USAP-DC

Albatrosses (family Diomedeidae) are among the most threatened of bird species. Of the 22 species that are currently recognized, all are considered at least Threatened or Near-Threatened, and 9 are listed as Endangered or Critically Endangered. Because of the decline in albatross populations and the birds' role as a top predator in the pelagic ecosystem, it is vitally important to understand the factors affecting the population dynamics of these birds to better inform strategies for conservation and mitigating environmental change. The goal of this project is to answer the question: What are the population consequences of albatross bioenergetics and foraging strategies? The project took a two pronged approach: 1) constructing, parameterizing, and validating a Dynamic Energy Budget model to understand growth and constraints on foraging; and 2) undertaking an in-depth meta-analysis of existing individual tracking and life history data from multiple albatross species across successive life stages. This theoretical work will be grounded with a unique and extensive data set on albatrosses provided by collaborator Richard Phillips from the British Antarctic Survey. Bioenergetics constrain a variety of behaviors. A more complete understanding of how individuals use energy can give insight into how behaviors from foraging to breeding and survival, and resulting population attributes, might change with environmental factors, due to anthropogenic and other drivers. This work will further a general understanding of how bioenergetics shapes behavior and drives population level processes, while providing an approach that can be used to guide conservation strategies for endangered populations. The research findings and activities were made accessible to public audiences through websites and a blog maintained for the project by a postdoctoral researcher. The project involved undergraduate researchers in the project, within formal laboratory groups and also through in-classroom presentations and activities. This project also involved public outreach through twitter and other venues. All project publications are open access, the resulting open source software was released to the public, and metadata and analyses are fully documented to promote further collaborative exploration of this system.

Person	Role
Johnson, Leah	Investigator and contact
Ryan, Sadie	Co-Investigator

Antarctic Organisms and Ecosystems	Award # 1740239
Antarctic Organisms and Ecosystems	Award # 1341649

USAP-1740239_1

None in the Database

1. Two case studies detailing Bayesian parameter inference for dynamic energy budget models (doi:10.1016/j.seares.2018.07.014)
2. Surface temperatures of albatross eggs and nests (doi:10.1080/01584197.2017.1406311)
3. Changing measurements or changing movements? Sampling scale and movement model identifiability across generations of biologging technology (doi:10.1002/ece3.3461)
4. deBInfer: Bayesian inference for dynamical models of biological systems in R (doi:10.1111/2041-210X.12679)
5. Djurhuus, A., Boersch-Supan, P. H., Mikalsen, S.-O., & Rogers, A. D. (2017). Microbe biogeography tracks water masses in a dynamic oceanic frontal system. Royal Society Open Science, 4(3), 170033. (doi:10.1098/rsos.170033)
6. Boersch‐Supan, P. H., Ryan, S. J., & Johnson, L. R. (2016). deBInfer: Bayesian inference for dynamical models of biological systems in R. Methods in Ecology and Evolution, 8(4), 511–518. (doi:10.1111/2041-210x.12679)
7. Nguyen, K. H., Boersch-Supan, P. H., Hartman, R. B., Mendiola, S. Y., Harwood, V. J., Civitello, D. J., & Rohr, J. R. (2021). Interventions can shift the thermal optimum for parasitic disease transmission. Proceedings of the National Academy of Sciences, 118(11), e2017537118. (doi:10.1073/pnas.2017537118)