1、Designation: E2385 11 (Reapproved 2016)Standard Guide forEstimating Wildlife Exposure Using Measures of HabitatQuality1This standard is issued under the fixed designation E2385; the number immediately following the designation indicates the year oforiginal adoption or, in the case of revision, the y
2、ear of last revision. A number in parentheses indicates the year of last reapproval. Asuperscript epsilon () indicates an editorial change since the last revision or reapproval.1. Scope1.1 Ecological Risk Assessments (EcoRAs) typically focuson valued wildlife populations. Regulatory authority for co
3、n-ducting EcoRAs derives from various federal laws forexample, Comprehensive Environmental Response, Compen-sation and Liability Act 1981, (CERCLA), Resource Conser-vation Recovery Act (RCRA), and Federal Insecticide,Fungicide, and Rodenticide Act, (FIFRA). Certain proceduresfor conducting EcoRAs (1
4、-4)2have been standardized E1689-95(2003) Standard Guide for Developing Conceptual SiteModels for Contaminated Sites; E1848-96(2003) StandardGuide for Selecting and Using Ecological Endpoints forContaminated Sites; E2020-99a Standard Guide for Data andInformation Options for Conducting an Ecological
5、 Risk As-sessment at Contaminated Sites; E2205/E2205M-02 StandardGuide for Risk-Based Corrective Action for Protection ofEcological resources; E1739-95(2002) Standard Guide forRisk-Based Corrective Action Applied at Petroleum ReleaseSites. Specialized cases for reporting data have also beenstandardi
6、zed E1849-96(2002) Standard Guide for Fish andWildlife Incident Monitoring and Reporting as have samplingprocedures to characterize vegetation E1923-97(2003) Stan-dard Guide for Sampling Terrestrial and Wetlands Vegetation.1.2 Most states have enacted laws modeled after the federalacts and follow si
7、milar procedures. Typically, estimates oflikely exposure levels to constituents of potential concern(CoPC) are compared to toxicity benchmark values orconcentration-response profiles to establish the magnitude ofrisk posed by the CoPC and to inform risk managers consid-ering potential mitigation/rem
8、ediation options. The likelihoodof exposure is influenced greatly by the foraging behavior andresidence time of the animals of interest in the areas containingsignificant concentrations of the CoPC. Foraging behavior andresidence time of the animals are related to landscape features(vegetation and p
9、hysiognomy) that comprise suitable habitatfor the species. This guide presents a framework for incorpo-rating habitat quality into the calculation of exposure levels foruse in EcoRAs.1.3 This guide is intended only as a framework for usingmeasures of habitat quality in species specific habitat suita
10、bil-ity models to assist with the calculation of exposure levels inEcoRA. Information from published Habitat Suitability Index(HSI) models (5) is used in this guide. The user should becomefamiliar with the strengths and limitations of any particular HSImodel used in order to characterize uncertainty
11、 in the exposureassessment (5-7). For species that do not have publishedhabitat suitability models, the user may elect to develop broadcategorical descriptions of habitat quality for use in estimatingexposure.2. Referenced Documents2.1 ASTM Standards:3E1689 Guide for Developing Conceptual Site Model
12、s forContaminated SitesE1739 Guide for Risk-Based Corrective Action Applied atPetroleum Release SitesE1848 Guide for Selecting and Using Ecological Endpointsfor Contaminated SitesE1849 Guide for Fish and Wildlife Incident Monitoring andReportingE1923 Guide for Sampling Terrestrial and Wetlands Veget
13、a-tion (Withdrawn 2013)4E2020 Guide for Data and Information Options for Conduct-ing an Ecological Risk Assessment at Contaminated SitesE2205/E2205M Guide for Risk-Based Corrective Action forProtection of Ecological Resources3. Terminology3.1 The words “must,” “should,” “may,” “can,” and “might”have
14、 specific meanings in this guide. “Must” is used to express1This guide is under the jurisdiction ofASTM Committee E50 on EnvironmentalAssessment, Risk Management and Corrective Action and is the direct responsibil-ity of Subcommittee E50.47 on Biological Effects and Environmental Fate.Current editio
15、n approved Feb. 1, 2016. Published May 2016. Originallyapproved in 2004. Last previous edition approved in 2011 as E238511. DOI:10.1520/E2385-11R16.2The boldface numbers in parentheses refer to the list of references at the end ofthis standard.3For referenced ASTM standards, visit the ASTM website,
16、www.astm.org, orcontact ASTM Customer Service at serviceastm.org. For Annual Book of ASTMStandards volume information, refer to the standards Document Summary page onthe ASTM website.4The last approved version of this historical standard is referenced onwww.astm.org.Copyright ASTM International, 100
17、 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959. United States1an absolute requirement, that is, to state that the test ought tobe designed to satisfy the specified condition, unless thepurpose of the test requires a different design. “Should” is usedto state that the specified con
