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Memorias de investigación
Artículos en revistas:
Modelling bird species richness with neural networks for forest landscape management in NE Spain
Año:2010
Áreas de investigación
  • Monte
Datos
Descripción
For preserving biodiversity of European-Mediterranean forest ecosystems in current and future scenarios of global change by means of sustainable forest management it is necessary to determine how environment and forest characteristics correlate with biodiversity. For this purpose, neural networks were used to model forest bird species richness as a function of environment and forest structure and composition at the 1 × 1 km scale in Catalonia (NE Spain). Univariate and multivariate models respectively allowed exploring individual variable response and obtaining a parsimonious (ecologically meaningful) and accurate neural network. Forest area (with a canopy cover above 5%), mean forest canopy cover, mean annual temperature and summer precipitation were the best predictors of forest bird species richness. The resultant multivariate network had a good generalization capacity that failed however in the locations with highest species richness. Additionally, those forests with different degrees of canopy closure that were more mature and presented a more diverse tree species composition were also associated with higher bird species richness. This allowed us to provide management guidelines for forest planning in order to promote avian diversity in this European-Mediterranean region
Internacional
Si
JCR del ISI
Si
Título de la revista
Investigacion Agraria-Sistemas y Recursos Forestales
ISSN
1131-7965
Factor de impacto JCR
0,558
Información de impacto
Volumen
19
DOI
Número de revista
Desde la página
113
Hasta la página
125
Mes
ENERO
Ranking
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Santiago Fulgencio Saura Martinez de Toda (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Economía y Sostenibilidad del Medio Natural
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