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Reproducibility of species lists, visual cover estimates and frequency methods for recording high‐mountain vegetation
Author(s) -
Vittoz Pascal,
Bayfield Neil,
Brooker Rob,
Elston David A.,
Duff Elizabeth I.,
Theurillat JeanPaul,
Guisan Antoine
Publication year - 2010
Publication title -
journal of vegetation science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 115
eISSN - 1654-1103
pISSN - 1100-9233
DOI - 10.1111/j.1654-1103.2010.01216.x
Subject(s) - quadrat , summit , vegetation (pathology) , lichen , physical geography , ecology , variation (astronomy) , geography , environmental science , biology , transect , medicine , pathology , physics , astrophysics
Question: When multiple observers record the same spatial units of alpine vegetation, how much variation is there in the records and what are the consequences of this variation for monitoring schemes to detect changes? Location: One test summit in Switzerland (Alps) and one test summit in Scotland (Cairngorm Mountains). Method: Eight observers used the GLORIA protocols for species composition and visual cover estimates in percentages on large summit sections (>100 m 2 ) and species composition and frequency in nested quadrats (1 m 2 ). Results: The multiple records from the same spatial unit for species composition and species cover showed considerable variation in the two countries. Estimates of pseudo‐turnover of composition and coefficients of variation of cover estimates for vascular plant species in 1 m × 1‐m quadrats showed less variation than in previously published reports, whereas our results in larger sections were broadly in line with previous reports. In Scotland, estimates for bryophytes and lichens were more variable than for vascular plants. Conclusions: Statistical power calculations indicated that unless large numbers of plots were used, changes in cover or frequency were only likely to be detected for abundant species (exceeding 10% cover) or if relative changes were large (50% or more). Lower variation could be reached with the point method and with larger numbers of small plots. However, as summits often strongly differ from each other, supplementary summits cannot be considered as a way of increasing statistical power without introducing a supplementary component of variance into the analysis and hence into the power calculations.