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U. S. Environmental Protection Agency
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National Center for Environmental Research
Science to Achieve Results (STAR) Program
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Exploratory Research: Understanding Ecological Thresholds In Aquatic Systems Through Retrospective Analysis
This is the initial announcement of this funding opportunity.
Sorting Code Number: 2004-STAR-K2
Catalog of Federal Domestic Assistance (CFDA) Number: 66.509
Opening Date: February 20, 2004
Closing Date: June 22, 2004
Technical Contact: Iris Goodman, 202-564-2164, email: firstname.lastname@example.org
Eligibility Contact: Tom Barnwell, 202-343-9862, email: email@example.com
Electronic Submission Contact: Bronda Harrison, 202-564-1790, email: firstname.lastname@example.org
Summary of Program Requirements
Specific Research Areas of Interest
Mechanisms of Support/Funding
Submitting an Application
Application Processing and Review Information
Authority and Regulations
SPECIAL INSTRUCTIONS: This RFA is being used as a Pilot Program for electronic submission through http://grants.gov/ . Electronic submission is encouraged but optional. Special Application Instructions for both electronic and paper submissions follow the RFA. Only one application set, either electronic or paper copy, may be submitted. DO NOT USE the 2003/2004 Standard Instructions for STAR Grants found on the National Center for Environmental Research (NCER) web site. Follow the Application Instructions below using only those forms on the NCER site that are specifically called out in these instructions.
Synopsis of Program:
The U.S. Environmental Protection Agency, as part of its Science to Achieve Results (STAR) program, is seeking applications for retrospective research on non-linear ecosystem dynamics and threshold behavior in response to ecosystem disturbance. The objective of this research is twofold: (1) to advance our basic understanding of ecosystem resilience as it relates to ecological thresholds, and (2) to produce practical insights from retrospective analysis of past threshold events that can be applied to adaptive management of similar ecosystems to prevent problems before they occur.
Anticipated Type of Award: Grant
Estimated Number of Awards: Approximately ten awards
Anticipated Funding Amount: Approximately $3 million total costs
Potential Funding per Grant per Year: Up to $150,000/year total costs with a duration of 2 years and no more than a total of $300,000, including direct and indirect costs. Proposals with budgets exceeding the total award limits will not be considered.
Institutions of higher education, not-for-profit institutions, and Tribal, state and local governments located in the U.S. are eligible to apply. See full announcement for more details.
EPA's Office of Research and Development (ORD) recently completed its Strategic Plan (http://www.epa.gov/osp/stplan.htm) in which a new goal was established "to anticipate future environmental issues." Under this goal, “ORD will evaluate opportunities for and, as appropriate, will conduct research to anticipate and assess future environmental stressors – whether human health or ecological – before their effects adversely impact people or the environment.” This new goal builds on a long history of interest in “futures” issues by EPA (Reducing Risk: Setting Priorities and Strategies for Environmental Protection (1990), Beyond the Horizon: Using Foresight to Protect the Environmental Future (1995), Remembering the Future: Applying Foresight Techniques to Research Planning at EPA (1999)).
In 2002, ORD sponsored a Workshop on Ecological Thresholds at the Woodrow Wilson Center, Washington DC. The purpose of the workshop was to review the state of the science regarding ecological thresholds, discuss methods for determining thresholds, and review examples where knowledge of threshold behavior has been applied in ecosystem management. Information on the workshop presentations and discussions are available online at: http://www.environmentalfutures.org/agenda.htm. As a result of insights gleaned from this meeting and from the scientific literature, EPA decided to publish this request for applications.
Ecological thresholds are closely related to ecological resilience. Ecological resilience has been defined as the amount of disturbance that an ecosystem can withstand without changing its self-organizing processes and variables that control its structures, i.e., without shifting to an alternative stable state (Holling 1973, Gunderson et al. 2002). An ecological threshold can be defined as a condition beyond which there is an abrupt change in a quality, property, or phenomenon of the ecosystem. Previous research has established that ecosystems often do not respond to gradual change in forcing variables in a smooth way. Instead, they respond with abrupt, discontinuous shifts to an alternative state as the ecosystem exceeds a threshold in one or more of its key variables or processes.
