kapustka assessing risk of chemicals and radiation

Assessing Risks to Humans and the Environment

1

Ecological Risk Assessment: Chemicals and Radiation

Lawrence (Larry) Kapustka, Ph.D.

LK Consultancy

Turner Valley, Alberta Canada [email protected]

Getting started

What is ecology?What is risk?What is ecological risk assessment?Why would one do an ecological risk assessment?

Assessing Risks to Humans and the Environment 2

Learning Objectives:

become aware of the strengths and limitations of ecological risk assessment as a way to inform environmental management decision-making

gain experiential knowledge of the challenges that arise while structuring an ecological risk assessment (i.e., the Problem Formulation phase)

improve their ability to critique study plans and reports that use ecological risk assessments to inform management decisions


Content: Disclosure of some of my biases (developed from Kapustka and Landis 1998) Overview of the ecological risk assessment process Limitations of ecological risk assessment (developed from Kapustka 2008) Using habitat quality and a landscape perspective to improve exposure

estimates (Kapustka 2004, 2005 and ASTM E2385)

Closure


some of my biases ecology, as other sciences, is value neutral ecological resources are given value by humans

Specific values are assigned differently by different humans (cultural, ethnic, class, age, gender, differences)

emergent properties of ecological systems are key if the aim is to manage populations, communities, and system functions

ecological systems: cannot be restored; they can only be emulated change is inevitable predictions of future conditions are tenuous at best

Kapustka, L. A., and W. G. Landis. 1998. Ecology: the science versus the myth. Human and Ecol. Risk Assessment 4: 829-838.


Dealing with Paradigms and Perceptions

Ecology: The Science versus the Myth

(Kapustka and Landis 1998)

The catechism of environmentalism Stability Recovery Balance of nature Integrity Health

Ecological systems are highly dimensional and dynamic collections of organisms and abiotic structures that interact with a multitude of potential responses (modulated by feedback)

Ecological systems are abstract. No one has ever seen one; they are merely perceived.


Ms Northing

Mr. Easting

Anamorphic Imagery (1)


Twisted Cube 2001; Matheau Haemaker



Cube to Pyramid 2001; Guido Moretti



Duet 2001; Shigeo Fukuda

Decision Space

Malcolm Gladwell (Blink)

Posits that humans are wired to make critical decisions quickly we act on thin slices of information

It follows that the formal deliberative processes used in environmental decision-making are distinctly unnatural; an outgrowth of a complex society


Ecology Culture Economics

Impulsive/Inherent Information Barrier

Engineering

Managing within Ecological Systems Contemporary ecology recognizing that historic events determine current

and future structures and that past conditions cannot be repeated. Ecological systems are self-organizing, complex, multidimensional, nonlinear, and dynamic

Consequently, management goals must reflect these ecological realitiesgoals should be dynamic, multidimensional, and responsive to constantly changing ecological conditions as we collectively strive for

sustainability


See Kapustka et al. (2008)


It is better to be roughly right, than precisely wrong.John Maynard Keynes (Economist, journalist, and financier, 1883 1946)

High Accuracy, Low Precision

High Accuracy, High Precision

Low Accuracy, Low Precision

Low Accuracy, High Precision

Complexity of Environmental Issues Challenge our inherent abilities to make wise decisions

We desire more data believing that the additional information will reduce uncertainties and make it easier to make decisions

We struggle to find compelling answers when challenged with so-what? retorts

We are frustrated when decisions are made that do not seem to have given appropriate weight to our science-based insights

Assessing Risks to Humans and the Environment13

leaf

stem

fruit

root

detritus soil invertebrates

aerial invertebrates

herbivoregranivore

carnivore

omnivore

insectivore

microbes

seed

air

soil

leaf

stem

fruit

root

detritus soil invertebrates

aerial invertebrates

herbivoregranivore

carnivore

omnivore

insectivore

microbes

seed

air

soil

Case 1 Case 2 -- plant uptake pathway dominant

-- mycorrhizae pathway dominant

[red arrow thickness depicts relative amount of chemical transfer]

What to do when we dont know which relationships are operative?

"To know that we know what we know, and that we do not know what we do not know, that is true knowledge.

Henry David Thoreau. 1854. Walden: On Life in the Woods.

Tomorrow: ecosystem approach


IUR Task Group

Report available at www.iur-uir.org


ShortcommunicationtoJournalofEnvironmentalRadioactivityUsinganEcosystemsApproachtoComplementProtectionSchemesbasedonOrganismlevelEndpoints.

