-A two-step mortality model for even-aged Pinus radiata stands in Galicia (Northwestern Spain) is presented. The model was developed using data from two inventories of a trial network involving l30 permanent plots. The model consists of two complementary equations. The first equation is a logistic function predicting the probability of complete survival depending on stems per hectare, age and relative spacing index. The second equation estimates the reduction in the number of stems that is observed in a stand where natural mortality occurs. Fourteen equations were fitted utilising the plots where trees died over the time period analyzed. Estimates from this second model are then reduced using three different stem number projection methods: a stochastic approach, a deterministic rule-based method and another deterministic approach that compares the probability of mortality using a threshold value. The values and signs of the parameters in both equations are consistent with existing experience about natural mortality of Pinus radiata in the region of Galicia. logistic regression / Pinus radiata / even-aged forest / mortality Résumé -Modèle de mortalité en deux étapes pour des peuplements équiennes de Pinus radiata D. Don en Galicie (nord-ouest de l'Espagne). Il s'agit de la présentation d'un modèle de mortalité à deux étapes pour des peuplements équiennes de Pinus radiata en Galicie (au nord de l'Espagne). Le modèle a été développé à partir de données de deux inventaires de 130 échantillons permanents. Le modèle est basé sur deux équations: la première, est une fonction logistique pouvant prévoir la probabilité de survie totale en fonction du nombre d'arbres par hectare, de l'âge et de l'index d'espacement relatif. La seconde équation donne une estimation de la réduction du nombre d'arbres observée dans un peuplement où il y a mortalité naturelle. Quatorze équations ont été inclues en utilisant des parcelles où des arbres sont morts durant la période d'analyse. Les estimations tirées de ce second modèle sont ensuite réduites en utilisant trois différentes méthodes de projection du nombre d'arbres: une approche stochastique, une méthode déterminative réglementée et une autre approche déterminative qui compare la probabilité de mortalité en utilisant une méthode de seuil. Les valeurs et signes paramétriques des deux équations s'accordent avec les expériences existantes sur la mortalité naturelle du Pinus radiata de la région de Galicie. régression logistique / Pinus radiata / peuplements équienne / mortalité

-Ten algebraic difference equations were used to develop site index models for even-aged stands of Pinus pinaster in two ecoregions of Galicia (northwestern Spain). Data from 204 stem analyses were obtained and a data structure involving all possible growth intervals was used to fit the equations. Generalized nonlinear least square methods were applied to take into account the error structure. Autocorrelation was corrected expanding the error term to allow a first-order autoregressive model adequate for the data structure. Different weighting factors were employed to satisfy the equal error variance assumption. Bias, root mean square error and Akaike's information criterion were calculated and cross-validation residuals were used to evaluate the performance of the equations. Ecoregional differences in the site index models were analysed using the non-linear extra sum of squares method and Lakkis-Jones test. The parameters of the models were significantly different between ecoregions. Relative error in site index predictions was used to select 20 years as the best reference age. Based on the analysis, an algebraic difference equation derived from the base model of Chapman-Richards with a different set of parameters for each ecoregion can be recommended. This model is polymorphic and with multiple asymptotes. It provides compatible site index and height growth estimates.site index model / ecoregion-based / Pinus pinaster / generalized nonlinear regression Résumé -Modèles écorégionaux de site index pour Pinus pinaster en Galice (nord-ouest de l'Espagne). Dix équations en différences algébriques ont été utilisées pour développer des courbes de croissance pour futaies régulières de pin maritime en deux éco-régions de la Galice (nord-ouest de l'Espagne). Les données utilisées pour ajuster les équations proviennent d'analyse de tiges de 204 arbres dominants avec une structure de tous les intervalles de croissance possibles. Les méthodes des minima quadratiques généralisés ont été considérées pour tenir en compte la structure des erreurs. On a corrigé l'auto-corrélation avec un terme additionnel de l'erreur qui donne un model autorégressif de premier ordre qui s'adapte à la structure des données. Différents facteurs de pondération ont été employés pour satisfaire l'hypothèse de variance semblable. Biais, erreur moyenne quadratique et le critère d'information d'Akaike ont été calculés et les résidus de la validation croisée ont été utilisés pour évaluer le comportement des équations. On a analysé les différences des modèles de croissance entre éco-régions avec la méthode de la somme additionnelle des carrés des résidus et le test de Lakkis-Jones. Les paramètres des modèles sont significativement différents entre éco-régions. L'erreur relative pour la prédiction de l'indice de station a été employée pour sélectionner 20 années comme l'âge de référence optimale. Une équation en différences algébriques dérivée du modèle de Chapman-Richards avec un ensemble différent de paramètres pour chaque éco-région est proposée...

