U.S. Department of the Interior

U.S. Geological Survey

Open-File Report 2020–1098

Prepared in cooperation with the Montana Department of Environmental Quality

Understanding and Documenting the Scientific Basis of 

Selenium Ecological Protection in Support of Site-Specific 

Guidelines Development for Lake Koocanusa, Montana, 

U.S.A., and British Columbia, Canada
Cover. Photograph showing Libby Dam on the Kootenai River near Libby, Montana. Photograph by 

U.S. Army Corps of Engineers, Seattle District Public Affairs Office.
Understanding and Documenting the 

Scientific Basis of Selenium Ecological 

Protection in Support of Site-Specific 

Guidelines Development for Lake 

Koocanusa, Montana, U.S.A., and British 

Columbia, Canada

By Theresa S. Presser and David L. Naftz

Prepared in cooperation with the Montana Department of Environmental Quality

Open-File Report 2020–1098

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

DAVID BERNHARDT, Secretary

U.S. Geological Survey

James F. Reilly II, Director

U.S. Geological Survey, Reston, Virginia: 2020

For more information on the USGS—the Federal source for science about the Earth, its natural and living resources, 

natural hazards, and the environment—visit https://www.usgs.gov or call 1–888–ASK–USGS.

For an overview of USGS information products, including maps, imagery, and publications, visit 

https://store.usgs.gov/.

Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. 

Government.

Although this information product, for the most part, is in the public domain, it also may contain copyrighted materials 

as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner.

Suggested citation:

Presser, T.S., and Naftz, D.L., 2020, Understanding and documenting the scientific basis of selenium ecological 

protection in support of site-specific guidelines development for Lake Koocanusa, Montana, U.S.A., and British 

Columbia, Canada: U.S. Geological Survey Open-File Report 2020–1098, 40 p., https://doi.org/10.3133/ofr20201098.

Associated data for this publication:

Presser, T.S., and Naftz, D.L., 2020, Selenium concentrations in food webs of Lake Koocanusa in the vicinity of Libby 

Dam (MT) and the Elk River (BC) as the basis for applying ecosystem-scale modeling, 2008–2018: U.S. Geological 

Survey data release, https://doi.org/10.5066/P9VXYSNZ.

Presser, T.S., Naftz, D.L., and Jenni, K.E., 2018, USGS measurements of dissolved and suspended particulate material 

selenium in Lake Koocanusa in the vicinity of Libby Dam (MT), 2015–2017 (update): U.S. Geological Survey data 

release, https://doi.org/10.5066/P9HB5S5F.

ISSN 2331-1258 (online)
iii

Acknowledgments

This work was funded by the U.S. Geological Survey and the Montana Department of 

Environmental Quality. We thank the Federal, Provincial, and State agencies and Teck Coal Ltd., 

that monitor and contributed data to support this modeling effort within the binational study of 

Lake Koocanusa.

v

Contents

Acknowledgments........................................................................................................................................iii

Abstract...........................................................................................................................................................1

Introduction.....................................................................................................................................................2

Setting and Ecosystem..................................................................................................................................4

Overarching Federal and State Policies for Ecosystem Setting and Species .....................................9

Methods—Modeling, Contours, and Cross Sections ............................................................................10

Supporting Data—Scope of Studies and Study Area ...........................................................................13

Transboundary Metadata and Suspended Particulate Material Sampling .......................................20

A Lake-Gradient Approach to Support Modeling and Resulting Decisions on Data Reduction ....20

Data Utility for Modeling—Field Collection and Selenium Analysis of Invertebrates and Fish .....22

Influence of Ecosystem Characteristics on Selenium—Status of Ecosystems and Data 

Limitations for Modeling ...............................................................................................................24

Diet Component Analysis and Categorization of Fish Species ............................................................25

Modeling and Fish Scenario Development .............................................................................................25

Model Validation ..........................................................................................................................................26

Prediction of Protective Dissolved Selenium Concentrations—Invertebrate to Fish Model 

and Trophic-Level (Predatory to Forage) Fish Model ...............................................................28

Modeled Bioaccumulation Potentials for Lake Koocanusa .................................................................28

Illustrated Scenarios—Prediction of Protection for Westslope Cutthroat Trout, Rainbow 

Trout, Redside Shiner, Longnose Sucker, Bull Trout, and Burbot ...........................................29

Species-Specific TTFfish for Predator and Forage Fish .........................................................................29

Gradient Map Perspectives .......................................................................................................................29

Conclusions...................................................................................................................................................34

References Cited..........................................................................................................................................35

Appendix Supplementary References ..................................................................................................40

Figures

1. Study areas map of Lake Koocanusa showing locations of Libby Dam, the 

border between Montana and British Columbia, and the Elk River, which 

discharges selenium from five coal mines in British Columbia into the reservoir ............3

2. Graphs showing water-column selenium concentrations for sites on the Elk River ........5

3. Graph showing phytoplankton profiles at the forebay for 2014–17 ......................................6

4. Graph showing macrozooplankton profiles (150-micron net) for 2009–15 ..........................7

5. Graphs showing zooplankton densities for 2014–17 (63-micron net) ..................................8

6. Graphs showing percent composition of major fish species ................................................9

7. Ecosystem-scale selenium model methodology ...................................................................12

8. Map showing location of sites where water quality and (or) suspended 

particulate material samples were collected from Lake Koocanusa, Elk River, 

and the Kootenai River, Montana, and Kootenay River, British Columbia ........................13

9. Map showing location of sites where zooplankton samples were collected from 

Lake Koocanusa, Montana and British Columbia .................................................................14

10. Map showing location of sites where invertebrate samples were collected from 

Lake Koocanusa, Montana and British Columbia .................................................................15
vi

11. Maps showing location of sites where fish samples were collected from Lake 

Koocanusa ...................................................................................................................................16

12. Graphs showing depth-specific gradients across three reservoir monitoring 

sites in 2017..................................................................................................................................21

13. Graphs showing cross sections of dissolved selenium concentrations from 

monitoring sites on Lake Koocanusa during calendar year 2016 .......................................30

14. Graphs showing cross sections of dissolved selenium concentrations from 

monitoring sites on Lake Koocanusa during calendar year 2017 .......................................31

15. Graphs showing cross sections of dissolved selenium concentrations from 

monitoring sites on Lake Koocanusa during calendar year 2018 .......................................32

16. Graphs showing cross sections of dissolved selenium concentrations from 

monitoring sites on Lake Koocanusa during calendar year 2019 .......................................33

17. Graphs showing monthly cross-sectional areas in Lake Koocanusa specific to 

a dissolved selenium concentration of greater than 1 microgram per liter for 

2016–19 from the international boundary to Libby Dam and showing annual 

summation of monthly cross-sectional areas specific to a dissolved selenium 

concentration of greater than 1 microgram per liter ............................................................34

Tables

1. Fish traits, sampling details, and species-specific limiting factors .....................................7

2. Excerpts concerning ecotoxicology and fish tissue monitoring or 

tissue-to-tissue relationships ...................................................................................................23

3. Dietary percentage of biomass for diet of fish species .......................................................25

4. Categorization of fish species for modeling ...........................................................................25

5. Validation ranges of observed and predicted selenium concentrations in 

invertebrates ...............................................................................................................................26

6. Calculation of bioaccumulation potentials for the insect to fish model ............................28

7. Calculation of bioaccumulation potentials for the trophic fish model ...............................28

8. Spreadsheet scenarios and calculations for the insect to fish model using the 

complete dataset for Kd (USEPA, 2016a) .................................................................................29

9. Spreadsheet scenarios and calculations for the trophic fish model using 

complete dataset for Kd (USEPA, 2016a) .................................................................................29

10. Spreadsheet example of comparative scenarios using species-specific trophic 

transfer factors for fish species ...............................................................................................29
vii

Conversion Factors

U.S. customary units to International System of Units

Multiply By To obtain

Length

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

Area

square mile (mi2) 259.0 hectare (ha)

square mile (mi2) 2.590 square kilometer (km2)

Volume

acre-foot (acre-ft) 1,233 cubic meter (m3)

acre-foot (acre-ft) 0.001233 cubic hectometer (hm3)

International System of Units to U.S. customary units

Multiply By To obtain

Length

meter (m) 3.281 foot (ft)

meter (m) 1.094 yard (yd)

Area

square kilometer (km2) 247.1 acre

square kilometer (km2) 0.3861 square mile (mi2)

Flow rate

cubic meter per second (m3/s) 70.07 acre-foot per day (acre-ft/d)

Mass

kilogram (kg) 2.205 pound avoirdupois (lb)

Supplemental Information

Concentrations of chemical constituents in water are given in either micrograms per gram 

(μg/g) or micrograms per liter (μg/L).

A water year is the period from October 1 to September 30 and is designated by the year in 

which it ends; for example, water year 2019 was from October 1, 2018, to September 30, 2019.
viii

Abbreviations

> greater than

< less than

AE assimilation efficiency

BAP bioaccumulation potential

CF tissue-to-tissue conversion factor

dw dry weight

EC effect concentration or level of toxicity (for example, an EC10 is the toxicant 

concentration that causes a 10-percent effect in the endpoint of interest such as 

incidence of larval fish deformity in the case of selenium

ESA Endangered Species Act

GSI gonadosomatic index

IFM invertebrate to fish model

Kd environmental partitioning factor

MTDEQ Montana Department of Environmental Quality

MTFWP Montana Department of Fish, Wildlife and Parks

n number of samples

RG_DSELK downstream Elk River

SOE south of Elk

SPM suspended particulate material

TFM trophic-level (predator to forage) fish model

TL trophic level

TTF trophic transfer factor

USFWS U.S. Fish and Wildlife Service

USGS U.S. Geological Survey

wb whole body
Understanding and Documenting the Scientific Basis of 

Selenium Ecological Protection in Support of Site-Specific 

Guidelines Development for Lake Koocanusa, Montana, 

U.S.A., and British Columbia, Canada

By Theresa S. Presser and David L. Naftz

Abstract

Modeling of ecosystems is a part of the U.S. Environmental 

Protection Agency’s protocol for developing site-specific 

selenium guidelines for protection of aquatic life. Selenium as 

an environmental contaminant is known to bioaccumulate and 

cause reproductive effects in fish and wildlife. Here we apply a 

modeling methodology—ecosystem-scale selenium modeling—

to understand and document the scientific basis for predicting 

and validating ecological protection for Lake Koocanusa, a 

transboundary reservoir between Montana and British Columbia. 

A comprehensive set of site-specific data compiled from public 

databases (Federal, State, and Provincial) and reports by Teck Coal 

Ltd., is available in a companion U.S. Geological Survey data 

release. The tissue guideline used within modeling here to assess 

protection is the U.S. Environmental Protection Agency’s national 

selenium guideline for whole-body fish (dry weight); however, 

other numeric values for a whole-body guideline or other tissue 

types may be assumed if applicable tissue-to-tissue conversion 

factors are available.

We consider the report assembled here as a working 

document that presents a model that can effectively address and 

structure the needs of (1) scientific understanding in representing 

the lake’s ecosystem and selenium biodynamics and (2) policy 

and management development during a decision-making 

process, but it is open to modification and updating as more 

ecologically detailed data become available. The approach 

brings together the main concerns involved in selenium toxicity: 

likelihood of high exposure, inherent species sensitivity, and 

close connectivity of ecosystem characteristics and behavioral 

ecology of predators. Detailed site-specific modeling equations 

are provided to document the linked factors that determine 

the responses of ecosystems to selenium. A series of scenarios 

quantifies the implications of choices of site-specific variables 

including food-web species, bioavailability of particulate material, 

and partitioning between the dissolved and particulate phases at 

the base of food webs. A gradient mapping tool applied to Lake 

Koocanusa provides a precedent for ecosystem-scale modeling 

of lakes by recognizing the importance of lake strata and 

hydrodynamics as components of modeling.

Data requirements for ecosystem modeling, including 

ecological and hydrological process information fundamental 

to the dietary biodynamics of selenium in site-specific food 

webs, were assessed as a precursor to model validation for Lake 

Koocanusa. Understanding these relationships is necessary to 

connect modeling outcomes to reproductive effects and establish 

boundaries, in the case of Lake Koocanusa, for the influences of 

dam operation, fish-community viability, and its Clean Water Act 

impaired 303(d)-listing status on ecosystem function.

We find that an assemblage of conditions affects the 

representation of Lake Koocanusa’s ecosystem within 

modeling scenarios but that the constructed gradient maps, 

mechanistic model, and associated bioaccumulation potentials 

portray and quantify the variables that are determinative to 

protection of predator species. Ecological and hydrological 

sorting of compiled individual data points on a site- and 

species-specific basis helps identify and address model 

uncertainties. Sources of uncertainty include (1) the scarcity 

of data for some environmental media compartments across 

time and locations, (2) the complexity of hydrodynamic 

conditions that can lead to seasonal ecological disconnects 

such as in selenium partitioning from water into particulates, 

and (3) the functional status of Lake Koocanusa’s ecosystem 

because of cumulative effects of various environmental 

stresses (for example, fish-community changes, flow regime 

changes, parasites, gonadal dysfunction, and increasing mining 

input-selenium concentrations since 1984). To this last point, 

it is important to determine where Lake Koocanusa is in an 

impairment-restoration cycle so as not to base protection 

on survivor bias, the maintenance of a currently degraded 

ecosystem, or normalized toxicity. In a broader context, one 

of the overall consequences of revised selenium regulations is 

that their derivation is now dependent on being able to define 

and understand the status of the ecosystem on which protection 

is based.
2 Scientific Basis of Selenium Ecological Protection in Support of Site-Specific Guidelines Development

Introduction

The objective of this work is to document the scientific 

basis of selenium ecological protection in support of the 

development of selenium guidelines for Lake Koocanusa 

(fig. 1). Both the British Columbia Ministry of Environment 

and Climate Change Strategy (hereafter referred to as 

“BCMOE”) and the U.S. Environmental Protection Agency 

(hereafter referred to as “USEPA”) provide guidance for 

recently revised selenium regulations that recognizes the 

importance of linking the primacy of a fish tissue toxicity 

guideline with the practicality of a water-column guideline 

through a site-specific modeled ecosystem (BCMOE, 2014; 

USEPA, 2016a). The overall goal of this work is to provide an 

ecosystem-scale model that illustrates the site-specific range 

of potential selenium exposure and bioaccumulation that can 

inform the basis for regulatory decision-making by the State 

and the Province.

Explicit goals related to modeling as expressed at the 

conception of this work and embedded in a cooperative 

funding agreement between the U.S. Geological Survey 

(USGS) and the Montana Department of Environmental 

Quality (MTDEQ) are as follows:

• consideration of ecologically significant species and 

those important to stakeholders;

• protection of 100 percent of the fish species in the 

reservoir assuming a reproductive endpoint from 

reproductively mature females that are feeding in an 

ecosystem that functions as a lentic reservoir;

• long-term protection for fish in all parts of the reservoir 

during all phases of reservoir operation, all selenium 

loading profiles, and all water years (precipitation/

runoff scenarios);

• protection of ecosystems during maximum dietary 

selenium exposure (that is, feeding within a benthic 

food web); and

• protection of downstream uses including protection 

of the endangered Kootenai River Acipenser 

transmontanus (white sturgeon).

As a working document, the report integrates information, 

data, and graphs from the following:

• Teck Coal Ltd., Lake Koocanusa Monitoring Reports, 

2014–16 and 2018 (Teck Coal Ltd., 2018a, 2019);

• Lotic Environmental Ltd., Lake Koocanusa Food Webs 

(Baranowska and Robinson 2017; Baranowska, 2018);

• USGS data release (Presser and others, 2018;

https://doi.org/10.5066/P9HB5S5F) that includes data 

from sample collection in 2015–17 and a plan designed 

for ecosystem-scale selenium sample collection for 

Lake Koocanusa;

• a modeling methodology that is well documented 

in the literature (for example, Presser and Luoma, 

2010a); and

• a methodology for sampling and analysis of suspended 

particulate material (SPM) that was implemented 

specifically for Lake Koocanusa (Presser and 

others, 2018).

Presented here in support of modeling are the following:

• USGS data release (Presser and Naftz, 2020;

https://doi.org/10.5066/P9VXYSNZ) that is specific to 

the basis of ecosystem-scale selenium modeling;

• summary tables that characterize and justify site- and 

species-specific choices in model development;

• spreadsheets that show model scenarios and 

computations for validation of ecosystem selenium 

concentrations and prediction of protective dissolved 

selenium concentrations based on those scenarios;

• a series of lake contours or gradient maps for 2017 

showing observed dissolved and SPM selenium 

concentrations and calculated environmental 

partitioning factors (Kd values);

• observed dissolved selenium concentration cross 

sections specific to lake strata and location that address 

both north-to-south and depth selenium gradients for 

April–October (2016–19); and

• supplemental data that may help identify additional 

predator, contaminant, and stressor pathways in the 

future (Presser and Naftz, 2020).

Hence, there are a number of ways to build upon the structure 

and templates presented here as data-collection efforts go 

forward and model runs are needed to test the implications of 

additional site-specific variables.

This report is in answer to a specified need by 

MTDEQ and other stakeholders concerning the derivation 

of site-specific aquatic-life protection for Lake Koocanusa. 

That need was to model the ecosystem in terms of selenium 

dietary biodynamics and provide modeling spreadsheets as 

an interactive way for stakeholders to participate in scenario 

building within a decision analysis structure (Jenni and others, 

2017). The audience for this work is expected to be somewhat 

familiar with the environmental setting, regulatory issues, and 

the transboundary nature of the work. As such, this work cuts 

across Federal, State and Provincial boundaries and, hence, 

agency protocols. In this regard, terms such as criterion, 

standard, and guideline, which are specific to regulatory 

agencies cited in this report, are collectively referred to here 

as “guideline.” The guidelines cited are those recommended 

on a national basis by the USEPA through the Clean Water Act 

section 304(a) or on a Provincial basis by BCMOE (USEPA, 

2016a; BCMOE, 2014). For fish tissue, the whole-body (wb) 

selenium guidelines are as follows: USEPA, 8.5 micrograms 
Introduction 3

LAKE

KOOCANUSA

Kootenai River

Kootenay River

Elk River

Sand

Creek

Tobacco River

LAKE

KOOCANUSA

LAKE

KOOCANUSA

Elk River

Kootenai River

Tenmile

Creek

37

93

93

3

95

2

37

93

CANADA

UNITED STATES

BRITISH COLUMBIA

MONTANA

Libby

Rexford

Jaffray

Elko

LIBBY DAM

LIBBY DAM

USGS tailwater gage

(site 12301933)

Forebay

RG_DSELK

LK2 South

of Elk

Elk River

East Arm

Lake Koocanusa

upstream from Elk

Elk River at

Hwy 93 near Elko

Border

Lake Koocanusa 

near Tenmile Creek

115°40' 115°20' 115°0'

49°20'

49°0'

48°40'

0 10 20 MILES

0 10 20 KILOMETERS BRITISH COLUMBIA

MONTANA

Map area

EXPLANATION

Sampling location

Figure 1. Study areas map of Lake Koocanusa showing locations of Libby Dam, the border between Montana and British Columbia, 

and the Elk River, which discharges selenium from five coal mines in British Columbia into the reservoir (see figures 11A–F for all 

sampling locations).
4 Scientific Basis of Selenium Ecological Protection in Support of Site-Specific Guidelines Development

per gram dry weight (μg/g dw), and BCMOE, 4 μg/g dw. 

