CHYTRÝ, Milan, Lubomír TICHÝ, Stephan M HENNEKENS a Joop H J SCHAMINÉE. Assessing vegetation change using vegetation-plot databases: a risky business. Applied Vegetation Science. Wiley, roč. 17, č. 1, s. 32-41. ISSN 1402-2001. doi:10.1111/avsc.12050. 2014.
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Základní údaje
Originální název Assessing vegetation change using vegetation-plot databases: a risky business
Autoři CHYTRÝ, Milan (203 Česká republika, garant, domácí), Lubomír TICHÝ (203 Česká republika, domácí), Stephan M HENNEKENS (528 Nizozemské království) a Joop H J SCHAMINÉE (528 Nizozemské království).
Vydání Applied Vegetation Science, Wiley, 2014, 1402-2001.
Další údaje
Originální jazyk angličtina
Typ výsledku Článek v odborném periodiku
Obor 10600 1.6 Biological sciences
Stát vydavatele Spojené státy
Utajení není předmětem státního či obchodního tajemství
WWW URL
Impakt faktor Impact factor: 2.548
Kód RIV RIV/00216224:14310/14:00073527
Organizační jednotka Přírodovědecká fakulta
Doi http://dx.doi.org/10.1111/avsc.12050
UT WoS 000328544400005
Klíčová slova anglicky Permanent plot; Phytosociological database; Plant community; Releve; Revisitation study; Sampling bias; Species composition; Temporal trend
Štítky AKR, rivok
Příznaky Mezinárodní význam, Recenzováno
Změnil Změnila: Mgr. Lucie Jarošová, DiS., učo 205746. Změněno: 13. 3. 2018 10:47.
Anotace
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.
Návaznosti
GAP505/11/0732, projekt VaVNázev: Zobecněná řízená klasifikace v ekologii společenstev
Investor: Grantová agentura ČR, Generalized supervised classification in community ecology
VytisknoutZobrazeno: 18. 4. 2024 22:53