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Utilizing the density of inventory samples to define a hybrid lattice for species distribution models: DISTRIB‐II for 135 eastern U.S. trees / Matthew P. Peters in Ecology and evolution, vol 9 n° 15 (August 2019)  

Public [article]  inEcology and evolution > vol 9 n° 15 (August 2019) . - pp 8876 - 8899 Titre : Utilizing the density of inventory samples to define a hybrid lattice for species distribution models: DISTRIB‐II for 135 eastern U.S. trees Type de document : Article/Communication Auteurs : Matthew P. Peters, Auteur ; Louis R. Iverson, Auteur ; Anantha M. Prasad, Auteur ; Stephen N. Matthews, Auteur Année de publication : 2019 Article en page(s) : pp 8876 - 8899 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] arbre (flore) [Termes IGN] densité [Termes IGN] distribution spatiale [Termes IGN] données météorologiques [Termes IGN] inventaire forestier étranger (données) [Termes IGN] modèle mathématique [Termes IGN] placette d'échantillonnage [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Species distribution models (SDMs) provide useful information about potential presence or absence, and environmental conditions suitable for a species; and high‐resolution models across large extents are desirable. A primary feature of SDMs is the underlying spatial resolution, which can be chosen for many reasons, though we propose that a hybrid lattice, in which grid cell sizes vary with the density of forest inventory plots, provides benefits over uniform grids. We examine how the spatial grain size affected overall model performance for the Random Forest‐based SDM, DISTRIB, which was updated with recent forest inventories, climate, and soil data, and used a hybrid lattice derived from inventory densities. Modeled habitat suitability was compared between a uniform grid of 10 × 10 and a hybrid lattice of 10 × 10 and 20 × 20 km grids to assess potential improvements. The resulting DISTRIB‐II models for 125 eastern U.S. tree species provide information on individual habitat suitability that can be mapped and statistically analyzed to understand current and potential changes. Model performance metrics were comparable among the hybrid lattice and 10‐km grids; however, the hybrid lattice models generally had higher overall model reliability scores and were likely more representative of the inventory data. Our efforts to update DISTRIB models with current information aims to produce a more representative depiction of recent conditions by accounting for the spatial density of forest inventory data and using the latest climate data. Additionally, we developed an approach that leverages a hybrid lattice to maximize the spatial information within the models and recommend that similar modeling efforts be used to evaluate the spatial density of response and predictor data and derive a modeling grid that best represents the environment. Numéro de notice : A2019-374 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1002/ece3.5445 Date de publication en ligne : 17/07/2019 En ligne : https://doi.org/10.1002/ece3.5445 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93415 [article]