?/EPA
EPA/600/R-10/180 I December 2010 | vwwv.epa.gov/athens
United States
Environmental Protection
Agency
Ecosystem Services Research
Program (ESRP)
Albemarle-Pamlico Watershed
and Estuary Study (APWES)
Research Plan
Office of Research and Development
National Exposure Research Laboratory, Ecosystems Research Division, Athens, GA 30605
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EPA/600/R-10/180
December 2010
www.epa.gov/athens
Ecosystem Services Research Program
(ESRP)
Albemarle-Pamlico Watershed and Estuary
Study (APWES) Research Plan
Project Co-Leaders:
Brenda Rashleigh, EPA/ORD/National Exposure Research Laboratory
(NERL)/Ecosystems Research Division, Athens, GA
Darryl Keith, EPA/ORD/National Health and Environmental Effects Research Laboratory
(NHEERL)/Atlantic Ecology Division, Narragansett, Rl
Core Writing Team:
Dave Williams, EPA/ORD/NERL/ Environmental Science Division, RTP, NC
Deborah Mangis, EPA/ORD/NERL/Environmental Science Division, RTP, NC
Donna Schwede, EPA/ORD/NERL/Atmospheric Modeling Division, RTP, NC
Dorsey Worthy, EPA/ORD/NERL/Environmental Science Division, RTP, NC
John Names, EPA/ORD/NERL, Environmental Science Division, RTP, NC
Katie Pugh, Centers for Disease Control (CDC) Agency for Toxic Substances and
Disease Registry (ATSDR), Atlanta, GA
Steven C. McCutcheon EPA/ORD/NERL/Ecosystems Research Division, Athens, GA
National Exposure Research Laboratory
Office of Research and Development
Athens, GA 30605
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APWES Team Members
EPANERLESD
EPA NERL AMAD
Donna Schwede
Ellen Cooler
Jesse Bash
Rob Pinder
Robin Denis
EPA NERL EERD
Brad Autrey
Chuck Lane
Heather Golden
Joe Flotemersch
EPANHEERL
CDC ATSDR
Betsy Smith
Bill Kepner
Caroline Erickson
Dave Bradford
Dave Holland
David Williams
Deb Chaloud
Deb Mangis
Drew Pilant
Dorsey Worthy
Gail Harris
Jay Christiansen
Joe Sickles
John Names
Keith Endres
Megan Van Fossen
Ralph Baumgardner
Ric Lopez
Ross Lunetta
EPA NERL ERD
Brenda Rashleigh
Chris Knightes
Katie Price
Mark Gabriel
Roger Burke
Stephen Kraemer
Steve McCutcheon
Autumn Oczkowski
Bryan Milstead
Cathleen Wigand
Darryl Keith
Don Cobb
Ed Dettmann
Glenn Thursby
Henry Walker
Janet Nye
Ken Rocha
Kristen Hychka
Laura Coiro
Laura Jackson
Marilyn ten Brink
Mohamed Abdelrhman
Marty Chintala
Sandra Robinson
Steve Hale
Suzy Ayvasian
Ted DeWitt
Warren Boothman
EPANRMRL
Ann Vega
Brian Dyson
John Walker
Tim Canfield
Verle Hansen
Katie Pugh
Contractors
Tom Stockton
Special Govt. Employees
Ken Reckhow
Roel Boumans
EPA NCEA
Tom Johnson
Chris Weaver
EPA Region 4
Linda Rimer
Mel Parsons
Pete Kalla
EPAOW
Rich Sumner
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NOTICE
This work has been subject to external peer and administrative review, and has been
approved for publication as an EPA document. Mention of trade names or commercial
products does not constitute endorsement or recommendation for use.
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TABLE OF CONTENTS
ABSTRACT 1
INTRODUCTION 2
RESEARCH APPROACH 10
1. Mapping and Monitoring 10
2. Modeling 19
3. Decision Support 26
SYNTHESIS AND FUTURE DIRECTIONS 28
ACKNOWLEDGEMENTS 30
REFERENCES 31
APPENDIX 1 36
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ABSTRACT
The APWES is a place-based study for the U.S. EPA Ecosystem Services
Research Program conducted through the collaboration across the EPA Office of
Research and Development. The mission of the APWES is to develop ecosystem
services science to inform watershed and coastal management decisions in the
Albemarle-Pamlico watershed and estuary in North Carolina and Virginia. Over the next
three years (2011 to 2014), the study will apply analysis of seven ecosystem services
(clean air; clean water; climate resilience; flood and storm protection; food, fiber, and
fuel; recreation; and biodiversity) to these management decisions. This study uses a
systems approach to address the drivers, pressures, state, ecosystem services, and
management decisions in the Albemarle-Pamlico watershed and estuary.
APWES research will be conducted according to three goals: 1) mapping and
monitoring, 2) modeling, and 3) decision support. First, mapping and monitoring
projects will develop methods to quantify ecosystem services, as well as drivers and
pressures to the system. Results will lead to an assessment of ecosystem services,
and support modeling efforts. Second, modeling will be used to relate changes in
drivers and pressures to changes in ecosystem services. This research will include
empirical and mechanistic modeling for the air, watershed, and estuary, informed by
mapping and monitoring, and the linkage of models within modeling frameworks. Third,
decision support tools will be developed to understand how management decisions alter
services, so that quantified services can be used to inform watershed and estuary
management decisions. For this goal, decision alternatives developed with stakeholder
input and decision support tools, including an interactive web-based software
application and Bayesian networks, will be developed and applied at multiple scales.
Ecosystem services will be used to inform decisions in the Albemarle-Pamlico
watershed and estuary -the study will focus primarily on decisions related to EPA
regulatory authority in air quality, wetlands, and water quality, and the related issue of
water quantity. Tools developed for this work can also inform decisions related to
reservoir management, species conservation, and climate adaptation. The APWES will
examine tradeoffs or synergies among services under alternative management
decisions, and seeks to understand how ecosystems can be managed sustainably for
ecosystem protection and economic benefit. This study can also serve as a regional
pilot for EPA Sustainable and Healthy Communities Research Program, to understand
how the natural and built environments interact to affect community well-being and
sustainability.
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INTRODUCTION
EPA ESRP
Ecosystem services are the benefits that humans derive from ecosystems.
Although these services, such as the provisioning of clean air and water, have
traditionally been considered gifts of nature, recent advances in ecological and resource
economics suggest that these services need to be included in economic analyses of
costs and benefits (MEA 2005). An ecosystem services approach results in increased
awareness of the environmental and economic costs of all goods and services and will
help promote effective environmental policy and management strategies. The
Ecosystem Services Research Program (ESRP) is a multi-year research initiative by the
U.S. EPA to transform the way stakeholders understand and respond to environmental
issues by making clear how our management choices affect the type, quality and
magnitude of the services we receive from ecosystems (EPA 2008a). The program
examines tradeoffs or synergies among services, and seeks to understand how we can
manage ecosystems sustainably for ecosystem protection and economic benefit.
The Albemarle-Pamlico Watershed Study is one of five ESRP place-based
studies. The place-based studies are designed to "...illustrate how regional and local
managers can proactively use alternative future scenarios to conserve and enhance
ecosystem goods and services" (U.S. EPA 2008a). The mission of the APWES is to
use ecosystem services science to inform watershed decisions in the Albemarle-
Pamlico watershed and estuary. Research will be conducted from 2011 to 2014 by
multiple divisions of the EPA Office of Research and Development: the National
Exposure Research Laboratory (NERL) Ecosystems Research Division (ERD) in
Athens, GA; Environmental Sciences Division (ESD) in Las Vegas, NV and Research
Triangle Park, NC; Ecological Exposure Research Division (EERD) in Cincinnati, OH;
Atmospheric Modeling and Analysis Division (AMAD) in Research Triangle Park, NC,
National Health and Ecological Effects Research Laboratory (NHEERL) Atlantic Ecology
Division (AED) in Narragansett, Rl; National Risk Management Research Laboratory
(NRMRL) Air Pollution Prevention and Control Division (APPCD), Research Triangle
Park, NC; and National Center for Environmental Assessment (NCEA) in Washington,
DC with assistance from outside partners and collaborators.
The APWES is closely integrated with the ESRP Nitrogen and Wetlands
Programs. The ESRP-Nitrogen program is focusing largely on national scale issues of
nitrogen loading, removal, and impacts on ecosystems across the U.S. (Compton et al.
2009). APWES will develop nitrogen response relationships for ecosystem services
provided by wetlands and waters, and produce high resolution maps of watershed-scale
nitrogen loading and removal as well as predict estimates of probable changes in other
ecosystem services affected by changes in nitrogen loading. In this framework, APWES
data and information will be used to compare nitrogen response functions in a variety of
geographic settings where sensitivity to nitrogen loading may vary, to inform more
explicit national scale modeling efforts to examine scenarios associated with reactive
nitrogen, and provide nitrogen input and output data for national data layers. Similarly,
the ESRP Wetlands team is focused on national mapping efforts, and local-scale work
done in APWES will inform this effort.
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DESCRIPTION OF THE STUDY SITE
The Albemarle-Pamlico Watershed (APW) consists of about 80,000 km2 of land
and water in thirty-six counties in North Carolina and sixteen counties in Virginia (Figure
1). Six major freshwater river basins flow into the sounds- the Pasqotank, Roanoke,
Chowan rivers flow into Albemarle Sound; the Tar-Pamlico and Neuse rivers flow into
the Pamlico Sound; and the White Oak flows into Bogue Sound. Land cover in the
watershed is predominantly forest (45 %), wetlands (14 %) and cultivated cropland and
pasture (26 %); urban land cover accounts for less than 7 % (USEPA/USGS 2010).
The region features a variety of habitat types, including pocosins (southeastern shrub
bogs), pine savannahs, hardwood swamp forests, bald cypress swamps, salt marshes,
brackish marshes, freshwater marshes and beds of submerged aquatic vegetation
(SAV), and beaches. The Roanoke drainage is known for the most distinctive
freshwater fish communities on the Atlantic Slope of the U.S. (Virginia OCR 2010).
Significant ecological features of the Albemarle-Pamlico watershed and estuary are the
numerous freshwater tidal wetland communities with rare species of vascular plants
such as Coastal Plan Bottomland Hardwoods and Cypress-Gum Swamps that merge
with vast, flat estuarine tidal marsh and forested wetlands on the estuary margins. The
Albemarle-Pamlico estuarine system is the largest lagoonal estuarine system in the
U.S. and second largest U.S. estuary. Annually, the system generates >$4 billion in
fisheries, employment, and tourism (NC Div. of Marine Fisheries 1995, SELC 2009).
MQN1
/ FR.SWKL
FI nvn
FORSYTH
GULFORC
River Basins
PASQUOTANK
CHOWAN
ROANOKE
TAR-PAMLICO
NEUSE
WHITE OAK
APNEP Study Area
0 10 20 40 60
Figure 1. Albemarle-Pamlico watershed and estuary showing major river basins and county boundaries.
