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Functional responses in habitat selection: clarifying hypotheses and interpretations.

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TLDR
Assessment of the conceptual and statistical foundations of methods currently used to model functional responses and the ecological tests evaluated within each approach helps clarify the similarities and differences among current approaches and, therefore, assists the integration of functional responses into the mainstream of habitat ecology and management.
Abstract
A fundamental challenge in habitat ecology and management is understanding the mechanisms generating animal distributions. Studies of habitat selection provide a lens into such mechanisms, but are often limited by unrealistic assumptions. For example, most studies assume that habitat selection is constant with respect to the availability of resources, such that habitat use remains proportional to availability. To the contrary, a growing body of work has shown the fallacy of this assumption, indicating that animals modify their behavior depending on the context at broader scales. This has been termed a functional response in habitat selection. Furthermore, a diversity of methods is employed to model functional responses in habitat selection, with little attention to how methodology might affect scientific and conservation conclusions. Here, we first review the conceptual and statistical foundations of methods currently used to model functional responses and clarify the ecological tests evaluated within each approach. We then use a combination of simulated and empirical data sets to evaluate the similarities and differences among approaches. Importantly, we identified multiple statistical issues with the most widely applied approaches to understand functional responses, including: (1) a complex and important role of random- or individual-level intercepts in adjusting individual-level regression coefficients as resource availability changes and (2) a sensitivity of results to poorly informed individual-level coefficients estimated for animals with low availability of a given resource. Consequently, we provide guidance on applying approaches that are insensitive to these issues with the goal of advancing our understanding of animal habitat ecology and management. Finally, we characterize the management implications of assuming similarity between the current approaches to model functional responses with two empirical data sets of federally threatened species: Canada lynx (Lynx canadensis) in the United States and woodland caribou (Rangifer tarandus caribou) in Canada. Collectively, our assessment helps clarify the similarities and differences among current approaches and, therefore, assists the integration of functional responses into the mainstream of habitat ecology and management.

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Citations
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Wolverines in winter: Indirect habitat loss and functional responses to backcountry recreation

TL;DR: In this paper, the effect of back-country recreation on wolverine habitat relationships was investigated using Global Positioning System (GPS) collars to 24 individual wolverines and acquired >54,000 GPS locations over 39 animal-years during winter.
Journal ArticleDOI

Habitat selection patterns are density-dependent under the Ideal Free Distribution.

TL;DR: It is shown 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.
Journal ArticleDOI

California spotted owl habitat selection in a fire-managed landscape suggests conservation benefit of restoring historical fire regimes

TL;DR: This paper studied the behavior of 22 GPS-tagged California spotted owls in three national parks (Yosemite, Sequoia, and Kings Canyon) in the Sierra Nevada, California, USA where natural fires have largely been allowed to burn during the past 50 years and controlled burning has been used to target additional areas.
Journal ArticleDOI

Conceptual and methodological advances in habitat-selection modeling: guidelines for ecology and evolution

TL;DR: An overview and synthesis of the literature on habitat-selection analyses (HSAs) conducted using selection functions is provided in this article, which is by far the most applied modeling framework for understanding the habitat selection process.
Journal ArticleDOI

Functional responses to anthropogenic linear features in a complex predator-multi-prey system

TL;DR: In this paper, the authors evaluated functional responses of threatened boreal woodland caribou, moose, and gray wolves to roads and seismic lines to assess the influence these responses might have on predator-prey interactions.
References
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Journal Article

R: A language and environment for statistical computing.

R Core Team
- 01 Jan 2014 - 
TL;DR: Copyright (©) 1999–2012 R Foundation for Statistical Computing; permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and permission notice are preserved on all copies.
Journal ArticleDOI

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Douglas H. Johnson
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Journal ArticleDOI

Some characteristics of simple types of predation and parasitism

TL;DR: In an earlier study (Holling, 1959), the basic and subsidiary components of predation were demonstrated in a predator-prey situation involving the predation of sawfly cocoons by small mammals.
Book

Resource Selection by Animals : Statistical design and analysis for field studies

TL;DR: This paper presents a meta-modelling procedure for estimating a resource selection probability function from a census of resource units using logistic regression and discriminant function methods and its applications in resource selection and resource selectory studies.
Journal ArticleDOI

Evaluating resource selection functions

TL;DR: A form of k -fold cross validation for evaluating prediction success is proposed for presence/available RSF models, which involves calculating the correlation between RSF ranks and area-adjusted frequencies for a withheld sub-sample of data.
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How do correlations and studies of habitat selection help us understand animal behavior?

Correlations and studies of habitat selection help us understand animal behavior by linking patterns of animal behavior to underlying resource availability.