AFFOREST sDSS: a metamodel based spatial decision support system for afforestation of agricultural land

Abstract

Abstract. The concept and structure of the Spatial Decision Support System AFFOREST sDSS dealing with environmental performance (EP) of afforestation on agricultural land in northwestern Europe, is presented. EP is defined in terms of three environmental impact categories: (1) carbon sequestration (2) groundwater recharge and (3) nitrate leaching. The core of the sDSS is a raster based geographical database which allows for queries addressing 14 types of questions on where, how and how long to afforest in order to reach a desired EP or change in EP due to afforestation of the agricultural land. First the study area is differentiated according to the site conditions (based on soil texture, soil drainage, initial land use, yearly average precipitation, and yearly average N deposition. Then the EP for every site class is computed as a function of time using the VSAM metamodel. VSAM results from a conceptual simplification of an existing mechanistic point model, the forest process model SMART2. Input data for the metamodel are limited to the classified site conditions, the tree species used for afforestation, the afforestation strategy and the evaluation time. Besides limiting the data requirements, the metamodel approach allows for rapid and flexible computations on large numbers of pixel classes. Finally, depending on the type of question, the sDSS creates georeferenced outputs based on SQL-type spatial or attribute queries and more advanced multiple goal programming techniques.

Simulation tools for decision support to adaptive forest management in Europe

“…likely outcomes of alternatives from which a DSS can identify the most preferable one to maximise different user-defined objectives (see e.g Gilliams et al, 2005). In absence of a genuine DSS, stand alone simulation tools often include a user interface with attractive output visualization features to provide decision support ( Fig.…”

“…On the other hand, in strategic planning decisions, such as the strategic choice between maximum sustained yield or close-to-nature management, multicriteria decision analysis methods (MCDA) have been used. MCDA methods have drawn considerable attention and promising examples for successful integration in DSS have been presented (e.g., Lexer et al, 2005;Gilliams et al, 2005;Vacik et al, 2007;Twery et al, 2005). For instance, Lexer et al (2005) developed a DSS to support the forestry staff of extension services in southern Austria in preparing informed recommendations for forest management to small private landowners based on owner's goal preferences.…”

“…in decision optimization tools (e.g. Kurttila, 2001;Gilliams, 2005). There is also a trend to enhance stakeholder involvement through participatory model development or scenario selection.…”

“…Available forest simulators provide a large array of outputs, ranging from growing stock and yield related variables to quantification of important ecosystem services, such as carbon sequestration in biomass and soil, water recharge, etc. (García Quijano et al, 2005;Mol Dijkstra et al, 2009;Gilliams et al, 2005) but are not capable of generating the whole indicator set required by SFM standards. Nevertheless every model is able to generate at least a few indicators covering one or more sustainability principles (e.g.…”

Sensitivity and uncertainty analysis of the carbon and water fluxes at the tree scale inEucalyptusplantations using a metamodeling approach

“…A recent alternative approach is to build a metamodel (or surrogate model), which is a new computationally efficient model that gives almost the same results as the PBM but makes it easier to carry out sensitivity and uncertainty analyses (Faivre et al 2013). The metamodel approach has recently started to be used in forest modeling to develop faster modules for light interception (Marie and Simioni 2014), biomass prediction (de-Miguel et al 2014), or land use changes (Gilliams et al 2005;Sieber et al 2013.). In addition to facilitating sensitivity analysis, a metamodel of a tree-scale PBM could give simple modules of carbon and water fluxes that are easier to couple with a tree-scale allocation scheme for simulating individual-tree growth.…”