geochemical characterization, acid-base accounting (ABA) static tests, and
kinetic leachate testing [e.g., see (American Society for Testing and Materials (ASTM)
2000, Hornberger and Brady 1998, Lapakko 2002)]. ABA tests are rapid methods to
determine the acid-generation potential (AP) and neutralization potential (NP) of a rock
or mining waste material, independent of reaction rates (i.e., in contrast to kinetic
tests). These potentials are then compared to one another by either their differences
(net neutralization potential, NNP) or their ratios (neutralization potential ratio, NPR).

Although methods used for ABA have limitations, it is common industry practice to
consider materials that have an NPR of 1 or less as potentially acid generating (PAG)
(e.g., Brodie et al., 1991; Price and Errington, 1998) and materials with a ratio greater
than 3 (Brodie et al., 1991) or 4 (Price and Errington, 1998) as having no acid generation
potential (non-PAG or NAG). Materials having a ratio between 1 and 4 require further
testing via kinetic tests and geochemical assessment for classification (Brodie et al.,
1991; Price and Errington, 1998). This further testing and assessment are necessary
because if neutralizing minerals react before acid generating minerals, the neutralizing
effect may not be realized and acid might be generated in the future. Additionally,
some toxic elements (e.g., selenium and arsenic) may be released from mining materials
under neutral or higher pH conditions, which would be observed during kinetic leaching
tests conducted at variable pH values.

Waste rock is susceptible to acid generation due to the open pore network allowing for
easy advection of air (Mining Minerals and Sustainable Development (MMSD) 2002) to
oxidize minerals, which subsequently are dissolved in water that encounters the rocks.

1.1 STANDARD PRACTICES

There are numerous mitigation measures available for waste rock piles. The selection of
mitigation measures are site-specific and depend on the sizes and amounts of the
material to be placed in the pile, the methods employed during mining, the mineralogy
of the material, the site's specific hydrology, climate, seismicity, and topography, and
plans for future land-use.

1.1.1 Operational Phase

Non-reactive (i.e., NAG) waste rock might be used in creation of mining roadways or
transported off-site for use in roadways or another purpose requiring rockfill, with
unused waste rock stored in piles. Waste rock piles generally are disposed in locations
close to the mine site to reduce handling costs and are placed in locations that provide
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***internal deliberative materials-do not cite, quote, or distribute***

physical stability. Waste rock and overburden piles typically are not placed on lined
foundations because of the cost and stability risk (Mining Minerals and Sustainable
Development (MMSD) 2002), but rather are constructed on natural terrain; although
the decision for lined or unlined piles is site-specific. Prior to placement of a waste rock
pile, the topsoil is removed and stockpiled for later use in reclamation. The angle of
repose (where the outer slope is just stable under static loading conditions) is typically
37-40° (Mining Minerals and Sustainable Development (MMSD) 2002), but will depend
on site-specific and material-specific factors. Piles constructed in lifts or by using
benches typically have lower slope angles and concurrent increased stability (U.S.
Environmental Protection Agency (U.S.EPA) 1995b, Mining Minerals and Sustainable
Development (MMSD) 2002).

When waste rock contains materials that have the potential to generate acid or release
metals, metalloids, or other ions of concern that would have environmental or human
health impacts, management of the materials must include practices to minimize
potential for any environmental impacts. Mitigation/management measures used
during the operational phase can include a variety of methods either used
independently or in combination; these include diversion systems to route water away
from the pile, use of liners underneath the waste rock pile, selective handling /
segregation, blending and layering, minimization of infiltration potential, leachate
collection systems and seepage drains and routing systems to divert leachate to
treatment facilities, addition of bactericides to slow oxidation of PAG, encapsulation,
and/or adding low permeability materials to slow infiltration rates (Boak and Beale
2008, Mining Minerals and Sustainable Development (MMSD) 2002, U.S. Environmental
Protection Agency (U.S.EPA) 1995b, U.S. Environmental Protection Agency (Region 10)
2003a, U.S. Environmental Protection Agency (Region 10) 2003b, Perry et al. 1998).
Additionally, the amount of waste rock exposed to the environment can be reduced by
disposing the rock into depleted pits or underground mine tunnels, or through
reclamation activities conducted concurrent with active mining (called progressive
reclamation).

Selective handling involves placement of materials combined with management
strategies to avoid or minimize release of acidic drainage. Physical separation of PAG
and NAG materials will not prevent acid-rock drainage formation, but may be necessary
to control the amount and location of potential drainage and to manage the PAG
material. PAG material can be kept completely saturated to minimize air exposure (e.g.,
placed into the open pit post active mining), disposed in a separate lined or unlined
engineered containment system, or blended with NAG material and stored in an
aboveground pile, coupled with minimizing exposure to water.

Blending involves mixing waste rock types of varying acid-producing potential (AP) and
neutralization potential (NP) to create a mixture that has acceptable quality (i.e., no net
acid-generation potential). The viability of blending as a mitigation measure depends on
the materials available and the mine plan, the stoichiometric balance between acid
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generating and neutralizing materials, geochemical properties, reactivity of waste rock
types, flow pathways created within the waste rock pile, and extent of mixing and
blending. If a site does not have sufficient neutralizing material with which to blend the
PAG material, limestone or other neutralizing rock might be used, if available from
another location on-site, or trucked into the site. The geochemical characteristics of the
materials being blended and mixed must be well-characterized in order to attain a
resultant mix that has no net acid production potential.

PAG materials may be kept isolated from direct exposure to precipitation and oxygen
transfer by layering NAG materials on top of them in the waste pile. This would involve
layering of PAG with a mix of PAG-NAG material, with a top layer of NAG only material,
or another combination.

Encapsulation of a waste rock pile with an impermeable layer serves to limit infiltration
and oxygen transfer. Progressive reclamation with multiple impermeable layers within a
waste rock pile can minimize infiltration, seepage, and oxygen transfer. Compaction is
used also, if it can be done safely (physically). Once a pile is covered, overburden or
other non-reactive material can be placed on top and the site vegetated to provide
stability against erosion and to meet regulatory requirements for restoration.

