A multi-scale looping approach to predict spatially dynamic patterns of functional species richness in changing landscapes


Land-use/land-cover (LU/LC) change is one of the main drivers of global biodiversity change. However, the lack of detailed data on species’ local distributions is frequently a major constraint to identify effective indicators of impact and to prescribe effective conservation and management measures. Here we aim to describe and demonstrate the applicability of a novel looping approach to predict spatially dynamic ecological responses to LU/LC changes. The methodology integrates statistical downscaling, multi-model inference, stochastic-dynamic modelling and simulations, and spatial projections under a common and interactive framework. We illustrate the approach with a study of passerine foraging groups and their potential indicator role under LU/LC change scenarios. Based on the coarse occurrence data from published atlases, this approach allowed transposing species richness to fine resolutions in order to assess regional ecological integrity by up scaling the local responses of those indicators again at the landscape level. Overall, our proposed framework was able to provide realistic patterns of passerine foraging responses to LU/LC changes, highlighting the usefulness of existing databases for model-based research in addressing complex emergent problems across scales. Comparative analysis between simulations and independent field data showed a promising model performance, with consistent projections of the local passerine functional composition for a significant number of point-counts tested. Our approach represents a contribution for more universal applications in the scope of conservation and landscape planning, especially when fine resolution data is difficult to obtain due to resources constraints.

In Ecological Indicators