Assessing vegetation change using vegetation-plot databases: a risky business

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Authors

CHYTRÝ Milan TICHÝ Lubomír HENNEKENS Stephan M SCHAMINÉE Joop H J

Year of publication 2014
Type Article in Periodical
Magazine / Source Applied Vegetation Science
MU Faculty or unit

Faculty of Science

Citation
Web http://onlinelibrary.wiley.com/doi/10.1111/avsc.12050/abstract
Doi http://dx.doi.org/10.1111/avsc.12050
Field Ecology
Keywords Permanent plot; Phytosociological database; Plant community; Releve; Revisitation study; Sampling bias; Species composition; Temporal trend
Description Aim: Data from vegetation plots can be used for the assessment of past vegetation change in three ways: (1) comparison of old and new records from permanent plots established for vegetation monitoring; (2) revisiting historical phytosociological plots and subsequent comparison of old and new records; (3) comparison of large sets of old and new phytosociological records from the same area but different plots. Option (3) would be the cheapest in regions where large vegetation-plot databases are available, but there is a risk of incorrect results due to a spatial mismatch of old and new plots. Here we assess the accuracy of such analyses. Methods: We used three data sets of permanent plots from Czech mountain bogs and Dutch oak forests and heathlands to quantify vegetation change. We selected subsets to simulate analyses based on (1) data from permanent plots or revisited phytosociological plots, i.e. containing old and new records from the same plots, (2) vegetation-plot databases with old and new records from different, randomly selected sites, and (3) vegetation-plot databases with old and new records from different but close sites. We repeated each subset selection 1000 times and analysed vegetation change in each of the three data sets and each variant of subset selection using permutational multivariate analysis of variance. Results: For data sets with no actual vegetation change, analyses of some subsets simulating vegetation-plot databases incorrectly suggested significant changes. For a data set with real change, a change was detected in analyses of simulated vegetation-plot databases, but in several cases it had a different direction or magnitude to the real change. Conclusions: The assessment of vegetation change using vegetation-plot databases should be either avoided or interpreted with extreme caution because of the risk of incorrect results. Analyses such as these may be used to propose hypotheses about past vegetation change, but their results should not be considered valid unless confirmed using more reliable data. In many contexts, re-visitation studies of historical phytosociological plots may be the best strategy to assess past vegetation change, while new networks of carefully stratified permanent plots are preferable for monitoring future change.
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