Abstract

AbstractUnderstanding how populations respond to spatially heterogeneous habitat disturbance is as critical to conservation as it is challenging. Here, we present a new, free, and open‐source metapopulation model: Dynamic Habitat Disturbance and Ecological Resilience (DyHDER), which incorporates subpopulation habitat condition and connectivity into a population viability analysis framework. Modeling temporally dynamic and spatially explicit habitat disturbance of varying magnitude and duration is accomplished through the use of habitat time‐series data and a mechanistic approach to adjusting subpopulation vital rates. Additionally, DyHDER uses a probabilistic dispersal model driven by site‐specific habitat suitability, density dependence, and directionally dependent connectivity. In the first application of DyHDER, we explore how fragmentation and projected climate change are predicted to impact a well‐studied Bonneville cutthroat trout metapopulation in the Logan River (Utah, USA). The DyHDER model predicts which subpopulations are most susceptible to disturbance, as well as the potential interactions between stressors. Further, the model predicts how populations may be expected to redistribute following disturbance. This information is valuable to conservationists and managers faced with protecting populations of conservation concern across landscapes undergoing changing disturbance regimes. The DyHDER model provides a valuable and generalizable new tool to explore metapopulation resilience to spatially and temporally dynamic stressors for a diverse range of taxa and ecosystems.

Highlights

  • The distribution and composition of habitats in a landscape are governed by the interactions between regional climate, geology, ecological succession, and disturbance regimes, generating a mosaic of patchy habitats across multiple spatial scales (e.g., Whited et al 2007, Turner 2010)

  • While we did not evaluate perturbation response times here, one could with the Dynamic Habitat Disturbance and Ecological Resilience (DyHDER) model

  • While age-0 Bonneville cutthroat trout (BCT) are important to the population dynamics, we did not include them in our comparative results, as they are not effectively sampled

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Summary

Introduction

The distribution and composition of habitats in a landscape are governed by the interactions between regional climate, geology, ecological succession, and disturbance regimes, generating a mosaic of patchy habitats across multiple spatial scales (e.g., Whited et al 2007, Turner 2010). Our ability to predict biotic population-level responses to acute or chronic disturbances requires detailed information about the biotic processes affecting survival and recruitment rates, as well as the landscape-scale physical processes influencing the relative quality of local habitat patches (Murphy et al 1990, AkCß akaya, 2000, Wilcox et al 2006)

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