Some microorganisms are able to facilitate rapid oxidation of PAG sulfidic minerals;
thus, a bactericide could be added to eliminate their presence and slow the oxidation
rate. Such an amendment must be mixed thoroughly into the PAG material as the pile is
constructed to ensure effectiveness.

Sub-economic ore removed during the active mining phase might be segregated from
the primary waste rock pile to be mined if/when it becomes economically feasible.
These piles may be mined with their resultant waste disposed into a tailings
impoundment or placed directly in the completed pit, if mined at closure.

Building an under-drain system to collect seepage/leachate water potentially containing
leached ions/acidity allows this water to be directed toward collection systems for
either use in processing or treatment and discharge to a surface water body. Diversion
structures collect and direct runoff and seepage to treatment and/or settling ponds.
Groundwater monitoring wells are used downstream of these structures to evaluate
their performance.

1.1.2 Closure and Post-Closure

During the closure phase of mining, a dry cover (or encapsulation) can be placed over
the waste rock pile to isolate it from water and oxygen, or the pile can placed into the
completed open pit to be kept below the water line (subaqueous disposal if PAG
material), with choices dependent upon site specifics (O'Kane and Wels 2003).
Additionally, in some settings, it is beneficial to fill the pit with waste rock and other
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waste material and then construct a dry cover over the filled pit area. When stored
above ground, the stockpiled overburden may be used to cover the pile and then it is
vegetated to provide stability against erosion. Blight and Fourie (Blight and Fourie 2003)
recommend that outer slopes reclaimed with vegetation not exceed 15%. Post-closure
monitoring, maintenance, and inspection are conducted indefinitely when a pile
requires long-term collection and treatment of leachate through use of the drainage
collection and monitoring structures in place during the operational phase of mining. A
number of different types of covers could be used, with each having their benefits and
limitations. Factors affecting the long-term performance of covers include physical
stability, volume change, vegetation, soil evolution, and ecological stability (Wilson,
Williams and Rykaart 2003).

1.2 ACCIDENTS AND FAILURES

If waste rock piles are designed properly with appropriate mitigation measures,
monitored and maintained, release of contaminants is possible, but unlikely; however,
accidents and failures causing contaminants to be transported may still occur. Seven
major factors affecting the physical stability of a waste rock pile against failure are: 1)
configuration; 2) foundation conditions; 3) waste material properties; 4) method of
construction; 5) dumping rate; 6) piezometric and climatic conditions; and 7) seismic
and blasting activities ((Piteau Associates Engineering Ltd. 1991), as referenced in (U.S.
Environmental Protection Agency (U.S.EPA) 1995b)). An additional factor to consider is
monitoring and maintenance for early detection of conditions that indicate inadequate
stability. Although it depends on a number of site-specific factors, data indicate that
most waste dump failures occur on foundations with slopes in excess of 20 degrees (U.S.
Environmental Protection Agency (U.S.EPA) 1995b).

Physical failures of waste rock piles may occur through slope failures. These result from
changes in the effective stresses of the rock material, variations in material properties
(including particle size and gravity sorting), or changes in the rock pile's geometry
(Pastor et al. 2002, Tesarik and McKibbin 1999). Changes in effective stress can result
from earthquakes, human actions, changes in underlying soil properties, or through
changing pore pressures resulting from rainfall, snowmelt, or changes in drainage
conditions. Properties of the rock will change over time due to weathering and from the
influence of acid dissolution, if any nearby PAG materials are oxidized and dissolved.
Changes in a waste rock pile's geometry can result from erosion or from actions such as
excavation, construction, or rebuilding/reshaping of the pile.

Waste rock piles typically have heterogeneous particle size distribution and varied
permeability throughout the depth and breadth of the pile. In a field test using tracers,
Eriksson et al. (Eriksson, Gupta and Destouni 1997), found that 55-70% of the total
water followed preferential flow pathways. The authors also found that chemical
tracers behaved differently in weathered waste rock piles versus newer piles. Results
from Eriksson et al. (Eriksson et al. 1997), support the need for understanding longer-
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term behavior of the materials and their distribution within a waste rock pile through
leaching tests, modeling, and field measurements. Blending waste rock with limestone
is a standard practice to minimize the production of acidic leachate; however, the
mixing method used during construction of the pile construction may influence the
method's success. For example, Miller et al. (Miller et al. 2006), reported blending
during waste rock pile construction to have only limited success when using haul trucks,
due to insufficient blending of the limestone with the finer size fraction of waste rock,
but that better mixing was achieved using a conveyer and stacker. Morin and Hutt
(Morin and Hutt 2004), as presented in Price (Price 2009), found that variability in
acidity from seeps of a single waste rock dump ranged from zero to approximately 90 g
CaC03/L (standard unit for acidity, where 50 grams of CaC03 neutralizes 1 mol H+) in one
year, which further supports the need for homogenous blending of neutralizing
materials and complete characterization of waste rock materials.

Isolation covers have the highest probability of success against geochemical failure (i.e.,
leaching of acidic and/or contaminant-laden water), with their purpose being to limit
infiltration and oxygen transfer. In a study of a waste rock pile at a mine site in Papau
Province, Indonesia, however, Andrina et al. (Andrina et al. 2006), found aspects of a
waste rock pile, including the type of waste rock, particle size distribution, and dumping
methods, each influenced variations in oxygen and temperature profiles. At that site,
they found that an impermeable surface cover had only a limited effect on oxygen
concentrations within the profile of the waste rock pile and concluded that advection of
airflow through the coarse rock / rubble zone at the foundation of the dump was the
primary pathway for oxygen transport.

