Search

A general review of the crystalline solutions of the generalized Skyrme model and their application to the study of cold nuclear matter at finite density and the Equation of State (EOS) of neutron stars is presented. For the relevant range of densities, the ground state of the Skyrme model in the three torus is shown to correspond to configurations with different symmetries, with a sequence of phase transitions between such configurations. The effects of nonzero finite isospin asymmetry are taken into account by the canonical quantization of isospin collective coordinates, and some thermodynamical and nuclear observables (such as the symmetry energy) are computed as a function of the density. We also explore the extension of the model to accommodate strange degrees of freedom, and find a first order transition for the condensation of kaons in the Skyrme crystal background in a thermodynamically consistent, non-perturbative way. Finally, an approximate EOS of dense matter is constructed by fitting the free parameters of the model to some nuclear observables close to saturation density, which are particularly relevant for the description of nuclear matter. The resulting neutron star mass-radius curves already reasonably satisfy current astrophysical constraints., 54 pages, 28 figures, review

Cancer is one of the major socio-health problems in the world. The level of education, the profession and/or employment status of the patient and the family can influence the amount of household income, the additional expenditure, and the possible socio-economic impact of the disease. The main objective of the study is to analyse and evaluate the influence of the level of education, the employment status of the patient, and the need for care and how these factors influence the additional expenditure and the possible socio-economic impact. Methods: descriptive cross-sectional randomised observational epidemiological study without replacement at the Hospital Universitario de Salamanca (CAUSA). Results: total sample (n = 365) comprised 53.2% of patients with no education or primary education, 25.8% with secondary education and 21.1% with higher education. Overall, 36.4% of patients were employed, 10.1% were self-employed, 53.0% were not employed, and 38.9% were experiencing other conditions. Significant statistics were found for educational level, employment status of the patient and main caregivers in terms of financial expenditure. Conclusions: Oncology patients with more education spend more on home help and/or accompanying the patient and transfers to the hospital for treatment. Higher incomes are not synonymous with higher expenditure in the sample. The patient’s main caregivers are a fundamental pillar of the patient’s household income and additional spending on orthopaedic material.

We address the possibility of the appearance of a charged kaon condensate in neutron star cores described within a generalized Skyrme model. Our treatment of strange degrees of freedom is based on the Bound State Approach by Callan and Klebanov, which allows to obtain an in-medium effective potential for the $s$-wave kaon condensate. We predict the onset of kaon condensation at a certain threshold density - whose value depends on the parameters of the model, and ranges between 1.5 and 2.5 times saturation density -, and obtain both the particle fractions and equation of state for dense matter in the kaon condensed phase. Finally, we discuss the effect of such condensates on the mass-radius curves and other observable properties of neutron stars with kaon condensed cores., 17 pages, 8 figures

A precise estimation of agricultural production provides relevant information for upcoming seasons, and helps in the assessment of crop losses before harvest in case of adverse situations. The objective of this work is to explore the development of a model capable of estimating barley production of a small agricultural production (127 ha) in Belchite, Spain. Variables adapted to the crop calendar of the growing barley are used to achieve that purpose. The variables have been created with weather data and remote sensing images. These images are acquired in two ranges of the electromagnetic spectrum, i.e., microwaves and optical spectral range, obtained from Sentinel-1 and Sentinel-2, respectively. Models are defined with a multiple linear regression method using all combinations of the independent variables correlated with production. The best linear regression model has a prediction error of 57.38 kg/ha (4%). The use of spectral variables, derived from radar vegetation index Cross Ratio (CR) and optical Inverted Red Edge Chlorophyll Index (IRECI), and climatic variables adapted to the crop calendar and climatic conditioning is revealed as an adequate strategy to obtain adjusted models.

Boson stars represent a hypothetical exotic type of compact stellar object that may be observed from the gravitational signal of coalescing binaries in current and future GW detectors. In this work we show that the moment of inertia $I$, the (dimensionless) angular momentum $\chi$ and the quadrupole moment $Q$ of rotating boson stars obey a universal relation, valid for a wide set of boson star models. Further, the obtained $I-\chi-Q~$ relation clearly differs from its famous neutron star counterpart, providing us with an unequivocal diagnostic tool to distinguish boson stars from ordinary compact stars or other celestial bodies in GW observations. Such universal (i.e. model-independent) relations also provide a useful tool to probe the strong gravity regime of general relativity and to constrain the equation of state of matter inside compact stars., Comment: 12 pages, 20 figures. In this current version, we have changed the format and the Appendix