Figure supplied by the APNEP ( http://www.apnep.org).
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More than three million people live in the APW, and many habitats and waters
are affected by human activities. The most impaired river basins are the Neuse and
Tar-Pamlico River basins, based on Aquatic Life Use Support, Recreation, and Fish
Consumption (Deamer 2009). For more than thirty years, the Neuse River estuary has
experienced harmful algal blooms, outbreaks of toxic microorganisms, and fish kills from
nitrogen overload (Borsuk et a/. 2001). Because of this impairment, the APWES can
serve as a mesocosm for nutrient issues across the eastern U.S. Based on the
substantial available body of science from past and current nutrient studies, the
Albemarle-Pamlico watershed is a good study region to examine the effects of multiple
pressures on high-value resources and services. Results of the APWES will be
relevant to other Atlantic drainage systems to the north (e.g., Chesapeake Bay) and
south (e.g., Savannah River Basin), where pressures and resources are similar.
ECOSYSTEM SERVICES IN THE ALEMARLE-PAMLICO WATERSHED & ESTUARY
Based on literature and discussions with stakeholders, we focus on seven main
ecosystem services for the APWES (Table 1). To be consistent with the overall ESRP
approach, we only consider final ecosystem services, which are biophysical indicators
representing the last contribution of the ecosystem (Boyd and Banzhaf 2007). For
example, for the service of recreation, the population size of sport fish is a final,
measurable endpoint. These services are consistent with results from public hearings
and surveys of stakeholders concerning the impairment of the Neuse River estuary,
(Borsuk et a/. 2001). Table 1 is also similar to the water quality use support ratings
recognized by the NC Department Environment and Natural Resources (NCDENR
2007): aquatic life, including fishing and shellfishing; fish consumption (i.e., "fishing"
through sport and commercial methods); recreation, such as swimming, boating, and
waterskiing; and biological integrity, the ecosystem capability to support and maintain a
balanced community of organisms having structure and function similar to that of
reference conditions. Important environmental services in the region, including energy
generation, transportation, and mining can be incorporated in the future. The
understanding of final services is a research question for ESRP (Ringold et a/. 2009).
In general, a valuation approach is necessary for putting services in terms that
can best inform decisions. Some services (e.g., fisheries and forestry) already have
monetary value; other services can be valued by employing different environmental
economics valuation methods, including hedonic pricing, the travel cost method, and
contingent valuation. Hedonic pricing, or revealed preference, is an indirect method that
looks at the value individuals place on a particular ecosystem service through property
values. For example, properties near a lake have higher values because of the
environmental amenities the lake provides. Travel cost is also an indirect method
where the value people place on ecosystem services is inferred by measuring the costs
they incur in order to experience the services (Perman et al. 2003). This method is used
to measure the value of recreational services. Contingent valuation is a direct method
that involves asking a segment of the population about their willingness to pay for or
willingness to accept a particular environmental change (e.g., Weber and Stewart
2008). The APWES will also assess who receives the benefits and who pays the costs
for various ecosystem service tradeoffs.
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Table 1. APWES Ecosystems Services, Indicators, and Associated APWES Projects
Ecosystem Definition Service Indicators APWES APWES
Services
Mapping
and
Monitoring1
Modeling/
Clean air
Clean
water
Climate
resilience
Air quality for
human health,
clear air for
visibility and safety
Water quality and
quantity used by
humans for
drinking,
agricultural, and
industrial uses
Carbon
sequestration
capacity, N2O
emissions
Air quality measurements
Time series of flow and water
quality measurement
Amount sequestered/time by
vegetation
Estimated emissions
Aq
Em, Fp
F, E, A
Wa
W
Flood and Avoidance of
storm damages from
protection flood and storms
Food, Agricultural
Fiber, and products, forest
Fuel products,
fish/shellfish
consumed by
humans
Recreation Boating,
swimming,
birdwatching
(fishing is
considered under
food)
Areal extent of wetlands Wa, Fp W
Amount and quality of La H , F, E
crops/livestock
Amount and health of target tree
species
Fish and shellfish populations
Bacteria and chemical content
Water quantity Ts, Em F, E, S
Bacterial concentrations in
recognized swimming areas
Populations of watchable birds -
Important bird habitats include
gull/tern/skimmer colonies and
colonial wading birds colonies as
well as marsh bird nest areas.
Biodiversity
Sustainability of
iconic species for
existence value
Habitat suitability and population
viability for selected species -
fish, amphibians, shellfish
Ts, Fp
1 Aq= Air quality monitoring (1.1); La = Landscape analysis (1.2.1, 1.2.2, 1.2.3); Ts = Mapping terrestrial
species (1,2,4); Fp = Functional process zones (1.2.5); Wa = Wetland assessment (1.2.6, 1.2.7, 1.3.1,
1.3.2); Em = Estuarine monitoring - harmful algae blooms, hypoxia (1.3.3, 1.3.4, 1.3.5).
2 A = CMAQ Air model (2.1); F = Freshwater quality and quality models (2.2.1, 2.2.2, 2,2,3); E =
Estuarine hydrodynamic and water quality models (2.3.1, 2.3.2); S = Habitat and population models for
terrestrial species (2.2.6), freshwater fish (2.2.5), and estuarine fish and shellfish (2.3.4); W = Wetlands
models (2.2.4, 2.3.3). Production functions (2.3.5) will be used to relate ecosystem state to services.
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ALBEMARLE-PAMLICO WATERSHED AND ESTUARY DECISIONS
Watershed and estuary decision-making occurs for many issues at multiple
levels of governance. We consider classes of decisions in Table 2, developed from a
literature review, public listening sessions, and discussions with stakeholders. The
APWES will focus primarily on decisions related to water quality, water quantity, and
wetlands. Although current decision-making occurs separately in these three areas,
our vision is that these decisions are considered together in an ecosystem services
context. Also, the EPA National Ambient Air Quality Standards NOx/SOx five-year
review will occur in 2015, and will include nitrogen and services science supporting
information. The Neuse River basin was a study area for the previous review, so it will
likely be a focus in 2015 (U.S. EPA 2008b). We aim to meet short-term science needs
for these decisions, and to provide a longer-term holistic services perspective.
Additional decision categories could include agricultural policies, land management
(e.g., zoning, permit variances), and forest management.
One of the most important water quality issues in the Albemarle-Pamlico
watershed and estuary is related to management of reactive nitrogen (Nr). Nr includes
all biologically, chemically, and radiatively active nitrogen compounds in the atmosphere
and biosphere: ammonia (NH3) and ammonium (NH4+), nitric oxide (NO), nitrogen
dioxide (N02), nitric acid (HNOs), nitrous oxide (N20), and nitrate (N0s~), and organic
compounds (urea, amines, and proteins). Past impacts associated with excessive
nitrogen loading to the Albemarle-Pamlico estuary include high primary productivity and
nuisance phytoplankton blooms that negatively impacted recreation and fisheries. As a
result, in 1995, the North Carolina state legislature adopted a strategy to improve water
quality in the Neuse River estuary through a 30 % reduction in the annual nitrogen
loading from all sources based on 1995 levels. This reduction target (the "Neuse rules")
took effect in 1998 and required point sources and selected nonpoint sources
(agriculture and new development) to modify operations to reduce nitrogen inputs.
Since full implementation of the nutrient reduction strategy, point source and agricultural
loads have been reduced by 65 % and 45 %, respectively, but total nitrogen loading to
the Neuse River estuary has remained essentially unchanged (Osmond 2009, Deamer
2009, Paerl et al. 2010). A similar situation exists for the Tar-Pamlico watershed. The
APWES will combine monitoring, mapping, and modeling work on the airshed,
watershed, and estuary to inform future nutrient management decisions. For example,
ecosystem services may be used as indicators of benefits gained through alternative
nonpoint source pollution control options.
STRATEGIC GOALS OF THE APWES
The APWES conceptual model (Figure 2) uses the DPSIR framework (GIWA
2001) to show how drivers of land use and climate change create pressures that alter
the state of the system and the provisioning of ecosystem services. Management
responses (decisions) affect drivers and pressures, alter services, however, these
effects are often not considered when decisions are made (MEA 2005). Figure 2 shows
how ecosystem services can inform the decisions, which feed back to the drivers and
pressures in the form of adaptive management, which is consistent with Ecosystem
Based Management (EBM) (Arkema et al. 2006). ESRP science is designed to
quantify the links within the DPSIR framework to support improved decision-making.
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Table 2. Watershed and Estuary Decisions to be supported by the APWES
Issue Management responses (Decisions) Decision maker Science questions
Water quality
Develop standards
Develop Total Maximum Daily Loads
(TMDLs)
Implement BMPs, green
infrastructure, land acquisition for
protection, and trading to achieve
TMDLs
Revise riparian buffer rules (e.g., for
Neuse, Tar-Pamlico)
EPA Office of
Water (OW)/NC ,
VA
NC DWQ, VA
Dept. of Env.
Quality (DEQ)
State: NC DWQ,
NC
Environmental
Management
Commission
(EMC)
What levels in streams are
protective of estuary (Downstream
Protection Values - DPVs) (e.g.,
FL Dept Env Protection 2010)
What are the spatial contributions
of different areas (e.g., Falls Lake)
What are the relative contributions
of different pressures?
What are the missing sources of
nitrogen (air, groundwater, storage
in dams)? How is nitrogen
removed in wetlands?
How to optimize BMP efforts for
the reduction of pollutants (and co-
benefits)? (e.g., Chesapeake Bay)
Water quantity
Permit interbasin transfers of water
Permit water withdrawals
Implement green infrastructure
(related to EPA's Healthy Watersheds
program in Virginia -VA OCR 2010)
MS4 Stormwater regulation -
Promulgate national standards for
urban stormwater discharges
including green infrastructure
State: NC
Division of Water
Resources
(DWR), VA DEQ
NC DWR, NC
Ecological Flows
Science Advisory
Board
EPA, Local
communities
EPA OW (also a
water quality
issue)
What are the effects of transfers on
water quality and aquatic
communities?
What levels are needed instream
(ecological flows)?
How to implement green
infrastructure to best reduce
stormwater and pollutants (and
gain other benefits?)
What are the stormwater retention
benefits (and other benefits)
associated with green
infrastructure?
Wetlands
CWA 404 permitting for dredge and
fill of waters, compensatory mitigation
Army Corps of
Engineers (CoE),
with EPA
consultation
Are functions and services
conserved through mitigation?
Wetlands restoration to ameliorate
local and coastal eutrophication
NC Ecosystem
Enhancement
Program
(NCEEP)
Where to restore for the greatest
improvement (and services
benefit)?
Significant nexus determination
(assessment of connection or
significant effect on
physical/chemical/biological integrity
of waters of U.S.) (Leibowitz et a/.,
2008, Munozefa/.,2009)
EPA Region 4 Do ephemeral streams and non-
adjacent wetlands have significant
nexus (e.g., wetlands attenuating
floods)?