The fuel complex variables canopy bulk density and canopy base height are often used to predict crown fire initiation and spread. Direct measurement of these variables is impractical, and they are usually estimated indirectly by modelling. Recent advances in predicting crown fire behaviour require accurate estimates of the complete vertical distribution of canopy fuels. The objectives of the present study were to model the vertical profile of available canopy fuel in pine stands by using data from the Spanish national forest inventory plus low-density airborne laser scanning (ALS) metrics. In a first step, the vertical distribution of the canopy fuel load was modelled using the Weibull probability density function. In a second step, two different systems of models were fitted to estimate the canopy variables defining the vertical distributions; the first system related these variables to stand variables obtained in a field inventory, and the second system related the canopy variables to airborne laser scanning metrics. The models of each system were fitted simultaneously to compensate the effects of the inherent cross-model correlation between the canopy variables. Heteroscedasticity was also analyzed, but no correction in the fitting process was necessary. The estimated canopy fuel load profiles from field variables explained 84% and 86% of the variation in canopy fuel load for maritime pine and radiata pine respectively; whereas the estimated canopy fuel load profiles from ALS metrics explained 52% and 49% of the variation for the same species. The proposed models can be used to assess the effectiveness of different forest management alternatives for reducing crown fire hazard.

No abstract

Understanding the linkage between accumulated fuel dryness and temporal fire occurrence risk is key for improving decision-making in forest fire management, especially under growing conditions of vegetation stress associated with climate change. This study addresses the development of models to predict the number of 10-day observed Moderate-Resolution Imaging Spectroradiometer (MODIS) active fire hotspots-expressed as a Fire Hotspot Density index (FHD)-from an Accumulated Fuel Dryness Index (AcFDI), for 17 main vegetation types and regions in Mexico, for the period 2011-2015. The AcFDI was calculated by applying vegetation-specific thresholds for fire occurrence to a satellite-based fuel dryness index (FDI), which was developed after the structure of the Fire Potential Index (FPI). Linear and non-linear models were tested for the prediction of FHD from FDI and AcFDI. Non-linear quantile regression models gave the best results for predicting FHD using AcFDI, together with auto-regression from previously observed hotspot density values. The predictions of 10-day observed FHD values were reasonably good with R 2 values of 0.5 to 0.7 suggesting the potential to be used as an operational tool for predicting the expected number of fire hotspots by vegetation type and region in Mexico. The presented modeling strategy could be replicated for any fire danger index in any region, based on information from MODIS or other remote sensors.

Crown fires combine high rates of spread, flame lengths, and intensities, making it virtually impossible to control them by direct action and having significant impact on soils, vegetation, and wildlife habitat. For these reasons, fire managers have great interest in preventive silviculture of forested landscapes to avoid the initiation and propagation of crown fires. The minimum conditions necessary to initiate and propagate crown fires are assumed to be strongly influenced by the stand structural variables canopy bulk density (CBD) and canopy base height (CBH). However, there is a lack of quantitative information on these variables and how to estimate them. To characterize the aerial fuel layers of Pinus radiata D. Don, the vertical profiles of canopy fuel in 180 sample plots of pure and even-aged P. radiata plantations were analysed. Effective CBD and CBH were obtained from the vertical profiles, and equations relating these variables to common stand variables were fitted simultaneously. Inclusion of the fitted equations in existing dynamic growth models, together with the use of current fire behaviour and hazard prediction tools, will provide a decision support system for assessing the crown fire potential of different silvicultural alternatives for this species.

Aim of study: To present the evolution of the current multi-objective Spanish National Forest Inventory (SNFI) through the assessment of different key indicators on challenging areas of the forestry sector.Area of study: Using information from the Second, Third and Fourth SNFI, this work provides case studies in Navarra, La Rioja, Galicia and Balearic Island regions and at national Spanish scale.Material and methods: These case studies present an estimation of reference values for dead wood by forest types, diameter-age modeling for Populus alba and Populus nigra  in riparian forest, the invasiveness of alien species and the invasibility of forest types, herbivore preferences and effects on trees and shrub species, the methodology for estimating cork production , and the combination of SNFI4 information and Airborne Laser Scanning datasets with the aim of updating forest-fire behavior assessment information with a high degree of accuracy.Main results: The results show the suitability and feasibility of the proposed methodologies to estimate the indicators using SNFI data with the exception of the estimation of cork production. In this case, additional field variables were suggested in order to obtain robust estimates.Research highlights: By broadening the variables recorded, the SNFI has become an even more important source of forest information for the development of support tools for decision-making and assessment in diverse strategic fields such as those analyzed in this study.

No abstract