EPA910-R-05-002
            United States
            Environmental Protection
            Agency
Region 10
1200 Sixth Avenue
Seattle WA 98101
Alaska
Idaho
Oregon
Washington
            Office of Water & Watersheds
              December 2005
            A Classification of Lakes in the
            Coast Range Ecoregion with
            Respect to Nutrient Processing

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                                                         EPA910-R-05-002
                                                            December 2005
    A CLASSIFICATION OF LAKES IN THE COAST RANGE ECOREGION WITH
                   RESPECT TO NUTRIENT PROCESSING
R.M. Vaga, US Environmental Protection Agency, Office of Water and Watersheds,
      Region 10, 1200 Sixth Ave. Seattle, WA 98101

R.R. Petersen, M.M. Sytsma and M. Rosenkrantz, Environmental Sciences and
      Resources, Portland State University, Portland Oregon, 97202

AT. Herlihy, Department of Fisheries and Wildlife, Oregon State University, 104 Nash
      Hall, Corvallis, OR 97331

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                                   DISCLAIMER
The information in this document has  been funded wholly  or in part by the United States
Environmental Protection Agency. It has been subjected to the Agency's peer and administrative
review and it has been approved for publication as an EPA document. Mention of trade names or
commercial products does not constitute endorsement or recommendation for use.
(Cover photo: An unnamed dune lake on the Southern Oregon coast. Photo by R.M. Vaga)
                                         11

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                       TABLE OF CONTENTS








                                                     Page




ABSTRACT	  iv




1. INTRODUCTION	   1




2 LAKE INVENTORY	  2




3. CLASSIFICATION OF LAKES IN THE COAST RANGE ECOREGION ..   4




4. ANALYSIS OF HISTORICAL WATER QUALITY DATA	   12




4. NUMERIC CRITERIA DEVELOPMENT AND BENEFICIAL USES	  24




5. REFERENCES	 29




6. APPENDIX	 31
                              in

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                                  ABSTRACT
This report presents one methodology to classify natural lakes with respect to nutrient
processing. Lakes in the Coast Range Ecoregion were inventoried and lakes greater than
4 ha in surface area were chosen as the target population.  A methodology was then
developed based upon "expert opinion" to categorize lakes in the ecoregion based upon
basic limnological principles.  The categories were developed without recourse to nutrient
data.

Analysis of total P, total N, chlorophyll and Secchi was carried out for 1) the Coast Range
lakes as a whole and 2) for each lake category. Results suggest that these parameters
have inherently different variability among lake categories which affects their utility in
developing numeric nutrient criteria.

Stratification of lakes was also performed using Level IV Ecoregions.  Although a rough
correlation appeared to exist between lake category and ecoregion, data were insufficient
to draw any conclusions.

Two empirical methods are described whereby numeric nutrient criteria can be derived in
relation to beneficial uses.
                                       IV

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This report presents the results of a study
conducted in the Coast Range Ecoregion in
support of the nutrient criteria development
effort in Region 10 EPA. The goals of this
study were to 1) define the population  of
lakes and reservoirs  in  the  Ecoregion,  2)
classify the  lakes with  respect to nutrient
processing based on limnological principles,
3) analyze water quality data to characterize
the lake categories and 4) explore methods to
derive numeric criteria for the nutrient criteria
variables (Total P, Total  N, chlorophyll and
Secchi) in relation to designated uses.

The approach used in this study was adapted
from  methods  described  in  the  Nutrient
Criteria Technical Guidance Manual:  Lakes
and  Reservoirs  (EPA 2000).   Figure 3-1
presents a flow chart of the methodology
used for deriving numeric nutrient criteria for
lakes in the Coast Range Ecoregion.  Lakes
were  inventoried  (Chapter 2)  and  lakes
greater than 4 hectares in surface area were
considered  the   population  for   which
categories  were  to   be   derived.     A
methodology to categorize lakes based upon
"expert opinion"   and  basic  limnological
principles was developed for this population.
The   categories   were  developed without
recourse to nutrient data. As a result  seven
categories were  developed as described in
Chapter 3.

Analysis of Total P, Total N, chlorophyll and
Secchi depth was carried out for 1) the Coast
Range Ecoregion as a whole and 2) for lake
categories. Results show that the categories
roughly defined different trophic conditions.
In  addition   an  analysis   of  variance
components in the historical  data  is  also
presented.   Results  suggest the  different
parameters  have   inherently  different
variability  which  affects  their  utility  in
developing numeric criteria.
CHAPTER 1. INTRODUCTION
                   appeared to be a rough correlation between
                   Level  IV Ecoregion and  lake category but
                   there have been too few lakes categorized to
                   draw any firm conclusions.
                   Two empirical  methods to develop numeric
                   criteria in relation to beneficial  uses are
                   presented in Chapters. The illustrations show
                   that while empirical descriptions of reference
                   lake types are  possible, the development of
                   numeric criteria for Total P vis-a-vis beneficial
                   uses requires  specific interpretation  of the
                   definition of the beneficial use and judgement
                   regarding  how  protective  to  make  the
                   criterion.

                   In this report we demonstrate that for certain
                   Ecoregions, stratification of lakes at the Level
                   III  and  even  Level  IV  Ecoregion  is not
                   sufficient for  classification  purposes with
                   respect to nutrient processing.  The  use of
                   non-codified, unpublished information, e.g.
                   local and 'expert judgement' are a source of
                   information  of significant  value  in lake
                   classification.
Stratification  of  lakes  by  category  was
compared to Level IV Ecoregions.  There

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                 CHAPTER 2. DEFINING THE LAKE POPULATION
2.1 Methods

The Coast Range Ecoregion extends from the
tip of the Olympic Peninsula in Washington
State to the  Oregon-California border and
approximately 50 miles inland from the Pacific
Ocean (Omenik, 1986) (Fig. 2-1).  Spatial
data on lakes and reservoirs in the Coast
Range Ecoregion used in this report were
obtained from various sources. The spatial
data  were checked and corrected  using
topographic   maps  for   Oregon   and
Washington  (Delorme  1998,2001).    A
complete description of the procedure used to
verify the spatial data is described in Vaga
and Herlihy (2004).  Lakes greater that 4 ha
in  surface area were defined as the target
population of lakes.  This size of lake was
selected because it is readily identifiable on
the topographic maps used in the verification
process.
2.2 Results

There are a total of 353 named lakes in the
Coast Range Ecoregion (Appendix Table 1).
Of those, there are 171 lakes greater than or
equal to 4 hectares in surface area and 182
less than 4 ha  (Table 2-1).   Of the 171
features greater  than 4 hectares that were
identified as existing on the landscape, most
were confirmed  to  be lakes.    It was  not
possible to determine from maps whether 16
features were actually lakes. However, they
were  included   in  the  population.    For
purposes of this report, the lake population in
the Coast Range Ecoregion  is therefore
defined as the set of 171 lakes.

Lakes  are  found  in  the Coast  Range
Ecoregion from southern Oregon to the tip of
the Olympic Peninsula in Washington  (Fig.
2-1). The highest density of lakes is found on
the southern Oregon Coast where many of
the lakes are right on the Pacific Coast, e.g.
 A Lakes

Level III Ecoregions
   | Coast Range
    Klamath Mountains
    North Cascades
    Puget Lowland
   I Willamette Valley
         Figure 2-1. Location of the 171 lakes > 4 ha in
         surface are in the Coast Range Ecoregion.

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dune lakes.   There  are no lakes north of
Grays Harbor in Washington that are truly
coastal, i.e. right on the coast.  Most of the
lakes in Washington are inland (Fig. 2-1).

The cumulative distribution of lakes > 4 ha in
the Ecoregion with respect to surface area is
presented  in Figure 2-2.  About half of the
lakes (n =  86) are less than 11  hectares in
surface area.

The total lake surface area of the 353 lakes
is  156.3 km2. The171  lakes  >  4 hectares
accounted  for 153.9 km2 or over  98% of total
lake area in the Ecoregion.

Very few lakes account for a large percentage
of the total surface area of lakes.  Just over
fifty  percent of the  total lake area  in  the
Ecoregion  is accounted for  by only 5 lakes
(LakeOzette, Lake Crescent, LakeCushman,
Lake Quinault,  Siltcoos Lake)   (Fig. 2-3).
There are  30 lakes larger than  50 ha and
these account for 89% of the total surface
area (Appendix Table 2). Lake Ozette (3,007
ha) is the largest lake in the Ecoregion and
alone accounts for 19.3% of the total surface
area.
LLJ
o
e
U]
0.
I
5
O
   100
   80
   eo
40
20
             50
                     100
                             •BO
                                     200
                 LAKE AREA flia)
 Figure 2-2. Cumulative distribution of lake
 surface areas of lakes in the Coast Range
 Ecoregion (> 4 ha). About half of the lakes are
 less than 11 ha in surface area.
            0.5   1.0   1.5  2.0   2.5   3.0

               LAKE SURFACE AREA (ha x 1000)
                                      3.5
                                               Figure 2-3.  Cumulative disbribution of total lake
                                               surface area in the Coast Range Ecoregion by lake
                                               size. The five largest lakes in the region account for
                                               one-half of total lake surface area.
Table 2-1.  The number of lakes in Coast Range Ecoregion  < 4 ha and > 4 ha in surface area. The
number of lakes > 4 ha in the Coast Range Ecoregion accounts for only 48% of the Total Number of lakes
but 98% of the total lake surface area.
Total
Number of
Lakes
353
Total
Number
(< 4ha)
182
Total Area
(< 4ha)
(sq km)
2.4
Total
Number
(a 4 ha)
171
Total Area
( 2 4 ha)
sq km
153.9
% Numb
(;>4ha)
48
%
Area
(* 4ha)
98
Density
No/sq km x
100
0.05

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  CHAPTER 3. CLASSIFICATION OF LAKES IN THE COAST RANGE ECOREGION
3.1 Introduction

The EPA National Nutrient Strategy calls for
setting water body specific nutrient criteria
for lakes  and reservoirs.   Documentation
provided by  EPA  suggests a  number  of
approaches  for setting nutrient criteria for
individual lakes. (EPA,  2000).  Importantly,
the Manual recommends  segregating lakes
by  Ecoregion  (Omernik) and identifying
lakes   thought  to  be  representative  of
undisturbed conditions ("Reference Lakes").
  Implicitly,  these   recommendations
recognize the necessity of assigning lakes
to  categories   of  similar   limnological
character  to allow  setting realistic  and
useful  criteria for  nutrients.   Indeed, the
Technical  Guidance  Manual  explicitly
recommends the  development  of  ..."a
classification  scheme   for  rationally
subdividing the population of lakes  in the
State"  .   A  classification scheme for the
lakes  in the Coast Range  Ecoregion  is
presented as a step toward  setting criteria
that are neither unrealistically permissive for
several  large, very oligotrophic lakes nor
impossibly restrictive for many smaller lakes
heavily influenced by wetlands.
3.2  History  of  the  concept  of  lake
classification or lake tyopology

Lake classification or lake tyopology has a
long  history  in  limnology.    The  most
important of the early (1900 to 1920) effort
on  lake classification was work by August
Thienemann in Germany and Einar Nauman
in  Sweden, who together introduced  the
now  generally  accepted  scheme   of
oligotrophy to  eutrophy  to describe  the
general patterns of variation in  lakes (Moss
et   al.  1994).     Indeed,  the  trophic
classification  system   became  a  central
paradigm   in   modern  limnology.  Other
systems of classification  were developed
based  on  geological origin of  lake  basins
(Hutchinson,  1957)  or  annual  temperature
stratification  patterns   (Hutchinson  and
Loeffler, 1956).

Naumann and  his  successors  continued
with  constructing ever more elaborate lake
tyopology schemes.  The belief in the utility
of the approach reached its apex when lake
tyopology (Seetypenlehre) was the  major
topic  of the  International  Congress  for
Limnology in Finland in 1956  (Moss et al.
1994).  However, Moss et al.  (1994) point
out in their review that the "concept of lake
types was flawed and attention [turned]  to
processes  in  lakes."   Beginning  in the
1960s, it was recognized that each lake was
unique  and that lakes vary  continuously
along many variables.  Moss et al. conclude
their historical review with:  "But the concept
of discrete types is dead...".

Nevertheless, Moss et al  (1994) return  to
the issue of lake classification  as a means
to deal  with  cultural  eutrophication and
environmental regulations meant to cope
with  the problem.   They recommend  a
scheme  based  on three  "major  axes"
(roughly,  morphometry,  major  ions  and
nutrients) as a method for the classification
of individual lakes  while avoiding  "...a
tyopology with   named  units  defined by
preconception".   Their intent is to describe
lakes in their  present condition  and  to
provide  a framework for estimating the prior
condition of each lake  before the onset  of
cultural eutrophication.  Nevertheless, in the
end,  they adopt a set of discrete categories
because continuous  variation leads to "...an
infinity of possibilities not practicable in a
scheme  intended   for  use  by  statutory
regulatory authorities." In short, the concept
of Seetypen (Lake  Tyopology)  has been
abandoned but the classification of lakes in
some   manner  has   reemerged   as  a
necessary  component  of setting  realistic
criteria for nutrients in lakes.

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3.3   Current   research   in
classification
lake
A   current  approach   to   develop  lake
classifications   is  to   use  multivariate
statistical methods based on the structure of
the  data   collected   from   the   lakes
themselves, or  as stated  by Thierfelder
(2000):   "...  a supplemental  approach to
lake  classification  is   conceivable.  With
exploratory   methods  of   multivariate
statistical   analysis,  relatively   objective
analyses of empirically  observed data are
facilitated."