Old age represents a social group that is undergoing continuous expansion. The aging population will be prone to chronic diseases and falls, which is a marker of frailty and a public health problem. This study aims to examine the relationship between living conditions and the prevalence of the risk of falls in older adults within the community. As an observational cross-sectional study, intentional sampling was carried out on residents of the metropolitan area over 75 years of age. The socio-demographic data of the subjects and their history of falls were collected. Additionally, the subjects were evaluated on the risk of falling, basic activities of daily living, such as walking and balance, fragility, and their fear of falling. The statistical analyses used were based on the Shapiro–Wilk test for normality, statistics of central tendency with description, mean (M) and dispersion, standard deviation (SD), bivariate contingency tables for studying the relationships between the variables, and the analysis of Pearson’s relational statistics (χ2). The comparisons of means were resolved by parametric or non-parametric routes. We obtained the following results: 1. The socio-demographic profile of our sample consisted of adults over 75 years of age, the majority of whom were overweight or obese women living in an urban area, specifically in an apartment, and receiving care; 2. Older people in the studied community had mild dependency and frailty, and were also at severe risk of falls; 3. The prevalence of falls was higher in women than in men in this study. Through these results, we confirmed the relationship between living conditions and the prevalence of risk of falls in older adults within the community.

The canonical quantization method for collective coordinates in crystalline configurations of the generalized Skyrme model is applied in order to find the quantum ground state of Skyrmion crystals and study the quantum corrections to the binding energy resulting from the isospin degrees of freedom. This leads to a consistent description of asymmetric nuclear matter within the Skyrme framework and allows us to compute the symmetry energy of the Skyrmionic crystal as a function of the baryon density, and to compare with recent observational constraints., Comment: V3: 16 pages, 4 figures. Some typos corrected. Minor changes in figures 1, 3 and 4. References added

Identification of forest fuels is a key step for forest fire prevention since they provide valuable information of fire behavior. This study assesses NASA’s Global Ecosystem Dynamics Investigation (GEDI) system to classify fuel types in Mediterranean environments according to the Prometheus model in a forested area of NE Spain. We used 59,554 GEDI footprints and extracted variables related to height metrics, canopy profile metrics, and aboveground biomass density estimates from products L2A, L2B, and L4A, respectively. Four quality filters were applied to discard high uncertainty data, reducing the initial footprints to 9,703. Spectral indices from Landsat-8 OLI scenes were created to test the effect of their integration with GEDI variables on fuel types estimation. Ground-truth data were comprised of Prometheus fuel types estimated in two previous studies. Only the types that matched in each GEDI footprint in both studies were used, resulting in a final sample of 1,112 footprints. Spearman’s correlation coefficient, Kruskal-Wallis and Dunn’s tests determined the variables to be included in the classification models: the relative height at the 85th percentile, the Plant Area Index, and the Aboveground Biomass Density from GEDI, and the brightness from Landsat-8 OLI. Best performances were achieved with Random Forest (RF) and Support Vector Machine with radial kernel (SVM-R), which were lower including only GEDI variables (accuracies: RF and SVM-R = 61.54 %) than integrating the brightness from Landsat-8 OLI (accuracies: RF = 83.71 %, SVM-R = 81.90 %). These results allow validating GEDI for fuel type classification of Prometheus model, constituting a promising information for forest management over large areas.

Skyrmion crystals are the field configurations which minimize the energy per baryon in the infinitely large topological charge sector of the Skyrme model, at least for sufficiently high density. They are, therefore, an important tool to describe the ground state of cold, symmetric nuclear matter at high density regimes. In this work, we analyze different crystalline phases and the existence of phase transitions between them within the generalized Skyrme model, with the ultimate goal of describing symmetric nuclear matter in a wide regime of densities. Furthermore, we propose a new energy-minimizing phase for densities lower than the nuclear saturation point ($n_0$) which also presents a good qualitative behavior in the zero density limit, thereby improving the description of strongly interacting matter in the region $n, Comment: 16 pages, 10 figures; v2: presentation slightly improved, some references added

The estimation of forest residual biomass is of interest to assess the availability of green energy resources. This study relates the Pinus halepensis Miller forest residual biomass (FRB), estimate...

