r/EPA
EPA/1 OO/R-09/006 | October 2009
www.epa.gov/osa
United States
Environmental Protection
Agency
Summary Report:
Risk Assessment Forum Technical
Workshop on Population-level
Ecological Risk Assessment
Supplementary Material:
Workshop Presentations
Office of the Science Advisor
Risk Assessment Forum
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Summary Report:
Risk Assessment Forum Technical
Workshop on Population-level
Ecological Risk Assessment
Supplementary Material:
Workshop Presentations
Risk Assessment Forum
U.S. Environmental Protection Agency
Washington, DC 20460
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NOTICE
The statements in this report reflect the individual expert views and opinions of the workshop attendees,
together with summary observations and recommendations of an Agency technical panel. They do not represent
analyses or positions of the Risk Assessment Forum or of the U.S. Environmental Protection Agency.
This document has been reviewed in accordance with U.S. Environmental Protection Agency policy. Mention
of trade names or commercial products does not constitute endorsement or recommendation for use.
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Breakout Group Charge
RAF's Activities in Ecological
Risk Assessment
June 16,2008
Elizabeth Lee Hofmann, Ph.D.
Executive Director
Risk Assessment Forum
Long-term RAF Accomplishments
• 1992: EPA's Risk Assessment Forum
developed "Framework for Ecological
Risk Assessment"
• 1998: Published the "Guidelines for
Ecological Risk Assessment"
• 2003: Produced the "Generic Ecological
Assessment Endpoints (GEAEs) for
Ecological Risk Assessment"
• 2p06: RAF held a Population Ecological
Risk Assessment Modeling Training
Workshop
I fUSK ASSESSMENT FORUM
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Current State of ERAs
Current practice focuses on organism-
level endpoints
Practical (uses toxicity testing)
Expedient (extrapolate to the population)
This approach assumes if you protect
the individual (organism), you in turn
protect the population
Shift from organism-level to population-
level endpoints
• Allows direct evaluation of risk to
populations
This shift will require:
Improved assessment planning
Evaluation of historical precedence
Evaluation of practice and use of population
assessments
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Meeting Goals, Process &
Outcomes
Goals:
Solicit your individual opinions
Assess current state-of-the-science
Discuss population ecology's methods and
tools
Three approaches for conducting
assessments
Observational, Experimental, and Modeling
Summary workshop report
RAF Staff (Seema Schappelle, Colleen
Flaherty, Gary Bangs)
Wayne Munns (ORD) and Jim Chapman
(Region 5)
Todd Bridges (from USAGE)
Richard Sibly (University of Reading)
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Risk Assessment Forum
Workshop on
Population-Level Ecological Risk Assessment
Workshop Overview
Context for Workshop
Continuing dialog revolving around
populations as fundamental ecological units
to consider in environmental decisions
Lack of consensus & guidance about
approaches for assessing risk
Assessments at population level are:
- becoming more commonplace
- ad hoc
- often contentious
&EPA
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Why We're Here
• To draw a line in the sand regarding
maturity of science and practice
• To inform decisions by U.S. EPA's Risk
Assessment Forum regarding
development of guidance
Workshop Objectives
1. Identify current approaches, methods &
tools
2. Identify strengths, current limitations,
tradeoffs & outstanding research needs
3. Identify technical needs with respect to
development of guidance & additional
steps to facilitate development of
guidance
&EPA
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Approach
Plenary interactions
- provide background information
- communicate needs of EPA & others
- illustrate case studies
- identify additional issues to be addressed
Breakout group discussions
- gather expert opinion re. state of science & practice
- organized broadly by methodological approach
Plenary discussions
- summarize breakout discussions
- facilitate cross-approach interaction
&EPA
Breakouts
• Observation Approaches
- monitoring responses of populations to stressors &
natural variables in real-world situations
- sometimes called "ecoepidemiology"
Experimental Approaches
- manipulative experiments (e.g., toxicity tests) to
evaluate population response
- performed in laboratory, field or semi-field systems
• Modeling Approaches
- application of process models to evaluate general &
specific population risk problems
- often based on underlying biological processes
&EPA
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General Considerations
Helping to define maturity of science &
practice, and not recommending specific
approaches or developing guidance/best
practice descriptions
Exploring technical issues &
considerations, and not policy issues
• Seeking individual input & opinions, and
not consensus statements
Expected Products & Uses
• Workshop report
-summarizing discussions
-communicating steering committee
recommendations
- input to RAF follow-on activities & potentially
to guidance
• Distribution & publication
- RAF web site
- peer refereed article(s)?
&EPA
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Key Contacts
Seema Schappelle, RAF Liaison i
Jerry Cura, Workshop Facilitator I
Breakout Groups Leads
- Observational approaches: Glenn Suter, Mary
Sorensen
- Experimental approaches: Tom Forbes, Diane Nacci
- Modeling approaches: Steve Newbold, Rob Pastorok
Amy Barnes, Muncie Wright, Joan Gades,
logistics & recording
RAF Working Group & Steering Committee
&EPA
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Risk Assessment Forum
Workshop on
Population-Level Ecological Risk Assessment
Setting the Stage:
Relevant Past
Activities
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Initiating RAF Activities
1998 Guidelines for Ecological Risk
Assessment
RAF Colloquium in 1999
-to identify nature & scope of follow-on
projects
-focused on assessment endpoints, risk
characterization & effects at higher levels of
biological organization
- identified specific activities for population &
communities endpoints, including guidelines
(model development, selection, use &
interpretation)
Current RAF Project
Working group of EPA staff
Training in use of models in population-
level ecological risk assessment
This workshop
Follow-on activities?