These regulatory guidelines and their derivation (for example, 

exposure-response curves) are not addressed here in any 

detail. However, it should be kept in mind when modeling 

that protection goals associated with these guidelines differ 

(for example, through application of an uncertainty factor; 

consideration of wildlife in addition to fish). The citations 

mentioned previously also document additional recommended 

national or Provincial water-column and diet guidelines for 

selenium that are used in this report.

Integration of available datasets within modeling for 

Lake Koocanusa was affected as we attempted to sort through 

fundamental landscape and ecosystem function alterations 

known to be caused by Libby Dam itself to establish sensitive 

locations and timing with which to inform regulatory and 

management actions. New sampling methods and tools 

also were implemented during the length of this project in 

response to ecosystem conditions assessed during our study. 

For example, collection of SPM, as the phase of particulate 

material most relevant to modeling of the base of food webs, 

was adapted for an oligotrophic lake setting of as much as 

315 feet (ft) of depth. Additionally, a gradient mapping tool 

was formulated and applied to spatially integrate the influence 

of variables such as hydrodynamics and selenium source 

inputs within the lake. The generated plots illustrate the type 

of conceptualization and quantification that is possible to 

support food-web modeling of lake settings in comparison to 

stream-network or estuarine systems (Presser, 2013; Presser 

and Luoma, 2013). Overall, some tolerance is needed to 

accept these interim efforts as they are meant, as a way to 

move forward when encountering unforeseen uncertainty in 

ecosystem functioning and health.

As part of future monitoring to support ecosystem-scale 

modeling and constrain uncertainty within regulatory and 

management actions, the USGS deployed a monitoring 

platform in August 2019 at the U.S. and Canada border 

(fig. 1). In addition to standard, hourly limnological profiles 

that can be viewed in near-real time, filtered water samples 

are collected on a daily time step from four depths and 

preserved for selenium analysis (USGS site 12300110; 

https://nwis.waterdata.usgs.gov/usa/nwis/qwdata/?site_no=

12300110). Similar equipment was deployed within the 

existing tailwater gaging station below Libby Dam (USGS site 

12301933; https://nwis.waterdata.usgs.gov/usa/nwis/qwdata/

?site_no=12301933). This station provides (1) coordinated 

monitoring for a second downstream location of the reservoir 

and (2) information on the variability of selenium inputs to the 

downstream lotic habitats of the Kootenai River. Hence, with 

the addition of these datasets in the future, the distribution of 

selenium concentrations with time and depth during varying 

hydrodynamic conditions (for example, spring freshet, fall 

turnover, density driven currents) can inform modeling 

scenarios.

Setting and Ecosystem

Lake Koocanusa is a transboundary reservoir between 

Montana and British Columbia created by the impoundment 

of the Kootenai River when Libby Dam was built in 1972 

(Bonneville Power Administration and others, 1995) (fig. 1). 

Its construction was authorized as part of a treaty between 

the United States and Canada for cooperative development of 

flood storage, hydroelectric power generation, and recreation 

within the Columbia River Basin. The drainage area captured 

by the dam is 8,985 square miles (mi2) and reservoir capacity 

is 6.0 million acre-feet (https://www.nwd-wc.usace.army.mil/

dd/common/projects/www/lib.html). The reservoir is 90 miles 

(mi) in length, with 48 mi on the Montana side and 42 mi 

on the British Columbia side. Full-pool elevation is 2,459 ft, 

with a maximum depth of 350 ft at the forebay (Easthouse, 

2013). Minimum pool is 2,287 ft, with drawdown occurring 

approximately from November to May (see also Presser 

and others, 2018, figs. 11, 13, 15). As part of the Columbia 

River Basin, many ecological studies were completed before 

and after impoundment. The status of the lake is currently 

monitored by (1) the U.S. Army Corps of Engineers for 

parameters critical to meeting management goals including 

flow, water quality, and productivity (https://www.nwdwc.usace.army.mil/ftppub/water_quality/tdg/#LBQM) 

and (2) the USGS for outflow (river discharge) from 

the dam (https://waterdata.usgs.gov/nwis/uv/?site_no=

12301933&agency_cd=USGS). Beginning in 2019, the USGS 

also monitors water quality and selenium concentrations at 

the international boundary (site number 12300110) and below 

Libby Dam (site number 12301933).

The Kootenai River drainage basin has its origin in British 

Columbia and is located within the Northern Rocky Mountain 

physiographic province (Woods and Falter, 1982). The basin 

lies within a latitude range of 48–51 degrees north, which is 

at the edge of the boreal (that is, high latitude) zone of climate 

classification. Lake Koocanusa’s Trophic State Index fluctuates 

between oligotrophic and mesotrophic. This index compares 

lakes according to their summer (June–September) biological 

productivity on a scale of 0–100. At the lower end of the 

scale (oligotrophic, less than [<] 40), a lake would have low 

productivity, high water clarity, and low nutrients.

The Fording River and Elk River watersheds (240 and 

1,718 mi2, respectively) of the Kootenai River Basin are the 

sources of selenium to Lake Koocanusa. Drainage from five 

surface coal mines is transported by these rivers under permits 

administered by the BCMOE (Teck Coal Ltd., 2014; BCMOE, 

2018). Mining of this mineral resource is through a technique 

similar to mountaintop removal that requires large-scale 

storage of selenium-enriched waste rock in valley drainages 

or open pits. Management of selenium risk is necessary 

once these waste rocks are exposed, oxidation to mobile 

selenate occurs, and the resulting leachate interfaces with the 

environment (Presser and others, 2004; Presser, 2013). Since 

1984, selenium concentrations in the Elk River measured 

at a station 2.2 mi above its discharge into Lake Koocanusa 
Setting and Ecosystem 5

(that is, at Highway 93) show a continuing increase as mines 

have expanded (https://www.canada.ca/en/environmentclimate-change/services/freshwater-quality-monitoring/

online-data.html) (fig. 2A). Selenium concentrations in the 

Elk River have exceeded BCMOE’s Provincial guideline 

of 2 micrograms per liter (μg/L) for protection of aquatic 

life (Nagpal and Howell, 2001; BCMOE, 2014) since 1993 

and the USEPA’s guideline of 3.1 μg/L for lotic waters 

(USEPA, 2016a) since 2002 on a seasonal basis. In terms 

of maxima, selenium concentrations at this site exceeded 

8 μg/L in February 2014 and April 2018. This upward trend 

has created a nonsteady state for dissolved selenium in the 

lake that the ecosystem is responding to throughout this 

35-year period. The USEPA (2016a) describes concerns about 

site-specific derivations under new input conditions that lead 

to nonsteady-state conditions and recommends a series of 

steps that involve investigating the dynamics of selenium 

bioaccumulation within such an ecosystem. Expansion of 

mining is ongoing, and management plans for selenium call 

for a doubling of the amount of waste-rock storage by 2023 

(Teck Coal Ltd., 2014).

A snapshot in 2014 of selenium concentrations farther 

downstream (1) in the Elk River at its mouth (fig. 1) shows a 

range of concentrations of 3.2–8.5 μg/L at the surface from 

January to December (fig. 2B) and (2) in the east arm (fig. 1), 

where the Elk River discharge enters into the reservoir, shows 

a range of 0.8–3.8 μg/L at different depths in May–November 

of 2014 (fig. 2C). A study in 2018 addressed riverine mixing 

within the reservoir during three pool conditions (low, 

intermediate, high). Specific conductance and temperature 

elucidated the density gradient from the river input to the 

order station (that is, permitted water-quality site; RG_DSELK 

[downstream Elk River]) at approximately 4.4 mi downstream 

(fig. 1) (Teck Coal Ltd., 2018b). The Elk River discharge is 

characterized by elevated specific conductance and cooler 

water temperatures compared to reservoir waters, thus setting 

up the potential for characteristic density-layering effects. 

Profiles of the east arm of the reservoir indicate that the Elk 

River waters were generally confined to bottom contours, 

but downstream mixing took place as river water rose to 

midcolumn. Confinement of river-water mixing to the 

eastern side of channelized flow also occurred until below 

RG_DSELK.

Lake Koocanusa’s highly modified hydrological and 

ecological systems contribute to the interpretation of how 

its ecosystems are functioning, especially here, in terms of 

the fundamental processing of selenium. In general, Lake 

Koocanusa has the traditional problems associated with dam 

management for power generation in that large elevation 

changes (for example, 140–170 ft below full pool) occur 

during drawdown and refilling operations (Bonneville Power 

Administration and others, 1995). A series of hydrographs 

illustrate the magnitude of these types of changes (that is, 

elevation, discharge) specific to Lake Koocanusa in 2015–17 

(Presser and others, 2018, figs. 11–16). An example of this 

type of disturbance specific to the species of the lake is that 

0

2

4

6

8

10

1980 1985 1990 1995 2000 2005 2010 2015 2020

Water-column selenium, in parts per billion

Date

A. Elk River at Highway 93, Aug. 1984 to Jan. 2019

0

2

4

6

8

10

Dissolved or total selenium, in parts per billion

Individual analysis

B. Mouth of the Elk River, 2014

Surface dissolved Surface total

Mar.

Feb.

Dec.

July

June

May

Apr. Nov.

Mar.

Oct.

Sep.

Jan. Feb.

Jan.

Apr.

May

Aug.

June

July

Aug.

Sep.

Oct.

Nov.

Dec.

0

2

4

6

8

10

Individual analysis

Dissolved or total selenium, in parts per billion

C. East arm, 2014

May

Nov. Nov.

Surface dissolved Surface total

Sep.

June June

Oct.

Sep.

July July

Aug. Aug.

May

Oct.

Figure 2. Water-column selenium concentrations for sites on the 

Elk River. A, for the Elk River at Highway 93 from 1984 to 2019; B, the 

mouth of the Elk River in 2014; C, the east arm in 2014.
6 Scientific Basis of Selenium Ecological Protection in Support of Site-Specific Guidelines Development

the spawning time of Lota lota (burbot) coincides with the 

timing of maximum drawdown in Lake Koocanusa (Teck Coal 

Ltd., 2015).

Given the variable retention and flushing times, residence 

time of water in the lake also varies. Woods (1982) calculated 

a range of annual hydraulic residence times of 1.7–7.5 months 

during initial conditions after dam construction (1972–80). 

Holderman and others (2009) cite 5.5 months based on a 

mean annual discharge of 440 cubic meters per second. The 

U.S. Army Corps of Engineers (Easthouse, 2013) cites a mean 

water residence time of approximately 9 months. Residence 

time profiles, if measured on a monthly time scale, could further 

elucidate a connection to lake productivity and, hence, ecosystem 

function (see later discussion, “Transboundary Metadata and 

Suspended Particulate Material Sampling” section).

Hauer and Stanford (1997) referred to the large-scale effects 

of river regulation on the ecology of the Kootenai River Basin as 

a functional reset of a river continuum. Impacts include decreases 

in (1) production of zooplankton and benthic invertebrates and 

(2) availability of terrestrial insects, especially when refill is not 

achieved (Bonneville Power Association and others, 1995, appendix K). Decreases in prey organisms can, in turn, lead to decreased 

fish growth. Impacts also affect the extent and quality of shoreline 

and littoral habitats, which can contribute to reduced nesting for 

birds and spawning areas for fish.

Phytoplankton and invertebrate densities (Presser and 

Naftz, 2020) elucidate shifts in taxa and provide measures 

of seasonal productivity for Lake Koocanusa (figs. 3–5). For 

example, diatoms dominated in 2014 and 2015 with a substantial 

shift to dominance by dinoflagellates in 2016 and 2017 (fig. 3). 

Yearly macrozooplankton (that is, excluding rotifers) densities 

(150-micron net) show dominance by the copepod Cyclops from 

2009 to 2015 (fig. 4; Dunnigan and others, 2017). Mean densities 

for that period show productivity peaks in May and August, but 

the most recent profile in 2015 shows a series of peaks occurring 

during May, July, August, and September. Zooplankton densities 

(63-micron net) at three reservoir locations show rotifers dominate 

most profiles as increases occur from the border location to sites 

farther downstream towards the forebay of the dam (fig. 5A, B, 

and C). Experimental data for farm-raised fish show rotifers to 

be a nonnutrient food, low in selenium (for example, Mæhre 

and others, 2012); therefore, dilution of selenium in a composite 

sample of zooplankton could take place if a large number of 

rotifers were present compared to other zooplankton taxa.

Abundance data for macroinvertebrates in Lake 

Koocanusa are less available. Chisholm and others (1989)

report large density peaks of aquatic macroinvertebrates 

in April–May, and to a lesser extent in August, based on 

a seasonal study of limnetic and nearshore habitats in 

1983–87. For terrestrial macroinvertebrates, a peak in 

August dominates the 1983–87 profile. Also for this period, 

the density of individual invertebrate taxa, in decreasing 

order, was Hymenoptera (ants), aquatic dipterans (midges), 

Homoptera (leafhoppers), Coleoptera (beetles), Hemiptera 

(corixids, aphids), and Arachnida (spiders, ticks, mites) 

(Richards, 1997).

Figure 3. Phytoplankton profiles at the forebay for 2014–17.

0

20

40

60

80

100

Phytoplankton density (63-micron net), as percent

2014 2015 2016 2017

Year (April through October)

Apr

Oct

Bluegreen

Chrysophyte

Cryptophyte

Diatom

Dinoflagellates

Euglenoid

Green

Forebay EXPLANATION
Setting and Ecosystem 7

Figure 4. Macrozooplankton profiles (150-micron net) for 2009–15.

Specific to Lake Koocanusa for fish-community 

fluctuations, Oncorhynchus mykiss (rainbow trout), 

Oncorhynchus clarki lewisi (Westslope cutthroat trout), and 

Prosopium williamsoni (mountain whitefish) all demonstrated 

substantial decreases in abundance after construction of 

the dam caused a habitat shift from riverine to lacustrine, 

whereas Mylocheilus caurinus (peamouth chub) and 

Ptychocheilus oregonensis (northern pikeminnow) (that is, 

smaller bodied fish) have gone from rare during predam 

conditions to abundant during postdam conditions (Dunnigan 

and others, 2017). During the period 1979–85, inadvertent 

introduction of nonnative Oncorhynchus nerka (kokanee), 

stocking of hatchery rainbow trout, and invasion by Perca 

flavescens (yellow perch) all have added to the disruption 

of fish-community profiles and of species composition of 

zooplankton and invertebrate food sources. In 1985, kokanee 

accounted for 96 percent of the number of fish harvested from 

the reservoir (Chisholm and Hamlin, 1987). The Montana 

Department of Fish, Wildlife and Parks (MTFWP) introduced 

rainbow trout to feed on kokanee with goals of (1) reducing 

the number of kokanee and thereby increasing the size of trout 

and (2) providing a trophy fishery as trout attained an ultimate 

large size. Kokanee are also an important food source for 

Salvelinus confluentus (bull trout) and burbot.

Species of fish currently monitored, their histories, 

and important traits and characteristics are listed in 

table 1 (available for download at https://doi.org/10.3133/

ofr20201098) and discussed in more detail later. Percentage 

composition of species in spring and fall from 2009 to 2016 is 

shown in figure 6A and B (Presser and Naftz, 2020). Peamouth 

chub, northern pikeminnow, and Catostomus macrocheilus

(largescale sucker) are dominant in spring, with the remaining 

species making up <10 percent of totals. In fall, peamouth 

chub, northern pikeminnow, and kokanee dominate, with the 

remaining species again making up <10 percent of totals. 

Tracking of hatchery rainbow trout shows few fish of the 

approximately 30,000 to 90,000 stocked per year since 2001 

are caught in nets (2.2 fish, mean) (Dunnigan and others, 2017, 

2020; Presser and Naftz, 2020), which leads to the supposition 

that hatchery fish do not thrive or recruit.

Mitigation of the effects of Libby Dam on the lake’s 

ecosystem is an ongoing effort since its construction in 1972. 

Focus in terms of fish is on (1) stream habitat enhancement or 

restoration; (2) removal of nonnative species; (3) protection 

of subwatersheds supporting native species; (4) assessment of 

burbot stock, restored natives, and hatchery fish (for example, 

hybridization between Westslope cutthroat trout and rainbow 

trout); and (5) increasing the productivity of fish populations 

0

2

4

6

8

10

12

14

2009 2010 2011 2012 2013 2014 2015

Yearly mean total macrozooplankton density (150-micron net), in number per liter

Year

2009–15 copepods and cladocerans

Leptodora

Bosmina

Daphnia

Diaphanosoma

Cyclops

Epischura

Diaptomus

EXPLANATION
8 Scientific Basis of Selenium Ecological Protection in Support of Site-Specific Guidelines Development

to help recruitment to adult stages (Dunnigan and others, 

2017). The Kootenai River below the dam (that is, tailwater 

fishery) benefits from entrainment of kokanee through the 

dam because the fish become food for the river’s population of 

rainbow trout; however, entrainment is detrimental to kokanee 

themselves.

Mitigation actions for minimizing the effects of Libby 

Dam operations that are temporal in nature include managing 

(1) downstream effects in the Kootenai River where the 

endangered white sturgeon and culturally sensitive burbot 

reside (for example, U.S. Fish and Wildlife Service [USFWS], 

1999; Idaho Department of Fish and Game, 2008) and 

(2) tributary habitats for spawning (Dunnigan and others, 

2017). Libby Dam has a selective withdrawal system that 

allows dam operators to mimic the natural annual temperature 

regime in the dam discharge in comparison to a traditional 

dam release of the hypolimnial layer (that is, bottom water). 

