Using ecological niche models to support tree species selection for forest restoration planning in largely deforested regions

Gastón González, Aitor y Garcia Viñas, Juan Ignacio (2011). Using ecological niche models to support tree species selection for forest restoration planning in largely deforested regions. En: "Restoring forests: advances in techniques and theory", 27/09/2011 - 29/09/2011, Madrid, España.

Descripción

Título: Using ecological niche models to support tree species selection for forest restoration planning in largely deforested regions
Autor/es:
  • Gastón González, Aitor
  • Garcia Viñas, Juan Ignacio
Tipo de Documento: Ponencia en Congreso o Jornada (Póster)
Título del Evento: Restoring forests: advances in techniques and theory
Fechas del Evento: 27/09/2011 - 29/09/2011
Lugar del Evento: Madrid, España
Título del Libro: Abstract book of Restoring forests: advances in techniques and theory
Fecha: 2011
Materias:
Escuela: E.U.I.T. Forestal (UPM) [antigua denominación]
Departamento: Producción Vegetal: Botánica y Protección Vegetal [hasta 2014]
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

Species selection for forest restoration is often supported by expert knowledge on local distribution patterns of native tree species. This approach is not applicable to largely deforested regions unless enough data on pre-human tree species distribution is available. In such regions, ecological niche models may provide essential information to support species selection in the framework of forest restoration planning. In this study we used ecological niche models to predict habitat suitability for native tree species in "Tierra de Campos" region, an almost totally deforested area of the Duero Basin (Spain). Previously available models provide habitat suitability predictions for dominant native tree species, but including non-dominant tree species in the forest restoration planning may be desirable to promote biodiversity, specially in largely deforested areas were near seed sources are not expected. We used the Forest Map of Spain as species occurrence data source to maximize the number of modeled tree species. Penalized logistic regression was used to train models using climate and lithological predictors. Using model predictions a set of tools were developed to support species selection in forest restoration planning. Model predictions were used to build ordered lists of suitable species for each cell of the study area. The suitable species lists were summarized drawing maps that showed the two most suitable species for each cell. Additionally, potential distribution maps of the suitable species for the study area were drawn. For a scenario with two dominant species, the models predicted a mixed forest (Quercus ilex and a coniferous tree species) for almost one half of the study area. According to the models, 22 non-dominant native tree species are suitable for the study area, with up to six suitable species per cell. The model predictions pointed to Crataegus monogyna, Juniperus communis, J.oxycedrus and J.phoenicea as the most suitable non-dominant native tree species in the study area. Our results encourage further use of ecological niche models for forest restoration planning in largely deforested regions.

Más información

ID de Registro: 11186
Identificador DC: http://oa.upm.es/11186/
Identificador OAI: oai:oa.upm.es:11186
Depositado por: Memoria Investigacion
Depositado el: 27 Jun 2012 10:47
Ultima Modificación: 20 Abr 2016 19:20
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