Section 11.0 Aquatic Food Web Data

1 For clarity, bioconcentration factors (BCFs) are a measure of chemical accumulation into biota tissues

associated with exposure to the surrounding media only (e.g., surface water) while bioaccumulation factors (BAFs)

are associated primarily with the additive exposure from both contaminated prey and the surrounding media. For

simplicity in this discussion, BCFs and BAFs are referred to jointly as bioaccumulation factors. 

11-1

11.0 Aquatic Food Web Data

Two primary databases were designed in support of the aquatic food web: the aquatic

food web chemical properties database (referred to herein as the chemical properties database)

and the fish attribute database. 

# The chemical properties database contains two types of parameters: (1) equation

variables used in estimating the bioconcentration and bioaccumulation of

nonionic organic compounds into aquatic organisms using chemical-specific

properties (e.g., log Kow, the octanol/water partition coefficient) and (2)

experimentally derived bioconcentration and bioaccumulation factors

(BCFs/BAFs) for ionic compounds, such as metals.1

 

# The fish attribute database is composed of data characterizing the physiological

traits and dietary preferences of aquatic biota. This database characterizes the life

history attributes that influence the exposures of fish and other aquatic food web

biota. Life history parameters such as fish body weight, tissue lipid fraction,

tissue water fraction, and common prey items are identified. This database also

supports the human health exposure analysis by identifying the types of fish that

are likely to be consumed by humans. 

11.1 Parameters

These two databases are discussed individually throughout this section. The parameters

included in each database are outlined in Table 11-1 with a corresponding module parameter

code and brief description. The final values used for each parameter are reported in

Appendix 11A for the chemical properties database and Appendix 11B for the fish attribute

database.

11.2 Data Sources

Various sources were investigated to compile the databases for the aquatic food web. 

Each database was constructed to reflect different degrees of variability. The chemical

properties database was compiled to reflect average constituent BCFs and BAFs for individual

biota in the aquatic food web. In the case of the fish attribute database, the aim of the data 
Section 11.0 Aquatic Food Web Data

11-2

Table 11-1. Summary of Parameters Applied in Modeling the Aquatic Food Web

Chemical Properties Database Fish Attribute Database

# Slopes (a and b) and error term (c) of the bioconcentration

factor (BCF) regression equation for muscle tissue in fish

(a_mus, b_mus, and c_mus, respectively)

# Slopes (a and b) and error term (c) of the BCF regression

equation for whole body tissue in fish (a_fish, b_fish, and

c_fish, respectively)

# Aquatic macrophyte BCF (ChemaqmpBCFm)—Ratio of

the measured concentration in the tissue of aquatic

macrophytes to the concentration measured in the

surrounding water

# Aquatic macrophyte biota-sediment accumulation factor

(BSAF) (ChemaqmpBSAFm)—Ratio of the measured

concentration in the tissue of aquatic macrophytes to the

concentration measured in the sediment

# Benthic filter feeder bioaccumulation factor (BAF)

(ChembenthffBAFm)—Ratio of the measured

concentration in the tissue of the benthic filter feeder to the

concentration measured in the surrounding water and/or

prey

# Benthic filter feeder BSAF (ChembenthffBSAFm)—Ratio

of the measured concentration in the tissue of the benthic

filter feeder to the concentration measured in the sediment. 

# Trophic level 3 (T3) and trophic level 4 (T4) fish BAF

(ChemT3fishBAFm and ChemT4fishBAFm)—Ratio of the

measured concentration in the tissue of the whole fish to

the concentration measured in the surrounding water and

prey

# T3 and T4 muscle BAF (ChemT3musBAFm and

ChemT4musBAFm)—Ratio of the measured concentration

in the muscle of the fish to the concentration measured in

the surrounding water and prey

# Fish body weight (BwFish)—Weight

of whole fish in kg

# Lipid fraction (LipFrac)—Fraction of

lipid in the whole fish

# Muscle lipid fraction

(LipFracMus)—Fraction of lipid in the

fish muscle (fillet)

# Minimum prey preference

(MinPreyPref)—Minimum fraction of

diet for a given prey item

# Maximum prey preference

(MaxPreyPref)—Maximum fraction of

diet for a given prey item

# Fillet fraction (FilletFrac)—Fraction of

fish that is fillet

# Muscle water fraction

(MusWaterFrac)—Water fraction in

the muscle (fillet) of fish

# Fish water fraction

(FishWaterFrac)—Water fraction

across all tissues of fish 

# T3 edible fish (T3EdibleFish)— Edible

T3 fish for human consumption

collection effort was to represent the variability of parameters at the national level across

different waterbody types (e.g., lakes and streams) and surface water temperatures (e.g., warm

and cold). To accomplish these tasks, various government agencies, U.S. Environmental

Protection Agency (EPA) offices, research laboratories, and primary literature sources were

consulted to review publications, databases, and guidance documents to support the development

of the aquatic food web databases. Key sources identified for each database are reviewed. 
Section 11.0 Aquatic Food Web Data

11-3

11.2.1 Chemical Properties Database

The chemical properties database characterized the chemical-specific bioaccumulation

parameters in the aquatic food web. The sources identified for this database were limited. 

Bioconcentration factors (BCFs), bioaccumulation factors (BAFs), and biota-sediment

accumulation factors (BSAFs) were the primary metrics needed for this database to estimate

measures of chemical bioaccumulation. Most measured BAFs were identified in the primary

literature or in EPA’s Aquatic Information and Retrieval (AQUIRE) database (U.S. EPA,

1999a). For organic constituents, accumulation was predicted using regression models based on

chemical properties. The models proposed by Bertelsen et al. (1998) and Gobas (1993) were

adopted for this analysis to predict the bioaccumulation of organic contaminants into fish. The

following key sources were used in developing the chemical properties database: 

# Bertelsen et al. 1998. Evaluation of log Kow and tissue lipid content as predictors

of chemical partitioning to fish tissues. Environmental Toxicology and Chemistry

17:1447-1455.

# Gobas, F.A.P.C. 1993. A model for predicting the bioaccumulation of

hydrophobic organic chemicals in aquatic food webs: Application to Lake

Ontario. Ecological Modelling 69:1-17.

# Primary literature (Barrows et al., 1980; Kumada et al., 1973; Lemly, 1985;

Murphy et al., 1978; Stephan, 1993; Naqvi et al., 1993; Dirilgen and Inel, 1994;

Mekela et al, 1991; Basack et al., 1997Thomann et al, 1995; Gossett et al., 1983;

Hendriks et al., 1998; Metcalfe-Smith, 1994; Betchel Jacobs, 1998).

# U.S. EPA Databases/Publications and Other Government Agency Resources. 

(U.S. EPA, 1999a; U.S. EPA, 1993; FWS, 1990; Ruiz, 1994) 

11.2.2 Fish Attribute Database

The goal in developing the fish attribute database was to characterize the variability of

the parameters in different aquatic habitats at the national scale. No single database was

identified that classified the physical and behavioral attributes of fish at this level of resolution;

therefore, this task required pooling multiple resources across different regions to represent the

variability of parameters across a number of ecotypes and waterbodies. Although true national

data distributions were preferred for this assessment, the data collection effort only reflects the

initial stages of compiling such an extensive database. The key sources that were identified to

characterize the module parameters of the fish attribute database are outlined in Table 11-2. 

11.3 Methodology

The methods used to generate values for each parameter in the databases are detailed in

this section, which is structured around the general databases developed for the aquatic food

web: the chemical properties database and the fish attribute database. In each database

discussion, methods of database compilation and processing and assumptions and uncertainties

are addressed.
Section 11.0 Aquatic Food Web Data

11-4

Table 11-2. Key Data Sources Identified to Evaluate for Fish Attribute Database

Government Agencies

# U.S. Geological Survey. National Ambient Water Quality Assessment (NAWQA) Program. 

Available online at http://water.usgs.gov/nawqa/

- South Platte River Basin (USGS, 1998a)

- Lake Erie-Lake St. Clair Drainage (USGS, 1998b)

- Albemarle Pamlico Drainage (USGS, 1998c)

- San Joaquin-Tulare (USGS, 1998d)

- Upper Snake River Basin (USGS, 1998e)

# Lutz, C. 1999. The BSAF Database for Windows Version 1.0. Environmental Laboratory. 

Waterways Experiment Station.

EPA Documents

# OEPA (Ohio Environmental Protection Agency). 1997, 1998a, b, c. Ecological Assessment Division of

Surface Water. 

- OEPA (Ohio Environmental Protection Agency). 1997. Biological and Water Quality Study of

Big Walnut Creek: D.E. Edwards Landfill. October. Monitoring and Assessment Division. 

Division of Surface Water. 

- OEPA (Ohio Environmental Protection Agency). 1998a. Biological, Fish Tissue, and Sediment

Study of the Ottawa River. Dura Avenue Landfill, 1996. January. Monitoring and Assessment

Division. Division of Surface Water. 

- OEPA (Ohio Environmental Protection Agency). 1998b. Biological and Water Quality Study of 

Lower Big Walnut Creek and Walnut Creek Tributaries, 1996: Rickenbacker Airport. April. 

Ecological Assessment Unit. Division of Surface Water. 

- OEPA (Ohio Environmental Protection Agency). 1998c. Biological and Water Quality Study of 

Little Cuyahoga River and Tributaries. April. Ecological Assessment Unit. Division of Surface

Water. 

# U.S. EPA (Environmental Protection Agency). 1993b. Interim Report on Data and Methods for

Assessment of 2,3,7,8-Tetrachlorodibenzo-p-dioxin Risks to Aquatic Life and Associated Wildlife.

EPA-600/R-93/055. Office of Research and Development, Washington, DC. 

# U.S. EPA (Environmental Protection Agency). 1995a. Great Lakes Water Quality Initiative Technical

Support Document for the Procedure to Determine Bioaccumulation Factors. EPA-820-B-95-005. 

Office of Water, Washington, DC. 

# U.S. EPA (Environmental Protection Agency). 1995b. Trophic Level and Exposure Analyses for

Selected Piscivorous Birds and Mammals. Volumes II and III. Analysis of Species in the Conterminous

United States. Office of Science and Technology, Office of Water, Washington, DC. Prepared by ICF

Incorporated, Fairfax, VA, under EPA Contract No. 68-W3-0008 and No. 68-C3-0332.

(continued)
Table 11-2. (continued)

Section 11.0 Aquatic Food Web Data

11-5

Primary Literature

# Primary references (Clarke et al., 1988; Donald et al., 1998; Glassmeyer et al., 1997; Kuehl et al.,

1987; Miskimmin et al., 1995).

General Reference

# Cohen, J.E, F. Briand, and C.M. Newman. 1990. Community Food Webs Data and Theory.

Springer-Verlag: Berlin.

# FishBASE. 1998. FishBASE ‘98: Concepts, Design and Data Sources. Available online at

http://www.fishbase.org/manual/contents.htm.

# Gerking, S.D. 1994. Feeding Ecology of Fish. Academic Press: San Diego, CA.

# Hackney, C.T, S.M. Adams, and W.H. Martin. 1992. Biodiversity of the Southeastern United

States Aquatic Communities. John Wiley & Sons: New York, NY.

# Lee, D.S., et al. 1980. Atlas of North American Freshwater Fishes. North Carolina State Museum

of Natural History. 

# Page, L.M., and B.M. Burr. 1991. A Field Guide to Freshwater Fishes. Houghton Mifflin: 

Boston. 

# Simon, T.P. (ed). 1999. Assessing the Sustainability and Biological Integrity of Water Resources

Using Fish Communities. CRC Press: Boca Raton, FL. 

# Smith, C.L. 1994. Fish Watching: An Outdoor Guide to Freshwater Fishes. Cornell University

Press: Ithaca, NY. 

# Sternberg, D. 1987. Freshwater Gamefish of North America. Cowles Creative Publishing: 

Minnetonka, MN. 