&EPA
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SET ACPelisten Workshop
Population-Level Ecological Risk
Assessment
August 2003 in Roskilde, Denmark
Experts from USA, Europe, Japan &
Australia
Focus on advancing acceptance & practice
of population-level ecological risk
assessment F
Pelisten Objectives
Evaluate policy contexts for assessments
Explore technical issues & opportunities
Identify appropriate empirical & modeling
methods w/in varying decision contexts
Develop a framework for conducting
population-level assessments to support risk
management decisions
&EPA
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Key Pellston Conclusions
Science sufficiently mature
Develop program-specific guidance
for use of models & data within a
tiered assessment format
Develop training to improve
communication with managers &
stakeholders
Define acceptable population risk
in different management contexts
Assessment
SETAC LEMTOX Workshop
Ecological Models in Support of Regulatory
Risk Assessments of Pesticides:
Developing a Strategy for the Future
September 2007 in Leipzig, Germany
Experts from Europe, USA & Asia
Primary focus on role of population
modeling in risk assessments supporting
regulatory submissions in the EU
&EPA
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Specific LEMTOX Questions
Benefits of population modeling to
pesticide registration?
Obstacles preventing use of population
models in pesticide risk assessment?
• How can obstacles be overcome?
• What recommendations will help ensure
good population modeling practice in
pesticide risk assessment? i
Key LEMTOX Conclusions
• Develop guidance on Good Modeling
Practice
- model development & evaluation
-documentation & communication
- analysis & interpretation
• Case studies to explore value added by
using models
&EPA
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Is There a Potential for Using
Population Models in the
Aquatic Life Criteria Program?
Charles Delos
Office of Water
June 16, 2008
Aquatic Life Criteria & Standards
Define biological goals in terms of
community, not particular species.
- Biocriteria: densities of indigenous species
Claim to protect populations, not individuals.
Chemical criteria describe level of protection
based on toxicity test responses:
- % of individuals
- % of species
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Program Use of Population Models
Saltwater dissolved oxygen criterion (2000):
- Used population model in deriving the time-
variability facet of the criterion.
Future toxicant criteria derivation method:
- Talked to Science Advisory Board three times
(1993-2005) about our proposed approach
incorporating population modeling as a critical
component.
Case Study:
Time-Variable Exposure Problem
- concentrations vary rapidly in flowing waters -
To address the question:
How often can toxicant criteria
concentrations be exceeded without
impairing aquatic life beneficial uses?
- Traditionally the program had cited ecological
recovery time as a key determinant.
- Office of Water and Office of R&D favored use of
population modeling considerations.
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How does a population respond to
exposure to time-variable levels of effect?
- How quickly does attrition take place when
reproduction or early life stage survival is
reduced?
- How long does it take to replace individuals
lost to toxicity?
Components
of the
Case Study
Assessment
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Consider the Sensitivity of Tested Species
Genus
Ceriodaphnia
Daphnia
Ictalurus
Catostomus
Micropterus
Pimephales
Lepomis
Muscullium
Hyalella
Chronic EC20
(mg/L)
16.10
12.30
8.84
4.79
4.56
3.09
2.85
2.26
1.45
For Each Species, Consider the Effect
of a Long Series of Daily Exposures,
Applying Two Models
Kinetic toxicity model to translate from lab
test exposures to continuously variable
concentrations.
Life-stage structured population model to
reflect:
- Population reduction from effects on survival
and reproduction.
- Rate of recovery after population loss.
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Kinetic Toxicity Model
Structured as a first-order, single-
compartment accumulation model:
- Accumulation-depuration
- Damage-repair
Calibrated to acute & chronic effects data.
May take one of two forms:
- Stochastic Process Model
- Deterministic Process Model
One Form of Toxicity Model
Stochastic Process Model
-An organism might die if stress exceeds a
certain threshold.
-All individuals in a life stage have identical
sensitivity.
- Partial toxic responses are a manifestation of
probabilities of effects appearing among the
identical individuals.
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Second Form of Toxicity Model
Deterministic Process Model
-An organism iv/7/die if stress exceeds a certain
threshold.
- Different individuals have different sensitivity.
- Partial responses stem from these differences.
- Better fits the data. Recognizes "survivor bias".
- Requires that population model maintain an
accounting of groups having differing sensitivity.
Stage-Structured Population Model
F2(1-(2)
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c
o
• Toxicant 1
concentration, |
short example
• Accumulation &
of stress or |
damage
§
• Population |
response 1
A iM j\
A
r \ /vT^
/ ^~~/'^
\^^^^
Density Dependent
Days
Risk Measure
Society for Risk Analysis definition of "risk":
The probability of the event occurring
times
the consequence of the event if it occurs.
The expected value of loss: E p, loss.
Measured in the units of what is lost, in our
case, percentage of the population.
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Obtaining Criterion that Protects One Assemblage
- Using Density-Dependent Model -
V)
-§.
2
CD
Species D
Species C
Species B
Species A
—
60
SO
100
Day
Density-Dependent
versus
Density-Independent
Approaches
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c
o
Is
Q.
O
Q.
C
O
'•5
_re
3
Q.
O
Q.
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O
Density Dependent
Density Independent
Reference-'
Ex posed
20
40 60
Days
80
100
< Reduction
in
population
density
< Reduction
in
population
growth rate
How to Make Density and Growth
Reduction Mathematically Equivalent
Condition 1
Define Endpoints as Long-Term
Fractional Reductions
Density-dependent
density reduction
i
z
t=1
N
Ref
Density-independent
growth reduction
r - r
1 Ref ' Exp
^Ref
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Condition 2
For the Density Dependent Approach
Use Beverton-Holt Survival Function
Reference daily survival is the joint
probability of surviving:
- Ordinary perils. Density-independent
background survival probability: a constant.
- Crowding. Density-dependent survival
probability: Beverton-Holt function.
1
1 + aN
How to Make Density and Growth
Reduction Mathematically Equivalent
Condition 3
Set Density-Dependence Parameter, a, to
Maintain Density-Independent,
Unlimited Growth Age Distribution
• For two life stages, 0/02 = N2/N1 where N
is from unlimited growth model results.
• The DD model ends up with the same
degrees of freedom as the Dl model.
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Result of Applying
the Previous Three Conditions
The combined density-independent and
density-dependent assessment can be
thought of as:
-A population growth assessment,
-Made more understandable through a
density translation or interpretation,
given certain assumptions about the
density dependence.
Another Question Suited to
Application of Population Models
The WQ Criteria Program routinely says it
protects species populations by protecting:
- Survival of the most sensitive life stage.