Air quality
Next NOx/SOx five-year review -
selecting an atmospheric
concentration (or deposition rate) to
protect public welfare
EPA Office of Air
Are functions and services altered
or impaired by current ambient air
levels of NOx and SOx?
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Reservoir management
Dam removal
Reservoir re-operation (e.g.,
Sustainable Rivers Project on the
John B. Kerrdam - Roanoke River
www.nature.org/success/dams.html)
NCEEP
CoE, Nature
Conservancy
(TNC)
What are the costs and benefits of
dam removal?
How do services change with
different operation scenarios?
Coastal climate adaptation
Restoring oyster reefs and seagrass
beds and building artificial reefs to
buffer storm energy
Protect land upslope for inland
migration of marsh and species - land
acquisition, rolling easements, living
shorelines, planting bald cypress to
aid forest transition
Planting marsh grasses to prevent
mass wasting of the shore
Hydrologic restoration to control salt
intrusion (management of ditches)
NOAA, AP
National Estuary
Program
(APNEP), TNC,
NC Coastal
Resources
Commission
How to prioritize restoration
projects?
How to prioritize land for protection
(Pearsall and Poulter 2005)?
What type and effort of restoration
is needed for sustainability?
What are the benefits of this action
under different sea level rise
scenarios?
Species and habitat protection
Fishery regulations (limit season),
close areas to fishing
List species as Threatened/
Endangered or State Concern,
identify and conserve critical habitat
Evaluation of impacts on species
(Endangered Species Act Section 7)
Habitat Restoration - Coastal Habitat
Protection Plan (CHPP), Virginia
Healthy Waters program (Va Dept of
Conservation and Recreation OCR
2010)
Plan for climate change - protect
areas for species range shifts
(USFWS 2009)
State: NC Div. of
Marine Fisheries,
U.S. Fish and
Wildlife Service
(USFWS), NOAA
National Marine
Fisheries Svcs
(NMFS), Atlantic
Coast Fisheries
Commission
USFWS, NMFS,
APNEP, NC Div.
Of Coastal Mgmt,
VADCR
USFWS
Landscape
Conservation
Cooperatives
What factors lead to bacteria
impairments in coastal waters?
What are the habitat needs of
species?
How is connectivity threatened?
How viable are populations under
future scenarios?
How do human activities affect
species?
Where should habitat be protected
and restored?
How will species ranges shift with
climate change?
The APWES mission is to use ecosystem services science to inform watershed
decisions in the Albemarle-Pamlico watershed and estuary. ORD and others have
worked extensively in the past on assessing and forecasting drivers, stressors
(pressures), and ecosystem condition (state) for airsheds, watersheds, and estuaries.
The work proposed here will advance this science, as well as expand our research to
explicitly link to ecosystem services and management decisions. We identified three
goals to accomplish our mission:
1. MAPPING AND MONITORING. Develop methods to quantify ecosystem services,
as well as drivers and pressures
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Develop indicators for ecosystem services, and identify and map the provisioning
of key ecosystem services from different ecosystem types
Assess the condition of ecosystem services provided by rivers, wetlands and
coastal waters, at a variety of spatial and temporal scales.
2. MODELING. Relate changes in drivers and pressures to changes in ecosystem
state and services
Provide the scientific basis and response functions needed to evaluate changes
in ecosystem services provided by watersheds under future scenarios
Quantify and account for the combined and cumulative effects of point and non-
point pollution sources to the airshed, watershed, and estuary
3. DECISION SUPPORT. Understand how management decisions alter all services,
and use this understanding to inform watershed management decisions
Examine tradeoffs or synergies among ecosystem services
Forecast economic and societal costs and benefits of management actions and
seek to manage sustainably for ecosystem protection and economic benefit.
create.
affect
provide
Drivers
Land use]
Climate
change
V
Pressures
Emissions ]
Discharge
and runoff
Physical
alteration
j
State
\z\
[Watershed
Estuary J
m
inform
Decisions
Water quality j [ Air quality
f Water quantity ] f Climate adaptation
[wetlands] [ Reservoir management
Species and habitat protection
Ecosystem Services
[dean air]
[Clean water]
[Climate resilience]
Flood and
storm protection
Food, fiber, and fuel
[ Recreation ]
[ Biodiversity ]
<3
Figure 2. APWES conceptual model, where drivers are socioeconomic and natural forces influencing the
ecosystem; pressures are stresses that human activities place on the ecosystem; the state is the
condition of the ecosystem; services are benefits that ecosystems provide to humans (Table 1); and
decisions are the management responses by society to the environment (Table 2).
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RESEARCH APPROACH
The APWES Research Plan is framed through the goals of mapping and
monitoring, modeling, and decision support, which will be conducted at the same time.
While each goal will directly provide results that inform decisions, there will also be a
flow of information between these efforts: monitoring and mapping will provide input for
modeling; modeling will create functions that are built into decision support tools; and
decision analysis will identify future needs for monitoring, mapping, and modeling.
Research products, including publications, maps, modeling and decision support tools,
will be delivered to stakeholders for informing decisions (Appendix 1).
1. MAPPING AND MONITORING
Mapping and monitoring will be used to establish a current baseline against
which future management scenarios will be compared to inform decisions. Mapping and
monitoring research will also supply information for the modeling (Goal 2) and decision
support (Goal 3) aspects of the APWES. Mapping and monitoring help identify where
services are and define their baseline condition. APWES mapping and monitoring will
be conducted in the context of the ESRP National Atlas, where data for eight ecosystem
services (Clean water for recreation and aquatic habitat; Adequate water supply; Food,
fuel and fiber; Recreation, cultural and aesthetic amenities; Climate regulation;
Protection from hazardous weather; Habitat and the maintenance of biodiversity; Clean
air) are summarized by the 83,000 U.S. watersheds (12-digit hydrologic unit codes -
HUCs). APWES efforts seek to improve on the Atlas approach, with a focus on the
drivers, pressures, and services most significant to the Albemarle-Pamlico watershed
and estuary for the airshed, watershed, and estuary. Primary assessment activities for
air include characterization of the current state of nutrient drivers and pressures and the
improvement of monitoring of atmospheric and terrestrial nutrients. Watershed mapping
and monitoring will be conducted to characterize land cover change and agricultural
systems, map terrestrial species, identify functional process zones in rivers, and
characterize processes in isolated and tidal wetlands. For the estuary, research
includes mapping of coastal wetlands, monitoring of wetlands below-ground biomass,
and monitoring of water quality, algae, and hypoxia in water.
We acknowledge that these efforts are limited by time, money, and personnel
Research gaps include the characterization of organic nitrogen and measurements of
air deposition over urban and wetland land use classes. Additional work could also be
conducted on phosphorus, and in particular, understanding the role of the Aurora
Phosphate Mine in the Tar-Pamlico watershed, and the interaction of sea level rise and
phosphate in Miocene sediments. If possible, we would add to our sensor suite for
other chemical species. Research is needed on characterizing the diffuse exchange of
water and associated chemicals (e.g., nitrogen) between shallow aquifers and the
estuary in the tidewater region of the Neuse. Characterization would benefit from
focused field studies, such as the flow path studies (wells in transect), combination with
seepage meters and remote sensing technology. A better understanding of the impact
of engineered systems (artificial drainage, etc), is needed for wetlands and watersheds.
While data efforts are strongest in the Neuse River basin, additional data collection in
other parts of the watershed would support model transfer and validation.
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1.1. Air Mapping and Monitoring
Atmospherically deposited nitrogen reaches coastal areas via direct deposition,
or through deposition in the watershed and transport to the coast. It can play a major
role in coastal nitrogen budgets and may also contribute to eutrophication and other
coastal biological and chemical changes. Nitrates (N0s~) {wet and dry}, nitric acid
(HMOs) {dry}, ammonia (NHs) {dry}, and ammonium (NhU"1") {wet and dry} are the
principle components of atmospherically deposited nitrogen, however new emphasis is
being placed in understanding the role of other compounds such as N20 and organic
compounds. APWES research efforts will include characterizing the ecosystem state
with respect to these compounds and quantifying pollutant sources and sinks.
1.1.1. Ammonia
Ambient Concentrations
Although NHs may contribute to as much as 30 % of the total atmospheric
deposited nitrogen, very little long term data of ammonia concentrations is available in
the U.S. In 2007 the Ammonia Monitoring Network (AMoN) monitoring program was
initiated by the National Atmospheric Deposition Program (NADP, nadp.sws.uiuc.edu/).
The aim of this initiative was to study the feasibility of establishing a nationwide network
of passive ammonia monitors. In 2009 a study was initiated between EPA's NERL,
Office of Air and Radiation (OAR), Clean Air Markets Division (CAMD); and the Office of
Air Quality Planning and Standards (OAQPS) to deploy different monitoring techniques
for NH3 at a small number of CASTNET (Clean Air Status and Trends Network,
epa.gov/castnet/) sites co-located with NADP AMoN sites to determine NHs levels and
to evaluate existing ammonia measurement technology.
For APWES, atmospheric ammonia measurements from the CASTNET site
(BFT142) near Beaufort, North Carolina (www.epa.gov/CASTNET/sites/bft142.html) are
being enhanced to provide a more complete depiction of the total atmospheric nitrogen
budget. These measurements will be collected for one week every five weeks for 9
sampling periods over one year. The suite of standard CASTNET constituents: NH3,
nitric acid, nitrates, and ammonia ion will be collected. Also, a weekly annular denuder
system (ADS) and a weekly standard CASTNET three-stage filter pack and a filter pack
with an additional phosphorus acid impregnated filter used to capture NHs will run
during the measurement week. This data will then be available for use in model
evaluation. (Lead - Baumgardner, EPA/NERLJESD)
The spatial and temporal variability of atmospheric NH3 concentrations is being
investigated in the Neuse and Cape Fear River basins, where animal and crop
production and subsequent NH3 emissions is widespread. Since 2008, EPA's APPCD
has been monitoring NHs concentrations using passive sampling technology at 20 - 25
sites within these watersheds to characterize the magnitude and seasonal variability of
atmospheric NHs concentrations across a range of local emission densities. These
ground-based measurements are used to develop concentration fields for high spatial
resolution NHs dry deposition modeling, evaluation of regional air quality models, and,
most recently, validation of NH3 measurements from the tropospheric emission
spectrometer on board the AURA satellite, (Leads - Walker, EPA/NRMRL/APPCD;
Finder, EPA/NERL/AMAD; Bash, EPA/NERL/AMAD)
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Concentrated Animal Feeding Operations (CAFOs)
Concentrated Animal Feeding Operations (CAFOs) are concentrated sources of
multiple pressures: reactive nitrogen (ammonia, nitrates), methane, phosphorous, fecal
matter, bacteria, Pharmaceuticals, pesticides, salts and metals. CAFOs emit gases
directly into the atmosphere with consequent nitrogen deposition onto the landscape
and open water, and cause human respiratory and other health effects downwind.
