Search

Density-dependent mortality occurs in the evolution of even-aged populations when these approach crown closure age. This density-dependent mortality is regulated by the so-called "3/2 power law of self-thinning" that assumes a constant slope for the line relating the log of stand density with the log of the average tree size, the self-thinning line or maximum size–density relationship, MSDR. A good estimate of the self-thinning line is therefore an essential component to any forest growth model. Two concepts for the MSDR have emerged: (1) a static upper limit for the species; and (2) a dynamic self-thinning line influenced by several factors (e.g., management techniques, site quality and/or genetics). The objective of this study was to estimate a new static self-thinning line based on the quadratic mean diameter at breast height (Reineke's self-thinning line) for the generalized use in maritime pine growth models in Portugal. Data from 41 observations obtained in nine long-term permanent experimental trials of maritime pine species were carefully selected from a data set of 186 plots as being under self-thinning. Two methods were used: OLS and mixed linear models. An exploratory analysis on the impact of each environmental variable on the slope and intercept of the self-thinning line led to the selection of a subset of environmental variables later used in an all possible regressions algorithm to find the subsets leading to the lowest values of Akaike information criterion (AIC). The OLS procedure showed that the differences between the plots could be explained by site index, by climate variables (e.g., evaporation or climatic indices) and the use of more than one covariable slightly improved the fit. Nevertheless, the best MSDR line fitted with mixed linear models (ln N = 12.97158 − 1.83926 ln dg) having the plot random effect in the intercept, largely outperformed the best OLS model and is therefore recommended for generalized use in forest growth models. [ABSTRACT FROM AUTHOR]

The necessity for accurate biomass estimates is greater than ever for the sustainable management of forest resources, which is an increasingly pressing matter due to climate change. The most used method to estimate biomass for operational purposes is through allometric equations. Typically, each country develops their own models to be applied at the local scale because it is more convenient. But, for Quercus suber, a joint regional model can be more beneficial, since the species is distributed across the Mediterranean and is challenging to account for due to felling limitations and the nature of mature cork biomass itself. We found that these characteristics are reflected in the biomass datasets and compatibility was, perhaps, the largest impediment to such a model. The use of dummy variables to differentiate between countries, as well as compromises in the limits of biomass compartments, allowed us to develop two joint models to estimate aboveground biomass in Portugal, Spain and Tunisia. One model as a function of diameter and another as a function of diameter and total tree height. In addition, we developed a separate model for roots (modelling efficiency of fitting = 0.89), since it was not possible to assure additivity of the whole tree. All coefficients were estimated using Seemingly Unrelated Regressions (SUR) and model fitting assured additivity in the aboveground compartments—leaves and woody biomass (modelling efficiency of fitting = 0.89 and 0.93, respectively). This work proves that it is possible to have a biologically sound and efficient model for the three countries, despite differences in the observed allometric patterns. [ABSTRACT FROM AUTHOR]

Cork oak stands are one of the major sources of income from Portuguese Mediterranean forests. Future climate is projected to increase temperatures, reduce precipitation and decrease current forests' productivity and therefore, adapting management, is a key strategy to mitigate impacts of future climate on cork supply. The central objective of this research was to compare conventional and adaptive management regimes under scenarios of climate change. The adaptive management focussed on adopting optimal harvest schedules while considering different management objectives. The study focused on the Chamusca region, one of the most productive areas of cork, and considered four distinct spatial scales for analysis. For each scale, the management objective was defined according to field information and considered the maximization of cork production while targeting different cork harvesting flows: (a) more frequent and regular or (b) less frequent and concentrated. A forest growth model was used to simulate climate change impact on future yield of cork oak stands under different forest management alternatives. A mixed integer programming model was developed to find the most adequate cork debarking cycle calendar for cork oak stands. Our results suggest that (1) business as usual management under climate change scenarios could decrease cork supply and carbon stock in the tree component of the forests by up to 20 and 30 %, respectively, (2) the development of adaptive management strategies, including cork extraction schedule optimization, to address climate change has advantages over traditional practices and (3) may contribute further to increase cork production (up to double productivity in mid-long term) while addressing concerns with the regulation of cork extraction flows through the adaptation of debarking periods. The mixed integer programming allowed the spatial visualization of the debarking cycle delay. Furthermore, results underline the relevance of an approach to develop adaptive management strategies that can consider different management goals, with different constraints to address climate change. [ABSTRACT FROM AUTHOR]

