PRR Project

Summary

Tasks:The Researcher will develop decision support-based research to address management planning of forest ecosystems. This will encompass the integration of ecological data and models developed by CEF with socio-economic data (e.g., stakeholders’ and decision-makers’ preferences and objectives, prices, discount rate) within resource capability models of forested landscapes. The emphasis will be both on model building and model solving to generate and address management planning scenarios in a wide range of decision-making contexts, e.g., from single to multiple objectives, from traditional timber supply to a plethora of ecosystem services, from a stand to a landscape spatial scale, from an operational to a strategic temporal horizon, from a-spatial to spatial optimization concerns. The researcher will explore and develop mathematical programming (e.g. multiple-objective programming, mixed integer programming), multiple attribute methods (e.g, AHP) and heuristic approaches (e.g., combinatorial optimization techniques) to propose optimal schedules of management options and to assess the sensitivity of those schedules to uncertain parameters and events (e.g, climate change, wildfire occurrence, prices). The researcher will take a leading role in the management and use of these decision support systems within CEF, ISA, and in collaboration with TERRA’s broader research community. The researcher will collaborate in teaching management planning courses, namely Forest and Natural Resources Management. This will include the development and supervision of new practical exercises for exploring opportunities afforded by landscape-level case studies and living labs in the framework of projects coordinated by CEF (e.g., Vale do Sousa). The Researcher will collaborate in supervising the use of decision support systems in CEF’s computer servers, including specialized Pareto frontier software. The researcher will participate in the development and teaching of short courses on management planning techniques, in domains of interest for the TERRA Associate Lab partner research units, such as restoration planning, territorial management and climate-resilient scenarios of choice.Scientific profile:The Researcher will need to have demonstrated competence in forest management science, including formal academic training, publications in peer-reviewed journals, and participation in relevant research projects. He/she will be required to have competences in the development of multiple criteria approaches to forest management and in ecosystem services’ tradeoffs analysis, with preference given to those who, additionally, are also skilled in the development of resource capability models targeting a wide range of ecosystem services and in the integration of fire and forest management. The primary substantive domain of expertise should be the analysis of alternative schedules of management options over several temporal and spatial scales, the assessment of tradeoffs between ecosystem services as well as risk analysis, namely for forests, woodlands, shrublands, and riparian vegetation. The tasks to be developed by the Researcher will require good data analytic skills, including proficiency in operations research techniques and multiple criteria approaches. The Researcher will also need good skills in the use of other modules of forest management decision support systems (e.g, GIS, MIS, Simulators).Rationale for hiring this profile:The potential losses from uninformed decisions, plans and policies are enormous and call for the development of effective forest ecosystem management planning and decision support approaches.  This development will be instrumental to address sustainability concerns shared by a variety of applied research areas at CEF and within the TERRA Associate Lab community. There is an increasing demand of products requiring materials based in forest resources. At the same time, we are increasingly aware of the impacts of extractive activities on forest ecosystems that provide biodiversity, erosion control, recreation and other non-market services.  These ecological values must be safeguarded even as we extract tangible economic products from forest ecosystems. While the innovation of management planning methods at CEF started in the late 1990s in research focusing on the management of industrial plantations, the domain of application gradually expanded to other areas, such as National Forests’ management planning, integration of forest and fire management and landscape-level multiple criteria spatial optimization. Subsequent technological progress, namely in computing power which allows the generation of complex decision and criteria spaces further increased the demand for novel combinations of spatial optimization and multiple criteria techniques. CEF needs to strengthen its capability to respond to this trend and increase our competitiveness with the recruitment of a talented young Researcher.