Hence, overall management of the Lake Koocanusa ecosystem 

is highly dependent on actions directed towards downstream 

mitigation.

The British Columbia side of Lake Koocanusa offers 

comparatively less elevation changes than the Montana 

side; hence, the ecological values of the northern reservoir 

shoreline (that is, foreshore as described here) areas for birds 

Figure 5. Zooplankton densities for 2014–17 (63-micron net). A, at the border; B, at Tenmile; C, at the forebay.

0

50

100

150

200

250

300

2014 2015 2016 2017

Apr. Oct.

0

50

100

150

200

250

300

Zooplankton density (63-micron net), in number per liter

2014 2015 2016 2017

Apr. Oct.

0

50

100

150

200

250

300

Year (April through October)

2014 2015 2016 2017

Apr. Oct.

Rotifer

Copepod

Cladoceran

A. Border

C. Forebay

B. Tenmile

Zooplankton density (63-micron net), in number per liter

Zooplankton density (63-micron net), in number per liter

EXPLANATION

Year (April through October) Year (April through October)
Overarching Federal and State Policies for Ecosystem Setting and Species 9

increase for such activities as foraging, migratory staging, 

and nesting/breeding (VAST Resource Solutions Inc., 2017). 

A list of recently observed birds for the British Columbia 

side foreshore areas includes species such as geese, grebes, 

loons, and mergansers and many migrating duck species 

(VAST Resource Solutions Inc., 2017, appendix C). A listing 

of bird species from eBird in 2016 for sites across the entire 

reservoir including Libby Dam (VAST Resource Solutions 

Inc., 2017, appendix D) shows an extensive array of aquatic, 

riparian, shore, and wetland species that are protected under 

the Migratory Bird Treaty Act.

The lake encompasses transboundary migratory routes 

and is a part of the Pacific Flyway. Northbound migration 

occurs from mid-April through mid-May. Southbound 

migration begins in mid-August for many shorebirds such as 

sandpipers, plovers, and dowitchers. Species that breed close 

to the lake’s shores are Actitis macularius (spotted sandpiper), 

Charadrius vociferus (killdeer), and Numenius americanus

(long-billed curlew). Upland wildlife that use the foreshore 

include songbirds (warblers, sparrows, flycatchers). Raptors 

utilizing the lake are Falco peregrinus (peregrine falcon), 

Haliaeetus leucocephalus (bald eagle), and Pandion haliaetus

(osprey). Zones of sensitivity include specific protection 

rationales: active nesting for bank swallow and long-billed 

curlew; and designated Wildlife Habitat Areas for Melanerpes 

lewis (Lewis’s woodpecker) and long-billed curlew (VAST 

Resource Solutions Inc., 2017). Selenium was analyzed in 

(1) spotted sandpiper eggs at the mouth of the Elk River in 

2013–14 and (2) killdeer eggs in 2016 (Presser and Naftz, 

2020). The maximum concentration in spotted sandpiper eggs 

was 8.4 μg/g dw (number of samples [n] =17), which exceeds 

the USFWS EC00 of 5.5 μg/g dw and EC10 of 7.7 μg/g dw for 

sensitive species (Presser and Luoma, 2010b). The maximum 

concentration in killdeer eggs was 3.7 μg/g dw (n=4).

Overarching Federal and State Policies 

for Ecosystem Setting and Species

The MTDEQ has identified Lake Koocanusa as 

threatened by selenium sources outside the State of Montana’s 

jurisdiction or borders and listed the water body as impaired 

under section 303(d) of the U.S. Clean Water Act in 2012 

(MTDEQ 303(d) list [MTDEQ, 2018]). The lake was 

identified as not fully supporting aquatic life as a beneficial 

use because of selenium, but also because of flow regime 

modifications. The current State regulation for selenium 

is through an aquatic-life standard of 5 μg/L (chronic) and 

20 μg/L (acute) (MTDEQ, 2019). For comparison, the current 

0

10

20

30

40

50

60

70

2009 2010 2011 2012 2013 2014 2015 2016

Species composition, in percent

Date

A. Spring 2009–16

0

10

20

30

40

50

60

2009 2010 2011 2012 2013 2014 2015 2016

Species composition, in percent

Date

B. Fall 2009–16

Peamouth chub

Kokanee

N pikeminnow

Largescale sucker

Mountain whitefish

Rainbow trout

Bull trout

Redside shiner

Westslope cutthroat trout

Longnose sucker

Yellow perch

EXPLANATION

Figure 6. Percent composition of major fish species. A, in spring 2009–16; B, in fall 2009–16.
10 Scientific Basis of Selenium Ecological Protection in Support of Site-Specific Guidelines Development

aquatic-life guidelines are 1.5 μg/L for lentic waters of the 

United States (USEPA, 2016a) and 2 μg/L for waters of 

British Columbia (Nagpal and Howell, 2001; BCMOE, 2014).

In the 303(d)-list assessment record for Lake Koocanusa, 

selenium loads were estimated to increase by an average 

of 376 kilograms per year (kg/yr) or 19.7 percent per year, 

with planned mine expansions and new mines adding to that 

trend in the future. Loads measured in 2017 in connection 

with British Columbia’s permit monitoring show a total input 

of 10,398 kg/yr based on monthly selenium concentrations 

at the mouth of the Elk River and extrapolated daily flow 

measurements (Teck Coal Ltd., 2018b). The two highest 

monthly inputs are approximately 2,400 kilograms during 

May and June. Establishment of a total maximum daily load 

as part of State regulatory actions is required, but the status of 

attainment is currently unassigned, and its priority is listed as 

low. The assessment unit is only that part of the lake located in 

the United States. Additionally, in consideration of permitting, 

a mixing zone of approximately 4.4 mi extends between the 

Elk River input and the permit sampling location RG_DSELK 

(fig. 1). Technically, mixing zones are not applicable in 

U.S. regulation of contaminants that bioaccumulate such as 

selenium (USEPA, 2016d).

Qualifying statements about the regulatory status of Lake 

Koocanusa (that is, the source of pollution is not controlled by 

actions of a locally issued discharge permit and pollutant loads 

are increasing) introduce the question of whether permits for 

the coal mines in British Columbia will be adjusted based 

on selenium guidelines adopted by the State of Montana. 

In this regard, Lake Koocanusa is subject to transboundary 

regulations: namely, the Boundary Waters Treaty Act of 1909 

between Canada and the United States. The treaty establishes 

(1) an International Joint Commission to carry out the 

provisions of the act when requested by national governments 

and (2) a framework for dealing with disputes. The U.S. State 

Department, U.S. Department of the Interior, and USEPA, 

along with their Canadian counterparts, are actively engaged 

in this transboundary issue, but not to the point of referring the 

issue to the International Joint Commission.

The USFWS lists bull trout as threatened and designated 

Lake Koocanusa as critical habitat for this species (USFWS, 

1998). In Montana, this species is considered a “species of 

concern,” and in British Columbia, bull trout is blue listed 

(that is, a species of special concern). Westslope cutthroat 

trout is a species of concern in Montana and is blue listed 

in British Columbia. Burbot is red listed (that is, potentially 

extirpated, endangered, or threatened) in British Columbia, 

with lower Kootenay River populations designated as 

critically imperiled (Teck Coal Ltd., 2018a; BCMOE, 2015). 

Burbot also is considered culturally important to native Tribes, 

with resources being actively dedicated to its preservation, 

especially below Libby Dam (Idaho Department of Fish and 

Game, 2008).

White sturgeon do not inhabit Lake Koocanusa, but in 

1999, the USFWS published a recovery plan for the Kootenai 

River population of endangered white sturgeon that depends 

on the implementation of a long-term flow strategy for Libby 

Dam (USFWS, 1999). Thus, the selenium guidelines for Lake 

Koocanusa are required to protect the downstream use of 

provision of habitat for white sturgeon under the requirements 

of the Endangered Species Act (ESA). For ESA-listed species, 

a site-specific guideline can only be approved by the USEPA 

if the guideline either would not harm a single individual of 

any listed species or would harm so few individuals as to 

avoid a jeopardy biological opinion under section 7 of the 

ESA. If even one individual could reasonably be expected 

to be harmed (as might be the case for a guideline that is 

based on an EC10 level of toxicity), at a minimum, a formal 

biological opinion would need to be prepared by USFWS 

and an incidental-take statement would be required. The 

opinion could include perpetual-monitoring requirements for 

the documentation of compliance with the incidental-take 

statement. Additionally, a guideline could not adversely 

modify any critical habitat, which would include perturbations 

of food webs.

Methods—Modeling, Contours, and 

Cross Sections

The derivation of the methodology used here and 

the need for regulatory revision of selenium protection is 

extensively documented in Reiley and others (2003), Luoma 

and Rainbow (2005), Luoma and Presser (2009), Chapman 

and others (2010), and Presser and Luoma (2010a). Examples 

of the site-specific application of ecosystem-scale selenium 

modeling are available for the coal mining regions of southern 

West Virginia and several regions of San Francisco Bay 

affected by discharges from oil refineries, agriculture, and 

municipalities (Presser, 2013; Presser and Luoma, 2013; 

Luoma and Presser, 2018). The USEPA’s national guidelines 

(2016a) and those developed for California (USEPA, 2018) 

used an approach based on ecosystem-scale modeling.

Jenni and others (2017) describe an ecosystem-scale 

modeling framework applicable to Lake Koocanusa. Their 

report (1) serves as a coherent and consistent structure for 

organizing relevant scientific information within modeling 

parameters, (2) provides an appropriate context for 

interpreting new information as datasets and site parameters 

are developed, and (3) identifies data and science gaps 

that limit understanding of the implications of alternative 

selenium guidelines. Also available is an initial assessment of 

a site-specific monitoring design that meets the data needs of 

modeling selenium in Lake Koocanusa (Presser and others, 

2018). This sampling matrix focuses on (1) spatially and 

temporally paired samples of environmental media (water, 

particulates, prey and predator tissue), (2) a site nearest the 

source of selenium entering Lake Koocanusa from the Elk 

River in British Columbia, and (3) sites at the forebay of 

Libby Dam and at the international border in the United States.
Methods—Modeling, Contours, and Cross Sections 11

Ecosystem-scale selenium modeling conceptualizes and 

quantifies the site-specific variables that determine the effects of 

selenium (Presser and Luoma, 2010a) (fig. 7). Used optimally, 

the model provides a tool for framing a site-specific ecological 

problem or occurrence of selenium exposure, quantifying 

exposure within that ecosystem, and narrowing uncertainties about 

how to protect it by understanding the specifics of the underlying 

system ecology, biogeochemistry, and hydrology.

This mechanistic approach uses dietary selenium 

biodynamics to explain bioaccumulation and predict responses 

in ecosystems to selenium (note: all environmental media 

selenium concentrations are expressed as micrograms per 

gram dw except dissolved selenium, which is expressed as 

micrograms per liter). Dietary selenium biodynamics establish 

that (1) invertebrates biomagnify selenium (influx is greater 

than efflux) from particulate material at the base of the food 

web by as much as 38-fold depending on species-specific 

differences in dietary assimilation efficiency (AE) and the 

rate constant of loss and (2) dietary transfer of invertebrate 

selenium to fish species (as measured in wb dw tissue) has 

a median of approximately one, which reflects a cumulative 

preservation of selenium. Thus, trophic transfer from 

particulate material, based on dietary selenium concentrations 

and feeding, controls bioaccumulation within an ecosystem. 

The mechanistic dietary transfer model was validated through 

use of datasets from 29 historical and recent field case studies 

of selenium-exposed sites (Presser and Luoma, 2010a).

Choices explicit to running the model that are critical 

to deriving site-specific protection are (1) the choice of 

fish species, which determines the food web through 

which selenium is modeled; (2) the choice of food web, 

which determines the particulate material to prey kinetics 

of bioaccumulation; (3) the characterization of the type 

(for example, SPM, bed sediment) and bioavailability (for 

example, selenium speciation) of particulate material, which 

determines exposure at the base of the food web; and (4) the 

metric describing partitioning between particulate material 

and dissolved selenium concentrations, which is specific to 

the attributes of the hydrologic setting. Overall, the approach 

illustrates that environmentally safe dissolved selenium 

concentrations will differ among ecosystems depending on 

the ecological pathways and biogeochemical conditions in 

that system.

The constructed model here is first run in validation 

mode. For Lake Koocanusa, this model uses an observed SPM 

selenium concentration and categorized food-web types, with 

their associated trophic transfer factors (TTFs), to predict 

selenium concentrations in prey and predators. The predictions 

are then compared to observed selenium concentrations. The 

equation as applied to Lake Koocanusa is

CSe fish wb = (CSe SPM) (TTFinvertebrate) (TTFfish wb) (1)

where

CSe x is the selenium concentration in SPM, 

invertebrate, or fish (wb);

 TTFinvertebrate = CSe invertebrate ÷ CSe SPM; and

 TTFfish wb = CSe fish wb ÷ CSe invertebrate.

As stated previously, the main mathematically 

determinative variables are the type of particulate material 

used to represent the ecosystem, the selenium concentration 

in the particulate material, and the taxa or species of the 

invertebrate consuming that food. The effect of multistep 

food webs that include forage fish as additional prey (that is, 

trophic level 3 to trophic level 4 [TL3 to TL4] food webs) 

and the bioavailability of selenium to the invertebrate (that is, 

selenium speciation of the particulate material) also may be 

quantified through additional equation components (Presser 

and Luoma, 2010a).

The model is then run in translation mode, which 

addresses the regulatory aspects of modeling. Here, an 

assumed fish tissue selenium guideline (Cfish Se guideline wb) 

and an observed environmental partitioning factor [Kd SPM

= (CSe SPM/CSe dissolved) (1,000)] indicative of hydrological 

setting characteristics are used to predict a dissolved selenium 

concentration (CSe dissolved) that is protective of the site-specific 

ecosystem. The equation as applied to Lake Koocanusa is

CSe dissolved = Cfish Se guideline wb ÷ [(TTFfish wb) (TTFinvertebrate) (Kd SPM)](2)

where

(Kd SPM) (Cdissolved) is substituted for CSe SPM and the equation 

is solved for CSe dissolved.

Kd SPM reflects the efficiency of environmental partitioning of 

selenium from the dissolved phase to the chosen particulate 

phase (Presser and Luoma, 2010a). In the modeling here, 

wb fish tissue is used as the endpoint (Cfish Se guideline wb), 

but egg-ovary tissue can be substituted if tissue-to-tissue 

conversion factors (CFs) are available (Janz and others, 

2010; USEPA, 2016a, b). Thus, the predicted dissolved 

selenium concentration would quantify the ecosystem 

condition where fish would adhere to the assumed tissue 

guideline.

A series of modeling scenarios are used throughout 

the modeling process based on a range of choices that are 

informed by selenium science and stakeholders’ decisions. 

Through both data utilization, as described below, and 

scenario development, sensitive locations, timing, and food 

webs can be identified to understand the maximum selenium 

bioaccumulation potential (BAP) and, hence, the focus of 

effective regulation and management.

The contouring package in OriginPro (v. 9.1, 2014) 

software was used to construct gradient plots of monitoring 

data from Lake Koocanusa. The triangulation method was 

used to contour the data. Selected polygons (for example, 

dissolved selenium concentrations greater than [>] 1.0 μg/L) 

from the gradient plots were extracted with the digitizer tool 

for x- (distance from Libby Dam) and y- (depth below water 

surface) coordinates from each monthly concentration gradient 

map. The absolute area of each polygon was calculated using 

the polygon area calculator.
12 Scientific Basis of Selenium Ecological Protection in Support of Site-Specific Guidelines Development

Wildlife

Se

concentration

Kd

TTFinvertebrate

ECOLOGY

EFFECTS

Reproduction in

birds (hatchability;

teratogenesis;

chick survival

and growth)

Reproduction in

fish (deformity;

larva and fry

survival and

growth)

Processes

Factors

Se measurements

Management guidelines

Effects and ecology

Predator/prey links

Loss of individuals

Population decline

Loss of species

Community change

Dissolved Se concentration

Particulate

Se concentration

Particulate Se speciation

(phytoplankton, suspended

material, biofilm, sediment)

Dissolved Se speciation

(selenate, selenite, organo-Se)

Ecosystem-Scale Selenium Model Methodology

TTFfish TTFbird

Invertebrate

Se concentration

Fish

Se

concentration

Trophic

transfer

Bioaccumulation

Receivingwater hydrology

Environmental

partitioning

Bioavailability

Transformation

RISK MANAGEMENT

Source

Se protective

reference dose

Se toxicity

guidelines

Volume (hydrodynamics) Load and

speciation

Figure 7. Ecosystem-scale selenium model methodology. The model conceptualizes processes and parameters 

important for quantifying and understanding the effects of selenium in the environment. The model can be applied to 

forecast exposure and to evaluate the implications of management or regulatory choices. [Kd, empirically determined 

environmental partitioning factor between water and particulate material; TTF, biodynamic food-web transfer factor 

between an animal and its food; Se, selenium (adapted from Presser and Luoma, 2010a)]
Supporting Data—Scope of Studies and Study Area 13

Supporting Data—Scope of Studies 

and Study Area

Sets of site-specific data support and give context to 

ecosystem-scale selenium modeling in this interpretative report 

(Presser and Naftz, 2020). These data were compiled from 

publicly available databases of Federal, State, and Provincial 

agencies and reports by Teck Coal Ltd. Some sets of raw data that 

helped inform the data presented in Presser and Naftz (2020) are 

available from MTDEQ (lakekoocanusaconservation.pbworks.

com). The spreadsheets within our compilation are designed in an 

ecosystem-component format to assist modeling. Water-quality 

data are generically termed as “water column” for descriptive 

purposes below, but the data themselves are specific to dissolved 

(filtered) or total (unfiltered) samples. Reservoir sampling sites 

extend from the Elk River input in the north to the forebay in the 

south (see fig. 1 and figs. 8–11 for detailed maps of water-quality, 

invertebrate, and fish sampling locations).

