Determinants of diet selection by Blackbuck Antilope cervicapra at Point Calimere, southern India: quality also matters
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Abstract
Unlike the wide-ranging habitat generalists that move seasonally across heterogenous habitats to optimize the energy intake, short-ranging habitat specialists fulfil the same by restricting to single habitat. Understanding how habitat-specialists do this is an interesting question and essential for their conservation. We studied the diet composition and evaluated the covariates belonging to climate, habitat and grass dynamics to assess the determinants of seasonal diet selection by Blackbuck Antilope cervicapra, an antelope endemic to the Indian subcontinent, at Point Calimere Wildlife Sanctuary, southern India. Diet composition studied following feeding trail observation (n = 102322) and the influence of covariates on the top five major diet species selected seasonally was tested using Regression with Empirical Variable Selection. The results showed that overall Blackbucks consumed 30 plant species—six browse and 27 grass species. While wet season diet was less diverse (22 species) with higher dependency on principal diet Cyperus compressus (>40%) and Aeluropus lagopoides (24%), the dry season diet was more diverse (30) species, with decreased dependency on principal diet. Among 13 covariates belonging to climate, habitat, and grass dynamics tested against selection of top five major diet plants by Blackbucks, grass dynamics covariates alone entered as the predictors both in wet and dry seasons. While cover and green leaves of the grass were the most common predictors in the top-five diets selection during wet season, in dry season besides cover and green leaves, grass texture (hard and soft), also entered as the most common predictors. The entry of grass cover, a quantitative related measure, and texture and green condition of the grass, quality related measures, as the drivers indicate that diet selection by Blackbuck is not just a matter of grass quantity, but also its quality.
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Science and Engineering Research Board
Grant numbers Grant File. No. EMR/2016/001536
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