Modeling and Mapping Abundance of American Woodcock Across the Midwestern and Northeastern United States

We used an over-dispersed Poisson regression with fixed and random effects, fitted by Markov chain Monte Carlo methods, to model population spatial patterns of relative abundance of American woodcock (Scolopax minor) across its breeding range in the United States. We predicted North American woodcoc...

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Veröffentlicht in:	The Journal of wildlife management 2007-04, Vol.71 (2), p.376-382
Hauptverfasser:	THOGMARTIN, WAYNE E, SAUER, JOHN R, KNUTSON, MELINDA G
Format:	Artikel
Sprache:	eng
Schlagworte:	animal preferences Bayesian Bayesian analysis Betula Climate models climatic factors conditional autoregression count data Forest habitats forests Geographic information systems Grasslands Growing seasons Habitat conservation habitat preferences Habitats Heterogeneity Human influences Land cover linear models Management Markov chain Markov chain Monte Carlo Markov chains mathematical models Modeling Monte Carlo method Monte Carlo simulation Parametric models Poisson distribution Polls & surveys Population population size Populus tremuloides prediction regression analysis Relative abundance Research s Scolopax Scolopax minor Shrubs simulation models Singing Ground Survey spatial autocorrelation spatial distribution Spatial models surveys vegetation cover wild birds wildlife habitats Wildlife management
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