Previous studies have examined ecological resilience and thresholds within rangelands, coral reefs, forests, lakes, and ocean ecosystems (Folke et al. 2002, Ludwig et al. 1997). These studies have shown that human induced loss of ecosystem resilience can lead to sudden, unexpected switches to alternative ecological states, also referred to as alternative stability domains or multiple stable states. Sometimes the new, alternative state is less desirable with respect to ecological services valued by society, e.g., as when a freshwater lake shifts from being a clear water lake with benthic vegetation to a turbid water lake with blue-green algae. Examples of such shifts are shown in Table 1.
|Table 1: EXAMPLES OF DOCUMENTED SHIFTS IN STATES IN AQUATIC ECOSYSTEMS (modified from Folke et al. 2002)|
|Ecosystem||Alternative State 1||Alternative State 2||References|
|Freshwater Systems||Clear water
|Carpenter 2001 Scheffer et al. 2001|
|Oligotrophic macrophytes and algae||Cattails and blue green algae||Gunderson 2001|
|Game fish abundant||Game fish absent||Post et al. 2002|
|Marine Systems||Hard coral||Fleshy algae||Nystrom et al. 2000|
|Kelp forests||Urchin dominance||Estes and Duggins 1993|
|Seagrass beds||Algae and muddy water||Gunderson 2001|
Some shifts to new states are reversible but may require a significant investment of time and expense. Other shifts are reversible, but exhibit hysteresis (Gunderson et al. 2002). Still other shifts in ecological states are irreversible (Carpenter et al. 1999, Walker et al. 2002).
Previous field and modeling studies have identified important areas of research for understanding ecological resilience and ecological thresholds. These studies suggest that ecosystem structures are primarily regulated by the interaction of three to six processes (Gunderson and Holling 2002, Carpenter et al. 1999, Levin 1992, Carpenter and Leavitt 1991, Holling 1996). Each of these processes operates at characteristically distinct temporal and spatial scales, and these variables often have process rates that differ by an order of magnitude (Holling 2002, 1992). Examples of process variable rates for aquatic systems are shown in Table 2 (modified from Holling et al. 2002).
|Table 2: RATES OF AQUATIC ECOSYSTEM PROCESS VARIABLES|
|Shallow lakes and seas||phytoplankton and turbidity||sea grasses
||grazers||Scheffer et al. 1993,
|Deep lakes||phytoplankton||zooplankton||fish and habitat; phosphate in mud||Carpenter et al. 1999a, Carpenter et al. 1999b|
|Wetlands||periphyton||saw grass||tree island; peat accretion||Gunderson 1994, 1999|
Numerous studies suggest that it is the interaction of “fast” and “slow” ecosystem processes that produce cyclical patterns, potential oscillations, and sudden large shifts in ecosystem state (Carpenter and Turner 2000). Abrupt shifts can occur when a gradual change in a slow variable alters the interaction and relationships among the faster variables (Rinaldi and Scheffer 2000). Systems that are characterized by such coupled nonlinear dynamics can exhibit unexpected threshold shifts (Gunderson et al. 2002, Holling et al. 2002). Prototype modeling studies have successfully captured simple patterns in threshold behavior and have provided insights regarding the behavior of lake systems in response to alternative management scenarios (Carpenter 1999, Janssen and Carpenter 1999).
Resource management objectives often focus on relatively fast ecological variables. Previous research suggests that ecological threshold events (e.g., resource collapses, surprises) result from changes in the relatively slow ecosystem variables (Carpenter et al. 1999a). Previous research also suggests that human stressors tend to accelerate processes associated with the slow variables that structure ecosystem processes, e.g., changes in climate, increased homogeneity in the spatial pattern of land cover, depletion of soil nutrients, and enrichment of lake sediments (Gunderson et al. 2002, Scheffer et al. 2000, Folke et al. 2002). Thus, human stressors can push ecosystem processes beyond critical thresholds by reducing ecological resilience.
This RFA is using a retrospective approach to see how lessons learned from rigorous analysis of past threshold events for freshwater or estuarine ecosystems can be used to anticipate impending and future problems before they occur. This research will be based primarily on analyses of existing data sets and modeling studies.
