Endangered species determinations require reliable scientific analyses to assess species risk of extinction (Carroll et al. 1996, Doremus and Tarlock 2005, Waples et al. 2015, Murphy and Weiland 2016). Recently, the U.S. Fish and Wildlife Service (USFWS) has adopted the species status assessment (SSA) process that results in a scientific analysis to be used in endangered species decisions (McGowan et al. 2017, Smith et al. 2018). The U.S. Geological Survey (USGS) is collaborating with USFWS to improve scientific input to SSAs to work towards more accurate decisions about species status and more effective conservation efforts.
The SSA process includes three sequential tasks: description of species ecology, estimation of current condition, and forecast of future condition. The SSA incorporates predictive modeling, species distribution modeling, population genetics, scenario analysis, formal expert elicitation, and decision analysis. Often the bottleneck in an SSA is the science required for estimation and forecasting.
Improving efficiency of the SSA process, while maintaining accuracy, is needed given the high number of petitioned species and recovery plans to be updated. For example, the single-species approach is the traditional method, but efficiency might be improved by assessing multiple species at the same time (Franklin 1995, McClure et al. 2003, Joseph et al. 2009, USFWS 2014, Bouska et al. 2018). The potential trade-off between accuracy and efficiency is paramount because insufficient understanding of species-specific ecology resulting from a multiple species focus could undermine conservation effectiveness (Clark and Harvey 2002, Heinrichs et al. 2018). Currently, the USFWS lacks a consistent theoretically grounded multiple species assessment approach. Thus, guidance is needed for when and how a multiple species assessment is effective and efficient for endangered species determinations. The utility of multiple-species assessments might depend on a typology or road map defined by taxonomic guild, overlapping distribution, susceptibility to similar stressors, ecosystem dependence, and life histories.
Because decision making provides the context for the science, there may also be a decision analysis aspect for research under this Opportunity (Runge 2011, Gregory et al. 2013, Smith et al. 2016, Smith et al. 2018). An effective species assessment will be structured to have inputs and outputs that conform to the type of endangered species decision that it supports. A decision to list a species as endangered or threatened relies on an assessment of extinction risk under plausible threat scenarios. Development of a recovery plan relies on a maximization of species viability among alternative recovery actions and strategies. Mitigation of project-level impacts relies on a minimization of incidental take across alternative conservation measures. A value-of-information approach, common to decision analysis, might be useful in evaluating the value of multiple species assessment to the particular decision context (Bal et al. 2018).
This Mendenhall Research Fellowship will provide an excellent opportunity for an early career researcher to work collaboratively with USGS scientists and USFWS managers to provide scientific information through analyses and models that will support consequential decision making. In particular, the candidate will 1) develop models, future scenarios, and analyses to estimate current condition and forecast future condition for multiple species of freshwater mussels and cave/karst amphipods, and 2) develop principles, practices, methods, tools, and guidance for multiple-species assessments. While multiple-species assessment is a focal point in this Opportunity, there is room for creatively exploring other ways to gain efficiency and improve accuracy of species assessments. The research is expected to result in widely-distributed guidance and publications on achieving accurate and efficient species assessments. The candidate will work with a research team on assessments for priority species and will be expected to produce peer-reviewed publications. The candidate’s work on the case studies will provide the experience, along with literature reviews and previous experiences, to develop novel analyses, guidance, and protocols.
Bal P, Tulloch AIT, Chadès I, Carwadine J, McDonald-Madden E, Rhodes JR. 2018. Quantifying the value of monitoring species in multi-species, multi-threat systems. Methods in Ecology and Evolution (in press).
Bouska K, Rosenberger A, McMurray SE, Lindner GA, Key KN. 2018. State-level freshwater mussel programs: current status and a research framework to aid in mussel management and conservation. Fisheries https://doi.org/10.1002/fsh.10106
Carroll R, Augspurger C, Dobson A, Franklin J, Orians G, Reid W, Tracy R, Wilcove D, Wilson J. 1996. Strengthening the use of science in achieving the goals of the Endangered Species Act: An assessment by the Ecological Society of America. Ecological Applications 6:1–11.