First proposed in 2013 by Yagi and Yunes, the quasi-universal \emph{I-Love-Q relations} consist of a set of relations between the moment of inertia, the spin-induced quadrupole moment and the electric quadrupolar tidal deformability of neutron stars which are independent of the Equation of State (EoS) within an accuracy of $\sim1\%$. In this work, we show that these relations hold for different Skyrme-based nuclear matter EoS and also for the star-like solutions of different Einstein-BPS-Skyrme-models, some of which do not even present a barotropic equation of state. Further, other quasi-universal relations are analyzed, and together with recent GW observations, we use them to select the generalized Skyrme model that better reproduces observations. Our results reaffirm both the universality of the \emph{I-Love-Q} relations and the suitability of generalized Skyrme models to describe nuclear matter inside neutron stars., Comment: 23 pages, 11 figures

Fuel type is one of the key factors for analyzing the potential of fire ignition and propagation in agricultural and forest environments. The increase of three-dimensional datasets provided by active sensors, such as LiDAR (Light Detection and Ranging), has improved the classification of fuel types through empirical modelling. Empirical methods are site and sensor specific while Radiative Transfer Models (RTM) approaches provide broader universality. The aim of this work is to analyze the suitability of Discrete Anisotropic Radiative Transfer (DART) model to replicate low density small-footprint Airborne Laser Scanning (ALS) measurements and subsequent fuel type classification. Field data measured in 104 plots are used as ground truth to simulate LiDAR response based on the sensor and flight characteristics of low-density ALS data captured by the Spanish National Plan for Aerial Orthophotography (PNOA) in two different dates (2011 and 2016). The accuracy assessment of the DART simulations is performed using Spearman rank correlation coefficients between the simulated metrics and the ALS-PNOA ones. The results show that 32% of the computed metrics overpassed a correlation value of 0.80 between simulated and ALS-PNOA metrics in 2011 and 28% in 2016. The highest correlations were related to high height percentiles, canopy variability metrics as for example standard deviation and Rumple diversity index, reaching correlation values over 0.94. Two metric selection approaches and Support Vector Machine classification method with variants were compared to classify fuel types. The best-fitted classification model, trained with the DART simulated sample and validated with ALS-PNOA data, was obtained using Support Vector Machine method with radial kernel. The overall accuracy of the classification after validation was 88% and 91% for the 2011 and 2016 years, respectively. The use of DART demonstrates its value for simulating generalizable 3D data for fuel type classification providing relevant information for forest managers in fire prevention and extinction.

Made available in DSpace on 2020-12-12T01:34:32Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-11-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Fire severity assessment is crucial for predicting ecosystem response and prioritizing post-fire forest management strategies. Although a variety of remote sensing approaches have been developed, more research is still needed to improve the accuracy and effectiveness of fire severity mapping. This study proposes a unitemporal simulation approach based on the generation of synthetic spectral databases from linear spectral mixing. To fully exploit the potential of these training databases, the Random Forest (RF) machine learning algorithm was applied to build a classifier and regression model. The predictive models parameterized with the synthetic datasets were applied in a case study, the Sierra de Luna wildfire in Spain. Single date Landsat-8 and Sentinel-2A imagery of the immediate post-fire environment were used to develop the validation spectral datasets and a Pléiades orthoimage, providing the ground truth data. The four defined severity categories – unburned (UB), partial canopy unburned (PCU), canopy scorched (CS), and canopy consumed (CC) – demonstrated high accuracy in the bootstrapped (about 95%) and real validation sets (about 90%), with a slightly better performance observed when the Sentinel-2A dataset was used. Abundance of four ground covers (green vegetation, non-photosynthetic vegetation, soil, and ash) was also quantified with moderate (~45% for NPV) or high accuracy (higher than 75% for the remaining covers). No specific pattern in the comparison of sensors was observed. Variable importance analysis highlighted the complementary behavior of the spectral bands, although the contrast between the near and shortwave infrared regions stood out above the rest. Comparison of procedures reinforced the usefulness of the approach, as RF image-derived models and the multiple endmember spectral unmixing technique (MESMA) showed lower accuracy. The capabilities for detailed mapping are reflected in the development of different types of cartography (classification maps and fraction cover maps). The approach holds great potential for fire severity assessment, and future research needs to extend the predictive modeling to other burned areas – also in different ecosystems – and analyze its competence and the possible adaptations needed. Department of Geography and Spatial Management University of Zaragoza, C/Pedro Cerbuna 12 GEOFOREST-IUCA research group Environmental Sciences Institute (IUCA) University of Zaragoza, C/Pedro Cerbuna 12 Lab of Vegetation Ecology Instituto de Biociências Universidade Estadual Paulista (UNESP), Avenida 24-A 1515 Centro Universitario de la Defensa de Zaragoza Academia General Militar, Ctra. Huesca s/n Lab of Vegetation Ecology Instituto de Biociências Universidade Estadual Paulista (UNESP), Avenida 24-A 1515 FAPESP: 2019/07357-8