Successful proposals will integrate theory, data, and modeling techniques to interpret existing field and experimental data. Proposals must also describe the rationale for selecting a particular study approach. For example, comparative studies of multiple aquatic systems that have undergone similar changes (such as temperate lakes switching between macrophytes and phytoplankton dominance) could provide inferences applicable to a specific, widespread problem. Analysis of aquatic systems that have undergone different types of changes could yield insights regarding higher-order patterns (e.g., types of interactions among slow and fast system variables) that lead to state changes.
The proposal should describe how the aquatic ecosystem proposed for study will be characterized and should include the internal and external “driving variables” that cause the system to cross a threshold, including socioeconomic drivers. These variables should be scaled relative to the process, organisms, or type of disturbances being studied (Ives 1995, Paine et al. 1998, Carpenter and Turner 2000). Each proposal should identify the hypothesized slow, intermediate, and fast variables for the ecosystem being studied and describe how the study will investigate the interaction of these variables. Where possible, proposals that explicitly link these variables to their spatial domains are encouraged.
Modeling techniques can include statistical, mechanistic, quantitative, or qualitative mathematical modeling (Puccia and Levins 1985) or a combination of methods (Ives 1995, Scheffer 1999, Scheffer 1999, Rinaldi and Scheffer 2000, Ludwig et al. 2002, Myers and Quinn 2002). Proposed models must be able to represent ecosystem dynamics that involve nonlinear interactions of variables with distinctly different process rate (Carpenter et al.1999a, Levin 1992, Rinaldi and Scheffer 2000).
Key objectives for the modeling analyses are to test the ideas suggested by the retrospective analyses, to advance methods for identifying ecological thresholds, and for determining the position of thresholds along the driving variables. Where existing data is insufficient for developing precise response curves, plausible ranges of parameter values may be used to examine the implications of changes in driving variables on system behavior (Walker et al. 2002). Modeling approaches that help determine how spatial patterns of critical variables affect threshold dynamics and that identify sources of spatial and functional resilience within the ecosystem are especially encouraged.
Finally, proposals must address how the anticipated results of the retrospective analysis might be applied to adaptive management. Examples of results especially relevant to management issues include: (1) qualitative predictions of thresholds that presage shifts to new ecosystem states; (2) development of scenarios that explicitly incorporate spatial and temporal sources of ecosystem resiliency and its effect on threshold behavior; (3) recommendations for ecosystem monitoring techniques that provide early warning that a system is approaching a threshold or, conversely, to determine that ecosystem resilience is improving; and (4) identifying ecosystem shifts that are likely to be irreversible.
Proposal budgets must include provisions for travel funds for annual STAR program progress reviews and a final workshop to report on results.
Carpenter, S.R. 2001. Alternate states of ecosystems: Evidence and its implications. Pages 357-383 in Press, M.C., Huntly, N. and Levin, S. (eds.) Ecology: Achievement and Challenge. Blackwell, London.
Carpenter, S.R. and P.R. Leavitt. 1991. Temporal variation in paleolimnological record arising from trophic cascade. Ecology. 72: 227-285.
Carpenter, S.R. and M.G. Turner. 2000. Hares and tortoises: interactions of fast and slow variables in ecosystems. Ecosystems 3:495-497.
Carpenter, S.R., W. Brock, and P. Hanson. 1999a. Ecological and social dynamics in simple models of ecosystem management. Conservation Ecology 3(2):4 [online] URL: http://www.consecol.org/vol3/iss2/art4
Carpenter, S.R., D. Ludwig, and W. Brock.1999b. Management of lakes subject to potentially irreversible change. Ecological Applications 9(3):751-771.
Estes, J.A. and Duggins, C.O. 1995. Sea otters and kelp forests in Alaska: Generality and variation in a community ecological paradigm. Ecological Monographs 65:75-100.
Folke, C. et al. Resilience and Sustainable Development: Building Adaptive Capacity in a World of Transformations. April 16, 2002. Scientific Background Paper on Resilience for the process of The World Summit on Sustainable Development on behalf of The Environmental Advisory Council to the Swedish Government URL: http://www.sou.gov.se/mvb/pdf/resiliens.pdf (PDF, 73pp., 343.47 KB) about PDF)
Gunderson, L.H. 1994. Vegetation of the Everglades: Determinants of community composition. In The Everglades: The Ecosystem and Its Restoration. S. Davis and J. Ogden (eds.) St. Lucie Press, Deerfield Beach, FL.