Thierfelder demonstrated such an analysis
using data collected from 76 Swedish lakes
sampled monthly over a period of 5 years.
He based  his  analysis  on pH,  alkalinity,
conductivity, hardness, color, Secchi depth
and Total  Phosphorus data. Data for each
parameter  were  linearly  transformed  to
approximately   suitable  statistical
distributions.  Theirfelder then analyzed the
data  by  principal  components  analysis,
obtaining just two principal components that
efficiently   described  most of  the  data
structure.   The first  principal  component
could be  represented  by  hardness alone
(pH, alkalinity  and conductivity were highly
correlated with hardness),  and  the  second
principle component could  be represented
by  color alone (Secchi  depth  was  highly
correlated). The result was a 2 dimensional
framework,  one  dimension for  inorganic
characteristics (hardness) and a second for
organic  characteristics  (color)  for  the
classification of individual lakes  (his figure
4).  Individual lakes were then plotted on the
resulting   framework   based   on   their
individual   water  quality  characteristics.
Thierfelder concludes:"...the  base  is well
suited   for the  chemometric   lake  water
classification  in  accordance  with  the
objectives set."

Toivonen  and  Huttunen (1995)  also use
multivariate  statistical   methods  for  lake
classification using TWINSPAN, followed by
ordination with detrended correspondence
analysis   (DCA)   and   canonical
correspondence  analysis (CCA).    They
compare  the  results  with   two a  priori
classification   systems:   the  trophic
classification  system and  the  traditional
Finnish botanical lake classification system.
For their  analysis they  included data  on
altitude   above   sea  level,  lake  area,
maximum depth,  pH, conductivity,  Secchi
depth  and  color.    (They   assume that
conductivity is  a good overall parameter  for
the general  nutrient status.)  They used
data from 57 small lakes in southern Finland
collected over several years.  Using the a
priori classification systems,  they described
six groups  of  lakes  based on  trophic
conditions and dystrophic influences.  The
multivariate methods, applied to data on the
species composition  of  the macrophytes
collected from the lakes, produced much the
same groupings.  They conclude: "Most of
the final  ...clusters constitute more or less
recognizable lake groups, which  match to a
great  extent  the  a priori  groupings."
Nevertheless, Toivonen and  Huttenen note
a common difficulty:  ..."some of the lakes
are  difficult  to  place  [into   a  priori
groupings]."  In this regard, the dichotomous
classification produced by TWINSPAN (their
figure 4)  is based on objective criteria and
doesn't  require  the  sometimes arbitrary
designation of borderline  lakes under the a
priori classification systems.

A   third   very  useful   example   is   a
classification   method   suggested   for
northern Wisconsin lakes by  Emmons et al
(1999).  They also note that the uniqueness
of individual  lakes  poses a challenge  to
management approaches,  since effective
management requires some  generalization.
To this end, they observe:   "Classification
systems   that  account   for ecologically
meaningful variation provide  a way to group
lakes  into units in which similar  ecological
processes operate and similar responses to
anthropogenic  impacts  or  management
strategies   can  be  expected."   They

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examined  two   alternative   classification
procedures for the  nearly 15000 individual
lakes in  Wisconsin, one a familiar use  of
multivariate  methods and  the second an
iterative dichotomous splitting of the  lakes
to form  a hierarchical  classification  tree.
Their objective was to  compare a cluster
and  discriminate  analysis approach with a
tree-structured classification approach with
data  from Wisconsin  lakes.   The  data
(originally reported  in  Lillie  and  Mason,
1983) consist of  morphometric parameters
(lake area, maximum depth, drainage  basin
area),  inorganic   chemistry   (calcium,
magnesium,   alkalinity,   chloride,  pH),
nutrients  (Total   Phosphorus,   Total
Nitrogen), Secchi  transparency, turbidity,
and  chlorophyll a for a total of 667  lakes
sampled  during 1979. They first describe a
multivariate  method  of  classification  that
uses cluster analysis (k-means) to form lake
groups and discriminate function analysis to
assign  individual   lakes  to   the  clusters
(following methods of Schupp, 1992).  They
also discuss  some of the weaknesses  of
multivariate  approaches,  notably that the
results are often difficult to interpret and  to
explain for management purposes.  As an
alternative,  they   proposed  using  tree-
structured methods, know  as classification
and  regression  tree  analysis  (CART).
They argue that the tree-structured methods
..."may  provide   a   powerful  tool   for
classifying ecological units in a reliable and
interpretable  framework",  in  part because
such  methods   recognize  the   often
hierarchical  data  structure of  lakes.   A
significant  problem  with  tree-structured
approaches   is  that  they  require  group
membership to be known in advance. In the
end,  the authors  adopt  a   method  that
combines aspects of both approaches.  "We
propose combining some of the advantages
of  tree-structured  methods  with  cluster
analysis into an approach that forms groups
and  models group  membership.  We take
advantage of the   recursive  nature   of
classification   trees  to   include  variable
interactions,  hierarchical relationships, and
reduction  of  dimensionality  while  avoiding
some  of  the  potential  pitfalls  of  more
traditional  multivariate techniques."   As a
final result, they identify six clusters of lakes
(their figure 3) based on familiar limnological
parameters.  The lakes were first split into
two large  groups based solely on alkalinity
(more   or  less  than   55  mg/l),   with
subsequent splits  based  on morphometric
characteristics  (depth,  area)  or nutrients
and water clarity.    In the  authors words:
"This  results in  a  more  accurate  and
interpretable  classification  with   fewer
variables...".

In summary,  although lake  tyopology  may
have fallen into disuse, the need to classify
lakes for  management purposes  persists.
As  part of an effort to implement realistic
nutrient  criteria,   some   system   of
classification  is  necessary.    On  the  one
hand,  the  great  variety  of  limnological
conditions  must be recognized  by  any
system for setting criteria, but in the  end,
criteria  must be  established for  individual
lakes to have any management value.  It is
of interest that  the three examples  cited
make use  of the latest multivariate statistical
methods yet arrive at classification schemes
that  can be described in  terms of familiar
and  traditional  limnological  characteristics:
water color and clarity, lake morphometry,
major ion  chemistry and of  course  nutrient
concentrations.   It is also  worth noting that
each of the three examples was based on
the  analysis of  a  very  large database.
Unfortunately such data are not generally
available  for lakes  in  the Coast Range
Ecoregion.

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3.4  Coast   Range  Ecoregion   Lake
Classification: "Expert Opinion"

As part of an effort to gather data  for the
development of lake  nutrient  criteria for
lakes  in   EPA  Region   10,   data  were
collected  during  1999  and  2000  for 24
lakes,  all  in  the  Coast  Range  Ecoregion
(Omernik  1986).  The lakes were selected
randomly  from a  database  of  all  known
lakes in the  Ecoregion using a procedure
developed for the Environmental Monitoring
and   Assessment   Program  (EMAP)
Northeast Lake Survey (Larsen et al. 1994),
and  can  therefore  be  interpreted  as  a
representative sample of all the  lakes in the
Ecoregion.

Lake categories were constructed based on
this   sample   of  24   following   the
recommendations  in   the  EPA  Nutrient
Criteria Technical Guidance Manual  (EPA,
2000).    The  categories  were  developed
without reference to  nutrient  data,  i.e.
characteristics other than trophic state were
used  to  define  a category.   They were
developed  by the  authors with  input from
local experts.  The categories are based on
how  the  lake might be  described  by the
author to a  local limnologist who is  not
familiar with  the  particular lake.    The
categories   may   be   thought   of   as   a
"thumbnail sketch" of  the  lakes.    The
categories  are  explicitly  not   meant  to
represent a gradient of disturbed to pristine.
Rather, the categories are based  on  the
overall character of the lakes. A flow chart
of the categorization scheme is presented in
Figure 3-1.   Within the various  categories
are lakes that are nearly pristine or partially
disturbed by human influence. The possible
interaction  between degree of disturbance
and lake category is discussed below. Thus
the  categories  presented  here  were
constructed based on  what appeared to be
significant  characteristics  influencing  their
limnological character.
All lakes in the sample are from the Coast
Range Ecoregion.  It is recognized that the
sample  size  is  not  sufficient to justify  a
proper statistical description of the various
categories.   Instead,  the  categories  are
suggested based on the notion of  "expert
opinion"  suggested  in  the EPA  manual.
While not sufficient to develop a statistically
sound  lake  classification,  the results do
suggest  that   designation  of  lakes  by
ecoregion alone will  not be  sufficient to
recommend appropriate nutrient criteria for
the entire Ecoregion.  The results suggest
that  morphometric characteristics such as
mean depth  and  exposure to  the  direct
influence of coastal winds, dissolved humic
substances (color), and major ion chemistry
can  influence   lake  characteristics  and
should be reflected in  appropriate nutrient
criteria  designations.    Clearly,  additional
random sampling  would be  necessary to
extend  the  list  and   construct  similar
categories for other Ecoregions within EPA
Region 10.
3.5 Lake Categories

Seven lake categories were identified in the
Coast  Range  Ecoregion.  The lakes were
assigned to categories according to  their
overall appearance, or as noted above, how
they  might  be   described   to  a   local
limnologist.    Characteristics  that appear
significant  include the  effects of wetland
drainage  (dissolved  humic   substances),
mean   depth,   wind   exposure,   and
surrounding soil type (sand versus other soil
types).   The  conceptual  scheme for  this
classification is presented in Figure 3-1  and
defines seven categories.   Category 7 is
composed  of  unique  lakes which are not
subject to  classification based  upon  this
scheme. The location of each of the lakes is
presented in Figure 3-2.

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                               ALL COAST ECOREGION LAKES
                                            n = 353
                                  No
                                       Unique Characteristics "
                                                             Yes
                                            Place into existing
                                            categories or consider
                                            case by case
                                            n = 182
                                Meromictic due to
                                seawater ?
                                                                Yes
               Humic influence9


                 Yes
                                        LAKES WITH LITTLE
                                        HUMIC INFLUENCE
          1  DYSTROPHIC LAKES
            n = 11
                      6 SEAWATER
                        INTRUSION
                        LAKES
                        n = 1
    Lakes < 1 km from coast
                                                             No
                                                                   Lakes man made '


                                                             Yes      /  \    No
        2 SHALLOW COASTAL
          LAKES
          n = 12
3 DEEP COASTAL
  LAKES
  n = 10
4 FORESTED
  LAKES
  n = 15
5 LOG PONDS
 n = 4
Figure 3-1. Schematic illustrating the characteristics used to categorize lakes in the Coast Range Ecoregion.
The number of lakes in each category is also shown. See text for explanation.
 Category  1:     Lakes   with  significant
 dystrophic influence.

 Lakes  in this  category are relatively small
 and  have a watershed with a significant
 amount  of  wetlands  (Table  3-1).    The
 primary causal factor  of the designation is
 the  presence   of   large  to  moderate
 concentrations  of   dissolved   "humic"
 materials. The immediate effect of the
            humic   materials   is   to   limit   water
            transparency,  although  other  effects  may
            also be important (Williamson  et al.  1999).
            For some of the lakes (Cullaby, Clam) this
            lack of  transparency is  almost certainly
            sufficient to bring about light limitation  of
            primary production.   The remaining  lakes
            may be less prone to light limitation  in spite
            of the  presence of significant  dissolved
            organic matter as a  consequence  of  their

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very shallow depth.

These  lakes  are  also  characteristically
shallow (maximum  depth of 7  meters or
less).    Cultural  eutrophication  influences
vary from very little  to strong.  These lakes
can be either  strongly dystrophic (highly
colored, e.g. Clam  Lake, Creep  and Crawl
Lake,  Cullaby  Lake, Long Lake  or have a
somewhat   lower  dystrophic   influence
(colored, e.g. Freshwater Lake, Island Lake,
Sunset Lake, Failor, Wentworth).

There is some tendency for  loss of oxygen
near the bottom of each of these lakes,  i.e.
clinograde oxygen profiles.  It is  likely  that
the tendency for  low oxygen at  depth  is a
result of decomposition of the relatively high
concentration of dissolved organic matter.
Category 2: Shallow Coastal Lakes.

The  defining characteristics of these lakes
are their shallow mean depth,  large surface
area  and  frequent  exposure  to strong
coastal winds, resulting in polymixis (Table
3-1,  Fig.  3-2).  Mean depth ranges from 1 to
3 meters. The lakes mix frequently and are
stratified only weakly and for short periods.
Not   surprisingly,   they   remain   well
oxygenated  from  top  to  bottom.    Water
transparency,  as  measured by the Secchi
disk,  is  sufficient  that light  limitation of
primary production is  not probable in these
shallow lakes.

Cultural eutrophication influences vary from
slight to moderate.

Category 3: Deep Coastal Lakes.

Lakes in this category have a  large surface
area and are sufficiently deep (mean depth
greater than 4 meters) to stratify during the
summer  and  are  accordingly designated
"Deep Coastal Lakes". Each of these lakes
lies in a basin formed by sand dunes (still
Figure 3-2. Location of lakes in the Coast Range
Ecoregion that were placed into one of the seven
lake categories.

