Suchergebnisse

The aim of this paper is to present approaches to optimize stand-level, short-rotation coppice management planning, taking into account uncertainty in stand growth due to climate change. The focus is on addressing growth uncertainty through a range of climate scenarios so that an adaptive capacity may be possible and the vulnerability of the stand to climate change may be reduced. The optimization encompasses finding both the harvest age in each cycle and the number of coppice cycles within a full rotation that maximize net present revenue. The innovation lies in the combination of the process-based model (Glob3PG) with two dynamic programming (DP) approaches. The former is able to project growth of eucalypt stands under climate change scenarios. The innovative approaches are thus influential to define the management policy (e.g., stool thinning, number of coppice cycles, and cycle length) that maximizes net present revenue taking into account uncertainty in forest growth due to climate change. In both approaches, the state of the system is defined by the number of years since plantation, whereas DP stages are defined by the cumulative number of harvests. The first approach proposes the optimal policy under each climate change scenario at each state. The second approach addresses further situations when the climate scenario is unknown at the beginning of the planning horizon. Both help address uncertainty in an adaptive framework, as a set of readily available options is proposed for each scenario. Results of an application to a typical Eucalyptus globulus Labill. stand in central Portugal are discussed. ; Le but de cet article est de présenter des approches pour optimiser la planification de l'aménagement de taillis en révolution courte à l'échelle du peuplement en tenant compte de l'incertitude entourant la croissance du peuplement à cause des changements climatiques. L'accent est mis sur l'incertitude de la croissance par le biais d'une gamme de scénarios climatiques de façon à rendre possible une capacité adaptative, ce qui peut réduire la vulnérabilité du peuplement aux changements climatiques. L'optimisation comprend la recherche de l'âge de récolte à chaque rotation et le nombre de rotation de taillis à l'intérieur d'une révolution complète qui maximise les revenus actualisés nets. L'innovation réside dans la combinaison du modèle fondé sur les processus (Glob3PG) et de deux approches de programmation dynamique (PD). Le modèle est en mesure de projeter la croissance de peuplements d'eucalyptus selon des scénarios de changements climatiques. Les approches novatrices permettent donc d'influencer la définition de la politique d'aménagement (p. ex. : l'éclaircie des rejets, le nombre de rotation de taillis et la durée de la rotation) qui maximise les revenus actualisés nets en tenant compte de l'incertitude de la croissance forestière à cause des changements climatiques. Dans les deux approches, l'état du système est défini par le nombre d'années depuis la plantation alors que les stades de PD sont définis par le nombre cumulatif de récoltes. La première approche propose la politique optimale pour chaque scénario de changements climatiques à chaque état. La deuxième approche traite de situations non couvertes, lorsque le scénario climatique est inconnu au début de l'horizon de planification. Les deux approches aident à tenir compte de l'incertitude dans un cadre adaptatif puisqu'un ensemble d'options facilement disponibles est proposé pour chaque scénario. Nous discutons des résultats d'une application dans un peuplement typique d'Eucalyptus globulus Labill du centre du Portugal. ; This study was partially supported by the projects UID/MAT/04561/2013, funded by the Portuguese Foundation for Science and Technology (FCT, Fundação para a Ciência e a Tecnologia). Furthermore, this research has received funding from the European Union's Seventh Programme for research, technological development and demonstration under grant agreements (i) Nr 282887 INTEGRAL"Future-Oriented Integrated Management of European Forest Landscape" and (ii) Nr PIRSES-GA-2010-269257 (ForEAdapt, FP7-PEOPLE-2010-IRSES). It was also partially supported by Project PTDC/AGR-FOR/4526/2012 Models and Decision Support Systems for Adressing Risk and Uncertainty in Forest Planning (SADRI). Jordi Garcia-Gonzalo was supported by a "Ramón y Cajal" research contract from th MINECO (Ref. RYC-2013-14262).