Bradshawetal.(inpress)

Highlights

An Ecosystem Approach to radiation safety complementsthe organismlevel approach

Emergent properties in ecosystems are not captured byorganismlevel endpoints

The proposed Ecosystem Approach better aligns withmanagement goals

Practical guidance with respect to systemlevel endpoints isneeded

Guidance on computational model selection would benefitan Ecosystem Approach


Population level endpoints:

Population growth rate Population density Population size (numbers, biomass) Population age/size structure Net reproduction rate Probability of extinction

Populations/communities

Structure and functionsof ecosystems

Reference organismapproach

Individual organisms levelendpoints:

Morbidity Early mortality Reproductive success Chromosome damage

Mismatch, method not fully

appropriate

Individualsof selected species

Target of protection

Methods to achieve

protection goals

Goal of protection fully appropriateonly for endangered species

Goal of protection yieldinglargest consensus

Community-level endpoints:Structural

BiodiversityTaxonomic compositionTrait distributionFood web structure

Functional Primary production Biomass/energy flow mineralization

Ecosystem approach

Population level endpoints:

Population growth rate Population density Population size (numbers, biomass) Population age/size structure Net reproduction rate Probability of extinction

Populations/communities

Structure and functionsof ecosystems

Reference organismapproach

Individual organisms levelendpoints:

Morbidity Early mortality Reproductive success Chromosome damage

Mismatch, method not fully

appropriate

Individualsof selected species

Target of protection

Methods to achieve

protection goals

Goal of protection fully appropriateonly for endangered species

Goal of protection yieldinglargest consensus

Community-level endpoints:Structural

BiodiversityTaxonomic compositionTrait distributionFood web structure

Functional Primary production Biomass/energy flow mineralization

Ecosystem approach

Figure1.Targetobjectivesofenvironmentprotectionversusmethodstoachievethem

FromBradshawelal.(inpress)JournalofEnvironmentalRadioactivity

Wicked Problems are


Those that cannot be defined so all agree on the problem to solve Require complex judgment about the level of abstraction at which

to define the problem

Have no clear stopping rules Have no right/wrong answer; just better/worse conditions Have no objective measure of success Require iteration every trial counts Have no given alternative solutions these must be discovered Often have strong moral, political, or professional dimensions

*Rittel and Webber, 1973

Wicked Problemsthe Realm of Risk-based Decision Analysis

Plan Cost Fish DucksA 100 10 5B 100 5 10C 150 10 10D 150 10 15


Comparing Apples and Oranges

(or Fish, Ducks, and Money)

Do you want ducks?

Do you want fish?

Do you want cheap?

or

or

There is no right answer! It all depends on priorities.By courtesy of I Linkov (2005)

Which plan should you choose?


http://www.ted.com/talks/eric_berlow_how_complexity_leads_to_simplicity

Overview of risk assessment


Types of Risk Assessment Engineering

Structural failure Slope stability Flood control

Financial Investments Insurance Liabilities Contracts

Human health Cancer Mortality Morbidity

Ecological Organism Population System


Ineachofthesedisciplines,riskassessmentevaluatesscenariosbyaskingwhatif?questionsasawaytodescribethelikelihoodofanadverseconsequencesothattheriskscanbemanaged.

WhichofthesetypesofrisksareinvolvedinHotSpotremediation?

Definitions of Risk and Risk Assessment Risk the likelihood (or probability)

of an adverse event occurring

Risk Assessment a formal process used to evaluate scenarios by estimating the magnitude of exposures

to some agent or stress

relating estimated exposures to effects or consequences


Environmental Risk Assessment as an Organizing Tool

The formal procedures developed to determine environmental risks can effectively guide or facilitate

technical work in a way that is useful in making environmental management decisions

cost effectiveness and efficiency communications with affected stakeholders


Ecological Risk AssessmentA formal process to describe the likelihood of a receptor being exposed to a stressor that results in a particular effect.


+pDDT

Components of Ecological Risk Assessment

Problem Formulation Analysis Risk Characterization


Problem Formulation [1 of 5]

Management Goals


Birds are not hatching. The public wants healthy birds. There may be toxins in our waters. I need to know the cause. I need to know how bad the problem is. I need to know how to fix it!