-------
Table 3-1.  List of lake categories, number of
lakes in each category (n) and mean lake area ±
1 sd.
Lake
No Category
1 Dystrophic Lakes
2 Shallow Coastal Lakes
3 Deep Coastal Lakes
4 Inland/Forested Lakes
5 Log Ponds
6 Seawater Intrusion Lakes
7 Unique Lakes
n
11
12
10
15
4
1
5
Mean
Area
(ha)
32.1 ± 34
293.6 ± 280
158.4 ± 122
114.6± 123
16.5 ± 10
53.1 ± -
2123.5 ±577
active in some cases).  Each of the lakes in
this category develops  pronounced thermal
stratification during the summer.  The depth
of the thermocline  at the height of summer
stratification is conspicuously related to the
degree of exposure  to  the typical coastal
northwest wind.  The most protected of the
lakes, Laurel Lake, develops a thermocline
at about  4  or 5 meters,  as do  the central
and northern basins  of Collard  Lake.  The
southern  basin of Collard Lake  and Sutton
Lake are more exposed and each  develops
a thermocline at about 7 meters. The most
wind-exposed  lake,   Woahink  Lake,
develops a thermocline at 16 to 17  meters.

The watershed of each of the lakes includes
a   number   of  residences   although
eutrophication effects are not obvious.

Category 4: Inland and Forested  Lakes

Lakes in this  category  are located in  the
Coast Range  of Oregon and the Olympic
Peninsula of Washington and are typically
surrounded  by  hills covered  with  native
forest,  mostly  second  growth  (Fig 3-2).
Most are not directly influenced by coastal
winds.  Surface area  varies widely
(Table3-1).

There   are   many  residences  on   the
immediate  shore  of  Triangle  Lake  and
Pleasant Lake but few or no residences in
the watershed of the  others.  Rink Creek
and Ollala are water supply reservoirs, and
experience changes  in surface elevation
depending on  precipitation and demand for
water.  Because of the considerable number
of residences around Triangle Lake, it might
be anticipated that this lake would be more
eutrophic than the other lakes.
Category 5: Log Ponds.

Each   of  these  lakes   is  actually  an
abandoned log  pond.  They were originally
constructed  by  excavation   and   dike
construction,  resulting  in  small  shallow
basins.   Although  they owe their origin to
their use as  log ponds,  none  have been
used for that  purpose for many years. The
ponds  are  still  cluttered  with  debris  from
their  original   use:  scattered   logs  and
branches.  Each  is  shallow,  weedy  and
surrounded by re-grown alders.

These  ponds  are small and too shallow to
stratify,   but  nevertheless  oxygen  was
sometimes  depleted (Table 3-1).   At the
time of sampling, Johnson Log Pond was
less than 50%  saturation  throughout the
water column.  Lake Creek exhibited very
low oxygen in  the deepest half  meter of
water, and  Vernonia Pond was about 25%
less than saturation from top to bottom.

The ponds are now used  by  anglers, but
without  any "official" developed boat ramp.
Currently there is no evidence of activities in
the watershed  that  might  contribute  high
nutrient concentrations in  water flowing into
the  lakes.     However,   each  receives
considerable  use by anglers and all show
evidence of a history of heavy impact from
their prior use as a  log pond.
                                          10

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Category 6: Sea water intrusion.

This category consists  of  a single  lake,
Garrison Lake, which contains a very high
concentration of sea water from a recent
intrusion during a winter storm.   (The lake
would probably be grouped with Category 3
without   the  seawater  intrusion.)    The
intrusion of  salt  water has  produced  a
meromictic   lake   with    predictable
consequences.    The  monimolimnion   is
anoxic and  highly saline. Depending on the
date of  sample collection, the chemocline
may  be supersaturated  with oxygen  or
under saturated.

In terms of  its location and morphology,
Garrison Lake could be expected to share
the same characteristics as "category 2", or
more  likely, "category 3" lakes (Fig.  3-2).
Indeed,   data from  earlier  years suggest
such  an assignment.   However, a major
winter  storm  overtopped  the  dunes
bordering the western side  of  the  lake,
introducing  a  large amount of seawater into
the lake.   The  seawater  remains in the
deeper northern basin of the lake as a very
heavy deep layer, or monimolimnion, at the
bottom of the lake.  For the last 2  years, the
lake has not destratified at any time, and is
therefore  clearly  an  example   of   a
monomictic  lake.     The   very  strong
stratification  and  the  presence  of   a
chemocline  have  introduced   a  novel
influence to the lake and make it  distinctive
among  the lakes  in  this  sample.   The
monimolimnion  is  completely  anoxic.
Oxygen   profiles are  sometimes positive
heterograde,   with   a   considerable
supersaturation (with  respect to surface
atmospheric pressure) accumulating in the
chemocline.    Nutrient  values  in  the
monimolimnion  are  apparently  very  high.
No data are  available on the presence of
reduced chemical species such as sulfide or
ferrous iron, but it is likely that such species
are accumulating.  The present meromictic
condition is likely to persist  for a very long
time, with the accumulation of more reduced
chemicals in the monimolimnion.

Based    solely   on  water   quality
characteristics  of the mixolimnion, Garrison
Lake could  be described  as  mesotrophic,
and  similar to  lakes  in  "Category  3".
However,  the  presence of the very high
nutrient   concentrations   in   the
monimolimnion and very high  oxygen and
chlorophyll, at times, in the chemocline defy
such  a  classification.   Any  reasonable
designation  useful  for   setting   nutrient
criteria for the lake will need  to take the
present  meromictic character  of the lake
into account.
Category 7: Unique, Very Large Lakes

These lakes are lakes that cannot be placed
into any of the other six categories due to
their unique nature, primarily large surface
area and depth (Table 3-2).  For example,
Lake Crescent (2,004 ha) has a mean depth
of 92.8  meters  and Secchi transparencies
that  typically exceed 15 meters.   Lake
Ozette (3007 ha) has a mean depth of 38.4
meters  but  due to  dystrophic influences
Secchi transparency seldom  exceeds 3.5
meters.
                                         11

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                CHAPTER 4.  ANALYSIS OF WATER QUALITY DATA
4.1 Introduction

We combined data  for Coast Range lakes
collected in the 1999 - 2000 sampling with
the large 1,000+ site historical database for
Region  10 lakes described in an  earlier
report (Vaga and Helihy 2004).

For regional  analysis  of the  lake  data, a
single value was created, the summer lake
index value, for each  lake and parameter.
Only surface data   collected between May
and October  (inclusive)  were  used.   For a
given parameter a  lake  index value was
calculated by first taking the median for the
parameter  for  each  year and for each
unique lake sample location in each lake. A
median value for each sample location was
calculated by taking the median across all
the yearly medians.  The final lake summer
index value was then  taken as  the median
of all the median site location values for all
sites on each lake.   For lakes with only one
sample site, the index value  is simply the
median  of all the   yearly  median  surface
May-October data.    Medians  were used
instead of means to minimize the influence
of large  outliers.   By  taking  yearly and
station medians at each lake we minimized
the influence of  large  sample sizes in just
one   year   or   one  particular sampling
location.

To   investigate  relationships   among
parameters,  a monthly  median parameter
value for each lake was calculated by taking
the median across all  lake stations by year
and month (Appendix Table 3).  Lakes from
the historical data set were classified into
one  of the seven categories described in
Section 3 (57 of 71 lakes).
 4.2 Ecoregional Patterns

 Median Ecoregional values of water quality
 parameters were indicative of  mesotrophic
 conditions. For the 71 lakes for which water
 quality data exist, median Total  P was  15
 ug/L, Total N 270 ug/L, Secchi depth 3.4 m
 and chlorophyll  4.9  ug/L  (Table   4-1).
 Interquartile  ranges  were  small,   as
 compared with the median  values.

 There  were strong  relationships between
 parameters  across   lakes  (Table   4-2).
 Regressions  of  log-transformed  monthly
 means were highly significant in all cases.

 Total  N increased with Total  P  across  all
 lakes (Fig. 4-1). Total P  ranged from  <1
 ug/L to over 100 ug/L and  Total N from less
 than 20 ug/L to over 1  mg/L.    Monthly
 median chlorophyll increased with Total P
 concentrations across lakes but  there was
 large amount of scatter in  the  data (Fig. 4-
 2).  There was a strong decrease in Secchi
 depth  with   increasing   chlorophyll
 concentrations (Figs.  4-3).

 There   was  also  a  strong  relationship
 between and Secchi depth  and Total P
  •i

  8
  i«
  i
  e  i
      Late
      Categoty
                     «** Shaltow Goosta
            0 Ruwted     -*' ~~ Log PEwifa
     0.0
                                      2.5
           0.5     1.0     1.5     2.0
           LOG TOTAL PHOSPHORUS (ug/L)
Figure 4-1. Relationship of monthly median Total
N and Total P across all lake categories.  There
was a clear increase in Total N with  Total P.
Regression is for all data.  Dashed lines are ±
95% confidence envelope.
                                          12

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Table 4-1.  Summary of summer index 25th percentile, median and 75th percentile values for all lakes in
the Coast Range Ecoregion and lakes in each lake category. The number of lakes (No) refers to the Total
Number of lakes having Total P data.  For comparative purposes 25th percentile values Ambient  Water
Quality  Criteria  Recommendations  are  also  presented for the Western  Forested Mountains and  Coast
Range Ecoregions (Level III) (EPA 2000).
Cat


1
2
3
4
5
6
7
Category Name

All Lakes
Dystrophic
Shallow Coastal
Deep Coastal
Inland/Forested
Log Ponds
Sea Water Intrusion
Unique
Western Forested Mtns.
Coast Range Ecoregion
No

71
11
12
10
15
4
1
4
296
71
Total P Total N Chi Secchi
(ug/L) (ug/L) (ug/L) (m)
25th
10.0
71.8
15.0
9.8
9.5
27.5
-
8.4
8.8
10.0
Med
15.0
81.0
22.8
11.5
10.0
39.0
30.0
9.6
-
15.0
75th
26.0
159.3
26.8
18.0
15.0
92.0
-
11.3
-
26.0
25th
180
530
250
160
150
495
-
64
100
180
Med
270
650
320
220
225
875
365
105
-
270
75th
520
940
638
230
280

-
140
-
520
25th
2.2
7.7
0.8
2.2
2.1
7.6
-
0.4
1.9
2.2
Med
4.9
16.6
6.1
2.4
4.6
7.6
3.3
1.1
-
4.9
75th
10.3
25.5
7.8
4.2
7.3
7.6
-
10.2
-
10.3
25th
2.0
0.6
1.9
4.0
3.0
1.0
-
3.8
4.5
2.0
Med
3.4
0.9
2.0
4.5
3.9
1.0
3.2
10.1
-
3.4
75th
4.2
1.3
2.5
5.6
4.2
2.0
-
17.4
-
4.2
' Values from Table 2, Reference conditions for Nutrient
* Values from Table 3a, Reference conditions for Level I
                                           Ecoregion II lakes, Western Forested Mountains. (EPA 2000).
                                           II ecoregion I, Coast Range Ecoregion. (EPA 2000).
   1.5
   10
   0.5
   0.0
     0.0
                                           2.5
            0.5      10      15     2.0
            LOG TOTAL PHOSPHORUS (ugyL)
Figure  4-2.   Relationship  of monthly median
chlorophyll to Total  P across all lake categories.
There was significant scatter of the data.
                                                       CO
                                                       8
                                                           0.0 \
                                                                     Lake
                                                                     category  ;  Dyetropntc    "• Shallow coastal
                                                                            nnn pjjj, coastal   Kl" Foresten
                                                                            "' log Ponds       Sea Water
                                                                            xx* unique
                                                             0.0
                                                                         0.5
                                                                                      1.0
                                                                                                   1.5
                                                                       LOG CHLOROPHYLL (ug/L)
                                                       Figure 4-3. Median monthly Secchi versus Total
                                                       P. There was a general decrease in Secchi with
                                                       increasing Total P.  Data for Deep Coastal lakes
                                                       tended  to fall above the  line whereas Shallow
                                                       Coastal lakes fell well below the line.
                                                  13

-------
    15
                                2.0
                                       2.5
            0.5     1.0      15
            LOG TOTAL PHOSPHORUS
Figure 4-4. Median monthly Secchi versus Total
P  across  lake  categories.   Secchi generally
decreased with increasing Total  P.  Shallow
Coastal lakes tended to fall below the line.
                                                    4.0
                                                    3.0
                                                  5
                                                  o. 2.0
                                                     10
                                                    0.0
      0.0
                                                                    TDHL KirifttEl
                                       1.5
                 0.5         1.0
                  LOG SECCHI (m)
Figure 4-5.  Relationship between Secchi Total P
and Total N. Sechhi decreased in a similarfashion
with both nutrients.
Table  4-2.    Regression  statistics  for log-
transformed water quality parameters.   Values
are monthly means. * - intercept not significantly
different from  zero.  All slopes significant (p <
0.001).
Dep
Mar
LogTN
LogChl
LogSecchi
LogChl
LogChl
LogSecchi
Ind
Mar
LogTP
LogTP
LogTP
LogSecchi
LogTN
LogTN
N
63
68
113
114
51
45
slope
0.558
0.58
-0.55
-0.45
0.68
-0.71
int
1.77*
0.04*
1.12
0.76
-0.92
2.22
r2
0.68
0.45
0.63
0.42
0.2
0.56
(Figure 4-4).  It should be noted that all of
the high Secchi  depth readings (>  15 m)
come  from  Crescent  Lake  in  Olympic
National Park and  are definitely outliers in
the TP-Secchi  plot  in  Figures 4-3,  4-4.
Interestingly, while  they are at the extreme
end of the TN-Secchi plot in Figure 4-5, the
high Secchi  depth Crescent  Lake data fit
right on  the  line with  the rest of the data.
This is most likely  due to the fact that the
Total  P  concentrations are  actually  much
lower  than   reported,  i.e. detection  limits
were  reported.   In that event the Total
data would fall onto the TP - Secchi line.
4.4  Patterns   in  Coast  Range   Lake
Categories

In Chapter 3 a lake categorization scheme
was proposed for lakes in the Coast Range
Ecoregion.  We classified each of 71  lakes
into one of the seven categories and looked
at  how the  nutrient  parameters  varied
among  categories.  The seven  categories
along with  how many sample lakes we had
in that category are given in Table 4-1.

