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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10618 - Ecology

Projekt

<a href="/cs/project/EF15_003%2F0000441" target="_blank" >EF15_003/0000441: Mechanismy a dynamika makromolekulárních komplexů</a><br>

Návaznosti

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

Rok uplatnění

2019

Kód důvěrnosti údajů

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

Název periodika

Ecology and Evolution

ISSN

2045-7758

e-ISSN

—

Svazek periodika

9

Číslo periodika v rámci svazku

15

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

14

Strana od-do

8541-8554

Kód UT WoS článku

000479278000011

EID výsledku v databázi Scopus

2-s2.0-85070460365