Monitoring and maintenance activities must continue beyond construction of a waste
rock pile. Although the pile may have been constructed based on sound slope stability
studies, and have appropriate covers and means to divert water, the properties of the
pile may change over time and breaches to covers may occur. Additionally, freeze/thaw
cycling in colder climates may cause cracks, channeling, and exposure of surfaces below
the cover (Sartz et al. 2011) and should be considered when designing piles and
mitigation measures in these climates. Such cycling could result in accelerated
weathering and leaching of materials (Dawson and Morin 1996, SRK Consulting 2009).
With careful monitoring and early remedy of observed defects, some catastrophic
consequences can be avoided.
2. TAILINGS

Tailings are a solid-liquid slurry material comprising fine-grained waste particles
remaining after ore processing (e.g., milling, flotation, separation, leaching) and typically
in the silt size-fraction ranging from 0.001 to 0.6 mm, along with water and residual
chemicals (Mining Minerals and Sustainable Development (MMSD) 2002, U.S.
Environmental Protection Agency (U.S.EPA) 1994). Similar to waste rock, tailings
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materials may be potentially acid-generating (PAG) or non-acid generating (NAG) and
testing is conducted to assess their characteristics. The majority of ore mined and
processed ends up as tailings. Tailings slurries have a solids content from 15 to 55
percent weight (U.S. EPA 1994). The liquid portion of tailings comprises water and
chemicals used in processing of the ore (e.g., sodium ethyl xanthate, methyl isobutyl
ketone, hydroxy oxime, acids, alcohols). Cyanide and metals may be present if the
process includes cyanidation, with disposal of waste solution and tailings in the tailings
impoundment. Logsdon et al (Logsdon, Hagelstein and Mudder 1999) present
concentrations of cyanide and various metals that might be expected (if present in the
ore) in solutions following gold extraction: total cyanide (50-2000 mg/l), arsenic (0-115
mg/l), copper (0.1-300 mg/l), iron (0.1-100 mg/l), lead (0-0.1 mg/l), molybdenum (0-4.7
mg/l), nickel (0.3-35 mg/l) and zinc (13-740 mg/l).

The sources of potential environmental impacts to water from tailings storage facilities
(TSF) are sediment loading and leaching of acidity and inorganic contaminants, such as
metals and metalloids, and other chemicals used that may be present in the processing
waste tailings. The main environmental influences originate from seepage of
contaminants into groundwater, leakage through containment walls, and exposure of
waterfowl (if a tailings pond is present) to chemical contaminants. Additional routes of
environmental exposure include movement of material mass from structural failure of a
tailings impoundment (e.g., through breach of embankments) into a water body, and
wind erosion carrying finer particles through the air during construction.

2.1 STANDARD PRACTICES

The selection and design of a tailings disposal site is site specific and depend on factors
such as climate, topography, geology, hydrology, seismicity, economics, and
environmental and human safety (e.g., see (Commonwealth of Australia 2007, U.S.
Environmental Protection Agency (Region 10) 2003a, U.S. Environmental Protection
Agency (Region 10) 2003b). The most basic requirements of any tailings storage facility
(TSF), also called a tailings disposal facility, are that it is safe, stable, and economical,
and that it presents negligible public health and safety risks and acceptably low social
and environmental impacts during operation and post-closure. Effective construction
must be based on a correct geotechnical assessment.

2.1.1 Operational Phase

Disposal options for tailings include 1) land-based placement into an impoundment; 2)
disposal into underground workings or open pits; and 3) underwater (sub-aqueous)
disposal into an existing water body or a constructed water body. The most common
method of disposal is into a tailings slurry impoundment. Tailings impoundments are
constructed as water-holding structures. This generally is accomplished by constructing
a tailings dam in a valley. As tailings are placed behind the dam, a basin is formed. The
solid portion of the tailings settles and the liquid portion creates a tailings pond.
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Construction of a tailings impoundment is done in lifts over the life of the mine. Tailings
deposited against the embankment in creation of beaches leads to water draining away
from the embankment, which reduces seepage and increases dam stability. Water
levels in the tailings pond are controlled through removal of excess water for use in the
mining process or for treatment and discharge to the local surface water; this minimizes
water storage to enhance stability.

Special care must be taken during operations and post-closure to isolate acid-
producing/metal leaching tailings from oxidation. A common method is for disposal of
such tailings underwater (either into an existing water body or into a tailings pond).
Sub-aqueous disposal is common in Canada and is considered a BMP for long-term
isolation of tailings from oxidation; loss of any existing water body through this method
must be replaced (O'Kane and Wels 2003). Sub-aqueous disposal has the potential for
problems with physical stability, seepage, and water quality; however, if properly
designed, constructed, and maintained, this type of storage provides good long-term
isolation post-closure. At least a 30-cm barrier of stagnant water should overly the
tailings (wave action would re-suspend particles closer to the surface if not stagnant); in
Canada, a minimum recommended depth is 100-cm (SRK Consulting 2005). Sub-
aqueous disposal is not applicable in all environments (e.g., arid regions), and disposal
into an existing water body is not supported at all in Australia (Witt et al. 2004).

Tailings impoundments can be constructed using upstream, downstream, and centerline
methods. The upstream method involves construction of walls on top of consolidated
and desiccated tailings in an upstream direction, using waste rock or tailings for
construction material; the downstream method involves construction with waste rock
or borrow materials in a downstream direction; and the centerline method involves
construction of the walls above a fixed crest alignment, using waste rock, borrow
materials, or tailings (Commonwealth of Australia 2007). According to the International
Commission on Large Dams (ICOLD), from a seismic standpoint, tailings dams built by
the upstream method are less stable than dams built by either the downstream or the
centerline method (International Commission on Large Dams (ICOLD) 2001). The state
of Idaho considers upstream construction unsuitable for impoundments intended to be
very high and/or to contain large volumes of water or solids
(http://www.idl.idaho.gov/Bureau/Minerals/bmp manuall9927pl6-ch4.pdf). The
downstream method is considered more stable, but it is also the most expensive option;
centerline construction is a hybrid of the two and has risks and costs lying between
(Chambers and Higman 2011, Martin et al. 2002).