Problem Formulation [2 of 5] Conceptual Model


DDT

Physical Transport

Biological Transport


Assessment Endpoints (what is to be protected)


years

N

u

m

b

e

r

o

f

B

i

r

d

s

NormalRange

P

o

p

u

l

a

t

i

o

n

S

i

z

e


Measurement Endpointswhat will be measured


DDTConcentration in eggs

Number of fledging chicks


Project Planspecific details of study Number of nests to observe Number of eggs to analyze for DDT Number of chicks that fledge Relate concentration to effects


[DDT]

HatchingRate

HatchingRate

Population

Analysis [1 of 4]

Description of hazards Fate in the environment,

Movement through media (transport)

Environmental concentration

Bioavailability

Description of effects [how do organisms respond] Death

Reduced growth

Reduced reproduction

Impaired behaviour


Analysis [2 of 4]

Exposure DDT concentration in food items DDT concentration in water DDT concentration in sediment

Effects Atwhatconcentrationsishatchingdecreased Howmanychicksfledgenestsatdifferentconcentrations

Literature

ComputationalModels

Directobservationsatsite


Analysis [3 of 4]

m

spotADD

1

n

1jtotalsjjsjss )FIRFS(D)NIR FR (CP


ADDpot = Potential average daily dosePs = AUF; the proportion of time spent foraging in sub-area sCjs = Average concentration of contaminant in food type j in sub-area sFRjs = Fraction of food type j contaminated in sub-area sNIRj = Normalized ingestion rate of food type jDs = Average contaminant concentration in soils in sub-area sNIRtotal = Normalized ingestion rate summed over all foodsFS = Fraction of soil in diet

Analysis [4 of 4] QuotientsforScreeningAssessments

HazardQuotient=EnvironmentalConcentration/EffectsConcentration PredictedEnvironmentalConcentration/PredictedNoEffectsConcentration

ConcentrationResponseRelationship


Exposure Concentration0 High

E

n

d

p

o

i

n

t

I

n

h

i

b

i

t

i

o

n

0

100

a b

Risk Characterization [1 of 2]

Likelihood of exposure Magnitude of exposure (dose) Effects at predicted exposure concentrations (dose) Uncertainty (explain what is unknown) Certitude (explain what is known)


Risk Characterization [2 of 2]

Likelihood of Effects given DDT concentration in food items DDT concentration in water DDT concentration in sediment

Uncertainties Samplingerror Modeluncertainty Knowledgegaps Othercauses

Certitudes Whatdoweknowforsure


Tiers of Risk Assessment Scoping (Tier 1)

Coarse

Minimum data acquired

Highly protective default assumptions

Screening (Tier 2)

Some refinement

More data acquired

Still relying on protective default assumptions

Definitive (Tier 3)

Finer detail

Considerable data acquired

Greater realism replaces default assumptions


Scoping

Screening

Definitive

Problem FormulationAnalysisRisk Characterization



?

?

No

No

Decision

Decision

Decision


Scoping

Screening

Definitive

Possible

Plausible

Probable

Exposure Assumptions


Default Assumptions

Site-specific Data

No Adverse Consequences Expected

Adverse Consequences Presumed

Environmental Realism

L

o

w

H

i

g

h

Actual Threshold Adverse Consequences May be Demonstrable

E

n

v

i

r

o

n

m

e

n

t

a

l

C

o

n

c

e

n

t

r

a

t

i

o

n

Default Threshold

Definitive

Screening

Scoping


More detail about the problem formulation stage


Management Goals, Objectives

What is the nature of the problem you are addressing? What are you hoping to achieve on your project/site? What are the constraints you face? How will you know if you are successful?


Components of Risk Assessment


Problem Formulation

[setting the parameters]

Characterization[estimating the likelihood

of effects occurring]

Analysis[gathering and processing

relevant information]

Exposure Effects

Risk Framework

Risk Management

Affected Stakeholders

Clarify the Goals before Launching into Sampling

Management goals should be stated clearly before any decisions are made about

Where to sample, What to sample, How many samples to take, Which analytes to measure, and Desired precision and accuracyThat is knowwhat the intended uses of data are, how will data be interpreted, what options are available.


Steps in Problem Formulation1. Clarify specific environmental management goals and objectives2. Delineate the extent of the landscape/waterscape of interest to stakeholders3. Develop a Site-Specific Conceptual Model that depicts

a. pathways from the point of release to the receptors of interest

b. other relevant stressors that may affect populations of receptors (e.g., predation, disease, habitat degradation)

4. Identify relevant chemicals of concern (CoC) and other stressors (physical and biotic)

5. Select assessment endpoints (the values to be protected)6. Define Data Quality Objectives

a. levels of precision and accuracy needed to evaluate relationships between stressors and receptor effects

b. requires iteration to consider what is measurable and with what level of certitude

7. Describe analytical methods and measurement endpoints to be used8. Produce a project-specific sampling and analysis plan9. Produce a project-specific quality assurance plan

Iterate all steps until consensus (if possible) is achieved.


