Publications
Predicting pack-ice seal occupancy of ice floes along the Western Antarctic Peninsula
Wethington, M.J., B. Sen, and H.J. Lynch. 2024. Predicting pack-ice seal occupancy of ice floes along the Western Antarctic Peninsula. PLoS ONE 19(12): e0311747.
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Detecting stochasticity in population time series using a non-parametric test of intrinsic predictability
Sen, B., C. Che-Castaldo, H.J. Lynch, F. Ventura, M.A. LaRue, and S. Jenouvrier. 2024. Detecting stochasticity in population time series using a non-parametric test of intrinsic predictability. Methods in Ecology and Evolution doi: 10.1111/2041-210X.14423.
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Species classification of Antarctic pack-ice seals using very-high-resolution satellite imagery
Wethington, M.J., B.C. Goncalves, E. Talis, and H.J. Lynch. 2023. Species classification of Antarctic pack-ice seals using very-high-resolution satellite imagery. Marine Mammal Science 1-17.
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Capturing stochasticity properly is key to understanding the LPI
Talis, E., and H.J. Lynch. 2023. Letter: Capturing stochasticity properly is key to understanding the nuances of the Living Planet Index. Nature Ecology & Evolution https://doi.org/10.1038/s41559-023-02086-w
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Antarctic Penguin Biogeography Project
Che-Castaldo, C., G. Humphries, and H.J. Lynch. 2023. Antarctic Penguin Biogeography Project: Database of abundance and distribution for the Adélie, chinstrap, gentoo, emperor, macaroni, and king penguin south of 60 S. Biodiversity Data Journal 11: e101476.
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Penguindex: A Living Planet Index for Pygoscelis Species Penguins
Talis, Emma, C. Che-Castaldo, T. Hart, L. McCrae, and H.J. Lynch. 2023. Penguindex: A biodiversity indicator for Pygoscelis spp. penguins identifies key eras of population change. Polar Biology, Online at https://doi.org/10.1007/s00300-023-03148-2
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Spatio-temporal transferability of environmentally dependent population models
Sen, B., C. Che-Castaldo, K. Krumhardt, L. Landrum, M.M. Holland, M.A. LaRue, M.C. Long, S. Jenouvrier, and H.J. Lynch. 2023. Spatio-temporal transferability of environmentally-dependent population models: Insights from the intrinsic predictabilities of Adelie penguin abundance time series. Ecological Indicators 150: 110239.
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Difficulties in summing log-normal distributions for abundance and potential solutions
Talis, E., C. Che-Castaldo, and H.J. Lynch. 2023. Difficulties in summing distributions for abundance and potential solutions. PLoS ONE 18(1): e0280351.
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Variability, skipped breeding, and heavy-tailed dynamics in an Antarctic seabird
Talis, E., C. Che-Castaldo, B. Sen, K. Krumhardt, and H.J. Lynch. Variability, skipped breeding, and heavy-tailed dynamics in an Antarctic seabird. Journal of Animal Ecology 91: 2437-2450.
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Age-structured model reveals prolonged immigration is key for colony establishment in gentoo penguins
Herman, R.W, and H.J. Lynch. 2022. Age-structured model reveals prolonged immigration is key for colony establishment in Gentoo Penguins. In Press at Ornithological Applications.
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Switching state-space models for modeling penguin population dynamics
El-Laham, Y., M. Bugallo, and H.J. Lynch. 2022. Switching state-space models for modeling penguin population dynamics. In Press at Environmental and Ecological Statistics.
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Correcting for Within-Season Demographic Turnover to Estimate the Island-Wide Population of King Penguins (Aptenodytes patagonicus) on South Georgia
Foley, C.M., W.F. Fagan, and H.J. Lynch. 2020. Polar Biology 43: 251-262.
The Importance of Topographically Correct Null Models for Analyzing Ecological Point Processes
McDowall, P., and H.J. Lynch. 2017. Ecology 98: 1764-1770.
Ultra-Fine Spatially-Integrated Mapping of Habitat and Occupancy Using Structure-from-Motion
McDowall, P., and H.J. Lynch. 2017. PLoS ONE 12(1): e0166773.
Dealing With Under- and Over-Dispersed Count Data in Life History, Spatial, and Community Ecology
Lynch, H.J., J. Thorson, O. Shelton. 2014. Ecology 95(11): 3173-3180.
Using Citizen Science to Estimate Lichen Diversity
Casanovas, P.V., H.J. Lynch, and W.F. Fagan. 2014. Biological Conservation 171: 1-8.
Modeling Structured Population Dynamics Using Data From Unmarked Individuals
Zipkin. E.F., J.T. Thorson, K. See, H. J. Lynch, E.H.C. Grant, Y. Kanno, R.B. Chandler, B.H. Letcher, J.A. Royle. 2014. Ecology 95: 22-29.
Phylogenetic Prediction of the Maximum Per Capita Rate of Population Growth
Fagan, W.F., Y. Pearson, E.A. Larsen, H.J. Lynch, J. Turner, H. Staver, A. Noble, S. Bewick, and E.E. Goldberg. 2013. Proceedings of the Royal Society B 280: 20130523.
Survivorship Patterns in Captive Mammalian Populations: Implications for Estimating Population Growth Rates
Lynch, H.J., S. Zeigler, L. Wells, J.D. Ballou, W.F. Fagan. 2010. Ecological Applications 20(8): 2334-2345.
Effects of Branching Spatial Structure and Life History on the Asymptotic Growth Rate of a Population
Goldberg, E., H.J. Lynch, M. Neubert, W.F. Fagan. 2010. Theoretical Ecology 3(3): 137-152.
Pitfalls and Challenges of Estimating Population Growth Rate From Empirical Data: Consequences for Allometric Scaling Relations
Fagan, W.F., H.J. Lynch, and B. Noon. 2010. Oikos 119(3): 455-464.
Survivorship Curves and Their Impact on the Estimation of Maximum Population Growth Rates
Lynch, H.J. and W.F. Fagan. 2009. Ecology 90(4): 1116-1124.
A Spatiotemporal Ripley’s K-function to Analyze Between Spruce Budworm and Fire in British Columbia, Canada
Lynch, H.J. and P.R. Moorcroft. 2008. Canadian Journal of Forest Research 38: 3112-3119.