Landscape connectivity, defined as the degree to which the landscape facilitates or impedes movement among resource patches, is an important issue for biodiversity conservation. However, the use of landscape connectivity measures has been strongly criticized due to uncertainties in the estimation of those metrics and the lack of empirical validation. Moreover, connectivity measures are always restricted to population level whereas management is generally carried out at the community level.
We used satellite imagery (Normalized Difference Vegetation Index NDVI) and network metrics to predict the landscape connectivity at community level for semi natural herbaceous patches in an urban area near Paris (France).
We assessed the fit of these predicted connectivity to empirical data on plant communities embedded in an urban matrix.
Our results indicate that connectivity estimated with the flow metric and taking into account the matrix heterogeneity produce the best fit to the empirical data. Overall our study helped to estimate the landscape connectivity of urban area and we proposed recommendations to optimize landscape planning with respect to conservation of urban biodiversity (Muratet et al. 2012).