27 pags., 2 figs., Quantum field theory in curved spacetimes suffers in general from an infinite ambiguity in the choice of Fock representation and associated vacuum. In cosmological backgrounds, the requirement of a unitary implementation of the field dynamics in the physical Hilbert space of the theory is a good criterion to ameliorate such ambiguity. In- deed, this criterion, together with a unitary implementation of the symmetries of the equations of motion, leads to an equivalence class of unitarily equivalent quantizations that, even though it is still formed by an infinite number of Fock representations, is unique. In this work, we apply the procedure developed for fields in cosmological settings to analyze the quantization of a scalar field in the presence of an external electromagnetic classical field in a flat background. We find a natural Fock representation that admits a unitary implementation of the quantum field dynamics. It automatically allows to define a particle number density at all times in the evolution with the correct asymptotic behavior, when the electric field vanishes. Moreover we show the unitary equivalence of all the quantizations that fulfill our criteria, so that they form a unique equivalence class. Although we perform the field quantization in a specific gauge, we also show the equivalence between the procedures taken in different gauges., Financial support was provided by the Spanish Government through the projects FIS2017- 86497-C2-2-P (with FEDER contribution) and FIS2016-78859-P (AEI/FEDER,UE). AGMC acknowledges financial support from the Ministry of Education, Culture, and Sports, Spain (Grant No. FPA2017-83814-P), the Xunta de Galicia (Grant No. INCITE09.296.035PR and Conselleria de Educacion), the Spanish Consolider-Ingenio 2010 Programme CPAN (CSD2007-00042), Maria de Maetzu Unit of Excellence MDM2016-0692, and FEDER.

The development of biorefinery processes to platform chemicals for most lignocellulosic substrates, results in side processes to intermediates such as oligosaccharides. Agrofood wastes are most amenable to produce such intermediates, in particular, cellooligo-saccharides (COS), pectooligosaccharides (POS), xylooligosaccharides (XOS) and other less abundant oligomers containing mannose, arabinose, galactose and several sugar acids. These compounds show a remarkable bioactivity as prebiotics, elicitors in plants, food complements, healthy coadyuvants in certain therapies and more. They are medium to high added-value compounds with an increasing impact in the pharmaceutical, nutraceutical, cosmetic and food industries. This review is focused on the main production processes: autohydrolysis, acid and basic catalysis and enzymatic saccharification. Autohydrolysis of food residues at 160−190 °C leads to oligomer yields in the 0.06−0.3 g/g dry solid range, while acid hydrolysis of pectin (80−120 °C) or cellulose (45−180 °C) yields up to 0.7 g/g dry polymer. Enzymatic hydrolysis at 40−50 °C of pure polysaccharides results in 0.06−0.35 g/g dry solid (DS), with values in the range 0.08−0.2 g/g DS for original food residues.

The aim of study is to map the carbon dioxide (CO2) emission of the aboveground tree biomass (AGB) in case of a fire event. The suitability of low point density, discrete, multiple-return, Airborne...

Mediterranean forests are recurrently affected by fire. The recurrence of fire in such environments and the number and severity of previous fire events are directly related to fire risk. Fuel type classification is crucial for estimating ignition and fire propagation for sustainable forest management of these wildfire prone environments. The aim of this study is to classify fuel types according to Prometheus classification using low-density Airborne Laser Scanner (ALS) data, Sentinel 2 data, and 136 field plots used as ground-truth. The study encompassed three different Mediterranean forests dominated by pines (Pinus halepensis, P. pinaster y P. nigra), oaks (Quercus ilex) and quercus (Q. faginea) in areas affected by wildfires in 1994 and their surroundings. Two metric selection approaches and two non-parametric classification methods with variants were compared to classify fuel types. The best-fitted classification model was obtained using Support Vector Machine method with radial kernel. The model includes three ALS and one Sentinel-2 metrics: the 25th percentile of returns height, the percentage of all returns above mean, rumple structural diversity index and NDVI. The overall accuracy of the model after validation was 59%. The combination of data from active and passive remote sensing sensors as well as the use of adapted structural diversity indices derived from ALS data improved accuracy classification. This approach demonstrates its value for mapping fuel type spatial patterns at a regional scale under different heterogeneous and topographically complex Mediterranean forests.

The account of total biomass can assist with the evaluation of climate regulation policies from local to global scales. This study estimates total biomass (TB), including tree and shrub biomass fractions, in Pinus halepensis Miller forest stands located in the Aragon Region (Spain) using Airborne Laser Scanning (ALS) data and fieldwork. A comparison of five selection methods and five regression models was performed to relate the TB, estimated in 83 field plots through allometric equations, to several independent variables extracted from ALS point cloud. A height threshold was used to include returns above 0.2 m when calculating ALS variables. The sample was divided into training and test sets composed of 62 and 21 plots, respectively. The model with the lower root mean square error (15.14 tons/ha) after validation was the multiple linear regression model including three ALS variables: the 25th percentile of the return heights, the variance, and the percentage of first returns above the mean. This study confirms the usefulness of low-density ALS data to accurately estimate total biomass, and thus better assess the availability of biomass and carbon content in a Mediterranean Aleppo pine forest.

