USAP-DC

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). Many biogeochemical and biophysical processes are changing in the present and coming century. The mechanisms and the predictability of these processes are still poorly understood. Limits in understanding of these progress limits climate forecasting. Similarly, ecological forecasting remains a nascent discipline. Comparative assessments of predictability, both within and among species, are critically needed to understand the factors that allow (or prevent) useful ecological forecasts. This study will reveal the influence of climate system dynamics on ecological predictability across a range of scales, and will examine how this role differs among ecological processes, species and regions of Antarctic. The project research will examine the predictability of Antarctic climate and its influence on seabird demographic response, predictability at various temporal and spatial scales, using the longest datasets available for several polar species. Specifically, the PI will 1) identify the physical mechanisms giving rise to climate predictability in Antarctica, 2) identify the relationships between climate and ecological processes at a range of scales, and 3) reveal the factors controlling ecological predictability across a range of scales (e.g., those relevant for short-term adaptive management versus those relevant at end-of-century timescales). These objectives will be achieved using the analysis of existing climate data and century length time-scales, Atmosphere-Ocean Global Circulation Models (AOGCMs), with coupled analysis of existing long-term demographic data for multiple seabird species that span a range of ecological niches, life histories, and study sites across the continent. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Person	Role
Jenouvrier, Stephanie	Investigator and contact
Holland, Marika	Co-Investigator

Antarctic Ocean and Atmospheric Sciences

Award # 2037561

USAP-2037561_1

None in the Database

Repository	Title (link)	Format(s)	Status
USAP-DC	Detecting climate signals in populations: case of emperor penguin	Not Provided	exists
Zenodo	Code for Şen et al. 2023		exists

1. Jenouvrier S., Long M., Coste C.F.D, Holland M., Gamelon M., Yoccoz N.G., Sæther B-E. Detecting climate signals in populations across life histories. Global Change Biology. (doi:10.1111/gcb.16041)
2. Şen B., Che-Castaldo C., Krumhardt K., Landrum L., Holland M., Long M., LaRue M., Jenouvrier S., Lynch. 2023. Intrinsic predictability as an indicator for spatio-temporal transferability of population dynamics. Ecological Indicators, 150:110239. (doi:10.1016/j.ecolind.2023.110239)
3. Jenouvrier S, La Rue M, Trathan P and Barbraud C (2023) Emperor Penguins on Thin Sea Ice. Front. Young Minds. 11:1052262. (doi:10.3389/frym.2023.1052262)
4. Jenouvrier S., Emperor penguins get Endangered Species Act protection – with 98% of colonies at risk of extinction by 2100, can it save them? The conversation. October 28, 2022. https://theconversation.com/emperor-penguins-get-endangered-species-act-protection-with-98-of-colonies-at-risk-of-extinction-by-2100-can-it-save-them-193439
5. Yeager, S. G., Rosenbloom, N., Glanville, A. A., Wu, X., Simpson, I., Li, H., Molina, M. J., Krumhardt, K., Mogen, S., Lindsay, K., Lombardozzi, D., Wieder, W., Kim, W. M., Richter, J. H., Long, M., Danabasoglu, G., Bailey, D., Holland, M., Lovenduski, N., Strand, W. G., and King, T. 2022. The Seasonal-to-Multiyear Large Ensemble (SMYLE) prediction system using the Community Earth System Model version 2, Geosci. Model Dev., 15, 6451–6493 (doi:10.5194/gmd-15-6451-2022)
6. LaRue, M., Iles, D., Labrousse, S., Fretwell, P., Ortega, D., Devane, E., Horstmann, I., Viollat, L., Foster-Dyer, R., Le Bohec, C., Zitterbart, D., Houstin, A., Richter, S., Winterl, A., Wienecke, B., Salas, L., Nixon, M., Barbraud, C., Kooyman, G., … Jenouvrier, S. (2024). Advances in remote sensing of emperor penguins: first multi-year time series documenting trends in the global population. Proceedings of the Royal Society B: Biological Sciences, 291(2018). (doi:10.1098/rspb.2023.2067)
7. Şen, B., Che‐Castaldo, C., Lynch, H. J., Ventura, F., LaRue, M. A., & Jenouvrier, S. (2024). Detecting stochasticity in population time series using a non‐parametric test of intrinsic predictability. Methods in Ecology and Evolution. Portico. (doi:10.1111/2041-210x.14423)