Dynamic species distribution models from categorical survey data

Mieszkowska, N. and Milligan, G. and Burrows, M. T. and Freckleton, R. and Spencer, M. (2013) Dynamic species distribution models from categorical survey data. Journal of Animal Ecology, 82. pp. 1215-1226. ISSN 0021-8790

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Abstract

Species distribution models are static models for the distribution of a species, based on Hutchinson's niche concept. They make probabilistic predictions about the distribution of a species, but do not have a temporal interpretation. In contrast, density‐structured models based on categorical abundance data make it possible to incorporate population dynamics into species distribution modelling. Using dynamic species distribution models, temporal aspects of a species' distribution can be investigated, including the predictability of future abundance categories and the expected persistence times of local populations, and how these may respond to environmental or anthropogenic drivers. We built density‐structured models for two intertidal marine invertebrates, the Lusitanian trochid gastropods Phorcus lineatus and Gibbula umbilicalis, based on 9 years of field data from around the United Kingdom. Abundances were recorded on a categorical scale, and stochastic models for year‐to‐year changes in abundance category were constructed with winter mean sea surface temperature (SST) and wave fetch (a measure of the exposure of a shore) as explanatory variables. Both species were more likely to be present at sites with high SST, but differed in their responses to wave fetch. Phorcus lineatus had more predictable future abundance and longer expected persistence times than G. umbilicalis. This is consistent with the longer lifespan of P. lineatus. Where data from multiple time points are available, dynamic species distribution models of the kind described here have many applications in population and conservation biology. These include allowing for changes over time when combining historical and contemporary data, and predicting how climate change might alter future abundance conditional on current distributions.

Item Type: Article
Faculty / Department: Faculty of Science > Geography and Environmental Science
Depositing User: Gregg Milligan
Date Deposited: 08 Apr 2019 10:32
Last Modified: 08 Apr 2019 10:32
URI: http://hira.hope.ac.uk/id/eprint/2781

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