Connectivity is a central concept in ecology, wildlife management and conservation science. Understanding the role of connectivity in determining species persistence is increasingly important in the face of escalating anthropogenic impacts on climate and habitat. These connectivity augmenting processes can severely impact species distributions and community and ecosystem functioning. One general definition of connectivity is an emergent process arising from a set of spatial interdependencies between individuals or populations, and increasingly realistic representations of connectivity are being sought. Generally, connectivity consists of a structural component, relating to the distribution of suitable and unsuitable habitat, and a functional component, relating to movement behavior, yet the interaction of both components often better describes ecological processes. Additionally, although implied by ‘movement’, demographic measures such as the occurrence or abundance of organisms are regularly overlooked when quantifying connectivity. Integrating demographic contributions based on the knowledge of species distribution patterns is critical to understanding the dynamics of spatially structured populations. Demographically-informed connectivity draws from fundamental concepts in metapopulation ecology while maintaining important conceptual developments from landscape ecology, and the methodological development of spatially-explicit hierarchical statistical models that have the potential to overcome modeling and data challenges. Together, this offers a promising framework for developing ecologically realistic connectivity metrics. This review synthesizes existing approaches for quantifying connectivity and advocates for demographically-informed connectivity as a general framework for addressing current problems across ecological fields reliant on connectivity-driven processes such as population ecology, conservation biology, and landscape ecology. Using supporting simulations to highlight the consequences of commonly made assumptions that overlook important demographic contributions, we show that even small amounts of demographic information can greatly improve model performance. Ultimately, we argue demographic measures are central to extending the concept of connectivity and resolves long-standing challenges associated with accurately quantifying the influence of connectivity on fundamental ecological processes.,This file contains simulation code implemented in R that created data used in the manuscript DOI:10.1111/ecog.05552 As well, The data the simulation code creates is provided as the simulation does take some time to run (up to several weeks depending on the parameter combinations). These will be found in 4 zips, each reflecting a different scenario found in the text. Combinations of the patch area to abundance relationship or it being disrupted; this intersects with whether those abundance are high or low within simulated patches. Within each of these will be found the model runs that correspond to combinations of 5 and 10 years and 30, 50, and 100 patches.,
Date made available | 10 Jun 2021 |
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Publisher | Dryad |
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