El aumento de la mortalidad y la pérdida de vitalidad de los bosques son procesos que afectan a diversas especies de árboles y biomas. Estos fenómenos de decaimiento forestal se han asociado a la interacción de múltiples factores relacionados con el cambio global, como el aumento de las sequías o la mayor incidencia de factores bióticos que generan estrés. Sin embargo, el papel que juegan estos organismos en el decaimiento del bosque en relación a la sequía no está del todo comprendido. En este trabajo caracterizamos retrospectivamente los efectos que ejercen dichos organismos sobre el crecimiento radial de árboles estresados por sequía utilizando dendrocronología. El efecto combinado del muérdago y las sequías reducen el crecimiento del pino silvestre y aumentan la defoliación, siendo estos efectos más evidentes en el ápice del árbol. La procesionaria induce pérdidas de crecimiento en pino laricio, pero en general se observa una recuperación dos años después. No encontramos un papel determinante de los hongos patógenos de raíz en el decaimiento del abeto. Finalmente, pinos carrasco muertos que presentaban ataques de insectos perforadores mostraron patrones de crecimiento similares a pinos vivos. Este estudio nos permite caracterizar algunos de los complejos y múltiples efectos de diferentes factores bióticos de estrés sobre el crecimiento y la vulnerabilidad de los bosques susceptibles a los efectos negativos de las sequías. Increasing mortality and decline of forests are affecting several tree species and biomes. These events of forest decline have been related to the interaction of several global change elements, like the increase in drought stress or a higher incidence of biotic stress factors. However, the roles played by biotic stressors have been scarcely explored as related to drought stress. In this paper we retrospectively characterize the effects of these organisms on radial growth of trees already stressed by drought using dendrochronology. The combined effect of mistletoe and droughts reduce tree growth in Scots pine and increase defoliation, being these effects more noticeable in the apex. The pine processionary moth induces growth losses in the affected stands of black pine, but they usually recover two years after the outbreak. We did not find a determinate role of root pathogens on silver fir dieback. Finally, dead Aleppo pine trees infested by bark beetles showed similar growth patterns than living pine trees. This study allows characterizing some of the complex and multiple effects of different biotic stressors on growth and vulnerability of forests subjected to the negative effects exerted by droughts. Este estudio ha sido financiado por los proyectos CGL-2007-6066-C04-02/BOS, CGL2008-04847-C02-01, CGL2011-26654 (MINECO), 387/2011 (Organismo Autónomo de Parques Naciona-les) y PROCLIM (La Caixa-Gobierno de Aragón).

Atmospheric correction of optical satellite imagery is an essential pre-processing for modelling biophysical variables, multi-temporal analysis, and digital classification processes. Sentinel-2 products available for users are distributed by the European Space Agency (ESA) as Top Of Atmosphere reflectance values in cartographic geometry (Level-1C product). In order to obtain Bottom Of Atmosphere reflectance images (Level-2A product) derived from this Level-1C products, ESA provides the SEN2COR module, which is implemented in the Sentinel Application Platform. Alternatively, ESA recently distributes Level-2A products processed by SEN2COR with a default configuration. On the other hand, the conversion from Level-1C to Level-2A product can be generated using alternative atmospheric correction methods, such as MAJA, 6S, or iCOR. In this context, this paper aims to evaluate the quality of Level-2A products obtained through different methods in Mediterranean shrub and grasslands by comparing data obtained from Sentinel-2 imagery with field spectrometry data. For that purpose, six plots with different land covers (asphalt, grass, shrub, pasture, and bare soil) were analyzed, by using synchronous imagery to fieldwork (from July to September 2016). The results suggest the suitability of the applied atmospheric corrections, with coefficients of determination higher than 0.90 and root mean square error lower than 0.04 achieving a relative error in bottom of atmosphere reflectance of only 2–3%. Nevertheless, minor differences were observed between the four tested methods, with slightly varying results depending on the spectral band and land cover. This work has been supported by the SynerTGE project (CGL2015-69095-R), funded by the Spanish Ministry of Economy and Competitiveness; the HyZCP project (2015-17), funded by the Centro Universitario de la Defensa de Zaragoza, and projects CGL2016-75217-R (MINECO/FEDER, EU) and PyrenEOS EFA 048/15, which has been 65% cofinanced by the European Regional Development through the Interreg V-A Spain-France-Andorra programme (POCTEFA 2014-2020).