11.3.1 Chemical Properties Database

11.3.1.1 Database Compilation. The chemical properties database contains variables

used in the module that are related to chemical accumulation in aquatic biota. Bioaccumulation

in fish and other prey items in the aquatic food web is a critical link in estimating exposures of

terrestrial organisms foraging primarily in aquatic food webs. Accumulation of chemicals into

biota is a dynamic process, and it can be minimized, mediated, or magnified depending on

chemical-specific properties, organism physiology and behavior, and other environmental

conditions. The bioaccumulation of chemicals into aquatic biota can be estimated empirically

using models or measured through laboratory exposure experiments. In this analysis, measured

BAFs were gathered for metals and for other constituents (i.e., polynuclear aromatic

hydrocarbons [PAHs], dioxin, and mercury compounds). For organic constituents, two different

models were applied to estimate accumulation into fish tissues (i.e., Bertelsen et al., 1998, and

Gobas, 1993). This section discusses each method (i.e., estimated versus measured values)

separately.
Section 11.0 Aquatic Food Web Data

11-6

Estimated Bioaccumulation Factors. Chemical accumulation is sometimes quantified

based on chemical properties (e.g., Kow) and uptake rates using linear relationships. For this

effort, accumulation of organic constituents (including dioxins) into fish tissues was estimated

using two chemical partitioning models: Bertelsen et al. (1998) and Gobas (1993). The

Bertelsen et al. (1998) approach was applied when the chemical log Kow values were less than

4.0. For chemicals with log Kow values exceeding 4.0, the Gobas (1993) model was applied. 

Different methods were applied because the accumulation of chemicals is highly dependent on

their hydrophobicity, which can be approximated based on the constituent-specific log Kow. Low

log Kow constituents are less hydrophobic than high log Kow constituents, by definition. For

chemicals with log Kow values less than 4.0, the bioaccumulation of dissolved chemicals from the

water column is a good predictor of the bioconcentration in fish tissues. The Bertelsen et al.

(1998) model primarily uses this relationship to estimate bioaccumulation in fish. For chemicals

with log Kow values greater than 4.0, bioaccumulation from the water column is minimal

compared to bioaccumulation from contaminated prey items. The Gobas (1993) model

incorporates food web dynamics to estimate bioaccumulation in fish. 

The equations proposed by Bertelsen et al. (1998) estimate the chemical residues in

different fish tissues resulting from the chemical concentrations in surrounding surface water

(i.e., estimated BCFs). This model was designed by the combination of two log-linear models to

estimate the bioaccumulation of contaminants from the water column to the fish tissue

(expressed on a lipid basis) (Bertelsen et al., 1998) (Equation 11-1).

(11-1)

where

Ktw = tissue/water equilibrium chemical partition coefficient

Kow = chemical-specific octanol/water partition coefficient

fraction lipid = assumed or empirically derived tissue lipid fraction

a, b, c = see Table 11-3.

The Ktw value quantifies the ratio of the chemical in the tissue to the chemical in the water (i.e.,

the BCF). The coefficients a, b, and c are empirically derived for different tissue types (i.e.,

whole body and muscle). The coefficients correspond to module parameters a_mus, b_mus, and

c_mus and a_fish, b_fish, and c_fish, which were used to derive BAFs for organic compounds in

muscle and whole body, respectively. Both a and b are slope terms describing a threedimensional data plane, and c is the error term. The variables a, b, and c are applied in

Equation 11-1 as outlined in Table 11-3.

For organic chemicals with a log Kow greater than 4.0, the Gobas (1993) model was

applied. The Gobas model uses a steady-state model that estimates accumulation into various

food web compartments of the aquatic ecosystem. It accounts for the toxicokinetics of uptake,

elimination rates, and multiple feeding interactions. For more information on the calculations

applied in the Gobas method, see the module documentation (U.S. EPA, 1999b) for the aquatic

food web. 
Section 11.0 Aquatic Food Web Data

11-7

Table 11-3. Constants for Different Tissue Types Applied to Equation 11-1

Equation Variable

Tissue Type

(Parameter names)

abc

Muscle 

(a_mus, b_mus, c_mus)

0.69 0.92 0.76

Whole body

(a_fish, b_fish, c_fish)

0.74 1.00 0.72

Measured Bioaccumulation Factors. For other constituents not assigned as organic

(e.g., metals and PAHs), bioaccumulation was approximated through experimental

measurements in the laboratory or field as reported in the literature. The availability of

measured BAFs and BSAFs for the following receptor categories was the focus of data

collection efforts: aquatic macrophytes, benthic filter feeders, and trophic level 3 (T3) and 4 (T4)

fish. The BAFs for T3 and T4 fish were further refined to estimate whole-body or fillet BAFs. 

For metals, BAFs identified for whole body were also applied as fillet BAFs. Data selection

criteria were used to identify measured BAFs from the sources in order to select values using

analogous standards. The following criteria were used in reviewing data:

# In data searches, a BAF value was preferred over a BCF value because most

organisms are usually more highly exposed through ingestion of contaminated

matter than through direct contact. This is the preferred metric because it more

accurately represents typical exposures observed in the environment. In spite of

this, the primary literature more commonly reports BCFs rather than BAFs,

creating data limitations for this analysis. For this method, BAFs were the first

choice; when they were not available, BCFs were used. 

# Exposures that reached steady-state conditions were preferred. To meet this

requirement, exposures to aquatic biota had to exceed a certain duration

depending on the receptor (e.g., algae >24 h, aquatic invertebrates >48 h, fish

>96 h). For this analysis, however, the measured BCF/BAF value with the

highest exposure duration was used. When a series of exposures at different

concentrations were used to estimate BCFs, the occurrence of steady-state

conditions (e.g., the plateau effect) was assessed. When this effect was observed,

a geometric mean of the plateau values was taken to determine the BCF estimate.

# Data reflecting exposures to freshwater benthic filter feeders were preferred. 

However, sufficient data were not always available within these requirements;

therefore, data reflecting exposures to marine organisms were used as well. There

is uncertainty with this approach given the fundamental differences in chemical

equilibria in marine waters that may influence chemical bioavailability and

speciation. Researchers have proposed that the BAFs and BSAFs measured in
Section 11.0 Aquatic Food Web Data

11-8

marine species may be different from those measured in freshwater species

(Metcalfe-Smith et al., 1996). 

# When available, surface water-based BAFs and sediment-based BSAF data were

collected for aquatic macrophytes and benthic filter feeders since these prey items

can have significant exposure through both pathways (Jackson, 1998). Data

reflecting sediment-based exposures were preferred for benthic filter feeders;

while surface water exposures were preferred for other aquatic macrophytes. 

Both types of accumulation factors were included in the database to increase the

flexibility of the model to evaluate both exposure pathways when data are

available. 

# Metal BAFs were derived from studies reporting values based on total metal

concentrations in tissue and media. This assumption introduces some uncertainty

because not all metals occur in a bioavailable form. Typically, the total dissolved

concentration is a better measure of what is actually bioavailable to fish.

The BAFs that were identified through data collection efforts were used to calculate

chemical-specific geometric means for the aquatic prey items. Bioaccumulation data were

assumed to be lognormally distributed; therefore, the geometric mean was the best estimate of

central tendency. Sources used to calculate geometric means and the BAFs and BSAFs

compiled in the database are provided in Appendix 11A, Tables 11A-1 and 11A-2. 

11.3.1.2 Data Processing. Estimated or measured BAFs were generated for prey items

in the aquatic food web, including macrophytes, benthic filter feeders, and fish. Data permitting,

fish BAFs were developed for both T3 and T4 fish based on both whole body and muscle tissue.

Estimated BAFs generated by applying models were calculated internally by the model. For

organics, BAFs used in the analysis were modeled for each prey item. The data presented in

Appendix 11A do not reflect these internally calculated values. In the chemical properties

database, these values are entered as the default value of 1. The default value acts as a

placeholder and was required by the modeling system.

For other constituents, classified as dioxins, mercury, metals, and special (e.g., PAHs),

measured BAFs were identified. The constituent-specific geometric mean of values was

calculated for prey items. These values were manually compiled into the spreadsheet and are

presented in Appendix 11A. When sufficient data were not identified through literature

searches, a default value of 1 was entered. 

11.3.1.3 Assumptions and Uncertainties. In developing the chemical properties

database, several key assumptions and points of uncertainty were apparent. These uncertainties

can be grouped into data gaps, default assumptions, and variability.

Data Gaps. Developing the chemical properties database was extremely limited by data

availability. For constituents that required measured BAFs and BSAFs, data collection revealed

that accumulation factors were unavailable for many constituents. When BAFs were not

identified, uncertainty was introduced into the evaluation of some aquatic food exposure

pathways.
Section 11.0 Aquatic Food Web Data

11-9

Default Values. When BAFs were not available, a default value of 1 was added to the

database. Default values should not be construed as estimates of bioaccumulation; rather, they

should be viewed only as placeholders until more representative data are identified. The risk

results need to be considered within the limitations of the default values. 

Variability. In the development of the chemical properties database, the BAFs reflected

central tendency estimates. Depending on the quantity of data identified, uncertainty was

associated with how accurately the central tendency value was estimated. In many cases, only a

few BAFs were identified to characterize the distribution of values. Because distributions based

on so few values can be influenced by extreme values (e.g., outliers) or clustered data, the central

tendency value may not adequately reflect the variability in this parameter. As the model is

refined, the variability in bioaccumulation may be better characterized through assumed

distributions and Monte Carlo simulations. 

11.3.2 Fish Attribute Database

11.3.2.1 Database Compilation. This database was used to reflect the variability in the

parameters of fish body weight, lipid fraction (whole body and muscle), and prey preferences;

the means for water fractions in whole body fish tissues and fillet fractions; and the fish

categories (e.g., T3 large benthivores, T4 piscivores) in the aquatic food web likely to be

consumed by humans. Because some of the parameters assessed in the fish attribute database

can vary significantly across different waterbodies, water temperatures, and habitat structures, it

was important to characterize some of the parameters across various aquatic ecosystems. 

An additional step of preprocessing was conducted on the fish attribute database in an

effort to capture the variability introduced into the body weights, lipid content (total body and

muscle), and dietary preference parameters resulting from fish that are distributed across

different environmental conditions. Species-specific data for these parameters were collated into

groups based on trophic level (i.e., 3 or 4), relative fish size (i.e., small, medium, or large), water

temperature preference (i.e., warm or cold), habitat preference (i.e., stream, pond, lake, or

wetland), and dietary classification (i.e., benthivore, zooplanktivore, omnivore, or piscivore). 

These categories are not explicitly included in the list of parameters for the fish attribute

database, but they were vital to the decision criteria used in compiling the database. Statistical

metrics (e.g., mean, minimum and maximum) of body weight, fraction lipid, and dietary

preference were derived for adult fish of specific trophic levels and habitat classifications. For

example, a mean body weight was derived for small T3 benthivores in warmwater lakes. The

following information outlines the important decision framework used in the preprocessing step

of the fish attribute database:

# Trophic Level–Trophic levels assigned to individual fish species in the fish

attribute database were taken from the U.S. EPA (1995b), Goldstein and Simon

(1999), and Halliwell et al. (1999). Trophic levels were assessed in these

resources by evaluating the diet of individual fish species. Dietary preferences

were reported in the form of quantitative dietary fractions and qualitative dietary

descriptions. The data sources did not assess all the species identified in the fish

attribute database. For fish species that did not have explicit trophic-level

assignments, an approach was used to assign a probable trophic level based on
Section 11.0 Aquatic Food Web Data

11-10

several lines-of-evidence that seemed to suggest one trophic assignment over

another (weight-of-evidence approach). When actual quantitative dietary

fractions were not reported, descriptive qualitative diets were used to assess

trophic levels. Four general rules in evaluating narrative dietary descriptions

were applied, as follows:

- If the species primarily consumed fish, it was assigned as T4. 

- If the fish ate mostly benthic invertebrates, phytoplankton, and

zooplankton, it was assigned as T3. 

- If the fish was closely related to another species that had an assigned

trophic level, similar species were assigned to the same trophic level. For

example, shiners were typically assigned to T3. 

- For related species that could be assigned to either T3 and T4 (e.g., bass)

depending on their life stage and habitat, no assumptions were made about

trophic level, and the species was not included in the database. 

