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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Research@WURarrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Research@WUR
Article . 2014
Data sources: Research@WUR
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Applied Vegetation Science
Article . 2013 . Peer-reviewed
License: Wiley Online Library User Agreement
Data sources: Crossref
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Assessing vegetation change using vegetation‐plot databases: a risky business

Authors: Chytry, M.; Tichý, L.; Hennekens, S.M.; Schaminee, J.H.J.;

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

Abstract

AbstractAimData 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.MethodsWe 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.ResultsFor 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.ConclusionsThe 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.

Country
Netherlands
Related Organizations
Keywords

forests, index, decades, long-term changes, phytosociological databases, plant-communities, netherlands, drivers, grassland, species richness

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
90
Top 1%
Top 10%
Top 10%
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