The paper assesses spatio-temporal patterns of land surface temperature (LST) and fire severity in the Las Hurdes wildfire of Pinus pinaster forest, which occurred in July 2009, in Extremadura (Spain), from a time series of fifteen Landsat 5 TM images corresponding to 27 post-fire months. The differenced Normalized Burn Ratio (dNBR) was used to evaluate burn severity. The mono-window algorithm was applied to estimate LST from the Landsat thermal band. The burned zones underwent a significant increase in LST after fire. Statistically significant differences have been detected between the LST within regions of burn severity categories. More substantial changes in LST are observed in zones of greater fire severity, which can be explained by the lower emissivity of combustion products found in the burned area and changes in the energy balance related to vegetation removal. As time progresses over the 27 months after fire, LST differences decrease due to vegetation regeneration. The differences in LST and Normalized Difference Vegetation Index (NDVI) values between burn severity categories in each image are highly correlated (r = 0.84). Spatial patterns of severity and post-fire LST obtained from Landsat time series enable an evaluation of the relationship between these variables to predict the natural dynamics of burned areas.

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.

Vegetation is one of the components of the ecosystems more affected by the fire and its destruction is, indeed, the most immediate and visible of its effects. In the same way, vegetal regeneration processes are a clear sign of the ecosystems recovery. These vegetal regeneration processes depends on the interaction of multiple factors (biotic and abiotic) which take place in different intensity/severity fire scenes. In this context, this work has as objective to study vegetal regeneration processes in two climatically contrasted environments (semiarid and subatlantic). It presents a methodology based on the controlled burning of experimental plots and on the capture of spectral information by means of a field spectro-radiometer during a period of two years. Collected data have shown important differences in the behavior of the two experimental stations, differences which can be summarize in the presence of quick vegetal regeneration processes in the subatlantic environment and their absence in the semiarid one. The low influence shown by some analyzed variables such as prefire vegetation level or immediate severity level allows concluding that, in these vegetal communities, the climatic variable is the one which influences vegetal regeneration processes.

Se analiza el impacto y la evolucion de la estructura del paisaje en un incendio del Prepirineo aragones utilizando 6 imagenes Landsat 5 TM, identificando relaciones entre valores de heterogeneidad espacial y comunidades vegetales. Se extraen los NDVI (Normalized Difference Vegetation Index), se calcula el indice de Shannon y se cartografia para cada ano. Se definen tres componentes representativos de los valores de diversidad (preincendio, a corto plazo y a medio plazo). Se concluye que a nivel de comunidad vegetal el incendio ha supuesto un incremento de la diversidad interna en algunas comunidades. No obstante, a medio plazo y a escala global el fuego provoca la homogeneizacion del paisaje, tal y como describen otros autores utilizando fuentes de informacion similar.

Remote sensing has been shown to be an efficient tool in the study of forest-fire processes. However, a lack of information on the amount of biomass burnt reduces the accuracy of fire severity and emission models. In this study, we use imagery from the Landsat Thematic Mapper to map crown biomass and burn severity for a large Mediterranean area. Considering the specific characteristics of the Mediterranean environment, two methods to extract useful remote sensing data were employed; both sought to analyze relationships between crown biomass and spectral information. As a result, a crown biomass map of Pinus spp. was created for the entire study area, applying nonlinear regression using the variable MID57 (TM5 + TM7) (R2 = 0.651). Considering only P. halepensis pixels that were burnt in the selected fire scar, the relationships between crown biomass and burn severity were found to be high and significant, yielding an R2 value of 0.516. Finally, a logistic regression model was constructed to map the presence or otherwise of high burn severity levels using crown biomass as the independent variable, yielding in the confusion matrix an overall percentage of data points correctly classified of 77% and a Kappa statistic in the validation sample of 0.554.

Fire severity can be considered one of the most influential factors in the postfire development of burnt areas. Ground level studies documenting changes in reflectance values improve the discrimination of spatial fire severity across large areas. The objective of this study was to determine those spectral regions most sensitive to fire severity levels by investigating the relationship between postfire surface materials and reflectance values. A total of 34 field plots were analyzed immediately following two natural fires in Spain. To obtain postfire data, we used a portable structure to obtain vertical photographs and reflectance values in the visible-near-infrared (VIS-NIR) range. Spectral reflectance and convolved Landsat Thematic Mapper (TM) bands were statistically correlated with individual postfire materials and with a fire severity index, the Combustion Products Index (CPI), derived from them. The wavelengths most sensitive to postfire materials were 450.6, 758.2, and 797 nm for ash, black carbon, and vegetation, respectively, although these wavelengths were included within ranges of comparable behavior. Finally, stepwise multiple regression models (SMLRs) were applied to the data. SMLR predicted ash, black carbon, and vegetation levels from reflectance data with accuracies higher than 75%. Estimation from Landsat-TM bands yielded slightly lower accuracies. The CPI severity index was also well estimated using either reflectance data or TM bands (r 2 = 0.925 and r 2 = 0.840 , respectively).