Clark JA, Harvey E. 2002. Assessing multi-species recovery plans under the Endangered Species Act. Ecological Applications 12:655-662.
Doremus H, Tarlock DA. 2005. Science, judgment, and controversy in natural resource regulation. Public Land & Resources Law Review 26:1–38.
Franklin JF. 1993. Preserving biodiversity: species, ecosystems, or landscapes. Ecological Applications 3:202-205.
Gregory R, Arvai J, Gerber LR. 2013. Structuring decisions for managing threatened and endangered species in a changing climate. Conservation Biology 27:1212-1221.
Heinrichs JA, Lawler JJ, Schumaker NH, Wilsey CB, Monroe KC, Aldridge CL. 2018. A multispecies test of source–sink indicators to prioritize habitat for declining populations. Conservation Biology 32: 648-659. doi:10.1111/cobi.13058
Joseph LN, Maloney RF, Possingham HP. 2009. Optimal allocation of resources among threatened species: A project prioritization protocol. Conservation Biology 23: 328–338.
McClure MM, Holmes EE, Sanderson BL, Jordan CE. 2003. A large-scale, multispecies status assessment: anadromous salmonids in the Columbia River Basin. Ecological Applications 13:964-989.
McGowan CP, Allan NL, Servoss J, Hedwall S, Wooldridge B. 2017. Incorporating population viability models into species status assessment and listing decisions under the U.S. Endangered Species Act. Global Ecology and Conservation 12:119-130.
Murphy DD, Weiland PS. 2016. Guidance on the use of best available science under the U.S. Endangered Species Act. Environmental Management 58:1–14.
Runge MC. 2011. An introduction to adaptive management for threatened and endangered species. Journal of Fish and Wildlife Management 2:220-233.
Smith DR, Allan NL, McGowan CP, Szymanski JA, Oetker SR, Bell HM. 2018. Development of a species status assessment process for decisions under the U.S. Endangered Species Act. Journal of Fish and Wildlife Management 9(1):302–320; e1944-687X. doi:10.3996/052017-JFWM-041
Smith DR, Butler RS, Jones JW, Gatenby CM, Hylton R, Parkin M, Shultz C. 2016. Developing a landscape-scale, multi-species, and cost-efficient conservation strategy for imperiled aquatic species in the Upper Tennessee River Basin, USA. Aquatic Conservation: Marine and Freshwater Ecosystems 27: 1224-1239
Waples RS, Nammack M, Cochrane JF, Hutchings JA. 2013. A tale of two acts: endangered species listing practices in Canada and the United States. BioScience 63:723–734.
US Fish and Wildlife Service (USFW). 2014. Imperiled aquatic species conservation strategy for the Upper Tennessee River Basin. Abingdon, VA: US Fish and Wildlife Service https://www.fws.gov/northeast/virginiafield/pdf/MISC/2014_UTRB_imperiled_aquatic_strategy.pdf; Accessed 21 Nov 2016.
Proposed Duty Station: The researcher will be located at the USGS Leetown Science Center near Shepherdstown, WV. The area is within the scenic and historic Potomac and Shenandoah River valleys, and located about 70 miles west of Washington DC.
Areas of PhD: Conservation biology, population ecology, community ecology, biology, quantitative ecology (candidates holding a Ph.D. in other disciplines, but with extensive knowledge and skills relevant to the Research Opportunity may be considered).
Qualifications: Applicants must meet one of the following qualifications: Research Biologist, Research Ecologist, Research Wildlife Biologist, Research Fish Biologist, Research Statistician (Biology).
Dave Smith, (304) 724-4467, firstname.lastname@example.org; Kelly Maloney, (304) 724-4579, email@example.com; Mary Freeman, (706) 201-5859, firstname.lastname@example.org; Amanda Rosenberger, email@example.com; John Young, (304) 724-4465, firstname.lastname@example.org
Human Resources Office Contact: Emilyn Claycomb, 703 648-7481, email@example.com
|Summary of Opportunities|