Multivariate effect gradients driving forest demographic responses in the Iberian Peninsula - Coll, Marta; Penuelas, Josep; Ninyerola, Miquel; Pons, Xavier; Carnicer, Jofre (Forest Ecology and Management, 2013)
A precise knowledge of forest demographic gradients in the Mediterranean area is essential to assess future impacts of climate change and extreme drought events. Here we studied the geographical patterns of forest demography variables (tree recruitment, growth and mortality) of the main species in Spain and assessed their multiple ecological drivers (climate, topography, soil, forest stand attributes and tree-spe- cific traits) as well as the geographical variability of their effects and interactions. Quantile modeling analyses allowed a synthetic description of the gradients of multiple covariates influencing forest demog- raphy in this area. These multivariate effect gradients showed significantly stronger interactions at the extremes of the rainfall gradient. Remarkably, in all demographic variables, qualitatively different levels of effects and interactions were observed across tree-size classes. In addition, significant differences in demographic responses and effect gradients were also evident between the dominant genus Quercus and Pinus. Quercus species presented significantly higher percentage of plots colonized by new recruits, whereas in Pinus recruitment limitation was significantly higher. Contrasting positive and negative growth responses to temperature were also observed in Quercus and Pinus, respectively. Overall, our results synthesize forest demographic responses across climatic gradients in Spain, and unveil the inter- actions between driving factors operating in the drier and wetter edges.
The following values have no corresponding Zotero field: publisher: Elsevier B.V.
Keywords: Forest demography; Growth; Macroecology; mortality; Quantile modeling; Recruitment

On the applicability of Landsat TM images to Mediterranean forest inventories - Salvador, Raymond; Pons, Xavier (Forest Ecology and Management, 1998)
Landsat TM images were used in combination with field measurements to create models for Mediterranean forests. Radiometric data from those images were related to field data from a forest inventory by means of regression analysis. Trials using plots with radiometrically homogeneous surroundings were carried out to evaluate the effect of high spatial heterogeneity frequently found in Mediterranean forests. Simple regression models were found to be consistent with the expected radiometric response of vegetation, and most of the multiple regression models fitted the observations sufficiently in order to make quantitative predictions for field variables from the remote sensing images. According to this study, however, these models should be regarded as exploratory models rather than fully operational ones. Spatially and non-spatially related factors are suggested as causes of the remaining dispersion of models created.
Keywords: forest quantitative variables; predictive models; radiometric response; spatial heterogeneity

A simple radiometric correction model to improve automatic mapping of vegetation from multispectral satellite data - Pons, Xavier; Solé-Sugrañes, Lluís (Remote Sensing of Environment, 1994)
A simplified model for radiometric corrections has been used to improve nonsupervised classification of vegetation cover in a hilly area near Barcelona, Spain. A digital elevation model and standard parameters for exoatmospheric solar irradiance, atmospheric optical depth, and sensor calibration are the only inputs required. Radiometric classes obtained by cluster classification of Landsat TM images from nonradiometrically corrected images include several classes related to terrain illumination, but not to vegetation or thematic cover differences. The use of radiometric correction allows identifying all radiometric classes obtained as vegetation or thematic classes with 83.3% global accuracy. Classes obtained include Pinus halepensis, Quercus ilex, and Quercus cerrioides forests, shrublands, grasslands, urban areas with vegetation, urban areas without vegetation, and denuded areas. Radiometric correction helps in estimating surfaces and spectral features of these classes. The results are discussed considering botanical composition, date (phenology), and vegetation dynamics.