# Relative T3 Fish Size–Relative size was determined across T3 fish, so that

reasonable assumptions about predation among T3 piscivorous fish could be

made in module development (i.e., to avoid the uncommon phenomenon of small

T3 fish preying on large T3 fish). The variability of size and morphology among

T3 fish makes relative size categories somewhat difficult to define. Developing

the relative size cutoffs for T3 fish (i.e., small, medium, or large) required

professional judgment. Because exceptions to these general size classifications

exist, they should only be considered reasonable guidelines in the majority of

cases. Upon examination of the range of fish body weights and lengths in the fish

attribute database, the following cutoffs were used to assigned T3 fish as either

small, medium, or large (Table 11-4). Low and high cutoffs for fish body weight

and fish length were determined by taking the 35th percentile and the 65th

percentile of the data, respectively. If a fish met either of the cutoff values, fish

length was used to assign it to the larger or smaller classification group.

Table 11-4. Fish Body Weight and Length Ranges Used in Relative Size Determinations

Size Classification T3 Benthivores T3 Zooplanktivores T3 Omnivores

Fish Body Weight (g)

Small <2 <3 <9

Medium 2 to 27 3 to 11 9 to 61

Large >27 >11 >61

Fish Length (mm)

Small <53 <61 <84

Medium 53 to 171 61 to 153 84 to 258

Large >171 >153 >258
Section 11.0 Aquatic Food Web Data

11-11

# Water Temperature Preference. Water temperature preference was assigned to

individual fish species as warmwater, coldwater, or both. For this task,

warmwater fish species were species that tolerate surface water temperatures that

annually exceed 25 °C. Warmwater fish typically inhabit surface water ranging

from 10 to 30 °C. Coldwater species typically do not tolerate surface waters that

exceed 25 °C, but they prefer surface waters ranging from 0 to 20 o C. Some fish,

however, are capable of inhabiting the entire range of temperature extremes. 

These fish were assigned to the category of both. Water temperature preferences

for individual fish species were reported by Halliwell et al. (1999). When water

temperature preference designations could not be located for a particular fish

species, a weight-of-evidence approach was used to predict the water temperature

preference of a fish. The weight-of-evidence approach consisted of qualitatively

examining the geographic distribution of a fish species, as follows: 

– If the fish inhabited hydrologic regions where water temperatures annually

exceeded 25 °C, the fish was assigned as warmwater. 

– If the fish consistently inhabited regions where temperatures did not

exceed 25 °C, it was categorized as coldwater. 

– If the species inhabited regions without a clear trend in water temperature,

the fish species was assumed to tolerate both high and low extremes in

water temperatures and was categorized as both.

# Habitat Preference. Habitat preferences (e.g., flowing versus standing water)

were assessed for individual fish species using Peterson’s Field Guide:

Freshwater Fish (Page and Burr, 1991) and Lee et al. (1980). In these references,

narrative descriptions of preferred habitats for individual fish species are

recorded. Typically, fish are capable of inhabiting a variety of freshwater

habitats, including streams, rivers, lakes, wetlands, and ponds. Habitat

preferences, however, can be highly dependent on the life stage of the fish. Data

collection efforts focused on characterizing habitat preferences for adult fish

populations. The fish attribute database assigned fish to habitats that may include

a number of potential waterbody types (e.g., flowing or standing). In the

preprocessing step, this distinction helps to assign fish species to aquatic habitat

types of the module.

# Dietary Classification. A dietary classification was assigned to each fish species

based on the preferred prey items. Dietary preference data were derived primarily

from U.S. EPA (1995b), Goldstein and Simon (1999), and Lee et al. (1980). Fish

were designated as predominantly benthivores, zooplanktivores, omnivores, or

piscivores (only T4 fish were classified as piscivores). Strict herbivores were not

common among fish species; hence, this dietary classification was not used for

this analysis (Gerking, 1994; Goldstein and Simon, 1999). The fish attribute

database identified dietary fractions for the following prey items: plant material,

detritus, zooplankton, benthos, terrestrial insects, and fish. Benthivores and

zooplanktivores are species of fish that forage primarily on benthos and
Section 11.0 Aquatic Food Web Data

11-12

zooplankton/phytoplankton, respectively. Omnivores are species of fish that meet

one of two criteria: (1) they forage on three or more different prey items or

(2) they forage on fish as one prey item. If the species forage on fish, it was

presumed likely to eat other categories of prey if fish were not available. Fish

were assigned to a dietary classification on which the fish attribute database was

sorted into the respective biota categories of the aquatic food web (e.g., small T3

benthivores).

Given these different classification levels in the preprocessing effort, parameters needed

for the model (e.g., fish body weight, lipid fraction) could be compiled specific to trophic level,

relative size, water temperature preference, habitat preference, and dietary classification. For

example, lipids and body weights were compiled from the fish attribute database specifically for

a small T3 omnivore in warmwater streams (i.e., this aquatic food web compartment uses all five

of the preprocessing descriptors). When data were available, module parameters were estimated

in each aquatic food web compartment across different habitats. A review of the methods used

in database compilation of the model parameters (as opposed to the preprocessing parameters) is

described for each variable in the fish attribute database: fish body weight, lipid fraction (whole

body and muscle), water fraction (whole body and muscle), fillet fraction, and T3 edible fish. 

11.3.2.1.1 Fish Body Weight. A species-specific mean of fish body weight was derived

from data generated in the preprocessing effort. These species-specific means were collapsed

into one value that represented an arithmetic mean body weight estimate for a fish category. For

example, medium-sized T3 benthivores of coldwater lakes were composed of the mean body

weights of the following species: longnose sucker, Sacramento sucker, splittail, and Utah sucker. 

The average of the species-specific means was used to characterized the variability of species

within a food web compartment. The database reflected increasing body weights based on

relative size (i.e., small, medium, or large) and trophic level (i.e., T3 or T4).

In compiling the fish body weight parameter, a few data decision criteria were used in

identifying comparable and appropriate data. Fish body weight data were gathered that

represented adult fish populations. There is some controversy about how to determine when fish

have reached maturity. Maturity can be assessed by size, morphology, weight measurements,

and, most commonly, sexual development. For many fish species, the transition across life

stages is not well-defined. Explicit juvenile weights were not included in the database; however,

in some cases, the fish age or life stage was not reported with the fish body weight. For

NAWQA data, a review of the sample collection methods did not indicate the average age of the

fish sampled. In most cases, fish weights were high enough to assume that the fish was an adult. 

As a gross check, these values were compared with reported general ranges, and, typically, fish

body weights were within the range. Table 11B-3 in Appendix 11B provides the fish body

weight results applied in this analysis.

11.3.2.1.2 Lipid Fraction (Whole Body). An analogous method, as that implemented for

fish body weight, was implemented for fish lipid (whole body). When data were available, an

average of species-specific means was used to estimate the lipid fraction in different aquatic

biota. Overall, the availability of lipid values was limited in the primary literature, especially to

estimate whole body fish lipid values. Given the lack of lipid data for some aquatic food web

compartments, several standard default lipid values were applied. These default values were
Section 11.0 Aquatic Food Web Data

11-13

adopted from the Great Lakes Water Quality Initiative (GLWQI): phytoplankton (0.5 percent),

periphyton (0.5 percent), aquatic macrophytes (0.5 percent), zooplankton (5 percent),

benthicdetritivores (3 percent), and benthic filter feeders (5 percent). (U.S. EPA, 1995a). For

fish, whole bodylipid fractions were assigned by calculating the mean of pooled data in each fish

category.

11.3.2.1.3 Lipid Muscle Fraction. This parameter quantified the fraction of lipid

present in fish muscle (or fillet). Data for this parameter did not capture the same variability

represented in the whole body lipid fraction values. Instead, values reported in the GLWQI that

estimated the fraction of lipid in the muscle were used. Muscle lipid fractions were set at 1.82

percent for T3 fish and 3.10 percent for T4 fish (U.S. EPA, 1995a). Because the default values

adopted from the GLWQI for T3 and T4 fish fillets were derived from a regional database,

uncertainty is introduced into the analysis by applying these default values to a national analysis.

Table 11B-2 in Appendix 11B provides the fish lipid muscle fraction results applied in this

analysis. 

11.3.2.1.4 Fillet Fraction. The fillet fraction is the conversion factor between the lipid

fraction whole body and the lipid muscle fraction. It was derived from the default lipid values

used for whole body and fillet in U.S. EPA (1995a). The GLWQI proposed a 6.46 percent lipid

fraction (whole body) and a 1.82 percent lipid fraction (muscle) for T3 fish. For T4 fish, the

GLWQI used a 10.31 percent lipid fraction (whole body) and a 3.10 percent lipid fraction

(muscle). The parameter fillet fraction was derived by calculating the fraction of muscle lipid to

whole body lipid. For example, to calculate the fillet fraction for T4 fish, the result of 3.10

divided by 10.31 generated a conversion factor of 0.29. The fillet fraction conversion factor was

used to extrapolate lipid-normalized BAFs from whole body fish lipid-normalized values to

muscle lipid-normalized values within a specified trophic level. A conversion factor (i.e., fillet

fraction) of 0.29 was used for T4 fish and a conversion factor of 0.28 was used for T3 fish. 

Table 11B-2 in Appendix 11B provides the fillet fraction results applied in the representative

national data set.

11.3.2.1.5 Fish Water Fraction and Muscle Water Fraction. The fish water fraction

was an estimate of the fraction of water in the whole fish. This value was adopted from the

Wildlife Exposure Factors Handbook (U.S. EPA, 1993a), which reports a percent water value of

75 percent for bony fish. The analogous variable that estimates water fraction in muscle tissue

was found in Bertelsen et al. (1998). The muscle water fraction of 0.79 used in this analysis was

a mean of three fish species (i.e., catfish, trout, and fathead minnow). Review of the Exposure

Factors Handbook (U.S. EPA, 1997a) confirmed that the muscle water fraction used here was

within the typical range for fillets. Table 11B-1 in Appendix 11B provides the fish water

fraction and fish muscle water fraction results applied in the representative national data set. 

11.3.2.1.6 T3 Edible Fish. Some relatively simple assessments were made of T3 fish

species that humans typically consume. Generally most fish are edible; however, not all fish are

eaten by humans. Preferences are usually a function of fish size. Sources that surveyed the

kinds of fish people eat and catch were consulted to select fish categories that were likely to be

consumed (U.S. DOI/U.S. DOC, 1997; U.S. EPA, 1997a). Across the fish categories assigned in

this analysis, most of the fish that humans eat are T4 piscivores (e.g., salmon, trout, walleye,

bass) and medium and large T3 omnivores (e.g., carp, smelt, perch, catfish, sucker, bullhead,
Section 11.0 Aquatic Food Web Data

2 The dietary fraction data identified for terrestrial insects did not translate into the food web compartments

used in the aquatic food web module. There is some uncertainty associated with excluding this prey type because

many fish consume these organisms in their diet. 

11-14

sauger). Occasionally, large T3 benthivores (e.g., lake whitefish) and zooplanktivores (e.g.,

paddlefish) also are consumed. Professional judgment was required to assign edible fish

categories across waterbodies. If a few examples of specific fish species could be found that

were documented to be eaten by humans, then the fish category was included. There are

exceptions to these general assignments; however, these assumptions are reasonable considering

the general patterns of fish typically consumed by humans. Table 11B-3 in Appendix 11B

provides the assignments of fish typically eaten by humans that were applied in the

representative national data set. 

11.3.2.1.7 Dietary Preferences. This parameter was developed to assess what prey

items fish prefer (i.e., dietary preference) and how much of each prey item contributes to the

total fish diet (i.e., dietary composition). Data were gathered that reported the percentage that

different prey items contributed to the whole diet of a fish species. Using these data, a minimum

and maximum dietary fraction for each prey item was quantified (U.S. EPA, 1995b). Two types

of dietary fraction data were reported in the literature: (1) true minima and maxima or (2) single

median values (i.e., values not necessarily reported in the same study). True minima and

maxima were preferred; however, in the absence of these data, the minimum and maximum

range of median values was used. When specific dietary fraction data could not be identified,

narrative descriptions of fish diets were used. In these cases, dietary fractions were equally split

across the prey items reported. 

