Graph theory, network theory, and circuit theory are increasingly being used to quantify multiple aspects of habitat connectivity and protected areas. There has been an explosive proliferation of network (connectivity) measures, resulting in over 60 measures for ecologists to now choose from. Conceptual clarification on the ecological meaning of these network measures and their interrelationships is overdue. We present a framework that categorizes network measures based on the connectivity property that they quantify (i.e., route-specific flux, route redundancy, route vulnerability, and connected habitat area) and the structural level of the habitat network to which they apply. The framework reveals a lack of network measures in the categories of "route-specific flux among neighboring habitat patches" and "route redundancy at the level of network components." We propose that network motif and path redundancy measures can be developed to fill the gaps in these categories. The value of this framework lies in its ability to inform the selection and application of network measures. Ultimately, it will allow a better comparison among graph, network, and circuit analyses, which will improve the design and management of connected landscapes.
Habitat loss fragments metacommunities, altering the movement of species between previously connected habitat patches. The consequences of habitat loss for ecosystem functioning depend, in part, on how these changes in connectivity alter the spatial insurance effects of biodiversity. Spatial insurance is the maintenance of biodiversity and stable ecosystem functioning in changing environments that occurs when species are able to move between local habitat patches in order to track conditions to which they are adapted. Spatial insurance requires a combination of species sorting dynamics, which allow species to disperse to habitats where they are productive, and mass effect dynamics, where dispersal allows species to persist in marginal habitats where environmental conditions do not support growth. Here we use a spatially explicit metacommunity model to show that the relative contribution of species sorting and mass effects to spatial insurance changes with the rate of dispersal. We then simulate different sequences of habitat loss by removing habitat patches based on their betweenness centrality (the degree to which a patch serves as a connection between other patches in the metacommunity). We demonstrate that the sequence of habitat loss has a large, non‐linear impact on diversity, ecosystem functioning and stability. Spatial insurance is lost because habitat fragmentation impedes species sorting, while promoting mass effects and dispersal limitation. We find that species sorting dynamics, and thus spatial insurance, are most robust to the removal of habitat patches with low betweenness centrality. These findings advance our understanding of how habitat connectivity facilitates the maintenance of biodiversity and ecosystem functioning, and may prove useful for the design of habitat networks.
Networks with a modular structure are expected to have a lower risk of global failure. However, this theoretical result has remained untested until now. We used an experimental microarthropod metapopulation to test the effect of modularity on the response to perturbation. We perturbed one local population and measured the spread of the impact of this perturbation, both within and between modules. Our results show the buffering capacity of modular networks. To assess the generality of our findings, we then analyzed a dynamical model of our system. We show that in the absence of perturbations, modularity is negatively correlated with metapopulation size. However, even when a small local perturbation occurs, this negative effect is offset by a buffering effect that protects the majority of the nodes from the perturbation.
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