Rule 1 for Conceptual ModelsEmphasize the most important elements


Human Dietary Exposure Routes


AfterFigure5.1.vanLeeuwenandVermeire(2007)fish

soil

air

meat

dairy products

crops

drinking water

HUMANS

surfacewater

groundwater

cattle

Grazers

Air

BacteriaFungi

Grasses & Forbs

Rocks & Soil

Detritus (dead organic matter)Shrubs & Trees

OmnivoresFruit & Seedeaters

Predators

CAMPINGHUNTING & FISHING

COMMERCIAL EXPLOITATION (e.g., mining, logging

Water Nutrients Courtesy of Dr. Doug Reagan, 2005 reformatted LAK 2006

CM: Western Society


Grazers

Air

BacteriaFungi

Grasses & Forbs

Rocks & Soil

Detritus (dead organic matter)Shrubs & Trees

OmnivoresFruit & Seedeaters

Predators

FOOD

CLOTHINGSHELTER

MEDICINESPIRITUAL

TOOLS

Community Vitality

Water Nutrients

CM: Indigenous Cultures


Courtesy of Dr. Doug Reagan, 2005 reformatted LAK 2006

Standard Guide: Conceptual Models


A helpful way to get organized!

Guiding Principles for Problem Formulation

Engage affected stakeholders in genuine dialogue at the earliest opportunity Think beyond the permits Think life-cycle, other stakeholders are!

Anticipate closure objectives Manage operations to minimize clean-up/rehabilitation activities Manage landscape to convert liabilities into assets

Complete Problem Formulation activities before drafting discipline workplans Get the right questions right! Identify interactions/synergies Match data needs with decisions to be made Achieve efficiency in gathering data whether from literature searches or through

new sampling efforts Achieve efficiency in the analyses of data

Outcome Determines how the remainder of the assessment is conducted the robustness of the analysis

Should constitute 50% or more of the cost of a risk assessment


Project-specific Conceptual ModelsThey are pictorial/narrative descriptions of how the project, stressor, or event is perceived to work in the specific ecological setting and context It is not about right and wrong! Often organized around trophic food webs In risk, models are intended to reflect values to be

assessed/protected and to show interrelationships through transfers along biotic and abiotic pathways

During the Problem Formulation stage a lot of critical thinking has to be done to reach an agreed Conceptual Model that ultimately guides the rest of the assessment process and continues through to the decision stage

But to what detail?


Choices for EcoRA focus

spatial scale temporal scale pathways consequencessitereachwatershedregionglobal

acuteepisodicchronicgenerational

bioticabioticcombined

organism (statistical population)population (biological)speciesecological system


Assessment Endpoint: DefinitionAn assessment endpoint is the formal expression of an actual environmental value of concern that can be evaluated objectively either through direct measurement/observation or through a logical relationship with a surrogate measurement or observation


Assessment Endpoints An Assessment Endpoint, at minimum, includes an entity and an

attribute, a location; time period is useful, but optional as it may be specified by regulations An entity (e.g., a species or population of interest) An attribute (e.g., number, size, rate, condition) A location (e.g., a specific reach of a stream)

Examples Ecological Receptors: {entity} {attribute} {location} The growth of trout in Fish Creek

An organism attribute associated with the individuals in an assessment population

The productivity of the trout population in Fish CreekA population attribute associated with an individual assessment population

The average productivity of trout populations in Region YA population attribute associated with a set of populations

After Suter et al. (2000), US EPA (2003), and Barnthouse et al. (2007)


Assessment Endpoints (Continued)Examples Human Health: {entity} {attribute} {location}

Diets with respect to EDC of reproductive-age women in Community XProtective of reproductive health of a sensitive sub-population

Drinking water with respect to arsenic and nitrite for children in Community XProtective of individuals

Air quality with respect to concentrations of PM2.5 for elderly in Region YProtective of respiratory health of human population in the region

56Assessing Risks to Humans and the Environment

Assessment Endpoint Guidance


Presents policy and technical foundation for adopting a wide range of assessment endpoints.

Measurement Endpoint: DefinitionA measurement endpoint is the categorical or quantitative expression of an observed or measured parameter and is linked directly to the assessment endpoint. For example, a school of fish may be observed directly or the effect of a substance may be evaluated through inference using toxicity tests from indicator/surrogate species and predicted exposure for the members of the population.