CAFO effluent leaked from ponds and sprayed on surrounding agricultural fields may
pollute surface and groundwater, degrading water quality in wells and contributing to
fish kills, hypoxia and algal blooms downstream. Accurate knowledge of the location
and landscape attributes surrounding the thousands of CAFOs in the Albemarle-
Pamlico watershed is essential to predicting their impacts. However, the geographic
coordinates of CAFOs in existing databases may be inaccurate (e.g., the CAFO is
reported to be at a business address in a town; other errors may misplace CAFOs up to
1000m from their true locations). This research addresses this geospatial information
gap by explicitly mapping locations of swine and poultry CAFOs in the landscape.
The method uses high resolution aerial photography and satellite imagery, and
advanced remote sensing feature extraction techniques. CAFO barns where animals
(swine, poultry) are housed are typically long, rectangular, light-colored buildings
situated in otherwise primarily agricultural and vegetated landscapes. This presents a
favorable combination of target and background for mapping by remote sensing. The
method uses automated feature extraction software to search for long, bright,
rectangular targets in a background of vegetation and agricultural fields. The output is a
map and vector overlay of potential CAFO barns, ready for export to CIS for further
analysis. Lidar data may enhance the analysis, and can provide additional information
about local topography and vegetation buffers surrounding CAFOs. (Note that the
analyst examines the output to correct false positives and false negatives (undetected
CAFOs)). This research will create spatially explicit maps of CAFO locations to support
development of emissions inventories of nitrogen compounds. Advances in the
emissions inventory are expected to improve CMAQ model estimates of concentration
and deposition. (Lead: Pliant, EPA/NERL/ESD).
1.1.2. Nitrous Oxide
The measurement of the production of nitrous oxide from both denitrification and
nitrification processes will aid our understanding of the magnitude and variability of
these two processes under a gradient of soil moisture and nitrogen input regimes within
a coastal wetland complex. Trace gas detectors using either quantum cascade lasers or
laser diode systems with cavity ring-down technologies have the sensitivity for
measuring and discriminating these nitrogen isotopes (Kroon et al. 2007, Waechter et
al. 2008, Hendriks et al. 2008). Our research includes deploying these sensors at the
ground-level as well as via aerial platforms. The stable isotopes of N20 are 14N and 15N,
and 160 and 180. Nitrifying microbes tend to fractionate N20 in favor of the lighter
isotope, so the N20 produced will generally be depleted in 15N and 180. The microbes
involved in denitrification do not show the same degree of fractionation (Baggs 2008).
This complex relationship means that it may be possible to more accurately determine
the reactive nitrogen removed by denitrification by subtracting the N20 produced by
nitrification (Perez etal. 2006, Sutka etal. 2006, Bouwman etal. 2010). This information
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is needed to quantify determine wetland ecosystem services for reactive nitrogen
removal and better describe the Mr removal efficiencies of various wetland types found
in coastal N.C. (Lead- Williams, EPA/NERL/ESD)
N20, which can be emitted from agricultural operations and from soil microbial
processes, is another Nr source that should be considered. Characterization of N20
emissions from the soil and water is a current gap in characterization of the Nr budget.
Groundbased and airborne measurements of N20 emissions from agricultural and
wetlands soils will be used to determine the sources and source strengths of N20 in the
atmosphere. Stable isotope techniques using laser based trace gas spectrometers can
help estimate the source contribution from soil nitrification or denitrification processes to
the atmospheric concentration of N20 in the study region. Additionally, water samples
are being collected at 25 sites in the Neuse River Estuary and Pamlico Sound
approximately biweekly, both at the surface and at depths within the water column.
Dissolved nitrous oxide concentrations, atmospheric nitrous oxide concentrations, and
meteorological data (wind speed) will be combined to quantify the emission of N20 into
the atmosphere from the water surface. Correlations between dissolved N20, oxygen,
temperature, salinity, and nutrient concentrations will be examined to investigate
potential N20 production mechanisms. These field data can be used to improved
estimation and modeling of N20 emission by CMAQ. (Leads- Williams,
EPA/NERL/ESD and Cooter, EPA/NERL/AMAD)
1.1.3. Nitrogen dioxide, Nitrogen Oxides
APWES research will build upon recent advances in the space-time modeling of
fused spatial information to provide: 1) a methodology for the routine development of
seasonal and annual spatial patterns of total sulfur and nitrogen deposition across the
eastern U.S.; and 2) State/regional estimates of total sulfur and nitrogen loadings. While
it is currently possible to construct a spatial wet deposition surface from National
Atmospheric Deposition Network (NADP) data, EPA is limited to reporting total loadings
(wet plus dry) only at the CASTNET dry deposition monitoring sites. To provide better
spatial information on total deposition, we will combine long-term wet and dry weekly
monitoring data with gridded numerical model deposition output from the Community
Multi-Scale Air Quality (CMAQ) model. These spatial surfaces can be used to calculate
(through numerical integration) the total sulfur or nitrogen loadings and associated
uncertainty for any ecological, air quality, or programmatic region of interest. Also, we
propose to use statistical fusion techniques to provide predictions of atmospheric
nitrogen species, (e.g., N02, NOx) in coastal North Carolina. These techniques have
never been applied to nitrogen species before, and these data will address issues
associated with the extremely limited deposition monitoring and sparse monitoring for
the atmospheric pollutants N02, NOx in this region. This effort combines air monitoring
data and CMAQ output to produce temporal and spatial deposition patterns to support
watershed and estuary models (Lead - Holland, EPA/NERL/ESD)
1.1.4 Regional scale atmospheric deposition
Deposition estimates from the CMAQ model are being made available for 2002-
2006 and provide more complete information about the atmospheric nitrogen budget
than current national monitoring studies. The data will be available at the 36 km grid
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resolution for the entire U.S. and the 12 km scale for the eastern U.S. Additional data
will include wet deposition estimates for 2002 that have been adjusted for bias in
precipitation. Deposition data from CMAQ will be used in the National Atlas. (Lead-
Dennis, EPA/NERL/AMAD)
1.2. Watershed Mapping/Monitoring
1.2.1. APWES Land Cover Characterization
Data from multiple Earth Observation System sensor systems will be
incorporated into a multi-temporal based approach to provide the modeling inputs
required to assess dentrification rates (i.e., temperature, redox potential,
evapotranspiration) and other Nr-flux measurements. Vegetation composition,
structure, and other bio-physical parameters will be derived using remotely sensed data
from NASA's prototype L-Band Polarmetric Synthetic Aperture Radar data, operational
MODIS (Moderate Resolution Imaging Spectroradiometer) data, available LIDAR (Light
Detection and Ranging) data, and hyperspectral imagery from the Environmental
Mapping Visible Imaging Spectrometer (EMVIS), a visible and near-infrared (VISNIR)
hyperspectral imager with 240 contiguous spectral bands spanning 400 nm- 900 nm.
These metrics can be useful parameters for nitrogen cycling and landscape biodiversity.
(Lead - Lunetta, EPA/NERL/ESD)
1.2.2. Land Cover Change
APWES will build upon existing methods of detecting landscape change within
the watershed, which has focused on the development and implementation of
automated procedures to monitor landscape change across the system in near-real time
using NASA's Moderate Resolution imaging Spectrometer (MODIS) instrument. The
goal of this research is to monitor and map the locations of change events across the
landscape and identify the outcome of the change event to provide an updated
classification reflecting the new landscape condition. Proposed research includes the
implementation of: 1) a new more robust change detection alarm capability that will
provide greater accuracy; 2) procedures developed in the Great Lakes Basin to map the
major crop types will be implemented across the Albemarle-Pamlico watershed on an
annual time-step and will track changes in crop rotational patterns; and 3) a new annual
land-cover classification map products for the APWES. This information is particularly
useful to support Nr modeling efforts related to fertilizer application rates (source
allocations), and potential de-nitrification processes associated with specific landscape
cover types (e.g., wetlands and riparian buffers). The phenology data used to create
the above landscape products can also be used to derive phenology-based metrics.
Data products currently available for the watershed include phenology data and annual
LC change alarm products beginning in year 2002-present. Both data sets can be
accessed for data visualization and downloads at maps6.epa.gov/viewer.htm.
Phenology metrics can be generated as needed to support future modeling efforts (i.e.,
onset of greenness, growing season duration, peak greenness, and senescence).
Correct characterization of the phenology is important to estimating dry deposition, as
vegetation has a significant role in deposition. (Lead - Lunetta, EPA/NERL/ESD)
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1.2.3. Remote sensing of agricultural systems
The APWES will use advanced remote sensing systems to accurately
characterize important components of the agriculturally-influenced Nr cycle. In
agricultural systems, applied nitrogen can be (1) incorporated by crop biomass, (2)
incorporated by microbial biomass, (3) lost to the atmosphere through nitrification and
denitrification processes, or( 4) leached thru the soil profile to the groundwater. Field
instrumentation will measure crop response to Nr applications to understand (1) using
imaging spectrometers and synthetic aperture radar. Trace gas spectrometery will
measure nitrous oxide emissions from fertilizer applications to understand (3) in
agricultural and wetland systems. University and other cooperators will assist in (2) and
(4) using measurement and modeling. Aggregation and analysis of this information will
allow for a mass balance of reactive nitrogen in agricultural systems.
This work is based in the use of field and airborne (for large-scale mapping)
imaging spectroscopy methods that detect plant biochemical response to nutrient
uptake. Remote sensing methods that can such as color infrared photography and
multispectral imaging such as commercial satellite imaging are not sensitive enough to
detect subtle differences in plant pigments or phytochromes that indicate nutrient status
and environmental stress. Imaging spectroscopic methods can characterize spectral
absorptions associated with leaf biochemistry and can be used to determine plant
nutrient utilization throughout the growing season. These methods are based on
reflectance spectroscopy absorption band-depth analysis (Clark and Roush 1984,
Kokaly and Clark 1999). This work will further these methods by applying them to
precision agriculture management for determining crop nitrogen status and needs.