Categories of data compiled in the companion USGS data 

release (Presser and Naftz, 2020) are as follows:

1. water-column selenium concentrations (2008–18),

2. recent USGS border platform water-column selenium 

concentrations (2019),

3. water-column selenium concentrations for the Elk River 

at Highway 93 (August 1984–January 2019),

4. spatially and temporally paired water-column and SPM 

selenium concentrations (2015–18),

5. recent detailed south of Elk (SOE) water-column 

selenium concentrations (2017–18),

6. dissolved selenium speciation (2015–16),

7. productivity (phytoplankton density) (2014–17),

8. zooplankton selenium concentrations (three net sizes) 

(2008, 2004–19),

9. zooplankton taxa metrics (2014–18),

10. invertebrate selenium concentrations (2013–16; 2018),

11. invertebrate taxa metric (2014–16; 2018),

12. dietary metrics for fish (percent of diet; relative 

importance index) (historical),

13. invertebrate taxa in fish stomachs (2017–18),

14. fish selenium concentrations (egg-ovary) (2008; 2013; 

2014–18),

15. fish species abundance (2009–16) and fish catches 

(2014–16; 2018),

16. number of stocked fish (1988–2016),

17. annex—bird egg selenium concentrations (2013, 

2014, 2016),

Lake Koocanusa upstream from Canada/U.S. border 

Lake Koocanusa at international boundary

Kootenai River below Libby Da

Lake Koocanusa in forebay

Lake Koocanus

upstream from

Gold Creek 

Lake Koocanusa west of Grasmere

Elk River east arm

Elk River

at Hwy 93

near Elko 

Lake Koocanusa upstream Elk

downstream Kikomun

Lake Koocanusa downstre

from Kikomun Creek 

LK2 - Lake Koocanusa south of Elk River

Lake Koocanusa near Tenmile Creek

Kootenay River at Wardner

Lake Koocanusa upstream from Canada/U.S. border 

Lake Koocanusa at international boundary

Kootenai River below Libby Da

Lake Koocanusa in forebay

Lake Koocanus

upstream from

Gold Creek 

Lake Koocanusa west of Grasmere

Elk River east arm

Elk River

at Hwy 93

near Elko 

Lake Koocanusa upstream Elk

downstream Kikomun

Lake Koocanusa downstre

from Kikomun Creek 

LK2 - Lake Koocanusa south of Elk River

Lake Koocanusa near Tenmile Creek

Kootenay River at Wardner

CANADA

UNITED STATES

BRITISH COLUMBIA

MONTANA

LAKE

KOOCANUSA

Kootenai River

Kootenay

River

0 5

0 5

10 MILES

10 KILOMETERS

N

Figure 8. Location of sites where water quality and (or) 

suspended particulate material samples were collected from 

Lake Koocanusa, Elk River, and the Kootenai River, Montana, and 

Kootenay River, British Columbia.
14 Scientific Basis of Selenium Ecological Protection in Support of Site-Specific Guidelines Development

Lake Koocanusa at

international boundary

Lake Koocanusa in forebay

Lake Koocanusa

near Gold Creek

Lake Koocanusa downstream from Elk River

Lake Koocanusa upstream from Elk River

Lake Koocanusa

at mouth of Elk 

Lake Koocanusa at Kikomun Bridge

Lake Koocanusa near Tenmile Creek

Lake Koocanusa at

international boundary

Lake Koocanusa in forebay

Lake Koocanusa

near Gold Creek

Lake Koocanusa downstream from Elk River

Lake Koocanusa upstream from Elk River

Lake Koocanusa

at mouth of Elk 

Lake Koocanusa at Kikomun Bridge

Lake Koocanusa near Tenmile Creek

CANADA

UNITED STATES

BRITISH COLUMBIA

MONTANA

LAKE

KOOCANUSA

Kootenai River

0 5

0 5

10 MILES

10 KILOMETERS

N

Figure 9. Location of sites where zooplankton samples were collected from Lake Koocanusa, 

Montana and British Columbia. Sample locations north of the international boundary may vary 

slightly depending on reservoir levels and other variables when the sample(s) were collected.
Supporting Data—Scope of Studies and Study Area 15

Lake Koocanusa near Gold Creek

Lake Koocanusa near Rexford

Lake Koocanusa in forebay

Lake Koocanusa downstream from Elk River

Lake Koocanusa upstream from Elk River

Lake Koocanusa near Sand Creek 

Lake Koocanusa at mouth of Elk River

Lake Koocanusa near Tenmile Creek

Lake Koocanusa near McGuire Creek drainage

Lake Koocanusa near Elk River

Lake Koocanusa near Gold Creek

Lake Koocanusa near Rexford

Lake Koocanusa in forebay

Lake Koocanusa downstream from Elk River

Lake Koocanusa upstream from Elk River

Lake Koocanusa near Sand Creek 

Lake Koocanusa at mouth of Elk River

Lake Koocanusa near Tenmile Creek

Lake Koocanusa near McGuire Creek drainage

Lake Koocanusa near Elk River

0 5

0 5

10 MILES

10 KILOMETERS

N

CANADA

UNITED STATES

BRITISH COLUMBIA

MONTANA

LAKE

KOOCANUSA

Kootenai River

Figure 10. Location of sites where invertebrate samples were collected from Lake Koocanusa, 

Montana and British Columbia. Sample location(s) may vary slightly depending on reservoir levels 

and other variables when the sample(s) were collected.
16 Scientific Basis of Selenium Ecological Protection in Support of Site-Specific Guidelines Development

Area 1

Area 2

Area 3

Area 4

CANADA

UNITED STATES

BRITISH COLUMBIA

MONTANA

Lake

Koocanusa

Kootenai River

A. Index map

0 5

0 5

10 MILES

10 KILOMETERS

N

LIBBY DAM

Figure 11. Location of sites (circles) where fish samples 

were collected from Lake Koocanusa. A, index map; B, Lake 

Koocanusa, British Columbia, area 1; C, Lake Koocanusa, 

Montana, area 2; D, Lake Koocanusa, Mont., area 3; E, Lake 

Koocanusa, Mont., area 4; F, Lake Koocanusa, British 

Columbia and Montana, areas 1–4 showing gill-net locations 

(triangles) used by Montana Fish, Wildlife and Parks.
Supporting Data—Scope of Studies and Study Area 17

3

4 5

6

7

8

9

EXPLANATION

B. Area 1

1

2

1. Lake Koocanusa near Sand Creek

2. Lake Koocanusa south of Kikomun Road bridge

3. Lake Koocanusa near Kikomun Creek Provincial Park

4. Lake Koocanusa north of cabin

5. Lake Koocanusa across from campground

6. Lake Koocanusa at cabin

7. Lake Koocanusa south of Elk River

8. Lake Koocanusa at south point of Elk River drainage

9. Lake Koocanusa near Gold Creek

N

10

11

12

14

13

15

16 17

18

19

20

EXPLANATION

C. Area 2 BRITISH COLUMBIA

MONTANA

CANADA

UNITED STATES

10. Lake Koocanusa at international boundary

11. Lake Koocanusa north of Sophie Creek drainage

12. Lake Koocanusa south of Sophie Creek drainage

13. Lake Koocanusa near Young Creek drainage

14. Lake Koocanusa North Point Murray

15. Lake Koocanusa at north point of Tobacco River drainage

16. Lake Koocanusa at south point of Tobacco River drainage

17. Lake Koocanusa near Tobacco River drainage

18. Lake Koocanusa farther south of Tobacco River drainage

19. Lake Koocanusa near Rexford

20. Lake Koocanusa North Black Lake

N

LAKE

KOOCANUSA

LAKE

KOOCANUSA

0 1 2 MILES

0 1 2 KILOMETERS

0 1 2 MILES

0 1 2 KILOMETERS

Figure 11. —Continued
18 Scientific Basis of Selenium Ecological Protection in Support of Site-Specific Guidelines Development

21

22

23

25

24

26

27

D. Area 3

N

EXPLANATION

21. Lake Koocanusa near Pinkham Creek drainage

22. Lake Koocanusa near Sutton Creek drainage

23. Lake Koocanusa near McGuire Creek drainage

24. Lake Koocanusa near Parsnip Creek drainage

25. Lake Koocanusa near Ural Creek drainage

26. Lake Koocanusa near Tenmile Creek drainage

27. Lake Koocanusa near Tenmile Creek

28

29

30

32

31

33

34

EXPLANATION

35

36

37

38

39

40

28. Lake Koocanusa near Fivemile Creek drainage

29. Lake Koocanusa near Bristow Creek drainage

30. Lake Koocanusa north of Barron Creek drainage

31. Lake Koocanusa north of Warland Creek drainage

32. Lake Koocanusa near Warland Creek drainage

33. Lake Koocanusa near Cripple Horse Creek drainage

34. Lake Koocanusa near McGillivray campground

35. Lake Koocanusa north of Jackson Creek drainage

36. Lake Koocanusa near Jackson Creek drainage

37. Lake Koocanusa near Peace Creek drainage

38. Lake Koocanusa near Canyon Creek drainage

39. Lake Koocanusa south of Canyon Creek drainage

40. Lake Koocanusa in forebay

E. Area 4

N

LAKE

KOOCANUSA

LAKE

KOOCANUSA

LIBBY DAM

0 1 2 MILES

0 1 2 KILOMETERS

0 1 2 MILES

0 1 2 KILOMETERS

Figure 11. —Continued
Supporting Data—Scope of Studies and Study Area 19

CANADA

UNITED STATES

BRITISH COLUMBIA

MONTANA

Lake

Koocanusa

Area 1

Area 2

Area 3

Area 4

F. Areas 1–4

0 5

0 5

10 MILES

10 KILOMETERS

N

LIBBY DAM

Figure 11. —Continued
20 Scientific Basis of Selenium Ecological Protection in Support of Site-Specific Guidelines Development

18. annex—fish mercury concentrations (muscle) 

(2013–18), and

19. annex—the State of Montana’s human health consumption 

advisories for mercury and selenium (2014).

Transboundary Metadata and Suspended 

Particulate Material Sampling

Metadata within Presser and Naftz (2020) give details 

of sampling and analysis methodologies for each category of 

data. Methodologies are specific to collection agency because 

of the transboundary nature of monitoring. Discussions are 

currently proceeding among Federal, Provincial, and State 

agencies about a potential transition to applying consistent 

monitoring protocols to ensure consistency in sample and data 

collection on both sides of the border.

It is important to note here that key to the data-collection 

effort to support modeling of Lake Koocanusa was the 

introduction of sampling of SPM on the Montana side in 2015 and 

on the British Columbia side in 2017. A selenium concentration 

in SPM is used to initiate modeling as the diet of invertebrates 

at the base of the food web, and its characterization is important 

in representing the dynamics of the system (Presser and Luoma, 

2010a). The oligotrophic/mesotrophic nature of Lake Koocanusa 

requires collecting large-volume water samples and using an 

efficient concentrating technique (that is, ultracentrifugation) 

to obtain a sufficient mass of SPM for chemical analysis 

(Horowitz,1986; Horowitz and others, 2001, 2008). This approach 

provides an integrated range of particle sizes representational of 

(1) seasonal sources, (2) hydrological transport conditions, and 

(3) the dynamics of ecological selenium processing within Lake 

Koocanusa.

SPM samples were spatially and temporally matched to 

water samples to enable calculation of Kd (Presser and others, 

2018; Presser and Naftz, 2020). Kd operationally defines the 

instantaneous partitioning of selenium between particulate and 

dissolved phases. This metric is driven by the residence time 

of water and, as such, offers a quantitative factor representing 

competing hydrologic and biogeochemical processes at work in 

complex aquatic systems (Presser and Luoma, 2010a). Monthly 

dissolved selenium concentrations, even if not paired with an 

SPM concentration, also are compiled as part of Presser and Naftz 

(2020) to further elucidate the impacts of hydrodynamics.

From 2015 to 2017 on the Montana side, paired samples 

were collected at two locations (forebay and international 

boundary) and at two depths (epilimnion, 3 meters (m) 

below lake surface; hypolimnion, 3 m above lake bottom). 

The number of SPM sampling times per year varied (2015, 

n=3; 2016, n=4; 2017, n=7), thus limiting direct comparative 

profiles. In 2018, paired sampling on the Montana side 

focused on concentrations for the epilimnion at the border, 

Tenmile, and forebay sites in May, June, and September (n=9). 

In 2019, sampling occurred at the border and forebay for May, 

July, and September for two depths except for the forebay in 

September (n=11). For the British Columbia side, sampling 

events at SOE occurred in June, July, and September in 2017 

at three depths (n=9) and in June–October in 2018 at the 

epilimnion (n=5). SPM data for 2019 were delayed and are not 

included here.

A Lake-Gradient Approach to Support 

Modeling and Resulting Decisions on 

Data Reduction

A dynamic, working system view of Lake Koocanusa 

during 2017 was developed from (1) detailed bar graphs 

for observed dissolved and SPM selenium concentrations 

specific to epilimnion and hypolimnion strata for SOE, border, 

and forebay sites (Presser and others, 2018; figs. 5–9) and 

(2) depth-dimensional gradient maps of observed dissolved 

and SPM selenium concentrations and calculated Kd values 

for sites at the SOE, border, and forebay (fig. 12A, B, C). The 

distribution of selenium in the lake, as illustrated in these 

figures, is influenced by hydrodynamics and source loading 

conditions of the lake. Specifically these conditions (1) drive 

environmental partitioning and may under some instances 

disconnect the particulate material and the water column 

as rapid flow transitions occur (Presser and others, 2018, 

figs. 11–16) or riverine conditions interface with the reservoir 

(for example, extensive range of Kd values for SOE) and 

(2) underlie the fundamental functioning of ecosystems that 

are portrayed and quantified in selenium modeling. These data 

and figures illustrate that (1) a distinct spring contaminant 

plume in dissolved selenium occurs at 13 m, with a similar 

plume occurring in fall at 21 m; (2) for both the epilimnion 

and hypolimnion, selenium concentrations in SPM at the 

forebay are generally greater than those at the border, with 

the trend reversing for dissolved selenium (that is, border is 

greater than forebay); (3) for SPM selenium concentrations in 

the forebay, the epilimnion generally exceeds the hypolimnion, 

but for dissolved selenium concentrations, the hypolimnion 

generally exceeds the epilimnion; and (4) patterns for Kd are 

similar to that for selenium concentrations in SPM.

The dynamic nature of Lake Koocanusa is an important 

consideration because (1) modeling is initiated through 

choice of SPM selenium concentrations and (2) site-specific 

water-column selenium concentrations are derived for 

regulatory purposes that are a function of both the choice of 

Kd and the food web. Hence, concentration gradient maps 

specific to lake strata and location can narrow uncertainty 

both in terms of selenium source and hydrodynamic effects. 

These gradient maps also help explain temporal variability of 

(1) dissolved selenium concentrations during April and May 

when snowmelt and drawdown are occurring and (2) SPM 

selenium concentrations during June, July, and August when 

biological productivity is elevated.
A Lake-Gradient Approach to Support Modeling and Resulting Decisions on Data Reduction 21

Kd

580

967

1,613

2,690

4,485

7,480

A

C

100

80

60

40

20

0

4/265/166/277/258/299/26

10/24

4/265/166/277/258/299/26

10/24

6/277/259/27

100 150 200 250 300 100 150 200 250 300 100 150 200 250 300

Depth below water surface, in meters

Julian day in 2017

South of Elk River inflow International boundary Forebay

0.72

1.12

1.75

2.72

4.24

6.60

80

60

40

20

0

B

100 150 200 250 300 100 150 200 250 300 100 150 200 250 300

Depth below water surface, in meters

Julian day in 2017

South of Elk River inflow International boundary Forebay 4/26 5/16 6/27 7/25 8/29 9/26 10/24 4/26 5/16

6/277/258/299/26

10/24

6/277/259/27

Particulate selenium,

in micrograms

per gram

100 150 200 250 300 100 150 200 250 300 100 150 200 250 300

100

80

60

40

20

0

Depth below water surface, in meters

0.60

0.86

1.12

1.38

1.64

≥1.90

South of Elk River inflow International boundary Forebay 4/26 5/16 6/27 7/25 8/29 9/26 10/24 4/26 5/16

6/277/258/299/26

10/24

6/277/259/27

Filtered selenium,

in micrograms

per liter

EXPLANATION

EXPLANATION

EXPLANATION

Julian day in 2017

Figure 12. Depth-specific gradients across three reservoir monitoring sites in 2017. A, for dissolved selenium concentrations; B, for 

suspended particulate material selenium concentrations; C, for environmental partitioning factor (Kd) values (that is, partitioning 

factor between the dissolved phase and particulate phase). [triangles denote sample depth; dashed lines denote when samples were 

collected: date (mm/dd) and Julian day (2017)]
22 Scientific Basis of Selenium Ecological Protection in Support of Site-Specific Guidelines Development

Given the importance of the dimensional nature of 

dissolved and SPM selenium concentrations in the lake as 

delineated above, the decision here, at this stage of knowledge 

for the lake, was not to statistically reduce datasets but rather 

to consider each paired sampling event and consequent 

Kd calculation as an independent scenario. Overall, a 

gradient-specific approach helps conceptualize potential 

seasonal and spatial interactions with food webs and inform 

modeling in terms of sensitive times and locations when 

considering regulatory and management options.

Data Utility for Modeling—Field 

Collection and Selenium Analysis of 

Invertebrates and Fish

Divergent goals for monitoring of Lake Koocanusa 

impinged on data usefulness for the dietary biodynamic 

modeling of selenium. In general, existing monitoring 

programs were not adjusted to protocols based on the 

ecosystem aspects of selenium modeling and, thus, do 

not provide essential spatially and temporally coordinated 

samples of ecosystem compartments that are important to 

narrowing modeling uncertainty. Further, species or taxa 

specificity, sampling of reproductive tissue in game fish 

species, and a gradient approach for a defined source of 

selenium contamination were not important design elements 

of monitoring. Rather, sampling programs were maintained 

at current objectives that pertain to (1) age, health, and 

recruitment of fish species; (2) fish-community aspects; 

(3) set times and sites for reservoir-reach scale sampling or 

broadly defined upstream-to-downstream sampling at the 

Elk River input; and (4) separate schedules and sites for 

sampling each media type. For example, fish sampling by 

MTFWP took place at a site designated as “Canada,” which is 

mainly above the Elk River discharge, the source of selenium 

(Presser and Naftz, 2020) (fig. 11F). On the British Columbia 

side, monitoring of zooplankton and invertebrate as food 

sources identified taxa, but selenium concentrations were 

analyzed on composited samples. Fish monitoring, which 

occurs on a 3-year cycle in Montana, also was not adjusted 

to accommodate matching fish samples with the scheduled 

intensive sampling of SPM in 2017. Additionally, selenium 

speciation for particulate material was not analyzed as part 

of monitoring. This parameter is important for determining 

the bioavailability of SPM selenium to prey species within a 

biodynamic model (Presser and Luoma, 2010a).