Gunderson, L.H. 1999. Resilience, flexibility and adaptive management: Antidotes for spurious certitude. Conservation Ecology 3 (1):7. Online at http://www.consecol.org/vol3/iss1/art7
Gunderson, L.H. 2001. Managing surprising ecosystems in the southern Florida. Ecological Economics 37:371-378.
Gunderson, L.H. and C.S. Holling., eds. 2002. Panarchy: Understanding Transformations in Human and Natural Systems. Island Press, Wash. D.C.
Gunderson, L.H., L. Pritchard Jr., C.S. Holling, C. Folke, and G.D. Peterson. 2002. “A Summary and Synthesis of Resilience in Large-Scale Systems,” in Gunderson, L.H. and L. Pritchard, Jr., eds. Resilience and the Behavior of Large-Scale Systems. Island Press, Wash. D.C.
Holling, C.S. 1973. Resilience and stability of ecological systems. Annual Review of Ecology and Systematics. 4:1-23. [online] URL: http://www.consecol.org/vol3/iss2/art15
Holling, C.S., G. Peterson, P. Marples, J. Sendzimir, K. Redford, L. Gunderson, and D. Lambert. 1996. Self-organization in ecosystems: lumpy geometries, periodicities and morphologies. In Global Change and Terrestrial Ecosystems. Cambridge Univ. Press.
Holling, C.S., L.H. Gunderson and G.D. Peterson. 2002. Sustainability and Panarchies, in Panarchy: Understanding Transformations in Human and Natural Systems. Island Press, Wash. D.C.
Ives, A.R. 1995. Measuring resilience in stochastic systems. Ecological Monographs 65:217-233.
Janssen, M.A. and S.R. Carpenter. 1999. Managing the resilience of lakes: a multi-agent modeling approach. Conservation Ecology 3(2):15.
Ludwig, D., B.H. Walker, and C.S. Holling. 1997. Sustainability, stability and resilience. Conservation Ecology, 1(1):7. [online] URL: http://www.consecol.org/vol1/iss1/art7.
Ludwig, D., B.H. Walker, and C.S. Holling. 2002. Models and Metaphors of Sustainability, Stability and Resilience, in Resilience and the Behavior of Large-Scale Systems. Island Press, Wash. D.C.
Levin, S.A. 1992. The problem of pattern and scale in ecology. Ecology 73:1943-1967.
Myers, R.A. and T.J. Quinn. 2002. Estimating and testing for non-additivity in fishing mortality: Implications for detecting fisheries collapse. Canadian Journal of Fisheries and Aquatic Sciences. 59( 4): 597-601.
National Academy of Public Administration,1999. Remembering the Future: Applying Foresight Techniques to Research Planning at EPA, Washington, DC.
Nystrom M., C. Folke, and F. Moberg. 2000. Coral-reef disturbance and resilience in a human-dominated environment. Trends in Ecology and Evolution 15:413-417.
Paine, R.T., M.J. Tegner, and E.A. Johnson. Compounded Perturbations Yield Ecological Surprises. Ecosystems (1998) 1:535-545.
Post, J.R., M. Sullivan, S. Cox, N.P. Lester, C.J. Walters, E.A. Parkinson, A.J. Paul, L. Jackson and B.J. Shuter, 2002. Canada’s recreational fisheries: The invisible collapse? Fisheries 27:6-17.
Puccia, C.J. and R. Levins. 1985. Qualitative Modelling of Complex Systems: An Introduction to Loop Analysis and Time Averaging. Harvard Univ. Press, Cambridge, MA.
Rinaldi, S. and M. Scheffer. Geometric Analysis of Ecological Models With Fast and Slow Processes. Ecosystems (2000) 3: 507-521.
Scheffer, M., S.H. Hosper, M.L. Meijer, B. Moss, and E. Jeppesen. 1993. Alternative equilibria in shallow lakes. Trends in Evolutionary Ecology 8:275-279.
Scheffer, M. 1999. Searching explanations of nature in the mirror world of math. Conservation Ecology 3(2):11. Online at http://www.consecol.org/vol3/iss2/art11
Scheffer, M., S. Carpenter, J. Foley, C. Folke, B. Walker. Catastrophic Shifts in Ecosystems, Nature 413: 591-596, (2001).