- Reproduction.
Does reducing reproduction have the same
effect as reducing survival?
Does reducing early life stage survival have
the same effect as reducing adult survival?
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Rapidity: Mortality v. Repro Effects
Bluegill: maturity time 2 yrs, A = 1.002 (/day) = 2 (/yr)
0.8
~ ~
-5 0.6
o.
o
^0.4
T3
<
0.2
0
Repro & ELS Survival EC5C
All Stages Survival EC50
Eventual plateau
Bluegill
0 100 200 300 400 500 600
Day
What About Time-Varying
Background Conditions?
This assessment
- Does not address seasonality.
- Does not address good years versus bad years
for the reference population.
Thus, the reference population growth rate or
density is uniform throughout the simulation.
If the background varied between favorable,
midrange, and adverse conditions, how
would it affect the results?
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Effect of Time-Variable
Background Conditions
The endpoints used by this assessment
are not affected.
But other possible endpoints, such as
used in PVA, would be strongly affected.
Conclude: what needs to be included in
the analysis depends on the question
asked.
Can We Effectively Address
Time Variable Exposure
Without Using
Population Modeling?
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Combining
with the T
1
>^0.8
'c/>
c
,
-i— »
10.4
.Q
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£ 0.2
0
0.(
Probability of a Concentration
oxicity-Test Response Curve
Alternative Risk Paradigm
/
/ Effect
/ level
f~\
Event / \ /
probability / \ /
density / \ /
function / \ /
/ \ /
/ \/
/ A
^ -• ^--' \^^
Fractional effect
D1 0.1 1 10
C/LC50
Comparing the Alternative Risk Paradigm
with the
Coupled Toxicity Model & Population Model
Alternative risk paradigm:
- Omits kinetics of toxicity.
- Omits sequencing of events.
- Cannot discern life-stage sensitivity differences.
- Omits persistence of loss (recovery time).
For same exposure series, fingernail clam:
-4.4% reduction, alternative risk paradigm.
-6.9% reduction, kinetic & population models.
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Future of Population Models in
Aquatic Life Criteria?
Additional complexity not especially welcome.
Mature program: change is problematic.
But... the program
has allowed
release of the draft
assessment
document to the
workshop
participants.
SERA Modeling Framework
Applied to Establishing
the Aquatic Life Criteria
Attainment Frequency
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.
Population Modeling in
Ecological Risk Assessment
Regulatory Perspective
Edward Odenkirchen, Ph.D.
Office of Pesticide Programs
United States Environmental Protection Agency
June,2008
United States
Environmental Protection |
Agency
Goals of the presentation
Explain:
• How population modeling fits into the regulatory
process
• Benefits of population modeling
• Requirements of models used for regulatory
purposes
• Challenges facing use of models in regulation
• Current Efforts in OPP
• Perspective of pesticide regulation
"your mileage may vary"
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FIFRA Regulatory Decisions
The Administrator shall register a pesticide if he
determines that "when used in accordance with
widespread and commonly recognized practice it will not
generally cause unreasonable adverse effects on the
environment"
PL 95396, sec. 3(c)(5)(D)
"Unreasonable adverse effects on the environment
means any unreasonable risk to man or the
environment, taking into account the economic, social,
and environmental costs and benefits of the use of any
pesticide"
PL 95396, sec. 2(bb).
Prediction of population effects has been
part of Agency concerns for some time
• "Reputable presumption of risk shall arise
if a pesticide's ingredients, metabolites, or
degradation products ...can be reasonably
I anticipated to result in significant local,
regional, or national popi
in nontarget organisms."
Federal Register Vol. 40 number 129, July 3, 1975
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Prediction of population effects has been
part of Agency concerns for some time
• "Define ecological risk assessment. .. as
estimating the likelihood or probability of
adverse effects (e.g. mortality to single species
of organisms,
due to acute, chronic, a
reproductive effects, or disruption in community
and ecosystem level functions"
Urban and Cook, 198P
Prediction of population effects has been
part of Agency concerns for some time
Risk Manager Questions
- What are the effects of concern?
- What is the magnitude and probability of these effects ?
- Are the effects seen across different species ?
- Will there be population effects?
- Will the effects influence the density and diversity of the
species?
- How confident are we in our estimates of effects?
(Steve Johnson 1997, currently EPA Administrator)
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Screening-Level Ecological Risk
Assessments
Focus on assessment endpoints related to survival,
fecundity, and growth
"These assessment endpoints, while measured at the
individual level, provide insight about risks at higher
levels of biological organization (e.g., populations)."
Overview of the Ecological Risk Assessment Process in the Office
of Pesticide Programs, U.S. Environmental Protection Agency
2004
For many risk management decisions these assessment
endpoints and their inference to population effects are
sufficient to inform the management decision
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The Regulatory Picture Informs the
Rigor/Complexity of the Assessment
Decision components such as the predicted benefits and
the nature of the expected effects may dictate the level
of risk assessment complexity.
Others may progress from simple risk quotient
approaches to estimation of the probability and
magnitude of individual effects and (in the future) on to
model predictions of population responses.
Benefits of Population Modeling
• Provide limited interpretations of screening level
risk assessment results
RQs—»• magnitude of effects —»• simple generic population tools
Refine problem formulation for future risk
assessments
Explore demographic characteristics
Identify types of species of greatest concern
Provides for common evaluatipn metric for cross
chemical and cross effects prioritizations
When are acute or chronic effects more important?
Which chemical's suite of risk predictions is of more concern?
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Benefits of Population Modeling
• Allow for considerations of temporal and spatial variability
in evaluating the consequences of predicted individual
effects
When or where can populations sustain temporary impacts?
Support biologically relevant mitigation options
• Evaluations of effects consequences for species of special
concern (e.g., federally listed threatened or endangered
species)
Assessments under the Endangered Species Act to inform the
question of species jeopardy
• Future: support efforts to establish risk and benefit
measures in common units
Requirements of models used for
regulatory purposes
Make use of existing effects data sets
- Minimize reliance on effects endpoints that are
outside current testing capability
Model variables can be readily populated
with existing data sources
Compatibility with existing individual risk
prediction tools
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Requirements of models used for
regulatory purposes
Adapt/Use existing Models from other
programs and scientific literature when
practical
Use of publicly accessible models
(avoiding proprietary models if possible)
Requirements of models used for
regulatory purposes
Explicit about model assumptions,
uncertainties, and limitations
- What simplifying assumptions have been made?