Listed in table 1 are the species of fish important to the 

Lake Koocanusa ecosystem and past decisions concerning 

field sampling of fish (for example, seasonal timing, type of 

tissue, number of samples per species) that took place during 

2008–18 at sites on both sides of the border. The components 

of table 1 also address the broader context of connecting to the 

reproductive nature of selenium’s toxicity as a requirement of 

regulatory policy. Specifically, as described by Janz (2011), 

selenium is an environmental reproductive toxicant for fish 

with a characteristic suite of early life-stage deformities 

resulting from maternal transfer of selenium-methionine to 

yolk proteins during vitellogenesis and subsequent selenium 

exposure during yolk resorption by developing larvae.

There is an important distinction in terms of derivation 

of tissue selenium guidelines themselves (that is, construction 

of toxic-response curves) and their subsequent connection 

to bioaccumulation equations in order to derive or predict 

site-specific dietary and dissolved selenium concentrations. 

The primacy of egg tissue as a guideline is related to its 

reliability for prediction of effects (Lemly and Skorupa, 

2007; Chapman and others, 2010; USFWS, 2012; 

USEPA, 2016a). The interconnectedness or partitioning 

of selenium concentrations among diet, egg, and wb 

selenium concentrations in fish is complex, although there is 

causality between diet and both egg and wb tissue selenium 

concentrations. The derived connection used by the USEPA 

in modeling and translating tissue guidelines is mainly 

between diet and wb concentrations (for example, 89 percent 

in field exposure scenarios) with a CF that is species specific 

in order to convert wb to egg-ovary concentrations (USEPA 

2016a, b, c, d, 2018). Hence, the practical consequence of 

the USEPA’s approach is that the diet to egg relationship is 

not defined as a primary relationship in fish when modeling 

the dietary transfer of selenium to connect to a water-column 

selenium concentration. However, studies have addressed the 

necessity of an internally consistent equilibrium relationship 

between wb and egg selenium concentrations based on dietary 

exposures, as would be expected in nature (Chapman and 

others, 2010). Additionally, few laboratory data are available 

to directly connect trophic transfer of selenium from diet to 

egg tissue.

To further inform our discussion here, excerpts relating 

the ecotoxicology of selenium to (1) fish tissue monitoring 

guidance for the implementation of site-specific selenium 

guidelines (USEPA, 2016b) and (2) tissue-to-tissue 

conversion relationships (Janz and others, 2010) are 

given in table 2. These rationales shed light on questions 

concerning (1) muscle tissue as an unacceptable surrogate 

for egg tissue and consequent connection to reproductive 

effects; (2) the importance of gravid females and sampling 

of expressed eggs; (3) problematic interpretations of data 

for combined egg-ovary tissue, in general, and specifically 

for nonsynchronous spawners like cyprinids; and (4) timing 

for preference of wb sample collection versus egg sample 

collection. The implications of the compiled information (1) as 

part of food-web and hydrological model inputs and (2) as 

to their ecological relevance in representing and quantifying 

fundamental processing of selenium are discussed below in the 

larger context of the status of the Lake Koocanusa ecosystem.
Data Utility for Modeling—Field Collection and Selenium Analysis of Invertebrates and Fish 23

Table 2. Excerpts concerning ecotoxicology and fish tissue monitoring or tissue-to-tissue relationships.

Excerpts (U.S. Environmental Protection Agency, 2016b)

Egg-ovary sampling including temporal factors associated with spawning

When using egg-ovary tissue for the implementation of the selenium criterion, States and authorized Tribes must be careful to consider the 

difficulty in timing egg-ovary sampling with spawning periods.

The only appropriate time to collect egg-ovary tissue from suitable species is when the female is gravid in the pre-spawn stage, just before 

mating and spawning. This is typically a very small window (see appendix B) of time for most synchronous species.

An egg-ovary tissue sample from a female that is not gravid will not be representative for monitoring and assessment when compared with 

gravid egg-ovary results because the egg-ovary tissues represent the potential selenium load available to eggs and larvae through maternal 

transfer.

Egg-ovary tissue is the preferable tissue to collect because the egg-ovary tissue of pre-spawn, reproductively mature (also called “gravid” or 

“vitellogenic”) females will give the most accurate view of potential selenium hazard to reproduction.

Egg-ovary tissue (which refers to eggs, ovaries, or both) data provide point measurements that reflect integrative dietary accumulation, transfer, and deposition of selenium over time and space in female fish at a given site.

Research has shown that selenium concentrations in egg-ovary tissue is strongly correlated with selenium in the maternal diet, which is 

transferred from the adult female during vitellogenesis.

It is the selenium concentration in eggs that drives early life-stage toxicity, so adult female fish must be collected during the late vitellogenic 

or preovulatory periods of oogenesis for this criterion to be scientifically and toxicologically meaningful.

Timing errors related to fish reproduction may result in data that falsely indicate the selenium criterion is being met.

Most fish species that are synchronous spawners do so in the spring, whereas fish tissue collection for advisories typically occurs in the late 

summer or early fall, when contaminant loads in the edible portion of the fish are highest. If an agency is limited to sampling outside of 

the pre-spawning period due to resource constraints, that will need to be considered when incorporating selenium fish tissue monitoring 

into the existing programs, or when developing a new program (for example, sampling whole-body or muscle tissue instead of egg-ovary 

tissue).

For egg-ovary tissue sampling, agencies with fish tissue monitoring responsibilities should consult with a State fisheries biologist to determine the appropriate time for sampling specific species in their region in order to capture the specimens in their pre-spawning phase. 

These regional experts will be familiar with the local species and able to use their best professional judgment to determine which are appropriate for selenium sampling and the appropriate sampling time frame based on spawning season.

Monitoring programs should sample for reproductively mature females from iteroparous fish species (that is, fish that have multiple reproductive life cycles over the course of its lifetime) that are single batch (synchronous) or multiple batch (asynchronous) spawners.

Fish species that spawn multiple times per season (asynchronous; for example, species in the family Cyprinidae) have variable cycles of 

oogenesis and, thus, special care should be taken when using these for egg-ovary monitoring as the pre-spawn window can be hard to 

predict.

Egg maturation may occur well before, immediately prior to, or during the spawning season.

For example, Lepomis cyanellus (Green Sunfish) can spawn multiple times per season (Osmundson and Skorupa 2011, Chapman and others, 

2010).

For many fish species, vitellogenesis can occur over several months prior to spawning, with a relatively large amount of yolk deposited into 

eggs (Osmundson and Skorupa 2011).

It is also possible that species with relatively large eggs and yolks deposit more selenium in their eggs than species with smaller eggs and 

yolks (Osmundson and Skorupa 2011).

Selenium concentrations in the eggs and ovarian tissues are expected to be at their maximum level when eggs have maximum levels of vitellogenin prior to spawning; therefore, egg-ovary tissue samples collected outside of the pre-spawn window are not suitable for assessment 

in comparison to the national egg-ovary fish tissue criterion element.

Reproductively mature females of most fish species, except indeterminate spawning species and viviparous species (that is, live bearing), 

will produce eggs that can be sampled for selenium. Appendix A of this document (i.e., USEPA, 2016b) presents egg and ovary collection 

and sample preparation methods.

The egg-ovary tissue element has primacy over all other elements; thus, when available, it is the ultimate arbiter for compliance with the 

selenium water-quality criterion. Most States and authorized Tribes do not currently collect egg-ovary tissue as part of their regular 

monitoring programs. The USEPA recognizes that many States and authorized Tribes may not have the resources to augment their existing 

monitoring programs to include egg-ovary tissue collection. Although egg-ovary tissue remains the preferable tissue type, whole-body or 

muscle samples can be used as an alternative.
24 Scientific Basis of Selenium Ecological Protection in Support of Site-Specific Guidelines Development

Influence of Ecosystem Characteristics 

on Selenium—Status of Ecosystems 

and Data Limitations for Modeling

The 12 species of fish considered for modeling are bull 

trout, burbot, kokanee, Catostomus catostomus (longnose 

sucker), largescale sucker, mountain whitefish, northern 

pikeminnow, peamouth chub, rainbow trout (wild strain), 

Richardsonius balteatus (redside shiner), Westslope cutthroat 

trout, and yellow perch (table 1). Fish characteristics used 

to ecologically sort these fish species to support modeling 

include (1) family; (2) origin and function (native, nonnative; 

game, nongame; introduced, invasive); (3) association of 

dietary habitat and life cycle; (4) species status, history, and 

abundance; (5) sampled tissue variations; (6) number of 

egg-ovary samples per species; (7) observations concerning 

female ripeness; (8) availability of a gonadosomatic 

index (GSI) metric; and (9) spawning type (for example, 

nonsynchronous spawning for cyprinids), location, and timing 

(table 1). Additionally, a diagram explicit to the life cycle 

of Lake Koocanusa fish species and their potential exposure 

opportunities was constructed by Baranowska and Robinson 

in 2017. This array of information (that is, a “fish grid”) helps 

identify the who, when, where, and why of exposure during 

the life cycle of species that can inform goals for monitoring 

and help interface with modeling (Presser and Luoma, 2013).

Restricting available observed data based on these listed 

fish factors yielded few species and few selenium concentrations 

per species (that is, a reduced fish-selenium-concentration 

database in Presser and Naftz, 2020) on which to validate model 

predictions. Species-specific factors that were found to limit 

the utility of available data as the basis of a dietary biodynamic 

selenium model are included in table 1. Overarching concepts 

that limit data utility relate to (1) dysfunctional selenium dietary 

bioaccumulation and tissue partitioning that affect tissue-to-tissue 

relationships, (2) effects to gonadal development, (3) uncertainty 

in connections to reproductive effects, and (4)sampling protocols 

not being designed for a known source gradient (that is, geographic 

focusing). Species-specific limiting factors are (1) timing of egg 

sampling when sampling is through net hauls of many species; 

(2) muscle plug sampling of game fish species, rather than egg or 

wb sampling; (3) egg-ovary selenium concentrations reported for 

Table 2. Excerpts concerning ecotoxicology and fish tissue monitoring or tissue-to-tissue relationships.—Continued

Excerpts (U.S. Environmental Protection Agency, 2016b)

Fish species selection—Fish body size

It is difficult to collect egg-ovary (or muscle) tissue samples from small fish species (for example, certain species in the family Cyprinidae or 

Cyprinodontidae) because the amount of tissue available for analysis is small, and many of these species are asynchronous spawners that 

do not have a large number or biomass of eggs at any one time.

Whole-body sampling

Measuring selenium concentration in ovarian tissue during other periods of oogenesis will be much less informative. Summer and fall may 

be prime periods for whole-body and muscle tissue collection due to the engorgement of populations to replenish fat and energy reserves 

post-spawn.

If agency resources limit fish tissue collection to times outside of these species-specific windows connected to spawning periods, then the 

only appropriate samples to collect are whole-body and muscle tissue. Target fish species collected in the fall may be common to selenium 

monitoring and human health risk assessment. In this case, muscle tissue can be composited and evaluated for selenium in addition to 

contaminants of interest for fish consumption advisories.

The USEPA is aware that some States and authorized Tribes make use of muscle plugs in their monitoring programs. However, it is important to remember that contaminant concentrations can vary considerably depending on where the plug is collected. Plugs provide very 

small tissue quantities (about 1 gram of tissue per fish) and, therefore, not enough biomass for possible reanalysis or quality assurance/

quality control considerations. In addition, relatively small individuals may not recover from a muscle plug biopsy punch. Care should be 

taken to ensure that the sampling protocols involving plugs have a sound scientific basis and that there is enough tissue for the analytical 

method.

Seasonal considerations are less stringent for whole-body and muscle tissue sampling. Seasonal collection of whole-body or muscle fish 

tissue samples should be timed to avoid the pre-spawning influence on selenium tissue concentrations, particularly for females, since 

enhanced depuration of selenium from tissue stores may occur during vitellogenesis prior to spawning (USEPA, 2016a).

Excerpts (Janz and others, 2010)

Section 6.4.5.1 Selenium Concentration Relationships between Fish Tissue (pages 167–168).

Therefore, tissue-tissue relationships should not be used generically to derive tissue-based selenium toxicity thresholds.

However, even within a species tissue-tissue, extrapolations should ideally be site-specific because individuals show considerable intraspecific variation in the ratio between egg/ovary and whole-body selenium.

If no species-specific tissue-tissue relationship is available, it is not possible to use adult tissue selenium [as opposed to eggs] to reliably 

estimate potential early life-stage exposure [text in brackets is for clarification purposes].
Modeling and Fish Scenario Development 25

nonripe or undeveloped ovaries as indicated by field observation 

or GSI values <1, especially in nonsynchronous spawners; (4) a 

high incidence of intestinal tapeworms in cyprinids; (5) ingestion 

of nematodes in trout; (6) a low number of samples for species 

important to representation of the lake's ecosystem; (7) no fish 

samples at ecologically important sites (for example, forebay, 

SOE) for species important to Lake Koocanusa; and (8) elevated 

mercury concentrations (Teck Coal Ltd., 2018a, 2019) that are 

known to cause antagonistic/synergistic effects within fish affected 

by selenium (for example, redistribution of selenium within tissues) 

(table 1). Individual discussions of these topics are beyond the scope 

of this report; however, selected literature citations concerning GSI, 

parasitism, and mercury/selenium interactions are included in a 

separate “Supplementary References” section in the appendix.

In sum, these identified ecosystem influences define and 

justify the constraining choices that were made for use of selenium 

concentration data for various fish species. For the future, modifying sampling protocols to accommodate these types of identified 

vulnerabilities and focusing modeling on exposures important to 

species of known concern would lower uncertainty and identify 

potential ecological bottlenecks (most sensitive species at time 

and place of greatest exposure) for Lake Koocanusa. To this point, 

selenium concentrations in ovaries of the few samples available of 

Westslope cutthroat trout (n=2) and rainbow trout (n=11) ranged 

from 5.6 to 19.8 μg/g dw, but none were downstream from the Elk 

River. Even fewer samples are available to assess bull trout (n=2) 

and burbot (n=3).

Diet Component Analysis and 

Categorization of Fish Species

Stomach content data for fish collected by the MTFWP 

from 1982 to 1992 are summarized in Baranowska and 

Robinson (2017) and Baranowska (2018). Results are either 

based on calculation of a relative importance index or percentage of biomass for each prey item. Detailed field methods and calculations are given in Dalbey and others (1998)

and Chisholm and others (1989) and are summarized in 

Baranowska and Robinson (2017) and Baranowska (2018).

Species-specific dietary data considered for each fish species 

modeled here are summarized as percentage of taxa-specific 

invertebrate biomass and relative importance index (Presser 

and Naftz, 2020). Percentage of biomass data are the most 

applicable for biodynamic modeling (Presser and Luoma, 2010a) 

and are used here as the basis for categorizing Lake Koocanusa 

fish species for modeling (table 3, available for download 

at https://doi.org/10.3133/ofr20201098). Recent selenium 

concentrations for invertebrate taxa in 2018 and a study of the 

contents of the stomachs of fish species caught in 2017 were also 

used to inform the categorization for modeling (Presser and Naftz, 

2020). Chironomids in particular were key components of benthic 

Diptera larvae sampling. Teck Coal Ltd. (2018a, 2019) also found 

chironomids and mayflies as the dominant taxa for sites on the 

British Columbia side of the reservoir including the Elk River sites 

(Presser and Naftz, 2020). Finally, qualitative information on the 

density of different invertebrate taxa at certain sites were included 

as an additional basis for diet component analysis (Presser and 

Naftz, 2020).

The number of fish species of interest necessitated each fish 

species being assigned to a generalized food-web category for 

modeling to reduce the number of scenarios (table 4, available 

for download at https://doi.org/10.3133/ofr20201098). The 

resultant initial diet categorizations for invertivores (aquatic 

insects and zooplankton to fish) are as follows: 100-percent 

aquatic insect (rainbow trout, Westslope cutthroat trout, redside 

shiner, longnose sucker), 50-percent aquatic insect and 50-percent 

zooplankton (peamouth chub, largescale sucker, mountain 

whitefish), 75-percent zooplankton and 25-percent aquatic insect 

(rainbow trout December–March), and 100-percent zooplankton 

(kokanee). Categorization for TL4 (predator fish) to TL3 (forage 

fish) is specific to bull trout, burbot (winter and summer), and 

northern pikeminnow. In these scenarios, forage fish ingest a range 

of higher risk insectivores and lower risk planktivores (that is, 

100-percent insectivores, 50-percent aquatic insect and 50-percent 

zooplankton, and 100-percent planktivores). Rainbow trout could 

be included in the last category if a scenario was desired to include 

adult rainbow trout switching to a diet of 100-percent kokanee. A 

food web consisting of 50-percent aquatic insects and 50-percent 

fish also can be considered for yellow perch as a combination of 

assimilation from two separate food webs (that is, the average of 

the two outcomes) but is not included here because of noninterest 

in using yellow perch as a species to represent Lake Koocanusa. 

These initial modeling categories can then be modified based 

on additional data collection or specific choices pertaining to 

decision-makers’ goals for protection and representation of the 

ecosystem in their efforts to narrow uncertainty.

Modeling and Fish Scenario 

Development

The equation for prediction of a selenium concentration 

in fish (CSe fish wb) is initialized from a selenium concentration 

in SPM (CSe SPM) as diet for an assumed invertebrate prey 

taxon (eq. 2). The equation modified by assigning a percentage 

of bioavailability to the SPM is

CSe fish wb = [(CSe SPM) (percent bioavailability)] 

 (TTFinvertebrate) (TTFfish). (3)

For an aquatic insect food web that assumes 100-percent 

bioavailability of SPM, the numeric version of the equation is

CSe fish wb = [(CSe SPM) (1.0)] (2.8) (1.1) (4)

where

TTFinvertebrate is the mean aquatic insect TTF of 2.8, which 

here also represents the TTFchironomid

of 2.7; and
26 Scientific Basis of Selenium Ecological Protection in Support of Site-Specific Guidelines Development

TTFfish is the mean fish (wb) TTF of 1.1, which is 

based on 25 fish species (Presser and 

Luoma, 2010a).