Examples

Mass of fish in a particular waterbody Rate of growth of young-of-year fish in a waterbody Yield of grain in a field Number of offspring in a population


sAssessing Risks to Humans and the Environment 59

Data Quality Objectives (DQOs)DQOs provide the foundation for an effective risk assessment by

specifying the levels of uncertainty permissible that will allow one to draw conclusions informing the decisions to be made

guiding the selection of sampling and measurement methods

bounding parameters in a Sampling and Analysis Plan (SAP)Developing DQOs is an iterative process that revolves around matching method detection limits with assessment requirements and serves to optimize the study plan by evaluating the signal noise and potential interferences associated with the chosen method


Sampling and Analysis Plan How does one get started? What should go into a site-specific model for potential

remediation of hot spots?

What does a site-specific sampling and analysis plan accomplish?

Why is it important to follow a data quality objective process?


Sampling and Analysis Plan (SAP)A SAP (or Workplan) provides project-specific details pertaining to all phases of

acquiring data type of sample number of samples location of samples methods used to measure parameters

analyzing data verification of authenticity of data (chain-of-custody as appropriate) processing (entry, simple descriptive statistics) statistical assumptions statistical methods presentation form (e.g., tables, graphs) interpretation/decision criteria


Understand the overarching goals of the assessment What decisions are to be made? Who will make the decisions? What input will other affected stakeholders have regarding

the decisions to be made? What factors (e.g., cost, time) influence the work to be

done? Technical components of Problem Formulation

Construct Project-specific Conceptual Model Agree on the Assessment Species (the Valued Ecological

Components) to be protected Articulate the Assessment Endpoints Define the Data Quality Objectives Select the Measurement Endpoints (i.e., what will be

measured) Prepare a Project-specific Sampling and Analysis Plan Prepare a Project-specific Quality Assurance Plan

Iterate until there is consensus (if possible) on all aspects of the work before preceding with the rest of the assessment!Revisit the overarching goals and decisions to be made if needed before completing Problem Formulation.

Iteration in Problem Formulation


Why is ecological risk assessment used today?


Current Uses of Ecological Risk Assessment

Evaluate remediation options to clean up hazardous wastes

Manage new chemicals/substances safely


Registration, Evaluation, Authorisation and Restriction of CHemical Substances [REACH]

European Community law in force since 1 June 2007 Protect humans and the environment REACH Regulation gives greater responsibility to industry to manage the risks

from chemicals and to provide safety information

register the information in a central database run by the European Chemicals Agency (ECHA) in Helsinki

http://ec.europa.eu/environment/chemicals/reach/reach_intro.htm


Linear Framework


AfterFigure1.3.fromvanLeeuwenandVermeire(2007)

Hazard IdentificationHazard Identification

Risk CharacterizationRisk Characterization

Risk Classification

Benefit:Risk Analysis

Risk Reduction

Monitoring

Exposure AssessmentExposure Assessment Effects AssessmentEffects Assessment

Tiers of Risk Assessment Scoping (Tier 1)

Coarse

Minimum data acquired

Highly protective default assumptions

Screening (Tier 2)

Some refinement

More data acquired

Still relying on protective default assumptions

Definitive (Tier 3)

Finer detail

Considerable data acquired

Greater realism replaces default assumptions

Complementary representation in next slide.


??

Iterative Framework


ScopingProblem FormulationAnalysisRisk Characterization

RiskAssessmentandRiskManagementintegratedthroughouttheprocess

No

Yes

ScreeningProblem FormulationAnalysisRisk Characterization

DefinitiveProblem FormulationAnalysisRisk Characterization

Decision

No

Yes Decision

Decision

a relatively simple hypothetical case

The task is to examine the information, sketchy as it is, and decide how you would address the concerns.

Working groups to determine:

What should the management goals be? How would one get information needed to manage the situation? What would one do once you got the information?


Brown circles are miscellaneous waste piles from mining operations, oil drums, includes tires, electrical transformers, etc.

Blue lines (solid and dashed) designate streams

Agricultural field

Tailings Pond[As,

Se, U, etc.]