When tailings impoundments are constructed in earthquake-prone locations, a critical
design criterion is magnitude of earthquake that could be expected to occur. The most
conservative design would consider the maximum credible earthquake (MCE), which
would be the largest quake that could occur reasonably at any location at the mine site,
based on seismological and geological evidence and interpretation (Chambers and
Higman 2011).
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Dewatering (thickening) of tailings prior to disposal enables more process water to be
directly recycled back to mineral processing plant to reduce losses and operational
demand, while reducing the amount of water stored in the TSF. Reduction of water
quantity will reduce risks of overtopping, seepage, and evaporative losses of water that
could be used in the mining process (rather than fresh water). Depositional beach
angles also are steeper, which aids in containment.

Paste tailings technology requires thickening (water content ~ 20%) the tailings and
placing them onto a lined disposal site. Dry stack tailings require thickening and filtering
the tailings and placing the tailings onto a lined pad. Tailings thickened to a paste and
filtered tailings can be 'stacked' for long-term storage. This method is relatively new,
but has the advantages of reduced potential for liquefaction during an earthquake and
tailings release from a breach in containment would be localized instead of flowing long
distances (Witt et al. 2004). Filtered (e.g., moisture content ~ < 20%) and stacked
tailings require a smaller footprint for storage, are easier to reclaim both at closure and
by progressive reclamation, and have lower potential for structural failure and
environmental impacts (Martin et al. 2002). Additionally, in cold climates, dry stacking
prevents pipes from freezing, prevents frosting problems associated with conventional
impoundments, and assists in retention and recycling of process water during cold
weather operations (Access Consulting Group 2007). Disadvantages include that dry
stacking is not appropriate for acid-generating tailings and pumping to the storage
facility is difficult due to high viscosity and resistance to flow (filtered tailings for
stacking are transported to storage via truck). There also is potential for generation of
dusts (Witt et al. 2004). Thickened and paste tailings disposal is becoming more
widespread; past limitations were high costs and lack of suitable thickener technology
(Commonwealth of Australia 2007). This type of storage has less application at larger
operations where tailings ponds may serve a dual role of process and excess water
storage as well as tailings storage. Dry stacked tailings disposal is most applicable in arid
regions or in cold regions where water handling is difficult (Martin et al. 2002).

Mitigation measures for a TSF may include any combination of a liner, under-drains, and
decant systems when there is expectation of seepage or the presence of groundwater,
and prevention of the formation of low permeability lenses or layers on tailings beaches
that could cause future seepage or stability concerns (Commonwealth of Australia
2007). Liners can include a high-density polyethylene (HOPE) or other type of
geosynthetic material, a clay cover over an area of high hydraulic conductivity, or a
combination. A properly constructed clay liner could be expected to have a saturated
hydraulic conductivity of 10"8 m/s and a geomembrane to have a hydraulic conductivity
of ~ 10"10 m/s; however, the lifetime of a geomembrane may vary widely, depending on
a number of factors, including composition and site temperature. For example, Koerner
et al. (2011) presents that a nonexposed HOPE liner could have a predicted lifetime of
69 years at 40 °C to 446 years at 20 °C. Where geomembranes are used, a drainage
layer atop the membrane is commonly included to reduce the water pressure on the
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liner and minimize leakage. Liners may cover the entire impoundment area, or only the
pervious bedrock or porous soils. Full liners beneath TSFs are not always used;
however, there is a growing requirement to use liners to minimize risks of groundwater
contamination, with new mines in Australia being required to justify why one wouldn't
be required (Commonwealth of Australia 2007). Under-drains serve a dual purpose of
reducing water saturation of the tailings sediments to improve geotechnical strength
and safety of the facility as well as for directing drainage toward a storage area for
subsequent treatment. If seepage from the TSF is expected (or if observed during
monitoring), mitigation or remedial measures include interception trenches and/or
seepage recovery wells to be installed around the perimeter and downstream to
capture the water for redirection to a treatment facility. A spillway diversion commonly
is constructed to provide a catchment for precipitation runoff.

When processing ore from Zn, Cu, or Pb sulfide porphyry deposits, two tailings streams
are created, with one from the rougher circuit (to remove gangue material comprising
silicates and oxides) and one from the cleaner circuit (pyrite-rich). It is possible to use a
technique called "selective flotation" to separate most of the pyrite into the cleaner
circuit tailings (PAG) with the rougher tailings comprising mostly NAG. Traditionally,
these tailings streams were combined, but they could be separated, with the PAG being
discharged deeper into the TSF and the NAG discharged and used as a cover for the
PAG. Success is dependent upon the ore and the efficiency of a clean separation
(Martin et al. 2002).

In leaching of gold ore, mitigation practices include not locating leaching operations in
or near a water body, detoxification of materials prior to disposal or closure, and
ensuring that the solution can be contained in the presence of increased flows, up to
the maximum reasonable storm event (U.S. Environmental Protection Agency (U.S.EPA)
1995a). When tank leached, the tailings and spent solution are stored in the TSF. The
conventional method for recovery of gold from ore typically involves tank leaching with
dilute (100-500 ppm) sodium cyanide (Logsdon et al. 1999). Following leaching, either
zinc metal or activated carbon is added to the solution to recover the gold. The residual
solution either is treated in a water treatment plant or stored with the process tailings
in the TSF pond. When stored in the TSF pond, the cyanide concentrations should be
such that there would be no adverse effects to wildlife, such as birds landing on the
pond. Although rates could depend on the climate and other site specifics, cyanide
concentrations are known to decrease through natural attenuation, including
volatilization and subsequent interactions with UV, biological oxidation, and
precipitation (Logsdon et al. 1999).

Monitoring groundwater quality for contaminant transport includes piezometers for
groundwater mounding assessment. Regular inspections/monitoring for TSF stability
include evaluation of seepage discharges through the dams, foundations, abutments,
and liners; phreatic surface in ponds and dams; pore pressures; horizontal and vertical
movement; and the status of leak detection systems, secondary containment, auto flow
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measurement and fault alarms, condition of pump and pipelines. Azam and Li (Azam
and Li 2010) point out the importance of monitoring pore water pressures and
embankment deformation based on correlation with several types of failure, and
provides a basis to rectify the situation before failure ensues.

