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. 2020 Dec;89(12):2777-2787.
doi: 10.1111/1365-2656.13352. Epub 2020 Oct 12.

Habitat selection patterns are density dependent under the ideal free distribution

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Habitat selection patterns are density dependent under the ideal free distribution

Tal Avgar et al. J Anim Ecol. 2020 Dec.

Abstract

Despite being widely used, habitat selection models are rarely reliable and informative when applied across different ecosystems or over time. One possible explanation is that habitat selection is context-dependent due to variation in consumer density and/or resource availability. The goal of this paper is to provide a general theoretical perspective on the contributory mechanisms of consumer and resource density-dependent habitat selection, as well as on our capacity to account for their effects. Towards this goal we revisit the ideal free distribution (IFD), where consumers are assumed to be omniscient, equally competitive and freely moving, and are hence expected to instantaneously distribute themselves across a heterogeneous landscape such that fitness is equalised across the population. Although these assumptions are clearly unrealistic to some degree, the simplicity of the structure in IFD provides a useful theoretical vantage point to help clarify our understanding of more complex spatial processes. Of equal importance, IFD assumptions are compatible with the assumptions underlying common habitat selection models. Here we show how a fitness-maximising space use model, based on IFD, gives rise to resource and consumer density-dependent shifts in consumer distribution, providing a mechanistic explanation for the context-dependent outcomes often reported in habitat selection analysis. Our model suggests that adaptive shifts in consumer distribution patterns would be expected to lead to nonlinear and often non-monotonic patterns of habitat selection. These results indicate that even under the simplest of assumptions about adaptive organismal behaviour, habitat selection strength should critically depend on system-wide characteristics. Clarifying the impact of adaptive behavioural responses may be pivotal in making meaningful ecological inferences about observed patterns of habitat selection and allow reliable transferability of habitat selection predictions across time and space.

Keywords: IFD with costs; RSF; SDM; availability dependence; functional response; mIFD; optimal foraging; patch choice.

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Figures

FIGURE 1
FIGURE 1
mIFD‐based habitat selection strength as function of mean consumer density (x‐axis) and mean resource density (dotted line: (Ri + Rj)/2 = 1, dashed line: (Ri + Rj)/2 = 5, solid line: (Ri + Rj)/2 = 10). The different sub‐plots represent different ecological scenarios: an Arditi–Akcakaya model where the two habitats differ by instantaneous resource availability only (Ri + Rj)/2 = 1; a), handling time only (b[Ai] = 1.5, b[Aj] = 0.5; c), or autecological fitness gain only (g[Ai] = 1.5, g[Aj] = 0.5; e), or a Beddington–DeAngelis model where the two habitats differ by instantaneous resource availability only (Ri − Rj = 1; b), handling time only (b[Ai] = 1.5, b[Aj] = 0.5; d), or autecological fitness gain only (g[Ai] = 0.5, g[Aj] = 0.5; f)
FIGURE 2
FIGURE 2
mIFD‐based habitat selection strength as function of mean consumer density (x‐axis), where the two habitats differ only by resource assimilation efficiency (s[Ai] – s[Aj] = 1). The different sub‐plots represent different ecological scenarios: a type II (b[Ai] = b[Aj] = 1) Arditi–Akcakaya model across three different mean resource densities (a; dotted line: Ri = Rj = 1, dashed line: Ri = Rj = 5, solid line: Ri = Rj = 10), a type II (b[Ai] = b[Aj] = 1) Beddington–DeAngelis model across three different resource densities (b; dotted line: Ri = Rj = 1, dashed line: Ri = Rj = 5, solid line: Ri = Rj = 10), a type I (b[Ai] = b[Aj] = 0) Arditi–Akcakaya model across three different magnitudes of assimilation‐efficiencies (c; thin line: s[Ai] = 1.5, medium line: s[Ai] = 10.5, wide line: s[Ai] = 100.5), and a type I (b[Ai] = b[Aj] = 0) Beddington–DeAngelis model across three different magnitudes of assimilation‐efficiencies (d; thin line: s[Ai] = 1.5, medium line: s[Ai] = 10.5, wide line: s[Ai] = 100.5)
FIGURE 3
FIGURE 3
mIFD‐based habitat selection strength as function of mean consumer density (x‐axis). The different sub‐plots represent different ecological scenarios: an Arditi–Akcakaya model where the two habitats differ by search rate only (a[Ai] − a[Aj] = 1) across three different magnitudes of search‐rate (a; thin line: a[Ai] = 1.5, medium line: a[Ai] = 5.5, wide line: a[Ai] = 10.5), a Beddington–DeAngelis model where the two habitats differ by search rate only (a[Ai] − a[Aj] = 1) across three different magnitudes of search‐rate (b; thin line: a[Ai] = 1.5, medium line: a[Ai] = 5.5, wide line: a[Ai] = 10.5), an Arditi–Akcakaya model where the two habitats differ by consumer interference only (c[Ai] − c[Aj] = 1) across three different magnitudes of consumer interference (c; thin line: c[Ai] = 1.5, medium line: c[Ai] = 5.5, wide line: c[Ai] = 10.5), and a Beddington–DeAngelis model where the two habitats differ by consumer interference only (c[Ai] − c[Aj] = 1) across three different magnitudes of consumer interference (d; thin line: c[Ai] = 1.5, medium line: c[Ai] = 5.5, wide line: c[Ai] = 10.5)

References

    1. Aarts, G. , Fieberg, J. , & Matthiopoulos, J. (2012). Comparative interpretation of count, presence‐absence and point methods for species distribution models. Methods in Ecology and Evolution, 3(1), 177–187. 10.1111/j.2041-210X.2011.00141.x - DOI
    1. Aarts, G. , MacKenzie, M. , McConnell, B. , Fedak, M. , & Matthiopoulos, J. (2008). Estimating space‐use and habitat preference from wildlife telemetry data. Ecography, 31(1), 140–160. 10.1111/j.2007.0906-7590.05236.x - DOI
    1. Abrahams, M. V. , & Dill, L. M. (1989). A determination of the energetic equivalent of the risk of predation. Ecology, 70(4), 999–1007. 10.2307/1941368 - DOI
    1. Abrams, P. A. (2007). Habitat choice in predator‐prey systems: Spatial instability due to interacting adaptive movements. The American Naturalist, 169(5), 581–594. 10.1086/512688 - DOI - PubMed
    1. Arditi, R. , & Akçakaya, H. R. (1990). Underestimation of mutual interference of predators. Oecologia, 83(3), 358–361. 10.1007/BF00317560 - DOI - PubMed

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