Pasture for Dairy Cattle

Wind pattern Resident complaints:

Milk tastes badLivestock miscarriagesKids often sickFish in river have tumoursWater has bad tasteChickens lay too few eggsAir stinks

Define management objectives such that a sampling plan to determine if there are real problems could be developed for an initial budget of 20.000


Town

= Farmstead

Risk assessment from a landscape perspective


Landscape Ecology

Formal characterization of spatial patterns of physiognomy/vegetation (type) grain size patch size (extent) connectivity

Builds upon classical ecology measures of communities, life-forms, distribution and abundance of species

Readily amenable to mapping routines including GIS techniques to create multiple views developed using different spatial scales of resolution

Geo-referenced layers (e.g., distribution of stressors such as chemicals, radionuclides, biota, physical parameters) link various databases to achieve multiple computational steps


1 km


Relevant spatial scales a landscape perspective


Image from www.omfra.gov.on.ca accessed June 2014

Bacteria -

climate

vegetation

soil

wildlife habitat(food, shelter)

landuse

population size(governed by habitat quality;

toxic substances but one factor)


Importance of Habitat in EcoRA

Wildlife respond to differences in landscape features (attraction, avoidance)

Spatial relationships between stressors and foraging activities influence exposure Co-located distributions increase exposure Disjoint distributions decrease exposure


Characterizing Habitat

Landscape features (vegetation cover, food items, physical components, etc.)

Range in degrees of sophistication Binary Proportional index

Qualitative (i.e., not explicitly linked to density) Semi- or Pseudo-quantitative

Absolute,QuantitativeMultiple regression Factor analyses


Strategy for Using Spatially-explicit Exposure Assessment

1. Identify scenarios where habitat maybe an important determinant

2. Considerations in selecting assessment species Home/forage range Available habitat suitability models Reasonable knowledge of dietary preferences (e.g., EPA exposure

handbook ) Expected to frequent the area (wildlife distribution information such

as breeding bird survey)

3. Use habitat quality to weight exposure estimates4. Develop a comprehensive workplan

staged from reconnaissance through definitive stages connected to remediation goals and post-remediation monitoring

effort


++OO

O++O

O+OO

heterogeneoushomogeneous

heterogeneousheterogeneous

homogeneousheterogeneous

homogeneoushomogeneous

spatial relationshiphabitatagent

Contingency table illustration relationships of home range (green circle) relative to site size (gold square) -- cases where habitat characterization may be useful in reducing uncertainty of exposure estimates (+) and cases where habitat considerations may be moot (O). (Adapted from Kapustka et al., 2001).


Hypothetical Foraging Pattern using Habitat Quality as an Attractant


Landscape Perspective LevelofAnalysis

Level of Organization (Scale Independent)

Ecological Type Component of

interest

Level of Observation Scale (Grain and

Extent)

Type Dependant Organism,

Population, Community

Change one; changes the Level of Analysis

Moves up-scale are where things usually go bad

Relates back to setting Assessment Endpoints Measurement Endpoints Data Quality Objectives

Multi-scale, multi-criteria analyses

Short-term, Long-term Scenarios


Fallacy of Averages

1.Heterogeneity in Ecological Systems (non-random distribution)

Physical features

Biotic features

2. Non-linear processes

Requires segregating landscape types into bins along gradients or at discontinuities (consistent with polygon delineation in mapping; GIS)


Predicted degradation of a hypothetical contaminant in a thermally-stratified lake. (Johnson and Turner 2010)

Ecological Fallacy Improper inferences

made from data where individual responses are aggregated into groups

Changing the spatial grain of the data, by aggregating individuals or small groups into larger groups (i.e., an extrapolation across scale) affects computed correlations


.

Human presence and biodiversity Positive correlation at grain >1 km Negative correlation at finer scale Over at least four orders of magnitude, the

correlation varies linearly with the logarithm of scale (grain or extent)

Pautasso M. 2007. Scale dependence of the correlation between human population presence and vertebrate and plant species richness. Ecol Lett10:1624.

Johnson and Turner (2010)

Metapopulations-level considerationsCase I Case II

Case III Case IV

Case I Case II

Case III Case IV


Metapopulation Consequences


A B C

stressor

N

to tj

N

to tj

N

to tj

Adapted from:Spromberg, J. A., B. M. Johns and W. G. Landis. 1998. Environ. Toxicol. Chem. 17:1640-1649Macovsky, Louis-A Test of the Action at a Distance Hypothesis using Insect Metapopulations (Dr. Landis-Huxley College). 1999

Reconnaissance Visit -- Habitat Checklist

Wildlife Habitat Present

Determine Agents of Concern

Select Assessment Species

Compile Habitat

Parameters for

Assessment Species

Stop

Problem Formulation Orientation Regional Ecology Context

yes

no



Compile Habitat

Parameters for

Assessment Species

Analysis

Delineate habitat areas (qualitatively by cover types, terrain, etc.)

