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Jaime Ashander, PhD

Jaime is a Research Biologist with the Eastern Ecological Science Center at the Patuxent Research Refuge in Laurel, MD. 

Jaime uses decision analysis, population dynamics models, and climate data to investigate optimal management of natural resources in a changing world. Jaime joined USGS in 2021 as a Research Ecologist working on time-dependent optimal strategies for natural resource management. Understanding such strategies will help in adapting current management practices to ongoing and future climate change. Since 2021, Jaime has worked on these issues in several areas including waterfowl harvest management, allocation of resources to land protection, and prioritization of conservation activities. Beginning in 2023, Jamie transitioned to a permanent role as a Research Biologist. 

Professional Experience

  • 2021–present Research Ecologist/Biologist at USGS Eastern Ecological Science Center at the Patuxent Research Refuge (formerly Patuxent Wildlife Research Center), Laurel, MD.

  • 2018–2021 Postdoctoral Fellow at Resources for the Future, Washington, DC.

  • 2016–2018 Postdoctoral Researcher at University of California—Los Angeles.

Education and Certifications

  • Ph.D. Population Biology, University of California—Davis (2016)

  • M.Sc. Applied Mathematics, University of Alberta (2010)

  • B.S. Physics, Stanford University (2004)

Science and Products

A community convention for ecological forecasting: Output files and metadata version 1.0

This paper summarizes the open community conventions developed by the Ecological Forecasting Initiative (EFI) for the common formatting and archiving of ecological forecasts and the metadata associated with these forecasts. Such open standards are intended to promote interoperability and facilitate forecast communication, distribution, validation, and synthesis. For output files, we first describe
Authors
Michael C. Dietze, R. Quinn Thomas, Jody Peters, Carl Boettiger, Gerband Koren, Alexy N. Shiklomanov, Jaime Ashander
By
Eastern Ecological Science Center

The power of forecasts to advance ecological theory

Ecological forecasting provides a powerful set of methods for predicting short- and long-term change in living systems. Forecasts are now widely produced, enabling proactive management for many applied ecological problems. However, despite numerous calls for an increased emphasis on prediction in ecology, the potential for forecasting to accelerate ecological theory development remains underrealiz
Authors
Abigail S L Lewis, Christine R. Rollinson, Andrew J Allyn, Jaime Ashander, Stephanie Brodie, Cole B Brookson, Elyssa Collins, Michael C. Dietze, Amanda S. Gallinat, Noel Juvigny-Khenafou, Gerbrand Koren, Daniel J McGlinn, Hassan Moustahfid, Jody Peters, Nicholas R. Record, Caleb J Robbins, Jonathan Tonkin, Glenda M Wardle
By
Eastern Ecological Science Center

Non-USGS Publications**

Ashander, J., K. Kroetz, R. Epanchin-Niell, R. Haight, N. Phelps, L.E. Dee. Guiding large-scale management of invasive species using network metrics. 2022. Nature Sustainability https://dx.doi.org/10.1038/s41893-022-00913-9
Felipe-Lucia, M.R., A. M. Guerrero, S. M. Alexander, J. Ashander, J. A. Baggio, M. L. Barnes, Ö. Bodin et al. (2022) Conceptualizing ecosystem services using social-ecological networks. Trends in Ecology & Evolution 37:211-222 https://dx.doi.org/10.1016/j.tree.2021.11.012
Ashander, J., Thompson, L.C., Sanchirico, J.N. and Baskett, M.L., 2019. Optimal investment to enable evolutionary rescue. Theoretical Ecology, 12, pp.165-177. https://dx.doi.org/10.1007/s12080-019-0413-8
Chmura, H.E., Kharouba, H.M., Ashander, J., Ehlman, S.M., Rivest, E.B. and Yang, L.H., 2019. The mechanisms of phenology: the patterns and processes of phenological shifts. Ecological monographs, 89(1), p.e01337. https://doi.org/10.1002/ecm.1337
Ashander, J., Chevin, L.M. and Baskett, M.L., 2016. Predicting evolutionary rescue via evolving plasticity in stochastic environments. Proceedings of the Royal Society B: Biological Sciences, 283(1839), p.20161690. https://doi.org/10.1098/rspb.2016.1690

**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.

link
Time-dependent Decisions Diagram

Markov decision processes in non-autonomous socio-ecological systems

Our ability to effectively manage natural resources is founded in an understanding of how our actions and the environment influence populations, communities, and ecosystems. Current practices use monitoring data from the past to determine key ecological relationships and make predictions about the future with the assumption that those relationships will remain constant. However, many natural syste
By
John Wesley Powell Center for Analysis and Synthesis
link

Markov decision processes in non-autonomous socio-ecological systems

Our ability to effectively manage natural resources is founded in an understanding of how our actions and the environment influence populations, communities, and ecosystems. Current practices use monitoring data from the past to determine key ecological relationships and make predictions about the future with the assumption that those relationships will remain constant. However, many natural syste
Learn More
link
Riparian birds