Data sources reported dietary fractions for the following prey items: plant material,

zooplankton, benthos, terrestrial insects2

, detritus, and fish. The prey items in the aquatic food

web were similar: periphyton, phytoplankton, macrophytes, zooplankton, benthic detritivores,

benthic filter feeders, T3 benthivores (small, medium, and large), T3 zooplanktivores (small,

medium, and large), and T3 omnivores (small, medium, and large). Because of the differences

between the prey items used to construct the aquatic food web and the prey items for which data

were identified, the data identified had to be translated into the aquatic food web prey items. 

The substitution scheme is presented in Table 11-5. Although detritus and benthic detritivores

are not directly transferable as the same prey, by habitat proximity, it is likely that a diet made up

of detritus also will be composed of benthic detritivores. 

Table 11-5. Assignment of Prey Items in Fish Attribute Database to

Prey Items in the Aquatic Food Web

Prey Items in Aquatic Food Web Prey Items in Fish Attribute Database

Periphyton Plant material

Phytoplankton Plant material

Macrophytes Plant material

Zooplankton Zooplankton 
Table 11-5 (continued)

Section 11.0 Aquatic Food Web Data

11-15

Benthic detritivores/detritus Detritus

Benthic filter feeders Benthos

T3 benthivores 

(small, medium, and large) 

Fish

T3 zooplanktivores 

(small, medium, and large)

Fish

T3 omnivores 

(small, medium, and large) 

Fish

T4 piscivores Fish

Because of the limited data identified to characterize fish dietary preferences,

professional judgment was required in determining an appropriate minimum and maximum

range for fish dietary fractions. When a fish category was not represented in the database, the

general trends in fish seen in other similar waterbodies were applied (e.g., comparing the same

fish in warmwater wetlands to fish that occur in warmwater ponds). When limited data, some of

which were derived from narrative descriptions of diets, were available, a weight-of-evidence

approach was used to generate a reasonable dietary fraction estimate for a particular fish species.

To help clarify how data manipulations were conducted, Table 11-6 provides an example

of the raw data conversion strategy for a small omnivore found in a warmwater pond. In many

cases, as apparent in Table 11-6, the raw data translated into useful ranges; however, in some

cases, the data had to be manipulated to meet the data requirements of the model. Note in the

table how the plant material dietary fractions identified in the literature were converted to the

prey categories of phytoplankton, aquatic macrophytes, and periphyton. Professional judgment

was used to assess which prey item would be eaten more frequently than others in the pond

ecosystem. Review of the literature indicated that in ponds macrophytes are likely to be the

most abundant, followed by phytoplankton and periphyton. Because the composition of the

algae and aquatic plant community in warmwater ponds varies over space and time, however,

these assumptions only represent a snapshot of what may be occurring temporally in the pond. 

The ranges of minima and maxima were selected so that the additive fish consumption of plant

material indicated in the raw data would not be exceeded (i.e., the sum of 0.10, 0.05, and 0.15

approximates the 0.31 indicated as the maximum in the raw data). An additional common

assumption made in raw data conversions is represented in the example when the

minimum/maximum range of 0.05 to 0.15 was derived for the prey item of fish. Obviously,

insufficient data were available to characterize the minimum and maximum dietary fractions for

this prey item; however, single median values were available to estimate a range. The low

median value (0.05) was used as the minimum. The median value, assigned as the default, was

taken from descriptive data in which two preferred prey items were noted (0.5 fish and 0.5

benthic invertebrates) for a particular fish species. Consideration that one of the median values

was relatively low and that an additional narrative diet description noted that some species of

small warmwater omnivores occurring in ponds do eat fish resulted in the reasonable estimation

of 0.15 as a maximum value. 
11-16

Table 11-6. Example of Dietary Fraction Raw Data Conversions to Meet Model and Food Web R

Small Omnivores in Warmwater Ponds Raw Data 1 Range Derived from Raw Data Range Translation to Aquatic Food 

Prey Item Minimums Maximums Single Value Min. Max. Prey Item MPlant material 0.04 0.04 0.045 0.064 0.075 0.308 0.044 0.33 (default) 0.136 0.04 0.31 Phytoplankton Periphyton Aquatic macrophytes 0.01 0.01 0.01 

Terrestrial insects 0.001 0.073 0.2 0.38 0.027 0.286 0.33 (default) 0.052 0 0.38 Terrestrial insects dropped as prey item 

included in aquatic food web. Zooplankton 0.166 0.199 0.577 0.324 0.045 0.3 0.47 0.741 0.353 0.049 ID 0.05 0.74 Zooplankton 0.05 

Benthic invertebrates 0.57 0.243 0.115 0.483 0.591 0.774 0.599 0.75 0.676 0.678 0.5 (default) 0.33 (default) 0.12 0.77 Benthic filter feeders Prey item 

warmwat

Detritus 0.042 0.004 0.09 0.378 0.022 0.037 0.052 0 0.38 Benthic detritivores 0 Fish ID ID 0.5 (default) 0.045 0.05 0.15 Small benthivores Small zooplanktivores These sm

small wa

1 Fish species represented by the raw data: banded killifish, brook silverside, golden shiner, brook stickleback, Eastern mosquitofish

central mudminnow. Bolded values indicate those minima and maxima selected as part of the range.
Section 11.0 Aquatic Food Web Data

11-17

This example further illustrates that, in some cases, dietary fraction data were available,

but the analogous prey item was not included in that particular waterbody. In the example, small

omnivores that may occur in warmwater ponds do consume fish in their diet; however, in the

aquatic food web, no other small fish has been assigned to this food web. Because the model

requires that a small fish cannot eat a larger fish, it is presumed that in the warmwater pond food

web the small omnivore will not eat fish. 

This example emphasizes the amount of professional judgment that was required to

derive some of the minimum and maximum prey preference data. Although a common weightof-evidence approach was used in most cases, there is uncertainty in the development of these

parameters based on the significant amount of professional judgment required for their

derivation.

After data were compiled into a format that met the prey categories of the aquatic food

web, several specific data requirements had to be met so that model errors would not occur. 

These requirements were considered important in setting the minimum and maximum prey

preferences for fish. If the raw data contradicted these requirements, a weight-of-evidence

approach had to be adopted that would conform data to meet these restrictions. 

# Dietary preferences of fish had to correspond with the largest fraction of the diet 

(e.g., zooplanktivores eat primarily zooplankton). This information was not

always reflected in the raw data when a fish category was not well-represented by

an array of different species.

# The minimum fraction could not exceed the maximum value for a given prey item

and fish category. 

# Maximums could not equal 0.

# None of the maximums used across the various prey items could be equal for a

fish category because the model ranks prey preferences in quantifying fish diets.

# Minimum dietary fractions, when added together across all prey items in a given

fish category, could not exceed 1.

# Omnivorous fish could not consume fish that were larger than themselves. 

Tables 11B-4 through 11B-19 in Appendix 11B provide the minimum and maximum prey

preferences for fish categories applied in the representative national data set. 

11.3.2.2 Database Processing. A significant amount of preprocessing was completed in

the fish attribute database, and this preprocessing was described for each parameter in the

database compilation section (Section 11.3.2.1). When deriving parameter metrics, the data were

formatted so that they could be used by the modeling system. The data were individually

dimensioned on different variables outlined in the module development. Two-dimensional

variables such as fish body weight, fraction lipid (whole body), muscle lipid, and T3 edible fish

were dimensioned on the biota type (e.g., T3 omnivore, T3 piscivore) and the aquatic food web
Section 11.0 Aquatic Food Web Data

11-18

(e.g., warmwater wetland, coldwater lake). Three-dimensional variables such as the minimum

and maximum prey preferences were dimensioned on the biota type, the aquatic food web, and

the prey type (i.e., synonymous with the biota type for the aquatic food web).

11.3.2.3 Assumptions and Uncertainties. Additional uncertainty discussions were

briefly mentioned in the methodology section for specific parameters; however, the key

assumptions and uncertainties associated with the development of the fish attribute database as a

whole can be grouped into the following general categories: default values and data gaps, fish

body weight uncertainty, and preprocessing assumptions. The critical issues within each

category are reviewed here.

Default Values and Data Gaps

Several default values were used for the parameters of lipid fraction (whole body and

muscle) and dietary prey preference. To derive a default lipid value, all lipid fractions across T3

and T4 fish, respectively, were independently averaged. This included all the lipid values

derived from the GLWQI (U.S. EPA, 1995a) document in addition to primary literature studies

identified during data collection efforts. When lipid data were not available for a fish category

in the aquatic food web, the default value for the lipid was applied. In the case of dietary

fractions, the description of what food items typically comprise fish diet varied substantially

across different sources. In some instances, no data were provided on the actual dietary fraction

- only the general components were known (e.g., aquatic plants, zooplankton, and benthos). In

these cases, the feeding guild to which the species was assigned (e.g., benthivore) was used to

inform professional judgement in selecting appropriate prey preferences. Applying default

values when data were not available to characterize the parameter introduces uncertainty into the

analysis. Because data gaps were evident across aquatic food web parameters, a level of

resolution in the analysis can be minimized or lost as more default values are applied. For

instance, the lipid content in fish will typically vary from warm- to coldwater habitats for some

fish. If default values are applied for medium benthivores in coldwater streams and medium

benthivores in warmwater streams, the variability in this parameter is not characterized.

The data gaps in the analysis limited the ability to characterize aquatic food web

parameters at the national scale. The parameters most limited by data gaps included fish body

weight, whole body lipid, and minimum/maximum prey preferences for fish. Because real

differences are noted in these parameters across different waterbodies and regions, the more data

that are identified to assess parameter distributions increases the resolution of the analysis. Data

limitations were probably the greatest uncertainty in the development of the aquatic food web

database. 

Fish Body Weight Uncertainty

Because a large portion of the fish body weight data was taken from the NAWQA

studies, any uncertainties associated with this database influence the uncertainty in the fish

attribute database. Some body weight data identified through the NAWQA appear to be low for

some species. The lower body weights reported could be due to any number of reasons. The

fish population sampled may have included juvenile fish. A review of the NAWQA biological

sampling method did not explicitly define fish collection by age. Further, many of the NAWQA
Section 11.0 Aquatic Food Web Data

11-19

sample sites were located in streams, ponds, and swamps, which larger fish may not inhabit as

frequently. These discrepancies may have resulted in a skewed body weight distribution toward

lower values. Applying these body weight values introduces some uncertainty into how well the

variability in body weights has been represented. 

Preprocessing Uncertainty

Uncertainty in the preprocessing effort was generated by the assumptions made when

data were insufficient to support a definitive decision. The decision criteria applied for each

preprocessing variable were explicitly stated. For instance, the assumptions associated with fish

water temperature preference were based on a weight-of-evidence approach when no water

temperature preference was reported for a fish species. In these cases, temperature

measurements taken at multiple sampling locations across different regions and drainage basins

were assessed for the maximum average annual temperatures. If a fish species was found

predominantly in regions where the temperature exceeded 25 oC, then the fish was presumed to

be warmwater. There is some uncertainty associated with these assignments because a fish

assigned as warmwater could possibly tolerate both cold and warm surface water temperatures. 

Because this database was developed to delineate preferences if they exist (not absolutes), the

weight-of-evidence approach was appropriate in spite of its limitations. Other assumptions and

professional judgments used in the preprocessing effort were outlined within the preprocessing

parameter discussions (Section 11.3.2.1). Assumptions also were made about trophic level,

relative size, and habitat preferences. Each decision framework applied influenced how the data

were categorized and manipulated. These assumptions cumulatively introduced uncertainty into

the resulting fish attribute database. 

11.4 Quality Assurance/Quality Control

11.4.1 Technical QA/QC

Data were compiled for the aquatic food web from extant databases developed by EPA

and other government agencies and programs. The use of highly reviewed sources and

scientifically accepted methods in the development of a database creates a high level of

confidence in the technical quality assurance/quality control (QA/QC) of the database. Studies

included in the chemical properties and fish attribute databases met specific criteria before they

were incorporated into the respective databases. For instance, the AQUIRE database (U.S. EPA,

1999a) reports a confidence rank for each study included in the database. The confidence rank

was based on the experimental methods that were used in the study. Studies assigned with a low

confidence rank were not included in the chemical-specific database. Upon compiling the data, a

QA/QC check of technical agreeability was performed by appropriate staff to judge whether the

numbers were technically defensible and that the assumptions and selection of default values

were reasonable. 

