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U.S. Environmental Protection Agency
Office of Research and Development
National Center for Environmental Research
Science to Achieve Results (STAR) Program
CLOSED - FOR REFERENCES PURPOSES ONLY
Wildlife Risk Assessment
Opening Date:
June 20, 2000
Closing Date:
October 17, 2000
Background
Research
Objectives
References
Funding
Eligibility
Standard
Instructions for Submitting an Application
Special
Requirement
Contacts
Get Forms and Standard Instructions
The ability to evaluate impacts of stressors on wildlife species is limited by many scientific uncertainties. This solicitation will support research to develop scientifically valid approaches for assessing and comparing the risks to a population of a wildlife species from multiple stressors. Stressors include (but are not limited to) contaminants, habitat loss or alterations, and introduced species. For the purposes of this solicitation, wildlife is defined as birds, mammals, amphibians, and reptiles. Research proposed through this solicitation should support a tiered approach to wildlife risk assessment, with the tiers progressing from general and broadly-based (screening level) to more realistic, accurate and situation-specific (definitive level) assessments. Such an approach permits development of wildlife risk assessments for a wide variety of applications with the sustainability of wildlife species populations remaining the assessment endpoint of concern. Such research would benefit federal, state, and local programs struggling to determine the relative risks posed by different stressors to populations of individual wildlife species.
In order to better predict the population-level responses of wildlife species to stressors, the tools of wildlife toxicology, population biology, and conservation biology need to be integrated so that stressor-response relationships can be considered in the context of a species’ life history and habitat requirements. Population models are a tool common to each of these disciplines (subdisciplines) and represent a means of integrating these approaches. For example, population models have been used to project population-level effects of chemicals on wildlife species (Caswell 1996; Munns et al. 1997) and to evaluate conservation measures for threatened and endangered species (Crouse, et al. 1987; Doak et al. 1994; Caswell et al. 1999). Additional uncertainties are introduced when wildlife risk assessments attempt to address the effects of multiple stressors and habitat characteristics on a wildlife population within a specific landscape. Numerous studies have documented that habitat characteristics and variability play an important role in influencing the long-term viability of a population (Doak et al. 1992; Kareiva and Wennergren 1995; Vitousek et al. 1997; Fahrig 1998). Many state and federal programs, given their responsibilities for resource management and contaminant clean-up and control, need novel approaches to assess the risks to wildlife species from contaminants within the context of the many other stressors that may affect them in a given landscape. It is anticipated that research supported through this solicitation will further develop population modeling and spatially-explicit modeling approaches and will improve the ability to assess and manage the risks posed to wildlife from multiple stressors at the national, state and local scale.
WILDLIFE RISK ASSESSMENT RESEARCH OBJECTIVES
This RFA solicits research to develop approaches to evaluate the relative and combined risks of multiple stressors (e.g., habitat alteration, chemical pollution, and presence of nonindigenous species) to the sustainability of a wildlife population. Research should be framed in a spatially explicit or landscape context and be directed towards one of two areas:
Area 1: Research to understand risks to a specific population or species of wildlife (e.g., threatened or endangered, or of particular interest to stakeholder groups). Research in area 1 should result in the development of species-specific models of population dynamics, as influenced by the combined effects of multiple stressors; generation of life history and demographic data (e.g., rates of survival, fecundity, and growth) for the identified species, and development of stressor-response relationships relating effects of stressors on demographic rates. This research should enhance the understanding of the real-world risks posed by multiple stressors to these identified species.
Area 2: Research to develop generalized approaches for assessing risks to wildlife populations. Research in area 2 should result in methods and approaches useful for predicting risk to wildlife populations as functions of their life history and demographic characteristics, and the characteristics of the stressors and habitats within which they live. Emphasis should be given to developing modeling approaches for predicting how multiple stressors in combination affect wildlife population dynamics. Proposed research should stress the applicability of methods and approaches to broad classes of wildlife species, perhaps representing a range of life history strategies or susceptibilities to stressors.
All proposed research should address explicitly the spatial and temporal heterogeneity of wildlife populations and stressors and the interactions of populations and stressors within landscapes. Proposed efforts also should: (1) provide population-specific models or modeling approaches that can integrate stressor-response data; (2) be compatible with spatially-explicit modeling approaches; and (3) enhance understanding of the importance of compensatory mechanisms (e.g., density dependence, tolerance, local adaptation) in wildlife populations, since they have the potential to significantly influence population response.
Funded proposals should result in assessment methods and approaches that can be used by resource managers to assess risk to wildlife populations. Desirable features of these methods and approaches include: (1) applicability in screening-level and/or definitive assessments; (2) ease of application and interpretation; and (3) utility in comparisons of alternate management scenarios.
Caswell, H. 1996. Demography meets ecotoxicology: untangling the population level effects of toxic substances. In: Newman, M.C. and C.H. Jagoe, Eds. Ecotoxicology: a Hierarchical Treatment. CRC Press, Lewis Publishers, Boca Raton, FL.
