Predicting species occurrences with habitat network models.

Détails

Ressource 1Télécharger: 31624560_BIB_E55AC555673F.pdf (1974.00 [Ko])
Etat: Public
Version: Final published version
Licence: CC BY 4.0
ID Serval
serval:BIB_E55AC555673F
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Predicting species occurrences with habitat network models.
Périodique
Ecology and evolution
Auteur⸱e⸱s
Ortiz-Rodríguez D.O., Guisan A., Holderegger R., van Strien M.J.
ISSN
2045-7758 (Print)
ISSN-L
2045-7758
Statut éditorial
Publié
Date de publication
09/2019
Peer-reviewed
Oui
Volume
9
Numéro
18
Pages
10457-10471
Langue
anglais
Notes
Publication types: Journal Article
Publication Status: epublish
Résumé
Biodiversity conservation requires modeling tools capable of predicting the presence or absence (i.e., occurrence-state) of species in habitat patches. Local habitat characteristics of a patch (lh), the cost of traversing the landscape matrix between patches (weighted connectivity [wc]), and the position of the patch in the habitat network topology (nt) all influence occurrence-state. Existing models are data demanding or consider only local habitat characteristics. We address these shortcomings and present a network-based modeling approach, which aims to predict species occurrence-state in habitat patches using readily available presence-only records.For the tree frog Hyla arborea in the Swiss Plateau, we delineated habitat network nodes from an ensemble habitat suitability model and used different cost surfaces to generate the edges of three networks: one limited only by dispersal distance (Uniform), another incorporating traffic, and a third based on inverse habitat suitability. For each network, we calculated explanatory variables representing the three categories (lh, wc, and nt). The response variable, occurrence-state, was parametrized by a sampling intensity procedure assessing observations of comparable species over a threshold of patch visits. The explanatory variables from the three networks and an additional non-topological model were related to the response variable with boosted regression trees.The habitat network models had a similar fit; they all outperformed the non-topological model. Habitat suitability index (lh) was the most important predictor in all networks, followed by third-order neighborhood (nt). Patch size (lh) was unimportant in all three networks.We found that topological variables of habitat networks are relevant for the prediction of species occurrence-state, a step-forward from models considering only local habitat characteristics. For any habitat patch, occurrence-state is most prominently influenced by its habitat suitability and then by the number of patches in a wide neighborhood. Our approach is generic and can be applied to multiple species in different habitats.
Mots-clé
Cost surface, connectivity, habitat network, habitat suitability, network topology, species occurrence, connectivity, cost surface, habitat network, habitat suitability, network topology, species occurrence
Pubmed
Open Access
Oui
Création de la notice
13/07/2019 0:47
Dernière modification de la notice
30/04/2021 7:15
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