- How do those assumptions limit the application and
interpretation of predictions?
Explicit about the model predictions
- Statements of the nature of the predictions being made
- Output of the model is based on agreed upon needs
from risk managers
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Requirements of models used for
regulatory purposes
Model architecture that allows for
advancement of the model in
complexity and realism
-Avoiding different tools at different levels of
refinement when practical
-Allow for incorporation of additional variables
without developing a new tool at each
iteration
Requirements of models used for
regulatory purposes
Scientific peer review following Agency
Fulfills Agency quality assurance and
Validation?
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Challenges facing use of models in
regulation
Achieving appropriate balance between three
factors:
- Model Simplicity
• Mathematical/software construct and information requirements
- Model Realism
• The extent to which the model represents real organisms under
real situations
- Model Portability
• The ability to apply the model across risk assessment
scenarios, geographical areas, and organism types
Challenges facing use of models in
regulation
Where to position the model?
Is there just one desired position or many depending on
situation?
Simple
Portable
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Challenges facing use of models in
regulation
Selecting Informative Outputs
- Numbers of organisms
- Age structure changes
- Trajectories over time
- Time to some threshold of concern
- Chance of recovery or extinction
Outputs as stand alone measure or relative
u I I/background condition
Challenges facing use of models in
regulation
• Dealing with the propagation of uncertainties
in individual effects risk predictions
• Can we avoid zero to infinity uncertainty bounds?
1 Overcoming the temptation to account for all
possible variables at every level of
assessment
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OPP Efforts
Currently partnering with the Office of Research
and Development on several projects
The goals for these projects
- Produce tools for near term application
- Provide a framework for development of more refined
population tools
- Establish a basis for dialogue with risk managers on
expected outputs and capabilities of population
OPP Efforts
ORD Mid-continent Ecology Division
- Methods to extract reproduction endpoints from
avian reproduction tests for future population
modeling
• Move from existing hypothesis testing based
assessments
• Incorporate the full extent of measurement endpoints
• Apply these endpoints to appropriate stages in the
avian reproduction cycle
Utilize OPP refined risk assessment model outputs
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OPP Efforts
ORD Atlantic Ecology Division
- Proof of concept model for estuarine invertebrates
using mysids
- List publicly available aquatic organism population
models
• I.D. models suitable for use in OPP risk assessment
• I.D. taxa in need of population model development
- Group birds by population demographics/life history
for large scale crops
- Matrix population models for life history groups of
OPP Efforts
ORD Western Ecology Division
- Developing a spatially explicit meta-
population model (PATCH) to predict avian
population responses to pesticide use in
selected agro-environments
• Make use of AED matrix models
• Incorporate OPP refined risk mortality outputs
'ncorporate MED reproduction impairment outpu1
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Last Thoughts
All models are wrong and some are useful
George Box
The purpose of computing is insight, not
numbers
Richard Hamming
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David W. Charters
Environmental Response Team
Office of Remediation and Technology Innovation
Office of Solid Waste and Emergency Response
Risk Assessment Forum
June 16, 2008
Washington D.C.
Comprehensive Environmental Response, Compensation and
Liability Act (CERCLA)
> CERCLA requires EPA to assess risk to Human
Health and the Environment at Sites
> Risk is only one of nine criteria for Remedial
Decisions
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OSWER Directive 9285.7-17
> CERCLA Ecological Risk Assessment Should:
-1. Identify and characterize current and
potential threats to the environment from a
hazardous waste spill
-2. Evaluate the ecological impacts of
alternative remedial strategies
-3. Establish Clean-up levels in the selected
remedy that will protect those natural
resources.
m
OSWER Directive 9285.7-28P
-Superfund ERAs gather effects data on
individuals in order to predict or postulate
potential effects on local wildlife, fish,
invertebrates, and plant populations and
communities that occur in specific habitats at
sites.
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EPA as a Natural Resource Trustee
> EPA is not a Natural Resource Trustee
> We do not do damage or restoration, we do
risk
Superfund Extrapolates Toxicity Data including
Benchmarks to Potential Impacts (risk) to Local
Populations
> Superfund based on causal relationships
> Superfund is based on hazardous material spills ("spills" not permitted)
> "Severe" liver damage in a population (laboratory or field collected) is extrapolated
to impacts (e.g., increases in mortality, decreases in reproduction).
> Frequently the Cleanup goals are based on No Observed Adverse Effect Levels or
Low Observed Adverse Effect Levels or another range of Tox. Benchmarks of which
there are many.
> It does not require that impacts are documented on sites, consistent with human
health assessments that do not require an epidemiological study showing impacts to
take action.
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Challenges to Assessing Population Risk at
Hazardous Waste Sites
> Size Matters... Small sites restrict data collection...Large sites take time
> Short time frames allotted for a Remedial Investigation/Feasibility Study do not allow
for long term studies
> Effects must be linked to hazardous substances releases
> We are probably weakest in the terrestrial and aquatic areas
> Some believe that we can assess risk to individual organisms on a site
> Reference locations
Unfortunately, a learned aversion to research at sites, there is a great need to
unlearn this reaction.
What would be Useful for a Positive Impact of
Population Sciences in the Superfund Program?
> Short term studies that could be implemented in two years or less.
> In rare cases that the assessment could take several years, what
population metrics could be utilized to develop a numeric cleanup goal.
> Technical projections of individual level effects (e.g., liver toxicity) to
population impacts.
> How impacts on relatively small local populations can impact larger
populations.
> How very small populations, e.g., threatened or endangered species might
be evaluated.
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Take Home Message
We need help in population science
We are a frustrating bunch many are linear thinkers (like that is a bad thing)
We generally are engineering based (We are there to fix the problem)
Many went to school specifically to learn to build walls (and other structures)
Frontal assaults denigrating our intelligence is met with withholding of funds (Golden Rule)
We are not quite as slow as people would think
And talking slower and louder usually does not help
Questions?
