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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.

Interactions between food demand, biomass energy and forest preservation are driving both food prices and land-use changes, regionally and globally. This study presents a new model called Nexus Land-Use version 1.0 which describes these interactions through a generic representation of agricultural intensification mechanisms within agricultural lands. The Nexus Land-Use model equations combine biophysics and economics into a single coherent framework to calculate crop yields, food prices, and resulting pasture and cropland areas within 12 regions inter-connected with each other by international trade. The representation of cropland and livestock production systems in each region relies on three components: (i) a biomass production function derived from the crop yield response function to inputs such as industrial fertilisers; (ii) a detailed representation of the livestock production system subdivided into an intensive and an extensive component, and (iii) a spatially explicit distribution of potential (maximal) crop yields prescribed from the Lund-Postdam-Jena global vegetation model for managed Land (LPJmL). The economic principles governing decisions about land-use and intensification are adapted from the Ricardian rent theory, assuming cost minimisation for farmers. In contrast to the other land-use models linking economy and biophysics, crops are aggregated as a representative product in calories and intensification for the representative crop is a non-linear function of chemical inputs. The model equations and parameter values are first described in details. Then, idealised scenarios exploring the impact of forest preservation policies or rising energy price on agricultural intensification are described, and their impacts on pasture and cropland areas are investigated.

International audience The mapping of ecosystem service supply has become quite common in ecosystem service assessment practice for terrestrial ecosystems, but land cover remains the most common indicator for ecosystems ability to deliver ecosystem services. For marine ecosystems, practice is even less advanced, with a clear deficit in spatially-explicit assessments of ecosystem service supply. This ``situation, which generates considerable uncertainty in the assessment of ecosystems' ability to support current and future human well-being, contrasts with increasing understanding of the role of terrestrial and marine biodiversity for ecosystem functioning and thereby for ecosystem services. This paper provides a synthesis of available approaches, models and tools, and data sources, that are able to better link ecosystem service mapping to current understanding of the role of ecosystem service providing organisms and land/seascape structure in ecosystem functioning. Based on a review of literature, models and associated geo-referenced metrics are classified according to the way in which land or marine use, ecological processes and especially biodiversity effects are represented. We distinguish five types of models: proxy-based, phenomenological, niche-based, trait-based and full-process. Examples from each model type are presented and data requirements considered. Our synthesis demonstrates that the current understanding of the role of biota in ecosystem services can effectively be incorporated into mapping approaches and opens avenues for further model development using hybrid approaches tailored to available resources. We end by discussing ways to resolve sources of uncertainty associated with model representation of biotic processes and with data availability. (C) 2016 Elsevier Ltd. All rights reserved.

Acknowledgements The authors are grateful to M. Scholes, D. Plaza-Bonilla, S. Menendez, P. Merino, S.C. Maris, H. Heller, D. Savvas, C. K. Kontopoulou, who were contacted and kindly supplied any missing information necessary for the meta-analysis. Special thanks to J.P.C. Eekhout for preparing Fig. 1 and F. Estellés for providing the basic data for the calculation of the fertilization in Spain. Also thanks to two anonymous reviewers for their helpful comments. M. L. Cayuela was supported by a 'Ramon y Cajal' research contract from the Spanish Ministry of Economy and Competitiveness. Thanks to Fundación Séneca, Agencia Regional de Ciencia y Tecnología de la Región de Murcia for support (grant number 19281/PI/14). Australian studies included in the meta-analysis were funded by the Australian Government, the Grains Research and Development Corporation, and the Department of Agriculture and Food WA. ; Peer reviewed ; Postprint ; Postprint ; Postprint ; Postprint ; Postprint