Similarly, for a zooplankton food web, the numeric version of 

the equation is

CSe fish wb = [(CSe SPM) (1.0)] (1.5) (1.1) (5)

where

TTFinvertebrate is the mean freshwater zooplankton 

TTF of 1.5.

However, a more conservative choice would be a TTF of 1.9 

that is specific to Daphnia (Presser and Luoma, 2010a).

Assimilation efficiencies (AEs) of different types of 

particulate matter can be considered in this type of equation 

to account for the site- or species-specific bioavailability of 

foods likely to be consumed by invertebrates. The selenium 

speciation of the particulate phase (that is, elemental 

selenium, adsorbed selenium, and organo-selenium), the 

type of particulate material (sediment, detritus, or algae), 

and the taxa of the invertebrate ingesting the particles all 

affect the efficiency of selenium assimilation as quantified 

in biodynamic modeling (Presser and Luoma, 2010a). For 

example, Schlekat and others (2004) determined an AE 

of 52 percent for the copepods Tortanus sp. and Acartia

sp. at a specific efflux rate. Both elemental and adsorbed 

selenium are probably minor components of the food of 

most organisms. Assimilation of selenium is more efficient 

when animals ingest living food or detritus, both of which 

are dominated by organo-selenium. From these materials, 

AEs vary from 55 to 86 percent among species, with smaller 

differences among living food types such as different species 

of algae. Estimates of AE for specific types of particulate 

material are 15 percent for sediment, 35 percent for detritus, 

and 60 percent for algae.

A similar equation where an assumed, generalized SPM 

bioavailability of 60 percent is applied to an aquatic insect 

food web is

CSe fish wb = [(CSe SPM) (0.6)] (2.8) (1.1). (6)

When applied to a zooplankton food web, the 

equation becomes

CSe fish wb = [(CSe SPM) (0.6)] (1.5) (1.1). (7)

Modeling of selenium bioaccumulation also can represent 

a diet that includes a mixed proportion of prey in the diet 

through use of the equation

CSe fish wb = (TTFinvertebrate) [(CSe invertebrate a) (prey fraction a) 

+ (CSe invertebrate b) (prey fraction b) 

 + (CSe invertebrate c) (prey fraction c)]. (8)

Accommodating longer food webs that contain more 

than one higher TL consumer (for example, forage fish being 

consumed by predatory fish) can be incorporated through 

additional TTF values.

For modeling of a food web with both a TL3 forage fish 

and a TL4 predatory fish, the equation is

CSe predator fish wb = (TTFinvertebrate) (CSe SPM) (TTFforage fish wb)

 (TTFpredator fish wb). (9)

Species specificity in terms of TTFfish for predator and 

forage fish can be addressed using factors compiled by the 

USEPA (2016a). The range of TTFfish is narrow though for the 

species of Lake Koocanusa (0.88–1.46), so the quantitative 

effect of deviating from the mean factor of 1.1 is relatively 

small (see later discussion).

Model Validation

For the ecosystem-scale selenium modeling methodology, 

validation or estimation of uncertainty is through comparison 

of predicted prey and predator selenium concentrations with 

observed selenium concentrations. For Lake Koocanusa, the 

availability of SPM samples establishes the modeled sites as 

the forebay, border, and SOE. Availability of field data from 

the lake (1) establishes the validation of invertebrates and 

zooplankton and (2) excludes comparison to observed fish 

because of the factors specified in table 1 and discussed above.

For sites at the forebay, border, and SOE, observed 

selenium concentrations for invertebrates and zooplankton 

(Presser and Naftz, 2020) are compared to selenium 

concentrations predicted using the invertebrate model 

equation described earlier calculated for each observed SPM 

selenium concentration and for two SPM bioavailabilities 

(100 percent and 60 percent) (table 5, available for download 

at https://doi.org/10.3133/ofr20201098). The SPM selenium 

concentrations applied in validation are specific to the time 

period of sample collection and encompass the entire available 

dataset (Presser and Naftz, 2020). Selenium concentrations 

are specific to taxa of invertebrates in field samples from the 

Montana side but are composited samples from the British 

Columbia side (Presser and Naftz, 2020). Zooplankton 

sampling was executed using three net sizes (64-, 80-, and 

150-micron nets) during a variety of months (Presser and 

Naftz, 2020).

Given the limited amount of field data and varied 

sampling methods and collection sites for invertebrates and 

zooplankton, comparison of ranges is more appropriate than 

statistical comparisons. Only one set of observations (May and 

September 2018, n=12) for invertebrates is available from a 

collective Tenmile/forebay and Rexford site on the Montana 

side due to the small mass of material available for analysis. 
Model Validation 27

For validation, comparisons are to predicted selenium 

concentrations for 2015–18 (table 5). The range of observed 

selenium concentrations is 0.4–9.1 μg/g dw in 2018, whereas 

the range of predictions throughout all years at 100-percent 

bioavailability is 1.2–18.8 μg/g dw and at 60-percent 

bioavailability is 0.7–11.3 μg/g dw.

For the British Columbia side, observed ranges for 

invertebrates at the SOE site are 5.3–9.7 μg/g dw in 2013–16 

(n=8) and 4.7–12 in 2018 (n=7). Predicted selenium 

concentrations at 100-percent bioavailability range from 3.8 

to 15.5 μg/g dw in 2017 and 9.3–21 μg/g dw in 2018. At 

60-percent bioavailability, the ranges are 2.3–9.3 μg/g dw in 

2017 and 5.6–12.6 μg/g dw in 2018.

Validation for zooplankton is affected by the transitory 

nature of the zooplankton community and the variable field 

dataset available for comparison (figs. 4 and 5). Specific 

factors involved are use of different net sizes (64-, 80-, and 

150-micron nets) for sampling and the variable uptake rate of 

selenium for different taxa that are composited for analysis. 

For example, rotifers are a major component of zooplankton 

sampled on the Montana side with density varying by site 

(fig. 5A, B, and C). In studies where rotifers were reared 

as food for fish larvae, rotifers were found to be devoid of 

selenium both prior and after enrichment and, thus, provided 

little nutrition to prey (for example, Mæhre and others, 2012).

For zooplankton on the Montana side (64- and 

150-micron nets), comparisons for predictions at 60-percent 

bioavailability based on years when the most data were 

collected (2017–18) showed a range of 0.7–5.9 μg/g dw 

compared to an observed range of 0.3–4.4 μg/g dw. For 

zooplankton on the British Columbia side (80-micron net), the 

predicted range at 60-percent bioavailability was 1.2–6.7 μg/g 

dw compared to an observed range of 2.2–4.9 μg/g dw.

Dietary guidelines give context for the observed 

selenium concentrations in the aggregate for the site-specific 

food sources of Lake Koocanusa. The BCMOE currently 

has a dietary guideline of 4 μg/g (BCMOE, 2014), which is 

exceeded by the ranges of observations and predictions for 

Lake Koocanusa. The USFWS has derived a dietary guideline 

of 3.6 μg/g dw for both fish and birds at the EC00 level, of 

<4.9 at the EC10 level, and of 5.7 μg/g dw at the EC20 level 

(Presser and Luoma, 2010b). Again, the ranges of observations 

and predictions for Lake Koocanusa exceed those values.
28 Scientific Basis of Selenium Ecological Protection in Support of Site-Specific Guidelines Development

Prediction of Protective Dissolved 

Selenium Concentrations—Invertebrate 

to Fish Model and Trophic-Level 

(Predatory to Forage) Fish Model

Two models for prediction of protective dissolved selenium 

concentrations were developed. The equation for the invertebrate 

to fish model (IFM) is

predicted protective CSe dissolved = fish guideline wb /TTFfish

 /[(TTFinvert1*invert fraction1) + (TTFinvert2*invert 

 fraction2)] / SPM % bioavailability/(Kd/1,000). (10)

The equation for the trophic-level (predatory to forage) fish 

model (TFM) is

predicted protective CSe dissolved = fish tissue guideline wb

 /TTFfishTL4/TTFfishTL3[(TTFinvert1*invert fraction1) 

 + (TTFinvert2*invert fraction2)]/SPM % bioavailability

 /(Kd/1,000). (11)

Modeled Bioaccumulation Potentials 

for Lake Koocanusa

Equations to calculate selenium BAPs as an intermediate 

numeric endpoint independent of setting (that is, Kd) for each 

of these models are

BAPIFM = (TTFfish) [(TTFinvert1*invert fraction1) 

 + (TTFinvert2*invert fraction2)], (12)

BAP TFM = (TTFfishTL4) (TTFfishTL3) [(TTFinvert1*invert 

 fraction1) + (TTFinvert2*invert fraction2)]. (13)

If SPM bioavailability (that is, with [w] bioavailability) is 

added as a factor in a composited BAP, then the equations are

BAPIFM w SPM bioavailability = (TTFfish) [(TTFinvert1*invert

 fraction1) + (TTFinvert2*invert fraction2)] (SPM % 

 bioavailability), (14)

BAPTFM w SPM bioavailability = (TTFfishTL4) (TTFfishTL3)

 [(TTFinvert1*invert fraction1) + (TTFinvert2*invert 

 fraction2)] (SPM % bioavailability). (15)

Applying the BAP equations to the species and diet 

categorizations shown in table 4 allows development of a 

set of scenarios within each model (tables 6 and 7, available 

for download at https://doi.org/10.3133/ofr20201098). 

As noted previously, specific species and scenarios for 

the IFM model are as follows: 100-percent aquatic insect 

(rainbow trout, Westslope cutthroat trout, redside shiner, 

longnose sucker), 50-percent aquatic insect and 50-percent 

zooplankton (peamouth chub, largescale sucker, mountain 

whitefish), 75-percent zooplankton and 25-percent aquatic 

insect (rainbow trout December–March), and 100-percent 

zooplankton (kokanee). The TFM scenarios for bull trout, 

burbot (winter and summer), and northern pikeminnow are as 

follows: 100-percent insectivores, 50-percent aquatic insect 

and 50-percent zooplankton, and 100-percent planktivores. 

Rainbow trout could be included in the latter category 

if a scenario was desired to include adult rainbow trout 

switching to a diet of 100-percent kokanee compared to an 

insectivorous diet.

The BAPs for IFM food-web scenarios range from 

3.08 to 1.65 at 100-percent bioavailability and from 1.85 to 

0.99 for 60-percent bioavailability (table 6). The scenario 

of kokanee ingesting a diet of 100-percent zooplankton 

represents a scenario where no bioaccumulation (BAP <1) is 

taking place. For TFM food-web scenarios, BAPs range from 

3.39 to 1.82 at 100-percent bioavailability and from 2.03 to 

1.09 for 60-percent bioavailability (table 7). Again, this last 

scenario (bull trout and burbot ingesting a diet of 100-percent 

planktivorous forage fish) is at the cusp of no bioaccumulation 

occurring; hence, choice of a fish species and its food web to 

represent the lake is a critical decision.
Gradient Map Perspectives 29

Illustrated Scenarios—Prediction of 

Protection for Westslope Cutthroat 

Trout, Rainbow Trout, Redside Shiner, 

Longnose Sucker, Bull Trout, and Burbot

Translation model equations for the IFM and 

TFM food-web scenarios are then applied to sites at the 

forebay, border, and SOE where data for paired selenium 

concentrations of dissolved and SPM are available to calculate 

observed, instantaneous Kd values (that is, within a common 

set of Kd values) (tables 8 and 9, available for download at 

https://doi.org/10.3133/ofr20201098). Given the importance 

of the dimensional nature of dissolved particulate material 

and SPM selenium concentrations in the lake (fig. 12A, B, 

and C), the modeling here does not statistically reduce the Kd

datasets; rather, each paired sampling event and consequent Kd

calculation is considered as an independent scenario (n=87). 

Using this all-encompassing set of available Kd values specific 

to timing, depth, and location, the range of values shows 

that 69 percent of values lie between 3,017 and 5,977, with 

the interval between 4,071 and 4,975 containing the greatest 

percentage (29 percent) (tables 8 and 9). The smallest Kd value 

in the observed data is 424, but only three observations are 

less than a Kd value of 1,000. The greatest value is 7,475, and 

only three observations are greater than 7,000.

The predictions for the illustrated food-web scenarios 

focus on protection of Westslope cutthroat trout, rainbow 

trout, redside shiner, and longnose sucker using the IFM 

and protection of bull trout and burbot using the TFM in 

accordance with one of the objectives of the proposed 

modeling (that is, a maximum dietary exposure through 

feeding within a benthic food web). Two SPM bioavailability 

factors (100 percent and 60 percent) are used within each 

food-web scenario to quantify the efficiency of assimilation of 

SPM by invertebrates.

Predicted protective dissolved selenium concentrations 

are based on a fish tissue wb guideline of 8.5 μg/g dw as the 

endpoint (tables 8 and 9). Egg-ovary tissue can be substituted 

if applicable tissue-to-tissue CFs are available (that is, 

species-specific extrapolations at a minimum, but ideally site 

specific if ecosystems are not degraded). As stated previously, 

the derived dissolved selenium concentration would 

quantify the ecosystem condition where fish would adhere 

to an 8.5-μg/g wb tissue guideline. Modeling shows that 

85–88 percent of predicted dissolved selenium concentrations 

are <1 μg/L for both the IFM and TFM with an assumption 

of 100-percent bioavailability. Using an assumption of 

60-percent bioavailability, 46–60 percent of values are 

<1 μg/L. From the perspective of a dissolved selenium 

concentration of <1.5 μg/L, the corresponding outcome ranges 

would be 91–93 percent for 100-percent bioavailability and 

78–85 percent for 60-percent bioavailability.

Species-Specific TTFfish for Predator 

and Forage Fish

These models can be further refined by substituting a 

species-specific TTFfish as provided by the USEPA (2016a). Using 

the IFM equation and an assumed Kd of 5,000, example scenarios 

for applicable fish species show the variation in predicted 

dissolved selenium concentrations when species-specific TTFfish

are applied and other modeling factors are held constant (table 10, 

available for download at https://doi.org/10.3133/ofr20201098).

Gradient Map Perspectives

Understanding the scientific basis of selenium ecological 

protection here includes connecting modeling outcomes and 

the representation of ecosystem conditions for Lake Koocanusa 

when deriving a water-column guideline or set of guidelines. The 

frequencies of occurrence of an assumed water-column condition, 

as discussed above, are only relevant within an understanding 

of the influences of hydrodynamics and source gradients on 

a chosen species and food web. Shown in figures 13–16 are a 

series of monthly (April–October) cross sections of observed 

dissolved selenium concentrations for 2016–19 that are examples 

of experimental plots of the type of conceptualization possible, 

but minimal data were available for building such plots. These 

constructs give time-, location-, and depth-specific contexts to 

conditions in the lake that overlap with modeling of food webs of 

the lake. The illustrated selenium cross sections are influenced by 

the hydrodynamic and biogeochemical cycles of the lake and the 

gradual dilution of selenium coming from the Elk River moving 

south in the lake; hence, comparison of dissolved selenium 

concentrations across years becomes meaningful when contoured 

to represent the dynamics of lake conditions. These contours also 

relate to interactions at the base of food webs and, hence, can 

elucidate modeling outcomes. These contours argue against using 

reductions of nonanchored (that is, nonlocation specific) dissolved 

selenium datasets because of the influences of the hydrologic 

setting of the lake, especially in terms of selection of Kd values for 

modeling predictions.

The constructs can be quantified by the cross-sectional 

area specific to a designated dissolved selenium concentration 

to illustrate existing conditions or adherence to a proposed 

guideline. In the example here, areas >1 μg/L are quantified 

for 2016–19 (fig. 17). Even though constructs are based on the 

relatively few available data points, seasonal trends are clear and 

the cross-sectional areas are seen to increase over the time period 

2016–19. Hence, if choices need to be made as the development of 

guidelines proceeds, this would be a methodology to meaningfully 

constrain data with the goal of identifying the time and place of 

greatest selenium sensitivity (that is, the ecological bottleneck). 

Going forward, this type of contouring can be used to project the 

effect of increases or decreases based on the current dissolved 

selenium conditions developed here.
30 Scientific Basis of Selenium Ecological Protection in Support of Site-Specific Guidelines Development

Figure 13. Cross sections of dissolved selenium concentrations from monitoring sites on Lake Koocanusa during calendar year 

2016. Contours based on two samples from each site. April selenium concentrations from the international boundary site are 

based on unfiltered water samples.

October FB

TM

IB

September FB

TM

IB

August FB

TM

IB

July FB

TM

IB

June FB

TM

IB

May FB

TM

IB

April

FB

TM

IB

EXPLANATION

FB Forebay

TM Tenmile Creek

IB International boundary

Selenium, in micrograms

per liter

Depth below water surface, in meters

100

80

60

40

20

0

100

80

60

40

20

0

0 10 20 30 40 50 60 70 80 90 0 10 20 30 40 50 60 70 80 90

0 10 20 30 40 50 60 70 80 90

Distance from Libby Dam, in kilometers

100

80

60

40

20

0

Distance from Libby Dam, in kilometers Distance from Libby Dam, in kilometers

≤0.70

0.86

1.02

1.18

1.34

≥1.50
Gradient Map Perspectives 31

Figure 14. Cross sections of dissolved selenium concentrations from monitoring sites on Lake Koocanusa during calendar 

year 2017. Contours based on one to three samples from each site.

