Beyond the State-of-the-Art

Science Policy Interface

The inclusion in the Kyoto Protocol of activities in agriculture and forestry that reduce emissions, or increase removals of greenhouse gases, has been a hotly debated and very controversial issue. This sector is usually referred to as Land Use, Land-use Change and Forestry (LULUCF). After the Kyoto Protocol was adopted in 1997, it become clear that many questions had been left unresolved in this area, so that the Intergovernmental Panel on Climate Change (IPCC) was commissioned to prepare a Special Report on this issue (IPCC, 2000). Subsequently, an agreement was reached in Marrakech (COP7, 2001) on the detailed rules, definition and modalities for LULUCF. This agreement included the types of activities that Annex I countries could use towards meeting their emission targets (afforestation, reforestation, deforestation, forest management, cropland management, grazing land management, and revegetation), how these activities would be accounted for, the maximum limits of credits that could be awarded, and that only afforestation and reforestation would be eligible in the Clean Development Mechanism (CDM). In Europe the ECCP (European Climate Change Programme) has played an important role to provide information and communication platform among European stakeholders. However, harmonised and consistent analysis across climate, agriculture, forestry and energy policies to assess the policy effectiveness of reducing greenhouse gases and adapt to climate change through bringing together established modelling tools from the relevant fields has not yet been carried out.

Biophysical Climate Change Impact Modelling

Several EU projects (e.g., INSEA, CAPRI-DYNASPAT, CARBOEUROPE, NITROEUROPE) have pursued the objective of making a selection of bio-physical process models (e.g., EPIC, DNDC, Sundial/RothC) applicable at EU scale. Consequently, each project has developed its own conceptual framework using data that are commonly available at the EU level (e.g., MARS, EU soil map, CORINE). For instance, INSEA has developed a 2-step hierarchical delineation change or change slowly under climate change and farm management (altitude, texture, slope, etc). This concept assures consistent integration of bio-physical impact vectors in endogenous economic land use models (e.g., EUFASOM). Similar, CAPRI-DYNASPAT has delineated Homogenous Spatial Mapping Units (HSMU) on the basis of agronomic parameters, and within NitroEurope slightly different mapping/calculation units (NCU) will be derived. Consequently, harmonization of these delineation processes within CC-TAME will increase the comparability between outputs from EPIC, DNDC, and Sundial/RothC and will allow model uncertainty to be better addressed using a common indicator set. In addition, data collected in these projects, particularly experimental data, will be used to perform site-specific Bayesian calibration on these models to allow uncertainty to be better quantified with respect to measured and simulated data.

The application of the CC-TAME model cluster will broaden the environmental indicator spectrum in a complementary manner. It is essential to fully evaluate and outline trade-offs in impact trajectories of alternative management practices that are promoted in distinct EU policy programmes (Climate Policy, Water Framework, Cross Compliance, etc.). Consequently, common and alternative management practices will be analysed including conventional, reduced and minimum tillage practices, precision farming, cover crop management systems, agro-forestry, crop residue systems, fertilization and irrigation regimes, manure handling systems, crop rotation and inter-cropping systems, etc. This has never been performed on Pan-European scales. Furthermore, the watershed model SWAT will be applied in selected EU watersheds to account for up- and down-stream effects of climate change on the water, carbon, and nutrient cycles across complex landscapes. The novelty here is to integrate SWAT with an economic watershed land use model that iteratively correspond through land use and management changes until environmental targets at the watershed outlets are reached.

Forest management can contribute to climate change mitigation by three general pathways: conservation (forests are currently the largest terrestrial C storage, i.e., prevent emissions from currently high forest carbon pools), sequestration (increase stocks in existing pools in and ex situ) and substitution (substitute energy-intensive products or products on fossil fuel basis with biological, regrowing products e.g., bioenergy). CC-TAME will offer the first consistent toolbox to an integrated assessment of all three pathways at a continental scale in Europe. The multi-model toolbox compiled and evaluated in the project will be the first to be able to cover large spatial scales while also being able to simulate detailed management strategies and their impacts with high realism. Furthermore, a major step to a comprehensive understanding of the impacts of economically optimised mitigation and adaptation strategies is undertaken in disaggregating such policy impacts by means of detailed regional biophysical process based models. This unique venture for the first time not only harnesses regional models for improved upscaling of management strategies but essentially utilizes the resolution of such detailed models to quantify the local impacts and externalities of optimised forest policies.