In analyzing patterns across lake categories
we  used  Lake  Crescent to represent the
Unique  category, since it represents  a truly
unique water body.

There  were clear  differences  in median
Total P values among lake categories, as
well as in  the range  of values  (Fig. 4-6).
Total P
                                            14

-------
^
§>

§
g
Q.

-------
Category 7  (Lake Crescent)  had very low
chlorophyl   concentrations  whereas
Dystrophic  lakes had  the highest.   It  is
interesting to note that Dystrophic lakes had
the highest chlorophyll  concentrations even
though these lakes have  the  lowest water
transparency due to humic materials.

As would be expected given these patterns
in   nutrient  levels,  Secchi  depths  were
highest in Lake Crescent (Fig. 4-9).   The
next highest Secchi depths were in the low
nutrient  Deep   Coastal   and   Forested
categories.  Secchi depths in the Dystrophic
and  Log Pond  classes were low, mostly
between 0.5 and 2.5 m.  This is likely due to
the  colored  water  associated  with  the
dystrophy/logging   history  of  these
categories.  In general the Shallow Coastal
lakes had slightly higher levels of  nutrients
than  the  Deep  Coastal  lakes   and  a
shallower Secchi depth. The latter may be
a function of the shallowness of these lakes.

Total N  to  Total P ratios generally  were
greater than 10 (by mass) for most lakes
categories   (Fig.   4-10).     Interestingly
Dystrophic   lakes  and  Lake   Crescent
(category  7) showed  some  evidence  of
nitrogen  limitation.     Even  if  Total  P
concentrations were reported at a detection
limit of 10 ug/L for Lake Crescent, a value of
5 ug/L Total P  would still put that lake on
the border of nitrogen limitation.

In order to test whether the nutrient-stressor
relationship  was  consistent  across
categories,   we  regressed   the  same
parameters  as  for the  entire Ecoregion by
lake category.  Generally, there too few data
to  draw  any conclusions within  any  lake
category.   For those categories that  had
sufficient data,   regression statistics  were
similar to those for the  Ecoregion as  a
whole.  However, additional data may show
that  lakes in different categories do show
differences in these statistic, as indicated by
relationships in  Figure 4-4.
60





0 *
«c
oc
a.
z
20
























J









Lake
Category 1 Dystrophic
2 Shallow Coastal
3 Deep Coastal
4 Forested
5 Log Ponds
6 sea Water
7 Unique




) I I

                 LAKE CATEGORY
 Figure 4-10. Total N to Total P ratios by lake
 category.  The horizontal line represents an N:P
 ratio of 10 by mass.
4.2  Temporal Variability  in  1999-2001
Lake Data

As part of the probability lake study in the
Coast Range Ecoregion, some of the lakes
were visited more than one time during the
1999-2000 sampling and during additional
visits in 2001.  We can use this information
to quantify temporal  variability  in lake
nutrient parameters  that will be  useful  in
calculating the power of classifying groups
and  in trend detection.  We restricted the
analysis to surface water chemistry samples
collected between May and October as that
is the data that we  are using to index lake
conditions.    To  quantify  the  temporal
variability,  we calculated  a  grand  mean,
pooled standard deviation and coefficient of
variation (CV)  using all the  lakes that had
multiple  visits.    The  pooled  standard
deviation  is  calculated  by  calculating  a
mean and variance  for each individual lake
based  on all the  revisit data, summing all
the  individual  lake  variances  together,
dividing  by the  appropriate  degrees   of
freedom and then taking the square  root to
get a standard deviation.  The grand mean
is just  the mean  of all the  individual lake
means and the CV is the pooled standard
deviation  divided   by the   grand  mean
                                           16

-------
expressed   as  a   percent.     TP  and
chlorophyll-a had the  most variability with
CV of 63% and 55%  (Table 4-3) and the
pooled standard deviation for TP was 9.6
|jg/L.  TN had the lowest CV (7%) whereas
Secchi depth had a CV of 23% based on a
pooled standard deviation of 1.2  m.  If the
concentrations observed in the repeat data
are around the concentration of interest, the
pooled   standard   deviation  is   a  good
indicator of the amount of variability that is
likely  to   be  found   in  taking  one
measurement as an index of site conditions.

Table 4-3.    Pooled  standard deviation  and
coefficient of variation for data collected from
sample lakes with repeat visits in the 1999-2001
probability survey.  Only  water chemistry data
collected  from the top depth and data collected
during May-October were used in calculations.
No - number of lakes, sd - standard deviation, cv
- coefficient of variation.
Variable No Grand Sd CV
Mean
Total P
(ug/L)
Total N
(ug/L)
Secchi
(m)
Chlorophyll-a
(pg/L)
Maximum
Profile DO
(mg/L)
Maximum
ProfileTemp
10

5

8

10

15


16

17.5

272

5.03

5.46

9.81


19.1

9.6

19.2

1.16

3.41

2.2


1.48

55%

7.1%

23%

63%

23%


7.7%

4.3 DISCUSSION

Value of Lake Categories

Data presented  here suggest that Level III
Ecoregion  is  not always  sufficient  as a
stratification variable in the development of
numeric  nutrient  criteria  for  lakes.  The
distributions of nutrient criteria parameters
(Total P, Total N, Seech  and chlorophyll) in
all  lake   categories  were  substantially
different  than the values derived for  either
the Nutrient Ecoregion or the Level III Coast
Range  Ecoregion (Table 4-1).   Although
future   investigation   may  permit   the
combining   of   certain  lake  categories,
different  lake  types  with respect to  basic
limnological character and  processing  of
nutrients should  be  taken into account in
any such effort.   For example, Total P and
chlorophyll  values were similar for Shallow
and   Deep  Coastal   lakes  but   water
transparency was much different (Figs. 4-6,
4-8, 4-9. This difference was mostly likely
due to the nonalgal turbidity in Shall Coastal
lakes  that  results from wind driven  mixing
and subsequent  resuspension of sediment.

The pooled standard deviation for nutrient
variables suggests  that within  any  given
lake category variability  may be relatively
small (Table 4-3).   Thus the sample sizes
required  to test whether  any given  lake
deviates from the observed distributions for
nutrient parameters may be relatively small.

The  need  for developing  Total  N criteria
may also be lake category dependent. Only
two  categories  (1   and  7)  indicated  the
possibility for nitrogen limitation (Fig. 4-10).

On the other hand,  the diversity of lakes
found in the Coast  Range Ecoregion may
not hold for other Ecoregions.  For example,
Vaga  and   Herlihy  (2004)  found  that  in
several  Ecoregions,  nutrient concentrations
in  lakes  were  quite   consistent.     For
example, there are a total of 455 lakes  > 4
                                           17

-------
ha in surface area in the North Cascades
Ecoregion.  In a sample of 189  lakes the
median Total P concentration was found  to
be 11.3 ug/L (25th percentile of 2.6 and 75th
percentile of 11.3  ug/L) (Vaga and Herlihy
2004). Thus  the hereogenity of lake types
should be investigated by Ecoregion prior to
determining their nature regarding  nutrient
processing.

Evaluation   Lake  Category   versus
Trophic Status

The  lake categories have been constructed
based on  a subjective impression of overall
limnological character.  The extent to which
the  trophic  conditions  in  the  lakes  are
correlated with those subjective  categories
can be evaluated by comparing the various
limnological measures of trophic conditions
collected from each of the lakes.  The EPA
manual identifies a  number  of "candidate
variables"  (Chapter  5  of  Manual)   for
evaluating  lake   trophic  status.     The
candidate variables  include:   phosphorus
and  nitrogen species,  chlorophyll, water
transparency  (Secchi   disk   depth),
hypolimnetic   oxygen   concentration   and
mixing type.  The lake categories identified
here   can  be  compared  across  these
candidate variables as a means  of testing
the  validity  of  such categories.    If the
categories have  any  value, they should
serve to predict, in some sense, the range
of  conditions  across  the   variables,
independently  of  degree  of   human
disturbance.  If the categories prove useful
in this sense, the results would suggest that
lake   category should  be  considered  in
setting nutrient criteria for monitoring lakes
for undesirable impacts.  As a means  of
comparison, the data available are listed for
each of the suggested lake categories.

Again, it is important to recognize that the
amount of data available is  insufficient  to
conduct any proper statistical  test of the
differences among the categories.  The
        1.5
                     1.0   1.5   2.0

                  LOG TOTAL P (ug/L)
                                     2.5
 Figure 4-10.  Relationship of median monthly
 Secchi to total P  (log-log) for  lakes that are
 clearly meso-oligotrophic and lakes that are
 eutrophic. The data tend to fall on the same line
 but segregate according to trophic group.


evaluation is attempted only in the sense of
using local "expert opinion" as a  means of
identifying  lakes  which might   serve  as
illustrating "reference conditions" and "water
body categories".
In summary, it may be seen that trophic
status of the lakes in this sample might be
predicted  to  some extent based  on "Lake
Category".   It is of course  obvious that the
categories   suggested  here  are  clearly
arbitrary in that they were created based on
the sample of less than 50 lakes.  However,
the descriptions  of  the "categories"  are
related  to   more   fundamental   lake
characteristics  such  as mean   depth  or
concentration of allochthonous  organic
matter  that  might   be  employed   for
establishing  a  more  objective  lake
classification.

The seven lake categories were found to be
generally  in  accordance with expectations
regarding trophic state.  By any  measure,
Dystrophic lakes (category 1)  are  eutrophic.
Nutrient  concentrations  are  very  high
(characteristic Total Phosphorus of 81  ug/L,
Total Nitrogen of 650 ug/L),  chlorophyll is
relatively  high   (characteristic   value   of
chlorophyll  a of 16.6  ug/L)  and  water
                                           18

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transparency   is  limited   (characteristic
Secchi depth of 0.9 meter) .  However, the
eutrophic  status  of  these  lakes  occurs
without, in most cases, direct evidence of
cultural eutrophication.   Freshwater Lake,
Clam Lake, Creep and Crawl Lake,  Long
Lake,  Failor  Lake   and  Island Lake are
nearly  pristine,  with  very  little   human
disturbance of their watershed, and only low
impact recreational use.  There are several
residences on  the shore of Cullaby Lake,
however, those residences  are served by a
sewer and treatment  plant  that  diverts
effluent away from the lake.   Only Sunset
Lake is subjected to the direct impact of
cultural eutrophication.   Many  residences,
served by septic tanks,  are  located along
the western shore of the  lake on a very
porous substrate  (a relict sand dune), and
much of the  eastern  shore of the lake is
bordered  by a  golf course  that is  fertilized
and irrigated.  It can be seen in the data that
Sunset Lake does not stand out among the
Category 1 lakes in spite of a notably higher
level of human disturbance in its watershed.
Shallow  Coastal  lakes  (category  2)  are
mesotrophic.      Nutrient  concentrations,
chlorophyll  a  concentrations,  water
transparency, and oxygen concentration all
indicate the same interpretation (Table 4-1).
Each of these lakes is a  popular recreation
lake, but impact is apparently relatively light.
There is very little motorboat traffic on Smith
Lake and Coffenbury Lake, whereas  Lake
Lytle  and  South  Tenmile  Lake are  more
heavily used.  Only South Tenmile Lake has
a  significant  number of residences in its
watershed. The watershed  of Tenmile Lake
is  also modified by recent  logging  and
ongoing  agricultural  activities.  Differences
among the lakes appear to  be slight. Since
none of these lakes could be argued to be
pristine,  their  "natural"  trophic  condition
remains undefined.   However, given  their
shallow depth,  their  mesotrophic status is
not surprising.

In  overall appearance,  Deep  Coastal  and
Forested (categories 3 and 4) are the most
nearly oligotrophic group of the lakes.  The
concentrations of phosphorus (Total P, 10 -
11.3  ug/L) and nitrogen (Total N, 220 - 225
ug/L)  suggest a mesotrophic status, and are
lower  than  other  lakes.     Chlorophyll
concentration  (characteristic values,  2.4 -
4.6   ug/L)  and  water  transparency
(characteristic Secchi disk depth,  3.9 - 4.5
meters) also suggest a mesotrophic status
for  these  lakes  (Table 3-1).  There are a
number of residences  located within the
watershed  of many of the lakes, although
the potential  impact on the lakes has not
been  evaluated.  The distinctly clinograde
oxygen  profile  that  develops  in each  of
these lakes would seem to suggest possible
impacts on the  lakes and  that the trophic
status of the  lakes may be more  eutrophic
than  indicated  by  other characteristics.
However,  similar lakes in  the  region (not
included   in  this  survey)  that  have  no
housing in their watershed and very little
human disturbance of any kind have also
been   observed  to  develop  clinograde
oxygen  profiles.   Given the very  porous
soils (relict sand dunes) bordering some  of
these  lakes,  it is  likely that  groundwater
moves relatively freely into the lakes and
may  be   in  part  responsible  for  the
clinograde oxygen profiles.  In this case, the
clinograde  oxygen   profiles  are  not
considered to indicate eutrophic conditions.