This project is a cooperative venture between EPA/NERL and NC State
University (Soil Science, Crop Science, Biological and Agricultural Engineering
Departments and Open Grounds Farm). We will use data and information fusion
techniques to integrate remote sensing data from sensors that measure biophysical or
chemical vegetation characteristics to characterize crop growth and response to
nutrients over time. This information will be integrated with other ancillary data including
nitrogen application rates to develop a method to predict crop response. These results
support precise and realistic nutrient management recommendations for applying
nutrients at optimal times based on site specific conditions, to reduce the amount of
reactive nitrogen loaded to receiving waters (Lead - Williams, EPA/NERL/ESD)
1.2.4. Mapping terrestrial populations and biodiversity services
This project will use land cover data, land stewardship data, and deductive
habitat models for terrestrial vertebrate species from the U.S. Geological Survey Gap
Analysis Program to map metrics reflecting ecosystem services or biodiversity aspects
valued by humans over large areas. Metrics will be derived from species-of-greatest-
conservation-need, threatened and endangered species, harvestable species (upland
game, migratory birds, and big game), total species richness, and taxon richness. We
will evaluate additional indices for application to provide a broad biodiversity
perspective. The project will be conducted at multiple scales: a focused study in the
Albemarle-Pamlico watershed, and a more general study for the Southeast U.S. (9
states) (Implemented through interagency agreement with USGS National Gap Analysis
Program, with Ken Boykin at New Mexico State University)
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1.2.5. Riverine Functional Process Zones
The Neuse River basin will be mapped according to Functional Process Zones
(FPZs), riverine hydromorphic patches organized longitudinally at various spatial scales
(Thorp etal. 2006, Thorp et al. 2010). The FPZs are repeatable and only partially
predictable in position (less so among ecoregions). Because they differ substantially in
hydrogeomorphic characteristics, FPZs are also likely to vary significantly in community
structure, ecosystem function, ecosystem services, and response to nutrient loadings,
and thus will respond differently to efforts at river rehabilitation. For this project, the
FPZs will be delineated for the entire Neuse River basin to explain more of the natural
variation that exists among different types of river sections. This information will also be
useful for the characterization of ecosystem services basin-wide. (Lead - Flotemersch,
EPA/NERL/EERD, in collaboration with Kansas University).
1.2.6. Isolated wetland below-ground denitrification characterization
ESRP researchers will be collecting multiple soil samples from six isolated
wetlands in the Croatan National Forest. Samples will be analyzed for ambient and
potential denitrification, and assessments for within-site and between-site determinants
of denitrification conducted. Isotopic analyses (Pb210 and Cs137) and down-core
measures of total phosphorus, total nitrogen, and total carbon will be conducted to
quantify historic rates of nutrient and carbon sequestration. N20 is also being
measured. These analyses are also being measured at isolated wetlands in northeast
Ohio and north central Florida to provide a multi-ecoregion assessment of nutrient
assimilation by wetlands. Coupled with other ESRP research on nitrogen removal in
Pacific Northwest emergent marshes and aquatic bed wetlands, Gulf of Mexico
marshes and mangroves, and upper Midwest fens and bogs, this data will inform
models of wetland denitrification. (Lead - Lane, EPA/NERL/EERD)
1.2.7. Tidal wetland reactive nitrogen flux characterization
APWES research will link ground-water and surface water modeling elements to
better understand and model nonpoint (diffuse) subsurface nitrogen source loadings to
coastal wetlands. The uncertainty associated with the nutrient processing function
provided by wetlands will be addressed using a step-wise and progressive modeling
approach. We will evaluate the utility of advanced remote sensing technologies,
specifically trace gas detectors, optical hyperspectral airborne imaging systems and
synthetic aperture radar for determining, in part, the mass flux of reactive nitrogen in
wetland and agricultural ecosystems. This information is needed to quantify nitrogen
removal by accounting for production and losses of important nitrogen species such as
N20 from agricultural and wetland sources. Two tidal wetland complexes with current
research monitoring of nutrient flux and hydrologic flow that are multi-agency wetland
creation/restoration projects have been selected as study sites. Both wetlands (400-
1000 acres) abut large active agricultural lands. Research at the Carteret County site is
led by NCSU in cooperation with the North Carolina Coastal Federation. The Tyrrell
County site research is lead by Duke University under a Department of Energy Grant.
(Lead- liames, EPA/NERL/ESD)
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1.3. Estuary Mapping/Monitoring
1.3.1. Extent and Quality of Tidal Wetlands in the APWES
To determine the potential functions and services that tidal wetlands provide, with
regard to storm surge protection and other services, it is necessary to first identify and
quantify the extent of tidal wetlands and their relative quality. To measure extent, we
propose using Landsat satellite data, multispectral airborne data, analogue remote
sensing data (e.g., aerial photography), and geographic information systems data (e.g.,
C-CAP,and/or National Wetlands Inventory data) to identify tidal wetlands and
monotypic stands of dominant wetland vegetation in tidal wetlands of the staged study
area. A hybrid image analysis approach similar to those techniques piloted by Lopez et
al. (2004) will be used to delineate relevant coastal-zone wetlands, utilizing the above-
described remote sensing and CIS data. The resulting gains and losses of wetlands
across that time period can be combined with coefficients of storm surge reductions with
wetland acreage to provide relative levels of vulnerability for coastal regions during the
different decades. Probabilities of storm activity vary widely along the Atlantic coast and
would also be incorporated into the level of vulnerability. Wetland condition will be
determined using the best available and practicable field-assessment protocol(s), such
as a floristic quality index or a (rapid) qualitative habitat assessment, which is robust
enough to apply to a representative sample of wetlands across a biophysical gradient
relevant to wetland quality. Where possible, this work will be integrated with the EPA
National Wetlands Condition Assessment. This work can inform decisions about which
land should be acquired for coastal wetland restoration and whether permits should be
granted for development in coastal areas. (Lead- Lopez, EPA/NERL/ESD)
1.3.2. Measurement of belowground structure in coastal wetlands
APWES research will also support the measurement of belowground structure in
coastal wetlands. Computed tomography (CT) imaging, for the first time, is being used
to successfully quantify wet mass of coarse roots, rhizomes, and peat in cores collected
from organic-rich (Jamaica Bay, NY) and mineral (North Inlet, SC) soils. In addition,
image analysis software was coupled with the CT images to measure abundance and
diameter of the coarse roots and rhizomes in marsh soils. CT imaging can discern the
roots, rhizomes, and peat based on their varying particle densities. Calibration rods
composed of materials with standard densities (i.e., air, water, colloidal silica, and glass)
were used to operationally define the specific x-ray attenuations of the coarse roots,
rhizomes, and peat in the marsh cores. Using CT imaging, significant positive nitrogen
fertilization effects on the wet masses of the coarse roots, rhizomes, and peat, and the
abundance and diameter of rhizomes were measured in the mineral soils. CT imaging
successfully assessed and quantified coarse roots, rhizomes, peat, and soil particle
densities in coastal salt marshes, and is a practical and effective approach to monitor
belowground structure in coastal wetlands (Wigand 2008). Because the belowground
structure in coastal wetlands is critical to the provision of key ecosystem services such
as flood abatement and carbon sequestration, the monitoring of belowground structure
should be part of wetland management, conservation, and restoration plans. (Lead-
Wigand, EPA/NHEERL/AED)
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13.3. Estuarine Chlorophyll a, Salinity, and Turbidity
Chlorophyll a (a standard measure of phytoplankton biomass), salinity and
turbidity will be mapped at a nominal spatial resolution of 300 m (7.5 ha) and at multiple
temporal scales across the Albemarle-Pamlico estuary system using data from the
European Space Agency (ESA) MEdium Resolution Imaging Spectrometer (MERIS),
flown on the ENVI-1 satellite, and a hyperspectral radiometer system, flown on a NASA
aircraft (EPA/NASA Interagency Agreement). These data will be integrated with in situ
measurement data from the MODMON and the automated system onboard NC State
ferries that cross the Pamlico Sound as part of the UNC/Duke/NC Dept of Natural
Resources/NC Dept of Transportation Ferry Monitoring (FERRYMON), to derive,
calibrate and validate empirical chlorophyll and turbidity bio-optical models to better
understand the spatial and temporal variability of phytoplankton production, distribution,
and suspended sediment flux rates across the study area. A salinity algorithm will be
derived from the satellite data to provide data for estimating freshwater residence times
on a regional scale for the Albemarle-Pamlico system. These datasets will also be used
to estimate nitrogen dynamics simulated by the Estuary Nitrogen Model and the RMA2
and RMA4, two-dimensional hydrodynamic and transport models. (Lead- Keith,
EPA/NHEERL/AED)
1.3.4. Estuarine Harmful Algal Blooms (HAB)
Studies on the transport and fate of nitrogen delivered to the Neuse estuary (Christian
et al. 1991, Paerl et al. 1998) indicated that during high winter and spring rainfall events
nonpoint source reactive nitrogen is introduced through direct atmospheric deposition
and stormwater runoff into the freshwater upper reaches of the estuary. During these
events, much of the reactive nitrogen that enters the Neuse estuary is in the form of
nitrate (NOs-) which is rapidly removed in the oligo-mesohaline segments of the upper
estuary to promote elevated phytoplankton growth rates that result in extensive winter-
spring blooms of dinoflagellates and crytomonads (Pinkney et. al. 1997). During
relatively dry summer and fall months the broad lower reaches of the Neuse estuary
vertically stratifies in a "lake-like" fashion (Paerl 1987, Showers et al. 1990) due to weak
circulation. Because of these hydrodynamics, NhU may be nitrified to nitrite and nitrate
by aerobic microbial processes which consumes dissolve oxygen and may contribute to
hypoxia (Christian and Thomas 2003). Also during these months, nuisance
cyanobacterial (Microcystic aeruginosa) blooms develop and proliferate in the
freshwater portions of the Neuse River. Research will create an early warning
framework for detecting HAB. This hierarchical framework would use daily MODIS
satellite imagery of the Albemarle-Pamlico estuary to monitor regional scale change in
chlorophyll concentrations. Aircraft and in situ hyperspectral data allow estimation of
pigment concentrations and identification of phytoplankton groups, based on their
unique spectral signatures. Cyanobacterial biomass will be quantified based on
algorithms to retrieve the biomarker pigment C-phycocyanin (C-PC) and chlorophyll
concentrations from Section 1.3.2. (Hunter et al. 2010). Results will be compared with
data collected from FERRYMON. Research will investigate if cyanobacteria are also
characteristic of other waters in the estuarine system and whether there is a link
between their presence in coastal stormwater ponds and lagoons associated with
CAFOs. (Lead-Keith, EPA/NHEERL/AED).
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1.3.5 Estuarine Hypoxia
Molybdenum (Mo), which has been used as a geochemical marker of hypoxic
bottom water conditions (Boothman and Coiro 2009), will be applied in Albemarle-
Pamlico sounds to rapidly assess the duration/frequency of hypoxia in these waters.
This research, which includes studies in laboratory microcosms and the field, relates the
accumulation rate and concentration of molybdenum in estuarine sediments to the total
number of days that dissolved oxygen concentrations occur below a threshold value.
