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Fakultät für Biologie, Chemie und Geowissenschaften

Abteilung Mykologie: Prof. Dr. Gerhard Rambold

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Cáceres, M; Lücking, R; Rambold, G: Efficiency of sampling methods for accurate estimation of species richness of corticolous microlichens in the Atlantic rainforest of northeastern Brazil, Biodiversity and Conservation, 17(6), 1285–1301 (2008), doi:10.1007/s10531-008-9342-3
Abstract:
Three different sampling methods were compared with regard to accurate estimation of species richness of crustose and microfoliose lichens in Atlantic rainforest remnants of northeastern Brazil. Quantitative transect sampling yielded three times as many species as non-quantitative opportunistic sampling, even if the number of sampled phorophyte trees was higher on average for the latter method. Repetitive non-quantitative opportunistic sampling of a single site resulted in twice the number of species than one-time sampling, but only two thirds of the number recovered by means of quantitative transect sampling, even of the number of sampled phorophyte trees was highest for this method. The analysis showed that opportunistic sampling fails to detect rare, inconspicuous, sterile, and/or cryptic species, usually neglected or overlooked even by the experienced collector upon visual inspection in the field. On the other hand, quantitative sampling forces even the inexperienced collector to sample lichen thalli or pieces of bark which only after detailed morphological, anatomical, and chemical study in the laboratory reveal themselves as distinct species. Accordingly, of the 456 lichen species collected and identified across the 22 studied localities, no less than 76 were unique to the quantitatively sampled transect, and the lichen species sampled with this method had a significantly higher proportion of rare, inconspicuous, sterile, and/or cryptic species. It is also apparent that it is not the higher number of specimens collected via quantitative sampling that results in a higher number of species, but the method of selection of the specimens, which is subjective and biased towards abundant, conspicuous, fertile and/or distinctive species in opportunistic sampling, but objective and unbiased in quantitative sampling.
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