The Inland/Forested lakes (category 4) and
Log Ponds (category  5)  are  mesotrophic
(characteristic  Total   P,   39   ug/L,
characteristic Chi a , 7.6 ug/L; characteristic
Secchi depth, 1 m).  There is a tendency for
loss of oxygen with depth. There is  not a
consistent  pattern of stratification for this
group of lakes,  e.g.   Ollala Reservoir and
Town Lake are  polymictic and  Rink Creek
Reservoir  and  Triangle  Lake are  warm
monomictic.  Given  their  history, it  is not
surprising that these ponds are eutrophic,  or
in the case of Johnson Pond, hypertrophic.
The ponds are very shallow and overgrown
                                          19

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with macrophytes in places.  Nevertheless,
the ponds are popular fishing  spots. They
lack any  "official"  boat ramps  or  other
developments  but  nevertheless  attract
anglers.  There  are no residences in  the
drainage basin of any of these  ponds, and
no  other significant source of disturbance
other  than  the  disruption   from  boat
launching   where  no   suitable  ramp  is
available.

The Seawater Intrusions lakes  (category 6)
represent  a unique limnological condition.
As  such this category is useful primarily for
segregating out such water bodies from the
scheme depicted in Figure 3-1.

The Unique lakes represent a category that
defies classification. These lakes are those
that have  characteristics  that obviously
make them unique.  Lake  Crescent is an
example.    Not  only  is  its  limnological
character unique  (maximum depth 195 m,
Secchi 20 m), there are two endemic trout
species in the lake.
Human   Disturbance  versus   Lake
Category

Several of the lakes in  the overall sample
could be described as "pristine" in that there
is very little  evidence of significant human
disturbance  of the  lake  or its  watershed.
Lakes  that could be so  described include
Clam  Lake,  Creep  and  Crawl   Lake,
Freshwater Lake, and Island  Lake.   Other
lakes are apparently subject to only light
disturbance,  such as Long Lake, Coffenbury
Lake, Smith Lake (McGruder),  Sutton Lake,
or Town Lake.   The lakes which  have the
most potential for nutrient enrichment from
residences in  their watershed are Sunset
Lake and Triangle Lake. Other lakes with
residences in their watershed but probably
lesser  nutrient enrichment include Cullaby
Lake,  Lake   Lytle,  South  Tenmile  Lake,
Collard  Lake,  Laurel Lake. Lake  Pleasant
and Woahink Lake.  Ollala  Reservoir and
Rink Creek Reservoir have no residences in
their watershed  but are  likely affected by
frequent changes in surface elevation with
consequent erosion of their shoreline.  The
four   log   ponds,  Johnson,  McCleary,
Vernonia and Lake Creek, are not presently
influenced by human disturbance other than
fishing but exhibit the effects of their history.
Garrison Lake is the only  meromictic lake in
the sample.

Unfortunately, with the exception  of South
Tenmile  Lake,   no quantitative  data  are
available to indicate nutrient loading to any
of the lakes. (More extensive studies would
be needed to develop a quantitative nutrient
budget for the lakes, including the loading
that is attributable to  human disturbance.)
However, the relationship between nutrient
concentration observed in the lakes can be
compared with the general description in the
paragraph above.  It is immediately evident
that  lake  "category"  is at least  equal  to
human disturbance in predicting  nutrient
concentration in  a particular lake.    For
example, some  of the  most "pristine" lakes,
Clam  Lake  and Creep  and Crawl  Lake,
have the highest phosphorus concentration.
On the other hand, Triangle  Lake, which
has at least 50 residences immediately on
the lake, has among the lowest phosphorus
concentration,  and Woahink  Lake,  with a
significant  number of residences  in its
watershed,   had  the   lowest  phosphorus
concentration.

The most eutrophic lakes, "Category 1", are
the  lakes  with  significant  dystrophic
influence,  including some lakes subject to
human disturbance but several that can be
described  as pristine.  Less surprising is
eutrophic status of the "Category  5" lakes:
relict   log  ponds.     Among  the  most
transparent lakes in this  sample,  Woahink
Lake and Triangle  Lake,  are lakes that are
clearly subject to some nutrient enrichment
from human disturbance.  In short, it seems
                                          20

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apparent  that trophic  status  among  the
lakes in this sample is largely determined by
factors  not   related   solely  to  human
disturbance.     There   is  considerable
variation among the lakes, all from the same
Level III Ecoregion.

It   must  be  acknowledged   that   the
"categories"  of lakes  described here  are
arbitrary,  and developed   based  on  the
overall appearance of each  lake  and its
watershed.   It is probable that  such a
subjective procedure will be influenced by
circular reasoning.  For example, Sunset
Lake  was placed  among  "Category  1",
humic  influenced   lakes,   where  its
concentration   of   phosphorus   and
chlorophyll and   water  transparency  are
characteristic values among the lakes in the
category.  The placement was based on the
concentration of organic matter in the lake.
Had  Sunset  Lake   been   placed   with
"Category 2", shallow coastal lakes, it would
be the most eutrophic lake in the category.
Arguably,  the  organic  matter  could  be
attributed  to  autochthonous   sources
resulting from  the nutrient enrichment from
the surrounding   residences and  the golf
course. Nevertheless,  it should be apparent
that for this  sample of lakes, location in a
particular  Level   III  Ecoregion  is  not a
sufficient  predictor of  expected  trophic
status  in   the   absence   of   human
disturbance.    Setting  protective  nutrient
criteria standards  will require recognition of
the important natural influences  on  lake
trophic status independent of the effects of
human disturbance.

Lake Category versus Level IV Ecoregion

All of the lakes in  this study are in the Level
III  Coast Range Ecoregion.  Recently Level
IV  Ecoregions have  been  developed that
refine Level III Ecoregions (Ref).  There are
nine Level  IV Ecoregions  in  the Coast
Range Ecoregion  (Fig.  4-11).
There appears to be some correspondence
between   lake   category  and   Level   IV
Ecoregion (Table 4-5).  However, there are
too few lakes that  have  been assigned a
category  to ascertain  any general  pattern.
However,  it  is  clear  that  even Level  IV
Ecoregions contain more  than  one  lake
type.  For example, the Coastal Lowlands
contain     representatives  of  all   lake
categories (Table 4-4, Fig. 4-11).

Nevertheless  the Level IV Ecoregions do
provide a geographic structure with which to
segregate   lake  types  for   further
investigation.   For example, Ecoregion 1a
(Coastal Lowlands) has the greatest density
and number of uncategorized lakes (Table
4-4).  It  apparently also has  the  highest
diversity  in lake type.  This suggests that
this Level IV  Ecoregion would provide the
greatest  benefit from  further effort in  lake
categorization.
                                          21

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    Lake Category

    ^ 1 Dystrophic

    [•] 2 Shallow Coastal

    Q 3 Deep Coastal

    Q 4 Forested

    Q 5 Log Ponds

    0 6 Sea Water

    ^ 7 Unique

     ^ No Category


    Level IVEcoregion
         Coastal Lowlands
         Coastal U plands
         Low Olympics
         Mid-Coastal Sediment
         Outwash
         Redwood Zone
         Southern Oregon Coas
         Volcanics
         Willapa Hills
         Level III Ecoregions
Figure 4-11. Locations of lakes by category in the Coast Range Ecoregion.  Level IV Ecoregions are also
shown.  Most lakes have yet to be categorized. The inset shows detail of three different lake categories (and
uncategorized lakes)  in the Coastal Lowlands Ecoregion.
                                                 22

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Table 4-4. Total Number of lakes in each Level
IV Ecoregion and number of lakes in each lake
category by Level IV Ecoregion.  The areas (sq
km) of Level  IV Ecoregions and density of lakes
are also given.    Most lakes in  this Level  III
Ecoregion have yet to be assigned a category. N
-   number  of  lakes,  Dn  -  lake density
(N/sqkmx1000).
Level IV
Ecoregion
Coastal Lowlands
Coastal Uplands
Low Olympics
Volcanics
Outwash
Willapa Hills
Mid-Coastal Sed
So Oregon Coast
Redwood Zone
Area
2531
6739
4361
9265
917
5258
9675
1793
81
N
96
27
13
17
4
12
12
1
0
Dn
37
4.0
2.9
1.8
4.4
2.3
1.2
0.6
-
1
8
_
_
_
1
1
_
_
-
2
11
1
_
_
_
_
_
_
-
3
10
_
_
_
_
_
_
_
-
4
1
4
4
_
1
_
3
_
-
5
1
_
_
_
_
2
1
_
-
6
1
_
_
_
_
1
_
_
-
7
1
1
1
1
_
_
_
_
-
                                             23

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    5. NUMERIC NUTRIENT CRITERIA DEVELOPMENT AND BENEFICIAL USES
5.1 Introduction

EPA guidance recommends using Total P,
Total  N,  chlorophyll  and  Secchi  to  set
numeric nutrient criteria (EPA 2000).  In the
preceding  chapters  lakes  in  the   Coast
Range   Ecoregion  were   inventoried
according to location and  size, classified
according into  seven  types based upon
basic  limnological   principles  and  then
characterized  with   respect  to  nutrients,
chlorophyll and Secchi transparency.

In this chapter we  illustrate two potential
ways  in  which the classification scheme,
coupled with water quality data, could  be
linked  to  designated  uses  to develop
numeric criteria.   The following discussion
is meant to be illustrative only, i.e.  not an
exhaustive exploration of the various ways
in which lake categories,  numeric nutrient
criteria and  beneficial uses  can  be  linked.
The illustration shows that numeric nutrient
criteria cannot be developed on the basis of
empirical  models  alone.   Development of
such criteria require judgements  as  to how
protective to make the standards.

5.2 Beneficial Uses

To  illustrate  the development of numeric
criteria we will  use the lake classification
scheme presented in Chapter 3,  beneficial
uses  defined in  Oregon's water  quality
standards (OAR Chapter 340) and available
water quality  data.   Table  5-1  lists  the
beneficial   uses for  estuaries,  adjacent
marine and all streams in the North  Coast-
Lower Columbia Basin. By implication lakes
and reservoirs are  included  in the streams
category.  There are four regulatory basins
in Oregon that overlap the Coast  Range
Ecoregion (Fig. 5-1).   All of those  basins
have the same beneficial uses for lakes and
reservoirs.  Thus  all  lakes  in  the   Coast
Range  Ecoregion   have  essentially   all
beneficial uses.
5.3 Reference Condition Approach

One approach suggested in the Technical
Guidance Manual is  that  of  a reference
condition  approach (EPA 2000).   In  this
method a standard for Total P is developed
relative to  a reference condition.   The
reference  condition   is  defined  as   a
percentile of Total P concentrations in a set
of reference lakes (least impacted).

The  25th, median and 75th percentiles for
summer index Total P, Total N, chlorophyll
and Secchi were calculated (as described in
Chapter 4) for all the lakes  in  the Coast
Range  ecoregion  and  by lake category
(Table 4-1, Figs. 4-6,9).   It is evident that
medians and percentile values for most
parameters  for  each  lake category  are
different from those of the lake  population
as  a  whole.  Therefore  using all lakes to
define  reference  values  would  not  be
justified.  The same  conclusion holds for
using values  derived for Aggregate Nutrient
Ecoregion II (Western Forested Mountains)
(Table  4-1).    For  example,  the   25th
percentile for Total P (8.8  ug/L) would be
appropriate   for  only  two  of  the  six
categories  (leaving out the unique lakes).
Therefore for purposes of setting reference
conditions  in this Ecoregion,  the  use of
percentiles  (or  any  other  statistic)
necessitates  consideration of  differences
among lake categories.
                                          24

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                                                 Figure 1: Oregon Basin Index Map
Basin Name
D£SCHUTES
GCCSE S SUMMER LKS
GRAfCE a-CNDE
HOOD
JOHN DAY
KIAWATH
MALH&JS jj^E
MALHEUfl RIVER
MiG COAST
NORTH CST-iWRCCl
OWVHEE
pQi&CER
fiOGUE
SANDY
SOUTH COAST
I^MATILIA
UWPOUA
WAI LA WALLA
WLLAM6H£
Basins
25
42
3!
24
26
43
41
33
t2
H-21
24
32
55
23
t4
27
!3
£•§
£2
OAR#
340-4 -0130
340-4 C!40
340 '4 01'j-l
MM 0160
34Q-4 61 70
340-4 -0130
340-4 CWJ
340-4 020!
340-4 0220
540 >4 0230
340-4 -C2-3Q
340-4 -OSbC
340-4 -C2?l
340^4 0286
340-4 -S3GC
S40-4 -C3^0
340-4 -C.'SO
340-4 -C3-50
340-4 -^j4£l
   Figure 5-1. Map showing basins used to designate beneficial uses in the State of Oregon.
   Basins corresponding to the Coast Range Ecoregion all have the same beneficial uses (OAR
   340-41-0230).
Assuming that the lakes included in this
analysis are relatively undisturbed (and
therefore can be called reference lakes),
the   75th  percentile   of  the  four
parameters could be used as a starting
point  to  set  criteria  for  a given lake
category.  The 25th percentile appears to
be too restrictive for many lakes in this
Ecoregion  where  the reference  lakes
are largely unimpacted (Table 4-1).