11.4.2 Data Entry QA/QC

Data entry was performed by both hardcopy data entry and database downloading from

Internet sites. When data were entered from hardcopy, manual review of the data input was

conducted. When data were downloaded from the Internet, a review of column headers and a
Section 11.0 Aquatic Food Web Data

11-20

partial random QA/QC check of approximately 10 percent of the values were conducted. The

databases downloaded from the Internet were manipulated both in form and report. Databases

that were downloaded typically reported values over several years and had to be condensed into

summary statistics. The conversion of these data was checked for proper statistical

manipulation.

11.4.3 Data Formatting

Manual QA/QC checks were conducted to identify errors that may have occurred during

data formatting efforts. Approximately 10 percent of the values were checked to ensure

formatting for the modeling system did not change or shift values. 

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(Ecological Assessment Unit) and Water Quality Section, Columbus, OH. Website at

http://chagrin.epa.state.oh.us/document_index/psdindx.html

http://chagrin.epa.state.oh.us/document_index/psdindx.html. April 14.

Page, Lawrence M., and Brooks M. Burr. 1991. A field guide to freshwater fishes. North

America, north of Mexico. In: The Peterson Field Guide Series. R.T.Peterson (ed.).

Houghton Mifflin Company, Boston, MA.

Sample, B. E., D. M. Opresko, and G. W. Suter II. 1996. Toxicological Benchmarks for 

Wildlife: 1996 Revision. ES/ER/TM-86/R3. Office of Environmental Management, U.S.

Department of Energy. Health Sciences Research Division, Oak Ridge National

Laboratory Risk Assessment Program, Oak Ridge, TN. June.

Simon, Thomas P. (ed.). 1999. Assessing the Sustainability and Biological Integrity of Water

Resources Using Fish Communities. CRC Press, Boca Raton, FL.

Smith, C. Lavett. 1994. Fish Watching: An Outdoor Guide to Freshwater Fishes. Cornell

University Press, Ithaca, NY.

Stephan, C. E. 1993. Derivation of Proposed Human Health and Wildlife Bioaccumulation

Factors for the Great Lakes Initiative. Environmental Research Laboratory, Office of

Research and Development, U.S. Environmental Protection Agency, Duluth, MN. March.

Sternberg, Dick. 1996. Freshwater Gamefish of North America. Cowles Creative Publishing,

Inc., Minnetonka, Minnesota.

U.S. DOI, and U.S. DOC (Department of the Interior; Department of Commerce). 1997. 1996

National Survey of Fishing, Hunting, and Wildlife-Associated Recreation. FHW/96 NAT.

U.S. Department of the Interior; U.S. Department of Commerce, Fish and Wildlife
Section 11.0 Aquatic Food Web Data

11-24

Service; Bureau of the Census, Washington, DC. Website at

http://www.nctc.fws.gov/library/pubs3.html. November.

U.S. EPA (Environmental Protection Agency). 1993a. Wildlife Exposure Factors Handbook.

Volumes I and II. EPA/600/R-93/187. U.S. Environmental Protection Agency, Office of

Health and Environmental Assessment and Office of Research and Development,

Washington, DC. December.

U.S. EPA (Environmental Protection Agency). 1993b. Interim Report on Data and Methods

for Assessment of 2,3,7,8-Tetrachlorodibenzo-p-dioxin Risks to Aquatic Life and

Associated Wildlife. EPA/600/R-93/055. U.S. Environmental Protection Agency, Office

of Research and Development, Washington, DC. March.

U.S. EPA (Environmental Protection Agency). 1995a. Great Lakes Water Quality Initiative

Criteria Documents for the Protection of Wildlife: DDT, Mercury, 2,3,7,8-TCDD, and

PCBs. EPA-820-B-95-008. U.S. Environmental Protection Agency, Office of Water,

Washington, DC. March.

U.S. EPA (Environmental Protection Agency). 1995b. Trophic Level and Exposure Analyes for

Selected Piscivorous Birds and Mammals. Volume I: Analyses of Species in the Great

Lakes Basin; Volume II: Analyses of Species in the Conterminous United States; Volume

III: Appendices. U.S. Environmental Protection Agency, Office of Science and

Technology, Office of Water, Washington, DC. March.

U.S. EPA (Environmental Protection Agency). 1995c. Great Lakes Water Quality Initiative

Technical Support Document for the Procedure to Determine Bioaccumulation Factors.

EPA-820-B-95-005. U.S. Environmental Protection Agency, Office of Water,

Washington, DC. March.

U.S. EPA (Environmental Protection Agency). 1995d. Great Lakes Water Quality Initiative

Criteria Documents for the Protection of Wildlife: DDT, Mercury 2,3,7,8-TCDD, and

PCBs. EPA-820-B-95-008. Office of Water, Washington, DC. March. 

U.S. EPA (Environmental Protection Agency). 1997a. Exposure Factors Handbook.

EPA/600/P-95/002Fa. U.S. Environmental Protection Agency, Office of Research and

Development, Washington, DC. August.

U.S. EPA (Environmental Protection Agency). 1997b. Mercury Study Report to Congress.

Volumes I - VIII. EPA 452/R-97/003. U.S. Environmental Protection Agency, Office of

Air Quality Planning and Standards and Office of Research and Development,

Washington, DC. Website at http://www.epa.gov/ttn/uatw/112nmerc/mercury.html.

December.

U.S. EPA (Environmental Protection Agency). 1999a. ECOTOX (ECOlogical TOXicity

Database). National Health and Environmental Effects Research Laboratory, MidContinent Ecology Division and Western Ecology Division, Duluth, MN. Website at

http://www.epa.gov/medecotx/. January 28.
Section 11.0 Aquatic Food Web Data

11-25

U.S. EPA (Environmental Protection Agency). 1999b. Aquatic Food Web Module. Background

and Implementation for the Multimedia, Multipathway, and Multireceptor Risk

Assessment (3MRA) for HWIR99. (Draft Report). U.S. Environmental Protection Agency,

October.

USGS (U.S. Geological Survey). 1998a. National Ambient Water Quality Assessment

(NAWQA) Program: South Platte River Basin. Website at

http://www/webserver.cr.usgs.gov/nawqa/splt/datarep/biosites/BIO.html.

USGS (U.S. Geological Survey). 1998b. National Ambient Water Quality Assessment 

(NAWQA) Program: Lake Erie-Lake St. Clair Drainage. Website at http://wwwoh.er.usgs.gov/nawqa/activities.html.

USGS (U.S. Geological Survey). 1998c. National Ambient Water Quality Assessment 

(NAWQA) Program: Albemarle Pamlico Drainage. Website at

http://sgi1dncrlg.er.usgs.gov/albe-html/ALBEdata.html.

USGS (U.S. Geological Survey). 1998d. National Ambient Water Quality Assessment 

(NAWQA) Program: San Joaquin-Tulare. Website at

http://water.wr.usgs.gov/sanj_nawqa/data_ae.html.

USGS (U.S. Geological Survey). 1998e. National Ambient Water Quality Assessment 

(NAWQA) Program: Upper Snake River Basin. Website at

http://wwwidaho.wr.usgs.gov/nawqa/data/archive.html.
Section 11.0 Aquatic Food Web Data

11-26

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Appendix 11A Parameter Values Applied for the Aquatic Food Web Chemical Properties Database

11-27

Appendix 11A

Parameter Values Applied for the Aquatic Food

Web Chemical Properties Database

Table 11A-1. Scalar Parameters Used in the Chemical Properties Database . . . . . . . . . . . . 11-29

Table 11A-2. Bioaccumulation Factors Identified for Aquatic Food Web Prey Items . . . . 11-30
Appendix 11A Parameter Values Applied for the Aquatic Food Web Chemical Properties Database

11-28

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Appendix 11A Parameter Values Applied for the Aquatic Food Web Chemical Properties Database

11-29

Table 11A-1. Scalar Parameters Used in the Chemical Properties Database

Variable Name Units Central Tendency

a_mus unitless 0.69

b_mus unitless 0.92

c_mus unitless 0.76

a_fish unitless 0.74

b_fish unitless 1

c_fish unitless 0.72
11-30

Table 11A-2. Bioaccumulation Factors Identified for Aquatic Food Web Prey Items Chemical Name Chemical CAS ID Number BAF Aquatic Macrophytes (L/kg plant tissue)a,b BSAF Aquatic Macrophytes (kg/kg plant tissue)a Aquatic Macrophyles Reference BAF Benthic Filter Feeders (L/kg benthos)a,b BSAF Bent

Filter Feeders (kg/kg benth

Acetonitrile 75-05-8 no data no data NA for organics no data no data Acrylonitrile 107-13-1 no data no data NA for organics no data no data Aniline 62-53-3 no data no data NA for organics no data no data Antimony 7440-36-0 no data no data default value no data no data Arsenic 7440-38-2 no data no data default value no data no data Barium 7440-39-3 no data no data default value no data no data Benzene 71-43-2 no data no data NA for organics no data no data Benzo(a)pyrene 50-32-8 no data no data default value no data no data Beryllium 7440-41-7 no data no data default value no data no data Bis(2-ethylhexyl) phthalate 117-81-7 no data no data default value no data no data Cadmium 7440-43-9 17 no data Naqvi et al., 1993 no data no data Carbon disulfide 75-15-0 no data no data NA for organics no data no data Chlorobenzene 108-90-7 no data no data NA for organics no data no data Chloroform 67-66-3 no data no data NA for organics no data no data Chromium (total) 7440-47-3 no data no data default value no data no data Chromium III (insoluble salts) 16065-83-1 no data no data default value no data no data Chromium VI 18540-29-9 no data no data default value no data no data Dibenz(a,h)anthracene 53-70-3 no data no data default value no data no data 
11-31

Chemical Name Chemical CAS ID Number BAF Aquatic Macrophytes (L/kg plant tissue)a,b BSAF Aquatic Macrophytes (kg/kg plant tissue)a Aquatic Macrophyles Reference BAF Benthic Filter Feeders (L/kg benthos)a,b BSAF Bent

Filter Feeders (kg/kg benth

Table 11A-2. (continued) Dichlorophenoxyacetic acid, 2,4- (2,4-D) 94-75-7 no data no data NA for organics no data no data 

Ethylene dibromide 106-93-4 no data no data NA for organics no data no data Hexachloro-1,3-butadiene 87-68-3 no data no data NA for organics no data no data Lead 7439-92-1 42 no data Naqvi et al., 1993 no data no data Methyl mercury 7439-97-6m no data no data default value no data no data Mercury (elemental) 7439-97-6e no datad no datad NA no datad no datad 

Mercury (divalent) 7439-97-6 no datad no datad NA no datad no datad Methoxychlor 72-43-5 no data no data NA for organics no data no data Methyl ethyl ketone 78-93-3 no data no data NA for organics no data no data Methyl methacrylate 80-62-6 no data no data NA for organics no data no data Methylene chloride 75-09-2 no data no data NA for organics no data no data Nickel 7440-02-0 no data no data default value no data no data Nitrobenzene 98-95-3 no data no data NA for organics no data no data Pentachlorophenol 87-86-5 no data no data NA for organics no data no data Phenol 108-95-2 no data no data NA for organics no data no data Pyridine 110-86-1 no data no data NA for organics no data no data Selenium 7782-49-2 no data no data default value no data no data Silver 7440-22-4 no data no data default value no data no data 
11-32

Chemical Name Chemical CAS ID Number BAF Aquatic Macrophytes (L/kg plant tissue)a,b BSAF Aquatic Macrophytes (kg/kg plant tissue)a Aquatic Macrophyles Reference BAF Benthic Filter Feeders (L/kg benthos)a,b BSAF Bent

Filter Feeders (kg/kg benth

Table 11A-2. (continued) 2,3,7,8 TCDD 1746-01-6 no data no data NA for organics no data no data 

Tetrachloroethylene 127-18-4 no data no data NA for organics no data no data Thallium 7446-18-6 no data no data default value no data no data Thiram 137-26-8 no data no data NA for organics no data no data Toluene 108-88-3 no data no data NA for organics no data no data 1,1,1-Trichloroethane 71-55-6 no data no data NA for organics no data no data Trichloroethylene 79-01-6 no data no data default value no data no data Vanadium 7440-62-2 no data no data default value no data no data Vinyl chloride 75-01-4 no data no data NA for organics no data no data Zinc 7440-66-6 no data no data default value no data no data 
11-33

