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Modelling the distribution and compositional variation of plant communities at the continental scale

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F18%3A00101496" target="_blank" >RIV/00216224:14310/18:00101496 - isvavai.cz</a>

  • Výsledek na webu

    <a href="https://dx.doi.org/10.1111/ddi.12736" target="_blank" >https://dx.doi.org/10.1111/ddi.12736</a>

  • DOI - Digital Object Identifier

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Modelling the distribution and compositional variation of plant communities at the continental scale

  • Popis výsledku v původním jazyce

    Aim: We investigate whether (1) environmental predictors allow to delineate the distribution of discrete community types at the continental scale and (2) how data completeness influences model generalization in relation to the compositional variation of the modelled entities. - Location: Europe. - Methods: We used comprehensive datasets of two community types of conservation concern in Europe: acidophilous beech forests and base-rich fens. We computed community distribution models (CDMs) calibrated with environmental predictors to predict the occurrence of both community types, evaluating geographical transferability, interpolation and extrapolation under different scenarios of sampling bias. We used generalized dissimilarity modelling (GDM) to assess the role of geographical and environmental drivers in compositional variation within the predicted distributions. - Results: For the two community types, CDMs computed for the whole study area provided good performance when evaluated by random cross-validation and external validation. Geographical transferability provided lower but relatively good performance, while model extrapolation performed poorly when compared with interpolation. Generalized dissimilarity modelling showed a predominant effect of geographical distance on compositional variation, complemented with the environmental predictors that also influenced habitat suitability. - Main conclusions: Correlative approaches typically used for modelling the distribution of individual species are also useful for delineating the potential area of occupancy of community types at the continental scale, when using consistent definitions of the modelled entity and high data completeness. The combination of CDMs with GDM further improves the understanding of diversity patterns of plant communities, providing spatially explicit information for mapping vegetation diversity and related habitat types at large scales.

  • Název v anglickém jazyce

    Modelling the distribution and compositional variation of plant communities at the continental scale

  • Popis výsledku anglicky

    Aim: We investigate whether (1) environmental predictors allow to delineate the distribution of discrete community types at the continental scale and (2) how data completeness influences model generalization in relation to the compositional variation of the modelled entities. - Location: Europe. - Methods: We used comprehensive datasets of two community types of conservation concern in Europe: acidophilous beech forests and base-rich fens. We computed community distribution models (CDMs) calibrated with environmental predictors to predict the occurrence of both community types, evaluating geographical transferability, interpolation and extrapolation under different scenarios of sampling bias. We used generalized dissimilarity modelling (GDM) to assess the role of geographical and environmental drivers in compositional variation within the predicted distributions. - Results: For the two community types, CDMs computed for the whole study area provided good performance when evaluated by random cross-validation and external validation. Geographical transferability provided lower but relatively good performance, while model extrapolation performed poorly when compared with interpolation. Generalized dissimilarity modelling showed a predominant effect of geographical distance on compositional variation, complemented with the environmental predictors that also influenced habitat suitability. - Main conclusions: Correlative approaches typically used for modelling the distribution of individual species are also useful for delineating the potential area of occupancy of community types at the continental scale, when using consistent definitions of the modelled entity and high data completeness. The combination of CDMs with GDM further improves the understanding of diversity patterns of plant communities, providing spatially explicit information for mapping vegetation diversity and related habitat types at large scales.

Klasifikace

  • Druh

    J<sub>imp</sub> - Článek v periodiku v databázi Web of Science

  • CEP obor

  • OECD FORD obor

    10611 - Plant sciences, botany

Návaznosti výsledku

  • Projekt

    <a href="/cs/project/GB14-36079G" target="_blank" >GB14-36079G: Centrum analýzy a syntézy rostlinné diverzity (PLADIAS)</a><br>

  • Návaznosti

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

Ostatní

  • Rok uplatnění

    2018

  • Kód důvěrnosti údajů

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

Údaje specifické pro druh výsledku

  • Název periodika

    Diversity and Distributions

  • ISSN

    1366-9516

  • e-ISSN

  • Svazek periodika

    24

  • Číslo periodika v rámci svazku

    7

  • Stát vydavatele periodika

    GB - Spojené království Velké Británie a Severního Irska

  • Počet stran výsledku

    13

  • Strana od-do

    978-990

  • Kód UT WoS článku

    000435934800010

  • EID výsledku v databázi Scopus

    2-s2.0-85048300217