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Disentangling spatial and environmental effects: Flexible methods for community ecology and macroecology

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F22%3A91602" target="_blank" >RIV/60460709:41330/22:91602 - isvavai.cz</a>

  • Result on the web

    <a href="https://esajournals.onlinelibrary.wiley.com/doi/full/10.1002/ecs2.4028" target="_blank" >https://esajournals.onlinelibrary.wiley.com/doi/full/10.1002/ecs2.4028</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1002/ecs2.4028" target="_blank" >10.1002/ecs2.4028</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Disentangling spatial and environmental effects: Flexible methods for community ecology and macroecology

  • Original language description

    Community ecologists and macroecologists have long sought to evaluate the importance of environmental conditions in determining species distributions, community composition, and diversity across sites. Different methods have been used to estimate species environment relationships, but their differences to jointly fit and disentangle spatial autocorrelation and structure remain poorly studied. We compared how methods in four broad families of statistical models estimated the contribution of the environment and space to variation in species occurrence and abundance. These methods included redundancy analysis (RDA), generalized linear models (GLMs), generalized additive models (GAMs), and three types of tree based machine learning (ML) methods: boosted regression trees (BRT), random forests, and regression trees. The spatial component of the model consisted of Morans eigenvector maps (MEMs in RDA, GLM, and ML), smooth spatial splines (in GAM), or tree based nonlinear modeling of spatial coordinates (in

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10511 - Environmental sciences (social aspects to be 5.7)

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2022

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Ecosphere

  • ISSN

    2150-8925

  • e-ISSN

    2150-8925

  • Volume of the periodical

    13

  • Issue of the periodical within the volume

    4

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    16

  • Pages from-to

    1-16

  • UT code for WoS article

    000787139500001

  • EID of the result in the Scopus database

    2-s2.0-85128903784