Table 11A-2. (continued) Chemical Name Chemical CAS ID Number T3 Fish Whole Body (L/kg)a,b T4 Fish Whole Body (L/kg)a,b T3 Fish Muscle (L/kg)a,b T4 Fish Muscle (L/kg)a,b 

Acetonitrile 75-05-8 no data no data no data no data NAcrylonitrile 107-13-1 no data no data no data no data NAniline 62-53-3 no data no data no data no data NAntimony 7440-36-0 0 0 0 0 SArsenic 7440-38-2 3.5 3.5 3.5 3.5 SBarium 7440-39-3 no data no data no data no data dBenzene 71-43-2 no data no data no data no data NBenzo(a)pyrene 50-32-8 no data no data no data no data dBeryllium 7440-41-7 19 19 19 19 SBis(2-ethylhexyl) phthalate 117-81-7 135 204 no data no data SCadmium 7440-43-9 265 265 no data no data KCarbon disulfide 75-15-0 no data no data no data no data NChlorobenzene 108-90-7 no data no data no data no data NChloroform 67-66-3 7 11 no data no data SChromium (total) 7440-47-3 no data no data 0.6 0.6 SChromium III (insoluble salts) 16065-83-1 no data no data 0.6 0.6 SChromium VI 18540-29-9 no data no data 0.6 0.6 S

Dibenz(a,h)anthracene 53-70-3 no data no data no data no data dDichlorophenoxyacetic acid, 2,4- (2,4-D) 94-75-7 no data no data no data no data N
11-34

Chemical Name Chemical CAS ID Number T3 Fish Whole Body (L/kg)a,b T4 Fish Whole Body (L/kg)a,b T3 Fish Muscle (L/kg)a,b T4 Fish Muscle (L/kg)a,b 

Table 11A-2. (continued) Ethylene dibromide 106-93-4 no data no data no data no data N

Hexachloro-1,3-butadiene 87-68-3 no data no data no data no data NLead 7439-92-1 46 46 46 46 SMethyl mercury 7439-97-6m no data no data 1,600,000c 6,800,000c U

Mercury (elemental) 7439-97-6e no datad no datad no datad no datad NMercury (divalent) 7439-97-6 no datad no datad no datad no datad NMethoxychlor 72-43-5 no data no data no data no data NMethyl ethyl ketone 78-93-3 no data no data no data no data NMethyl methacrylate 80-62-6 no data no data no data no data NMethylene chloride 75-09-2 no data no data no data no data NNickel 7440-02-0 0.8 0.8 0.8 0.8 SNitrobenzene 98-95-3 no data no data no data no data NPentachlorophenol 87-86-5 no data no data no data no data NPhenol 108-95-2 no data no data no data no data NPyridine 110-86-1 no data no data no data no data NSelenium 7782-49-2 485 1,692 485 1,692 LSilver 7440-22-4 0 0 0 0 B2,3,7,8 TCDD 1746-01-6 172,100 264,100 no data no data UTetrachloroethylene 127-18-4 no data no data no data no data NThallium 7446-18-6 no data no data no data no data d
11-35

Chemical Name Chemical CAS ID Number T3 Fish Whole Body (L/kg)a,b T4 Fish Whole Body (L/kg)a,b T3 Fish Muscle (L/kg)a,b T4 Fish Muscle (L/kg)a,b 

Table 11A-2. (continued) Thiram 137-26-8 no data no data no data no data N

Toluene 108-88-3 no data no data no data no data N1,1,1-Trichloroethane 71-55-6 no data no data no data no data NTrichloroethylene 79-01-6 no data no data no data no data NVanadium 7440-62-2 no data no data no data no data dVinyl chloride 75-01-4 no data no data no data no data NZinc 7440-66-6 354 354 354 354 M

a “No data” indicates that an empirical value was not used to calculate tissue concentration because: (1) suitable data were not identifie

to estimate chemical bioaccumulation in aquatic organisms. For organic chemicals and certain dioxin-like chemicals, the BAF values 

described in the Aquatic Food Web module documentation. For mercury, metals, and special chemicals, a default value of 1.0 was u

EPA is currently identifying additional data sources and developing methods to replace these default values. b BAFs are based on measured total water concentrations unless otherwise noted. c BAF based on measured, dissolved water concentration. d In the AFW, methylmercury is the only mercury species modeled.
11-36

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Appendix 11B Parameter Values Applied for the Aquatic Food Web Fish Attribute Database

11-37

Appendix 11B

Parameter Values Applied for the Aquatic Food

Web Fish Attribute Database

Table 11B-1. Scalar Parameters Used in the Fish Attribute Database . . . . . . . . . . . . . . . . 11-39

Table 11B-2. Lipid Fraction in Fish Muscle and Fillet Fraction Conversion Factors

Applied in the Fish Attribute Database . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-39

Table 11B-3. Fish Body Weight, Whole Body Lipid Fractions, and Edible T3 Fish Values

Applied in the Fish Attribute Database . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-40

Table 11B-4. Minimum Prey Preference Values Applied for Fish in Coldwater Streams . 11-45

Table 11B-5. Maximum Prey Preference Values Applied for Fish in Coldwater Streams . 11-46

Table 11B-6. Minimum Prey Preference Values Applied for Fish in Coldwater Wetlands 11-47

Table 11B-7. Maximum Prey Preference Values Applied for Fish in Coldwater Wetlands 11-48

Table 11B-8. Minimum Prey Preference Values Applied for Fish in Coldwater Ponds . . . 11-49

Table 11B-9. Maximum Prey Preference Values Applied for Fish in Coldwater Ponds . . 11-50

Table 11B-10. Minimum Prey Preference Values Applied for Fish in Coldwater Lakes . . . 11-51

Table 11B-11. Maximum Prey Preference Values Applied for Fish in Coldwater Lakes . . 11-52

Table 11B-12. Minimum Prey Preference Values Applied for Fish in Warmwater Streams 11-53

Table 11B-13. Maximum Prey Preference Values Applied for Fish in Warmwater Streams 11-54

Table 11B-14. Minimum Prey Preference Values Applied for Fish in Warmwater 

Wetlands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-55

Table 11B-15. Maximum Prey Preference Values Applied for Fish in Warmwater 

Wetlands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-56

Table 11B-16. Minimum Prey Preference Values Applied for Fish in Warmwater Ponds . . 11-57

Table 11B-17. Maximum Prey Preference Values Applied for Fish in Warmwater Ponds . 11-58

Table 11B-18. Minimum Prey Preference Values Applied for Fish in Warmwater Lakes . . 11-59

Table 11B-19. Maximum Prey Preference Values Applied for Fish in Warmwater Lakes . 11-60
Appendix 11B Parameter Values Applied for the Aquatic Food Web Fish Attribute Database

11-38

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Appendix 11B Parameter Values Applied for the Aquatic Food Web Fish Attribute Database

11-39

Table 11B-1. Scalar Parameters Used in the Fish Attribute Database

Variable Name Units Central Tendency

MusWaterFrac unitless 0.79

FishWaterFrac unitless 0.75

Table 11B-2. Lipid Fraction in Fish Muscle and Fillet Fraction Conversion Factors

Applied in the Fish Attribute Database

Biota Type Biota Type Index Lipid Fraction in Muscle Fillet Fraction

Periphyton 1 0 0

Phytoplankton 2 0 0

Aquatic macrophytes 3 0 0

Zooplankton 4 0 0

Benthic detrivores 5 0 0

Benthic filter feeders 6 0 0

T3benth_sm 7 0.0182 0.28

T3benth_med 8 0.0182 0.28

T3benth_lg 9 0.0182 0.28

T3zoop_sm 10 0.0182 0.28

T3zoop_med 11 0.0182 0.28

T3zoop_lg 12 0.0182 0.28

T3omni_sm 13 0.0182 0.28

T3omni_med 14 0.0182 0.28

T3omni_lg 15 0.0182 0.28

T4pisc 16 0.031 0.29
Appendix 11B Parameter Values Applied for the Aquatic Food Web Fish Attribute Database

11-40

Table 11B-3. Fish Body Weight, Whole Body Lipid Fractions, and Edible T3

Fish Values Applied in the Fish Attribute Database

Aquatic Food

Web Index Biota Type

Biota Type

Index

Fish Body

Weight

(kg)

Fish Lipid

Fraction

(Whole Body) T3 Edible Fish

1 periphyton 1 NA 0.01 0

1 phytoplankton 2 NA 0.01 0

1 aquatic macrophytes 3 NA 0.01 0

1 zooplankton 4 NA 0.05 0

1 benthic detrivores 5 NA 0.03 0

1 benthic filter feeders 6 NA 0.05 0

1 T3benth_sm 7 0.00 0.07 0

1 T3benth_med 8 0.01 0.07 0

1 T3benth_lg 9 0.15 0.07 0

1 T3zoop_sm 10 0.00 0.07 0

1 T3zoop_med 11 0.01 0.07 0

1 T3zoop_lg 12 0.04 0.07 0

1 T3omni_sm 13 0.01 0.07 0

1 T3omni_med 14 0.22 0.06 1

1 T3omni_lg 15 1.30 0.07 0

1 T4pisc 16 2.10 0.09 0

2 periphyton 1 NA 0.01 0

2 phytoplankton 2 NA 0.01 0

2 aquatic macrophytes 3 NA 0.01 0

2 zooplankton 4 NA 0.05 0

2 benthic detrivores 5 NA 0.03 0

2 benthic filter feeders 6 NA 0.05 0

2 T3benth_sm 7 0.00 0.07 0

2 T3benth_med 8 0.01 0.07 0

2 T3benth_lg 9 0.20 0.07 0

2 T3zoop_sm 10 0.00 0.07 0

2 T3zoop_med 11 0.01 0.06 0

(continued)
Table 11B-3. (continued)

Appendix 11B Parameter Values Applied for the Aquatic Food Web Fish Attribute Database

Aquatic Food

Web Index Biota Type

Biota Type

Index

Fish Body

Weight

(kg)

Fish Lipid

Fraction

(Whole Body) T3 Edible Fish

11-41

2 T3zoop_lg 12 0.02 0.07 0

2 T3omni_sm 13 0.00 0.07 0

2 T3omni_med 14 0.32 0.04 1

2 T3omni_lg 15 0.66 0.08 0

2 T4pisc 16 2.30 0.07 0

3 periphyton 1 NA 0.01 0

3 phytoplankton 2 NA 0.01 0

3 aquatic macrophytes 3 NA 0.01 0

3 zooplankton 4 NA 0.05 0

3 benthic detrivores 5 NA 0.03 0

3 benthic filter feeders 6 NA 0.05 0

3 T3benth_sm 7 0.00 0.07 0

3 T3benth_med 8 0.01 0.07 0

3 T3benth_lg 9 0.20 0.07 0

3 T3zoop_sm 10 0.00 0.07 0

3 T3zoop_med 11 0.01 0.06 0

3 T3zoop_lg 12 0.02 0.07 0

3 T3omni_sm 13 0.00 0.07 0

3 T3omni_med 14 0.32 0.04 1

3 T3omni_lg 15 0.66 0.08 0

3 T4pisc 16 2.10 0.07 0

4 periphyton 1 NA 0.01 0

4 phytoplankton 2 NA 0.01 0

4 aquatic macrophytes 3 NA 0.01 0

4 zooplankton 4 NA 0.05 0

4 benthic detrivores 5 NA 0.03 0

4 benthic filter feeders 6 NA 0.05 0

4 T3benth_sm 7 0.00 0.07 0

(continued)
Table 11B-3. (continued)

Appendix 11B Parameter Values Applied for the Aquatic Food Web Fish Attribute Database

Aquatic Food

Web Index Biota Type

Biota Type

Index

Fish Body

Weight

(kg)