The   simplest   way   to    assign
corresponding  values for the  various
beneficial   uses  for  each  parameter
would  be  to  define  them ipso facto.
Thus all the beneficial uses in Table 5-1
would  be met as  defined by the 75th
percentile values in Table 4-1.
Compliance  with  the  standard  could
then be  tested  using  simple  statistical
tests for each parameter, e.g. t-test. For
example,  the   difference   between
median  Total   P  values   during  the
growing season in a given lake can be
compared with the 75th percentile of the
reference population of lakes.
           i = f(P (ref)HP
                       (lake)
where P(,ake) is the median summer index
Total  P concentration in the
                                        25

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Table 5-1.  Beneficial uses in the North Coast
basin of Oregon.  Essentially all  beneficial uses
apply to all fresh water in this basin, as well as in
all of the Coast Range Ecoregion (OAR 340-41-
0230).
Beneficial Uses
Public Domestic Water1
Private Domestic Water1
Industrial Water Supply
Irrigation
Livestock Watering
Fish & Aquatic Life2
Wildlife & Hunting
Fishing
Boating
Water Contact
Aesthetic Quality
Hydro Power
Commercial Navigation
Estuaries
&
Adjacent
Marine
Waters


X


X
X
X
X
X
X

X
All Other
Steams &
Tributaries
Thereto
X
X
X
X
X
X
X
X
X
X
X


1 With Adequate pretreatment (filtration & disinfection) and
natural quality to meet drinking water standards.
2 See also Figures 230A and 230B for fish use designations
for this basin.
lake  being  tested,  P(ref)  is  the  75th
percentile of the summer index Total  P
concentrations  in  the  reference lakes
and (i) the lake category. The value of
A,  can take  on  values less  than or
equal to  zero.  The criterion,  i.e.  the
value of P (ref)),  could then be set for the
most sensitive beneficial use.

To  illustrate this we define  a  Total  P
standard for one lake category and  one
beneficial use:  Resident Fish & Aquatic
Life  Use  in Deep Coastal  Lakes.   In
other words, what is the largest  value of
A, that still protects  Resident  Fish  &
Aquatic Life Use in Deep Costal Lakes
(Table 5-1).   Perhaps the  most direct
effect of increased nutrient loading on
resident  aquatic  life  in  a  lake  is an
increase  in   the   areal   hypolimnetic
oxygen  demand (AHOD).  The increase
in  (AHOD) results  from the increase in
algal biomass and  subsequent decay of
organic  matter in  the  hypolimnion  and
sediment  surface.  In lakes that do not
naturally experience periods of anoxia in
the sediments, development of anoxia
will  profoundly change  the  species
composition of the  benthos.

In  this example if  A must be > 0 zero
then the median seasonal Total P (or
Total  N, Secchi and chlorophyll) in any
given lake in  this category could not be
significantly  greater  than  the   75th
percentile of the  reference  population
medians.    However,   lakes  naturally
eutrophy so  a less  restrictive  criterion
may be more appropriate.   Thus an
increase of 25%  in median  seasonal
Total  P  over  reference levels might be
an appropriate criterion for these lakes,
since a  change of  this  magnitude would
begin to  affect the  areal  hypolimnetic
oxygen  deficit.

The size of Type I  and  Type II error can
be defined by the  sample size used in
the test  to determine if diff is significantly
different from  the  75th  percentile.  (The
power of the statistical test can be made
arbitrarily   stringent.     However  the
accuracy of the test will be influenced by
how well the  lake categories have been
defined.)  This would include specifying
the  number   of  samples,  frequency,
season, etc.  For example, the test must
be based  on  10 Total  P samples taken
during the growing season not less than
two weeks apart.

It  is apparent  that the  relevance  and
magnitude of A, is  dependent upon lake
category.   Thus  for  dystrophic lakes
which  naturally experience  prolonged
periods   of   sediment  anoxia,   the
measure  of  AHOD   would  be
                                       26

-------
meaningless  as a way to link nutrient
concentrations to aquatic life use.  For
polymicitic lakes AHOD would also be of
little   use,   since  physical   mixing
reoxygenates  the  sediments.     In
contrast,   oligotrophic   lakes  that
thermally   stratify  are   sensitive  to
increases  in  nutrient  loading  so  the
value of A, should be relatively small.

Lakes in this ecoregion have a Total P
to Total N ratio of about 20. Therefore,
unless  there  is  a   potential  for
downstream effects, a criterion for Total
N may be unnecessary.
5.4 Stressor-Response Approach

An alternative manner in which to set
numeric  Total  P  criteria  is  using  a
stimulus-response  model such as linear
regression  equations of chlorophyll  a
versus Total P (Fig.  4-2). Table  4-2
provides  regression coefficients for four
different  lake types in the ecoregion. In
the example of Resident Aquatic Life in
Deep  Coastal  Lakes,  the  Total   P
standard could be set so as to prevent a
25%  increase  in   median  chlorophyll
concentrations  (from  4.3 to 5.4 ug/L)
(Fig.  4-2).  The lower  95th percentile
confidence envelope corresponding to a
median chlorophyll concentration of 5.4
ug/L is a Total P  concentrations of  15
ug/L.

This  equation  could  also  be used  to
define Total P standards with respect to
the aesthetic beneficial use, i.e.  water
transparency.  Similar equations can  be
developed for Secchi and chlorophyll or
Secchi and Total P to further refine the
Total  P standard.   This approach would
not be useful in dystrophic lakes where
water  transparency   is   largely   not
affected  by chlorophyll  concentrations.
It would be of greater use in lakes where
water  clarity  is  largely  a  function of
chlorophyll concentrations.

The  beneficial  uses  of  downstream
waters  must  be  protected.   If  it is
assumed  that  the  standards   are
protective of the  in situ beneficial  uses
the downstream waters in all probability
will also be protected, i.e. the given lake
is functioning normally in the landscape.

For Unique Lakes the use of epilimnetic
Total   P  concentration   will   not  be
sufficient  to protect beneficial  uses in
those lakes because these lakes are so
large  that significant changes in Total P
loading could   go undetected.  Thus a
nutrient criterion based upon epilimnetic
concentrations  would   have   little
meaning for lakes  such as these.  A
near  shore  criterion that  reflects  more
immediate impacts of nutrient loading
(including periphyton chlorophyll) would
be  more  appropriate for  these  unique
lakes.

5.5   Limitations   of    Empirical
Approaches

These empirical procedures for defining
numeric   nutrient   criteria    are
straightforward  in   that   they  define
whether  a lake is significantly different
from   the   reference    population.
However, they do not necessarily reveal
whether  a beneficial  use  is not  being
supported.  The  explicit  definition of a
nutrient   standard   with    respect  to
beneficial uses cannot be  derived from
descriptions  of  reference  conditions
alone.  This is because  lakes degrade
with respect to eutrophication along a
gradient.   Therefore where to set the
numeric nutrient criterion (the magnitude
of  diff  in  this  example)  involves a
judgement as to how conservative  to be
with  respect   to  the  eutrophication
gradient for each beneficial use.
                                       27

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5.6 CONCLUSIONS

The  results of this study have several
implications  for  the  development  of
numeric  nutrient  criteria in  Region  10
lakes.  First,  a more thorough inventory
of  the  water   bodies  should   be
undertaken so the this resource can  be
better defined.  Second,  it appears that
at least in some  Level III ecoregions a
lake  classification scheme needs to  be
developed   according  to   how   they
process  nutrients.   Lakes included  in
this  study  exhibit  characteristics that
suggest  that ecoregion alone is  not a
sufficient predictor of lake trophic  status
for the  purpose  of  setting  nutrient
criteria.  Additional factors that influence
natural  lake  trophic  status include  the
concentration  of  dissolved  organic
matter, lake and watershed morphology,
and location  of the lake with  respect to
the type of  geological terrain.  Therefore
without  such   categorization,  the
development of ecologically meaningful
nutrient criteria is problematic.
relevant beneficial uses for lakes in that
category.     Such  definitions  require
judgements  to   be  made  that  are
nonscientific  in   nature,   i.e.   how
protective  a  criterion should be  for a
given beneficial use.
Acknowledgments.     We  thank  Dave
Flemer  and  George Gibson  for their
comments  on  an earlier draft  of  this
report.
Third, long-term water quality sampling
should be carried out across the Region
with  the   goal   of   refining   lake
classification schemes.   A  potentially
useful method for collecting such data is
to combine nutrient TMDL's for many
different  systems by water body type,
define reference systems for those listed
systems, and then  collect water quality
data on  the reference systems.  Such
data could  be  used to  define nutrient
assimilative  capacity   for  the  listed
systems  as well as  be  used to  begin to
develop  numeric nutrient criteria for all
systems  of that  type.
Finally, work needs to be undertaken to
systematically  define numeric criteria for
each  lake  category  corresponding to
                                       28

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                              5. REFERENCES


Delorme Mapping 1998. Washington Atlas and Gazetteer. 3nd Edition.

Delorme Mapping 2001. Oregon Atlas and Gazetteer. 3nd Edition.

Emmons,  E.E., M.J.Jennings, and  C.  Edwards.  1999.  An  alternative classification
method for northern Wisconsin lakes. Can. J. Fish. Aquat. Sci. 56:661-669.

EPA 2000. Nutrient Criteria Technical Guidance Manual: Lakes and Reservoirs.  EPA-
822-BOO-001

Hutchinson, G.E. and H. Loeffler. 1956. The thermal classification of lakes, Proc. Nat.
Acad. Sci. 42:84-86.

Larsen, D.P.,  D. L Stevens  Jr.,  A.R. Selle,  S.G. Paulsen.  1991.  Environmental
monitoring and assessment program,  EMAP-surface waters:  a  Northeast lakes pilot.
Lake and Reservoir Management 7:1-11.

Larsen, D.P., K.W. Thornton, N.S. Urquhart, S.G. Paulsen. 1994. The role of sample
surveys for monitoring the condition of the Nation's lakes. Environmental Monitoring and
Assessment 32:101-134.

Lillie, R.A. and J.W. Mason. 1983. Limnological characteristics of Wsconsin lakes. Ws.
Dep. Nat.  Resour. Tech. Bull. No. 138.

Moss, B.,  P.  Johnes, and G. Phillips. 1994.  August Thienemann and Loch Lomond-an
approach to the design of a system for monitoring the state of north-temperate standing
waters. Hydrobiologia 290:1-12.

Omernik,  J.M.  1987.  Ecoregions of the conterminous Unites  States.  Map (scale
1:7,500,000).  Annals Assoc. Am. Geographers 77:118-125.

Schupp, D.H. 1992.  An ecological classification of Minnesota lakes with associated fish
communities.  Minn.  Dep. Nat. Resour. Invest. Rep. No. 417.

Thierfelder, T.K.  2000.  Orthogonal variance structures in lake water  quality data and
their use  for  geo-chemical classification of dimictic,  glacial/boreal  lakes.    Aquatic
Geochemistry 6:47-64.

Toivonen,  H and  P. Huttunen 1995. Aquatic macrophytes and ecological gradients in 57
small lakes in southern Finland. Aquatic Botany 51:197-221.

USEPA. 2000.   Nutrient Criteria Technical Guidance Manual Lakes  and Reservoirs,
EPA-822-BOO-001, U.S. Environmental Protection Agency: Washington, DC.
                                      29

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Vaga,  R.  M.  and  A.  T.  Herlihy.   2004.   A  GIS  inventory of Pacific  Northwest
lakes/reservoirs and analysis of historical nutrient and water quality data. EPA 910-R-04-
009.

