Jordi Garcia-Gonzalo

Characterization of wildfires in Portugal

Forest fires severity has increased in Portugal in the last decades. Climate change scenarios suggest the reinforcement of this severity. Forest ecosystem managers and policy-makers thus face the challenge of developing effective fire prevention policies. The characterization of forest fires is instrumental for meeting this challenge. An approach for characterizing fire occurrence in Portugal, combining the use of geographic information systems and statistical analysis techniques, is presented. Emphasis was on the relationships between ecological and socioeconomic features and fire occurrence. The number and sizes of wildfires in Portugal were assessed for three 5-year periods (1987–1991, 1990–1994, and 2000–2004). Features maps were overlaid with perimeters of forest fires, and the proportion of burned area for each period was modeled using weighted generalized linear models (WGLM). Descriptive statistics showed variations in the distribution of fire size over recent decades, with a significant increase in the number of very large fires. Modeling underlined the impact of the forest cover type on the proportion of area burned. The statistical analysis further showed that socioeconomic features such as the proximity to roads impact the probability of fires occurrence. Results suggest that this approach may provide insight needed to develop fire prevention policies.

The effects of forest structure on the risk of wind damage at a landscape level in a boreal forest ecosystem

Abstract• The aim of this work was to analyze how the forest structure affects the risk of wind damage at the landscape level in a boreal forest.• This was done by employing: (i) Monte Carlo simulation technique for generating landscapes with different age class distributions, proportions of open areas (gaps), and tree species composition; and (ii) a mechanistic wind damage model, HWIND, for predicting the critical wind speeds at downwind stand edges of open areas (gaps) for risk consideration. The level of risk of wind damage observed at the landscape level was significantly affected by the presence of gaps and old stands. Even a slight increase in the proportion of gap areas or older stands had a significant impact on the total length of edges at risk. As a comparison, variation in species composition (Scots pine and/or Norway spruce) had much smaller impact on the risk of damage.• In conclusion, the effects of forest structure on the risk of wind damage should especially be considered by forest managers in day-to-day forest planning in order to reduce the risk of wind damage both at the stand and landscape level.Résumé• L’objectif de ce travail était d’analyser comment la structure forestière affecte le risque de dommages causés par le vent à l’échelle du paysage dans une forêt boréale.• C’est objectif a été atteint par l’emploi : (i) de la technique de simulation de Monte Carlo pour générer des paysages de différentes distributions de classe d’âge, de proportions des zones ouvertes (trouées), et de composition des espèces d’arbres ; et (ii) d’un modèle mécaniste de dommages causés par le vent, HWIND, pour la prédiction des vitesses de vent critiques au niveau des lisières sous le vent des zones ouvertes (trouées) en relation avec les risques. Le niveau de risque de dommages causés par le vent observé à l’échelle du paysage a été significativement affecté par la présence de trouées et de vieux peuplements. Une augmentation même légère dans la proportion de trouées ou de vieux peuplements a eu un impact significatif sur la longueur totale des lisières à risque. À titre de comparaison, la variation dans la composition des espèces (pin sylvestre et/ou épicéa) a eu beaucoup moins d’impact sur le risque de dommages.• En conclusion, les effets de la structure de la forêt sur le risque de dommages causés par le vent devraient être examinées en particulier par les gestionnaires forestiers pour une planification des opérations forestière au jour le jour, afin de réduire le risque de dommages causés par le vent à la fois au niveau du peuplement et au niveau du paysage.

Are forest disturbances amplifying or canceling out climate change-induced productivity changes in European forests?

Recent studies projecting future climate change impacts on forests mainly consider either the effects of climate change on productivity or on disturbances. However, productivity and disturbances are intrinsically linked because 1) disturbances directly affect forest productivity (e.g. via a reduction in leaf area, growing stock or resource-use efficiency), and 2) disturbance susceptibility is often coupled to a certain development phase of the forest with productivity determining the time a forest is in this specific phase of susceptibility. The objective of this paper is to provide an overview of forest productivity changes in different forest regions in Europe under climate change, and partition these changes into effects induced by climate change alone and by climate change and disturbances. We present projections of climate change impacts on forest productivity from state-of-the-art forest models that dynamically simulate forest productivity and the effects of the main European disturbance agents (fire, storm, insects), driven by the same climate scenario in seven forest case studies along a large climatic gradient throughout Europe. Our study shows that, in most cases, including disturbances in the simulations exaggerate ongoing productivity declines or cancel out productivity gains in response to climate change. In fewer cases, disturbances also increase productivity or buffer climate-change induced productivity losses, e.g. because low severity fires can alleviate resource competition and increase fertilization. Even though our results cannot simply be extrapolated to other types of forests and disturbances, we argue that it is necessary to interpret climate change-induced productivity and disturbance changes jointly to capture the full range of climate change impacts on forests and to plan adaptation measures.