Fish Lipid

Fraction

(Whole Body) T3 Edible Fish

11-42

4 T3benth_med 8 0.01 0.07 0

4 T3benth_lg 9 0.20 0.07 0

4 T3zoop_sm 10 0.00 0.07 0

4 T3zoop_med 11 0.01 0.06 0

4 T3zoop_lg 12 0.05 0.07 0

4 T3omni_sm 13 0.01 0.07 0

4 T3omni_med 14 0.22 0.06 0

4 T3omni_lg 15 1.30 0.07 1

4 T4pisc 16 3.00 0.10 0

5 periphyton 1 NA 0.01 0

5 phytoplankton 2 NA 0.01 0

5 aquatic macrophytes 3 NA 0.01 0

5 zooplankton 4 NA 0.05 0

5 benthic detrivores 5 NA 0.03 0

5 benthic filter feeders 6 NA 0.05 0

5 T3benth_sm 7 0.00 0.07 0

5 T3benth_med 8 0.02 0.07 0

5 T3benth_lg 9 0.31 0.07 0

5 T3zoop_sm 10 0.00 0.07 0

5 T3zoop_med 11 0.00 0.07 0

5 T3zoop_lg 12 0.03 0.06 0

5 T3omni_sm 13 0.01 0.07 0

5 T3omni_med 14 0.18 0.07 1

5 T3omni_lg 15 2.60 0.06 0

5 T4pisc 16 3.00 0.09 0

6 periphyton 1 NA 0.01 0

6 phytoplankton 2 NA 0.01 0

6 aquatic macrophytes 3 NA 0.01 0

(continued)
Table 11B-3. (continued)

Appendix 11B Parameter Values Applied for the Aquatic Food Web Fish Attribute Database

Aquatic Food

Web Index Biota Type

Biota Type

Index

Fish Body

Weight

(kg)

Fish Lipid

Fraction

(Whole Body) T3 Edible Fish

11-43

6 zooplankton 4 NA 0.05 0

6 benthic detrivores 5 NA 0.03 0

6 benthic filter feeders 6 NA 0.05 0

6 T3benth_sm 7 0.00 0.07 0

6 T3benth_med 8 0.00 0.07 0

6 T3benth_lg 9 0.25 0.07 0

6 T3zoop_sm 10 0.00 0.07 0

6 T3zoop_med 11 0.01 0.06 0

6 T3zoop_lg 12 0.08 0.06 0

6 T3omni_sm 13 0.00 0.07 0

6 T3omni_med 14 0.23 0.05 1

6 T3omni_lg 15 0.89 0.06 0

6 T4pisc 16 1.80 0.08 0

7 periphyton 1 NA 0.01 0

7 phytoplankton 2 NA 0.01 0

7 aquatic macrophytes 3 NA 0.01 0

7 zooplankton 4 NA 0.05 0

7 benthic detrivores 5 NA 0.03 0

7 benthic filter feeders 6 NA 0.05 0

7 T3benth_sm 7 0.00 0.07 0

7 T3benth_med 8 0.00 0.07 0

7 T3benth_lg 9 0.25 0.07 0

7 T3zoop_sm 10 0.00 0.07 0

7 T3zoop_med 11 0.01 0.06 1

7 T3zoop_lg 12 0.08 0.06 0

7 T3omni_sm 13 0.00 0.07 0

7 T3omni_med 14 0.19 0.07 0

7 T3omni_lg 15 0.78 0.06 1

(continued)
Table 11B-3. (continued)

Appendix 11B Parameter Values Applied for the Aquatic Food Web Fish Attribute Database

Aquatic Food

Web Index Biota Type

Biota Type

Index

Fish Body

Weight

(kg)

Fish Lipid

Fraction

(Whole Body) T3 Edible Fish

11-44

7 T4pisc 16 1.40 0.09 0

8 periphyton 1 NA 0.01 0

8 phytoplankton 2 NA 0.01 0

8 aquatic macrophytes 3 NA 0.01 0

8 zooplankton 4 NA 0.05 0

8 benthic detrivores 5 NA 0.03 0

8 benthic filter feeders 6 NA 0.05 0

8 T3benth_sm 7 0.00 0.06 0

8 T3benth_med 8 0.01 0.06 0

8 T3benth_lg 9 0.17 0.07 1

8 T3zoop_sm 10 0.00 0.07 0

8 T3zoop_med 11 0.01 0.06 0

8 T3zoop_lg 12 0.08 0.06 0

8 T3omni_sm 13 0.01 0.07 0

8 T3omni_med 14 0.21 0.07 1

8 T3omni_lg 15 0.96 0.06 1

8 T4pisc 16 3.20 0.09 0

NA = Not applicable.
11-45

Table 11B-4. Minimum Prey Preference Values Applied for Fish in Coldwater Stream

(An entry of -999 indicates that the food item is not consumed.) Biota Type Peri- phyton Phyto- plankton Aquatic Macro- phytes Zoo- plankton Benthic Detrivores and Detritis Benthic Filter Feeders Small T3 Benthivore Medium T3 Benthivore Large T3 Benthivore Small T3 Planktivore Medium T3 Planktivore Large T3 Planktivore Small T3 Omnivore 

1 2 3 0 5 6 7 8 -999 -999 -999 -999 -999 

Periphyton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Phytoplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Aquatic macrophytes -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Zooplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic detrivores -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic filter feeders -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_sm 0.2 -999 0.1 -999 0.06 0.2 -999 -999 -999 -999 -999 -999 -999 

T3benth_med 0.2 -999 0.1 -999 0.06 0.2 -999 -999 -999 -999 -999 -999 -999 

T3benth_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 

T3zoop_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 

T3zoop_med -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 

T3zoop_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 

T3omni_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3omni_med 0.01 -999 0.01 -999 0 0.3 0.02 0.25 -999 -999 -999 -999 -999 T3omni_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T4pisc 0 -999 0 -999 0 0 0.02 0.3 -999 -999 -999 -999 -999 
11-46

Table 11B-5. Maximum Prey Preference Values Applied for Fish in Coldwater Stream

(An entry of -999 indicates that the food item is not consumed.) Biota Type Peri- phyton Phyto- plankton Aquatic Macro- phytes Zoo- plankton Benthic Detrivores and Detritis Benthic Filter Feeders Small T3 Benthivore Medium T3 Benthivore Large T3 Benthivore Small T3 Planktivore Medium T3 Planktivore Large T3 Planktivore Small T3 Omnivore 

1 2 3 0 5 6 7 8 -999 -999 -999 -999 -999 

Periphyton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Phytoplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Aquatic macrophytes -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Zooplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic detrivores -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic filter feeders -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_sm 0.5 -999 0.25 -999 0.2 1 -999 -999 -999 -999 -999 -999 -999 

T3benth_med 0.27 -999 0.4 -999 0.3 1 -999 -999 -999 -999 -999 -999 -999 

T3benth_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 

T3zoop_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_med -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3omni_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3omni_med 0.2 -999 0.15 -999 0.17 1 0.16 0.7 -999 -999 -999 -999 -999 T3omni_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T4pisc 0.07 -999 0.08 -999 0.12 0.8 0.1 0.85 -999 -999 -999 -999 -999 
11-47

Table 11B-6. Minimum Prey Preference Values Applied for Fish in Coldwater Wetlan

(An entry of -999 indicates that the food item is not consumed.) Biota Type Peri- phyton Phyto- plankton Aquatic Macro- hytes Zoo- plankton Benthic Detrivores and Detritis Benthic Filter Feeders Small T3 Benthivore Medium T3 Benthivore Large T3 Benthivore Small T3 Planktivore Medium T3 Planktivore Large T3 Planktivore Small T3 Omnivore 

1 2 3 4 5 -999 -999 8 -999 -999 -999 -999 13 

Periphyton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Phytoplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Aquatic macrophytes -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Zooplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic detrivores -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic filter feeders -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_med 0 0 0 0.1 0.25 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_med -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3omni_sm 0.04 0.04 0.04 0.2 0.2 -999 -999 -999 -999 -999 -999 -999 -999 

T3omni_med 0.01 0.01 0.01 0.2 0.1 -999 -999 0 -999 -999 -999 -999 0.02 T3omni_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T4pisc 0 0 0 0.2 0.1 -999 -999 0.1 -999 -999 -999 -999 0.1 
11-48

Table 11B-7. Maximum Prey Preference Values Applied for Fish in Coldwater Wetlan

(An entry of -999 indicates that the food item is not consumed.) Biota Type Peri- phyton Phyto- plankton Aquatic Macro- phytes Zoo- plankton Benthic Detrivores and Detritis Benthic Filter Feeders Small T3 Benthivore Medium T3 Benthivore Large T3 Benthivore Small T3 Planktivore Medium T3 Planktivore Large T3 Planktivore Small T3 Omnivore 

1 2 3 4 5 -999 -999 8 -999 -999 -999 -999 13 

Periphyton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Phytoplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Aquatic macrophytes -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Zooplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic detrivores -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic filter feeders -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_med 0.05 0.15 0.1 0.5 1 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_med -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3omni_sm 0.1 0.05 0.15 0.35 0.7 -999 -999 -999 -999 -999 -999 -999 -999 

T3omni_med 0.12 0.1 0.13 0.9 0.8 -999 -999 0.05 -999 -999 -999 -999 0.2 T3omni_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T4pisc 0.01 0.04 0.03 0.8 0.85 -999 -999 0.95 -999 -999 -999 -999 0.3 
11-49

Table 11B-8. Minimum Prey Preference Values Applied for Fish in Coldwater Ponds (An entry of -999 indicates that the food item is not consumed.) Biota Type Peri- phyton Phyto- plankton Aquatic Macro- phytes Zoo- plankton Benthic Detrivores and Detritis Benthic Filter Feeders Small T3 Benthivore Medium T3 Benthivore Large T3 Benthivore Small T3 Planktivore Medium T3 Planktivore Large T3 Planktivore Small T3 Omnivore 

1 2 3 4 5 -999 -999 8 -999 10 -999 -999 13 

Periphyton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Phytoplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Aquatic macrophytes -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Zooplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic detrivores -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic filter feeders -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_med 0 0 0 0.1 0 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_sm 0.05 0 0.1 0.3 0 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_med -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3omni_sm 0.01 0.01 0.01 0.02 0.04 -999 -999 -999 -999 -999 -999 -999 -999 T3omni_med 0.01 0.01 0.01 0.2 0 -999 -999 0.05 -999 0.05 -999 -999 0.05 

T3omni_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T4pisc 0 0 0 0.02 0 -999 -999 0.1 -999 0.1 -999 -999 0.1 
11-50

Table 11B-9. Maximum Prey Preference Values Applied for Fish in Coldwater Ponds (An entry of -999 indicates that the food item is not consumed.) Biota Type Peri- phyton Phyto- plankton Aquatic Macro- phytes Zoo- plankton Benthic Detrivores and Detritis Benthic Filter Feeders Small T3 Benthivore Medium T3 Benthivore Large T3 Benthivore Small T3 Planktivore Medium T3 Planktivore Large T3 Planktivore Small T3 Omnivore 

1 2 3 4 5 -999 -999 8 -999 10 -999 -999 13 

Periphyton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Phytoplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Aquatic macrophytes -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Zooplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic detrivores -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic filter feeders -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_med 0.2 0.05 0.1 0.5 1 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_sm 0.15 0.05 0.3 0.9 0.6 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_med -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3omni_sm 0.06 0.04 0.1 0.35 0.7 -999 -999 -999 -999 -999 -999 -999 -999 T3omni_med 0.12 0.1 0.13 0.9 0.8 -999 -999 0.11 -999 0.35 -999 -999 0.4 

T3omni_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T4pisc 0.01 0.04 0.03 0.8 0.85 -999 -999 0.5 -999 0.86 -999 -999 0.9 
11-51

Table 11B-10. Minimum Prey Preference Values Applied for Fish in Coldwater Lake

(An entry of -999 indicates that the food item is not consumed.) Biota Type Peri- phyton Phyto- plankton Aquatic Macro- phytes Zoo- plankton Benthic Detrivores and Detritis Benthic Filter Feeders Small T3 Benthivore Medium T3 Benthivore Large T3 Benthivore Small T3 Planktivore Medium T3 Planktivore Large T3 Planktivore Small T3 Omnivore 

