Non-invasive genetic sampling has been used to reconstruct spatial patterns of carnivore distributions, identify regions where conflicts with human activities could threaten the survival of a species, and assess the effectiveness of conservation strategies. In this study, we used detailed information on wolf (Canis lupus) and livestock distributions to infer depredation risks in a wide area of the Italian Apennines. We carried out a General Niche Environment System Factor Analysis (GNESFA) to define the potential distribution of wolves genotyped from 8565 samples collected during 12 years of non-invasive genetic monitoring in 3622 locations. Habitat suitability models indicated that the proportion of meadows, altitude, slope, roughness, and distance from human settlements were the main factors positively related to the potential wolf distribution, in contrast with the extension of cultivated fields and human settlements. Results of GNESFA were used to infer the local depredation risk, which was high in 46.9 % of the pastures, and to rank the areas where prevention tools should be used with priority. In this way, the use of often-limited financial resources for prevention could be promoted in pastures with the highest depredation risk and conflicts between husbandry and wolf presence might be mitigated.

Non-invasive genetic sampling to predict wolf distribution and habitat suitability in the Northern Italian Apennines: implications for livestock depredation risk

Milanesi P.;Meriggi A.;
2015-01-01

Abstract

Non-invasive genetic sampling has been used to reconstruct spatial patterns of carnivore distributions, identify regions where conflicts with human activities could threaten the survival of a species, and assess the effectiveness of conservation strategies. In this study, we used detailed information on wolf (Canis lupus) and livestock distributions to infer depredation risks in a wide area of the Italian Apennines. We carried out a General Niche Environment System Factor Analysis (GNESFA) to define the potential distribution of wolves genotyped from 8565 samples collected during 12 years of non-invasive genetic monitoring in 3622 locations. Habitat suitability models indicated that the proportion of meadows, altitude, slope, roughness, and distance from human settlements were the main factors positively related to the potential wolf distribution, in contrast with the extension of cultivated fields and human settlements. Results of GNESFA were used to infer the local depredation risk, which was high in 46.9 % of the pastures, and to rank the areas where prevention tools should be used with priority. In this way, the use of often-limited financial resources for prevention could be promoted in pastures with the highest depredation risk and conflicts between husbandry and wolf presence might be mitigated.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1103277
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