Special Issue - Decision Support for the Provision of Ecosystem Services under Climate Change

11
Apr
04.11.2016 |
hvacik
Harald Vacik's picture

The Special Issue provides an overview on Forest Management Decision Support Systems currently designed and applied for the sustained provision of ecosystem services within the context of climate change based on the presentations given at the 24th World Congress of the International Union of Forest Research Organizations (IUFRO). The contributions demonstrate an overview on models, methods, techniques used in decision support and the proposed frameworks to support decision making. In this Special Issue, four different spatial decision support approaches allow reviewing the state of art in considering spatial and temporal dimensions in forest management planning.

Firstly Reynolds et al. (2014) discuss, in their review, the design features behind the success of the Ecosystem Management Decision Support System (EMDS) and propose the needs for the next generation of spatial decision support for adaptive management under climate change. Generality, transparency, simplification, abstraction and complexity, as well as the consideration of the spatial scale have been identified as critical for the success of the EMDS system, and deserve careful consideration in the design of decision-support systems for natural resource management. Following this recommendations, Frank et al. (2015) demonstrate the platform GISCAME to model spatio-temporal dynamics of biomass production at a regional scale in order to identify land use strategies that enhance biomass provision and avoid trade-offs for other ecosystem services. The results showed that forest conversion towards climate-change-adapted forest types had positive effects on ecological integrity and landscape aesthetics. Marušák et al. (2015) introduce the GIS tool Optimal for supporting spatial and temporal decisions in harvest scheduling. The DSS is designed and applied for silvicultural systems comprising clear-cuts and shelterwood systems with respect to the environmental and economic constraints. Forest managers are enabled to create and check spatial limits of harvest units and create various scenarios with Optimal. Daleman et al. (2015) introduce the concept, characteristics, functionalities, components and use of the Sim4Tree DSS, which supports strategic and tactical forestry planning by providing simulations of forest development, ecosystem services potential and economic performance through time, from a regional to a stand scale, under various management and climate regimes. Finally, Biber et al. (2015) compiled scenario runs from regionally tailored forest growth models and DSS from 20 case studies throughout Europe and analyzed whether the ecosystem service provision depends on management intensity and other co-variables, comprising regional affiliation, social environment, and tree species composition. They found a strong positive correlation between management intensity and wood production, but only weak correlation with protective and socioeconomic forest functions.

In addition to the presentation of various DSS, several advances in decision support techniques were identified, ranging from multi-attribute to multi-objective decision making methods. Garcia-Gonzalo et al. (2015) demonstrate the integration of an Interactive Decision Maps (IDM) technique within a DSS for an interactive visualization of the Pareto frontier. The multi-objective forest planning scenario of 1 million ha of cork and holm oak forest ecosystems in Southern Portugal is facilitated by stakeholder participation. Kašpar et al. (2015) present an approach where multiple criteria programming and integer programming techniques are used to find an optimal program of forest harvesting with respect to both economic and environmental constraints. Aldea et al. (2014) propose a goal programming procedure for integrating ecosystem services into forest management including a deterministic and a Monte Carlo modeling approach. Similar to other authors they highlight the variability of the results depending on the methodological approach taken and propose to critically evaluate the methodological approach taken. In this context also Estrella et al. (2014) introduced three different ideal point-based multi-criteria decision methods, i.e., iterative ideal point thresholding (IIPT), compromise programming (CP) and balanced compromise programming (BCP) to find an optimal distribution of land use types for regional land performance. For most ecosystem service analyzed, CP and BCP produced balanced results that were closer to the absolute optimal values when compared to IIPT. From the wide field of multi-criteria decision making techniques, Mendoza et al. (2015) compare different forest management schemes of Mexico in order to identify best management approaches considering multi-resources, environmental impacts and non-timber values. Considering the increased need for the involvement of preferences of decision makers, Rinaldi et al. (2015) provide an example of how forest owner specific characterization can be integrated in a DSS by linking a behavioral harvesting decision model to a forest resource dynamics model. They showed that the distribution of different owner types on forestland affects harvesting intensity and inter-temporal forest development. In the work of Nobre et al (2016) the material produced in the context of the COST Action FORSYS was used to generate quantitative summaries of (i) the types of problem where FMDSS are used, (ii) models and methods used to solve these problems, (iii) knowledge management techniques, and (iv) participatory planning techniques.

The Editorial of the Special Issue highlight that the development in decision support for forest management is set by decision theory, available technology, and methods. In addition to the technological and methodological advances, there is a strong need to include decision makers and DSS users in the design of the DSS from the very beginning in order to better meet their demands.