2.1.2 Closure and Post-Closure

Closure requires the TSF to have either a continuous water cover or an engineered cover
to prevent oxidation of tailings. Sufficient capital is required to finance inspections,
maintenance, and repairs in post-closure for as long as the tailings exist.

Closure of a TSF includes containment/encapsulation, minimization of seepage,
stabilization with a surface cover to prevent erosion and infiltration, diversions and
collection of precipitation, and design of final landform to minimize post-closure
maintenance (the final landform desired should be considered during the planning
phase). There are a number of cover types and depths that can be chosen; the choice is
site specific and depends on climate, type and volume of tailings, size and geometry of
the TSF, available cover material, and the end-use for the property (e.g., (O'Kane and
Wels 2003, Wilson et al. 2003). A conventional cover is typically a low hydraulic
conductivity layer of clay (and/or a geosynthetic membrane) overlain with protective
soil layers and generally 1.2 to 1.5 meters thick (O'Kane and Wels 2003). The soil layers
minimize deterioration due to desiccation, frost action, erosion, animal burrowing, and
infiltration of plant roots [(Caldwell and Reith 1993) as reported in (O'Kane and Wels
2003)]. Covers are not used for submerged tailings, and placing covers on tailings that
have not been dewatered can cause future stability problems
(http://www.idl.idaho.gov/Bureau/Minerals/bmp manuall9927pl6-ch4.pdf).

Diversions and spillway structures are constructed to minimize potential erosion of the
cover from surface water. Traditionally, water in TSF ponds has been drained as
completely as possible prior to closure to reduce potential for overtopping and erosion
of the embankments; raising water levels in large dams could cause considerable long-
term risk. However, water covers might be used when feasible to maintain a
submerged condition, such as in regions where the hydrology is well-understood and
the terrain is flat, such as has been used and encouraged in Canada (Martin et al. 2002).

Regardless of the type of reclamation used for closure, the reclaimed facility must be
monitored and maintained to ensure stability over time. Post-closure monitoring for
contaminant transport is the same as during the operational phase, with piezometers
for assessment of ground water mounding and monitoring wells for groundwater
quality. The reclaimed facility should be monitored for any deformations, structural
changes, or weaknesses, and the surfaces should be inspected for intrusion by animals,
humans, or vegetation, any of which could compromise long-term stability.
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2.2 ACCIDENTS AND FAILURES

The main causes of physical failures of tailings storage facilities are related to 1) a lack of
control on the water balance; 2) lack of control on construction; and 3) a general lack of
understanding of the features that control safe operating conditions (International
Commission on Large Dams (ICOLD) 2001). Additionally, the upstream method for dam
construction was found to be more prone to failure as compared to those constructed
via the downstream method, most likely due to their being constructed with residual
coarse tailings materials.

In order of prevalence, failure mechanisms observed forTSFs are slope instability,
earthquakes, overtopping, inadequate foundations, seepage, and structural problems
(Blight and Fourie 2003, Commonwealth of Australia 2007). Failure during operation
could occur from any of the following: 1) rupture of delivery pipeline or decant water
return pipeline; 2) rainfall induced erosion or piping of outer tailings face; 3)
geotechnical failure or excessive deformation of containment dyke; 4) overfilling of the
tailings storage facility leading to overtopping by water; 5) seepage through
containment dyke; and/or 6) seepage into the foundation. In addition to the above
(aside from deliver and return pipelines), failures post-closure could result from failure
of the spillway (if present), or failure of the cover through internal or external forces,
including weathering of materials, erosion, extreme weather events, or intrusion by
vegetation or wildlife (Commonwealth of Australia 2007, Witt et al. 2004).

Earthquakes can cause liquefaction, which is a process in which a soil mass loses shear
resistance through increased water pressure. Liquefaction in the absence of an
earthquake is called static liquefaction. Static liquefaction can result from slope
instability or another mechanism. As reported in Davies (Davies 2001), upstream
constructed dams are "more susceptible to liquefaction flow events and are solely
responsible for all major static liquefaction events"; the author also states that
earthquakes are of little concern for non-upstream dams. Liquefaction of a large
volume of tailings causes them to flow out of a breach as a viscous liquid which is
capable of moving long distances before coming to rest. For example, 3 million cubic
meters of tailings escaped at Bafokeng, South Africa, and travelled 42 km before the
remaining 2 million cubic meters was stopped by flowing into a water retention dam
(Blight and Fourie 2003). Conventional TSF materials can have very low shear strength
and are susceptible to liquefaction. Therefore, earthquake-induced liquefaction is a key
design consideration to minimize risks of failure resulting from an earthquake event
(Martin et al. 2002). Earthquake risks also are reduced when tailings have a higher
density or are dry tailings.

Overtopping is caused by excessive water inflow, such as through precipitation or rapid
snowmelt, and is cited as being the primary failure mode for almost half of all reported
incidents occurring at inactive dams (Davies 2001). Overtopping can result in erosion
and breaching of the embankment to release tailings and contaminated water
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downstream. Internal erosion by water (called piping) is a slow process and related to
seepage/infiltration causing internal water pressures to exceed the critical hydraulic
gradient and result in a pathway through which particles are carried. Guidelines exist
forTSF design to minimize this risk; however, Jantzer and Knutsson (Jantzer and
Knutsson 2010) believe that, at least in Sweden, critical gradient guidelines are
insufficient to yield long-term stability. Unstable materials experience particle migration
at much lower hydraulic gradients than do more stable or compacted materials.