Tree biomass estimate is essential for carbon accounting, bioenergy feasibility studies, and forest sustainable management. This fact, added to the availability of airborne laser scanning (ALS) information, provided by the Spanish National Plan for Aerial Orthophotography (PNOA), and the existence of little research focusing on the use of ALS technology in Mediterranean Aleppo pine (Pinus halepensis Mill.) forest, determined the main objective of this research. Thus, this study aims to test the suitability of the low point density (0.5 points/m2), discrete, multiple-return, PNOA-ALS data, to estimate and map the total biomass (TB) and its carbon content in Pinus halepensis Mill. forest stands, located in Aragon (north-eastern Spain). TB was calculated in 45 field plots, using allometric equations, and related through a multivariate linear regression analysis with a collection of independent variables extracted from the ALS data. The predictive model was validated using a leave-one-out cross-validation (LOOCV) technique. Then, a regular grid with cell size 25 x 25 m corresponding to the sample plot size was generated by means of GIS, in order to compute TB at stand level and convert biomass to carbon by using the 0.5 conversion factor. The maximum height, kurtosis and the percentage of returns above 1 meter, were the ALS metrics included in the fitted model, which presented a R2 value of 0.89. The implementation of the model in a GIS showed an average of 68633 kg/ha of TB and 34247.95 kg/ha of carbon fixed. The results indicate that despite the low point density of the ALS data, the final model is accurate enough to be used in forestry applications.

espanolLa proliferacion y facilidad de acceso a grandes bases de datos de caracter cientifico tipo Open Data hace necesario un analisis sobre la adecuacion de cada una de ellas a los objetivos perseguidos en cualquier trabajo de investigacion o en la aplicacion de un proceso de modelado. En este trabajo se comparan tres fuentes de datos validadas por comuni-dad cientifica y ampliamente utilizadas para el analisis de la temperatura (del aire y de superficie) a escalas medias (WorldClim, ECA&D y MODIS) utilizando como area de estudio el territorio europeo al oeste de la fron-tera ruso-europea. Estas tres series de datos se comparan teniendo en cuenta dos tamanos de pixel y los distintos tipos de climas existentes. Co -mo resultado, se verifica la existencia de diferencias entre estas series de datos, aunque no significativas, y se describen las limitaciones y funcio-nalidad de cada una de ellas. EnglishThe easy access to scientific Open Data large databases makes it necessary to analyze the adequacy of each of them to the objectives pur-sued in any research work or in the application of a modeling process. This paper compares three data sources validated by scientific community and widely used for the analysis of 2 types of temperature (air and land surface) at medium scales (WorldClim, ECA&D and MODIS) using as study area the European territory west of the Russian-European border. These three datasets are compared taking into account two pixel sizes and diffe -rent types of climates. As a result, we verified the existence of differen- ces, although not significant, and described the limitations and functio-nality of each of these series.

Aim of study: Human settlements and activities have completely modified landscape structure in the Mediterranean region. Vegetation patterns show the interactions between human activities and natural processes on the territory, and allow understanding historical ecological processes and socioeconomic factors. The arrangement of land uses in the rural landscape can be perceived as a proxy for human activities that often lead to the use, and escape, of fire, the most important disturbance in our forest landscapes. In this context, we tried to predict human-caused fire occurrence in a 5-year period by quantifying landscape patterns.Area of study: This study analyses the Spanish territory included in the Iberian Peninsula and Balearic Islands (497,166 km2).Material and Methods: We evaluated spatial pattern applying a set of commonly used landscape ecology metrics to landscape windows of 10x10 sq km (4751 units in the UTM grid) overlaid on the Forest Map of Spain, MFE200.Main results: The best logistic regression model obtained included Shannon’s Diversity Index, Mean Patch Edge and Mean Shape Index as explicative variables and the global percentage of correct predictions was 66.3 %.Research highlights: Our results suggested that the highest probability of fire occurrence at that time was associated with areas with a greater diversity of land uses and with more compact patches with fewer edges.Keywords: human-caused wildfires; landscape ecology; logistic regression.