-------
^ Bruce Duncan
U.S. EPA Region 10, Seattle
(WA, OR, ID, AK)
Regional perspective:
Population-level ERA
Population-level ERA issues
Regional (10) Perspective - with focus on
contaminants
•Are there regulatory requirements?
•Management or stakeholder goals to protect populations?
•Are population-level risks involved directly in decisions that
are made?
•Where do you think the science is sufficiently developed, and
where are advancements needed?
•Are there issues with respect to the state of practice of that
science? Application issues? Interpretation issues?
•Do you think some sort of guidance would help to address
these?
•Relevant case studies
-------
Population-level ERA issues
Regional (10) Perspective - with focus on
contaminants
•Are there regulatory requirements?
•Management or stakeholder goals to protect populations?
•Are population-level risks involved directly in decisions that
are made?
•Where do you think the science is sufficiently developed,
and where are advancements needed?
•Are there issues with respect to the state of practice
of that science? Application issues? Interpretation
issues?
•Do you think some sort of guidance would help to
address these?
•Relevant case studies
Population-level ERA issues
Regional (10) Perspective - with focus on
contaminants
Shared Goal: To evaluate/predict population-level effects
relative to contaminant stress
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How might we bring population-level
ecological risk assessment into:
• CERCLA risk assessments, and
• State water quality standards approval process?
Why these two uses of PLERA?:
•Scale (state v smaller/tiny)
•Purpose (prospective v retrospective)
•Role of trustees (protective v damage assessment)
Looking for:
•How to evaluate & predict at
population-level
•How to extrapolate UP from levels
below
o
Keep in mind we do not assess individuals
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Issues related to evaluating population-
level effects*
•Definition of population
•Population parameters/measures/etc.
•Interpretation
•Uncertainty Analysis -
*these have been well-articulated before
Issues related to evaluating
population-level effects
•Definition of population -
relative to the needed decision,
(scale, purpose -
protect/recover, etc.)
Breeding, migratory,
subpopulation, habitat
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Issues related to evaluating population-level
effects
•Definition of population
•Population parameters/measures/etc.*-
which are best for:
•Evaluating contaminants?
•Existing effects? Potential effects? -
we generally need to predict potential
effects and what may happen after an
action is taken or even if habitat
changes
*density, sex/ratio, age structure, intrinsic rate of
growth,...
Issues related to evaluating population-level effects
•Definition of population
•Population parameters/measures/etc.
•Interpretation
•what is adverse*?
•How to make comparisons - with reference conditions/
gradients?
*determining "adverse" is helped by:
•strong relationships (cf vetted paradigms - AWQC; SpS Curves)
•better use of dose/response data
•consider the management decision and the role of protectiveness
in balancing uncertainty
-------
Issues related to evaluating population-level effects
•Definition of population
•Population parameters/measures/etc.
•Interpretation
•Uncertainty Analysis -
•What happens to the role of the population selected as
an indicator/surrogate?
•Does the assessment become too species-specific?
What I would like to
come away with
from this
Workshop:
1. Ideas on how to mainstream
PLERA in regions
• Framework,
• Tools,
• Case studies (decisions-
protective levels),
• Technical papers
-------
What I would like to
come away with:
2 Useful tips on population
measures/parameters (e.g.,
analogy to tox testing & tissue
residues). How to expand
experimental studies
•crosswalk measures of
exposure & effects for
populations
•contaminants as a subset
of multiple stressors
-------
Population modeling
in economic analysis
Steve Newbold
U.S. EPANational Center for Environmental Economics
EPA Risk Assessment Forum workshop
"Population-level Ecological Risk Assessment"
16 June 2008
The views expressed here are those of the author and do not necessarily represent those of the U.S.
EPA. No official Agency endorsement should be inferred.
Outline
1. Preliminaries
2. Section 316(b) economic analysis
3. Improved ecological benefits assessments
through population modeling
-------
Preliminaries
What is the relevance of economic analysis for
ecological risk assessment?
1. Many important ecosystem services derive from population-
level phenomena. Thus, economic valuation models often will
require population-level impacts as inputs.
2. The needs of an economic analysis can help inform the selection
of risk assessment endpoints.
3. Improved ERA practices should also help improve economic
assessments at the Agency.
http://yosemite.epa.gov/ee/epa/eermfile.nsf/vwAN/EE-0485-01.pdf
/$File/EE-0485-01.pdf 4
-------
Section 316(b) of the CWA
"...location, design, construction and capacity of cooling ater
intake structures shall reflect the best technology available for
minimizing adverse environmental impact" from entrainment and
impingement.
In 1994, Riverkeeper sued EPA for failing to implement national
standards.
Regulations passed in three phases—new facilities, existing large
facilities, existing small facilities.
Section 316(b) of the CWA
Benefit-cost analysis:
1. Costs to facilities of installing and maintaining control
equipment
2. Benefits of expected increases in commercial and recreational
fish harvests from reduced I&E
-------
Section 316(b) of the CWA
Final rule:
Of 550 in-scope facilities, 150 to install impingement controls, 200
to install impingement and entrainment controls, 200 required no
new controls.
Expected to increase total fishery yield by 65 million Ibs / yr.
Total social costs = $390 million / yr
Commercial fishing benefits = $3.5 million / yr
Recreational fishing benefits = $80 million / yr
Total (monetized) net social benefits = -$310 million / yr
Section 316(b) of the CWA
Biological model:
i. animal tishine; mor
iililv rate for fish ofii.ee
(http://www.epa.gov/waterscience/316b/phase2/casestudy/final/cha5.pdf.)
-------
Section 316(b) of the CWA
Simplifying assumptions:
"All of the key parameters used in the yield model, F, M, and
size-at-age, were assumed to be constant for a given species
regardless of changes in I&E rates... EPA recognizes that the
assumption that the key parameters are static is an important
one that is not met in reality... [but]...the use of more complex
fish population models would rely on an even larger set of
significant data uncertainties and would require numerous
additional and stronger assumptions about the nature of stock
dynamics that would be difficult to defend with available data.
