High-resolution and large-extent mapping of plant species richness using vegetation-plot databases

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F18%3A00100871" target="_blank" >RIV/00216224:14310/18:00100871 - isvavai.cz</a>

Result on the web

<a href="https://www.sciencedirect.com/science/article/pii/S1470160X17307173" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1470160X17307173</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.ecolind.2017.11.005" target="_blank" >10.1016/j.ecolind.2017.11.005</a>

Result language

angličtina

Original language name

High-resolution and large-extent mapping of plant species richness using vegetation-plot databases

Original language description

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.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10611 - Plant sciences, botany

Project

<a href="/en/project/GB14-36079G" target="_blank" >GB14-36079G: Plant diversity analysis and synthesis centre (PLADIAS)</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2018

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Ecological Indicators

ISSN

1470-160X

e-ISSN

—

Volume of the periodical

89

Issue of the periodical within the volume

June

Country of publishing house

NL - THE KINGDOM OF THE NETHERLANDS

Number of pages

12

Pages from-to

840-851

UT code for WoS article

000430760900079

EID of the result in the Scopus database

2-s2.0-85042376363