18、dition is recommended and oughtto be met if possible. Although violation of one “should” israrely a serious matter, violation of several will often render theresults questionable. “May” is used to mean “is (are) allowedto,” “can” is used to mean “is (are) able to,” and “might” isused to mean “could
19、be possible.” Thus, the distinctionbetween “may” and “can” is preserved, and “might” is neverused as a synonym for either “may” or “can.”3.2 Consistent use of terminology is essential for anyvegetation sampling effort. below is a list of terms that are usedin this guide, as well as others that may b
20、e encounteredcommonly in the wildlife habitat quality literature. this list isnot exhaustive.3.3 Definitions of Terms Specific to This Standard:3.3.1 abundancethe number of individuals of one taxon inan area; equivalent to the term density as used in botanicalliterature.3.3.2 basal area (BA)the cros
21、s-sectional area of a treetrunk at 1.4 m (4.5 ft) above ground. (See diameter at breastheight.)3.3.3 biomassthe mass of vegetation per unit area.3.3.4 canopythe uppermost layer, consisting of branchesand leaves of trees and shrubs, in a forest or woodland.3.3.5 carrying capacitythe theoretical densi
22、ty of organ-isms that can be supported in a specified ecological system.3.3.6 coverthe area of ground covered by plants of one ormore taxa.3.3.7 densitythe number of organisms in a specified area.3.3.8 diameter at breast height (DBH)the widest point ofa tree trunk measured 1.4 m (4.5 ft) above the g
23、round.3.3.9 foraging-rangethe area typically explored by ananimal while it is feeding. (See home-range.)3.3.10 forba non-graminoid (that is, broadleaf) herba-ceous plant.3.3.11 geographic information system (GIS)an integratedspatial data base and mapping system in which geographicalinformation can b
24、e used to produce digital maps, manipulatespatial data, and model spatial information. It allows theoverlay of layers of information, such as habitats or plantranges.3.3.12 global positioning system (GPS)a survey system inwhich a GPS unit is used to receive signals from satellites.Signals are then i
25、nterpreted to provide information such aslatitude and longitude or bearings for navigation, positioning,or mapping.3.3.13 graminoida grass (Poaceae), sedge (Cyperaceae),or rush (Juncaceae).3.3.14 habitatthe collection of biological, chemical, andphysical features of a landscape that provide conditio
26、ns for anorganism to live and reproduce.3.3.15 habitat suitability indexa calculated value thatcharacterizes a specified landscape unit (for example, a poly-gon) in terms of the features and conditions that are favorablefor a particular species. Values range between 0.0 (unsuitable)and 1.0 (ideal).3
27、.3.16 herba plant with one or more stems that die back tothe ground each year; (that is, graminoids and forbs).3.3.17 home-rangethe area around an animals estab-lished home, which is traversed in normal activities. (Seeforaging-range.)3.3.18 physiognomythe surface features of an area.3.3.19 populati
28、ona group of individuals of the samespecies occupying a habitat small enough to permit interbreed-ing.3.3.20 remote sensingthe use of satellites or high-altitudephotography to measure geographic patterns such as vegeta-tion.3.3.21 shrubwoody plant typically smaller than a treewhen both are mature (t
29、ypically with DBH 2to3mtall when mature (typically DBH 10 cm). The operational definition should be stated explicitlyfor each project.4. Habitat Approaches4.1 Naturalists and wildlife managers have understood, atleast in qualitative terms, the importance of critical habitat forvarious life history s
30、tages (for example, nesting sites, winterrange, etc.). Animals are drawn to suitable physical structureand food availability, while avoiding areas of lower quality.The term habitat, though often used loosely as an indication ofenvironmental quality, refers to the combination of physicaland biologica
31、l features preferred by a particular species.Habitat that is great for prairie chicken is unacceptable forbarred owls. Different habitat preferences reflect evolution andadaptation of species separating from each other in “n-dimensional niche space” (8). There are differential area userates by diffe
32、rent species. Animals are drawn to particularfeatures of the landscape for foraging, loafing, nesting/birthing,etc. Some species are attracted to disturbance zones and edges,but others avoid such areas.4.2 Habitat Suitability Index (HSI) Models have been de-veloped for many species of interest. Char
33、acterization ofhabitat for certain species was formalized by the U.S. Fish andWildlife Service in the 1990s (9). Currently, more than 160 HSImodels have been published, though usage is limited forquantitative predictions of population densities (6). Rand andNewman (10) describe the applicability of
