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

J 2018

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

DIVÍŠEK, Jan a Milan CHYTRÝ

Základní údaje

Originální název

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

Autoři

DIVÍŠEK, Jan (203 Česká republika, garant, domácí) a Milan CHYTRÝ (203 Česká republika, domácí)

Vydání

Ecological Indicators, Elsevier B.V. 2018, 1470-160X

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10611 Plant sciences, botany

Stát vydavatele

Nizozemské království

Utajení

není předmětem státního či obchodního tajemství

Odkazy

Odkaz na web vydavatele

Impakt faktor

Impact factor: 4.490

Kód RIV

RIV/00216224:14310/18:00100871

Organizační jednotka

Přírodovědecká fakulta

DOI

http://dx.doi.org/10.1016/j.ecolind.2017.11.005

UT WoS

000430760900079

Klíčová slova anglicky

Alpha diversity; Czech Republic; Diversity hotspots; Forests; Grasslands; Plant communities; Predictive modelling; Red List species

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 4. 1. 2019 16:47, prof. RNDr. Milan Chytrý, Ph.D.

Anotace

V originále

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.

Návaznosti

GB14-36079G, projekt VaV

Název: Centrum analýzy a syntézy rostlinné diverzity (PLADIAS) (Akronym: PLADIAS)

Investor: Grantová agentura ČR, Centrum analýzy a syntézy rostlinné diverzity

Přiložené soubory

Divisek_Chytry_2018_EcoInd.pdf

Požádat o autorskou verzi souboru

Citovat

DIVÍŠEK, Jan a Milan CHYTRÝ. High-resolution and large-extent mapping of plant species richness using vegetation-plot databases. 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.

@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.

Podrobný výpis o publikaci