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Land use contributes to environmental change, but is also influenced by such changes. Climate and atmospheric carbon dioxide (CO 2 ) levels' changes alter agricultural crop productivity, plant water requirements and irrigation water availability. The global food system needs to respond and adapt to these changes, for example, by altering agricultural practices, including the crop types or intensity of management, or shifting cultivated areas within and between countries. As impacts and associated adaptation responses are spatially specific, understanding the land use adaptation to environmental changes requires crop productivity representations that capture spatial variations. The impact of variation in management practices, including fertiliser and irrigation rates, also needs to be considered. To date, models of global land use have selected agricultural expansion or intensification levels using relatively aggregate spatial representations, typically at a regional level, that are not able to characterise the details of these spatially differentiated responses. Here, we show results from a novel global modelling approach using more detailed biophysically derived yield responses to inputs with greater spatial specificity than previously possible. The approach couples a dynamic global vegetative model (LPJ-GUESS) with a new land use and food system model (PLUMv2), with results benchmarked against historical land use change from 1970. Land use outcomes to 2100 were explored, suggesting that increased intensity of climate forcing reduces the inputs required for food production, due to the fertilisation and enhanced water use efficiency effects of elevated atmospheric CO 2 concentrations, but requiring substantial shifts in the global and local patterns of production. The results suggest that adaptation in the global agriculture and food system has substantial capacity to diminish the negative impacts and gain greater benefits from positive outcomes of climate change. Consequently, agricultural expansion and intensification may be lower than found in previous studies where spatial details and processes consideration were more constrained., (© 2018 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.)

Most climate mitigation scenarios involve negative emissions, especially those that aim to limit global temperature increase to 2°C or less. However, the carbon uptake potential in land-based climate change mitigation efforts is highly uncertain. Here, we address this uncertainty by using two land-based mitigation scenarios from two land-use models (IMAGE and MAgPIE) as input to four dynamic global vegetation models (DGVMs; LPJ-GUESS, ORCHIDEE, JULES, LPJmL). Each of the four combinations of land-use models and mitigation scenarios aimed for a cumulative carbon uptake of ~130 GtC by the end of the century, achieved either via the cultivation of bioenergy crops combined with carbon capture and storage (BECCS) or avoided deforestation and afforestation (ADAFF). Results suggest large uncertainty in simulated future land demand and carbon uptake rates, depending on the assumptions related to land use and land management in the models. Total cumulative carbon uptake in the DGVMs is highly variable across mitigation scenarios, ranging between 19 and 130 GtC by year 2099. Only one out of the 16 combinations of mitigation scenarios and DGVMs achieves an equivalent or higher carbon uptake than achieved in the land-use models. The large differences in carbon uptake between the DGVMs and their discrepancy against the carbon uptake in IMAGE and MAgPIE are mainly due to different model assumptions regarding bioenergy crop yields and due to the simulation of soil carbon response to land-use change. Differences between land-use models and DGVMs regarding forest biomass and the rate of forest regrowth also have an impact, albeit smaller, on the results. Given the low confidence in simulated carbon uptake for a given land-based mitigation scenario, and that negative emissions simulated by the DGVMs are typically lower than assumed in scenarios consistent with the 2°C target, relying on negative emissions to mitigate climate change is a highly uncertain strategy., (© 2018 John Wiley & Sons Ltd.)