A web-based ToolBox approach to support adaptive forest management under climate change

The design and implementation of the adaptive forest management (AFM) ToolBox is presented. Design principles derived from previous experiences in decision support system (DSS) development include support for (1) modularity, (2) accessibility via the Internet, (3) inclusion of different types of knowledge and information, (4) the use of different data sources, and (5) specific problem types. As major components of the AFM ToolBox DataBase, Vulnerability Assessment Tools (single user version, group mode) and an optimization tool to generate optimized management plans at the level of management units or landscapes are highlighted. A key feature is the distinction of two archetypical user profiles (manager, analyst). The AFM ToolBox is evaluated against eight criteria for the assessment of DSS. It is concluded that the ToolBox approach setting focus on modularity while avoiding to over-emphasis technical integration provides the right frame to secure the flexibility regarding tools and decision-making processes which is mandatory if a DSS should be taken up by practice.

Sustainability impact assessment of increasing resource use intensity in forest bioenergy production chains.

Changing forest management practices towards more intensive biomass utilization for energy purposes will affect the sustainability of resource management. The Tool for Sustainability Impact Assessment was applied to evaluate the environmental, social, and economic sustainability impacts of the stepwise increased extraction of forest biomass of three typical Scandinavian Scots pine bioenergy production chains (BPCs). The assessed sources of the woody biomass were pellets as a by‐product of the sawmilling industry, wood chips deriving from early whole‐tree harvesting, and residues from final cuttings. Three commercially practiced BPCs were compared. By the additional extraction of biomass for heat production, the employment increased by 0.6 person‐years 1000 m−3 solid wood chips, while there was a decrease in the costs and greenhouse gases emitted per unit of heat consumed. Furthermore this practice did not only add positive socio‐economic but also positive environmental impacts on sustainability, particularly on the greenhouse gas balance and the energy efficiency ratio (input to output ratio along the BPC), which was determined to be 1–24. Potential drawbacks, on the other hand, include decreasing nutrient returns to the soil and the associated potential reduction in future stand productivity. Fertilization might be needed to maintain sustainable forest growth on poor sites.

Institutional factors and opportunities for adapting European forest management to climate change

Abstract Despite the fact that the institutional environment is acknowledged to influence the implementation of regional adaptations of forest management to climate change, there are few empirical studies addressing the institutional factors and opportunities of adaptation. Using Ostrom’s institutional analysis and development framework, we aimed to identify : (1) the critical and distinctive characteristics of the forest resource and institutional context that may determine how climate change-adaptive forest management measures are implemented and (2) the opportunities for implementing the planned adaptation measures. The analysis is performed on ten European case study regions which differed in many resource-dependent factors, policy arena factors and incentives for changes. The main factors influencing the adaptation are the ownership pattern, the level of policy formation and the nature of forest goods and services. Opportunities for adaptation are driven by the openness of the forest management planning processes to the stakeholders participation, the degree to which business as usual management is projected to be non-satisfactory in the future, and by the number and nature of obstacles to adaptation. Promoting local self-governance mechanisms and the participation of the external stakeholders in forest management planning or in the regional forest or climate change policy adaptation may be a way of overcoming path dependency, behavioural obstacles and potential policy failures in implementing adaptation. The study argues that both climate change belief systems and political participation are important to explain adaptation to climate change when multiple decision-making levels are at stake.

Effects of climate change on optimised stand management in the boreal forests of central Finland

In boreal conditions, climate change is expected to increase mean annual temperature and precipitation, increasing forest growth and productivity in managed forests. In this study, we aimed at finding out how climate change affects the optimal management of Scots pine-, Norway spruce- and silver birch-dominated stands on sites of varying fertility (high-herb, mesic and sub-xeric sites) in the boreal forests of central Finland. The objective function was to maximise net present value (NPV), considering the future incomes from timber sales and costs of forest operations. The results showed that under the gradually changing climate, the optimised management schedules differed from those observed under the current climate. In Norway spruce- and birch-dominated stands, cuttings were done earlier under the changing climate than under the current climate, while in Scots pine-dominated stands they were delayed under the changing climate. The optimised management schedules also varied, depending on tree species and site fertility types. Under the changing climate, both timber production and NPV increased compared to the current climate, regardless of species and site fertility type.