34、HSI models forEcoRAin general terms, but provide no examples of its use anddo not give specific details to integrate habitat information withexposure assessment or risk characterization. Freshman andMenzie (11) describe two approaches to take into accountspatial differences in contaminant concentrat
35、ions with respectto foraging activities and the proportion of a local populationE2385 11 (2016)2likely to be exposed to the contaminants. Their approach doesnot incorporate HSI models formally, but does demonstrate thefundamental concepts for such use. Hope (12-14), Wickwire etal. (15), Linkov et al
36、. (16, 17) and Linkov and Grebenkov (18)have used placeholder habitat values to illustrate the effect ofhabitat on cumulative exposure levels. Kapustka et al. (5, 19)and Linkov et al. (20) have described procedures to use HSIsas the habitat quality parameter for use in estimating exposurelevels. The
37、 U.S. EPA Office of Solid Waste conducted anexploratory program in which they characterized vegetationtypes and physical features within a 2-km radius of more than200 chemically contaminated sites. The focus was on usinghabitat characteristics to modify estimates of risk. Landscaperelationships were
38、 used to incorporate ecological dynamicsinto risk assessments by another group within the U.S. EPA.The Program to Assist in Tracking Critical Habitat (PATCH)model used a GIS platform that allows user input in definingpolygons and their characteristics (21); www.epa.gov/wed/pages/models.htm). This pr
39、ogram has been incorporated intoHexSim(22). The Army Risk Assessment Modeling System(ARAMS) (www.wes.army.mil/el/arams/arams.html) devel-oped modules that use habitat quality assessments to improvethe realism of exposure assessments. Loos et al. (23) developeda receptor-oriented cumulative exposure
40、model (Eco-SpaCE)for wildlife species that includes relevant ecological processessuch as spatial habitat variation, food web relations, predation,and life history characteristics. Johnson et al. (24) found that aspatially explicit exposure model based on the general proce-dures outlined in this Stan
41、dard provided good agreement withfield observations and therefore produced more accurate riskestimates than conventional deterministic approaches. Loos etal. (25) provided a comparative review of approaches used tomodel exposures experienced by humans and wildlife. Wick-wire et al. (26) discussed th
42、e rationale for using spatiallyexplicit exposure models and also describe some of theimpediments that may be deterring a broader use of suchapproaches.5. Identifying Scenarios where Habitat Value can beImportant in EcoRAs5.1 Heterogeneous landscapes coupled with heterogeneousdistribution of contamin
43、ants introduce great uncertainty inexposure estimates for any species (Fig. 1). In such situations,the relative size of the site to the home range of the speciesdoes not matter. Two other cases occur in which habitatmodifications of exposure estimates would reduce uncertainty;one in which contaminan
44、t distribution is heterogeneous andhome range is small relative to the area of the site, the other inwhich habitat is heterogeneous and the home range is verylarge relative to the contaminated area. The combination ofhomogeneous habitat and homogeneous contaminant distribu-tion precludes using habit
45、at conditions as a modifier ofexposure regardless of the home range to site area relationship.Homogeneous contaminant distribution also makes habitatconditions moot for species with home ranges equal to or lessthan the site. Finally, with homogeneous habitat conditions,exposure estimates for species
46、 having home ranges equal to orlarger than the contaminated area would not be improved.6. Significance and Use6.1 Explicit consideration of landscape features to charac-terize the quality of habitat for assessment species can enhancethe ecological relevance of an EcoRA. This can help avoidassessing
47、exposure in areas in which a wildlife species wouldbe absent because of a lack of habitat or to bound exposureestimates in areas with low habitat quality. The measure ofCases where habitat characterization may be useful in reducing uncertainty of exposure estimates (+) and cases where habitat consid
48、erations may be moot (O).Adapted from Kapustka et al., 2001, (5).FIG. 1 Contingency Table Illustrating Relationships of Home Range (Circle) Relative to Site Size (Square).E2385 11 (2016)3habitat quality is used in place of the commonly usedArea UseFactor (AUF). Greater ecological realism and more in
49、formedmanagement decisions can be realized through better use oflandscape features to characterize sites.7. Interference7.1 Observed population density in field tests often is lowerthan expected based on HSI values (6). Such information canbe interpreted as a deficiency. However, it can also be thatexpectations of precision are too great and beyond the capa-bility of the model (7). HSI model predictions should beviewed as an indication of potential carrying capacity gener-alized over time, rather than a static predictor of populationdensity, and then t
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