October

FB

TM

IB

September

BE

FB

TM

IB

August

FB TM

IB

July

BE

FB

TM

IB

June

BE

FB

TM

IB

May

FB

TM

IB

April

FB

TM

IB

Depth below water surface, in meters

100

80

60

40

20

0

100

80

60

40

20

0

0 10 20 30 40 50 60 70 80 90

0 10 20 30 40 50 60 70 80 90

Distance from Libby Dam, in kilometers

100

80

60

40

20

0 0 10 20 30 40 50 60 70 80 90

Distance from Libby Dam, in kilometers Distance from Libby Dam, in kilometers

EXPLANATION

FB Forebay

TM Tenmile Creek

IB International boundary

BE Below Elk River inflow

Selenium, in micrograms

per liter

≤0.70

0.86

1.02

1.18

1.34

≥1.50
32 Scientific Basis of Selenium Ecological Protection in Support of Site-Specific Guidelines Development

Figure 15. Cross sections of dissolved selenium concentrations from monitoring sites on Lake Koocanusa during calendar year 

2018. Contours based on one to three samples from each site.

October

FB

TM

IB

BE

September

BE

FB

TM

IB

August

BE

FB

TM

IB

July

BE

FB

TM

IB

June

BE

FB

TM

IB

May FB

TM

IB

April FB

TM

IB

Depth below water surface, in meters

100

80

60

40

20

0

100

80

60

40

20

0

0 10 20 30 40 50 60 70 80 90 0 10 20 30 40 50 60 70 80 90

0 10 20 30 40 50 60 70 80 90

Distance from Libby Dam, in kilometers

Distance from Libby Dam, in kilometers Distance from Libby Dam, in kilometers

100

80

60

40

20

0

EXPLANATION

FB Forebay

TM Tenmile Creek

IB International boundary

BE Below Elk River inflow

Selenium, in micrograms

per liter

≤0.70

0.86

1.02

1.18

1.34

≥1.50
Gradient Map Perspectives 33

Figure 16. Cross sections of dissolved selenium concentrations from monitoring sites on Lake Koocanusa during calendar 

year 2019. Contours based on two to three samples from each site. No samples were collected from the Tenmile Creek site 

during May due to equipment problems.

October FB

TM

IB

BE

September FB

TM

IB

BE

August FB TM

IB

BE

July FB

TM

IB

BE

June FB

TM

IB

BE

May FB

IB

April FB

TM

IB

BE

EXPLANATION

FB Forebay

TM Tenmile Creek

IB International boundary

BE Below Elk River inflow

Selenium, in micrograms

per liter

Depth below water surface, in meters

100

80

60

40

20

0

100

80

60

40

20

0

0 10 20 30 40 50 60 70 80 90 0 10 20 30 40 50 60 70 80 90

0 10 20 30 40 50 60 70 80 90

Distance from Libby Dam, in kilometers

100

80

60

40

20

0

Distance from Libby Dam, in kilometers Distance from Libby Dam, in kilometers

≤0.70

0.86

1.02

1.18

1.34

≥1.50
34 Scientific Basis of Selenium Ecological Protection in Support of Site-Specific Guidelines Development

Conclusions

This working report and accompanying USGS data release 

(Presser and Naftz, 2020) provide the data, rationale, food-web 

modeling structure, and interactive spreadsheets for the 

quantitative derivation of site-specific selenium guidelines for 

Lake Koocanusa. Model scenarios and gradient maps presented 

here represent the lake’s ecosystem that is the link between 

the designated protective fish-tissue selenium concentration 

guideline and the modeled predictions of protective dissolved 

selenium concentrations. Model predictions for protective 

dissolved selenium concentrations are specific to the USEPA’s 

national guideline of 8.5 μg/g wb fish tissue, but the model 

outcomes can be modified to numerically support BCMOE’s 

guideline of 4 μg/g wb by dividing by a factor of 2.125 (that is, 

8.5/4). However, as stated previously, the tissue guidelines were 

derived with different protection goals.

Modeling of selenium overlays cumulative effects in the 

reservoir of (1) dam operation itself, (2) mitigation actions, and 

(3) its impaired selenium status for aquatic life designated in 2012 

as coal mining continues to expand in the Elk Valley region of 

British Columbia over the last 35 years. Concerns encompass 

fish-community changes, flow regime changes, and such 

ecological stressors as parasitic infection, gonadal dysfunction, 

and mercury-selenium interactions. The cumulative effects related 

to fish species were found to have affected the fundamental 

processing of selenium through food webs, which did have 

ramifications for data utility, choices for model validation, and 

connection to a reproductive selenium endpoint.

Our previously listed goals (see “Introduction” section) 

guided our choices and assumptions used in illustrating Lake 

Koocanusa’s ecosystem and modeling its dietary dynamics. Two 

models address protection of benthic feeders within the overall 

goal of identifying food webs with maximum BAPs (that is, 

maximum dietary exposure). As categorized and constructed, 

(1) the IFM protects a community of rainbow trout, Westslope 

cutthroat trout, redside shiner, and longnose sucker and (2) the 

TFM protects a community of bull trout and burbot. Constraining 

the variables for identification of sensitive locations and seasons 

to represent Lake Koocanusa led to a lake-gradient approach. In 

this approach, each paired sampling event of water-column and 

SPM and the consequent Kd calculation was considered as an 

independent scenario. Where data were most abundant for pivotal 

sites (forebay and SOE), temporal gradient maps of dissolved and 

SPM selenium concentrations and ecological partitioning factors 

(Kd values) specific to lake strata, hydrodynamics, and source 

gradient were constructed. These experimental plots show the kind 

of conceptualization possible when considering lake dynamics in 

general and connecting to selenium dynamics at the base of food 

webs in particular.

The results of our analysis and illustrated modeling scenarios 

show that at least 78 percent of predictions are <1.5 μg/L and at 

least 46 percent of predictions are <1 μg/L for protection of this 

community of core benthic feeders. The percentages are based on 

exposure through a 100-percent chironomid diet and two choices 

of bioavailability (100 percent and 60 percent for SPM); hence, 

these scenarios represent conservative, but realistic, choices 

within the set of 12 categorized fish species. Switching from an 

assumed guideline of 8.5 μg/g to 4 μg/g would decrease each 

individual model prediction, as stated previously, by a factor of 

approximately two.

To give context to this range of tested designated 

dissolved selenium concentrations, 1.5 μg/L is the USEPA’s 

national guideline derived for lentic systems. The range in 

comparison to recent conditions in Lake Koocanusa (fig. 17) 

0

1

2

3

4

2016 2017 2018 2019

Date

2016 2017 2018 2019

0

5

10

15

20

Calendar year

Monthly cross-sectional area with selenium greater 

than 1 microgram per liter, in square kilometers

Cross-sectional area (April–October) of selenium

greater than 1 microgram per liter, 

in square kilometers

A B

Figure 17. Graphs showing (A) monthly cross-sectional areas (2016–19, April–October) in Lake Koocanusa specific to a dissolved selenium 

concentration of greater than 1 microgram per liter for 2016–19 from the international boundary to Libby Dam and showing (B) annual summation 

of monthly cross-sectional areas specific to a dissolved selenium concentration of greater than 1 microgram per liter. Graph B indicates an 

annual increase from 2016 to 2019.
References Cited 35

shows that during 2016 and 2017, cumulative cross-sectional 

areas with selenium concentrations exceeding 1 μg/L in the 

reservoir south of the international border were <5 square 

kilometers (km2). During 2018, a more than threefold 

increase in the cross-sectional area (>15 km2) exceeding 

1 μg/L of dissolved selenium was observed, followed by a 

more than fourfold increase (about 20 km2) in 2019. These 

recent increases in the proportion of the reservoir containing 

selenium concentrations exceeding 1 μg/L indicate a system 

that is not at a steady state and raises concerns over the 

likelihood of continuing future increases.

The outcomes of formal protocols (for example, the USEPA’s 

recalculation procedure [USEPA, 2016d]) for addressing the 

ecotoxicological sensitivity of an assemblage of site-specific fish 

species are not publicly available for Lake Koocanusa. However, 

a practical, qualitative ranking of fish species can be achieved 

through the metric of vulnerability, which combines inherent 

selenium sensitivity and exposure through diet. This assessment 

is informed by (1) the site-specific analysis of the fish traits 

and connectivity to behavioral ecology of predators shown in 

table 1, (2) the ranking of fish species listed in USEPA (2016a, 

see table 3.1) and in other reviews (for example, Janz and others, 

2010, see figures 6.4), and (3) recent studies of Danio rerio

(zebrafish) documenting the elevated sensitivity of this species 

of Cyprinid (Thomas and Janz, 2014, 2015; Penglase and others, 

2014a,b). Our example of ranking based on species vulnerability 

is included as a working part of this report, which can be updated 

in the future when a formal analysis by regulatory agencies is 

prepared as guideline development proceeds.

Near the top of a vulnerability ranking would be concern 

for the Cyprinids of Lake Koocanusa (that is, redside shiner, 

peamouth chub, and northern pikeminnow) based on sensitivity 

and for burbot given its demersal feeding and winter spawning 

period. Redside shiner and peamouth chub as representative of 

Cyprinids would be interesting choices of species to protect as 

examples of small-bodied fish with 100-percent and 50-percent 

benthic diets, respectively (table 4). Concern for burbot is also 

anecdotally corroborated by the lack of fish caught in recent 

monitoring efforts and the fact that extensive drawdown occurs 

during the spawning season for this species. White sturgeon, 

although not residing in the lake, does inhabit waters downstream 

from the dam and is the most toxicologically sensitive fish as 

ranked by the USEPA in its national guidance (USEPA, 2016a); 

hence, extending protection to waters and habitat immediately 

downstream from the dam would seem advisable. Less concern 

would be for bull trout and mountain whitefish, which appear at 

the bottom of the sensitivity ranking (USEPA, 2016a). This leaves 

considering protection for remaining species such as rainbow trout 

and Westslope cutthroat trout, which rank near the middle of the 

sensitivity scale and are benthic feeders. Here too for these species, 

the percentages of composition among Lake Koocanusa species 

are low during spring and fall (fig. 6A, B).

In sum, this subset of modeling variables, species, and 

attributes appears to meet the specific goals set out at the 

beginning, which also impinge on operational interests. These 

considerations connect to specific scenarios and supporting 

rationales to represent the system. Going forward, qualifying 

the status of the Lake Koocanusa ecosystem within an 

impairment-restoration cycle would acknowledge concerns 

about using current conditions as a baseline for regulatory 

actions because of possible survivor bias and normalization 

of ecosystem degradation and dysfunction. Considerations 

for future endpoint and modeling-related actions include 

development of (1) a series of health endpoints related not only 

to long-term exposure to selenium, but also to food sources and 

fish communities; (2) a coordinated selenium portal where data 

are arranged within a set format specific to Lake Koocanusa’s 

food webs; (3) a comprehensive plan for taxa-specific selenium 

analysis of invertebrates; and (4) a strategy for filling the data 

gaps for selenium in samples of expressed eggs for fish species 

and studying the occurrence of deformities in developing 

larvae. In reference to these latter considerations, focus for 

monitoring would be on the main drivers of the outcomes of 

ecosystem-scale selenium modeling: (1) type of particulate 

material (SPM in the case here), (2) selenium concentration 

and speciation of the particulate material that is food for 

invertebrates, and (3) taxa of invertebrates consuming that 

food. Monitoring of dissolved selenium concentrations on a 

high-frequency basis (for example, USGS platform data) at 

several key sites across the reservoir would help to further 

develop seasonal spatial selenium gradients and to understand 

process-level relationships in order to pinpoint and assess sites 

consequential to defining future regulatory compliance.

References Cited

Baranowska, K., 2018, Koocanusa Reservoir food web 

amendment: Cranbrook, B.C., prepared by Lotic Environmental 

Ltd., 21 p.

Baranowska, K., and Robinson, M.D., 2017, Koocanusa Reservoir 

food web model—Final report: Cranbrook, B.C., prepared by 

Lotic Environmental Ltd., 48 p.

Bonneville Power Administration, U.S. Army Corps of Engineers, 

North Pacific Division, U.S. Department of Interior, and 

Bureau of Reclamation, Interagency Team, 1995, Columbia 

River System Operation Review—Final Environmental 

Impact Statement, appendix K, resident fish: U.S. Government 

Printing Office, No. DOE/EIS–0170, 297 p. [Also available at 

https://usace.contentdm.oclc.org/digital/collection/p16021coll7/

id/6482/.]

British Columbia Ministry of Environment [BCMOE], 

2014, Ambient water quality guidelines for selenium 

technical report update: Water Protection and Sustainability 

Branch, Environmental Sustainability and Strategic Policy 

Division, Victoria, B.C., p. 1–270, accessed May 2020 at 

https://www2.gov.bc.ca/assets/gov/environment/air-land-water/

water/waterquality/water-quality-guidelines/approved-wqgs/bc_

moe_se_wqg.pdf.
36 Scientific Basis of Selenium Ecological Protection in Support of Site-Specific Guidelines Development

British Columbia Ministry of Environment [BCMOE], 2015, 

Reports and references for Lota lota pop. 1 (Burbot, Lower 

Kootenay Population): Government of British Columbia web 

page, accessed May 2020 at http://a100.gov.bc.ca/pub/acat/

public/viewReport.do?reportId=9720.

British Columbia Ministry of Environment [BCMOE], 2018, 

Environmental Management Act Permit 107517 and 

AMS107517, Authorizing Effluent Discharges from Five 

Steelmaking Coal Operations in the Elk Valley; British 

Columbia Gazette, Vol CLIV, No. 40, Victoria, B.C., 2014 and 

amended 2018, accessed May 2020 at https://www.bclaws.ca/

civix/document/id/bcgaz1/bcgaz1/279370937.

 Chapman, P.M., Adams, W.J., Brooks, M., Delos, C.G., Luoma, 

S.N., Maher, W.A., Ohlendorf, H.M., Presser, T.S., and Shaw, 

P., eds., 2010, Ecological assessment of selenium in the 

aquatic environment: Boca Raton, Fla., CRC Press, 368 p., 

https://doi.org/10.1201/EBK1439826775.

Chisholm, I., and Hamlin, P., 1987, 1985 Libby Reservoir Angler 

Census—May 13–October 31, 1987 [ie 1985]: Kalispell, Mont., 

Montana Department of Fish, Wildlife and Parks, Interim 

Report (No. DOE/BP–12660–4) 106 p. [Also available at 

https://www.osti.gov/biblio/5494223.]

Chisholm, I., Hensler, M.E., Hansen, B., and Skaar, D., 

1989, Quantification of Libby Reservoir water levels 

needed to maintain or enhance reservoir fisheries—

Methods and data summary, 1983–1987: Kalispell, Mont., 

Montana Fish, Wildlife, and Parks, Bonneville Power 

Administration Project no. 83–467, 272 p. [Also available 

at http://docs.streamnetlibrary.org/BPA_Fish_and_Wildlife/

12660-5.pdf.]

Dalbey, S., DeShazer, J., Garrow, L., Hoffman, T., and Ostrowski, 

T., 1998, Quantification of Libby Reservoir water levels 

needed to maintain or enhance reservoir fisheries: Libby, 

Mont., Montana Fish, Wildlife, and Parks, Bonneville Power 

Administration Project no. 83–467, 117 p. [Also available at 

https://www.cbfish.org/Document.mvc/Viewer/12660-7.]

Dunnigan, J.L., DeShazer, J., Ostrowski, T., Benner, M., 

Lampton, J., Garrow, L., Tohtz, J., and Boyer, M., 2017, 

Mitigation for the construction and operation of Libby 

Dam—Annual Report 2016: Libby, Mont., Montana Fish, 

Wildlife and Parks, Bonneville Power Administration 

Project no. 1995–004–00, 270 p. [Also available at 

https://www.cbfish.org/Document.mvc/Viewer/P154535.]

Dunnigan, J.L., DeShazer, J., Ostrowski, T., Benner, M., 

Lampton, J., Garrow, L., Frye, J., Gabreski, C., and Boyer, M., 

2020, Mitigation for the construction and operation of Libby 

Dam—Draft Annual Report 2019: Libby, Mont., Montana 

Fish, Wildlife and Parks, Bonneville Power Administration 

Project no. 1995–004–00, 365 p. [Also available at 

https://www.cbfish.org/Document.mvc/Viewer/P171660.]

Easthouse, K., 2013, Libby Dam—Kootenai River and Lake 

Koocanusa water quality sampling and analysis plan 2013: 

Seattle, Wash., U.S. Army Corps of Engineers, 20 p., accessed 

May 2020 at https://usace.contentdm.oclc.org/digital/collection/

p266001coll1/id/8870.

Hauer, F.R., and Stanford, J.A., 1997, Long-term influence of 

Libby Dam operation on the ecology of macrozoobenthos 

of the Kootenai River, Montana and Idaho: Polson, Mont., 

Flathead Lake Biological Station, Open-File Report 

141–97, 80 p.

Holderman, C., Hoyle, G., Hardy, R., Anders, P., Ward, P., 

and Yassien, H., 2009, Libby Dam Hydro-electric Project 

mitigation—Efforts for downstream ecosystem restoration: 

Vancouver, B.C., Section C–4 of 33d International 

Association of Hydraulic Engineering and Research 

Congress, p. 6214–6222.

Horowitz, A.J., 1986, Comparison of methods for the 

concentration of suspended sediment in river water of 

subsequent chemical analysis: Environmental Science & 

Technology, v. 20, no. 2, p. 155–160. [Also available at 

https://doi.org/10.1021/es00144a007.]

Horowitz, A.J., Elrick, K.A., and Smith, J.J., 2001, Estimating 

suspended sediment and trace element fluxes in large river 

basins—Methodological considerations as applied to the 

NASQAN programme: Hydrological Processes, v. 15, no. 7, 

p. 1107–1132. [Also available at https://doi.org/10.1002/

hyp.206.]

Horowitz, A.J., Elrick, K.A., and Smith, J.J., 2008, Monitoring 

urban impacts on suspended sediment, trace element, and 

nutrient fluxes within the City of Atlanta, Georgia, USA—

Program design, methodological considerations, and initial 

results: Hydrological Processes, v. 22, no. 10, p. 1473–1496. 

[Also available at https://doi.org/10.1002/hyp.6699.]

Idaho Department of Fish and Game, 2008, Ecosystem 

rehabilitation study of the Kootenai River Investigations: 

Boise, Idaho, Ecosystem Rehabilitation Project Progress 

Report 2005–2007, Idaho Department of Fish and Game 

report no. 08–11, 61 p.

Janz, D.M., 2011, Selenium, in Wood, C.W., Farrell, A.P., and 

Brauner, C.J., eds., Fish physiology—Homeostasis and 

toxicology of essential metals: Academic Press, v. 31, part A, 

p. 327–374. [Also available at https://doi.org/10.1016/S1546-

5098(11)31007-2.]

