A spatial distribution model of cork oak (Quercus suber) in southwestern Spain: A suitable tool for reforestation
Title | A spatial distribution model of cork oak (Quercus suber) in southwestern Spain: A suitable tool for reforestation |
Publication Type | Journal Article |
Year of Publication | 2008 |
Authors | Hidalgo, P. J., Marín J. M., Quijada J., & Moreira J. M. |
Journal | Forest Ecology and Management |
Volume | 255 |
Pagination | 25-34 |
Keywords | binary logistic regression, climatic modeling, Cork oak, Quercus suber, Reforestation, spatial analysis |
Abstract | Cork oak (Quercus suber) is an evergreen tree characterized by a thick bark, which grows in Mediterranean schlerophyllous forests. It is most prevalent in the southwestern Iberian Peninsula. Despite the potential of the province of Huelva (southwestern Spain) to maintain mature forests of cork oak, the tree has been severely depleted and most forests have either disappeared or are seriously threatened. This paper presents a spatial distribution model of cork oak for the province of Huelva with a view to determining the optimal areas for reforestation. The model draws on all available digital cartographic information with respect to cork oak distribution: topographic data (altitude, slope and orientation) were obtained from a Digital Terrain Model (20 m scale); rainfall, temperature and PET models were based on data collected from a network of meteorological stations; litologic data derive from the litologic map of Huelva (1:100,000). The result of this work is a mesh of points at a resolution of 100 m, sufficient to meet the needs of any kind of reforestation or management programmes in the area studied. Each point of this mesh contains the corresponding values for bioclimatic, topographic and litologic variables in a georeferenced data matrix. The independent variables responsible for cork oak distribution (binary dependent variables) were then identified by means of binary logistic regression analysis. North-facing slopes, abundant annual rainfall and litology were the main explaining variables. The spatial distribution model was produced by applying the formula obtained to spatial analysis software. This model is proposed as a basis for future reforestation plans, especially in those areas most affected by forest fires. |