Caswell, H., M. Fujiwari and S. Brault. 1999. Declining survival probability threatens the North Atlantic right whale. Proc. Nat. Acad. Sci. 96:3308-3313.
Crouse, D.T., L.B. Crowder and H. Caswell. 1987. A stage-based population model for loggerhead seaturtles and implications for conservation. Ecology 68:1412-1423.
Doak, D. F., P. C. Marino and P. M. Kareiva. 1992. Spatial scale mediates the influence of habitat fragmentation on dispersal success: implications for conservation. Theoret. Pop. Biol. 41:315-336.
Doak, D., P. Kareiva and B. Klepetka. 1994. Modeling population viability for the desert tortoise in the western Mohave Desert. Ecol. Appl. 4:446-460.
Fahrig, L. 1998. When does fragmentation of breeding habitat affect population survival? Ecol. Model. 105:273-292.
Kareiva, P. and U. Wennergren. 1995. Connecting landscape patterns to ecosystem and population processes. Nature 373:299-302.
Munns, W.M., Jr., D.E. Black, T.R. Gleason, K. Salomon, D.A. Bengtson and R. Gutjahr-Gobell. 1997. Evaluation of the effects of dioxin and PCBs on Fundulus heteroclitus populations using a modeling approach. Environ. Toxicol. Chem. 16:1074-1081.
Vitousek, P. M., H. A. Mooney, J. Lubchenco and J. M. Melillo. 1997. Human domination of Earth’s ecosystems. Science 277:494-499.
Funding
Approximately $4 million is expected
to be available for awards in this program area. However,
awards are subject to the availability of funds. The projected award
is for up to $175,000/year total costs with a duration of 2 or 3
years. Do not exceed these guidelines. The results of
this research are intended to benefit researchers in academia and
decision makers at the federal, state, and local levels.
Eligibility
Academic and not-for-profit institutions located in the U.S., and state or local governments, are eligible under all existing authorizations. Profit-making firms are not eligible to receive grants from EPA under this program. Federal agencies and national laboratories funded by federal agencies (Federally-funded Research and Development Centers, FFRDCs) may not apply.
Federal employees are not eligible to serve in a principal leadership role on a grant. FFRDC employees may cooperate or collaborate with eligible applicants within the limits imposed by applicable legislation and regulations. They may participate in planning, conducting, and analyzing the research directed by the principal investigator, but may not direct projects on behalf of the applicant organization or principal investigator. The principal investigator's institution may provide funds through its grant from EPA to a FFRDC for research personnel, supplies, equipment, and other expenses directly related to the research. However, salaries for permanent FFRDC employees may not be provided through this mechanism.
Federal employees may not receive salaries or in other ways augment their agency's appropriations through grants made by this program. However, federal employees may interact with grantees so long as their involvement is not essential to achieving the basic goals of the grant.1 The principal investigator’s institution may also enter into an agreement with a federal agency to purchase or utilize unique supplies or services unavailable in the private sector. Examples are purchase of satellite data, census data tapes, chemical reference standards, analyses, or use of instrumentation or other facilities not available elsewhere, etc. A written justification for federal involvement must be included in the application, along with an assurance from the federal agency involved which commits it to supply the specified service.
1 EPA encourages interaction between its own laboratory scientists and grant principal investigators for the sole purpose of exchanging information in research areas of common interest that may add value to their respective research activities. However, this interaction must be incidental to achieving the goals of the research under a grant. Interaction that is “incidental” is not reflected in a research proposal and involves no resource commitments.
Potential applicants who are uncertain of their eligibility should contact Dr. Robert E. Menzer in the National Center for Environmental Research (NCER), phone (202) 564-6849, Email: menzer.robert@epa.gov.
Standard Instructions for Submitting an Application
A set of special instructions on how applicants should apply for an STAR grant is found on the NCER web site, http://www.epa.gov/ncerqa. Standard Instructions for Submitting a STAR Application and the necessary forms for an application will be found on this web site.
Sorting Codes
The need for a sorting code to be used in the application and for mailing is described in the Standard Instructions for Submitting a STAR Application. The sorting code for applications submitted in response to this solicitation is
2000-STAR-Q1 for Area
1: specific studies
2000-STAR-Q2 for Area
2: generalized studies
The deadline for receipt of applications by NCER is no later than 4:00 p.m. ET, October 17, 2000.
In research projects in which models are developed or applied, the grantee must provide, as a part of the Quality Assurance Statement described in the Standard Instructions, information on how the quality of the data used for or produced by the models will be assured. Special attention to this need should be applied to the six points for consideration in the Quality Assurance Statement. Of particular importance will be the aspects of model development, such as software verification and validation, the need for quality control of data used for modeling, and assurance that information obtained by GIS and/or remote sensing is accurate and verifiable. Reviewers will be asked to critically evaluate this aspect of the application.
Further information, if needed, may be obtained from the EPA official indicated below. E-mail inquiries are preferred.
Cynthia Nolt-Helms
202 564-6763
nolt-helms.cynthia@epa.gov