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The production of palm oil, soy, beef and timber are key drivers of global forest loss. For this reason, over 470 companies involved in the production, processing or distribution of these commodities have issued commitments to eliminate or reduce deforestation from their supply chains. However, the effectiveness of these commitments is uncertain since there is considerable variation in ambition and scope and there are no globally agreed definitions of what constitutes a forest. Many commitments identify high conservation value forests (HCVFs), high carbon stock forests (HCSFs) and forests on tropical peatland as priority areas for conservation. This allows for mapping of the global extent of forest areas classified as such, to achieve an assessment of the area that may be at reduced risk of development if companies comply with their zero deforestation commitments. Depending on the criteria used, the results indicate that between 34% and 74% of global forests qualify as either HCVF, HCSF or forests on tropical peatland. However, we found that the total extent of these forest areas varies widely depending on the choice of forest map. Within forests which were not designated as HCVF, HCSF or forests on tropical peatland, there is substantial overlap with areas that are highly suitable for agricultural development. Since these areas are unlikely to be protected by zero-deforestation commitments, they may be subject to increased pressure resulting from leakage of areas designated as HCVF, HCSF and tropical peatland forests. Considerable uncertainties around future outcomes remain, since only a proportion of the global market is currently covered by corporate commitments. Further work is needed to map the synergies between corporate commitments and government policies on land use. In addition, standardized criteria for delineating forests covered by the commitments are recommended.

This is the author accepted manuscript. The final version is available from European Geosciences Union (EGU) via the DOI in this record. ; Land-use and land-cover change (LULCC) represents one of the key drivers of global environmental change. However, the processes and drivers of anthropogenic land-use activity are still overly simplistically implemented in terrestrial biosphere models (TBMs). The published results of these models are used in major assessments of processes and impacts of global environmental change, such as the reports of the Intergovernmental Panel on Climate Change (IPCC). Fully coupled models of climate, land use and biogeochemical cycles to explore land use-climate interactions across spatial scales are currently not available. Instead, information on land use is provided as exogenous data from the land-use change modules of integrated assessment models (IAMs) to TBMs. In this article, we discuss, based on literature review and illustrative analysis of empirical and modeled LULCC data, three major challenges of this current LULCC representation and their implications for land use-climate interaction studies: (I) provision of consistent, harmonized, land-use time series spanning from historical reconstructions to future projections while accounting for uncertainties associated with different land-use modeling approaches, (II) accounting for sub-grid processes and bidirectional changes (gross changes) across spatial scales, and (III) the allocation strategy of independent land-use data at the grid cell level in TBMs. We discuss the factors that hamper the development of improved land-use representation, which sufficiently accounts for uncertainties in the land-use modeling process. We propose that LULCC data-provider and user communities should engage in the joint development and evaluation of enhanced LULCC time series, which account for the diversity of LULCC modeling and increasingly include empirically based information about sub-grid processes and land-use transition trajectories, to improve the representation of land use in TBMs. Moreover, we suggest concentrating on the development of integrated modeling frameworks that may provide further understanding of possible land-climate-society feedbacks. ; The research in this paper has been supported by the European Research Council under the European Union's Seventh Framework Programme project LUC4C (Grant No. 603542), ERC grant GLOLAND (No. 311819) and BiodivERsA project TALE (No. 832.14.006) funded by the Dutch National Science Foundation (NWO). This research contributes to the Global Land Project (www.globallandproject.org). This is paper number 26 of the Birmingham Institute of Forest Research.