Although acclaimed as a biofuel crop with high potential to sustainably replace fossil fuels, Jatropha curcas L. remains a poorly studied plant. Reliable yield assessments with conventional methods require agroclimatic and physiological knowledge, which is not yet available for Jatropha. To fill this gap, we tested a novel two-step approach integrating knowledge from biogeography and population biology with available Jatropha field data. In the first step, using MaxEnt, a widely implemented model in biogeography, we predicted Jatropha fitness in response to climate by relating natural occurrence recorded in herbaria with bioclimatic geodatasets. In the second step, we relied on population biology principles supported by seed mass addition experiments to relate fitness to reproductive potential, hence seed yield. Jatropha seed yield in response to climate was mapped worldwide for actual (1950-2000 average) and future (2020) climate conditions. The modelled Jatropha seed yield was validated against a set of on-field yield assessments (R 2 5 0.67, Po0.001). The discrepancies between estimated and measured yields were partially explained by model uncertainties, as quantified by the sensitivity analysis of our modelling (R 2 5 0.57, P 5 0.001). Jatropha has a pan-tropical distribution, plus specific adaptability to hot temperate areas. Climate variables most significantly affecting modelled yield response were annual average temperature, minimum temperature, annual precipitation and precipitation seasonality.

Abstract. Belgium's soil survey data collected between 1950 and 1970 (pre‐Kyoto Protocol) contain more than 13 000 geo‐referenced soil profile descriptions, which allow the computation of a spatially distributed baseline carbon content for incremental soil depths, based on soil/land‐use combinations (landscape units) and multiple matching soil profile observations. The results show that the soil organic carbon (SOC) and soil inorganic carbon (SIOC) contents of many landscape units do not differ significantly. However, landscape units under forest and grassland tend to contain more carbon. The same is true for landscape units on poorly drained and/or clayey soils, podzols or anthropogenic soils. The change of the SOC in the upper 100 cm of mineral soil follows a logarithmic decline with increasing depth, useful for the extrapolation of SOC of surface layers to deeper layers. SIOC values are strongly related to the geological soil characteristics and increase linearly with depth. Integrating the mean SOC and SIOC content of landscape units over the Belgian territory results in a total soil carbon stock of 303 Mt C in the upper 100 cm layer. Ectorganic horizons contain 35 Mt C and mineral soil contains 245 Mt C in organic form and 23 Mt C in inorganic form. These results are shown to be consistent with an independent set of SOC measurements on 3134 surface samples.

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Afforestation objectives vary from one country to another and even within countries. Apart from the objectives, the specific conditions from a biophysical, environmental and socioeconomic point of view should always be considered throughout the entire afforestation process, from policy decisions through location of the new forest, establishment and management, and the final utilisation of the forest. Decisions on how and where to afforest, and how much these decisions will affect the environmental impacts should ultimately be a compromise between the site quality in terms of climate, soil and preceding land-use, the initial goals set by planners and managers, and the stakeholders' preferences. The focus of AFFOREST has been on building knowledge and capacity to support decisions regarding afforestation of former arable land with respect to changes in C and N pools and fluxes and changes in 250 K. HANSEN ET AL. water recharge. The guidelines in this chapter are based on literature reviews, the experimental data from chronosequences of afforested stands in Denmark, Sweden, and the Netherlands (described in Chapter 2, 3 and 4), and on the developed mechanistic metamodel (METAFORE) and the spatial Decision Support System (AFFOREST-sDSS) (Chapter 7, 8, 9 and 10). The structure of the guidelines is based on questions and corresponding answers under the main themes of water recharge, nitrate leaching, C sequestration, diversity of understory vegetation and complex questions involving more than one of the first three issues. Hopefully, the guidelines will be helpful and inspire landscape and forest planners in planning how and where afforestation should take place.