Regarding the three objectives of European Union (EU) energy policy (secure supply, competitiveness and environmental protection) the EU Commission published the Communication entitled ‘White Paper: Energy for the Future Renewable Sources of Energy’ (EU Commission, 1997; Mourelatou & Smith, 2004). This document, which was the starting point for the European promotion and development of renewable energy, stated the objective that 12% of energy production in 2010 would come from renewable sources. In Spain, this objective was recognized by the government in 1999 in the Plan to the Promotion of Renewable Energies (PPRE). To achieve this objective, the PPRE focused on increasing the use of biomass, identifying forest residues as one of the biomass sources. Specifically, this document established an increase in the use of forest residual biomass to 450 000 tonnes of petroleum equivalent per year (TPE/year) (IDAE, 1999). Among the different sources of renewable energy, this chapter focuses on forest residual biomass (FRB). This term refers to branches, foliage, and unmerchantable stem tops that are commercially unsuitable in terms of the timber obtained from regular operations in forest management or in timber exploitation (Esteban et al., 2004; IDAE, 1999; Velazquez, 2006). Following the ‘complete-tree concept,’ the term ‘branches’ include the wood and bark of live and dead branches; ‘foliage’ refers to all leaves-needles, new shoots and reproductive organs; and the ‘unmerchantable stem top’ is the upper section of the stem that is left unutilized in logging operations due to its small diameter and high degree of branching (the bottom stem diameter of this unmerchantable top usually ranges from 5 to 10 cm) (Hakkila & Parikka, 2002). The treatments commonly applied to these residues in Spain include controlled burning, stacking within the forest and, less commonly, splintering to improve their incorporation into the soil (IDAE, 2005a, 2007; Velazquez, 2006). However, this biomass segment can also be used as a source of energy in heating applications (fuel for domestic or industrial stoves and boilers) and in the generation of electricity (replacing fossil fuels in power stations) (Asikainen et al., 2002; IDAE, 2005b), with the majority of the residue currently being utilized for the latter in Spain (IDAE, 2007). The benefits associated with this energy-related use can be divided into two types: environmental and socio-economic. The first benefits are generated in the production phase, as the recovery and elimination of FRB reduces the risk of forest fires and their severity (IDAE, 2005a; Velazquez, 2006), and also because the implementation of silviculture can

[ES] Although post-fire soil erosion has been studied, little attention has been paid to changes in soil surface cover following fires, despite this being a key factor in understanding the water and sediment yield. This study, at Peñaflor (Spain), investigated the effect of fire on soil erosion using data from soil erosion plots and high spatial resolution photography (HSRP). Measurements were made from October 2003 to October 2005 in a control plot and a plot experimentally exposed to a fire in October 2004. Ground cover components were identified, including vegetation, bare soil, stones, charcoal and ash. Runoff and sediment concentrations were low because of the absence of intense rainfall events, but the fire contributed to an increase of soil erosion by one order of magnitude. HSRP observations demonstrated that the sediments become mixed with ash and charcoal. Disappearance of the ash two months after the fire and a reduction in the amount of surface charcoal showed that these factors control erosion during the first few rainfall events following a fire. An increase in rock fragment cover was a consequence of the removal of vegetation and litter by the fire, and removal of the ash and charcoal by overland flow. © 2011 Elsevier Ltd., This research has been financially supported by the Spanish Ministry of Science and Technology (grants CGL2008-01083/CLI and CGL2006-11619/HID). We thank Deborah Martin and two anonymous referees for reviewing and improving the draft manuscript.

The modelling of habitat suitability for parasites is a growing area of research due to its association with climate change and ensuing shifts in the distribution of infectious diseases. Such models depend on remote sensing data and require accurate, high-resolution temperature measurements. The temperature is critical for accurate estimation of development rates and potential habitat ranges for a given parasite. The MODIS sensors aboard the Aqua and Terra satellites provide high-resolution temperature data for remote sensing applications. This paper describes comparative analysis of MODIS- derived temperatures relative to ground records of surface temperature in the western Palaearctic. The results show that MODIS overestimated maximum temperature values and underestimated minimum temperatures by up to 5-6 oC. The com- bined use of both Aqua and Terra datasets provided the most accurate temperature estimates around latitude 35-44o N, with an overestimation during spring-summer months and an underestimation in autumn-winter. Errors in temperature estima- tion were associated with specific ecological regions within the target area as well as technical limitations in the temporal and orbital coverage of the satellites (e.g. sensor limitations and satellite transit times). We estimated error propagation of temperature uncertainties in parasite habitat suitability models by comparing outcomes of published models. Error estimates reached 36% of annual respective measurements depending on the model used. Our analysis demonstrates the importance of adequate image processing and points out the limitations of MODIS temperature data as inputs into predictive models concerning parasite lifecycles.