Assessing the landscape functional connectivity using movement maps: a case study with endemic Azorean insects
There is a vast body of literature aiming to predict, for a large number of taxa, the spatial distribution of suitable areas given the expected future changes of climatic conditions. However, such studies often overlook the role of landscape functional connectivity. This is particularly relevant for species with low vagility, as ground-dwelling insects, inhabiting areas with high human pressure due to habitat destruction and fragmentation, namely in the islands. In this study, we developed an individual-based model (IBM) that simulates individual movement according to landscape resistance and mortality probability, in order to derive the landscape movement map, and applied it to five endemic ground-dwelling insects of Terceira Island (Azores). We then confronted the movement maps of each species against the species distribution models previously developed for both current and future climatic conditions, quantifying the amount of important movement areas that are enclosed by the distribution polygons. We further sought to identify where habitat restoration would increase the overall connectivity among large habitat patches. Our results showed that, for both timeframes, the distribution models enclosed small amounts of areas predicted to be important for animal movement. Additionally, we predicted strong reductions (up to 94%) of these important areas for functional connectivity. We also identified areas in-between native forest of primary importance for restoration that may significantly increase the probability of persistence of our model species. We anticipate that this study will be useful to both conservation planners and ecologists seeking to understand species movement and dispersal both is islands and elsewhere.
KeywordsClimate change adaptation Landscape management Individual-based model Island ecology Azores
A special thanks to Pedro Neves and David Avelar, for facilitating the computational resources that significantly reduced the simulation time; Luís Dias and Rita Godinho, for all the help and GIS support; and Luís Borda de Água, Mário Boieiro and Carla Rego for all the discussion and helpful comments and inputs. Data on species distributions was gathered based on the project ATLANTISMAR—“Mapping coastal and marine biodiversity of the Azores” (Ref: M2.1.2/I/027/2011). We also thank the anonymous reviewers, whose comments helped improving the quality of our manuscript.
BAA was partially founded by Fundação para a Ciência e Tecnologia (FCT) Unit funding (Ref: UID/BIA/00329/2013). PAVB, EBA and RBE were funded by the project “Implications of climate change for Azorean Biodiversity—IMPACTBIO” [M2.1.2/I/005/2011]. FA was funded by Infraestruturas de Portugal Biodiversity Chair and Fundação para a Ciência e Tecnologia (FCT, SFRH/BPD/115968/2016).
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
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