Assessment of forest fuel loading is a prerequisite for most fire management activities. However, the inclusion of shrub biomass in forest planning has been hindered by the inability to predict its growth and accumulation. The main objective of this study was to model shrub biomass over time under a tree canopy with the aim of including shrub management in fire risk mitigation plans. To this purpose, data was obtained from the 4th and 5th Portuguese National Forest Inventories. Five biologically realistic models were built to describe shrub biomass accumulation in Portuguese forests. The selected model indicates that maximum biomass is affected by stand basal area and the percentage of resprouting shrub species in the stand. Biomass growth rate was clearly affected by the regeneration strategies of shrubs in combination with climatic conditions (mean annual temperature). The model can be used in the accumulation form for initialization purposes or in one of the two alternative difference forms to project observed shrub biomass. The model proposed in this study facilitates the inclusion of shrub biomass in forest growth simulations, and will contribute to more accurate estimates of fire behavior characteristics and stored carbon. This is essential to improve decision-making in forest management plans that integrate fire risk, namely to schedule understory fuel treatments. [ABSTRACT FROM AUTHOR]

This paper presents a model to predict annual wildfire risk in pure and evenaged eucalypt stands in Portugal. Emphasis was in developing a management- oriented model, i.e., a model that might both: (a) help assess wildfire occurrence probability as a function of readily available forest inventory data; and (b) help predict the effects of management options (e.g., silvicultural treatments) on the risk of fire in eucalypt stands. Data from both the 1995/1998 and the 2005/2006 Portuguese National Forest Inventories as well as wildfire perimeters' data were used for modeling purposes. Specifically, this research considered 1122 inventory plots with approximately 1.2 million trees and 85 wildfire perimeters. The model to predict the probability of wildfire occurrence is a logistic function of measurable and controllable biometric and environmental variables. Results showed that wildfire occurrence probability in a stand increases with the ratio basal area/quadratic mean diameter and with the shrubs biomass load, while it decreases with stand dominant height. They further showed that the probability of wildfire occurrence is higher in stands that are over 1 Km distant from roads. These results are instrumental for assessing the impact of forest management options on wildfire risk levels thus helping forest managers develop plans that may mitigate wildfire impacts. [ABSTRACT FROM AUTHOR]

The wildfire regime in Portugal has been responsible for millions of hectares of burnt area, and Alvares parish is no exception. In 2017, a severe wildfire burnt 60% of its area. Land abandonment has been increasing since the mid 20th century, and a large fraction of the forest area belongs to quasi-absent landowners. This has given rise to large, almost unbroken expanses of undermanaged forests that, in combination with rugged topography, originates a landscape prone to large, intense wildfires. Thus, a change in landscape composition and structure capable of reducing flammability and promoting fuel discontinuity is urgently needed. A fire spread simulator and a forest growth simulator were combined to show the impact of improving management at landscape level. It was assumed that the probability of large wildfires may be reduced by setting aside forest area for the implementation of a fuel break network (FBN) and increasing the area under sustainable forest management. Three levels of management intensity were simulated by restricting the area of Quasi-absent non-industrial owners to 34.5%, 20.1%, and 8.5% of the Alvares forest area, in favor of increasing the area of active and semi-active non-industrial owners (current, moderate, and high management scenarios). Different FBN extents, representing four levels of network implementation priority were combined with the management levels, resulting in 12 scenarios. To evaluate the impact of fire, simulations assuming no-fire, no-FBN, and current management intensity were performed, whereas the impact of operation costs was assessed assuming reduced costs for silvicultural operations. Per hectare simulations were then scaled up to the parish level and volume harvested and net present values were used to compare the management improvement scenarios. Results showed that fire has major repercussions on forest income, but these impacts can be minimized. Intensifying forest management and implementing the first priority FBN segments originated substantial improvements in financial outcome from timber production, close to those obtained for the full FBN implementation. Results also evidenced contrasting contributions from industrial and non-industrial owners with the later evidencing unbalanced cash-flows derailing the possibility for interesting forest incomes. The coupling of fire and forest growth simulations can be an interesting approach to assess the impact of different management and policy scenarios and inform policies. [ABSTRACT FROM AUTHOR]