Moreover, CC-TAME will tackle a major current shortcoming in most of the available forest projections/tools in venturing for a consistent integration of vulnerabilities from natural disturbances and extreme events across scales. The high resolution climate anomalities data provided by the consortium’s RCMs will serve as basis for advances in modelling impacts of natural disturbances on stand to regional level. The biome-specific regional forest models and sub-national sample regions will provide an interface for an in-depth analysis of disturbance effects on mitigation objectives. In addition, they provide the basis for the scientifically challenging task of scaling such highly stochastic and non-linear effects to higher spatial levels for inclusion in the large scale forest scenario models applied.
Simulation experiments will be carried out with computed extreme weather events to assess vulnerability thresholds for major EU agricultural and forest production regions as well as for the terrestrial and aquatic ecosystems.

Economic Land-use and Land-use Change Modelling

Land-use scenarios have become a common tool for spatial planning at various scales. Most commonly, quantification of land use/cover change follows a general scheme (Busch, 2006): like climate scenarios, land-use scenarios start with storylines about future development on a broader scale (Europe, world); from these, assumptions on future land-use requirements are delineated, taking into account changing demand for agriculture products, demography, technological and economic progress. Finally land use requirements result in land use/cover changes depending on biophysical suitability and spatial restrictions of land resources. Studies have been performed on global (e.g., Rokityanskiy et al., 2007, Strengers et al., 2004, UNEP, 2002), European (SENSOR, Helming, 2006; ACCELERATES, Abildtrup et al., 2006; EURURALIS, Klijn et al., 2004; ATEAM, Rounsevell et al., 2006) and regional scales (e.g., Hoogeveen & Ribeiro, 2005). For global and European scale assessments, IPCC-SRES storylines are a common starting point.

While recent studies have impressively shown that land-use change could be a very important driver for future environmental changes in Europe, shortcomings are also reported:

• Linkages between global, European and regional economies are at most conceptual rather than developed from empirical data of a particular region.
• Climate change effects on land-use are not considered beyond limited case studies. More generally, economic models ignore the dynamic impact of a changing environment (climate, soil state, native flora and fauna) on land management.
• Climate models and geography based models of land use ignore market adjustments related to price changes from commodity supply and trade effects.
• The spatial and thematic resolution is either insufficient for global and continental assessments or limited to individual regions.
• Policy links and stakeholder responses are hardly considered. These are crucial for assessing the impacts of global change on the landscape scale (European Commission, 2004, Kok et al., 2007, Overmars et al., 2007).

CC-TAME will address these short-comings. In particular we would like to emphases the following points:

• CC-TAME couples global (POLES, GLOBAL FASOM, MESSAGE), European (EUFASOM, CAPRI, SF-GTM, RAINS/GAINS, PRIMES), and regional economy models (AROPAJ, PASMA, FAMOS, OSKAR) based on rich, bottom-up data sets. This allows to represent the complex, non-linear responses of land management to environmental policies and technical change. Schneider, Obersteiner, Schmid (2007) show that irrigation, tillage, and nitrogen intensities respond very different to climate policies.
• The effects of a changing environment will be integrated in two ways. Climate feedbacks to land use are portrayed in CC-TAME through the coupling of a regional climate model with biophysical models and in turn with both micro and macro-economic models. Furthermore, the dynamic relationship between land management and soil state (i.e., soil carbon levels) will for the first time be integrated in a land use decision model. Particularly, soil carbon functions – estimated by biophysical models (EPIC, DNDC, RothC, Yasso) – will be used to compute soil state transition probabilities for each soil-climate-management regime. These transition probabilities will then be incorporated in economic models as Markov process. A detailed description and test of this method has already been published by Schneider (2007).
• Market adjustments are accounted for with a simultaneous assessment of a large number of ecosystem services and markets for traditional land use products, i.e., for timber, food, and fibre. This method integrates both direct costs and indirect costs (opportunity costs based on market price changes) of environmental services. Schneider, McCarl, and Schmid (2007) have shown for greenhouse gas emission mitigation how much economic potentials can. CC-TAME uses the highest available spatial resolution in combination with global scope perspectives. Thematically, we will for the first time compute synergies and trade-offs between the three major international environmental conventions: biodiversity – climate protection – soil preservation. The importance of these impacts has been qualitatively assessed by Cowie, Schneider, Montanarella (2007) and will be quantified in CC-TAME.