Williams, C.E., D.P.Morris, M.L.Pace, O.G.Olson. 1999.  Dissolved organic carbon and
nutrients as regulators of lake ecosystems:  Resurrection of a more integrated paradigm.
Limnology and Oceanography 44: 795-803.
                                      30

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APPENDIX
   31

-------
Table 1.  List of the 349 lakes identified in the Coast Range Ecoregion.  Lake area and Level IV
Ecoregion are also provided.
LAKENAME
Aaron Mercer Reservoir
Aberdeen Reservoir
Ackerley Lake
Alder Lake
Astoria Reservoir
Barney Reservoir
Beale Lake
Beaver Lake
Bebe Pond
Big Creek Reservoir No. 2
Big Jones Lake
Black Lake
Blackwood Lake
Bluebill Lake
Bogachiel Lake
Boulder Lake
Bradley Lake
Breaker Lake (1)
Breaker Lake (2)
Briscoe Lake
Bunch Lake
Butterfield Lake
Camp 7 Pond
Carlisle Lake (1)
Carlisle Lake (2)
Carlisle Lake (2)
Carlisle Lakes (3)
Carter Lake
Case Pond
Cemetery Lake
Clam Lake
Clear Lake
Clear Lake
Clear Lake
Cleawox Lake
Coffenbury Lake
Cohassett Lake
Collard Lake
Crabapple Lake
Cranberry Lake
Crescent Lake
Croft Lake
Daley Lake
Damon Lake
Deer Lake
Deer Lake 1
Deer Lake 2
HECTARES
(ha)
18.8
5.4
3.2
0.6
12.2
81.3
20.7
14.7
1.4
25.6
5.8
11.5
6.3
5.9
0.5
3.7
9.6
2.9
1.4
4.8
4.7
5.1
1.2
1.4
2.0
0.4
0.8
13.4
0.9
3.2
3.4
4.1
60.5
5.8
40.0
21.8
0.7
14.7
9.4
7.3
7.5
28.7
5.4
4.7
2.5
3.4
0.4
Ecoregion
No
1d
1e
1a
1f
1f
1d
1a
1c
1f
1b
1b
1a
1c
1a
1c
1c
1a
1a
1a
1a
1d
1a
1f
1a
1a
1a
1a
1a
1b
1a
1a
1a
1a
1a
1a
1a
1a
1a
1a
1a
1b
1a
1a
1a
1a
1c
1c
ECOREGION
NAME
Volcanics
Outwash
Coastal Lowlands
Willapa Hills
Willapa Hills
Volcanics
Coastal Lowlands
Low Olympics
Willapa Hills
Coastal Uplands
Coastal Uplands
Coastal Lowlands
Low Olympics
Coastal Lowlands
Low Olympics
Low Olympics
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Volcanics
Coastal Lowlands
Willapa Hills
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Uplands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Uplands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Low Olympics
Low Olympics
                                              32

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LAKENAME
Devils Lake
Devils Lake
Dickey Lake
Dragon Lake
Dry Bed Lakes 2
Dry Beds 1
Duck Lake
Eagle Lakes 1
Eagle Lakes 2
Eagle Lakes 3
Edna, Lake
Eel Lake
Elbow Lake
Elk Lake
Elk Lake
Elk Lake
Elk Lake - Upper
Elochoman Lake
Esmond Lake
Fahys Lake
Failor Lake
Fishhawk Lake
Floras Lake
Fourth Creek Reservoir
Freshwater Lake
Fulton Lake
Gile Lake
Happy Lake
Helmicks Pond
Hidden Lake
Hobuck Lake
Hoquiam Water Works
Reservoir
Horsfall Lake
Huttula Lake
Intermittent Lake
Intermittent Lake
Intermittent Lakes (1)
Intermittent Lakes (2)
Intermittent Lakes (3)
I rely Lake
Island Lake
Jefferson Lake
Jefferson Lake - Upper
Jordan Lake
Jupiter Lakes 1
Jupiter Lakes 2
Jupiter Lakes 3
Jupiter Lakes 4
Klickitat Lake
Klone Lakes (1)
HECTARES
(ha)
233.5
4.5
208.3
2.4
1.8
2.8
100.6
0.1
0.3
0.5
14.5
151.3
6.5
20.6
3.7
4.2
1.5
2.0
6.5
9.9
24.5
29.6
113.7
3.4
3.1
0.1
7.5
1.0
1.0
2.1
3.3
0.5
132.1
4.8
4.7
2.4
0.4
2.2
0.4
10.8
21.5
4.9
1.9
1.2
0.6
0.6
2.9
1.3
14.9
3.1
Ecoregion
No
1a
1d
1b
1c
1d
1d
1a
1c
1c
1c
1a
1a
1a
1b
1d
1d
1d
1d
1Q
1a
1e
1f
1a
1a
1a
1d
1a
1c
1f
1c
1b
1e
1a
1f
1c
1f
1a
1a
1a
1b
1a
1d
1d
1a
1d
1d
1d
1d
1Q
1d
ECOREGION
NAME
Coastal Lowlands
Volcanics
Coastal Uplands
Low Olympics
Volcanics
Volcanics
Coastal Lowlands
Low Olympics
Low Olympics
Low Olympics
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Uplands
Volcanics
Volcanics
Volcanics
Volcanics
Mid-Coastal Sediment
Coastal Lowlands
Outwash
Willapa Hills
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Volcanics
Coastal Lowlands
Low Olympics
Willapa Hills
Low Olympics
Coastal Uplands
Outwash
Coastal Lowlands
Willapa Hills
Low Olympics
Willapa Hills
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Uplands
Coastal Lowlands
Volcanics
Volcanics
Coastal Lowlands
Volcanics
Volcanics
Volcanics
Volcanics
Mid-Coastal Sediment
Volcanics
33

-------
LAKENAME
Klone Lakes (2)
Klone Lakes (3)
Kurtz Lake
Lake Aberdeen
Lake Armstrong
Lake Connie
Lake Dilly
Lake Haven
Lake Mills
Lake Pleasant
Lake Success
Lake Sundown
Lake Sutherland
Lang Lake
Laurel Lake
Lena Lake - Lower
Lily Lake
Lily Lake
Litschke Lake
Lizard Lake
Long Lake
Loomis Lake
Loon Lake
Lords Lake
Lost Lake
Lost Lake
Lost Lake
Lower Empire Lake
Lyons Reservoir
Lytle, Lake
Makenzie Head Lagoon
Manmade Pond
Manmade Pond
Manmade Pond
Manmade Pond
Manmade Pond
Manmade Pond
Manmade Pond
Marie, Lake
McGravey Lake
McGwire Reservoir
Middle Empire Lake
Middle Lake
Mildre Lakes 2
Mildred Lakes 1
Mildred Lakes 3
Miles Lake
Mink Lake
Moose Lake
Mountain Spring Reservoir
HECTARES
(ha)
1.8
0.3
0.5
21.1
2.5
2.1
3.9
6.1
0.1
199.1
0.3
1.6
142.0
1.5
16.1
20.6
7.2
0.6
6.0
0.8
4.7
60.6
96.9
24.1
7.8
3.4
4.5
9.4
1.8
18.8
2.7
20.6
7.3
32.8
9.2
6.3
3.1
10.2
6.1
0.5
51.4
11.0
4.6
4.6
17.1
3.4
5.9
4.1
1.6
0.7
Ecoregion
No
1d
1d
1c
1a
1d
1c
1c
1d
1c
1b
1c
1c
1c
1a
1a
1d
1a
1c
1a
1c
1a
1a
1Q
1d
1a
1a
1d
1a
1a
1b
1a
1a
1a
1a
1a
1a
1a
1f
1a
1c
1d
1a
1f
1c
1c
1c
1a
1c
1f
1b
ECOREGION
NAME
Volcanics
Volcanics
Low Olympics
Coastal Lowlands
Volcanics
Low Olympics
Low Olympics
Volcanics
Low Olympics
Coastal Uplands
Low Olympics
Low Olympics
Low Olympics
Coastal Lowlands
Coastal Lowlands
Volcanics
Coastal Lowlands
Low Olympics
Coastal Lowlands
Low Olympics
Coastal Lowlands
Coastal Lowlands
Mid-Coastal Sediment
Volcanics
Coastal Lowlands
Coastal Lowlands
Volcanics
Coastal Lowlands
Coastal Lowlands
Coastal Uplands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Willapa Hills
Coastal Lowlands
Low Olympics
Volcanics
Coastal Lowlands
Willapa Hills
Low Olympics
Low Olympics
Low Olympics
Coastal Lowlands
Low Olympics
Willapa Hills
Coastal Uplands
34

-------
LAKENAME
Mountain Springs Ranch
Reservoir
Munsel Lake
Myrtle Point Log Pond
New Lake
North Fork Reservoir
North Tenmile Lake
Oakhurst Ponds (1)
Oakhurst Ponds (2)
Oakhurst Ponds (3)
Olalla Reservoir
Old Mill Pond
Oneal Lake
Pauls Lake
Pine Lake
Pope Lake
Powers Pond
Quinault Lake
Radar Ponds No. 1
Raymond City Reservoir
Reflection Lake
Reservoir
Reservoir
Reservoir
Reservoir
Reservoir
Ring Lake
Rink Creek Reservoir
Riverside Lake
Roaring Creek Slough
Roaring Ponds No. 2
Round Lake
Ryderwood Pond
Sandpoint Lake
Sarviniski Lakes (1)
Sarviniski Lakes (2)
Sarviniski Lakes (3)
Satsop Lake No. 1
Satsop Lake No. 2
Satsop Lake No. 3
Satsop Lake No. 4
Satsop Lake No. 5
Saunders Lake
Seafield Lake
Shag Lake
Shye Lake
Skating Lake
Skookum Lake
Slusher Lake
Smith Lake
Smith Lake
HECTARES
(ha)
2.0
37.1
11.2
44.3
2.5
342.2
0.1
0.1
0.0
40.3
1.0
3.9
6.8
3.1
2.9
7.4

1.3
0.5
0.5
0.4
0.7
0.6
3.1
4.3
0.9
4.5
1.8
2.8
1.1
1.1
1.8
36.2
1.7
1.0
0.8
1.1
0.9
0.1
0.6
0.7
18.1
7.1
1.8
3.3
10.7
15.9
8.1
18.1
9.2
Ecoregion
No
1d
1a
1a
1a
1d
1a
1f
1f
1f
1b
1a
1a
1a
1d
1b
1h
1b
1b
1b
1c
1a
1a
1a
1b
1b
1c
1Q
1a
1b
1b
1c
1f
1a
1f
1f
1f
1d
1d
1d
1d
1d
1a
1b
1a
1a
1a
1d
1a
1a
1b
ECOREGION
NAME
Volcanics
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Volcanics
Coastal Lowlands
Willapa Hills
Willapa Hills
Willapa Hills
Coastal Uplands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Volcanics
Coastal Uplands
Southern Oregon Coas
Coastal Uplands
Coastal Uplands
Coastal Uplands
Low Olympics
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Uplands
Coastal Uplands
Low Olympics
Mid-Coastal Sediment
Coastal Lowlands
Coastal Uplands
Coastal Uplands
Low Olympics
Willapa Hills
Coastal Lowlands
Willapa Hills
Willapa Hills
Willapa Hills
Volcanics
Volcanics
Volcanics
Volcanics
Volcanics
Coastal Lowlands
Coastal Uplands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Volcanics
Coastal Lowlands
Coastal Lowlands
Coastal Uplands
35

-------
LAKENAME
Snag Lake
Soapstone Lake
Solduck Lake
South Bend City Reservoir
Spider Lake
Spring Lake
Stanley Lake
Stump Lake
Summit Lake
Sunset Lake
Sutton Lake
Sylvia Lake
Tah ken itch Lake
Tape Lake
Tarheel Reservoir
Taylor Lake (Carnahan Lake)
Teal Lake
Tenmile Lake
Three Horse Lake
Three Lakes 2
Three lakes 1
Three lakes 3
Threemile Lake
Thunder Lake
Tinker Lake
Triangle Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
HECTARES
(ha)
14.2
3.4
11.4
0.5
7.3
3.6
3.9
11.0
206.7
44.5
40.4
11.5
621.8
3.5
8.1
3.5
2.9
479.9
1.6
0.1
0.4
0.1
28.8
4.4
4.2
110.5
0.1
1.5
1.9
1.1
0.7
1.0
1.0
2.2
0.9
0.6
1.4
1.1
3.9
0.2
0.5
0.4
1.0
0.4
1.0
0.1
0.2
0.3
0.4
1.4
0.8
Ecoregion
No
1a
1b
1c
1a
1d
1b
1a
1f
1d
1a
1a
1f
1a
1a
1a
1a
1a
1a
1c
1c
1c
1c
1a
1b
1a
1Q
1a
1a
1a
1a
1a
1a
1a
1a
1a
1a
1a
1a
1a
1a
1a
1a
1a
1b
1b
1b
1c
1c
1c
1c
1c
ECOREGION
NAME
Coastal Lowlands
Coastal Uplands
Low Olympics
Coastal Lowlands
Volcanics
Coastal Uplands
Coastal Lowlands
Willapa Hills
Volcanics
Coastal Lowlands
Coastal Lowlands
Willapa Hills
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Low Olympics
Low Olympics
Low Olympics
Low Olympics
Coastal Lowlands
Coastal Uplands
Coastal Lowlands
Mid-Coastal Sediment
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Uplands
Coastal Uplands
Coastal Uplands
Low Olympics
Low Olympics
Low Olympics
Low Olympics
Low Olympics
36

-------
LAKENAME
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
HECTARES
(ha)
1.8
3.8
1.2
2.8
11.0
0.6
0.5
0.4
0.2
0.4
0.4
1.2
0.3
0.1
0.7
2.6
1.2
0.1
0.6
0.5
2.6
1.4
0.4
0.1
0.1
0.5
0.4
6.5
5.9
6.2
8.4
2.5
5.9
4.5
4.7
22.9
6.0
5.2
8.4
4.8
7.9
10.9
4.2
6.7
7.1
6.1
8.1
4.2
14.0
4.4
6.8
Ecoregion
No
1c
1C
1C
1C
1C
1C
1C
1e
1d
1d
1d
1d
1f
1f
1f
1f
1f
1f
1f
1f
1f
1f
1f
1f
1f
1f
1f
1a
1a
1a
1a
1a
1a
1a
1a
1a
1a
1a
1a
1a
1a
1a
1a
1a
1b
1b
1b
1b
1Q
1Q
1a
ECOREGION
NAME
Low Olympics
Low Olympics
Low Olympics
Low Olympics
Low Olympics
Low Olympics
Low Olympics
Outwash
Volcanics
Volcanics
Volcanics
Volcanics
Willapa Hills
Willapa Hills
Willapa Hills
Willapa Hills
Willapa Hills
Willapa Hills
Willapa Hills
Willapa Hills
Willapa Hills
Willapa Hills
Willapa Hills
Willapa Hills
Willapa Hills
Willapa Hills
Willapa Hills
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Lowlands
Coastal Uplands
Coastal Uplands
Coastal Uplands
Coastal Uplands
Mid-Coastal Sediment
Mid-Coastal Sediment
Mid-Coastal Sediment
37