Structural failure could result in the release of large amounts of tailings solids and
water; for example, a failure at Church Rock, New Mexico released 357,000 cubic
meters of tailings water and ~990 tons of solids into an adjacent stream in 1979 (Witt et
al. 2004). Closed facilities are more prone to failures caused by external erosion,
primarily because of a lack of frequent monitoring, which occurs more easily when the
site is occupied daily during active mining. Diversion ditches help prevent erosion by
redirecting surface flow away from the TSF. Usually, failures result from a combination
of factors, with climate, tailings properties, and geometry influencing which of these
processes is likely to be the most prominent cause. Seepage-related failures are the
main failure mode for tailings dams constructed using downstream or centerline
methods (Davies 2001). Increases in seepage rates or turbidity can be key indicators of
a developing failure situation (Alaska Department of Natural Resources (AK DNR) 2005).
Thus, adequate planning, suitable design, and monitoring and control of operation and
post closure may prevent deteriorative actions.

The failure rate of tailings dams depends directly on the engineering methods used in
design and the monitoring and inspection programs in the other mine-life stages.
According to Witt et al. (Witt et al. 2004), with an assumption of 3500 worldwide tailings
dams and failure rates of 2-5 dams per year, the annual probability of a TSF failure is
between 1 in 700 to 1 in 1750, in contrast to < 1 in 10,000 apparent for conventional
water dams. Using data obtained from the World Information Service of Energy (WISE,
www.wise-uranium.org/mdaf.html) for the 10 years prior to March 22, 2011, Chambers
and Higman (Chambers and Higman 2011) report that the worldwide failure rate of
tailings dams has remained at 1 failure every 8 months (i.e. two failures every 3 years).
Azam and Li (Azam and Li 2010), using databases from the United Nations
Environmental Protection (UNEP), the International Commission on Large Dams (ICOLD),
the World Information Service of Energy (WISE), the United States Commission on Large
Dams (USCOLD), and the United States Environmental Protection Agency (U.S. EPA),
found that causes of observed failures occurring in the years of 2000-2009, regardless of
country (e.g., North American, South American, European, Asian, African, and
Australian), were unusual weather, management, seepage, instability, and defect, in
order of decreasing percentage contribution. Weather causes were observed to have
increased by 15% from pre-2000 failures and management issues by 20%. Azam and Li
(Azam and Li 2010) report that failures in all but Europe and Asia have decreased since
2000; this is attributed to improved engineering practices, with none from 2000-2009
being due to subsidence of the foundation or to overtopping. Additionally, seismic
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liquefaction was not a causal mechanism in failures between 2000 and 2009, but
accounted for 14% of failures prior to 2000. Data presented indicate that failures
peaked to about 5 per year in the 1960's through the 1980's and has dropped to about 2
per year over the last 20 years, with the frequency of failure occurrences shifting to
developing countries. The authors also estimate that, on average, one fifth of the
stored tailings are released resulting from tailings dam failure. Dalpatram (Dalpatram
2011) presented a slide at a recent Workshop on Dam Break Analysis that indicated
volumes released range from 20-40% of the stored tailings.

Reports of failures generally discuss physical failures causing a large release of tailings
and/or water, but failure in design, construction, monitoring, and/or maintenance of the
entire TSF system could result in slow release of contaminants into surface water or
groundwater. Additionally, releases could result from compromise to the cover over
PAG material or from inaccurate prediction of acid-generation potential for storage of
PAG versus NAG tailings.
3. PIT

Following open-pit mining, a wide and deep hole remains that typically is filled in (or fills
naturally) with water to form a pit lake. The source of environmental influence from
pits and resultant lakes includes their size and the potential for acid-rock drainage (ARD)
from dissolution of sulfidic minerals exposed on pit walls. Contaminated water may
seep into groundwater, overflow into surface water, or adversely affect waterfowl
landing in the formed pit lake. Additionally, the steep pit slopes generally remain after
closure and continue to pose a risk to wildlife from falling into the pit and not being able
to get out. Mitigation methods chosen will depend on site-specific considerations, as
well as the future use envisioned for the pit (McCullough 2011).

3.1 STANDARD PRACTICES

During the operational phase, pit walls are monitored closely for signs of weakness that
might lead to a failure. Suggested means for reducing operational hazards from a slope
failure in a pit include "1) safe geotechnical designs; 2) secondary supports or rock fall
catchment systems; 3) monitoring devices for adequate advance warning of impending
failures; and 4) proper and sufficient scaling of loose/dangerous material from
highwalls" (Girard 2001).

Modeling can assist in identifying if a pit lake will become acidic at closure. If acidity is
anticipated, mitigation measures to control for acid generation and/or for ensuring that
any such acidic water would not migrate to surface or groundwater must be considered.
At closure, pits may be used as a repository for waste rock, followed by sealing of the
area against air and water exposure, such as by an isolation cover, to minimize the
potential for generation of acidity. Partial backfilling and regrading of upper levels with
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subsequent vegetation and/or creation of wetlands provides for passive water
treatment. Most commonly, pits naturally fill with water over time, from groundwater,
surface water, and precipitation inflows. Filling may be accelerated by pumping water
from the TSF or other storage ponds both to minimize exposure of any PAG rock wall
materials and to balance high pore water pressures to help prevent slope failures. Once
the desired water level is achieved to retain the pit lake as a sink, water can be directed
away from entering the pit through diversions that were used during the operational
phase, or pit water can be pumped and treated prior to discharge to a surface water
body.

PAG waste rock and/or PAG tailings may be stored submerged in the pit lake to
minimize exposure to oxygen. If production of ARD and contaminant ions is anticipated
and exposed surfaces cannot be covered or sealed against oxidation, chemicals may be
added to the pit lake to neutralize acidity and precipitate metals. Organic material and
microorganisms may be added and conditions optimized for sulfate-reducing bacteria
(SRB) to allow for formation of insoluble metal sulfides in the anaerobic regions of the
lake. If pit water becomes contaminated with metals and/or acidity, treatment of any
water leaving the pit would be necessary to meet applicable water quality standards
prior to any discharge.