Concentrations of Mo in sediment will be used to assess interactions between sediment
diagenesis and water column dynamics and to examine their relationship to foodweb
dynamics in Pamlico Sound. (Lead-Boothman, EPA/NHEERL/AED, EPA Region 4)
2. MODELING
Modeling research in the APWES will improve the capability to relate changes in
drivers -> pressures -> ecosystem state -> ecosystem services (Figure 2), and forecast
how changes in drivers and pressures alter the provisioning of services. Mapping and
monitoring efforts (Goal 1) are critical for characterizing model inputs and supporting
model development. Model output will be translated to service measures that can be
used directly to inform management decisions; model output and relationships will also
be used in decision support efforts (Goal 3). APWES modeling research will focus on
model development, application, and uncertainty analysis for air, watershed, and
estuary. Efforts are also underway to link models in frameworks - research on the
FRAMES model framework is underway at NERL/ERD for several of the models
included in the APWES. The interrelated models for the APWES are shown in Figure 3.
Not shown in Figure 3 are additional data (e.g., USGS gaged flow, measured nutrient
data, measured population numbers) needed for calibration and validation. The relation
of models to services is also noted in Table 1.
While the APWES modeling approach is fairly comprehensive, research gaps
include models for plant and soil dynamics in agriculture and forest systems, modeling
future distributions of terrestrial species, and representing wetlands within watershed
models. Additionally, models of geomorphological changes in the river channel would
better support habitat and species models. We also need a better representation of
interactions between shallow aquifers and the estuary in the tidewater regions. This
would require expanded computational modeling tools such as the emerging state-of-
the-art full physics-based numerical models linking ground water and surface water
(beyond the current generation of semi-process based watershed models). As time
allows, we will also develop additional modeling capabilities for representing toxics,
including mercury, pesticides, and emerging contaminants in the estuary. We hope to
interface with modeling efforts for pesticides underway in ORD (U.S. EPA ORD 2010).
Also, more detailed modeling of shoreline/tidal wetland changes under future sea level
rise scenarios is needed (Hopkinson et al. 2008). Integrating models in frameworks
requires the development of standards for model input, output, and uncertainty analysis.
Also, model validation in new sites is needed, and this will require the support of
continued, comprehensive monitoring.
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Agriculture and forest
production
Groundwater
quantity and quality
Shallow groundwater
flow/leakage
f Biodiversity j
Figure 3. Relation of APWES modeling components to drivers (red), pressures (yellow), ecosystem state
(green) and services (blue) (analogous to top four boxes in Fig. 2):
Meteorological models (WRF or MM5) provide inputs (precipitation, temperature, etc) for CMAQ
Environmental Policy Integrated Climate (EPIC) model predicts effects of crop management on
movement of soil, water, nutrients and pesticides and their impact on crop productivity and water
quality; the Sparse Matrix Operator Kernel Emissions (SMOKE) Modeling System processes
emissions inventories to convert them to resolution needed by CMAQ
Air modeling relies on the Community Multiscale Air Quality (CMAQ) model, an Eulerian model that
ingests emissions (EPIC model) and meteorological data and provides atmospheric concentrations
and deposition across a gridded domain
Watershed models (SWAT, WASP) interface with the shallow groundwater models (GFLOW, which
interacts with MODFLOW for deep groundwater) to simulate flow, temperature, sediment, and
nutrients (and possibly bacteria and toxics, including mercury and pesticides).
SPARROW, an empirical model for nutrient loading, will inform SWAT calibration.
Estuary models (FVCOM, ENM) rely on atmospheric, watershed, and groundwater inputs to predict
estuarine water quality
Ecological models (SMURF, Population models) take inputs from watershed/estuary models to
forecast changes in species populations
The SLAMM sea level rise model forecasts wetland condition based on IPCC sea level rise
predictions
Additional model inputs are not shown here (e.g., data for soils, elevation, wind, emissions data,
CAFOs, species population parameters)
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2.1. Air Modeling
2.1.1. Improved CMAQ model input - Land surface characterization
Land cover - Land cover is a dynamic element and deposition estimates vary
greatly by underlying surface. CMAQ will be updated (e.g., modifying surface exchange
parameters) to use the NLCD 2001 and more detailed land cover data sets developed
using remote sensing techniques (Section 1.2), and model sensitivity to these
differences will be tested (Lead - Schwede, EPA/NERL/AMAD)
Crop type - Specification of the crop type in an area is critical to estimating
fertilizer usage as it greatly affects land management practices. Crop data bases
currently being used for CMAQ, including the USDA National Agricultural Statistics
Service Cropland data layer, Farm Service Agency/FAPRI CRP assessment,
Conservation Effects Assessment Project, and RCA analytical database, are static and
represent a snapshot in time. Procedures developed in the Great Lakes basin to map
the major crop types will be implemented across the Albemarle-Pamlico watershed on
an annual time-step and will track changes in crop rotational patterns. The crop maps
can be used as an alternative to the standard CMAQ data sets to investigate the
sensitivity of the predicted surface exchange to the crop specification. (Leads -
Lunetta, EPA/NERL/ESD and Cooter, EPA/NERL/AMAD)
Phenology - While remote sensing of phenological data (Section 1.2.2) provides
useful information and model inputs, use of the data will be restricted to retrospective
and current studies. Therefore, models of phenology must also be explored. The
FErtilizer Scenario Tool for CMAQ (FEST-C) will be used to generate phenological data.
For current conditions, output from FEST-C will be compared with remote sensing and
ground based measurements to establish comparability between the methods and
provide uncertainty estimates. (Leads- Cooter, EPA/NERL/AMAD and liames,
EPA/NERL/ESD)
Soil - Characterization of the soil type and condition is critical to improved
estimates of NH3 bidirectional exchange in CMAQ. Work with the FEST-C will provide
estimates of soil condition, nitrogen loss, and nitrogen transformation. Outputs from
FEST-C will be compared with remote sensing information. (Leads - Cooter,
EPA/NERL/AMAD and Williams, EPA/NERL/ESD)
2.1.2. Improved CMAQ model input - Nitrogen Emissions characterization
While sources of oxidized nitrogen tend to be well characterized in the National
Emissions Inventory, sources of reduced nitrogen (primarily NHs) are not. Agricultural
sources of reduced nitrogen, which represent about 75 % of total NH3 emissions,
include animal feeding operations (CAFOs), animal waste, and fertilizer application.
Currently, soil NH3 emissions from chemical fertilizers are estimated using emission
factors based on fertilizer sales. Using the new bidirectional algorithm in CMAQ, NHs
emissions due to chemical fertilizer application will be removed from the input and will
be modeled with CMAQ using inputs on fertilizer application timing, method and rates
from FEST-C. (Lead - Bash, EPA/NERL/AMAD)
Remote sensing data from sensors that measure different biophysical or
chemical characteristics of vegetation at locations in the Albemarle-Pamlico watershed
will be used to characterize crop response to nitrogen and growth over time. This
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information will be integrated with other ancillary data including nitrogen application
rates to predict crop response. These results to will be used to assist in making precise
and realistic nutrient management recommendations and will be available for
comparisons against the scenario representations in FEST-C. (Leads- Williams,
EPA/NERL/ESD and Cooter, EPA/NERL/AMAD)
2.1.3. Improve CMAQ process modeling
Several key process areas have been targeted for CMAQ development including
modeling the bidirectional exchange of pollutants such as NHs, mercury, and pesticides
and developing the CMAQ adjoint model for inverse modeling of net NH3 fluxes in bi-
directional exchange version of CMAQ. Missing pathways of air-surface exchange such
as lightning NOx production, cloud deposition, and emissions and deposition of base
cations have been identified in the model and will be addressed. For many ecological
assessments, deposition estimates for specific land use types are needed rather than
the grid-based value. CMAQ is being modified to allow output of land use-specific
deposition estimates as well as estimates due to stomatal flux only. (Leads- Bash,
Dennis, Schwede - EPA/NERL/AMAD)
2.1.4. CMA Q model evaluation and sensitivity
Estimates of uncertainty and variability are important aspects of any assessment.
Numerous CMAQ evaluations have been completed for concentration and wet
deposition as data for these studies is readily available from U.S. monitoring networks.
Evaluation of dry deposition estimates remains a challenge due to the limited data
availability. NH3 concentrations and deposition present a special situation due to the
bidirectional exchange of this pollutant. Standard monitoring networks do not provide
the spatial detail needed to evaluate model processes and special studies are needed.
We will assess the sensitivity of CMAQ depositions estimates of deposition to land use
and climate change scenarios, which can affect emissions, concentration, and
deposition. (Lead - Schwede, NERL/AMAD)
2.2. Watershed Modeling
2.2.1. Future climate, land use, and flow
Future land use and climate will be developed in a study focused on 20 U.S.
watersheds, including the Albemarle-Pamlico. Monthly climate data for 30-year future
periods will be taken from dynamically downscaled future climate change scenarios via
a partnership with the North American Regional Climate Change Assessment Program.
Future land use will be provided by the ICLUS tool, an ArcGIS application to derive land
use change projections for housing density and impervious cover consistent with the
Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions
Scenarios storylines (U.S. EPA 2009). This project will use the future land use and
climate to model of streamflow, sediment, and nutrients at the 8-digit HUC scale using
the SWAT watershed model (Neitsch et al. 2005); inputs will also be used for the finer-
scale modeling in 2.2.2 (Lead - Johnson/Weaver, EPA/NCEA).
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2.2.2. Upland hydrologic modeling
Upstream watershed (surface and sub-surface) processes may result in impaired
downstream water quality, which necessitates a holistic approach incorporating
atmospheric, watershed and water quality models to represent variations in spatial and
temporal processes. A set of watershed models will be applied at multiple (spatial and
temporal) scales in the Albermarle-Pamlico watershed. A multi-scale approach will allow
for assessment and forecasting of land use and climate change impacts on a variety of
ecosystem services, for which data resolution and lag times may widely differ. This work
moves forward from an initial analyses assessing how various spatially-explicit sources
of precipitation data affect linkages between air quality and watershed modeling. The
performance of various watershed models (e.g., SWAT) will be investigated in
simulating water and nutrient budgets. In order to determine the best source of
precipitation data for watershed modeling, multiple precipitation data sources are being
tested using SWAT at four different watershed scales within the Neuse basin.
Improved representation of bi-directional flow of nutrients will be developed with
NERL/AMAD by linking the CMAQ modeling system with watershed models. We will
use the results of the USGS SPARROW and MODFLOW models for improving our
calibrations on watershed flow and nutrient response (Figure 3). The SPARROW model
has been applied at the RF1 resolution (1:250,000) in the Southeast (Hoos and
McMahon 2009), and is now being applied using the NHD Plus catchments (1:100,000)
(USEPA/USGS 2010). A Neuse River basin groundwater model GFLOW (Haitiema
1995) in combination with the USGS MODFLOW model (Campbell and Goes 2010) of
the Coastal Carolinas will be used to represent recharge and leakage and constrain the
Neuse River SWAT model calibrations on flow. The groundwater model will also be
used to delineate subsurface flow paths from nitrogen sources to stream riparian zone,
Instream water and nutrient cycling processes will be represented with the WASP model
(Wool et al. 2003). This set of models will produce time series output at the Neuse
River watershed pour point of instream flow and depth and total suspended sediment,
dissolved oxygen, nutrient, and mercury concentrations. (Lead - Kraemer,
EPA/NERLJERD)
2.2.3. Improved rainfall-runoff relationships
Derivation of a practical rainfall-infiltration-runoff relationship eventually to
replace the curve number and other simplified rainfall-runoff relationships for assessing
ecosystem services provided by green infrastructure is targeted for the next decade.
