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Food security, climate change mitigation, and land use challenges are interlinked and need to be considered simultaneously. One possible solution is sustainable intensification, which is the practice of increasing food production per area of land whilst also reducing the environmental impacts associated with this. Agroforestry has been stated to be a practice that meets this definition. In this study, a new methodology is presented to assess the potential of different management options as sustainable intensification practices. The methodology is based on comparing the carbon emissions associated with the production of food and the carbon sequestered for that same activity for a particular quantity of food produced over a specific area and over a specific time. The resulting indicator, the "carbon balance" is the difference between the greenhouse gasses emitted (considered as negative values) and carbon sequestered (positive values) estimated in Mg CO2eq per Mg of food produced on one hectare of land for one year. The carbon balance quantifies the global warming potential associated with sustainable intensification by integrating a process-based model with life cycle analysis and is able to estimate above- and below-ground biomass and soil carbon content. This methodology is tested in Portugal for wheat production under crop monoculture and agroforestry systems. The results show agroforestry to be a suitable practice for sustainable intensification compared to a crop monoculture as it just slightly decreased wheat yields whilst providing a positive carbon balance from year 50 onwards of approximately 1 Mg of CO2eq sequestered per Mg of wheat produced. [ABSTRACT FROM AUTHOR]

A generalized non-linear tree crown diameter model was developed with the aim of allowing the computation of tree crown diameter over a large range of tree dimensions, and allowing its inclusion in forest growth and yield models. The model was formulated to provide biological meaning to the predicted values. Due to the nested structure of the data analyzed (trees within stands), both mixed- and fixed-effect models were developed. Since tree crown diameter is not frequently measured in forest inventories, the validation of the mixed model was carried out by considering the population specific response. The results demonstrate that when the measurements required for the mixed model calibration are not available, the use of the fixed effect model results in less biased and more accurate estimates. The fixed model was applied to the data from the two last Portuguese National Forest Inventories (NFI) to analyze the change in stand crown cover and assess the stocking evolution of cork oak stands in Portugal between 1996 and 2006. Results showed an increase in the frequency of stands with crown cover lower than 20%, as well as a decrease in the frequency of stands with crown cover between 20 and 40%. Average crown cover values were significantly different in the two NFI, with a decrease from 28.0 to 26.5% over the considered period. [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]