Developing customized fuel models for shrub and bracken communities in Galicia (NW Spain).

Geospatial fire behaviour and fire hazard simulators, fire effects models and smoke emission software commonly use standard fuel models in order to simplify data collection and the inclusion of complex fuel scenarios. These fuel models are often mapped using remotely sensed data. However, given the great complexity of fuelbeds, with properties that vary widely in both time and space, the use of these standard fuel models can greatly limit accurate fuel mapping. This affects fuel hazard assessment, fuel reduction treatment plans, fire management decision-making and evaluation of the environmental impact of wildfire. In this study, we developed unique customized fire behaviour fuel models for shrub and bracken communities, by using k-medoids clustering analysis based on both fuel structural characteristics and potential fire behaviour. We used an original database of 722 destructive sample plots in nine different shrub and bracken communities covering the entire distribution area in Galicia (NW Spain), one of the regions in Europe most affected by forest fires. Measurements of cover, height and fuel fractions loads differentiated by size and vegetative state (live or dead) were used to estimate the potential rate of fire spread with five different models including fireline intensity, heat per unit area and the flame length for each sampling site and considering extreme environmental conditions. The optimal number of clusters was established by combining practical knowledge about the shrubland communities under study and their associated fire behaviour, with maximization of the mean value of the silhouette variable and minimization of the within-cluster sum of squares. The structural characteristics of the medoids derived from the analysis were associated with each of the proposed customized fuel models. Finally, a simple dichotomous classification based only on shrub height was developed to enable construction of spatially explicit fuel model maps based on remotely sensed data. Thus, the methodology applied allows generation of a more realistic representation of fuel distribution in the landscape, based on fuel structure measurements of natural regional ecosystems rather than on the use of standard models. We believe that the proposed methodology is generally applicable to communities composed of other shrub and fern species in different biogeographical regions.

Assessing the effect of pruning and thinning on crown fire hazard in young Atlantic maritime pine forests.

Management of fuel to minimize crown fire hazard is a key challenge in Atlantic forests, particularly for pine species. However, a better understanding of effectiveness of silvicultural treatments, especially forest pruning, for hazard reduction is required. Here we evaluate pruning and thinning as two essential silvicultural treatments for timber pine forests. Data came from a network of permanent plots of young maritime pine stands in northwestern Spain. Vertical profiles of canopy bulk density were estimated for field data and simulated scenarios of pruning and thinning using individual tree biomass equations. Analyses of variance were conducted to establish the influence of each silvicultural treatment on canopy fuel variables. Results confirm the important role of both pruning and thinning in the mitigation of crown fire hazard, and that the effectiveness of the treatments is related to their intensity. Finally, models to directly estimate the vertical profile of canopy bulk density (CBD) were fitted using the Weibull probability density function and usual stand variables as regressors. The models developed include variables sensitive to pruning and thinning interventions and provide useful information to prevent extreme fire behavior through effective silviculture.

Co-limitation towards lower latitudes shapes global forest diversity gradients.

The latitudinal diversity gradient (LDG) is one of the most recognized global patterns of species richness exhibited across a wide range of taxa. Numerous hypotheses have been proposed in the past two centuries to explain LDG, but rigorous tests of the drivers of LDGs have been limited by a lack of high-quality global species richness data. Here we produce a high-resolution (0.025° × 0.025°) map of local tree species richness using a global forest inventory database with individual tree information and local biophysical characteristics from ~1.3 million sample plots. We then quantify drivers of local tree species richness patterns across latitudes. Generally, annual mean temperature was a dominant predictor of tree species richness, which is most consistent with the metabolic theory of biodiversity (MTB). However, MTB underestimated LDG in the tropics, where high species richness was also moderated by topographic, soil and anthropogenic factors operating at local scales. Given that local landscape variables operate synergistically with bioclimatic factors in shaping the global LDG pattern, we suggest that MTB be extended to account for co-limitation by subordinate drivers.

Modelling the vertical distribution of canopy fuel load using national forest inventory and low-density airbone laser scanning data.

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.

Development of a Compatible Taper Function and Stand-Level Merchantable Volume Model for Chinese Fir Plantations.