Simplified rainfall-runoff relationships are widely used in hydrology to estimate stream
flow. Best suited to urban landscapes, these simplified methods many times do not
realistically represent (and value) forest runoff, and ignore the infiltration, flow paths,
and source areas upon which several ecosystem services depend. Research within the
APWES will (1) pilot test curve number selection processes for use in formulating the
hydrologic component of the ESRP National Atlas if these tests can be coordinated with
evaluations of other hydrologic modeling approaches and (2) eventually (beyond 2014)
develop and demonstrate infiltration-based runoff forecasts for green infrastructure and
major land uses. The proposed rainfall-infiltration-runoff relationship will utilize advances
in remote sensing, including radiometry and spectrometry for soil moisture, digital
elevation models and LiDAR for slope and other watershed characteristics, and
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integration of NEXRAD, satellite, and other remote sensing for rainfall distribution.
Geographic information systems (CIS) will be used with revised soil moisture retention
databases and other remote sensing databases to dynamically forecast runoff at
different scales of analysis and quantify the uncertainty. Extensive rainfall-runoff data
from over 450 watershed studies worldwide, along with U.S. Geological Survey stream
flow data and National Weather Service rainfall data for many larger U.S. watersheds,
can be used to test estimates from the curve number method and the proposed
methods, and quantify the intrinsic uncertainty. The new rainfall-infiltration-runoff
relationship will be proposed by 2020 to upgrade critical hydrologic models, including
SWAT, used by ESRP to quantify ecosystem services involving stream flow, soil
moisture, and ground water after a comprehensive review of ecohydrologic modeling to
guide the derivation of a new simplified relationship. (Lead- McCutcheon,
EPA/NERL/ERD)
2.2.4. Representation of riparian buffers in the watershed
Riparian buffer areas, especially if forested, attenuate nutrients and provide
water quality and biodiversity services and thus are an important best management
practice encouraged by state and federal incentive programs. In the Coastal Plain of
the APW, flows often include a significant sub-surface component which can influence
riparian buffer effectiveness. Artificial drainage also reduces nitrogen attenuation by
effectively bypassing existing buffers. In addition, spatial variation in nutrient loads
influences the relative degree of water quality service provided by riparian buffers. We
have developed a simple CIS-based watershed riparian model that connects various
agricultural nitrogen sources with natural buffers via surface and sub-surface flows. The
model broadly assesses the relative nitrogen attenuation for buffers. To better account
for sub-surface flows in the model, we include CIS-derived data layers of landform and
baseflow. In addition, we use existing stream networks, digital elevation models, soils,
and landcover data to estimate the influence of artificial drainage layer on relative
nitrogen attenuation. When combined in the CIS riparian model, these additional data
layers produce maps that highlight the relative nitrogen attenuation by riparian buffers in
the APW. Such maps can then be used to inform watershed-scale nutrient management
as well as to most effectively target watersheds for conservation or restoration.
Validation of this relative nitrogen attenuation riparian model will be combined with other
monitoring/modeling work being planned for the Albemarle-Pamlico watershed. (Lead -
Christensen, EPA/NERL/ESD)
2.2.5. Modeling freshwater populations
Freshwater fish provide multiple ecosystem services, including food and
biodiversity. To map these services, empirical habitat suitability models will be
developed for selected species. To simulate the response of these services to
pressures, we will use SMURF, a spatially explicit metacommunity model for river
networks (Rashleigh 2009). These will be linked to dynamic watershed inputs (flow,
sediment, temperature) in an integrated modeling system to forecast the change in the
populations of valued species under future scenarios (Lead - Rashleigh,
EPA/NERL/ERD).
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2.3. Estuary Modeling
2.3.1. Estuarine hydrodynamic models
Data on reactive nitrogen transport derived from riverine loads based on U.S.
Geological Survey SPARROW models, and supplementary data from atmospheric
loading and direct discharges will be input into the RMA2 and RMA4 models, 2-
dimensional hydrodynamic and transport models developed by the U.S. Army Corps of
Engineers. Model results will be used to forecast nitrogen distribution in response to
circulation patterns and water residence time within the Albemarle-Pamlico estuarine
system. RMA 2-D predictions will be refined for use with the water quality, sediment
transport and biological modules of the 3-dimensional Finite Volume Coastal Ocean
Model (FVCOM), developed by UMASS-Dartmouth and Woods Hole Oceanographic
Institution. This model will simulate the effects of atmospheric (wind stress, heat flux,
precipitation), hydrodynamic (river discharge and groundwater flux), tidal forcings and
bathymetry on the distribution of reactive nitrogen concentrations in the Albemarle-
Pamlico estuary and its impact on dissolved oxygen, chlorophyll and dissolved organic
matter. (Lead-Abdelrhman, EPA/NHEERL/AED)
2.3.2. Estuarine nutrient modeling
The Estuary Nitrogen Model (ENM) will be used to estimate average nitrogen
concentrations in estuaries using riverine loads based on USGS SPARROW models,
and supplementary data for atmospheric loading and direct discharges. The ENM is a
mass balance model that assumes that nitrogen loss within estuaries can be formulated
as a first-order process for which the rate is proportional to system nitrogen content.
The model has been used to calculate: the fraction of watershed- and atmospherically-
derived nitrogen that flows through the estuary to the sea (throughput), estimate the
fraction of nitrogen from the watershed and atmosphere that is lost within the estuary to
denitrification, the mean annual concentration of total nitrogen in an estuary, compare
the fractions of total nitrogen in the estuary that derive from land-side loading and input
from the sea, and estimate the sensitivity of estuarine total nitrogen concentrations to
loading changes (Dettmann et al. 2005). The ENM has been used to demonstrate the
dependence of throughput, denitrification losses and concentrations of total nitrogen in
estuaries on flushing time. (Lead - Dettmann, EPA/NHEERL/AED)
2.3.3 Sea level rise modeling
Significant sea level rise may affect the APW, leading to changing shorelines and
loss of barrier islands and wetlands (Pearsall and Poulter 2005). Research in the
APWES seeks to address some of these potential consequences, using the Sea Level
Affecting Marshes Model (SLAMM), which simulates the dominant processes involved
in wetland conversions and shoreline modifications and provides maps of wetlands
distribution during long-term sea level rise (Craft et al. 2009). In the ESRP, SLAMM
modeling is being conducted on several coastal wetlands around the country, focusing
on one coastal marsh in CA and one in N.C. - the Markers Island region near Morehead
City. Additional efforts will relate urban/agricultural change and sea level rise to
potential changes in ecosystem services for these coastal wetlands, and develop less
computationally complex models for sea level rise, which may be more practicable at
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broad scales, and comparing these models to SLAMM. Modeling efforts will be
coordinated with ongoing NOAA work in this area (ADCIRC model) (Lead - Erickson,
EPA/NERL/ESD in collaboration with NOAA CSC, Charleston, SC)
2.3.4. Modeling estuarine populations
Population modeling of high value resources (oysters, blue crabs, mussels,
finfish, shrimp) will be conducted to investigate relationships between multiple,
interacting pressures to the provisioning services provided by these species. This
modeling will build on strong understanding of the estuary that already exists (e.g.,
Christian etal. 2009). These population models will be linked with data on reactive
nitrogen transport derived from coastal/estuarine hydrodynamic and nitrogen residence
time models to develop ecological production functions which relate the removal of
excess nitrogen from direct and indirect sources by shellfish and shellfish reefs by water
filtration (ecological function) to enhance provisioning and recreation services
(response) in estuaries and coastal waters. Both primary and secondary nursery areas
will be considered. (Lead- Thursby, EPA/NHEERL/AED with NOAA-Beaufort)
2.3.5 Production functions for ecological response endpoints and ecosystem services.
Most of the modeling projects presented in this section are designed to increase
our ability to predict how changes in pressures will affect biophysical processes.
Although this information is critical for understanding of the dynamics of the system,
these biophysical measures will need to be translated into endpoints (ecosystem
services) that policy makers and the general public can readily understand. To bridge
the gap between mapping and modeling to decision support ecological production
functions need to be developed. Ecological production functions are models that relate
changes in ecosystem state or condition to changes in the provisioning of ecosystem
services. For example, we can model how changes in reactive nitrogen loads to the
estuaries affect the occurrence probabilities of hypoxic events. To make the leap to
ecosystem services we also need to be able to translate model predictions into real
world effects on services such as commercial shellfish harvests or user recreation days.
This project will work with the modeling groups to develop the ecological production
functions necessary to translate model endpoints in indicators of ecological services.
(Lead- Milstead/Keith, EPA/NHEERL/AED)
3. DECISION SUPPORT
As the quality and quantity of ecosystem services are jointly determined by
ecological production and direct or indirect human consumption or enjoyment, a coupled
economic-ecological model is required for evaluating ecosystem service stocks and
flows. The strategy is to create economic-ecological decision support tools within which
decisions are represented explicitly, and baseline estimates can be updated as new
data become available and changes in ecosystem services can be estimated repeatedly
for different situations and in different decision making contexts. In terms of the DPSIR
framework (Fig. 2), this will complete the loop from ecosystem services -> decisions ->
drivers and pressures. Decision support research will use information from
Mapping/Monitoring (Goal 1) and Modeling (Goal 2). Specifically, results from the set of
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models described in Goal 2 will be summarized in production functions (relating drivers
and pressures -> ecosystem services) that are used in decision support tools. APWES
decision support research will involve improvement and development of existing tools.
Three different approaches are being used (DASEES, EOT, and MIMES), since they
approach decisions in different ways, and through our research, we will evaluate and
compare these different approaches. These tools fall at different levels of complexity,
so it is not a matter of selecting one, rather, we seek to understand which types of
approaches work best for which stakeholders, decisions, and scales.
Linking decisions to drivers and pressures requires a detailed understanding of
the decision-makers and the decision context. We recognize that ongoing interactions
with stakeholders are necessary for successful, useful products to inform decisions in
the Albemarle-Pamlico watershed and estuary (Table 2), We created a partnership with
the Albemarle-Pamlico National Estuary Program (APNEP) to support the delivery of
the products to decision-makers through the APNEP Policy Board and Management
Advisory Committee. The APNEP is one of six EPA National Estuary Program Climate
Ready Estuaries, so it is a particular focus for climate decisions. We are also in
collaboration with economists at CDC and economists and social scientists serving as
ESRP Special Government Employees for assistance on valuation.