The terrestrial biosphere plays a major role in the global carbon cycle, and there is a recognized need for regularly updated estimates of land‐atmosphere exchange at regional and global scales. An international ensemble of Dynamic Global Vegetation Models (DGVMs), known as the "Trends and drivers of the regional scale terrestrial sources and sinks of carbon dioxide" (TRENDY) project, quantifies land biophysical exchange processes and biogeochemistry cycles in support of the annual Global Carbon Budget assessments and the REgional Carbon Cycle Assessment and Processes, phase 2 project. DGVMs use a common protocol and set of driving data sets. A set of factorial simulations allows attribution of spatio‐temporal changes in land surface processes to three primary global change drivers: changes in atmospheric CO2, climate change and variability, and Land Use and Land Cover Changes (LULCC). Here, we describe the TRENDY project, benchmark DGVM performance using remote‐sensing and other observational data, and present results for the contemporary period. Simulation results show a large global carbon sink in natural vegetation over 2012–2021, attributed to the CO2 fertilization effect (3.8 ± 0.8 PgC/yr) and climate (−0.58 ± 0.54 PgC/yr). Forests and semi‐arid ecosystems contribute approximately equally to the mean and trend in the natural land sink, and semi‐arid ecosystems continue to dominate interannual variability. The natural sink is offset by net emissions from LULCC (−1.6 ± 0.5 PgC/yr), with a net land sink of 1.7 ± 0.6 PgC/yr. Despite the largest gross fluxes being in the tropics, the largest net land‐atmosphere exchange is simulated in the extratropical regions. Plain Language Summary: Around one third of human‐induced CO2 emissions are absorbed by land ecosystems and thus act to mitigate climate change. It is essential to understand the processes, ecosystems and regions responsible for this natural carbon sink, to inform on the efficiency of the sinks into the future. These sinks are susceptible to year‐to‐year variation in response to climate variations and extremes. At the same time deforestation and other forms of land management are changing the land surface, which overall adds significantly to the human‐induced CO2 emissions. There is a need to regularly update our estimate of land carbon dynamics to aid global stock takes for the Paris agreement to avoid dangerous climate change. Here we present an international initiative that on an annual basis assesses "Trends and drivers of the regional scale terrestrial sources and sinks of carbon dioxide" (TRENDY) using computer models of the land carbon cycle. We quantify the land sink during the contemporary period (2012–2021), and attribute to processes, mainly the large opposing effects of CO2 fertilization enhancing plant productivity and land‐use change. Forests and semi‐arid ecosystems are largely responsible for the mean and trend in the land sink, with the latter most important for its year‐to‐year variation. Key Points: We quantify and attribute land carbon dynamics to underlying processes at regional scales, contributing bottom‐up estimates to RECCAP‐2Models simulate a contemporary net land sink of 1.7 ± 0.6 PgC/yr, with large opposing effects of CO2 fertilization and land‐use changeDespite the largest gross fluxes being in the tropics, the largest net land‐atmosphere exchange is simulated in the extratropical regions [ABSTRACT FROM AUTHOR]

Biological nitrogen fixation (BNF) from grain legumes is significant importance in global agricultural ecosystems. Crops with BNF capability are expected to support the need to increase food production while reducing nitrogen (N) fertilizer input for agriculture sustainability, but quantification of N fixing rates and BNF crop yields remains inadequate. Here we incorporate two legume crops (soybean and faba bean) with BNF into a dynamic vegetation model LPJ-GUESS (Lund-Potsdam-Jena General Ecosystem Simulator). The performance of this new implementation is evaluated against observations from a range of water and N management trials. LPJ-GUESS generally captures the observed response to these management practices on legume biomass production, soil N uptake and N fixation, despite some deviations from observations in some cases. Globally, the simulated BNF is dominated by soil moisture and temperature, as well as amounts of N fertilizer addition. Annual inputs through BNF are modelled to be 11.6±2.2 Tg N for soybean and 5.6±1.0 Tg N for all pulses, with a total fixation of 17.2±2.9 Tg N yr-1 for all grain legumes during the period 1981-2016 on global scale. Our estimates show a good agreement with some previous statistical estimates but are relatively high compared to some estimates for pulses. This study highlights the importance of accounting for legume N fixation process when modelling C-N interactions in agricultural ecosystems, particularly when it comes to account for the combined effects of climate and land-use change on global terrestrial N cycle. [ABSTRACT FROM AUTHOR]

Land-use models and integrated assessment models provide scenarios of land-use and land-cover (LULC) changes following pathways or storylines related to different socioeconomic and environmental developments. The large diversity of available scenario projections leads to a recognizable variability in impacts on land ecosystems and the levels of services provided. We evaluated 16 projections of future LULC until 2040 that reflected different assumptions regarding socioeconomic demands and modeling protocols. By using these LULC projections in a state-of-the-art dynamic global vegetation model, we simulated their effect on selected ecosystem service indicators related to ecosystem productivity and carbon sequestration potential, agricultural production and the water cycle. We found that although a common trend for agricultural expansion exists across the scenarios, where and how particular LULC changes are realized differs widely across models and scenarios. They are linked to model-specific considerations of some demands over others and their respective translation into LULC changes and also reflect the simplified or missing representation of processes related to land dynamics or other influencing factors (e.g., trade, climate change). As a result, some scenarios show questionable and possibly unrealistic features in their LULC allocations, including highly regionalized LULC changes with rates of conversion that are contrary to or exceed rates observed in the past. Across the diverging LULC projections, we identified positive global trends of net primary productivity (+ 10.2 % ± 1.4 %), vegetation carbon (+ 9.2 % ± 4.1 %), crop production (+ 31.2 % ± 12.2 %) and water runoff (+ 9.3 % ± 1.7 %), and a negative trend of soil and litter carbon stocks (- 0.5 % ± 0.4 %). The variability in ecosystem service indicators across scenarios was especially high for vegetation carbon stocks and crop production. Regionally, variability was highest in tropical forest regions, especially at current forest boundaries, because of intense and strongly diverging LULC change projections in combination with high vegetation productivity dampening or amplifying the effects of climatic change. Our results emphasize that information on future changes in ecosystem functioning and the related ecosystem service indicators should be seen in light of the variability originating from diverging projections of LULC. This is necessary to allow for adequate policy support towards sustainable transformations. [ABSTRACT FROM AUTHOR]

