A B S T R A C TThis paper presents the overview of the Shared Socioeconomic Pathways (SSPs) and their energy, land use, and emissions implications. The SSPs are part of a new scenario framework, established by the climate change research community in order to facilitate the integrated analysis of future climate impacts, vulnerabilities, adaptation, and mitigation. The pathways were developed over the last years as a joint community effort and describe plausible major global developments that together would lead in the future to different challenges for mitigation and adaptation to climate change. The SSPs are based on five narratives describing alternative socio-economic developments, including sustainable development, regional rivalry, inequality, fossil-fueled development, and middle-of-the-road development. The longterm demographic and economic projections of the SSPs depict a wide uncertainty range consistent with the scenario literature. A multi-model approach was used for the elaboration of the energy, land-use and the emissions trajectories of SSP-based scenarios. The baseline scenarios lead to global energy consumption of 400-1200 EJ in 2100, and feature vastly different land-use dynamics, ranging from a possible reduction in cropland area up to a massive expansion by more than 700 million hectares by 2100.

In order to better assess the role of agriculture within the global climate‐vegetation system, we present a model of the managed planetary land surface, Lund–Potsdam–Jena managed Land (LPJmL), which simulates biophysical and biogeochemical processes as well as productivity and yield of the most important crops worldwide, using a concept of crop functional types (CFTs). Based on the LPJ‐Dynamic Global Vegetation Model, LPJmL simulates the transient changes in carbon and water cycles due to land use, the specific phenology and seasonal CO2 fluxes of agricultural‐dominated areas, and the production of crops and grazing land. It uses 13 CFTs (11 arable crops and two managed grass types), with specific parameterizations of phenology connected to leaf area development. Carbon is allocated daily towards four carbon pools, one being the yield‐bearing storage organs. Management (irrigation, treatment of residues, intercropping) can be considered in order to capture their effect on productivity, on soil organic carbon and on carbon extracted from the ecosystem. For transient simulations for the 20th century, a global historical land use data set was developed, providing the annual cover fraction of the 13 CFTs, rain‐fed and/or irrigated, within 0.5° grid cells for the period 1901–2000, using published data on land use, crop distributions and irrigated areas. Several key results are compared with observations. The simulated spatial distribution of sowing dates for temperate cereals is comparable with the reported crop calendars. The simulated seasonal canopy development agrees better with satellite observations when actual cropland distribution is taken into account. Simulated yields for temperate cereals and maize compare well with FAO statistics. Monthly carbon fluxes measured at three agricultural sites also compare well with simulations. Global simulations indicate a ∼24% (respectively ∼10%) reduction in global vegetation (respectively soil) carbon due to agriculture, and 6–9 Pg C of yearly harvested biomass in the 1990s. In contrast to simulations of the potential natural vegetation showing the land biosphere to be an increasing carbon sink during the 20th century, LPJmL simulates a net carbon source until the 1970s (due to land use), and a small sink (mostly due to changing climate and CO2) after 1970. This is comparable with earlier LPJ simulations using a more simple land use scheme, and within the uncertainty range of estimates in the 1980s and 1990s. The fluxes attributed to land use change compare well with Houghton's estimates on the land use related fluxes until the 1970s, but then they begin to diverge, probably due to the different rates of deforestation considered. The simulated impacts of agriculture on the global water cycle for the 1990s are∼5% (respectively∼20%) reduction in transpiration (respectively interception), and∼44% increase in evaporation. Global runoff, which includes a simple irrigation scheme, is practically not affected.

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Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change's representative concentration pathway with end-of-century radiative forcing of 8.5 W/m 2 . The mean biophysical yield effect with no incremental CO 2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.climate change adaptation | model intercomparison | integrated assessment | agricultural productivity C limate change alters weather conditions and thus has direct, biophysical effects on agricultural production. Assessing the ultimate consequences of these effects after producers and consumers respond requires detailed assessments at every step in the impact chain from climate through to crop and economic modeling.Comparisons of results from global studies that have attempted such model integration in the past show substantial differences in effects on key economic variables. Studies in the early 1990s found that climate change would have limited agricultural impacts globally, but with varying effects across regions (1-3). Adaptation and carbon dioxide (CO 2 ) fertilization effects were the two largest sources of variation in the results. New simulation approaches emerged in the mid-2000s, with gridded representation of yield impacts and more comprehensive coverage of variability in climate model projections (4, 5). However, these studies still relied on a single crop model and a single economic model. The number of economic models used for these types of analysis has remained relatively limited, and there has been no attempt to compare their behavior systematically. The Fourth Assessment Report of the Inte...

Bending the curve of terrestrial biodiversity needs an integrated strategy Summary paragraph Increased efforts are required to prevent further losses of terrestrial biodiversity and the ecosystem services it provides 1,2. Ambitious targets have been proposed, such as reversing the declining trends in biodiversity 3-yet, just feeding the growing human population will make this a challenge 4. We use an ensemble of land-use and biodiversity models to assess whether (and if so, how) humanity can reverse terrestrial biodiversity declines due to habitat conversion, a major threat to biodiversity 5. We show that immediate efforts, consistent with the broader sustainability agenda but of unprecedented ambition and coordination, may allow to feed the growing human population while reversing global terrestrial biodiversity trends from habitat conversion. If we decide to increase the extent of land under conservation management, restore degraded land, and generalize landscapelevel conservation planning, biodiversity trends from habitat conversion could become positive by mid-century on average across models (confidence interval: 2042-2061), but not for all models. Food prices could increase and, on average across models, almost half (confidence interval: 34-50%) of future biodiversity losses could not be avoided. However, additionally tackling the drivers of landuse change may avoid conflict with affordable food provision and reduces the food system's environmental impacts. Through further sustainable intensification and trade, reduced food waste, and healthier human diets, more than two thirds of future biodiversity losses are avoided and the biodiversity trends from habitat conversion are reversed by 2050 for almost all models. Although limiting further loss will remain challenging in several biodiversity-rich regions, and other threats, such as climate change, must be addressed to truly reverse biodiversity declines, our results show that bold conservation efforts and food system transformation are central to an effective post-2020 biodiversity strategy. Reversing biodiversity trends by 2050 Without further efforts to counteract habitat loss and degradation, we projected that global biodiversity will continue to decline (BASE scenario; Fig. 1). Rates of loss over time for all nine BDIs in 2010-2050 were close to or greater than those estimated for 1970-2010 (Extended data Extended Data Table 1). For various biodiversity aspects, on average across IAM and BDI combinations, peak losses over the 2010-2100 period were: 13% (range: 1-26%) for the extent of suitable habitat, 54% (range: 45-63%) for wildlife population density, 5% (range: 2-9%) for local compositional intactness , 4% (range: 1-12%) for global extinctions, and 4% (range: 2-8%) for regional extinctions (Extended Data Table 1). Percentage losses were greatest in biodiversity-rich regions (Sub-Saharan Africa, South Asia, South East Asia, the Caribbean and Latin America; Extended Data Fig. 2). The projected future trends for habitat loss and degradation and its driv...