4.7 Article

Spatial and temporal variability modify density dependence in populations of large herbivores

Journal

ECOLOGY
Volume 87, Issue 1, Pages 95-102

Publisher

ECOLOGICAL SOC AMER
DOI: 10.1890/05-0355

Keywords

Bayesian hierarchical model; climate variability; density dependence; large herbivores; Markov Chain Monte Carlo Method; normalized difference vegetation index; population dynamics; Rocky Mountains; spatial variability; temporal variability

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A central challenge in ecology is to understand the interplay of internal and external controls on the growth of populations. We examined the effects of temporal variation in weather and spatial variation in vegetation on the strength of density dependence in populations of large herbivores. We fit three subsets of the model ln(N-t) = a + (1 + b) x ln(Nt-1) + c x ln((Nt-2)) to five time series of estimates (N-t) of abundance of ungulates in the Rocky Mountains, USA. The strength of density dependence was estimated by the magnitude of the coefficient b. We regressed the estimates of b on indices of temporal heterogeneity in weather and spatial heterogeneity in resources. The 95% posterior intervals of the slopes of these regressions showed that temporal heterogeneity strengthened density-dependent feedbacks to population growth, whereas spatial heterogeneity weakened them. This finding offers the first empirical evidence that density dependence responds in-different ways to spatial heterogeneity and temporal heterogeneity.

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