Publications

A core process in forestry planning corresponds to the design of optimal harvesting policies along with road network layouts. In the most common setting, decision makers seek solutions that maximize the profit of the forest while respecting operative and market constraints. Due to the long-term nature of the industry, the inherent uncertainty in both forest growth and market conditions should be taken into account. Nowadays, forest planning must target sustainable management; the maximization of carbon sequestration and the minimization of land erosion are two common environmental goals. The planning challenge addressed in this paper integrates uncertainty of future forest growth and timber prices with the need for considering three criteria; net-present value, carbon sequestration, and land erosion caused by the road construction within the forest. By using mathematical programming tools and stochastic optimization techniques, we develop a stochastic multicriteria model that enables decision makers to have not only one, but a pool of long term planning policies. Moreover, a risk-averse variant of the framework is also considered. To the best of our knowledge, this is the first time that this type of forestry planning setting, which response to the new challenges of the industry, is addressed. The proposed tool is used on a eucalyptus forest located in Portugal; the obtained results show the benefit of the proposed framework for producing a pool of sustainable forest plans with efficient trade-offs among the three considered criteria.

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.

An approach is proposed for incorporating the variations in timber growth and yield due to climate change uncertainty into the forest harvesting decision process. A range of possible climate scenarios are transformed by a forest growth and yield model into tree growth scenarios, which in turn are integrated into a multistage stochastic model that determines the timber cut in each future period so as to maximize net present value over the planning horizon. For comparison purposes, a deterministic model using a single average climate scenario is also developed. The performance of the deterministic and stochastic formulations are tested in a case study of a medium-term forest planning problem for a Eucalyptus forest in Portugal where climate change is expected to severely impact production in the coming years. Experiments conducted using 32 climate scenarios demonstrate the stochastic model’s superior results in terms of present value, particularly in cases of relatively high minimum timber demand. The model should therefore be useful in supporting forest planners’ decisions under climate uncertainty.

Cork oak (Quercus suber L.) and holm oak (Quercus rotundifolia) ecosystems are characteristic of Mediterranean forestry in Portugal. Even though cork is the most valuable product, these ecosystems provide multiple products and services. Assessing trade-offs between multiple goals is thus critical for the effectiveness of oak ecosystem management planning. This paper focuses on the development of a decision support system for oak ecosystems’ scenario analysis including multiple criteria. It includes an innovative decision support systems (DSS) functionality to assess trade-offs between the criteria that may support negotiation and consensus building between decision-makers and forest stakeholders. Specifically, a module that encapsulates the Feasible Goals Method/Interactive Decision Maps (FGM/IDM) technique is developed for interactive visualization of the Pareto frontier. The Pareto frontier illustrates the degree to which improving one particular criterion requires accepting sacrifices in the achievements of others. It thus provides information about trade-offs between competing decision-makers’ preferences. Results are discussed for a large-scale application encompassing over 1 million ha of cork and holm oak forest ecosystems in Southern Portugal. This study demonstrates the potential of the new DSS functionality to enhance multi-objective forest planning, namely by facilitating participation by stakeholders and providing transparency to the decision-making processes. - See more at: http://www.mdpi.com/1999-4907/6/1/65/htm#sthash.lYuaqNt5.dpuf