Informing Management of Waterfowl Harvest in a Changing Climate

The ability to effectively manage wildlife in North America is founded in an understanding of how human actions and the environment influence wildlife populations. Current management practices are informed by population monitoring data from the past to determine key ecological relationships and make predictions about future population status. In most cases, including the regulation of waterfowl hu
By
Climate Adaptation Science Centers
link

Informing Management of Waterfowl Harvest in a Changing Climate

The ability to effectively manage wildlife in North America is founded in an understanding of how human actions and the environment influence wildlife populations. Current management practices are informed by population monitoring data from the past to determine key ecological relationships and make predictions about future population status. In most cases, including the regulation of waterfowl hu
Learn More

Science and Products

A community convention for ecological forecasting: Output files and metadata version 1.0

This paper summarizes the open community conventions developed by the Ecological Forecasting Initiative (EFI) for the common formatting and archiving of ecological forecasts and the metadata associated with these forecasts. Such open standards are intended to promote interoperability and facilitate forecast communication, distribution, validation, and synthesis. For output files, we first describe
Authors
Michael C. Dietze, R. Quinn Thomas, Jody Peters, Carl Boettiger, Gerband Koren, Alexy N. Shiklomanov, Jaime Ashander
By
Eastern Ecological Science Center

The power of forecasts to advance ecological theory

Ecological forecasting provides a powerful set of methods for predicting short- and long-term change in living systems. Forecasts are now widely produced, enabling proactive management for many applied ecological problems. However, despite numerous calls for an increased emphasis on prediction in ecology, the potential for forecasting to accelerate ecological theory development remains underrealiz
Authors
Abigail S L Lewis, Christine R. Rollinson, Andrew J Allyn, Jaime Ashander, Stephanie Brodie, Cole B Brookson, Elyssa Collins, Michael C. Dietze, Amanda S. Gallinat, Noel Juvigny-Khenafou, Gerbrand Koren, Daniel J McGlinn, Hassan Moustahfid, Jody Peters, Nicholas R. Record, Caleb J Robbins, Jonathan Tonkin, Glenda M Wardle
By
Eastern Ecological Science Center

Non-USGS Publications**

Ashander, J., K. Kroetz, R. Epanchin-Niell, R. Haight, N. Phelps, L.E. Dee. Guiding large-scale management of invasive species using network metrics. 2022. Nature Sustainability https://dx.doi.org/10.1038/s41893-022-00913-9
Felipe-Lucia, M.R., A. M. Guerrero, S. M. Alexander, J. Ashander, J. A. Baggio, M. L. Barnes, Ö. Bodin et al. (2022) Conceptualizing ecosystem services using social-ecological networks. Trends in Ecology & Evolution 37:211-222 https://dx.doi.org/10.1016/j.tree.2021.11.012
Ashander, J., Thompson, L.C., Sanchirico, J.N. and Baskett, M.L., 2019. Optimal investment to enable evolutionary rescue. Theoretical Ecology, 12, pp.165-177. https://dx.doi.org/10.1007/s12080-019-0413-8
Chmura, H.E., Kharouba, H.M., Ashander, J., Ehlman, S.M., Rivest, E.B. and Yang, L.H., 2019. The mechanisms of phenology: the patterns and processes of phenological shifts. Ecological monographs, 89(1), p.e01337. https://doi.org/10.1002/ecm.1337
Ashander, J., Chevin, L.M. and Baskett, M.L., 2016. Predicting evolutionary rescue via evolving plasticity in stochastic environments. Proceedings of the Royal Society B: Biological Sciences, 283(1839), p.20161690. https://doi.org/10.1098/rspb.2016.1690

**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.

link
Time-dependent Decisions Diagram

Markov decision processes in non-autonomous socio-ecological systems

Our ability to effectively manage natural resources is founded in an understanding of how our actions and the environment influence populations, communities, and ecosystems. Current practices use monitoring data from the past to determine key ecological relationships and make predictions about the future with the assumption that those relationships will remain constant. However, many natural syste
By
John Wesley Powell Center for Analysis and Synthesis
link

Markov decision processes in non-autonomous socio-ecological systems

Our ability to effectively manage natural resources is founded in an understanding of how our actions and the environment influence populations, communities, and ecosystems. Current practices use monitoring data from the past to determine key ecological relationships and make predictions about the future with the assumption that those relationships will remain constant. However, many natural syste
Learn More
link
Riparian birds

Informing Management of Waterfowl Harvest in a Changing Climate

The ability to effectively manage wildlife in North America is founded in an understanding of how human actions and the environment influence wildlife populations. Current management practices are informed by population monitoring data from the past to determine key ecological relationships and make predictions about future population status. In most cases, including the regulation of waterfowl hu
By
Climate Adaptation Science Centers
link

Informing Management of Waterfowl Harvest in a Changing Climate

The ability to effectively manage wildlife in North America is founded in an understanding of how human actions and the environment influence wildlife populations. Current management practices are informed by population monitoring data from the past to determine key ecological relationships and make predictions about future population status. In most cases, including the regulation of waterfowl hu
Learn More