Downscaling of species distribution models: a hierarchical approach

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11620%2F13%3A10188930" target="_blank" >RIV/00216208:11620/13:10188930 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1111/j.2041-210x.2012.00264.x" target="_blank" >http://dx.doi.org/10.1111/j.2041-210x.2012.00264.x</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1111/j.2041-210x.2012.00264.x" target="_blank" >10.1111/j.2041-210x.2012.00264.x</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Downscaling of species distribution models: a hierarchical approach

Popis výsledku v původním jazyce

1. Reliable methods to downscale species distributions from coarse to fine grain hold great potential benefit for ecology and conservation. Existing methods have been based on partially unrealistic assumptions and yield mixed results. 2. We introduce a novel and simple approach for downscaling species distribution models based on a hierarchical modelling framework. Our approach treats unknown fine-grain presences/absences as latent variables, which are modelled as a function of observed fine-grain environmental variables and constrained by observed coarse-grain presences/absences using logistic regression. The aim is to produce downscaled distributions that (1) closely resemble the probabilities produced by a logistic model parameterized with the observed fine-grain data (the 'reference model') and (2) are improvements over conventional downscaling methods. We additionally test how fine-grain occupancy based on power-law scale-area relationships modifies the downscaling results. We tes

Název v anglickém jazyce

Downscaling of species distribution models: a hierarchical approach

Popis výsledku anglicky

1. Reliable methods to downscale species distributions from coarse to fine grain hold great potential benefit for ecology and conservation. Existing methods have been based on partially unrealistic assumptions and yield mixed results. 2. We introduce a novel and simple approach for downscaling species distribution models based on a hierarchical modelling framework. Our approach treats unknown fine-grain presences/absences as latent variables, which are modelled as a function of observed fine-grain environmental variables and constrained by observed coarse-grain presences/absences using logistic regression. The aim is to produce downscaled distributions that (1) closely resemble the probabilities produced by a logistic model parameterized with the observed fine-grain data (the 'reference model') and (2) are improvements over conventional downscaling methods. We additionally test how fine-grain occupancy based on power-law scale-area relationships modifies the downscaling results. We tes

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

EH - Ekologie – společenstva

OECD FORD obor

—

Projekt

—

Návaznosti

R - Projekt Ramcoveho programu EK

Rok uplatnění

2013

Kód důvěrnosti údajů

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

Název periodika

Methods in Ecology and Evolution

ISSN

2041-210X

e-ISSN

—

Svazek periodika

4

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

13

Strana od-do

82-94

Kód UT WoS článku

000313993600010

EID výsledku v databázi Scopus

—