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Integrating demography, dispersal and interspecific interactions into bird distribution models
Author(s) -
Zurell Damaris
Publication year - 2017
Publication title -
journal of avian biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.022
H-Index - 76
eISSN - 1600-048X
pISSN - 0908-8857
DOI - 10.1111/jav.01225
Subject(s) - biological dispersal , interspecific competition , biology , ecology , abiotic component , ecological niche , niche , biodiversity , species distribution , environmental niche modelling , biotic component , habitat , population , demography , sociology
Species’ ranges are primarily limited by the physiological (abiotic) tolerance of the species, described by their fundamental niche. Additionally, demographic processes, dispersal, and interspecific interactions with other species are shaping species distributions, resulting in the realised niche. Understanding the complex interplay between these drivers is vital for making robust biodiversity predictions to novel environments. Correlative species distribution models have been widely used to predict biodiversity response but also remain criticised, as they are not able to properly disentangle the abiotic and biotic drivers shaping species’ niches. Recent developments have thus focussed on 1) integrating demography and dispersal into species distribution models, and on 2) integrating interspecific interactions. Here, I review recent demographic and multi‐species modelling approaches and discuss critical aspects of these models that remain underexplored in general and in respect to birds, for example, the complex life histories of birds and other animals as well as the scale dependence of interspecific interactions. I conclude by formulating modelling guidelines for integrating the abiotic and biotic processes that limit species’ ranges, which will help to disentangle the complex roles of demography, dispersal and interspecific interactions in shaping species niches. Throughout, I pinpoint complexities of avian life cycles that are critical for consideration in the models and identify data requirements for operationalizing the different modelling steps.

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