VTechWorks staff will be away for the Thanksgiving holiday beginning at noon on Wednesday, November 27, through Friday, November 29. We will resume normal operations on Monday, December 2. Thank you for your patience.

Browsing by Author "Keyes, Tim"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Application of Bayesian robust design model to assess the impacts of a hurricane on shorebird demography
    Gibson, Daniel; Riecke, Thomas V.; Keyes, Tim; Depkin, Chris; Fraser, James D.; Catlin, Daniel H. (Ecological Society of America, 2018-08)
    The increasing use of Bayesian inference in population demography requires rapid advancements in modeling frameworks to approach the rigor and flexibility of the current suite of maximum-likelihood models. We developed an unbiased, Jolly-Seber robust design (JSRD) model that is both accessible and generalizable in a Bayesian hierarchical multistate framework. We integrated band and age-classification data to estimate site entry, temporary emigration, and apparent survival rates, as well as estimate age-class specific abundances. The complete model parameterization is provided in the Appendix S1, as well as tools for simulating capture histories and an assessment of model fit. We applied this model to determine whether these demographic processes in non-breeding population of American oystercatchers (Haematopus palliatus) were affected by a major hurricane event (Hurricane Matthew) in coastal Georgia. The JSRD model was demonstrably unbiased at relatively small sample sizes, and the majority of parameters were identifiable in the fully saturated model parameterization. In the model application, we found that Hurricane Matthew temporarily altered local population abundances of American oystercatchers through increased movements of individuals into and out of the observable population, but mortality rates were largely unaffected. Together, our results suggest that American oystercatchers were largely able to avoid the immediate demographic consequences (i.e., reduced survival) of Hurricane Matthew. Integrating age and band ratios from survey data allowed for more descriptive and potentially less biased estimates of age-specific abundance, relative to estimates generated solely from either mark-resight or survey data.
  • Thumbnail Image
    Effects of future sea level rise on coastal habitat
    Von Holle, Betsy; Irish, Jennifer L.; Spivy, Annette; Weishampel, John F.; Meylan, Anne; Godfrey, Matthew H.; Dodd, Mark; Schweitzer, Sara H.; Keyes, Tim; Sanders, Felicia; Chaplin, Melissa K.; Taylor, Nick R. (2019-04)
    Sea level rise (SLR) and disturbances from increased storm activity are expected to diminish coastal ecosystems available to nesting species by removing habitat and inundating nests during incubation. We updated the United States Geological Survey's (USGS) Coastal Vulnerability Index, which provides a qualitative and relative assessment of a coastal area's vulnerability to erosion and shoreline retreat as a function of SLR and other factors, for the South Atlantic Bight. We considered a eustatic SLR projection of 14 cm by 2030. We linked long-term survey data for 3 sea turtle species, 3 shorebird species, and 5 seabird species to future coastal erosion vulnerability to SLR to understand effects of future SLR on nesting habitats. Over 2,000 km (43%) of the South Atlantic Bight coastline is projected to have an increase in coastal erosion vulnerability by the 2030s, with respect to its present vulnerability. Future vulnerability of SLR-induced erosion along the South Atlantic Bight is spatially variable, and the 11 coastal study species also varied in their use of coastal habitats with high future coastal vulnerability to SLR. For example, only 23% of high-density nesting habitat for the brown pelican (Pelecanus occidentalis) is expected to be at increased vulnerability to SLR, whereas >70% of the high-nesting density habitat for 2 seabird species (gull-billed tern [Gelochelidon nilotica], sandwich tern [Thalasseus sandvicensis]) is predicted to have higher future coastal erosion vulnerability by 2030. We provide predictions for the level of susceptibility of the study species to erosion from future SLR, which is the first step in managing coastal species for the changing environmental conditions associated with climate change and SLR. (c) 2019 The Authors. Journal of Wildlife Management Published by Wiley Periodicals, Inc. on behalf of The Wildlife Society.