Chinese fir (Cunninghamia lanceolata [Lamb.] Hook) is one of the most important plantation tree species in China with good timber quality and fast growth. It covers an area of 8.54 million hectare, which corresponds to 21% of the total plantation area and 32% of total plantation volume in China. With the increasing market demand, an accurate estimation and prediction of merchantable volume at tree- and stand-level is becoming important for plantation owners. Although there are many studies on the total tree volume estimation from allometric models, these allometric models cannot predict tree- and stand-level merchantable volume at any merchantable height, and the stand-level merchantable volume model was not seen yet in Chinese fir plantations. This study aimed to develop (1) a compatible taper function for tree-level merchantable volume estimation, and (2) a stand-level merchantable volume model for Chinese fir plantations. This "taper function system" consisted in a taper function, a merchantable volume equation and a total tree volume equation. 46 Chinese fir trees were felled to develop the taper function in Shitai County, Anhui province, China. A second-order continuous autoregressive error structure corrected the inherent serial autocorrelation of different observations in one tree. The taper function and volume equations were fitted simultaneously after autocorrelation correction. The compatible taper function fitted well to our data and had very good performances in diameter and total tree volume prediction. The stand-level merchantable volume equation based on the ratio approach was developed using basal area, dominant height, quadratic mean diameter and top diameter (ranging from 0 to 30 cm) as independent variables. At last, a total stand-level volume table using stand basal area and dominant height as variables was proposed for local forest managers to simplify the stand volume estimation.

Crecimiento de Ocotea cernua (Lauraceae) en bosques aluviales inundables de la Amazonía peruana / Growth of Ocotea cernua (Lauraceae) in Peruvian Amazon floodplain forests

Ocotea cernua (Nees) Mez, "moena negra", es una especie comercial que se desarrolla en los bosques del llano aluvial inundable de la Amazonía peruana. Este estudio, proporciona información sobre su crecimiento, y que puede utilizarse en el manejo de la especie. Se analizó la abundancia y estructura de O. cernua en nueve parcelas permanentes (100 m x 100 m) y 24 transectos (40 m x 100 m). El análisis de los registros sobre crecimiento en diámetro, mostró que el incremento anual medio y el incremento anual máximo, alcanzan un valor máximo de 9.5 y 17.4 mm/año, ambos en la clase diamétrica de 25 a 30 cm. Tomando como base ambos incrementos, el tiempo necesario para que un árbol alcance diámetros >30 cm DAP, sería de 60 y 34 años, respectivamente. Basado en factores de competencia entre árboles, el modelo de crecimiento ajustado estima que la tasa máxima de crecimiento en diámetro anual es 2.10, 1.28 y 0.50 cm para árboles con baja, media y alta competencia. Esta tasa máxima de crecimiento ocurre cuando los árboles cuentan con DAP que oscilan entre 21.10, 20.28 y 20.50 cm, para baja, media y alta competencia, respectivamente; sin embargo, el tiempo que requiere un árbol para obtener dichos diámetros varía enormemente, con valores de 12.31 cm para baja competencia, 20.35 para media competencia y 54.51 años para alta competencia.

Ocotea cernua (Nees) Mez "moena negra" is a commercial species that thrives in alluvial floodplain forests in the Peruvian Amazon. This study presents information about diameter growth of O. cernua and provides useful information for its forest management. The stand density and structure was analysed in nine permanent sample plots (100 m x 100 m) and 24 transects (40 m x 100 m). Analysis of tree diameters at different time indicates maximum values of 9.5 and 17.4 mm/year for the average annual diameter increment and the maximum annual diameter increment respectively; both into 25 ‒ 30 cm diameter classes. Considering this increments, a tree will reach a diameter higher than 30 cm DAP, in 60 to 34 years respectively. Estimations of the adjusted model showed the maximum annual growth increment estimated in 2.10, 1.28 and 0.50 cm for trees with low, medium and high competition, corresponding to trees with DBHs of 21.10, 20.28 and 20.50 cm for trees with low, medium and high competition, respectively. However, the time required to reach such diameters is highly variable with values of 12.31, 20.35 and 54.51 years, respectively.