Resurveying historical vegetation data – opportunities and challenges

0477575 - BÚ 2018 RIV GB eng J - Journal Article
Kapfer, J. - Hédl, Radim - Jurasinski, G. - Kopecký, Martin - Schei, F. H. - Grytnes, J.-A.
Resurveying historical vegetation data – opportunities and challenges.
Applied vegetation science. Roč. 20, č. 2 (2017), s. 164-171. ISSN 1402-2001. E-ISSN 1654-109X
EU Projects: European Commission(XE) 278065 - LONGWOOD
Institutional support: RVO:67985939
Keywords : environmental change * long-term vegetation dynamics * vegetation resampling
OECD category: Ecology
Impact factor: 2.331, year: 2017

Re-sampling error is caused by three main independent sources of error: error caused by plot relocation, observer bias and seasonality bias. For relocation error, vegetation plots can be divided into permanent and non-permanent plots, while the latter are further divided into quasi-permanent (with approximate relocation) and non-traceable (with random relocation within a sampled area) plots. To reduce the inherent sources of error in resurvey data, the following precautions should be followed: (i) resurvey historical vegetation plots whose approximate plot location within a study area is known, (ii) consider all information available from historical studies in order to keep plot relocation errors low, (iii) resurvey at times of the year when vegetation development is comparable to the historical survey to control for seasonal variability in vegetation, (iv) retain a high level of experience of the observers to keep observer bias low, and (v) edit and standardize data sets before analyses.
Permanent Link: http://hdl.handle.net/11104/0277137