-------
LAKENAME
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake
Unnamed Lake (?)
Unnamed Lake (?)
Unnamed Lake (?)
Unnamed Lake (?)
Unnamed Lakes
Unnamed Lakes
Unnamed Lakes
Unnamed Lakes
Unnamed Lakes
Unnamed Lakes
Unnamed Lakes
Unnamed Lakes
Unnamed Lakes
Unnamed Lakes
Unnamed Lakes
Unnamed Lakes
Unnamed Lakes
Unnamed Lakes
Unnamed Lakes
Unnamed Lakes
Unnamed Lakes
Unnamed Lakes
Unnamed Lakes
Unnamed Lakes
Unnamed lake
Upper Pony Creek Reservoir
Wagonwheel Lake
Wentworth Lake
West Lake
Wickiup Lake
Wild Ace Lake
Wild Cat Lake
Willoughby Lake
Woahink Lake
Yahoo Lake
HECTARES
(ha)
5.3
4.2
5.1
4.4
8.3
2.1
0.6
2.0
0.8
1.0
0.4
0.1
116.5
10.6
0.4
5.2
7.0
7.6
21.9
0.2
0.2
1.0
0.7
0.0
0.2
0.1
0.0
1.3
0.6
0.1
0.1
0.4
0.4
0.2
0.3
0.1
1.3
0.2
0.1
7.0
48.7
1.1
19.4
7.6
5.6
4.4
1.7
2.0
312.3
3.7
Ecoregion
No
ig
1e
1d
1d
1f
1f
1f
1f
1f
1f
1f
1f
1a
1Q
1d
1b
1b
1b
1b
1c
1d
1f
1f
1f
1f
1c
1d
1f
1f
1f
1f
1c
1f
1f
1f
1c
1f
1f
1f
1b
1b
1d
1b
1a
1f
1a
1d
1b
1a
1c
ECOREGION
NAME
Mid-Coastal Sediment
Outwash
Volcanics
Volcanics
Willapa Hills
Willapa Hills
Willapa Hills
Willapa Hills
Willapa Hills
Willapa Hills
Willapa Hills
Willapa Hills
Coastal Lowlands
Mid-Coastal Sediment
Volcanics
Coastal Uplands
Coastal Uplands
Coastal Uplands
Coastal Uplands
Low Olympics
Volcanics
Willapa Hills
Willapa Hills
Willapa Hills
Willapa Hills
Low Olympics
Volcanics
Willapa Hills
Willapa Hills
Willapa Hills
Willapa Hills
Low Olympics
Willapa Hills
Willapa Hills
Willapa Hills
Low Olympics
Willapa Hills
Willapa Hills
Willapa Hills
Coastal Uplands
Coastal Uplands
Volcanics
Coastal Uplands
Coastal Lowlands
Willapa Hills
Coastal Lowlands
Volcanics
Coastal Uplands
Coastal Lowlands
Low Olympics
38

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Table 2. There are 30 lakes greater than 50 hectares in
sufrace area in the Coast Range Ecoregion.  These lakes
account for 89.2% of the total surface area of lakes greater
than 4  hectares.  Lake Ozette alone accounts for 19.3%  of
the total lake surface area in the ecoregion.
Lakename
Ozette Lake
Lake Cresent
Lake Cushman
Quinault Lake
Siltcoos Lake
Tahkenitch Lake
Tenmile Lake
Wynoochee Lake
North Tenmile Lake
Woahink Lake
Devils Lake
Dickey Lake
Summit Lake
Lake Pleasant
Eel Lake
Lake Sutherland
Horsfall Lake
Mercer Lake
Lake Aldwell
Floras Lake
Clear Lake
Triangle Lake
Duck Lake
Loon Lake
Cullaby Lake
Barney Reservoir
Loomis Lake
Clear Lake
Garrison Lake
McGwire Reservoir
Area
(ha)
3007
2031
1623
1434
1205
622
480
406
342
312
234
208
207
199
151
142
132
125
122
114
113
111
101
97
84
81
61
61
53
51
Total 13900
Long
(dd)
-124.6
-123.8
-123.3
-123.9
-124.1
-124.1
-124.1
-123.6
-124.1
-124.1
-124.0
-124.5
-123.1
-124.3
-124.2
-123.7
-124.2
-124.1
-123.6
-124.5
-124.2
-123.6
-124.1
-123.8
-123.9
-123.4
-124.0
-124.1
-124.5
-123.4

Lat
(dd)
48.1
48.1
47.5
47.5
43.9
43.8
43.6
47.4
43.6
43.9
45.0
48.1
47.1
48.1
43.6
48.1
43.5
44.1
48.1
42.9
43.6
44.2
47.0
43.6
46.1
45.4
46.4
44.0
42.8
45.3

%
Area
19.3
13.0
10.4
9.2
7.7
4.0
3.1
2.6
2.2
2.0
1.5
1.3
1.3
1.3
1.0
0.9
0.9
0.8
0.8
0.7
0.7
0.7
0.6
0.6
0.5
0.5
0.4
0.4
0.3
0.3
89.2
                                              38

-------
Table  3.   Median values for selected  water quality parameters for lakes  in  each of seven  lake
categories. MD - mean depth, Chi a - chlorophyll, Sec - Secchi, Oxygen profile (O2) : clino = clinograde,
ortho = orthograde, na = not applicable. Mixing status (MS): mono = monomictic, poly = polymictic.
Lake Name Lat Long Area MD SRP TP TN NO3 NH3 TKN Chi a Sec O2 MS
Category 1 - Dystrophic Lakes
BLACK LAKE
CLAM LAKE
CREEP&CRAWL
CULLABY LAKE
FRESHWATER LAKE
ISLAND LAKE
LONG LAKE
SMITH-CLATSOP
SUNSET LAKE
FAILOR LAKE
STUMP LAKE
46.3
46.4
46.2
46.1
46.4
46.4
46.2
46.1
46.1
47.1
47.1
-124.0
-124.0
-124.0
-123.9
-124.0
-124.0
-123.9
-123.9
-123.9
-124.0
-123.3
12
4
0
84
3
22
5
18
15
25
11
-
1.0
1.0
1.6
1.0
1.4
0.8
3.3
2.5
1.8
-
-
0.0
0.0

0.0
0.0
0.0

0.0
0.0
-

166.5
184.0
77.5
82.0
26.0
152.0
66.0
90.5
22.0
42.0
10
940
1230
410
1070
530
875
650
530
280
520
10
0
0
30
0
2
3
50
15
1
-
-
-
-
60
-
-
-
90
60
5
-
0
-
-
0
-
-
-
600
0
-
500
-
26.7
54.2
3.1
24.3
10.0
23.0
5.4
11.6
17.5
29.5
-
0.8
0.6
1.0
0.4
2.0
1.2
-
1.3
2.4
2.1
?
clino
clino
clino
na
na
clino
clino
clino
clino
clino
?
mon
poly
poly
poly
poly
poly
poly
po
poly
poly
Category 2 - Shallow Coastal Lakes
BEALE LAKE
COFFENBURY LAKE
CROFT
DEVILS-LINCOLN
FLORAS
HORSFALL SPIRIT
LAKE LYTTLE
NORTH TENMILE
SILTCOOS
SMITH-MAGRUDER
SOUTH TEN MILE
TAHKENITCH
43.5
46.2
43.0
45.0
42.9
43.5
45.6
43.6
43.9
45.6
43.6
43.8
-124.2
-124.0
-124.5
-124.0
-124.5
-124.2
-123.9
-124.1
-124.1
-123.9
-124.2
-124.2
21
22
29
234
114
132
19
342
120
9
480
622
1.7
1.5
2.3
3.0
5.5
0.4
1.9
3.4
3.3
-
3.0
3.3
-
-
-
-
-
-
0.0
0.0
0.0
-
0.0
0.0
12.0
22.5
23.0
23.5
8.0
41.0
25.5
30.0
18.0
8.0
35.0
20.0
250
410
320
-
220
1120
250
720
320
230
970
320
50
50
20
-
20
20
3
10
10
-
100
50
20
50
20
-
20
20
-
30
-
-
130

200
400
300
0
0
1100
0
400
0
-
600
160
7.8
0.6
0.8
6.8
0.7
12.9
3.2
17.0
6.1
-
7.5
6.2
2.0
1.8
-
1.4
2.7
-
1.6
2.5
2.2
-
4.2
2.4
ortho
ortho
?
ortho
?
?
ortho
ortho
ortho
ortho
ortho
ortho
poly
poly
?
poly
?
?
poly
poly
poly
poly
poly
poly
Category 3 - Deep Coastal Lakes
CLEAR-DOUGLAS
CLEAR-LANE
CLEAWOX
COLLARD LAKE
EEL
LAUREL LAKE
MERCER
MUNSEL
SUTTON LAKE
WOAHINK LAKE
43.7
44.0
43.9
44.2
43.6
43.0
44.1
44.0
44.1
43.9
124.2
-124.1
-124.1
-124.1
124.2
-124.4
-124.1
124.1
-124.1
-124.1
113
61
40
15
151
16
125
37
22
312
16.5
12.2
5.2
6.6
10.5
4.6
7.1
9.3
5.8
10.9
0.0
0.0
-
0.0
0.0
0.0
-
0.0
-
0.0
10.0
10.0
10.0
10.0
20.0
20.5
20.0
10.5
18.0
5.0
395
120
220
235
230
180
-
160
230
135
215
44
20
5
228
1
-
1
-
112
9
4
20
20
3
-
-
0
-
2
220
0
0
0
0
-
0
0
-
0
2.3
1.5
2.3
4.3
4.1
15.6
9.2
2.9
-
2.0
7.9
6.4
4.9
3.9
4.0
3.2
4.2
5.5
4.0
5.2
?
?
clino
clino
clino
clino
?
clino
clino
clino
?
?
mon
mon
mon
mon
?
mon
mon
mon
                                              39

-------
Lake Name Lat Long Area MD SRP TP TN NO3 NH3 TKN Chi a Sec O2 MS
Category 4 - Forested Lakes
BEAVER LAKE
DICKEY LAKE
HORSESHOE LAKE
LAKE WYNOOCHEE
LAKE MILLS
LAKE PLEASANT
LAKE TARBOO
LAKE WENTWORTH
LOON-DOUGLAS
NAHWATZEL LAKE
OLLALA RESERVOIR
RINKCREEK
SANDY SHORE LAKE
TOWN LAKE
TRIANGLE LAKE
48.1
48.1
47.9
47.4
48.0
48.1
47.9
48.0
43.6
47.2
44.7
43.2
47.9
45.2
44.2
-124.2
-124.5
-122.8
-123.6
-123.6
-124.3
-122.9
-124.5
-123.8
-123.3
-123.9
-124.1
-122.8
-124.0
-123.6
15
208
5
406
180
199
8
19
97
115
40
5
14
4
111
6.5
7.5
-
-
-
3.0
-
3.5
16.3
3.9
8.2
5.8
-
1.6
15.8
0.0
0.0
0.0
0.0
-
0.0
-
0.0
0.0
0.0
-
0.0
-
0.0
-
10.0
10.0
9.5
6.5
20.0
8.5
10.0
13.0
10.0
7.0
8.0
15.0
10.0
21.5
12.0
150
200
280
50
-
150
-
250
230
220
150
300
-
270
190
13
77
2
74
-
77
-
69
30
65
-
894
-
76
20
18
40
6
33
-
33

26
20
22
-
-
-
-
20
500
-
500
0
500
500
500
-
0
-
-
-
500
-
0
22.4
7.8
2.6
0.4
-
4.6
11.6
10.3
0.5
1.3
-
20.5
2.0
4.2
2.1
2.5
2.1
4.0
6.4
4.3
5.1
3.0
2.5
2.6
4.0
4.0
4.0
4.5
3.5
4.0
clino
clino
clino
clino
clino
clino
clino
clino
?
clino
clino
clino
clino
ortho
clino
poly
mon
poly
mon
poly
poly
poly
poly
?
mon
poly
mon
poly
poly
mon
Category 5 - Log Ponds
JOHNSON LOG
LAKE CREEK
MCCLEARY LAKE
VERNONIA
43.1
44.2
47.0
45.9
-124.2
-123.5
-123.3
-123.2
33
11
8
10
1.2
-
1.0
0.5
0.0
-
0.0
-
145.0
16.0
39.0
39.0
2110
140
850
900
4
-
2
-
-
-
-
-
-
-
-
-
7.6
-
-
-
1.0
2.0
1.0

na
na
na
na
poly
poly
poly
poly
Category 6 - Sea Water Intrusion Lakes
GARRISON LAKE |42.8
-124.5
53
2.5
0.0
30.0
310
3
35
0
8.1
2.8
clino
mero
Category 7 - Unique Lakes
LAKE CUSHMAN
LAKE CRESCENT
LAKE OZETTE
LAKE QUINAULT
47.4
48.1
48.2
47.5
-123.2
-123.8
-124.7
-123.9
162
203
300
143
-
92.8
38.4
41.8
0.0
0.0
0.0
0.0
5.0
11.0
10.0
12.5
100
40
205
120
50
1
60
65
10
3
30
21
75
0
120
-
-
0.4
19.5
1.1
-
18.0
3.8
10.1
clino
clino
clino
clino
mon
mon
poly
mon
40

-------