Suchergebnisse

Outbreak insects are among the major biotic disturbances affecting Mediterranean forests by reducing their growth and vitality through severe defoliations. Despite their relevance for the management of these drought-prone areas, we lack information on the relationships between growth, canopy cover and insect defoliations at ample spatial and temporal scales. Here, we combine remote sensing (vegetation indexes) and dendrochronological information (basal area increment, BAI) to assess the effects of pine processionary moth (Thaumetopoea pityocampa, PPM) defoliations on growth and cover changes of several pine species, mainly focusing on Pinus nigra. We compared both datasets with a long-term field survey of PPM stand defoliations carried out in eastern Spain during the period 1970-2012. Lastly, we fitted linear-mixed models of BAI using as predictors climatic variables and a multi-scalar drought index to distinguish drought-related growth reductions from those attributed to PPM outbreaks. PPM severe defoliations mainly affected edge or low-density stands. Several vegetation indices (Moisture Stress Index, Normalized Burn Ratio and Normalized Difference Infrared Index) reflected the cover decrease corresponding to severe PPM defoliations. We found that trees affected by various severe PPM defoliations took at least 2. years to recover BAI values similar to those observed before the outbreak. The combined use of remote sensing and dendrochronology allows monitoring the impact of PPM defoliations from stands to trees, and these are valuable approaches to forecast outbreaks and their effects on Mediterranean forest. We consider both powerful tools to further assess the interacting effects of climate warming and PPM dynamics on drought-prone forests. © 2014 Elsevier B.V. ; This study was supported by projects PROCLIM and CGL2011-26654 financed by La Caixa-Aragón Government and the Spanish Commission of Science and Technology-FEDER, respectively. JJC acknowledges support by ARAID. We sincerely thank J. D. Galván, A.Q. Alla and the personal from the Forest Health Laboratory (Mora de Rubielos, Gobierno de Aragón) for the help in the field works. The authors acknowledge the Landsat scenes provided by the European Space Agency (ESA) in the context of the project C1P.15257. ; Peer Reviewed

Land Surface Temperature (LST) is one of the key inputs for Soil-Vegetation-Atmosphere transfer modeling in terrestrial ecosystems. In the frame of BIOSPEC (Linking spectral information at different spatial scales with biophysical parameters of Mediterranean vegetation in the context of global change) and FLUXPEC (Monitoring changes in water and carbon fluxes from remote and proximal sensing in Mediterranean "dehesa" ecosystem) projects LST retrieved from Landsat data is required to integrate ground-based observations of energy, water, and carbon fluxes with multi-scale remotely-sensed data and assess water and carbon balance in ecologically fragile heterogeneous ecosystem of Mediterranean wooded grassland (dehesa). Thus, three methods based on the Radiative Transfer Equation were used to extract LST from a series of 2009–2011 Landsat-5 TM images to assess the applicability for temperature input generation to a Landsat-MODIS LST integration. When compared to surface temperatures simulated using MODerate resolution atmospheric TRANsmission 5 (MODTRAN 5) with atmospheric profiles inputs (LSTref), values from Single-Channel (SC) algorithm are the closest (root-mean-square deviation (RMSD) = 0.50 °C); procedure based on the online Radiative Transfer Equation Atmospheric Correction Parameters Calculator (RTE-ACPC) shows RMSD = 0.85 °C; Mono-Window algorithm (MW) presents the highest RMSD (2.34 °C) with systematical LST underestimation (bias = 1.81 °C). Differences between Landsat-retrieved LST and MODIS LST are in the range of 2 to 4 °C and can be explained mainly by differences in observation geometry, emissivity, and time mismatch between Landsat and MODIS overpasses. There is a seasonal bias in Landsat-MODIS LST differences due to greater variations in surface emissivity and thermal contrasts between landcover components. ; This research has been financially supported by the BIOSPEC project ―Linking spectral information at different spatial scales with biophysical parameters of Mediterranean vegetation in the context of Global Change‖ [28] (CGL2008-02301/CLI, Ministry of Science and Innovation, Spain), the FLUXPEC project ―Monitoring changes in water and carbon fluxes from remote and proximal sensing in a Mediterranean dehesa ecosystem‖ [29] (CGL2012-34383, Ministry of Economy and Competitiveness, Spain), and by a collaboration agreement between the Aragón Government and the Obra Social ―La Caixa‖ (DGA-La Caixa, GA-LC-042/2011), Spain ; We acknowledge support by the CSIC Open Access Publication Initiative through its Unit of Information Resources for Research (URICI). ; Peer reviewed