Acquire HSI input data

Calculate HSIs

Estimate Exposure [i.e., wildlife exposure factors --

separately for each zone; each species]

Estimate Population (N)

by zone; species

N=Area x HSI x CC

Modify Exposure Estimates




Risk Characterization

Determine Magnitude and Extent of Affected

Populations

Uncertainty Analyses

Sensitivity Analyses

Risk Communication

Risk Management



Equation 1. For use with home range data

s

ss HR

AN Equation 2. For use with density data.

sss CCAN Where:

Ns = the number of individuals likely to inhabit the subdivision

As = the area of the subdivision

HRs = the approximate home range size of the animals within the

subdivision

CCs = the approximate carrying capacity of the subdivision where

carrying capacity is an expected density estimateFrom: ASTM E2385 Standard Guide for Estimating Wildlife Exposure using Measures of Habitat Quality


ns s

s

s

s

s

HRAHR

AP

1

Where:

Ps = Proportion of time spent foraging in sub-area s

As = Area of sub-area s

HRs = home range size associated with habitat quality in sub-area s

Equation 3. Time allocation as a function of habitat quality

From: ASTM E2385 Standard Guide for Estimating Wildlife Exposure using Measures of Habitat Quality


Equation 4. The basic exposure estimate used to calculate daily dose modified to incorporate Habitat Quality.

m

spotADD

1

n

1jtotalsjjsjss )FIRFS(D)NIR FR (CP

Where:

ADDpot = Potential average daily dose

Ps = AUF; the proportion of time spent foraging in sub-area s (equation 2)

Cjs = Average concentration of contaminant in food type j in sub-area s

FRjs = Fraction of food type j contaminated in sub-area s

NIRj = Normalized ingestion rate of food type j

Ds = Average contaminant concentration in soils in sub-area s

NIRtotal = Normalized ingestion rate summed over all foods

FS = Fraction of soil in dietFrom: ASTM E2385 Standard Guide for Estimating Wildlife Exposure using Measures of Habitat Quality

Risk Trace

Probabilistic receptor migration model. Generates receptor movement influenced by

habitat quality.

Spatially explicit exposure assessment model. Calculates internal exposure resulting from

ingestion of contaminated food, as well as any other applicable routes of exposure (e.g., soil).

Screening-level risk assessment model. Calculates Hazard Quotients (HQs) for each

contaminant; these are equal to the site contaminant concentration divided by the selected safe benchmark concentration for ecological receptors (toxicity reference values, TRVs).


Compile Habitat

Parameters for

Assessment Species

Analysis

Delineate habitat areas (qualitatively by cover types, terrain, etc.)

Acquire HSI input data

Calculate HSIs

Estimate Exposure [i.e., wildlife exposure factors --

separately for each zone; each species]

Estimate Population (N)

by zone; species

N=Area x HSI x CC




habitat units defined on recognizable polygons of vegetation cover and physiognomy


HSI=0.85

HSI=0.55

HSI=0.45

HSI=0.15

HSI=0.85

HSI=0.55

HSI=0.45

HSI=0.15

HSI=0.85

HSI=0.55

HSI=0.45

HSI=0.15

a1

a2

b1b2

b3

c1

c2

c3

c4

b4subunits defined by habitat x conc.Within each:bootstrap concentrationcombine with HSIsum resulting exposure estimate

overlay

habitat units CoC distribution


HSI=0.85

HSI=0.55

HSI=0.45

HSI=0.15

HSI=0.85

HSI=0.55

HSI=0.45

HSI=0.15

HSI=0.85

HSI=0.55

HSI=0.45

HSI=0.15

a1

a2

b1b2

b3

c1

c2

c3

c4

b4

overlay

habitat units CoC distribution

risk calculated for each subunit:high-risk areas targeted for intrusive clean-uplow-risk areas identified for habitat enhancement

habitatenhancementarea



potentialintrusivecleanuparea

conclusions Basic measures of landscapes (vegetation, physiognomy) used to

parameterize HSI, HEA models.

quantify habitat quality by polygons iterative calculations accumulate multiple HSIs for each polygon GIS techniques used to identify zones or nodes of convergence of high-

valued habitats

Scale must be adjusted for each assessment species if one is to avoid the Fallacy of Averages and the Ecological Fallacy

Traditional Risk estimates modified by HSI values. Hierarchical theory should be used to understand context and explore

mechanisms

Ecological problems are best viewed as wicked problems!


complex case study

Large area with legacy mines, operating mines, and proposed mines Legacy mines in various stages of remediation/restoration Chemicals of concern include Ba, Cd, Co, Cu, Po, Pb, Ra, Rn, Se, Sr, and U Applications for proposed mines in review Area has listed species of terrestrial and aquatic habitats for plants, birds,

fish, and amphibians

Area is used for timber harvest and agriculture Popular recreational area (hiking, photography, camping, birding, hunting,

and fishing)

