Understanding fire is essential to improving forest management strategies. More specifically, an accurate knowledge of the spatial distribution of fuels is critical when analyzing, modelling and predicting fire behaviour. First, we review the main concepts and terminology associated with forest fuels and a number of fuel type classifications. Second, we summarize the main techniques employed to map fuel types starting with the most traditional approaches, such as field work, aerial photo interpretation or ecological Keywords.modelling. We pay special attention to more contemporary techniques, which involve the use of remote Forest fuels sensing systems. In general, remote sensing systems are low-priced, can be regularly updated and are less Remote sensing time-consuming than traditional methods, but they are still facing important limitations. Recent work Fuel type nas snown that the integration of different sources of information and methods in a complementary way Fuel management helps to overcome most of these limitations. Further research is encouraged to develop novel and enhanced remote sensing techniques.

No abstract

Georeferencing field plots by means of GPS/GLONASS techniques is becoming compulsory for many applications concerning forest management and inventory. True coordinates obtained in a total station traverse were compared against GPS/GLONASS occupations computed from one navigation-grade and three survey-grade receivers. Records were taken under a high Pinus sylvestris L. forest canopy situated in a mountainous area in central Spain. The horizontal component of the absolute error was a better descriptor of the performance of GPS/GLONASS receivers compared to the precision computed by the proprietary software. The vertical component of absolute error also failed to show the effects revealed when the horizontal one was studied. These differences might be critical for applications involving high-demanding surveys, in which a comparison against a terrestrially surveyed ground truth is still mandatory for accuracy assessment in forested mountainous areas. Moreover, a comparison of diverse Differential GPS/GLONASS techniques showed that the effect of lengthening the baseline and lowering the logging rate was not significant in this study. Differences among methods and receivers were only observed for recording periods between 5 and 15 minutes. The hand-held receiver was inappropriate for plot establishment due to its inaccuracy and a low rate of fixed solutions, though it may be used for forest campaigns tolerating low precision or permitting the employment of periods of 20 minutes or longer for plot mensuration.Additional key words: forest inventory; georeferencing; global navigation satellite system (GNSS) (GLONASS); optimum observing time. Resumen Exactitud y precisión de receptores GPS bajo cubiertas forestales en ambientes montañososLa georreferenciación de trabajos de campo por medio de GPS/GLONASS es cada vez más necesaria para muchas aplicaciones en la gestión e inventario forestal. Se compararon coordenadas reales levantadas con estación total con las obtenidas por un navegador y tres equipos de calidad topográfica. Los registros se efectuaron bajo una masa de Pinus sylvestris L. del Sistema Central, España. La componente horizontal del error absoluto resultó ser un mejor descriptor de la calidad de las mediciones de los receptores GPS/GLONASS que los valores de precisión proporcionados por el software de los equipos. La componente vertical del error absoluto no mostró los efectos revelados por la componente horizontal. Estas diferencias pueden ser críticas para trabajos que requieran levantamientos topográficos de precisión, en los cuáles un contraste con itinerarios de validación sobre el terreno sigue siendo indispensable para calcular la exactitud en áreas forestales montañosas. Por otro lado, la comparación de diversas técnicas de GPS/GLO-NASS diferencial mostró que los cambios en la longitud de la línea base y de la tasa de registros no fueron significativos en este estudio. Sólo se observaron diferencias ente los métodos y receptores para tiempos de registro de 5 a 15 minutos. El navegador no resu...

Background: In Quercus suber, cork oak, a Mediterranean forest tree of economic and social interest, rapid production of isogenic lines and clonal propagation of elite genotypes have been achieved by developing in vitro embryogenesis from microspores and zygotic embryos respectively. Despite its high potential in tree breeding strategies, due to their recalcitrancy, the efficiency of embryogenesis in vitro systems in many woody species is still very low since factors responsible for embryogenesis initiation and embryo development are still largely unknown. The search for molecular and cellular markers during early stages of in vitro embryogenesis constitutes an important goal to distinguish, after induction, responsive from non-responsive cells, and to elucidate the mechanisms involved in embryogenesis initiation for their efficient manipulation. In this work, we have performed a comparative analysis of two embryogenesis pathways derived from microspores and immature zygotic embryos in cork oak in order to characterize early markers of reprogrammed cells in both pathways. Rearrangements of the cell structural organization, changes in epigenetic marks, cell wall polymers modifications and endogenous auxin changes were analyzed at early embryogenesis stages of the two in vitro systems by a multidisciplinary approach.

The evaluation of accuracy is essential for assuring the reliability of ecological models. Usually, the accuracy of above-ground biomass () predictions obtained from remote sensing is assessed by the mean differences (), the root mean squared differences (), and the coefficient of determination (2) between observed and predicted values. In this article we propose a more thorough analysis of accuracy, including a hypothesis test to evaluate the agreement between observed and predicted values, and an assessment of the degree of overfitting to the sample employed for model training. Using the estimation of forest from LIDAR and spectral sensors as a case study, we compared alternative prediction and variable selection methods using several statistical measures to evaluate their accuracy. We showed that the hypothesis tests provide an objective method to infer the statistical significance of agreement. We also observed that overfitting can be assessed by comparing the inflation in residual sums of squares experienced when carrying out a cross-validation. Our results suggest that this method may be more effective than analysing the deflation in 2. We proved that overfitting needs to be specifically addressed since, in light of , and 2 alone, predictions may apparently seem reliable even in clearly unrealistic circumstances, for instance when including too many predictor variables. Moreover, Theil's partial inequality coefficients, which are employed to resolve the proportions of the total errors due to the unexplained variance, the slope and the bias, may become useful to detect averaging effects common in remote sensing predictions of. We concluded that statistical measures of accuracy, precision and agreement are necessary but insufficient for model evaluation. We therefore advocate for incorporating evaluation measures specifically devoted to testing observed-versuspredicted fit, and to assessing the degree of overfitting.