Changes in forest cover have a strong effect on climate through the alteration of surface biogeophysical and biogeochemical properties that affect energy, water, and carbon exchange with the atmosphere. To quantify biogeophysical and biogeochemical effects of deforestation in a consistent setup, nine Earth System models carried out an idealized experiment in the framework of the Coupled Model Intercomparison Project, phase 6 (CMIP6). Starting from their pre- industrial state, models linearly replace 20 million km2 of tree area in densely forested regions with grasslands over a period of 50 years followed by a stabilization period of 30 years. Most of the deforested area is in tropics, with a secondary peak in the boreal region. This study compares the effect of this large deforestation perturbation on energy and carbon fluxes across models. The effect on global annual near-surface temperature ranges from no significant change to a cooling by 0.55 °C, with a multi-model mean of -0.22 ± 0.21 °C. Five models simulate a temperature increase over deforested land in the tropics and a cooling over deforested boreal land. In these models, the latitude at which the temperature response changes sign ranges from 11 to 43° N, with a multi-model mean of 23° N. A multi-ensemble analysis reveals that the near-surface temperature changes emerge within 50 years over the tropical regions propagating from the centre of deforestation to the edges, indicating the influence of non-local effects. The biogeochemical effect of deforestation are land carbon losses of 259 ± 80 PgC. Based on transient climate response to cumulative emissions (TCRE) this would yield a warming by 0.46 ± 0.22 °C, suggesting a net warming effect of deforestation. While there is general agreement across models in their response to deforestation in terms of change in global temperatures and land carbon pools, the underlying changes in energy and carbon fluxes diverge substantially across models and geographical regions. Future analyses of the global deforestation experiments could further explore the effect on changes in seasonality of the climate response as well as large-scale circulation changes to advance our understanding and quantification of deforestation effects in the ESM frameworks. [ABSTRACT FROM AUTHOR]

Land-use models and Integrated Assessment Models provide scenarios of land use/cover (LULC) changes following pathways or storylines related to different socio-economic and environmental developments. The large diversity of available scenario projections leads to a recognizable variability in impacts on land ecosystems and the levels of services provided. We evaluated 16 projections of future LULC until 2040 that reflected different assumptions on socio-economic demands and modeling protocols. By using these LULC projections in a state of the art dynamic global vegetation model, we simulated their effect on selected ecosystem service indicators related to ecosystem productivity and carbon sequestration potential, agricultural production and the water cycle. We found that although a common trend for agricultural expansion exists across the scenarios, where and how particular LULC changes are realized differs widely across models and scenarios. They are linked to model-specific considerations of some demands over others and their respective translation into LULC changes and also reflect the simplified or missing representation of processes related to land dynamics or other influencing factors (e.g., trade, climate change). As a result, some scenarios show questionable and possibly unrealistic features in their LULC allocations, including highly regionalized LULC changes with rates of conversion that are contrary to or exceeding rates observed in the past. Across the diverging LULC projections we identified positive global trends of net primary productivity (+10.2 %), vegetation carbon (+9.2 %), crop production (+31.2 %) and water runoff (+9.3 %), and a negative trend of soil and litter carbon stocks (-0.5 %). The variability in ecosystem service indicators across scenarios was especially high for vegetation carbon stocks (± 4.1 %) and crop production (± 12.2 %). Regionally, variability was highest in tropical forest regions, especially at current forest edges, because of intense and strongly diverging LULC change projections in combination with high vegetation productivity dampening or amplifying the effects of climatic change. Our results emphasize that information on future changes in ecosystem functioning and the related ecosystem service indicators should be seen in light of the variability originating from diverging projections of LULC. This is necessary to allow for adequate policy support towards sustainable transformations. [ABSTRACT FROM AUTHOR]

To support the assessments of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), the IPBES Expert Group on Scenarios and Models is carrying out an intercomparison of biodiversity and ecosystem services models using harmonized scenarios (BES-SIM). The goals of BES-SIM are (1) to project the global impacts of land-use and climate change on biodiversity and ecosystem services (i.e., nature's contributions to people) over the coming decades, compared to the 20th century, using a set of common metrics at multiple scales, and (2) to identify model uncertainties and research gaps through the comparisons of projected biodiversity and ecosystem services across models. BES-SIM uses three scenarios combining specific Shared Socio-economic Pathways (SSPs) and Representative Concentration Pathways (RCPs) – SSP1xRCP2.6, SSP3xRCP6.0, SSP5xRCP8.6 – to explore a wide range of land-use change and climate change futures. This paper describes the rationale for scenario selection, the process of harmonizing input data for land use, based on the second phase of the Land Use Harmonization Project (LUH2), and climate, the biodiversity and ecosystem services models used, the core simulations carried out, the harmonization of the model output metrics, and the treatment of uncertainty. The results of this collaborative modeling project will support the ongoing global assessment of IPBES, strengthen ties between IPBES and the Intergovernmental Panel on Climate Change (IPCC) scenarios and modeling processes, advise the Convention on Biological Diversity (CBD) on its development of a post-2020 strategic plans and conservation goals, and inform the development of a new generation of nature-centred scenarios. [ABSTRACT FROM AUTHOR]