Assessing impacts of management strategies may allow designing more resistant forests to wildfires. Planning-oriented models to predict the effect of stand structure and forest composition on mortality for supporting fire-smart management decisions, and allowing its inclusion in forest management optimization systems were developed. Post-fire mortality was modeled as a function of measurable forest inventory data and projections over time in 165 pure and 76 mixed forest stands in Portugal, collected by the 5th National Forest Inventory plots (NFI) plus other sample plots from ForFireS project, intercepted within 2006–2008 wildfire perimeters' data. Presence and tree survival were obtained by examining 2450 trees from 16 species one year after the wildfire occurrence. A set of logistic regression models were developed under a three-stage modeling system: firstly multiple fixed-effects at stand-level that comprises a sub-model to predict mortality from wildfire; and another for the proportion of dead trees on stands killed by fire. At tree-level due to the nested structure of the data analyzed (trees within stands), a mixed-effect model was developed to estimate mortality among trees in a fire event. The results imply that the variation of tree mortality decreases when tree diameter at breast height increases. Moreover, the relative mortality increases with stand density, higher altitude and steeper slopes. In the same conditions, conifers are more prone to die than eucalyptus and broadleaves. Pure stands of broadleaves exhibit noticeably higher fire resistance than mixed stands of broadleaves and others species composition. ; This researchwas supported by ProjectUID/AGR/00239/2013, PTDC/AGR-CFL/64146/2006 "Decision support tools for integrating fire and forest management planning" and project FIRE-ENGINE "Flexible Design of Forest Fire Management Systems" (MIT/FSE/0064/2009), both funded by the Portuguese Science Foundation (FCT), and contributes to the activities of the ALTERFOR Project "Alternative models and robust decision-making for future forest management"—H2020-ISIB-2015-2/grant agreement No. 67654, funded by European Union Seventh Framework Programme. This research has received also funding from the European Union's H2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No. 691149 (SuFoRun). The authors would like to thank the Portuguese Science Foundation for funding the doctoral scholarships of Brigite Botequim (SFRH/ BD/44830/2008) and the Post Doc grant SFRH/BPD/96806/2013 of Susete Marques. Researcher Jordi Garcia-Gonzalo was supported by a "Ramon y Cajal" research contract from the MINECO (Ref. RYC-2013-14262) and has received funding from CERCA Programme / Generalitat de Catalunya. In addition, the authors wish to acknowledge the Portuguese Forest Service (ICNF) for supplying the perimeters of wildfires and NFI Databases and ForFireS Project for providing the inventory Databases.

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. ; This work was supported by the Seventh Framework Program of the EC Grant Agreement No. 226544. We thank the MINECO "Ramón y Cajal" (Ref. RYC-2013-14262) for funding the research contract of JGG. KK was funded by the project Resilient Forests (KB-29-009-003) of the Dutch Ministry of Economic Affairs. BJT and JBJ acknowledge support from the Danish National Research Foundation (DNRF Grant No 96). This research has received also funding from the European Union's H2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No. 691149 (SuFoRun).

For forest sustainability and vulnerability assessment, the landscape scale is considered to be more and more relevant as the stand level approaches its known limitations. This review, which describes the main forest landscape simulation tools used in the 20 European case studies of the European project "Future-oriented integrated management of European forest landscapes" (INTEGRAL), gives an update on existing decision support tools to run landscape simulation from Mediterranean to boreal ecosystems. The main growth models and software available in Europe are described, and the strengths and weaknesses of different approaches are discussed. Trades-offs between input efforts and output are illustrated. Recommendations for the selection of a forest landscape simulator are given. The paper concludes by describing the need to have tools that are able to cope with climate change and the need to build more robust indicators for assessment of forest landscape sustainability and vulnerability. ; The INTEGRAL project has received funding from the European Union's Seventh Programme for research, technological development and demonstration under grant agreement No. 282887. http://www. integral-project.eu/. Moreover, financial support by the Transnational Access to Research Infrastructures activity in the 7th Framework Programme of the EC under the Trees4Future project (No. 284181) for conducting the research is gratefully acknowledged. This research has also received funding from the European Union H2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 691149 (SuFoRun). Researcher Jordi Garcia-Gonzalo was supported by a "Ramon y Cajal" research contract from the MINECO (Ref. RYC-2013-14262) and has received funding from CERCA Programme/Generalitat de Catalunya. This paper could be achieved thanks to support of EFIATLANTIC donors: Conseil regional d'Aquitaine, Ministère de l'agriculture et de la forêt.