[Notional map on next slide]



Abandoned

Company A

Legacy

Active Company A

Company B

Company A,B

Company C

Proposed Company C

Company A,B10 Km

Intriguing Literature

Mandelbrot, Benoit see Gleick, James (1987). Chaos: Making a New Science. London: Cardinal. p. 229

May, Robert M. 1976. Simple mathematical models with very complicated dynamics. Nature 261:459-467

Rittel H, Webber M. 1973. Dilemmas in a general theory of planning. Policy Sci 4:155169.

Thoreau, Henry David. 1854. Walden; or Life in the Woods. Ticknor and Fields, Boston.

Taleb, Nassim Nicholas. 2001. Fooled by Randomness: The Hidden Role of Chance in Life and in the Markets. Random House, New York

Taleb, Nassim Nicholas. 2007. The Black Swan: The Impact of the Highly Improbable. Random House, New York

Gladwell, Malcolm. 2005. Blink: the Power of Thinking without Thinking. Little Brown, and Company, New York


References and Selected Readings ASTM-I. 2009. E-1689 Standard Guide for Developing Conceptual Site Models for Contaminated Sites. Annual Book of

Standards. American Society for Testing and Materials-International, Conshohocken, Pennsylvania USA

ASTM-I. 2009. E2348 Standard Guide for Framework for a Consensus-based Environmental Decision-making Process. Annual Book of Standards. American Society For Testing and Materials-International, Conshohocken, Pennsylvania USA

Barnthouse, L. 2008. The Strengths of the Ecological Risk Assessment Process: Linking Science to Decision Making. Integr Environ Assess Manage 4:299-305.

Holling CS. 1992. Cross-scale morphology, geometry and dynamics of ecosystems. Ecological Monographs. Volume 62, Number 4. Pages 447 to 502.

Kapustka L, McCormick R, Froese K. 2008. Social and Ecological Challenges within the Realm of Environmental Security. pp 203 211 in Linkov I, Ferguson E, Magar VS. (eds) Real-time and Deliberative Decision Making. Springer, The Netherlands. 456 pp.

Kapustka LA , Landis WG. (Eds.) 2010. Environmental Risk Assessment and Management from a Landscape Perspective. John Wiley & Sons, Hoboken, NJ 396 pp.

Kapustka LA. Limitations of the Current Practices Used to Perform Ecological Risk Assessment. Integr Environ Assess Manage4:290-298.Ka

Kiker GA, Bridges TS, Varghese A, Seager TP, Linkov I. 2005. Application of Multicriteria Decision Analyses in Environmental Decisions Making. Integr. Environ. Assess. Manag. 1:95-108.

Linkov I, Satterstrom FK, Kiker GA, Bridges TS, Benjamin SL, Belluck DA. 2006. From optimization to adaptation: shifting paradigms in environmental management and their application to remedial decisions. Integr. Environ. Assess. Manag. 2:92-98.

Suter GW. 2008. Ecological Risk Assessment in the United States Environmental Protection Agency: A Historical Overview. Integr Environ Assess Manage 4:285-289.

Van Leeuwen CJ. 2007. Introduction. In: Risk assessment of chemicals. In: Risk Assessment of Chemicals. An Introduction (2nd edition). Van Leeuwen, C.J. and T.G. Vermeire, eds. Springer Publishers, Dordrecht, The Netherlands, pp 1-36.


Selected Websites of Interest ASTM-I (Standards): www.astm.org DQO training: http://epa.gov/quality//trcourse.html#intro_dqos European Chemicals Agency: http://ec.europa.eu/echa/home_en.html European Chemicals Bureau: http://ecb.jrc.it/reach/ European Commission

http://ec.europa.eu/environment/chemicals/reach/reach_intro.htm

http://www.epa.gov/nerleerd/stat2.htm http://www.library.uiuc.edu/envi/toxigateway.htm SAICM: http://www.saicm.org/index.php?ql=h&content=home US EPA on DQOs: http://epa.gov/quality/dqos.html US EPA on hazardous waste cleanup and training: http://www.clu-in.org US EPA on Risk Assessment: http://www.gov/oswer/riskassessment


kapustka assessing risk of chemicals and radiation

Documents

ecological risk assessments

feedback ecological

neutral ecological resources

different humans cultural

biases ecology

environmental decisionmaking

exposure estimates kapustka

future structures