<div><div>Oral presentation at the 1st International Conference on Community Ecology, September 28-29, 2017, Budapest</div><div><br></div><div>Abstract:</div><div>Habitat connectivity is of major importance in biodiversity conservation, and is one of the key aspects to be taken into consideration in the spatial design of networks of protected areas. Network analyses provide efficient tools for modelling habitat connectivity and defining priority areas for protecting it [1]. Widespread prioritization approaches are based on rankings of the centrality (or importance) of individual habitat patches. However, it has been noted that the set of nodes selected as key for conservation through individual ranking may depart from the optimal or most efficient group of nodes [2]. Multi-node analyses calculate the combined centrality of a set of n habitat patches in order to identify groups of patches that maximally complement each other in order to increase the protection of connectivity for the whole network. We apply multi-node analyses to the prioritization of habitat patches for five vulnerable bird species in Catalonia, Spain, using two different approaches to connectivity, based on fragmentation and reachability. Groups of patches based on fragmentation are usually concentrated on core areas, while reachability groups are widely spread. Fragmentation sets have higher centrality value for low-mobility species, and reachability sets for long distance dispersers. The protection of the networks against fragmentation requires fewer patches, allows for more gradual implementation and is currently better accounted for by the Natura 2000 network of protected areas, while the protection of reachability is less costly and more efficient in terms of area requirements. Our work contributes to the inclusion of multi-node approaches in landscape graph analysis for reserve design.</div><div><br></div><div>References</div><div>1. D.L. Urban, E.S. Minor, E.A. Treml and R.S. Schick, “Graph models of habitat mosaics”, Ecology Letters, 12(3), 260–273, 2009</div><div>2. S.P. Borgatti, “The Key Player Problem”, Dynamic Social Network Modeling and Analysis: Workshop Summary and Papers (eds R. Breiger, K. Carley & P. Pattison), pp. 241-252. Committee on Human Factors, National Research Council, 2003</div></div><div><br></div
