MoosePOPd: Population Dynamics in the Presence of Lethal Parasites

This interdisciplinary research contains data contributions from the New York State Department of Environmental Conservation and academic contributions from our collaborators at the Cornell Wildlife Health Lab at Cornell University and at the State University of New York Environmental Science and Forestry. Contributions may have provided intellectual property, knowledge, data, software code, time, suggestions, comments, and extension and communication products to one or more research products. Contributors, we thank you. 

Additional thanks to:

Niki Keith, who aided the project while at the Cornell Wildlife Health Lab, but has since moved on to Hamilton College of New York

Research:

Connelly, P, Hanley, B, Friar, J, Hurst, J, Stickles, J, Kramer, D, & Schuler, K. 201X. The effect of disease on Moose in New York, USA from 2015-2019. In preparation.

Hanley, B, Dennis, B, Kramer, D, & Schuler, K. Estimating parameters from adult time series data for population matrix models. In peer revision. 

Hanley B, Connelly P, & Dennis B. 2019. Another look at the eigenvalues of a population matrix model. PeerJ 7:e8018. doi: https://doi.org/10.7717/peerj.8018​ 

Interactive software:

¹ Connelly, P., Hanley, B., Frair, J., & Schuler, K. 2020. MoosePOPd Web Interactive: Software to investigate the demography of Moose in New York, USA from 2015-2019 [Software]. Cornell University Library eCommons Repository. doi: https://doi.org/10.7298/k033-va79

² Hanley, B, Connelly, P, & Dennis, B. 2019. IsoPOPd: Interactive software to understand how elements in a population matrix model influence the asymptotic population growth rate [Software]. Cornell University Library eCommons Repository. doi: https://doi.org/10.7298/bcmg-7w08

³ Connelly, P., Hanley, B., Frair, J., & Schuler, K. 2020. MooseCounterPOPd Web Interactive: Software to investigate the population scale impact of Brain Worm and Liver Fluke in Moose in New York, USA from 2015-2019 [Software]. Cornell University Library eCommons Repository. doi: https://doi.org/10.7298/kxme-kq04​

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