DE BELLO, Francesco, Pavel FIBICH, David ZELENÝ, Martin KOPECKÝ, Ondřej MUDRÁK, Milan CHYTRÝ, Petr PYŠEK, Jan WILD, Dana HOLUBOVÁ, Jiří SÁDLO, Petr ŠMILAUER, Jan LEPŠ and Meelis PÄRTEL. Measuring size and composition of species pools: a comparison of dark diversity estimates. Ecology and Evolution. Wiley, 2016, vol. 6, No 12, p. 4088-4101. ISSN 2045-7758. Available from: https://dx.doi.org/10.1002/ece3.2169.
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Basic information
Original name Measuring size and composition of species pools: a comparison of dark diversity estimates
Authors DE BELLO, Francesco (380 Italy), Pavel FIBICH (203 Czech Republic), David ZELENÝ (203 Czech Republic, belonging to the institution), Martin KOPECKÝ (203 Czech Republic), Ondřej MUDRÁK (203 Czech Republic), Milan CHYTRÝ (203 Czech Republic, guarantor, belonging to the institution), Petr PYŠEK (203 Czech Republic), Jan WILD (203 Czech Republic), Dana HOLUBOVÁ (203 Czech Republic, belonging to the institution), Jiří SÁDLO (203 Czech Republic), Petr ŠMILAUER (203 Czech Republic), Jan LEPŠ (203 Czech Republic) and Meelis PÄRTEL (233 Estonia).
Edition Ecology and Evolution, Wiley, 2016, 2045-7758.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 10600 1.6 Biological sciences
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
WWW URL
Impact factor Impact factor: 2.440
RIV identification code RIV/00216224:14310/16:00088319
Organization unit Faculty of Science
Doi http://dx.doi.org/10.1002/ece3.2169
UT WoS 000379342900020
Keywords in English Beals smoothing; biodiversity monitoring; Biomod; dark diversity; Ellenberg indicator values; method comparison; species distribution modeling
Tags AKR, rivok
Tags International impact, Reviewed
Changed by Changed by: Mgr. Lucie Jarošová, DiS., učo 205746. Changed: 13/3/2018 10:25.
Abstract
Ecological theory and biodiversity conservation have traditionally relied on the number of species recorded at a site, but it is agreed that site richness represents only a portion of the species that can inhabit particular ecological conditions, that is, the habitat-specific species pool. Knowledge of the species pool at different sites enables meaningful comparisons of biodiversity and provides insights into processes of biodiversity formation. Empirical studies, however, are limited due to conceptual and methodological difficulties in determining both the size and composition of the absent part of species pools, the so-called dark diversity. We used >50,000 vegetation plots from 18 types of habitats throughout the Czech Republic, most of which served as a training dataset and 1083 as a subset of test sites. These data were used to compare predicted results from three quantitative methods with those of previously published expert estimates based on species habitat preferences: (1) species co-occurrence based on Beals’ smoothing approach; (2) species ecological requirements, with envelopes around community mean Ellenberg values; and (3) species distribution models, using species environmental niches modeled by Biomod software. Dark diversity estimates were compared at both plot and habitat levels, and each method was applied in different configurations. While there were some differences in the results obtained by different methods, particularly at the plot level, there was a clear convergence, especially at the habitat level. The better convergence at the habitat level reflects less variation in local environmental conditions, whereas variation at the plot level is an effect of each particular method. The co-occurrence agreed closest the expert estimate, followed by the method based on species ecological requirements. We conclude that several analytical methods can estimate species pools of given habitats. However, the strengths and weaknesses of different methods need attention, especially when dark diversity is estimated at the plot level.
Links
GB14-36079G, research and development projectName: Centrum analýzy a syntézy rostlinné diverzity (PLADIAS) (Acronym: PLADIAS)
Investor: Czech Science Foundation
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