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Responses of generalist and specialist species to fragmented landscapes

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  • Ramiadantsoa, Tanjona
  • Hanski, Ilkka
  • Ovaskainen, Otso

Abstract

Empirical studies have shown that, unlike species with specialized resource requirements, generalist species may benefit from habitat destruction. We use a family of models to probe the causes of the contrasting responses of these two types of species to habitat destruction. Our approach allows a number of mechanisms to be switched on and off, thereby making it possible to study their marginal and joint effects. Unlike many previous models, we do not assume any intrinsic competitive asymmetry between the species, and we assume pre-emptive rather than displacement competition. Under these assumptions, in the mean-field model the prevalences of all species decrease monotonically with decreasing habitat availability, independently of the degree of specialization. However, in the stochastic and spatial individual-based simulations of the same model, the specialists dominate in landscapes of high quality, whereas generalists thrive in landscapes of intermediate quality; no species persist in very poor landscapes. The same pattern also occurs in a non-spatial stochastic model but not in a deterministic spatial model, showing that demographic stochasticity plays a key role in shaping the outcome of competitive interactions.

Suggested Citation

  • Ramiadantsoa, Tanjona & Hanski, Ilkka & Ovaskainen, Otso, 2018. "Responses of generalist and specialist species to fragmented landscapes," Theoretical Population Biology, Elsevier, vol. 124(C), pages 31-40.
  • Handle: RePEc:eee:thpobi:v:124:y:2018:i:c:p:31-40
    DOI: 10.1016/j.tpb.2018.08.001
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    1. Stuart L. Pimm & Peter Raven, 2000. "Extinction by numbers," Nature, Nature, vol. 403(6772), pages 843-845, February.
    2. Jesper Møller & Rasmus P. Waagepetersen, 2007. "Modern Statistics for Spatial Point Processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 34(4), pages 643-684, December.
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