Research gaps for decision support include: 1) how to translate decision
alternatives into scenarios for model input; 2) how information from process-based
models (Goal 2) are captured as production functions that can be used in decision tools
(building on 2.3.5); 3) how valuation approaches can be integrated with services and
decision support (Fisher et al. 2008), and 4) how decision support tools should be
delivered to stakeholders (e.g., what type of computer interface, what type of training
and technology transfer are needed). Within decision support research, we hope to
gain a better understanding of how to evaluate trade-offs across space and time
(Rodriguez et al. 2006).
3.1. Decision Analysis for a Sustainable Environment, Economy and Society
(DASEES)
The DASEES decision support tool supports multiple steps. First, it supports an
understanding of the context of a decision, though social network analysis and a "build-
your-own DPSIR" tool (and associated training module) that can be used by decision-
makers. Second, it develops an approach for identifying objectives, and includes a
"value of information for conflict resolution" tool to facilitate discussions among
stakeholders on costs and benefits of management actions. Third, DASEES supports
developing management options, with a database of "sustainable" options for land and
resource use decisions. Fourth, DASEES supports evaluating management options
with a Bayesian modeling tool that builds an influence diagram representing the
relationships within DPSIR, and the associated uncertainties. This tool allows users to
visualize the impacts of the various management options, including a breakdown of the
Impacts on the relevant ecosystem services and a comparison of the impacts on
ecosystem, economic, and social services. The APWES worked with the ESRP
Decision Support team to hold one stakeholder workshop in the basin (Sept. 2010), to
build a stakeholder community associated with the project. (Lead- Ten BrinkA/ega,
EPA/NRMRL in collaboration with Neptune, Inc.)
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3.2. Environmental Decision Toolkit (EOT)
The EPA environmental decision toolkit (EOT) is an interactive web-based
software application designed according to client input regarding key assessment
questions, issues, and management needs within a region. The EOT integrates
available spatial data and model outputs in different combinations, allowing users to
explore environmental conditions and vulnerabilities from a number of perspectives,
e.g., economic development, conservation planning, water quality protection. The
toolkit can be used to prioritize areas for management, identify watersheds for additional
monitoring or research, compare alternative future scenarios (once completed), and
complete an integrated assessment of conditions and vulnerabilities across an entire
region or basin. The toolkit provides both regional overview and zoom-in capabilities to
individual watersheds. The EOT is being developed for application across ESRP, with
targeted development for the Albemarle-Pamlico watershed (Lead- Smith,
EPA/NERL/ESD)
3.3. Multiscale Integrated Models of Ecosystem Services (MIMES)
The MIMES system is a suite of five submodels -Atmosphere, Lithosphere,
Hydrosphere, Biosphere and Anthroposphere - that are synthesized and interrelated.
MIMES enables understanding of the contributions of ecosystem services by quantifying
the effects of varying environmental conditions derived from land use change (Boumans
and Costanza 2007). MIMES evaluates effects of land use changes and management
decisions on ecosystem services, and how these in turn affect natural, human and built
capital. A benefit of the MIMES approach is that changes in the ecosystem feed back to
influence changes in the human system. (Lead- RoelBoumans, EPA Special Govt.
Employee)
SYNTHESIS AND FUTURE DIRECTIONS
The APWES mission is using ecosystem services science for informing
watershed decisions (Figure 2). Each of the three study goals provide direct input to
services and decision: assessments from Goal 1 can be used to support prioritization of
management actions, such as land acquisition, protection, and restoration. Model
forecasts (Goal 2) will be used to relate future land use and climate scenarios to
changes in services; and decision support tools (Goal 3) can be used directly by
decision-makers to run alternative management scenarios that explicitly relate decisions
to services. Projects goals are linked to one another: mapping/monitoring (Goal 1)
supports modeling (Goal 2), and both provide input for decision support (Goal 3). An
example of this model-data input connection is seen in the linkage of reactive nitrogen
flux measurements within APWES tidal wetlands, a current project within the
EPA/NERL/LCB (Figure 4). This theoretical schematic (Figure 4) helps to identify the
data gaps as wetland nitrogen flux is modeled from fine spatial scale/high model
complexity (i.e. process-based models) at the wetland level to medium spatial
scale/medium model complexity (spatially-distributed models) at the 6-digit HUC level
(i.e., Neuse River basin), and ultimately to the entire Albemarle-Pamlico watershed.
The work described will focus mainly on informing decisions most closely related
to the mission of EPA: water quality, water quantity, and wetlands. To inform these
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decisions, we will focus mainly on state-level decision-makers, and work with EPA
Region 4 to facilitate connections with the states. While our outreach to North Carolina
has been extensive, additional efforts are needed for Virginia. We plan to bring science
on both the ecosystem state and services to inform decisions (Figure 2). For example,
decisions on implementation of nitrogen TMDLs (and nutrient management strategies)
in the Neuse and Tar-Pamlico basins require a better understanding on the state of the
system (e.g., lag times, air and groundwater contributions) and well as the services
(how to optimize restoration efforts?) (Table 1). Similarly, wetlands management
requires knowledge of the state of the system to understand the role of wetlands in the
landscape and to establish significant nexus, as well as understanding how functions
and services are best conserved in compensatory mitigation. Banzhaf (2010)
emphasized the need to communicate the results of environmental economic analyses
to policy makers to help inform their decisions. We will employ economic analysis for
services, through incorporation of existing work (e.g., drinking water analysis in the
Neuse River basin, Elsin et al. 2010), or through the development of simple
approaches. Our vision is that in the future, watershed decisions will be made more
holistically, where multiple decisions and their impacts are considered together as
integrated watershed management. For example in the estuary, oyster reef restoration
is typically considered for improvement of harvest and reduction of public health risks,
but also has benefits for climate adaptation (Coen and Luckenbach 2000). We hope
that the APWES can lead to better watershed decision-making in the Albemarle-
Pamlico watershed and estuary, and ultimately benefit human and ecological well-
being.
This project is designed to be compatible with the new direction in EPA's Office
of Research and Development, the Sustainable and Healthy Communities Research
Program (SHCRP). The SHCRP integrates the three key elements of sustainability
economics, environment, and social (human health and social justice). The Albemarle-
Pamlico watershed and estuary can serve as a potential pilot site for the sustainable
regional communities component of the SHCRP, due to our existing research, as well
as other sustainability research in the region (Popp et al. 2001; "Sustainable Raleigh";
sustainable Roanoke - sustainableroanoke.org/). In particular, we envision partnering
with the Albemarle-Pamlico Conservation and Communities Collaborative (AP3C),
where several conservation and community groups are working together to protect the
region's natural resources while providing economic opportunities (Adams 2010). The
Albemarle-Pamlico watershed and estuary is characterized by multiple pressures,
landscape diversity, and upland-to-estuary linkage; possible urban (e.g., Raleigh, where
studies are already underway) and rural (e.g., Goldsboro, Elizabeth City) communities
are available as pilot sites across mountain, piedmont, and coastal ecoregions.
Because the watershed and estuary system is representative of other Atlantic slope
systems, the APWES will develop transferable products and outcomes for other
regions. The decision science and analysis developed though this project is
comprehensive and flexible enough to explore new SCHRP directions, including new
technologies and environmental justice. In the future, our vision in that the research
outlined here can support EPA's effort s to understand how the natural and built
environments interact to affect community well-being and sustainability.
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Low
n
Wetland Data and Modeling Flow Chart
Nr Loadings Modeling
(Lump-Sum Parameter Models)
_
c.
E
U
-o
o
Data Needs
LC (250m)
LC Change (250m)
Nr Loadings Modeling
(Spatially Distributed Models)
Data Needs
LC (20m)
Riparian Buffers (5m)
Legacy Sediments
Drainage Ditch Density (Agricultu
Wetlands Nr Modeling
(Process-based)
Data Needs
NRB
(6-digit HUC
Tidal Wetland
(14-digitHUC)
Biomass
Nr Flux
Wetlands Hydrologic Modeling
(Process-based)
Data Needs
Tidal creek density
Stem densities
High
Figure 4. Example data/model flow chart for reactive nitrogen in wetland showing interaction of mapping,
monitoring and modeling at multiple scales.
ACKNOWLEDGEMENTS
We are grateful to the reviewers of this plan (Dean Carpenter, Mark Brinson, Jana
Compton, Jessica Whitehead, Pete Kalla, and Joe Rudek) for their time and effort to
help improve this document. We are also grateful for the guidance of Wayne Munns,
Anne Rea, Jana Compton, and Kathryn Saterson for their initial direction in Feb. 2010.
This work builds on the past leadership of Dorsey Worthy and Deborah Mangis, and
could not be successful without their efforts. We also thank several stakeholders for
useful discussions: Dianne Reid, Dean Carpenter, Bill Crowell, Tom Augspurger,
Ashton Drew, Jack Thigpen, Paul Angermeier, Lisa Creasman, Joe Rudek, Sam
Pearsall, George Hess, Rich Sumner, the U.S. Geological Survey N.C. Water Science
Center, and the Duke Ecosystem Services Working Group members.
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APPENDIX 1. Expected APWES Products 2011-2014 (to be updated yearly)
Mapping and Monitoring Products
Estimates of atmospheric deposited
nitrogen load in the coastal environment
Mapping Biodiversity Metrics Representing
Ecological Services at the U.S. National ,
Regional, and Watershed Scales. EPA
report
FPZ coverage for the Neuse River basin
Maps of extent and quality of coastal
wetlands; relative levels of vulnerability for
coastal regions during the different
decades.
Detailed maps of water quality and
provisioning ecosystem services in the
Albemarle-Pamlico estuary
Year
2013
2014
2012
2013
2013
Section
1.1
1.2.4
1.2.5
1.3.1
1.3.4,
1.3.5
Notes
Schwede, Cooter, Dennis
(NERL)
Kepner, Neale Bradford
(NERL)
Flotemersch (NERL)
Lopez (NERL)
Keith (NHEERL)
Modeling Products
Air deposition predictions
30-year future climate predictions (monthly
2011
2011
2.1
2.2.1
Schwede, Cooter, Dennis
(NERL)
Johnson, Weaver (NCEA)
delta at weather stations) to support
modeling
Review Article: Limitations of the curve 2011 2.2.3
number relationship between rainfall and
runoff (APM)
Maps of Sea level rise inundation for 2.3.3
Morehead City area, NC
An evaluation of currently available models 2011 2.3.4
for estuarine species of interest.
Population models for selected high value 2012 2.3.4
resources
Ecological productions functions that 2012 2.3.5
empirically model relationships between
ecological response endpoints and
ecosystem services using biophysical data
McCutcheon (NERL)
Erickson (NERL)
Thursby, Ayvasian, Nye
(NHEERL)
Thursby, Ayvasian, Nye
(NHEERL)
Milstead (NHEERL)
Decision Support Products
DASEES system for the Neuse River basin 2012 3.1
Prototype EOT for APW 2011 3.2
MIMES model for the APW, including the 2011 3.3
estuary
Vega, Dyson , Tenbrink
(NRMRL)
Smith (NERL)
Boumans
36
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