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Gauging the impact of management expertise on the distribution of large mammals across protected areas
Author(s) -
Li Sheng,
McShea William J.,
Wang Dajun,
Lu Zhi,
Gu Xiaodong
Publication year - 2012
Publication title -
diversity and distributions
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.918
H-Index - 118
eISSN - 1472-4642
pISSN - 1366-9516
DOI - 10.1111/j.1472-4642.2012.00907.x
Subject(s) - ecology , geography , distribution (mathematics) , environmental resource management , biology , environmental science , mathematics , mathematical analysis
Aim The world's network of protected areas ( PA s) plays a critical role in biodiversity conservation. The management expertise within PA s is a function of the training, support and depth of the staff tasked with protecting the resources and should be a significant factor determining the distribution of wildlife species. However, there are few measurable linkages between wildlife populations and management effectiveness. Here, we addressed whether the management expertise within a PA is an important covariate explaining the occupancy of large terrestrial mammals, and identify the attributes of mammal species that would be effective for comparative monitoring of management effectiveness within PA s of developing countries. Location Six PA s within giant panda region, south‐west China. Methods We used systematic camera‐trapping as the primary field methodology to detect the presence of large mammals and used expert scoring to assess the management level of these PA s. Occupancy modelling and logistic regression were used to determine those mammal species with adequate detections to control for ecological covariates and to compare differences in management level between the sampled PA s. Results Thirty‐eight mammal species were recorded with a total sampling effort of 16,521 camera‐days at 722 sample sites. Among the 14 examined mammals, Takin ( Budorcas taxicolor ) was the most detected mammal (333 detections at 153 locations), whereas Asiatic black bear ( Ursus thibetanus ) was estimated with the highest occupancy rate (ψ = 0.49) and leopard cat ( Prionailurus bengalensis ) was estimated with the highest detection probability ( P  =   0.55). The independently assessed estimate of management expertise was a significant positive predictor for the occupancy of 11 of the 14 mammal species. Main conclusions Our results suggest that there are measurable consequences for increasing PA patrolling and that standardized monitoring of large mammals is an adequate comparative measure of management effectiveness across diverse PA s that experience extensive poaching pressure.

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