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Evaluating the sampling bias in pattern of subterranean species richness: combining approaches
Authors:Maja Zagmajster  David C Culver  Mary C Christman  Boris Sket
Institution:(1) Oddelek za biologijo, Biotehniška fakulteta, Univerza v Ljubljani, Večna pot 111, p.p. 2995, 1000 Ljubljana, Slovenia;(2) Department of Environmental Science, American University, 4400 Massachusetts Ave, NW, Washington, DC, 20016, USA;(3) Department of Statistics—IFAS, University of Florida, PO Box 110339, Gainesville, FL 32611-0339, USA
Abstract:We investigated the pattern of species richness of obligate subterranean (troglobiotic) beetles in caves in the northwestern Balkans, given unequal and biased sampling. On the regional scale, we modeled the relationship between species numbers and sampling intensity using an asymptotic Clench (Michaelis–Menten) function. On the local scale, we calculated Chao 2 species richness estimates for 20 × 20 km grid cells, and investigated the distribution of uniques, species found in only one cave within the grid cell. Cells having high positive residuals, those with above average species richness than expected according to the Clench function, can be considered true hotspots. They were nearly identical to the observed areas of highest species richness. As sampling intensity in a grid cell increases the expected number of uniques decreases for any fixed number of species in the grid cell. High positive residuals show above average species richness for a certain level of sampling intensity within a cell, so further sampling has the most potential for additional species. In some cells this was supported by high numbers of uniques, also indicating insufficient sampling. Cells with low negative residuals have fewer species than would be expected, and some of them also had a low number of uniques, both indicating sufficient sampling. By combining different analyses in a novel way we were able to evaluate observed species richness pattern as well as identify, where further sampling would be most beneficial. Approach we demonstrate is of broad interest to study of biota with high levels of endemism, small distribution ranges and low catchability.
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