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Null model analyses of temporal patterns of bird assemblages and their foraging guilds revealed the predominance of positive and random associations

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12310%2F19%3A43899390" target="_blank" >RIV/60076658:12310/19:43899390 - isvavai.cz</a>

  • Result on the web

    <a href="https://onlinelibrary.wiley.com/doi/epdf/10.1002/ece3.5372" target="_blank" >https://onlinelibrary.wiley.com/doi/epdf/10.1002/ece3.5372</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1002/ece3.5372" target="_blank" >10.1002/ece3.5372</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Null model analyses of temporal patterns of bird assemblages and their foraging guilds revealed the predominance of positive and random associations

  • Original language description

    Patterns of species associations have been commonly used to infer interactions among species. If species positively co-occur, they may form predominantly neutral assemblages, and such patterns suggest a relatively weak role for compensatory dynamics. The main objective of this study was to test this prediction on temporal samples of bird assemblages (n = 19, 10-57 years) by the presence/absence and quantitative null models on assemblage and guild levels. These null model outcomes were further analyzed to evaluate the effects of various data set characteristics on the outcomes of the null models. The analysis of two binary null models in combination with three association indices revealed 20% with significant aggregations, 61% with random associations, and only 19% with significant segregations (n = 95 simulations). The results of the quantitative null model simulations detected more none-random associations: 61% aggregations, 6% random associations, and 33% segregations (n = 114 simulations). Similarly, quantitative analyses on guild levels showed 58% aggregations, 20% segregations, and 22% random associations (n = 450 simulations). Bayesian GLMs detected that the outcomes of the binary and quantitative null models applied to the assemblage analyses were significantly related to census plot size, whereas the outcomes of the quantitative analyses were also related to the mean population densities of species in the data matrices. In guild-level analyses, only 9% of the GLMs showed a significant influence of matrix properties (plot size, matrix size, species richness, and mean species population densities) on the null model outcomes. The results did not show the prevalence of negative associations that would have supported compensatory dynamics. Instead, we assume that a similar response of the majority of species to climate-driven and stochastic factors may be responsible for the revealed predominance of positive associations.

  • 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

    10618 - Ecology

Result continuities

  • Project

    <a href="/en/project/EF15_003%2F0000441" target="_blank" >EF15_003/0000441: Mechanisms and dynamics of macromolecular complexes</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2019

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Ecology and Evolution

  • ISSN

    2045-7758

  • e-ISSN

  • Volume of the periodical

    9

  • Issue of the periodical within the volume

    15

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    14

  • Pages from-to

    8541-8554

  • UT code for WoS article

    000479278000011

  • EID of the result in the Scopus database

    2-s2.0-85070460365