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@article{1412157,
author = {Divíšek, Jan and Chytrý, Milan},
article_number = {June},
doi = {http://dx.doi.org/10.1016/j.ecolind.2017.11.005},
keywords = {Alpha diversity; Czech Republic; Diversity hotspots; Forests; Grasslands; Plant communities; Predictive modelling; Red List species},
language = {eng},
issn = {1470-160X},
journal = {Ecological Indicators},
title = {High-resolution and large-extent mapping of plant species richness using vegetation-plot databases},
url = {https://www.sciencedirect.com/science/article/pii/S1470160X17307173},
volume = {89},
year = {2018}
}
TY - JOUR
ID - 1412157
AU - Divíšek, Jan - Chytrý, Milan
PY - 2018
TI - High-resolution and large-extent mapping of plant species richness using vegetation-plot databases
JF - Ecological Indicators
VL - 89
IS - June
SP - 840-851
EP - 840-851
PB - Elsevier B.V.
SN - 1470160X
KW - Alpha diversity
KW - Czech Republic
KW - Diversity hotspots
KW - Forests
KW - Grasslands
KW - Plant communities
KW - Predictive modelling
KW - Red List species
UR - https://www.sciencedirect.com/science/article/pii/S1470160X17307173
L2 - https://www.sciencedirect.com/science/article/pii/S1470160X17307173
N2 - The recent increase in the availability of large vegetation-plot databases has created unprecedented opportunities for analysing and explaining patterns of fine-scale plant species richness across large areas and for individual habitat types. Here we demonstrate how these data can be used to (1) prepare country-wide high-resolution maps of species richness and identify national diversity hotspots for grassland and forest vegetation; (2) compare diversity patterns of all, native, alien and Red List species; and (3) identify potential environmental drivers of these patterns. At the same time we examine and quantify the stability of predicted species-richness patterns with respect to the most common biases that are inherent to large vegetation-plot databases. Vegetation-plot records were obtained from the Czech National Phytosociological Database and the Random Forest method was used to map fine-scale spatial diversity patterns of all, native, alien and Red List vascular plant species, separately for grasslands and forests across the Czech Republic. The stability of the predicted species-richness patterns was tested using differently resampled datasets in which we either reduced or increased local oversampling and preferential sampling of more species-rich communities. Models for grassland and forest vegetation explained 40–65% of variation in fine-scale species richness. Spatial patterns of all and native species richness differed considerably between grasslands and forests, whereas alien and Red List species showed a higher congruence between these two vegetation types. Patterns of modelled species richness were highly stable with respect to all resampling strategies applied to the initial datasets. We conclude that vegetation-plot databases are a valuable source of data for high-resolution mapping of the plant species richness of different vegetation types and species groups, because each of them can exhibit a different diversity pattern. The resulting maps provide robust representation of the spatial patterns of fine-scale species richness and can be used both for testing scientific hypotheses about the controls of diversity patterns and for conservation planning.
ER -
DIVÍŠEK, Jan a Milan CHYTRÝ. High-resolution and large-extent mapping of plant species richness using vegetation-plot databases. \textit{Ecological Indicators}. Elsevier B.V., 2018, roč.~89, June, s.~840-851. ISSN~1470-160X. Dostupné z: https://dx.doi.org/10.1016/j.ecolind.2017.11.005.
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