Barriers, such as fences, berms, or other structures, are constructed to mitigate
unauthorized access by humans and access by wildlife and should be monitored and
maintained regularly for stability.
4. UNDERGROUND MINE WORKINGS

The sources of potential environmental influences from underground mining are similar
to those for open pit mining, i.e., waste rock piles, tailings, dust, and wastewater. An
additional source of potential impact to both groundwater and surface water is from
acid rock drainage from tunnels and adits created during mining. Depending on many
factors, including the depth of the underground mine to the surface and the strength of
the overburden rock, mine workings have the potential to subside and may create a
depression in the landscape and alterations in surface and ground water flows.

4.1 STANDARD PRACTICES

The mitigation measures to prevent potential significant environmental impacts from
wastes originating from underground mining are similar to those for open pit mining. In
addition, waste rock and or tailings may be disposed in mined out tunnels, which may
assist in minimizing impacts from subsidence. Additionally, void-filling grout may be
used to mitigate subsidence. In regions where there is potential for ground water
interaction with mine workings, cracks may be sealed with grouting or other material.
Additionally, groundwater flow paths may be intercepted (such as by grouting of faults
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and sheer zones, or by a grout curtain) and thus redirected to avoid the mined out area,
minimizing contact of the water with potentially acid-generating rock surfaces (e.g.,
(Wireman and Stover 2011)). In some cases, the mine workings are flooded, which, if
done prior to oxidation occurring on PAG surfaces and kept anaerobic, will minimize the
formation of acidic drainage.

5.0 DUST

Mining activities can generate dust during multiple stages in the operational phase,
including those generated during construction of roads, trucking of materials, and heavy
equipment exhaust. Fugitive dusts are diffuse and generated through wind erosion of
large areas, including waste rock piles, tailings, the pit, and other disturbed areas. Other
dusts originate at locations where processes are occurring, such as blasting, crushing,
grinding, and milling. Dusts containing metals from mining activity pose human health
concerns through inhalation. The particles are carried by the wind and may cause
environmental concerns through sedimentation in water bodies and/or by being
transported further downstream.

5.1 STANDARD PRACTICES

Mitigation of dust from processing points within mining operations can include
collection by dry collectors, wet scrubbers, enclosures at the source, and/or wetting of
surfaces (Commonwealth of Australia 1998). A cover on a truck bed can minimize dusts
originating from materials being hauled. Wetting of surfaces is most useful for active
blasting, haul roads, and material movement and placement activities, and may involve
the use of water or water mixed with a chemical dust suppressant. Typically, dust from
waste rock piles is controlled by wetting during the operational phase. During closure,
waste rock piles are covered and vegetated; this can be done as piles are completed
during the operational phase to minimize potential for dust production. Although wet
slurry tailings do not pose a dust issue, dust from large dry beaches of tailings facilities is
a concern, and wetting or using special products to stabilize the surfaces is used for
temporary wind erosion and dust control. Tailings beaches are covered with gravel (or
other material) and may be vegetated during closure.
6. STORM AND WASTEWATER

Storm and wastewater have the potential to contain suspended sediment and
particulate and dissolved contaminants that could contaminant water bodies if they
were to leave the site untreated. The main environmental influences originate from
seepage of contaminants into groundwater, leakage through barriers (e.g., tailings
embankment), and flooding or washout into nearby surface water bodies.
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6.1 STANDARD PRACTICES

Mitigation of stormwater begins with designing components using an accurate site
water balance to assure adequate storage and treatment capacity. Conventionally,
runoff and seepage are diverted through ditches and diversion channels to a treatment
pond, or to a settling pond if the water source is solely from precipitation. Water from
settling ponds can be decanted and discharged (if it meets required water quality
criteria), or used in the mining process if of sufficient quality. Spillway diversions
commonly are constructed around waste rock and tailings facilities to provide
catchments for precipitation runoff. Excess water in tailings ponds is controlled through
removal and treatment for use in the mining processes or discharge to the surface
water. Traditionally, water in TSF ponds is drained as completely as possible prior to
closure to minimize potential for overtopping due to precipitation. For TSF ponds
containing sub-aqueously disposed PAG tailings, sufficient water would remain in the
pond post-closure to ensure they remain isolated from oxygen.

Stormwater from undisturbed areas may require treatment only for sediment, which is
accomplished through simple settling in a sedimentation pond. Stormwater from
disturbed areas and mining wastewater is treated via either active or passive methods
prior to being used in the mining process or released into a water body. Active
treatment generally involves a chemical addition (e.g., lime, alum, iron oxides) to
precipitate or adsorb metals and metalloids, or a physical process (e.g., reverse
osmosis). Active treatments also include microbial methods, such as the use of
contained bioreactors. Passive treatments are those that capitalize on natural
processes and do not require constant reagent addition for operation. Wetlands are an
example of a commonly used passive treatment system for water contaminants at
mining sites, as are anaerobic biochemical reactors (also called sulfate-reducing
bioreactors). Although they can be used during the operational phase, passive
treatment systems are most commonly used post-closure.
7. CHEMICALS

Chemicals used at mining sites have the potential to enter into the environment through
accidental spills during transport, storage, and/or use, or from excess usage in processes
to recover metals being mined (e.g., during flotation/frothing, cyanidation, or smelting).

7.1 STANDARD PRACTICES

Standard practices include having a chemical hygiene plan and training of all personnel
in the proper handling of chemicals, including how to deal with cleanup of spills,
provision of spill kits and personal protective equipment, and availability of MSDS for
consultation (e.g., see (Logsdon et al. 1999)). Secondary containment (dikes or
collection basins) must be used and incompatible chemicals must be isolated from one
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another during storage and use. Storage containers are commonly equipped with
indicators and instrumentation to monitor levels in tanks to ensure that a spill does not
occur, or that any spill/leak is captures quickly when it begins.

8. PIPELINES

A slurry-concentrate pipeline break or spill has potential to affect aquatic life adversely,
if into a nearby stream. Additionally, placement of pipelines results in land disturbance
and can cause soil/sediment to enter streams through runoff.

