Measuring functional connectivity using long-term monitoring data
2011
Powney, Gary D | Roy, David B | Chapman, Daniel S | Brereton, Tom | Oliver, Tom H | Natural Environment Research Council | Department for Environment Food & Rural Affairs | Centre for Ecology & Hydrology (CEH) | Centre for Ecology & Hydrology (CEH) | Centre for Ecology & Hydrology | Butterfly Conservation Ltd | Centre for Ecology & Hydrology (CEH) | 0000-0003-1836-4112
1. We use population synchrony as a new empirical method to assess functional connectivity - the permeability of landscapes given species dispersal attributes. Functional connectivity is important because well-connected metapopulations are expected to be more resistant to stochastic events causing extinction. 2. A variety of factors impact population synchrony, and we attempt to account for several of these (shared climate, distance, habitat similarity and location within the range) before investigating impacts of the suitability of the landscape between populations - a proxy for permeability to dispersal. 3. For the Speckled Wood butterfly (Pararge aegeria), we find that population synchrony is positively correlated with landscape suitability, suggesting that synchrony might be used to measure functional connectivity. 4. The importance of landscape suitability for population synchrony shows a humped relationship with distance - suitability has no effect between 0 and 20 km, then showing a significant positive effect above 20 km but with reduced (still significant) effect from 160 to 200 km. This suggests that relatively close populations may exchange sufficient migrants for synchronisation, regardless of the matrix suitability. In contrast, more separate populations are synchronised only where the landscape permits functional connectivity, most likely through dispersal between intermediate stepping-stone populations. 5. Synthesis and applications. We show that patterns of synchrony in long-term monitoring data can be used to estimate functional connectivity of landscapes. As such, this technique might be used to test and prioritise the effectiveness of land management for conservation of species and to mitigate the effects of climate change.
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