Habitats as predictors in species distribution models: Shall we use continuous or binary data?

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F22%3A91594" target="_blank" >RIV/60460709:41330/22:91594 - isvavai.cz</a>

Výsledek na webu

<a href="https://onlinelibrary.wiley.com/doi/10.1111/ecog.06022" target="_blank" >https://onlinelibrary.wiley.com/doi/10.1111/ecog.06022</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1111/ecog.06022" target="_blank" >10.1111/ecog.06022</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Habitats as predictors in species distribution models: Shall we use continuous or binary data?

Popis výsledku v původním jazyce

The representation of a land cover type (i.e. habitat) within an area is often used as an explanatory variable in species distribution models. However, it is possible that a simple binary presenceabsence of the suitable habitat might be the most important determinant of the presenceabsence of some species and, thus, be a better predictor of species occurrence than the continuous parameter (area). We hypothesize that the binary predictor is more suitable for relatively rare habitats (e.g. wetlands) while for common habitats (e.g. forests) the amount of the focal habitat is a better predictor. We used the Third Atlas of Breeding Birds in the Czech Republic as the source of species distribution data and CORINE Land Cover inventory as the source of the landcover information. To test our hypothesis, we fitted generalized linear models of 32 water and 32 forest bird species. Our results show that for water bird species, models using binary predictors (presence/absence of the habitat) performed better than

Název v anglickém jazyce

Habitats as predictors in species distribution models: Shall we use continuous or binary data?

Popis výsledku anglicky

The representation of a land cover type (i.e. habitat) within an area is often used as an explanatory variable in species distribution models. However, it is possible that a simple binary presenceabsence of the suitable habitat might be the most important determinant of the presenceabsence of some species and, thus, be a better predictor of species occurrence than the continuous parameter (area). We hypothesize that the binary predictor is more suitable for relatively rare habitats (e.g. wetlands) while for common habitats (e.g. forests) the amount of the focal habitat is a better predictor. We used the Third Atlas of Breeding Birds in the Czech Republic as the source of species distribution data and CORINE Land Cover inventory as the source of the landcover information. To test our hypothesis, we fitted generalized linear models of 32 water and 32 forest bird species. Our results show that for water bird species, models using binary predictors (presence/absence of the habitat) performed better than

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10619 - Biodiversity conservation

Projekt

<a href="/cs/project/SS02030018" target="_blank" >SS02030018: Centrum pro krajinu a biodiverzitu</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název periodika

Ecography

ISSN

0906-7590

e-ISSN

1600-0587

Svazek periodika

2022

Číslo periodika v rámci svazku

7

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

9

Strana od-do

1-9

Kód UT WoS článku

000782391400001

EID výsledku v databázi Scopus

2-s2.0-85128222211