Janz, D.M., DeForest, D.K., Brooks, M.L., Chapman, P.M., 

Gilron, G., Hoff, D., Hopkins, W.A., McIntyre, D.O., Mebane, 

C.A., Palace, V.P., Skorupa, J.P., and Wayland, M., 2010, 

Selenium toxicity to aquatic organisms, in Chapman, P.M., 

Adams, W.J., Brooks, M., Delos, C.G., Luoma, S.N., Maher, 

W.A., Ohlendorf, H.M., Presser, T.S., and Shaw, P., eds., 

Ecological assessment of selenium in the aquatic environment: 

Boca Raton, Fla., CRC Press, p. 141–231.
References Cited 37

Jenni, K.E., Naftz, D.L., and Presser, T.S., 2017, Conceptual 

modeling framework to support development of site-specific 

selenium criteria for Lake Koocanusa, Montana, U.S.A., and 

British Columbia, Canada: U.S. Geological Survey Open-File 

Report 2017–1130, 14 p. [Also available at https://doi.org/

10.3133/ofr20171130.]

Lemly, A.D., and Skorupa, J.P., 2007, Technical issues affecting 

the implementation of U.S. Environmental Protection Agency’s 

proposed fish tissue-based aquatic criterion for selenium: 

Integrated Environmental Assessment and Management, v. 3, 

no. 4, p. 552–558. [Also available at https://doi.org/10.1897/

IEAM_2007-024.1.]

Luoma, S.N., and Presser, T.S., 2009, Emerging opportunities 

in management of selenium contamination: Environmental 

Science & Technology, v. 43, no. 22, p. 8483–8487. [Also 

available at https://doi.org/10.1021/es900828h.]

Luoma, S.N., and Presser, T.S., 2018, Status of selenium in south 

San Francisco Bay—A basis for modeling potential guidelines 

to meet National tissue criteria for fish and a proposed wildlife 

criterion for birds: U.S. Geological Survey Open-File Report 

2018–1105, 75 p. [Also available at https://doi.org/10.3133/

ofr20181105.]

Luoma, S.N., and Rainbow, P.S., 2005, Why is metal 

bioaccumulation so variable? Biodynamics as a unifying 

concept: Environmental Science & Technology, v. 39, no. 7, 

p. 1921–1931. [Also available at https://doi.org/10.1021/

es048947e.]

Mæhre, H.K., Hamre, K., and Elvevoll, E.O., 2012, Nutrient 

evaluation of rotifers and zooplankton—Feed for marine fish 

larvae: Aquaculture Nutrition, v. 19, no. 3, p. 301–311. [Also 

available at https://doi.org/10.1111/j.1365-2095.2012.00960.x.]

Montana Department of Environmental Quality [MTDEQ], 

2018, Appendices A–J of Final 2018 water quality integrated 

report: Helena, Montana Department of Environmental 

Quality, 72 p., accessed May 2020, at http://deq.mt.gov/Water/

Resources/report.

Montana Department of Environmental Quality [MTDEQ], 2019, 

Montana numeric water quality standards: Helena, Mont., 

Montana Department of Environmental Quality, Water Quality 

Planning Bureau, Water Quality Standards and Modeling 

Section, Circular DEQ–7, 80 p., accessed May 2020 at 

https://deq.mt.gov/Portals/112/Water/WQPB/Standards/PDF/

DEQ7/DEQ-7.pdf.

Nagpal, N.K., and Howell, K., 2001, Water quality guidelines 

for selenium—Technical appendix: Victoria, B.C., Ministry 

of Water, Land and Air Protection, Water Protection Branch, 

27 p., accessed May 2020 at http://www.speciation.net/

Database/Links/Government-of-British-ColumbiaMinistry-of-Environment-Water-Quality-Guidelines-forSelenium-;i374.

Osmundson, B., and Skorupa, J., 2011, CO-Selenium in fish 

tissue—Prediction equations for conversion between whole 

body, muscle, and eggs: U.S. Fish and Wildlife Service, Project 

FFS ID 6F50, 49 p.

Penglase, S., Hamre, K., and Ellingsen, S., 2014a, Selenium 

and mercury have a synergistic negative effect on fish 

reproduction: Aquatic Toxicology (Amsterdam, Netherlands), 

v. 149, p. 16–24. [Also available at https://doi.org/10.1016/

j.aquatox.2014.01.020.]

Penglase, S., Hamre, K., Rasinger, J.D., and Ellingsen, S., 

2014b, Selenium status affects selenoprotein expression, 

reproduction, and F1 generation locomotor activity in 

zebrafish (Danio rerio): British Journal of Nutrition, v. 111, 

no. 11, p. 1918–1931. [Also available at https://doi.org/

10.1017/S000711451300439X.]

Presser, T.S., 2013, Selenium in ecosystems within the 

mountaintop coal mining and valley-fill region of southern 

West Virginia—Assessment and ecosystem-scale modeling: 

U.S. Geological Survey Professional Paper 1803, 86 p., 

accessed April 2020 at https://doi.org/10.3133/pp1803.

Presser, T.S., and Luoma, S.N., 2010a, A methodology 

for ecosystem-scale modeling of selenium: Integrated 

Environmental Assessment and Management, v. 6, no. 4, 

p. 685–710. [Also available at https://doi.org/10.1002/

ieam.101.]

Presser, T.S., and Luoma, S.N., 2010b, Ecosystem-scale selenium 

modeling in support of fish and wildlife criteria development 

for the San Francisco Bay-Delta Estuary, California: U.S. 

Geological Survey Administrative Report, prepared for 

and released by U.S. Environmental Protection agency, 

Region 9, San Francisco, Calif., 46 p., accessed July 2020 

at https://archive.epa.gov/region9/water/archive/web/pdf/

selenium-modeling_admin-report.pdf.

Presser, T.S., and Luoma, S.N., 2013, Ecosystem-scale 

selenium model for the San Francisco Bay-Delta Regional 

Ecosystem Restoration Implementation Plan (DRERIP): 

San Francisco Estuary and Watershed Science, v. 11, 

no. 1, p. 1–39. [Also available at https://doi.org/10.15447/

sfews.2013v11iss1art2.]

Presser, T.S., and Naftz, D.L., 2020, Selenium concentrations 

in food webs of Lake Koocanusa in the vicinity of Libby 

Dam (MT) and the Elk River (BC) as the basis for applying 

ecosystem-scale modeling, 2008–2018: U.S. Geological Survey 

data release, https://doi.org/10.5066/P9VXYSNZ.

Presser, T.S., Naftz, D.L., and Jenni, K.E., 2018, USGS 

measurements of dissolved and suspended particulate 

material selenium in Lake Koocanusa in the vicinity of Libby 

Dam (MT), 2015–2017 (update): U.S. Geological Survey 

data release, accessed May 2020 at https://doi.org/10.5066/

P9HB5S5F.
38 Scientific Basis of Selenium Ecological Protection in Support of Site-Specific Guidelines Development

Presser, T.S., Piper, D.Z., Bird, K.J., Skorupa, J.P., Hamilton, 

S.J., Detwiler, S.J., and Huebner, M.A., 2004, The 

Phosphoria Formation—A model for forecasting global 

selenium sources to the environment, in Hein, J.R., ed., Life 

cycle of the Phosphoria Formation—From deposition to the 

post-mining environment: New York, Elsevier, p. 299–319.

 Reiley, M.C., Stubblefield, W.A., Adams, W.J., Di Toro, 

D.M., Hodson, P.V., Erickson, R.J., and Keating, F.J., Jr., 

eds., 2003, Reevaluation of the state of the science for 

water-quality criteria development: Pensacola, Fla., Society 

of Environmental Toxicology and Chemistry Press, 224 p.

Richards, D., 1997, Kootenai River biological baseline 

status report: Portland, Oreg., U.S. Department of Energy, 

Bonneville Power Administration, Environment, Fish 

and Wildlife, Project no. 94–49, 71 p. [Also available at 

https://www.cbfish.org/Document.mvc/Viewer/40364-1.]

Schlekat, C.E., Purkerson, D.G., and Luoma, S.N., 

2004, Modeling selenium bioaccumulation through 

arthropod food webs in San Francisco Bay, California, 

USA: Environmental Toxicology and Chemistry, v. 23, 

no. 12, p. 3003–3010. [Also available at https://doi.org/

10.1897/03-4.1.]

Teck Coal Ltd., 2014, Elk Valley Water Quality Plan: 

Sparwood, B.C., Teck Coal Ltd., 290 p., accessed May 2020 

at https://www2.gov.bc.ca/gov/content/environment/wastemanagement/industrial-waste/mining-smelting/teck-areabased-management-plan.

Teck Coal Ltd., 2015, Burbot monitoring in Lake Koocanusa, 

2014 and 2015: Sparwood, B.C., Teck Coal Ltd., 

prepared by Minnow Environmental, Inc., Georgetown, 

Ontario, 86 p.

Teck Coal Ltd., 2018a, Koocanusa Reservoir monitoring 

report, 2014 to 2016: Sparwood, B.C., Teck Coal Ltd., 

prepared by Minnow Environmental, Inc., 655 p., accessed 

May 2020 at https://www.teck.com/media/KoocanusaReservoir-Monitoring-Report,-2014-to-2016.pdf.

Teck Coal Ltd., 2018b, Permit 107517—2017 summary 

report of monitoring results in the Koocanusa Reservoir—

Sparwood. B.C., Teck Coal Ltd., 97 p. [Also available at 

https://www.teck.com/media/Koocanusa-Water-Quality2017-Report.pdf.]

Teck Coal Ltd., 2019, Koocanusa Reservoir monitoring report, 

2018: Sparwood, B.C., Teck Coal Ltd., prepared by Minnow 

Environmental Inc., Georgetown, Ontario, 632 p., accessed 

May 2020 at https://www.teck.com/media/KoocanusaReservoir-Monitoring-2018-Report.pdf.

Thomas, J.K., and Janz, D.M., 2014, In ovo exposure to 

selenomethionine via maternal transfer increases developmental 

toxicities and impairs swim performance in F1 generation 

zebrafish (Danio rerio): Aquatic Toxicology (Amsterdam, 

Netherlands), v. 152, p. 20–29. [Also available at https://doi.org/

10.1016/j.aquatox.2014.03.022.]

Thomas, J.K., and Janz, D.M., 2015, Developmental and 

persistent toxicities of maternally deposited selenomethionine in 

zebrafish (Danio rerio): Environmental Science & Technology, 

v. 49, no. 16, p. 10182–10189. [Also available at https://doi.org/

10.1021/acs.est.5b02451.]

U.S. Environmental Protection Agency [USEPA], 2016a, 

Aquatic life ambient water quality criterion for selenium—

Freshwater: Washington, D.C., U.S. Environmental Protection 

Agency, EPA 822–R–16–006), 807 p., accessed May 2020 at 

https://www.epa.gov/sites/production/files/2016-07/documents/

aquatic_life_awqc_for_selenium_-_freshwater_2016.pdf.

U.S. Environmental Protection Agency [USEPA], 2016b, 

Technical support for fish tissue monitoring for implementation 

of EPA’s 2016 selenium criterion: U.S. Environmental 

Protection Agency, EPA 820–F–16–007, 49 p., accessed May 

2020 at https://archive.epa.gov/epa/sites/production/files/

2016-10/documents/technical-support-fish-tissue-monitoringselenium.pdf.

U.S. Environmental Protection Agency [USEPA], 2016c, Water 

quality standards—Establishment of revised numeric criteria 

for selenium for the San Francisco Bay and Delta, State of 

California: Federal Register, v. 81, no. 178, p. 46030–46042, 

accessed May 2020 at https://www.federalregister.gov/d/

2016-22087.

U.S. Environmental Protection Agency [USEPA], 2016d, 

Technical support for adopting and implementing EPA’s 2016 

selenium criterion in water quality standards: Washington, D.C., 

U.S. Environmental Protection Agency, 16 p., accessed May 

2020 at https://archive.epa.gov/epa/sites/production/files/2016-

10/documents/technical-support-adoption-implementationselenium.pdf.

U.S. Environmental Protection Agency [USEPA], 2018, Water 

quality standards—Establishment of a numeric criterion 

for selenium for the State of California: Federal Register, 

v. 83, no. 239, p. 64059–64078, accessed May 2020 at 

https://www.federalregister.gov/d/2018-26781.

U.S. Fish and Wildlife Service [USFWS], 1998, Endangered and 

threatened wildlife and plants—Determination of threatened 

status for the bull trout in the conterminous United States: 

Federal Register, v. 64, no. 210, p. 58910–58933, accessed May 

2020 at https://www.federalregister.gov/d/99-28295.
References Cited 39

U.S. Fish and Wildlife Service [USFWS], 1999, Recovery 

plan for the Kootenai River population of the white sturgeon 

(Acipenser transmontanus): Portland, Oreg., U.S. Fish and 

Wildlife Service, 96 p. plus appendixes.

U.S. Fish and Wildlife Service [USFWS], 2012, Technical 

Review—Smoky Canyon Mine site-specific selenium 

criterion report: Denver, Colo., Division of Environmental 

Quality, Environmental Contaminants Program, 154 p.

VAST Resource Solutions Inc, 2017, Lake Koocanusa foreshore 

inventory and mapping and aquatic habitat index: VAST 

Resource Solutions, Inc., prepared for East Kootenay Integrated 

Lake Management Partnership, 155 p., accessed May 2020 

at https://westsidekoocanusa.wildapricot.org/resources/

Documents/EKIMP%20ForeShore%20Mapping%20Mgmt_

FINAL_Oct%2017.pdf.

Woods, P.F., 1982, Annual nutrient loadings, primary productivity, 

and trophic state of Lake Koocanusa, Montana and British 

Columbia, 1972–80: U.S. Geological Survey Professional Paper 

1283, 24 p. [Also available at https://doi.org/10.3133/pp1283.]

Woods, P.F., and Falter, C.M., 1982, Limnological 

investigations—Lake Koocanusa, Montana—Part 4, factors 

controlling primary productivity: Seattle, Wash., U.S. Army 

Corps of Engineers, Special Report 82–15, 106 p., accessed 

May 2020 at https://hdl.handle.net/11681/12346.
40 Scientific Basis of Selenium Ecological Protection in Support of Site-Specific Guidelines Development

Appendix Supplementary References

Tapeworm and Nematode

Carter, V., Pierce, R., Dufour, S., Arme, C., and Hoole, 

D., 2006, The tapeworm Ligula intestinalis (Cestoda—

Pseudophyllidea) inhibits LH expression and puberty in 

its teleost host, Rutilus rutilus: Reproduction (Cambridge, 

England), v. 130, no. 6, p. 939–945. [Also available at 

https://doi.org/10.1530/rep.1.00742.]

Hursky, O., and Pietrock, M., 2015, Intestinal nematodes affect 

selenium bioaccumulation, oxidative stress biomarkers, and 

health parameters in juvenile rainbow trout (Oncorhynchus 

mykiss): Environmental Science & Technology, v. 49, no. 4, 

p. 2469–2476. [Also available at https://doi.org/10.1021/

es5048792.]

Mahon, R., 1976, Effect of the cestode Ligula intestinalis on 

spottail shiners, Notropis hudsonius: Canadian Journal of 

Zoology, v. 54, no. 12, p. 2227–2229. [Also available at 

https://doi.org/10.1139/z76-254.]

Majdi, N., and Traunspurger, W., 2015, Free-living nematodes in the freshwater food web—A review: Journal of 

Nematology, v. 47, no. 1, p. 28–44.

Teck Coal Ltd., 2018a, Koocanusa Reservoir monitoring 

report, 2014 to 2016: Sparwood, B.C., Teck Coal Ltd., 

prepared by Minnow Environmental, Inc., 655 p., accessed 

May 2020 at https://www.teck.com/media/KoocanusaReservoir-Monitoring-Report,-2014-to-2016.pdf.

Mercury and Selenium

Canadian Council of Ministers of the Environment, 2000, 

Canadian tissue residue guidelines for the protection of 

wildlife consumers of aquatic biota—Methylmercury: 

Winnipeg, Ontario, Canadian Environmental Quality 

Guidelines, Canadian Council of Ministers of the 

Environment, 7 p.

Heinz, G.H., and Hoffman, D.J., 1998, Methylmercury 

chloride and selenomethionine interactions on health and 

reproduction in mallards: Environmental Toxicology and 

Chemistry, v. 17, no. 2, p. 139–145. [Also available at 

https://doi.org/10.1002/etc.5620170202.]

Montana Department of Fish, Wildlife and Parks, Montana 

Department of Environmental Quality, and Montana 

Department of Health and Human Services, 2014, Montana 

Sport Fish Consumption Guidelines (updated 2015): 

Montana Department of Fish, Wildlife and Parks, Montana 

Department of Environmental Quality, and Montana 

Department of Health and Human Services, 11 p.

Penglase, S., Hamre, K., and Ellingsen, S., 2014, Selenium 

and mercury have a synergistic negative effect on fish 

reproduction: Aquatic Toxicology, v. 149, p. 16–24. [Also 

available at https://doi.org/10.1016/j.aquatox.2014.01.020.]

Cyprinids

Janz, D.M., DeForest, D.K., Brooks, M.L., and Chapman, 

P.M., 2010, Selenium toxicity to aquatic organisms, in

Chapman, P.M., Adams, W.J., Brooks, M.L., Delos, C.G., 

Luoma, S.N., Maher, W.A., Ohlendorf, H.M., Presser, 

T.S., and Shaw, D.P., eds., Ecological assessment of 

selenium in the aquatic environment: Pensacola, Fla., 

Society of Environmental Toxicology and Chemistry Press, 

p. 141–231.

U.S. Environmental Protection Agency, 2016, Technical support for fish tissue monitoring for implementation of EPA’s 

2016 selenium criterion: U.S. Environmental Protection 

Agency, EPA 820–F–16–007, 49 p., accessed May 2020 

at https://archive.epa.gov/epa/sites/production/files/2016-

10/documents/technical-support-fish-tissue-monitoringselenium.pdf.

Rotifers

Mæhre, H.K., Hamre, K., and Elvevoll, E.O., 2012, Nutrient 

evaluation of rotifers and zooplankton—Feed for marine 

fish larvae: Aquaculture Nutrition, v. 19, no. 3, p. 301–311. 

[Also available at https://doi.org/10.1111/j.1365-

2095.2012.00960.x.]
For more information about this publication, contact:

Director, USGS Water Mission Area

345 Middlefield Rd.

Menlo Park, CA 94025

Publishing support provided by the Menlo Park and Rolla Publishing 

Service Centers
Presser and Naftz—Scientific Basis of Selenium Ecological Protection in Support of Site-Specific Guidelines Development—OFR 2020–1098

ISSN 2331-1258 (online)

https://doi.org/10.3133/ofr20201098