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Using null models to identify under-represented species in protected areas: A case study using European amphibians and reptiles

AutorSánchez-Fernández, David ; Abellán, Pedro
Palabras claveBiodiversity
Gap analysis
Mean percentage overlap (MPO)
Natura 2000
Effectiveness of protected areas
Fecha de publicaciónabr-2015
CitaciónBiological Conservation 184: 290-299 (2015)
ResumenOne of the main issues in conservation biology is assessing how much biodiversity is currently represented in protected areas (PA). Traditional approaches such as 'gap analysis' require the choice of arbitrary targets and thresholds that can greatly influence the obtained results. We present here a complementary approach that avoids typical methodological uncertainties being particularly useful when the aim is to explore differences in the effectiveness of PA networks in representing species with distinct features and varying range sizes. Firstly, we calculated how far the distribution of a species overlaps with a network. Then, null models were used to test if this value is significantly different from random expectations (i.e. compared with random species of the same number of occurrences), which allowed over and under-represented species to be identified. Using this approach, we aimed to determine how well amphibian and terrestrial reptile species in Europe were represented by two protected area networks: nationally designated protected areas (NPAs) and the Natura 2000 network (N2000). We also tested to see if there were any differences in species representation depending upon their conservation status, range size and distribution type. Although N2000 is more effective than NPAs, both PA networks performed poorly in representing European amphibians and reptiles, as the level of representativeness for most species (excepting reptiles in N2000) within these networks was either not significantly different or significantly lower than expected by chance. A combination of this approach with traditional gap analyses could provide valuable information to improve the future effectiveness of PAs. © 2015 Elsevier Ltd.
Versión del editorhttp://dx.doi.org/10.1016/j.biocon.2015.02.006
Identificadoresdoi: 10.1016/j.biocon.2015.02.006
issn: 0006-3207
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