To support the assessments of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), the IPBES Expert Group on Scenarios and Models is carrying out an intercomparison of biodiversity and ecosystem services models using harmonized scenarios (BES-SIM). The goals of BES-SIM are (1) to project the global impacts of land use and climate change on biodiversity and ecosystem services (i.e. nature's contributions to people) over the coming decades, compared to the 20th century, using a set of common metrics at multiple scales, and (2) to identify model uncertainties and research gaps through the comparisons of projected biodiversity and ecosystem services across models. BES-SIM uses three scenarios combining specific Shared Socio-economic Pathways (SSPs) and Representative Concentration Pathways (RCPs) to explore a wide range of land-use change and climate change futures. This paper describes the rationale for scenarios selection, the process of harmonizing input data for land use, based on the second phase of the Land Use Harmonization Project (LUH2), and climate, the biodiversity and ecosystem service models used, the core simulations carried out, the harmonization of the model output metrics, and the treatment of uncertainty. The results of this collaborative modelling project will support the ongoing global assessment of IPBES, strengthen ties between IPBES and the Intergovernmental Panel on Climate Change (IPCC) scenarios and modelling processes, advise the Convention on Biological Diversity (CBD) on its development of a post-2020 strategic plans and conservation goals, and inform the development of a new generation of nature-centred scenarios. [ABSTRACT FROM AUTHOR]

Land-use and land-cover change (LULCC) is one of the key drivers of anthropogenic climate change. In addition to greenhouse gases such as CO 2 or CH 4 , LULCC affects also the emission of other carbon trace gases such as biogenic volatile organic compounds (BVOCs). We investigate the impact of changing LULCC on the emission of isoprene and monoterpenes during the 21st century using seven different land-use projections, applying the dynamic vegetation modelling framework LPJ-GUESS. Climate change, and atmospheric CO 2 -concentration are based on the RCP2.6 scenario. The different LULCC-scenarios explore the impact of different land-based climate change mitigation strategies (such as afforestation and avoided deforestation, or bioenergy). We show that the increase of land area under crops or grassland would lead to a significant decrease of BVOC emissions, with a strong negative correlation between the fraction of managed global land area and the emission of isoprene and monoterpenes. But the choice of crops is important, especially for the bioenergy scenarios in which increasing fractional cover leads to decreasing BVOC emissions in our simulations; use of woody bioenergy crops can reverse this decrease. The strong impact of LULCC on the global and regional emission of BVOCs implies the need to include the impact of these changes in projections of atmospheric composition and air quality. [ABSTRACT FROM AUTHOR]

Although the relevance of ongoing global greening for climate change has been recognized, its impact on the surface energy partitioning is yet to be quantified. Changes in vegetation structure and density are expected to influence the redistribution of heat and moisture across the climate system ultimately affecting water and energy cycles. Here, we analyse satellite leaf area index (LAI) and surface energy fluxes at the global scale for the period 1982¬–2016, and explore how variations in LAI have affected the energy partitioning. We show that latent fluxes (LE) increase and sensible fluxes (H) decrease with an increase in LAI, with sensitivities of 4.46±0.04 and -4.10±0.05 Wm-2 per unit change of LAI, respectively. These sensitivities show a remarkable increase of about 50% after 2000, possibly due to a more active stomatal control and an increased transpiration/evaporation ratio, triggered by decreasing soil moisture and/or increasing atmospheric evaporative demand. The long-term positive trend in LAI led to a decline in Bowen ratio (B=H/LE) prominently in arid zones (-0.031±0.002 decade-1) attributable to the increased evaporative surface and the consequent enhancement of transpiration. Overall, annual surface energy partitioning appears more strongly influenced by LAI (itself driven by climate and biotic factors) than directly by climate drivers. Land surface models in general tend to overestimate the vegetation control over tree biomes compared to observation-based records, due to the poor representation of LAI variability. Improving the model representation of vegetation dynamics and related biophysical processes is therefore crucial in view of the projected increases in LAI and aridity. [ABSTRACT FROM AUTHOR]