A multicriteria optimization model for sustainable forest management under climate change uncertainty:an application in Portugal

Abstract We propose a multicriteria decision-making framework to support strategic decisions in forest management, taking into account uncertainty due to climate change and sustainability goals. In our setting, uncertainty is modeled by means of climate change scenarios. The decision task is to define a harvest scheduling that addresses, simultaneously, conflicting objectives: the economic value of the strategy, the carbon sequestration, the water use efficiency for biomass production and the runoff water, during the whole planning horizon. While the first objective is a classical managerial one, the later tree objectives aim at ensuring the environmental sustainability of the forest management plan. The proposed framework is a combination of Goal Programming and Stochastic Programming. Depending on the decision-maker preferences, the model produces harvest scheduling policies that yield different trade-offs among the conflicting criteria. Furthermore, we propose the incorporation of a risk-averse component in order to improve the performance of the obtained policies with respect to their economical value. This novel approach is tested on a real forest, located in central Portugal, which is comprised of a large number of stands (aggregated into 21 strata), climate change is modeled by 32 scenarios, and a planning horizon of 15 years is considered. The obtained results show the capacity of the designed framework to provide a pool of diverse solutions with different trade-offs among the four criteria, giving to the manager the possibility of choosing a harvesting policy that meets her/his requirements.

Coupling fire behaviour modelling and stand characteristics to assess and mitigate fire hazard in a maritime pine landscape in Portugal

Silvicultural models are often developed and applied without due consideration of fire modelling. Yet, this information is important for designing treatment options to lower fire hazard. We used the FlamMap software to assess potential fire behaviour under extreme fire weather conditions within a 10,881-ha maritime pine landscape in central Portugal, the Leiria National Forest. Models describing fire hazard and providing information to assess potential benefits of stand-level fuel treatments were developed based on fire behaviour simulation. These models use as predictors stand variables and may assist forest managers in identifying hazardous areas in pine forests. Models were built from a database comprising 94,207 unique combinations of variables to detect significant fire-landscape interactions between stand-level features and fire behaviour. A set of compatible models that express crown fire likelihood and tree mortality were fitted using logistic regression. Additionally, classification tree analysis was used to model the type of fire, fire suppression difficulty, and tree mortality. The results highlight the potential of this methodology to explain the influences of fuel- and stand-related variables on fire hazard. This approach allowed the identification of straightforward discrimination rules to implement fuel treatments that prevent crown fires, enhancing the effectiveness of fire suppression and thereby reducing fire damage in fire-prone forest stands. Results further allow developing specific hazard-reduction prescriptions based on common forest metrics without resorting to advanced simulation modelling.

A framework for modeling adaptive forest management and decision making under climate change

Adapting the management of forest resources to climate change involves addressing several crucial aspects to provide a valid basis for decision making. These include the knowledge and belief of decision makers, the mapping of management options for the current as well as anticipated future bioclimatic and socioeconomic conditions, and the ways decisions are evaluated and made. We investigate the adaptive management process and develop a framework including these three aspects, thus providing a structured way to analyze the challenges and opportunities of managing forests in the face of climate change. We apply the framework for a range of case studies that differ in the way climate and its impacts are projected to change, the available management options, and how decision makers develop, update, and use their beliefs about climate change scenarios to select among adaptation options, each being optimal for a certain climate change scenario. We describe four stylized types of decision-making processes that differ in how they (1) take into account uncertainty and new information on the state and development of the climate and (2) evaluate alternative management decisions: the “no-change,” the “reactive,” the “trend-adaptive,” and the “forward-looking adaptive” decision-making types. Accordingly, we evaluate the experiences with alternative management strategies and recent publications on using Bayesian optimization methods that account for different simulated learning schemes based on varying knowledge, belief, and information. Finally, our proposed framework for identifying adaptation strategies provides solutions for enhancing forest structure and diversity, biomass and timber production, and reducing climate change-induced damages. They are spatially heterogeneous, reflecting the diversity in growing conditions and socioeconomic settings within Europe.