The only slide with equations
Consider an aggregate biomass, or "scalar, " model:
At NH
(3)
(4)
(5)H
3H _ 3H/3/ _ fti
~dL~~ dL/di ~ r-f-2i
-------
Examples
(1) r = 2,f=0.5,i = 0.1 ->
About 25% lower than prediction from proxy model.
(2) r = 1.5, f= 0.75, i = 0.2
Nearly 200% higher than prediction from proxy model.
(Harvest increases by more than the number of fish "saved"
per year!)
Conclusions
1. Ignoring density-dependence not always
"conservative."
2. Improved population modeling and risk
assessment practices can improve ecological
benefits assessments.
-------
The Relevance of Populations to
USAGE
Todd S. Bridges, Ph.D.
Senior Scientist, Environmental Science
U.S. Army Engineer Research and Development Center
Vicksburg, MS
Ecological Risk
Ecological Risk Assessment: "...a
process...to evaluate the likelihood of
adverse ecological effects", USEPA, Fed.
Reg. Vol. 61 No. 175(1996)
- Ecology: "The scientific study of the
interactions that determine the distribution
and abundance of organisms." Krebs (1972)
The two key questions:
- Where are they?
- How many are there?
-------
USAGE Missions and Problems
• Navigation
- Dredged material management
• Hydropower and reservoir management
- Fish passage and "take"
• Ecosystem restoration
- Sturgeon and Interior Least Tern
- Contaminant remediation
• Invasive species management
U.S. Navigation
Dredging Program
• 400 U.S. Ports
- Transport for 95%
of international
trade
• 25,000 miles of
navigation channel
• 200 million cubic
yards of sediment
dredged annually
• $1 billion budget
• •**"* .*
-------
Marine Protection, Research
and Sanctuaries Act of 1972, i
102: "...changes in marine
ecosystem diversity,
productivity, and stability; and
species and community
population changes."
• SF-DODS
40 CFR § 227.27(b)
"Materials...will not cause
unreasonable
acute or chronic toxicity or other
sublethal adverse effects..."
Population Modeling
Individual >»»»»»:
Survivorship, Growth, Reproduction
Population
0 0 0
0 0 P3 0
0 0 0 ••• P
-------
Daphnia magna
• Evaluated chronic
toxicity of 17 Great
Lakes sediments over
21-d exposure
• Measured effects on
survival, development
rates, reproductive rates
• Summarized effects
using an age-classified
population model
niiiiiii
nun
lIMllIlllIlff Illllllll
II III II III
Daphnia magna
Bridges, T.S., R.B. Wright, B.R. Gray, A.B.
Gibson, and T.M. Dillon. 1996. Chronic
toxicity of Great Lakes sediments to
Daphnia magna: elutriate effects on
survival, reproduction, and population
growth. Ecotoxicology 5: 83-102.
Population Size
-------
-------
Contributions
•Effect of BRH on
lambda due to
reduced survival
in 0-3 wk olds and
reduced fecundity
during weeks 4-8
• Magnitude of the
contributions from
survival and
fecundity are
similar
7 8 9 10 11 12 13 14 15 16 17 1
age class
10 11 12 13 14 15 16 17 1819
-------
Historic Area Remediation Site
• NY Mud Dump Site
closed in 1997
• Revising approach for
evaluating whether
material suitable for use
as remediation material
HARS/MDS
Using spatially explicit
exposure modeling of
fish
Linkov, I., D. Burmistrov, J. Cura, T.S. Bridges. 2002. Risk based management of
contaminated sediments: consideration of spatial and temporal patterns in exposure
modeling. Environmental Science and Technology 36:238-246.
Fish Tagging Study
Project team from NMFS,
Sandy Hook, NJ
- Fabrizio, Pessutti,
Manderson, Drohan, Phelan
Black Sea Bass and
Summer Flounder
identified as study species
- Site use and relevance
to humans health
-------
Fish Tagging Study
• 72 moored acoustic
receivers placed at HARS
in April 2003
- 800 m apart
• 129 BSB and 24 SF tagged
and released in May-Jun
2003
• Completed array retrieval
in Sept 2004
- 1,625,315 detections
-------
Richard B. Russell Dam
• Pumped storage
operations entrain
fish from J. Strom
Thurmond Reservoir
• Study purpose:
evaluate long-term
population-level
impact of mortality
from entrainment
• threadfin shad,
blueback herring,
striped bass, hybrid
bass, black crappie
-------
Blueback Herring
Stochastic matrix population model with 4
age classes built using monthly gillnet
data, hydroacoustic surveys, and fecundity
estimates using Boltin (1995)
Density dependence modeled using
Beverton-Holt and site data
Scenarios evaluated included estimates of
total entrainment mortality using:
- Measured estimates of 1.3% (Scenario A) and
0.56% (Scenario B)
- Hypothetical estimates of 4%, 8%, 12%
Blueback Herring Risk of Decline
Mean Entrainment
4% Entrainment
- - - -8% Entrainment
12% Entrainment
o i—
O.E+00
1.E+07
2.E+07
Abundance Threshold
-------
-------
Ecosystem Restoration
Projects range from
small to very large
Budget
justifications
closely scrutinized
by OMB
Need to strongly
establish
quantitative,
scientific basis for
environmental
benefits
- E.g., more of
species x
Missouri R.
-------
Leptocheirus plumulosus Metapopulation Model For
Gunpowder River, Aberdeen Proving Ground, MD
Extinction Risk
Without Creeks
With Creeks
0 1e+9 2e+9 3e+9 4e+9 5e+9 6e+9
Threshold Abundance
T.S. Bridges, H.R. Akcakaya, B. Bunch. 2008.
Leptocheirus plumulosus in the upper Chesapeake Bay:
sediment toxicity effects at the metapopulation level. In,
Demographic Toxicity: Methods in Ecological Risk
Assessment H.R. Akcakaya, J.D. Stark, T.S. Bridges,
eds. Oxford University Press, pp. 242-254.