1 2 3 4 5 6 -999 8 -999 -999 11 -999 13 

Periphyton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Phytoplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Aquatic macrophytes -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Zooplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic detrivores -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic filter feeders -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_med 0 0 0 0.1 0 0.25 -999 -999 -999 -999 -999 -999 -999 T3benth_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_med 0 0 0 0.5 0 0 -999 -999 -999 -999 -999 -999 -999 T3zoop_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3omni_sm 0.04 0.04 0.04 0 0.02 0.48 -999 -999 -999 -999 -999 -999 -999 T3omni_med -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3omni_lg 0.01 0.01 0.01 0.07 0.02 0 -999 0.03 -999 -999 0.03 -999 0.03 

T4pisc 0 0 0 0.1 0 0.15 -999 0.1 -999 -999 0.1 -999 0.1 
11-52

Table 11B-11. Maximum Prey Preference Values Applied for Fish in Coldwater Lake

(An entry of -999 indicates that the food item is not consumed.) Biota Type Peri- phyton Phyto- plankton Aquatic Macro- phytes Zoo- plankton Benthic Detrivores and Detritis Benthic Filter Feeders Small T3 Benthivore Medium T3 Benthivore Large T3 Benthivore Small T3 Planktivore Medium T3 Planktivore Large T3 Planktivore Small T3 Omnivore 

1 2 3 4 5 6 -999 8 -999 -999 11 -999 13 

Periphyton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Phytoplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Aquatic macrophytes -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Zooplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic detrivores -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic filter feeders -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_med 0.2 0.05 0.1 0.5 0.25 1 -999 -999 -999 -999 -999 -999 -999 T3benth_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_med 0.03 0.2 0.1 1 0.01 0.11 -999 -999 -999 -999 -999 -999 -999 T3zoop_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3omni_sm 0.03 0.12 0.05 0.35 0.1 1 -999 -999 -999 -999 -999 -999 -999 T3omni_med -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3omni_lg 0.06 0.2 0.1 0.9 0.92 0.75 -999 0.12 -999 -999 0.11 -999 0.09 

T4pisc 0.01 0.04 0.03 0.7 0.12 0.75 -999 0.85 -999 -999 0.9 -999 0.8 
11-53

Table 11B-12. Minimum Prey Preference Values Applied for Fish in Warmwater Strea

(An entry of -999 indicates that the food item is not consumed.) Biota Type Peri- phyton Phyto- plankton Aquatic Macro- phytes Zoo- plankton Benthic Detrivores and Detritis Benthic Filter Feeders Small T3 Benthivore Medium T3 Benthivore Large T3 Benthivore Small T3 Planktivore Medium T3 Planktivore Large T3 Planktivore Small T3 Omnivore 

1 -999 3 -999 5 6 7 8 -999 -999 -999 -999 -999 

Periphyton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Phytoplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Aquatic macrophytes -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Zooplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic detrivores -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic filter feeders -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_sm 0.07 -999 0.07 -999 0.03 0.63 -999 -999 -999 -999 -999 -999 -999 T3benth_med 0.015 -999 0.015 -999 0.01 0.2 -999 -999 -999 -999 -999 -999 -999 T3benth_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_med -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3omni_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3omni_med 0.01 -999 0.01 -999 0.1 0.2 0 0.05 -999 -999 -999 -999 -999 

T3omni_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T4pisc 0 -999 0 -999 0.05 0.05 0.01 0.1 -999 -999 -999 -999 -999 
11-54

Table 11B-13. Maximum Prey Preference Values Applied for Fish in Warmwater Strea

(An entry of -999 indicates that the food item is not consumed.) Biota Type Peri- phyton Phyto- plankton Aquatic Macro- phytes Zoo- plankton Benthic Detrivores and Detritis Benthic Filter Feeders Small T3 Benthivore Medium T3 Benthivore Large T3 Benthivore Small T3 Planktivore Medium T3 Planktivore Large T3 Planktivore Small T3 Omnivore 

1 -999 3 -999 5 6 7 8 -999 -999 -999 -999 -999 

Periphyton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Phytoplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Aquatic macrophytes -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Zooplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic detrivores -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic filter feeders -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_sm 0.25 -999 0.2 -999 0.24 1 -999 -999 -999 -999 -999 -999 -999 

T3benth_med 0.4 -999 0.3 -999 0.65 1 -999 -999 -999 -999 -999 -999 -999 

T3benth_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_med -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3omni_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3omni_med 0.45 -999 0.35 -999 0.87 1 0.11 0.8 -999 -999 -999 -999 -999 

T3omni_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T4pisc 0.4 -999 0.3 -999 0.85 0.9 0.21 0.95 -999 -999 -999 -999 -999 
11-55

Table 11B-14. Minimum Prey Preference Values Applied for Fish in Warmwater Wetla

(An entry of -999 indicates that the food item is not consumed.) Biota Type Peri- phyton Phyto- plankton Aquatic Macro- phytes Zoo- plankton Benthic Detrivores and Detritis Benthic Filter Feeders Small T3 Benthivore Medium T3 Benthivore Large T3 Benthivore Small T3 Planktivore Medium T3 Planktivore Large T3 Planktivore Small T3 Omnivore 

1 2 3 4 5 -999 -999 8 -999 -999 -999 -999 13 

Periphyton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Phytoplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Aquatic macrophytes -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Zooplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic detrivores -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic filter feeders -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_med 0.05 0.01 0.1 0.07 0.4 -999 -999 -999 -999 -999 -999 -999 -999 

T3benth_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 

T3zoop_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 

T3zoop_med -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 

T3zoop_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 

T3omni_sm 0.04 0.02 0.08 0.05 0.12 -999 -999 -999 -999 -999 -999 -999 -999 

T3omni_med 0.01 0.01 0.01 0.04 0.14 -999 -999 0 -999 -999 -999 -999 0 

T3omni_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 

T4pisc 0.01 0.01 0.01 0.1 0.2 -999 -999 0.22 -999 -999 -999 -999 0.08 
11-56

Table 11B-15. Maximum Prey Preference Values Applied for Fish in Warmwater Wetla

(An entry of -999 indicates that the food item is not consumed.) Biota Type Peri- phyton Phyto- plankton Aquatic Macro- phytes Zoo- plankton Benthic Detrivores and Detritis Benthic Filter Feeders Small T3 Benthivore Medium T3 Benthivore Large T3 Benthivore Small T3 Planktivore Medium T3 Planktivore Large T3 Planktivore Small T3 Omnivore 

1 2 3 4 5 -999 -999 8 -999 -999 -999 -999 13 

Periphyton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Phytoplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Aquatic macrophytes -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Zooplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic detrivores -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic filter feeders -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_med 0.15 0.1 0.3 0.52 1 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_med -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 

T3omni_sm 0.09 0.06 0.15 0.74 0.68 -999 -999 -999 -999 -999 -999 -999 -999 

T3omni_med 0.2 0.1 0.5 0.9 1 -999 -999 0.07 -999 -999 -999 -999 0.02 

T3omni_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 

T4pisc 0.06 0.03 0.09 0.8 0.68 -999 -999 0.9 -999 -999 -999 -999 0.5 
11-57

Table 11B-16. Minimum Prey Preference Values Applied for Fish in Warmwater Pond

(An entry of -999 indicates that the food item is not consumed.) Biota Type Peri- phyton Phyto- plankton Aquatic Macro- phytes Zoo- plankton Benthic Detrivores and Detritis Benthic Filter Feeders Small T3 Benthivore Medium T3 Benthivore Large T3 Benthivore Small T3 Planktivore Medium T3 Planktivore Large T3 Planktivore Small T3 Omnivore 

1 2 3 4 5 -999 -999 8 -999 -999 11 -999 13 

Periphyton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Phytoplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Aquatic macrophytes -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Zooplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic detrivores -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic filter feeders -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_med 0.08 0.08 0.08 0.07 0.06 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_med 0 0 0 0.5 0.01 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3omni_sm 0.01 0.01 0.01 0.05 0.12 -999 -999 -999 -999 -999 -999 -999 -999 

T3omni_med -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3omni_lg 0.02 0.02 0.02 0.04 0.05 -999 -999 0.03 -999 -999 0.03 -999 0 T4pisc -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 
11-58

Table 11B-17. Maximum Prey Preference Values Applied for Fish in Warmwater Pon

(An entry of -999 indicates that the food item is not consumed.) Biota Type Peri- phyton Phyto- plankton Aquatic Macro- phytes Zoo- plankton Benthic Detrivores and Detritis Benthic Filter Feeders Small T3 Benthivore Medium T3 Benthivore Large T3 Benthivore Small T3 Planktivore Medium T3 Planktivore Large T3 Planktivore Small T3 Omnivore 

1 2 3 4 5 -999 -999 8 -999 -999 11 -999 13 

Periphyton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Phytoplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Aquatic macrophytes -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Zooplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic detrivores -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic filter feeders -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_med 0.21 0.2 0.22 0.52 1 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_med 0.031 0.03 0.032 1 0.11 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_lg -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3omni_sm 0.1 0.05 0.15 0.74 0.77 -999 -999 -999 -999 -999 -999 -999 -999 T3omni_med -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3omni_lg 0.13 0.12 0.14 0.94 0.8 -999 -999 0.3 -999 -999 0.2 -999 0.07 

T4pisc -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 
11-59

Table 11B-18. Minimum Prey Preference Values Applied for Fish in Warmwater Lak

Biota Type Peri- phyton Phyto- plankton Aquatic Macro- phytes Zoo- plankton Benthic Detrivores and Detritis Benthic Filter Feeders Small T3 Benthivore Medium T3 Benthivore Large T3 Benthivore Small T3 Planktivore Medium T3 Planktivore Large T3 Planktivore Small T3 Omnivore 

1 2 3 4 5 6 7 -999 9 -999 -999 12 -999 

Periphyton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Phytoplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Aquatic macrophytes -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Zooplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic detrivores -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic filter feeders -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_sm 0.01 0.05 0.02 0 0.03 0.63 -999 -999 -999 -999 -999 -999 -999 T3benth_med -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_lg 0 0 0 0.02 0.01 0 -999 -999 -999 -999 -999 -999 -999 T3zoop_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_med -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_lg 0.03 0.03 0.03 0 0.04 0.5 -999 -999 -999 -999 -999 -999 -999 T3omni_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3omni_med 0.01 0.01 0.01 0 0 0 0 -999 -999 -999 -999 -999 -999 

T3omni_lg 0 0 0 0 0.02 0 0.01 -999 0.1 -999 -999 0.1 -999 

T4pisc 0 0 0 0.05 0 0.1 0.05 -999 0.2 -999 -999 0.15 -999 
11-60

Table 11B-19. Maximum Prey Preference Values Applied for Fish in Warmwater Lak

(An entry of -999 indicates that the food item is not consumed.) Biota Type Peri- phyton Phyto- plankton Aquatic Macro- phytes Zoo- plankton Benthic Detrivores and Detritis Benthic Filter Feeders Small T3 Benthivore Medium T3 Benthivore Large T3 Benthivore Small T3 Planktivore Medium T3 Planktivore Large T3 Planktivore Small T3 Omnivore 

1 2 3 4 5 6 7 -999 9 -999 -999 12 -999 

Periphyton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Phytoplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Aquatic macrophytes -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Zooplankton -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic detrivores -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 Benthic filter feeders -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_sm 0.05 0.12 0.1 0.58 0.24 1 -999 -999 -999 -999 -999 -999 -999 T3benth_med -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3benth_lg 0.1 0.25 0.12 0.99 0.96 1 -999 -999 -999 -999 -999 -999 -999 T3zoop_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_med -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3zoop_lg 0.05 0.2 0.1 1 0.5 0.91 -999 -999 -999 -999 -999 -999 -999 T3omni_sm -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 T3omni_med 0.2 0.3 0.25 0.95 0.87 1 0.4 -999 -999 -999 -999 -999 -999 

T3omni_lg 0.08 0.15 0.09 0.9 0.92 1 0.05 -999 0.5 -999 -999 0.45 -999 

T4pisc 0.06 0.08 0.07 0.75 0.15 0.8 0.1 -999 1 -999 -999 0.95 -999