8.1 STANDARD PRACTICES

Pipelines that might be necessary for mining operations include those for transport of
slurry, return water, and fuel for the mining site. Standard practices for construction,
operation, and monitoring of slurry pipelines are available from the American Society of
Mechanical Engineers (American Society of Mechanical Engineers (ASME) 2003).

Mitigation measures for pipelines include using the proper pipe material, protection
against leaks, breaks, and corrosion, containment drains or sumps along the corridor,
and secondary containment of the pipeline where crossing a river or transportation
route. Protection includes increased wall thickness, corrosion inhibitors, and internal
linings or coatings. Joints, welds, valves, etc. are designed to accommodate expected
stress, as based on flows desired for the pipeline. Pipelines may be equipped with
monitoring systems to detect flow, temperature, or pressure changes, along with alarms
and automatic shutoffs. Pipelines are stress-tested for leaks and weaknesses prior to
being placed into operation; and they require routine inspections over the course of
their use. Mitigation of construction impacts, such as soil erosion and turbid storm
water runoff caused by pipe installation (e.g., excavation and boring), can include silt
fences, ditches, or other temporary diversions. Pipelines that are constructed near
water bodies require containment and may or may not be placed above ground on
bridge structures.
9. NON-MINING MATERIAL AND DOMESTIC WASTE

Mining operations produce a number of wastes in addition to waste mineral materials.
Additionally, there is domestic waste produced from persons employed. These wastes
have the potential to attract wildlife (food wastes), or to contaminate water bodies
(e.g., sewage waste) and thus must be managed.

9.1 NON-MINING MATERIAL AND DOMESTIC WASTE
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At remote mining sites, non-hazardous wastes generally are managed on site. Non-
hazardous solid wastes typically would be disposed in engineered solid waste landfills
that meet regulatory requirements. For some types of wastes, and in some locations,
incineration may be an acceptable alternative. Recycling of segregated wastes such as
paper and plastic may be preferable, but high transportation costs could make this
option economically unattractive.

Sanitary waste often is treated via a decentralized system (e.g., septic tank) or in a
packaged sewage treatment plant, with the effluent discharged after verification that it
meets the permitted discharge standards. Sewage sludge may be land-farmed, hauled
to a licensed treatment facility, or land filled on site depending on local requirements.
10. COMPENSATORY MITIGATION

Compensatory mitigation refers to the restoration, establishment, enhancement, and/or
preservation of wetlands, streams, or other aquatic resources
(http://www.nap.usace.army.mil/cenap-
op/regulatory/documents/mitigation/mitigation-qa.pdf). The fundamental objective of
compensatory mitigation is to offset environmental losses resulting from unavoidable
impacts to waters of the United States authorized by Clean Water Act Section 404
permits issued by the U.S. Army Corps of Engineers (the Corps) (40 CFR Part
230.93(a)(l)). Compensatory mitigation becomes an option only after all opportunities
for aquatic resource impact avoidance and minimization have been exhausted (40 CFR
Part 230.91(c)). The Corps is responsible for determining the appropriate form and
amount of compensatory mitigation required (40 CFR Part 230.93(a)(l))
(http://water.epa.gov/lawsregs/guidance/wetlands/upload/2003 05 30 wetlands CMi
tigation.pdf).

Compensatory mitigation should be located within the same watershed as the impact
site and where it is most likely to successfully replace lost functions and services (40 CFR
230.93(b)(l)). Compensatory mitigation can be achieved through four methods:
restoration, enhancement, establishment, or preservation (40 CFR Part 230.93(a)(2)).
Restoration is the reestablishment or rehabilitation of a wetland or other aquatic
resource with the goal of returning natural or historic functions and characteristics to a
former or degraded wetland. Success is measured as a gain of wetland function or
wetland acres, or both. Establishment or creation is the development of a wetland or
other aquatic resource where one did not exist previously. Success is measured as a net
gain in both acres and function of the aquatic resource. Enhancement includes activities
conducted within existing wetlands that heighten, intensify, or improve one or more
wetland functions. There is no net gain in acres of the aquatic resource, but often it is
done to provide gains in wetland function, such as improved floodwater retention, or
wildlife habitat. Preservation is the permanent protection of ecologically important
wetlands or other aquatic resources through implementation of legal and physical
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mechanisms, such as conservation easements and title transfers. Upland adjacent areas
may be included in the region to be preserved. This may be used only in certain
circumstances, including when the particular aquatic resource contributes significantly
to the ecological sustainability of the watershed.

There are three general mechanisms for achieving the four methods of compensatory
mitigation. These include 1) permittee-responsible mitigation; 2) mitigation banking;
and 3) in-lieu fee. Each of these is described briefly below:

1) Permittee-responsible mitigation is mitigation that is undertaken by the
permittee and they are completely responsible for the implementation and
success of the mitigation after the permit is issued. Mitigation may occur at the
site where the regulated activity caused a loss of the water resource, or it may
be conducted at a different location, but should be within the same watershed.
2) A mitigation bank is an area that includes wetlands, streams or other aquatic
resources that have been restored, established, enhanced, or preserved and set
aside to compensate for future conversions of aquatic resources for
developmental activities. The bank sponsor works with the Corps and other
resource agencies to establish the number of compensation credits the bank site
will generate. A permittee purchases credits from the bank to meet their
requirement for compensatory mitigation. The bank sponsor is responsible for
the success of the mitigation bank.
3) For in-lieu mitigation a permittee provides funds to a sponsor (public agency or
non-profit). This mechanism usually is used after impacts are present and
typically occurs off-site. Usually, a sponsor collects funds from multiple
permittees and pools the resources to build and maintain the mitigation site(s),
and the sponsor is responsible for the success of these mitigation sites.

In the 2008 Final Rule for Compensatory Mitigation for Losses of Aquatic Resources (40
CFR Part 230), it was recognized that streams are difficult to replace; thus, preservation,
rehabilitation or enhancement are emphasized instead of establishment and re-
establishment. In addition, mitigated streams are required to be monitored for a
minimum of five years and evaluated based on ecological performance standards.
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