Upper Missouri River - Impounded 960
Lower Missouri River- Free-flowing 811
Middle Mississippi River 200
Lower Mississippi River 985
-------
Issues
Latitudinal trends in abundance and size over a 3,000 river mile range
Population status and threats vary geographically
Lower MS River stable populations; entrainment from water diversions is a threat
Middle MS River - harvesting impacts
Lower Missouri River - uncertain status; habitat restoration and stocking ongoing
Upper Missouri River no recruitment; stocking necessary to maintain populations
Movement between rivers has been documented single or multiple populations?
Genetic uncertainties undermining progress in recovery
Curtains for the
turgeon?
better understanding
Pallid sturgeon will
not go extinct, but
Applied
hyology
Can pallid sturgeon be
successfully maintained in
the impounded reaches of
the upper MO River ?
Are pallid sturgeon populations
viable in the free-flowing portion
of the ranae?
Determine if stocking is
adequate
Determine if population is self-
sustaining based on age
structured models.
Determine number and
nterrelati on ships among
populations
Evaluate
subpopulation
by reach
ne range
ovements and
habitat use
Genetics • Morphology • Behavior II Telemetry
Declining / Stable / Increasm
Single m Multiple
population J populations
Management
Action if
necessary
-------
Interior Least Tern
Background:
-Listed in 1985
- Recovery goals set at 7,000 birds
- 2005, ABC and ERDC conducted
the first range-wide survey and
detected >17,000 individuals.
Problem:
- Recent flooding created habitat
- Habitat is now declining
(vegetation encroachment, erosion,
lack of flood flows to create new or
sustain existing sandbars)
- Long-term sustainability?
2005 Rangewide Survey
Northern Plains (~2,000)
Southern Plains (~4,000)
Mississippi/Ohio (~12,000)
Coast (~12,000)
-------
Interior Least Tern
Approach: Develop a habitat-based
population model with three primary
objectives/capabilities:
1) Evaluate range-wide Interior Least Tern
population status
2) Evaluate sandbar habitat conditions for
all riverine reaches with >50 ILT
\) Evaluate the effects of different
management actions (including no action) on
1) tern populations; and 2) tern habitat.
Invasive Species
Impacts
- Navigation
- Flood control
- Hydropower
- Recreation
- Environment
Population-relevant questions
- Quantifying "invasiveness"
- Predicting spread
- Developing effective control strategies
• Mechanical
• Chemical
• Biological
-------
Population Issues
Establishing relevance to the decision
Reliability of information for decision-making
How to quantify and use information about uncertainty
Establishing confidence in models
• Physics envy"
• Prediction, projection, forecast
• Verification and validation
Distinguishing influence of multiple factors
Defining temporal limits on projections
Considering space
Broad range in scale (meters to 1,000s k)
Behavior and movement
• Requiring use of other information/models
Using "synthetic" populations
-------
Jill Awkerman
US EPA, Gulf Ecology Division
Plight of the Albatross
Long line bycatch
-------
Albatross bycatch in
-------
Band =
recoveries=
1500 adi
trasses =
Recovered ~1% b
lst=year (81.8% males) =
Observers present on 30 =
trips from Salaverry=and =
Callao=
Fishing Gear Deployment
Albatross Locations
laverry Gillnet
iverry Longline
llao Longline
Mark-resiqht analvsis=
Model=
<"> (E) P(t)
o (E) p(g+t)
o (g+E) p(g+t)
<"> (t) P(t)
o (t) p(g+t)
o (g+t) p(t)
o (g+t) p(g+t)
<"> (g) P(t)
1823.74
1825.14
1825.76
1827.15
1828.45
1829.28
1830.41
1830.57
1831.92
QAICC=
Weight-
Model =
likelihood=
Number of =
parameters=
> survival, p = recapture probability =
(.) = constant, (t) = year, (E) = El Nino, (g) = sex=
-------
99-00 00-01 01-02 02-03 03-04 04-05 05-06
50 -,
|«-
o
ol 30 -
ro
;g
0)
-a
03
en
(a 10 -
0 -
0.
^^^_^^^^
_j t ^
JO 0.70 0.75 0.80 0.85 0.90
Sobrevivencia Annual
/
/
/
0.95
-------
Stochastic =
population growth
Year
1960s
1999 to 2000
2000 to 2001
»i!i] t.O'wv;
2003 to 2004
2004 to 2005
2005 to 2006
Adult survival
probability
0.953
0.929
0,930
0.930
0.8S9
0.925
0.921
0.928
Productivity
0.254
0.230
0.304
0.369
0.114
0.079
0.278
0.230
Current A = 0.9615=
1970 1980 1990 2000 2010
t t t t
Additional Years to
Mortality Extinctio
0 212
Action Plan for Waved Albatross
Phoebastria irrorata
Agreement on the Conservation
of Albatrosses and Petrels
-------
Sex-specific differences
Higher male band
recovery rate (82%)
Suggestion of differential
mortality in mark-resight
models
More female adults
Differences in foraging
behavior
-------
Hatchling Fledgling Juvenile
Known fates analysis of chick survival=
Model
likelihood
Number of
parameters
S = survival=
(.) = constant, (g) = sex, (a) = age, (e) = effort=
-------
Age at start of interval (days)
Hatcnlmg Fledgling Juvenile Adult
-------
Summary
Incidental catch and intentional harvest contribute to
increased mortality in waved albatrosses
ENSO events further impact a reduced population growth
rate
Fishery capture possibly contributing to differential
mortality
Males are more susceptible to capture because of their
foraging behavior
migo pescador...!
Cuida
tuspajarotes!!
