Which bird traits most affect the goodness-of-fit of species distribution models?

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F24%3A97311" target="_blank" >RIV/60460709:41330/24:97311 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.ecolind.2023.111317" target="_blank" >http://dx.doi.org/10.1016/j.ecolind.2023.111317</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.ecolind.2023.111317" target="_blank" >10.1016/j.ecolind.2023.111317</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Which bird traits most affect the goodness-of-fit of species distribution models?

Popis výsledku v původním jazyce

Species distribution models (SDMs) are numerical tools that combine species occurrence (or abundance) data with environmental variables, to predict the species' distribution spatially. SDMs are increasingly used for purposes of conservation planning and management of ecosystems. The model performance can be measured as the goodness-of-fit (GOF), which describes how well it fits (e.g., the discrepancy between the statistical model and the data observed). However, there is still a need for a deeper understanding of the ecological characteristics of the modelled species which can affect the accuracy of those models. Here, we compared the goodness-of-fit of SDMs, considering several ecological characteristics of 56 bird species: Most frequently used environment, body mass, home-range, species specialization index (SSI), diet specialization and detectability. All SDMs were performed on the same dataset, and the relative frequency of each species was also incorporated to account for occurrence heterogeneity. GOF of SDMs was not significantly correlated with species' frequency, home-range, body mass, degree of detectability or level of diet specialization. Overall, the birds with more accurate SDMs (GOF) were species of grasslands and the GOF was positively associated with SSI, indicating that more habitatspecialized species are better predictable. Our findings suggest that is important to focus not only on statistical issues potentially related to model performance but also on ecological characteristics of single species because can improve the performance of modellistic procedures, increasing their predictive power.

Název v anglickém jazyce

Which bird traits most affect the goodness-of-fit of species distribution models?

Popis výsledku anglicky

Species distribution models (SDMs) are numerical tools that combine species occurrence (or abundance) data with environmental variables, to predict the species' distribution spatially. SDMs are increasingly used for purposes of conservation planning and management of ecosystems. The model performance can be measured as the goodness-of-fit (GOF), which describes how well it fits (e.g., the discrepancy between the statistical model and the data observed). However, there is still a need for a deeper understanding of the ecological characteristics of the modelled species which can affect the accuracy of those models. Here, we compared the goodness-of-fit of SDMs, considering several ecological characteristics of 56 bird species: Most frequently used environment, body mass, home-range, species specialization index (SSI), diet specialization and detectability. All SDMs were performed on the same dataset, and the relative frequency of each species was also incorporated to account for occurrence heterogeneity. GOF of SDMs was not significantly correlated with species' frequency, home-range, body mass, degree of detectability or level of diet specialization. Overall, the birds with more accurate SDMs (GOF) were species of grasslands and the GOF was positively associated with SSI, indicating that more habitatspecialized species are better predictable. Our findings suggest that is important to focus not only on statistical issues potentially related to model performance but also on ecological characteristics of single species because can improve the performance of modellistic procedures, increasing their predictive power.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

10619 - Biodiversity conservation

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2024

Kód důvěrnosti údajů

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

Název periodika

ECOLOGICAL INDICATORS

ISSN

1470-160X

e-ISSN

1470-160X

Svazek periodika

158

Číslo periodika v rámci svazku

111317

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

9

Strana od-do

1-9

Kód UT WoS článku

001125982600001

EID výsledku v databázi Scopus

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