U.S. Environmental Protection Agency, Science Advisory Board 1990. Reducing Risk: Setting Priorities and Strategies for Environmental Protection, Washington, DC.
U.S. Environmental Protection Agency, Science Advisory Board, 1995. Beyond the Horizon: Using Foresight to Protect the Environmental Future, Washington, DC.
Walker, B., S. Carpenter, J. Anderies, N. Abel, G.S. Cumming, M. Jannsen, L. Lebel, J. Norberg, G.D. Peterson, and R. Pritchard. 2002. Resilience management in social-ecological systems: a working hypothesis for a participatory approach. Conservation Ecology 6(1): 14. Online at http://www.consecol.org/vol6/iss1/art14
Wooten, J.T., 1994. The nature and consequences of indirect effects in ecological communities. Annual Review of Ecology and Systematics. 25:443-466.
It is anticipated that a total of approximately $3 million will be awarded, depending on the availability of funds. Approximately ten awards will be made under this RFA. The projected award per grant is up to $150,000 per year total costs, for up to 2 years. Requests for amounts in excess of a total of $300,000, including direct and indirect costs, will not be considered.
Institutions of higher education, not-for-profit institutions, and Tribal, state and local governments located in the U.S. are eligible to apply. Profit-making firms are not eligible to receive grants from EPA under this program. Nonprofit organizations described in Section 501(c)(4) of the Internal Revenue Code that engage in lobbying activities as defined in Section 3 of the Lobbying Disclosure Act of 1995 are not eligible to apply.
National laboratories funded by federal agencies (Federally-funded Research and Development Centers, “FFRDCs”) may not apply. 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, organization, or governance 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 agencies may not apply. Federal employees are not eligible to serve in a principal leadership role on a grant, and 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. 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. This interaction must be incidental to achieving the goals of the research under a grant. Interaction that is “incidental” does not involve resource commitments.
The principal investigator’s institution may 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. 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.
Potential applicants who are uncertain of their eligibility should contact Tom Barnwell, in NCER, phone 202-343-9862, e-mail: email@example.com
Institutional cost-sharing is not required.
Special Instructions for Submitting an Application
This RFA is being used as a Pilot Program for electronic submission through http://grants.gov/ . Electronic submission is encouraged but optional. Special Application Instructions for both electronic and paper submissions follow the RFA. Only one application set, either electronic or paper copy, may be submitted. DO NOT USE the 2003/2004 Standard Instructions for STAR Grants found on the National Center for Environmental Research (NCER) web site. Follow the Application Instructions below using only those forms on the NCER site that are specifically called out in these instructions. Further information, if needed, may be obtained from Bronda Harrison, in NCER, phone 202-564-1790, e-mail: firstname.lastname@example.org
The need for a sorting code to be used in the application and for mailing is described in the Instructions for Paper Copy Submission of an Application that follow this announcement. No sort code is needed for electronic submissions. The sorting code for paper copy applications submitted in response to this solicitation is 2004-STAR-K1.
Applications must be received by the application receipt date listed in this announcement. If an application is received after that date, it will be returned to the applicant without review.
The following is the schedule for this RFA. It should be noted that this schedule may be changed without notification due to factors that were not anticipated at the time of announcement.
Application Receipt Date: June 22, 2004
Earliest Anticipated Start Date: February dd, 2004
The application review process is found in the Special Instructions. Consideration of an application’s merit is based on the following criteria: (1) the originality and creativity of the proposed research, the appropriateness and adequacy of the research methods proposed and the quality assurance statement; (2) the qualifications of the principal investigator(s) and other key personnel; (3) the responsiveness of the proposal to the research needs identified for the topic area; (4) the availability and/or adequacy of the facilities and equipment proposed for the project; and (5) although budget information does not reflect on the application’s scientific merit, the reviewers are asked to provide their view on the appropriateness and/or adequacy of the proposed budget.
Further information, if needed, may be obtained from the EPA official indicated below. Email inquiries are preferred.
This program is described in the Catalog of Federal Domestic Assistance 66.509.
The authority for this RFA and resulting awards is contained in the Clean Water Act, Section 104, as amended, Public Law 95-217, 33 U.S.C. 1251 et seq.