-------
Acknowledgments
National Science Foundation
Swiss Friends of Galapagos
Sigma Xi
Wake Forest Environmental
Studies Grant
Vecellio Fund
Canadian Wildlife Service
Equipment
Dr. Akira Fukuda & r. Hiroshi
Higuchi
Ferguson Manufacturing
Field & Lab Support
X. Mora Alvarez
Tiffany Beachy
M. Benjamin
Kevin Birchler
Julius Brennecke
Alfredo Castillo Guerr
Audrey Calkins
Andrew 'Epagnier
Alex Gunnison
Kate Huyvaert
Terri Maness
Mark McCaustland
Martina Miiller
Heather Reider
Santiago Salazar
Kim Tice
Ewan Wakefield
Mark Westbrock
-------
Population ecology
Richard Sibly
University of Reading, UK
-------
Barnthouse et al 2008 Population-level ecological risk assessment
A firm scientific foundation is in place ...[but need to
include]
compensatory processes within populations
heterogeneous environments
Talk structure
What are the population endpoints
Stress and density can be measured in small animals
Relating lab and field
Microarrays will one day predict growth reproduction
and survival
York workshop 2004
-------
the scientific foundation
abundance
population growth rate
Paramecium in the lab
5 10 15
Time (days)
population growth rate
= (Nt+1 - Nt) I N,
-------
Paramecium in the lab
s-
-a
I
1.25-
1.00-
0.75-
0.50-
0.25-
0.00-
population growth rate
= (Nt+1 - Nt) I N
400 600
Number of Paramecium
Paramecium in the lab
200 400 600
Number of Paramecium
K
-------
How stress affects population growth
10000
01
w 750°
c
1 5000
3
Q.
S. 2500
50 100 150
Simulation Year
200
How is pgr affected by stress and density
Springtails Folsomia Candida
-------
How design experiments?
Obvious way is
Population
density
Chemical concentration
4 replicates
5 densities x 5 zinc concentrations
\ l>.
-------
-------
Varying stress level and density
Contour Plot of pgr
100 —
D>
3. 50
S 20 -
•o
I 5
2 —
0.3_ ^ \ ',
I I I I I I I I
50 100
I
200
I I I I I I I ill
500 1000 2000 5000
Zinc concentration (jjg/g), log scale
Noel et al 2006
-------
Relating lab and field
Daphnia magna
Ponds sampled for Daphnia magna in Yorkshire by G Fryer
-------
Ponds containing Daphnia magna
Occurrence of Daphnia magna in relation to pH and Calcium
3.0-
2.5-
2.0-
I "I
1
s» 1.0-
£
0.5-
0.0-
-0.5-
3456
7
pH
10 11
-------
Experiment to measure pgr at selected positions
3 i
2 -
» Treatments
0 Control
**•**#
******
34567
10 11
Image analysis
-------
-------
pgr=1/floge=Sf/S0=
8, = population surface area at time t=
Hooper et al 2006=
Laboratory niche of Daphnia magna=
FOR d'1
-2.0 - -1.0
-1.0 - -0.5
-0.5 - -0.2
-0.2 - 0.0
PH
-------
Ecological niche of Daphnia magna
60
O
60
O
pgr = 0.2=
pH
pgr=0=
9 10 11
How genes control growth, reproduction and survival
Daphnia magna
-------
Pgr declines as Cadmium concentration increases
0.2 - =
0.1
-0.1
10 20
Nominal Cd^
30
University of Reading
Daphnia magna microarray
-------
Changes in D. magna gene expression
Functional category
Upregulation
1. METABOLISM
1.1 Carbohydrate and fat
metabolism (A)
Glycolysis/Gluconeogenesis
Cellulose activity
Lipid Metabolism
1.2 Energy metabolism (B)
Coenzymes
Electron transport
Citric acid cycle
1.3 Amino acid and polypeptide
metabolism (C)
Oxidative deamination
Peptidases
Metalloendopeptidase
Glycogen synthase
Glucose-6-phosphatase
Endoglucanase 2
NADH dehydrogenase subunit 3
ATP synthase a chain
Cytochrome c oxidase subunit 1
Carboxypeptidase Al
Trypsin
Chymotrypsin B2
Downregulation
GM2 ganglioside activator p
NADH dehydrogenase subun
Cytochrome b
Succinate dehydrogenase
Glutamate dehydrogenase
Trypsin
Astacin (zinc metalloproteas
2.TRANSCRIPTION AND
TRANSLATION (D)
ID 1 KIN A.
Where we want to go with microarrays
Identify genes/pathways involved in control of
• Reproduction
• Survival
• Growth
-------
York workshop 2004
Population risk assessment of birds and
mammals in the UK
Andy Hart and Mark Klook
The York approach: five steps to population risk assessment
• toxicity endpoints in the lab
• extrapolate between species
• assess exposure in the field
• extrapolate from lab to field
• evaluate effects on populations of woodmice and skylarks
-------
How stress affects population growth
10000
01
N 7500
(/)
c
| 5000
3
Q.
S. 2500
50 100 150
Simulation Year
200
Winter Wheat
No Insecticide
Winter Wheat
With Insecticide
Broad Habitats
No Insecticide
Broad Habitats
With Insecticide
-------
Agent-based model (ABM)
Spatially explicit model of
animal behaviour of the
vole
The study landscape
Real 10x10 km Danish
landscape by Bjerringbro,
1-m resolution
Legend
• Main road
D Roadside verge
• Permanent grass
D Unmanaged grassland
n Rotational field (same colours for all crops)
• Coniferous forest
• Deciduous forest
-------
Agent specification
Agent-based model (ABM)
Spatially explicit model of
animal behaviour of the
vole
Population dynamics
emerge as result of local
interactions
Dynamic landscape with
crop rotation and
weather-dependent plant
growth
-------
Winter Wheat
No Insecticide
Winter Wheat Broad Habitats
With Insecticide No Insecticide
Broad Habitats
With Insecticide
The York approach: five steps to population risk assessment
• toxicity endpoints in the lab
• extrapolate between species
• assess exposure in the field
• extrapolate from lab to field
• evaluate effects on populations of woodmice and skylarks
-------
Variation in carrying capacity (K)=
Vole
Skylark
White areas have N=0.=
Summary
Endpoints are abundance and population growth rate
Stress and density can be measured in springtails
Ecological niche relates lab and field
Microarrays will one day predict growth reproduction
and survival
Individual based models
-------
xvEPA
United States
Environmental Protection
Agency
U.S. Environmental Protection Agency
Office of Research and Development
Washington, DC 20460
Official Business
Penalty for Private Use
$300
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------- |