Establishing the link between habitat selection and animal population dynamics

By Jason Matthiopoulos, J. Fieberg, G. Aarts, H. Beyer, J. Morales, Daniel T. Haydon. 2015

153 citations recorded by the source corpus.

Although classical ecological theory (e.g., on ideal free consumers) recognizes the potential effect of population density on the spatial distribution of animals, empirical species distribution models assume that species–habitat relationships remain unchanged across a range of population sizes. Conversely, even though ecological models and experiments have demonstrated the importance of spatial heterogeneity for the rate of population change, we still have no practical method for making the connection between the makeup of real environments, the expected distribution and fitness of their occupants, and the long-term implications of fitness for population growth. Here, we synthesize several conceptual advances into a mathematical framework using a measure of fitness to link habitat availability/selection to (density-dependent) population growth in mobile animal species. A key feature of this approach is that it distinguishes between apparent habitat suitability and the true, underlying contribution of a habitat to fitness, allowing the statistical coefficients of both to be estimated from multiple observation instances of the species in different environments and stages of numerical growth. Hence, it leverages data from both historical population time series and snapshots of species distribution to predict population performance under environmental change. We propose this framework as a foundation for building more realistic connections between a population's use of space and its subsequent dynamics (and hence a contribution to the ongoing efforts to estimate a species' critical habitat and fundamental niche). We therefore detail its associated definitions and simplifying assumptions, because they point to the framework's future extensions. We show how the model can be fit to data on species distributions and population dynamics, using standard statistical methods, and we illustrate its application with an individual-based simulation. When contrasted with nonspatial population models, our approach is better at fitting and predicting population growth rates and carrying capacities. Our approach can be generalized to include a diverse range of biological considerations. We discuss these possible extensions and applications to real data.

Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/ec23518cec28ee307135d9fcb600e17d972121be

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In Ecological Modeling

In Ecology

In Nature and Landscape Conservation

Citations in the corpus

Accounting for individual-specific variation in habitat-selection studies: Efficient estimation of mixed-effects models using Bayesian or frequentist computation (2018, background): “In particular, resource selection will not be constant across individuals, namely due to individual-specific preferences and/or functional responses in habitat selection (Mysterud and Ims, 1998; Hebblewhite and Merrill, 2008; Matthiopoulous et al., 2011; Aarts et al., 2013; Matthiopoulos et al., 201”
Roles of Raptors in a Changing World: From Flagships to Providers of Key Ecosystem Services (2016, background): “Bio-logging innovations and practical analytical methods are increasingly formalising the close relationship between individual behaviour, habitat selection, species abundance, and population dynamics (Morales et al., 2010; Matthiopoulos et al., 2015; Van Moorter, 2015).”