BACKGROUND: Resurveying historical vegetation plots has become more and more popular in recent years as it provides a unique opportunity to estimate vegetation and environmental changes over the past decades. Most historical plots, however, are not permanently marked and uncertainty in plot location, in addition to observer bias and seasonal bias, may add significant error to temporal change. These errors may have major implications for the reliability of studies on long-term environmental change and deserve closer attention of vegetation ecologists. MATERIAL & METHODS: Vegetation data obtained from the resurveying of non-permanently marked plots are assessed for their potential to study environmental-change effects on plant communities and the challenges the use of such data have to meet. We describe the properties of vegetation resurveys distinguishing basic types of plots according to relocation error, and we highlight the potential of such data types for studying vegetation dynamics and their drivers. Finally, we summarise the challenges and limitations of resurveying non-permanently marked vegetation plots for different purposes in environmental change research. RESULTS AND CONCLUSIONS: Resampling 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) keep a high level of experience of the observers to keep observer bias low; and (v) edit and standardise datasets before analyses.

Department of Biology University of Bergen Thormøhlensgate 53A 5020 Bergen Norway

Department of Botany Palacký University Šlechtitelů 27 78371 Olomouc Czech Republic

Department of Forest Ecology Faculty of Forestry and Wood Sciences Czech University of Life Sciences Prague Kamýcká 129 CZ 165 21 Praha 6 Suchdol Czech Republic

Institute of Botany The Czech Academy of Sciences Lidická 25 27 60200 Brno Czech Republic

Landscape Ecology and Site Evaluation University of Rostock 18059 Rostock Germany

Norwegian Institute of Bioeconomy Research Fanaflaten 4 5244 Fana Norway

Norwegian Institute of Bioeconomy Research Holtveien 66 9016 Tromsø Norway

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