Global trends and scenarios for terrestrial biodiversity and ecosystem services from 1900 to 2050.

Based on an extensive model intercomparison, we assessed trends in biodiversity and ecosystem services from historical reconstructions and future scenarios of land-use and climate change. During the 20th century, biodiversity declined globally by 2 to 11%, as estimated by a range of indicators. Provisioning ecosystem services increased several fold, and regulating services decreased moderately. Going forward, policies toward sustainability have the potential to slow biodiversity loss resulting from land-use change and the demand for provisioning services while reducing or reversing declines in regulating services. However, negative impacts on biodiversity due to climate change appear poised to increase, particularly in the higher-emissions scenarios. Our assessment identifies remaining modeling uncertainties but also robustly shows that renewed policy efforts are needed to meet the goals of the Convention on Biological Diversity.

Land-based climate change mitigation measures can affect agricultural markets and food security.

Earlier studies have noted potential adverse impacts of land-related emissions mitigation strategies on food security, particularly due to food price increases-but without distinguishing these strategies' individual effects under different conditions. Using six global agroeconomic models, we show the extent to which three factors-non-CO2 emissions reduction, bioenergy production and afforestation-may change food security and agricultural market conditions under 2 °C climate-stabilization scenarios. Results show that afforestation (often simulated in the models by imposing carbon prices on land carbon stocks) could have a large impact on food security relative to non-CO2 emissions policies (generally implemented as emissions taxes). Respectively, these measures put an additional 41.9 million and 26.7 million people at risk of hunger in 2050 compared with the current trend scenario baseline. This highlights the need for better coordination in emissions reduction and agricultural market management policies as well as better representation of land use and associated greenhouse gas emissions in modelling.

Land-based measures to mitigate climate change: Potential and feasibility by country.

Land-based climate mitigation measures have gained significant attention and importance in public and private sector climate policies. Building on previous studies, we refine and update the mitigation potentials for 20 land-based measures in >200 countries and five regions, comparing "bottom-up" sectoral estimates with integrated assessment models (IAMs). We also assess implementation feasibility at the country level. Cost-effective (available up to $100/tCO2 eq) land-based mitigation is 8-13.8 GtCO2 eq yr-1 between 2020 and 2050, with the bottom end of this range representing the IAM median and the upper end representing the sectoral estimate. The cost-effective sectoral estimate is about 40% of available technical potential and is in line with achieving a 1.5°C pathway in 2050. Compared to technical potentials, cost-effective estimates represent a more realistic and actionable target for policy. The cost-effective potential is approximately 50% from forests and other ecosystems, 35% from agriculture, and 15% from demand-side measures. The potential varies sixfold across the five regions assessed (0.75-4.8 GtCO2eq yr-1 ) and the top 15 countries account for about 60% of the global potential. Protection of forests and other ecosystems and demand-side measures present particularly high mitigation efficiency, high provision of co-benefits, and relatively lower costs. The feasibility assessment suggests that governance, economic investment, and socio-cultural conditions influence the likelihood that land-based mitigation potentials are realized. A substantial portion of potential (80%) is in developing countries and LDCs, where feasibility barriers are of greatest concern. Assisting countries to overcome barriers may result in significant quantities of near-term, low-cost mitigation while locally achieving important climate adaptation and development benefits. Opportunities among countries vary widely depending on types of land-based measures available, their potential co-benefits and risks, and their feasibility. Enhanced investments and country-specific plans that accommodate this complexity are urgently needed to realize the large global potential from improved land stewardship.

Short- and long-term warming effects of methane may affect the cost-effectiveness of mitigation policies and benefits of low-meat diets.

Methane's short atmospheric life has important implications for the design of global climate change mitigation policies in agriculture. Three different agricultural economic models are used to explore how short- and long-term warming effects of methane can affect the cost-effectiveness of mitigation policies and dietary transitions. Results show that the choice of a particular metric for methane's warming potential is key to determine optimal mitigation options, with metrics based on shorter-term impacts leading to greater overall emission reduction. Also, the promotion of low-meat diets is more effective at reducing greenhouse gas emissions compared to carbon pricing when mitigation policies are based on metrics that reflect methane's long-term behaviour. A combination of stringent mitigation measures and dietary changes could achieve substantial emission reduction levels, helping reverse the contribution of agriculture to global warming.

Comparing the impact of future cropland expansion on global biodiversity and carbon storage across models and scenarios.

Land-use change is a direct driver of biodiversity and carbon storage loss. Projections of future land use often include notable expansion of cropland areas in response to changes in climate and food demand, although there are large uncertainties in results between models and scenarios. This study examines these uncertainties by comparing three different socio-economic scenarios (SSP1-3) across three models (IMAGE, GLOBIOM and PLUMv2). It assesses the impacts on biodiversity metrics and direct carbon loss from biomass and soil as a direct consequence of cropland expansion. Results show substantial variation between models and scenarios, with little overlap across all nine projections. Although SSP1 projects the least impact, there are still significant impacts projected. IMAGE and GLOBIOM project the greatest impact across carbon storage and biodiversity metrics due to both extent and location of cropland expansion. Furthermore, for all the biodiversity and carbon metrics used, there is a greater proportion of variance explained by the model used. This demonstrates the importance of improving the accuracy of land-based models. Incorporating effects of land-use change in biodiversity impact assessments would also help better prioritize future protection of biodiverse and carbon-rich areas. This article is part of the theme issue 'Climate change and ecosystems: threats, opportunities and solutions'.

Projecting terrestrial biodiversity intactness with GLOBIO 4.

Scenario-based biodiversity modelling is a powerful approach to evaluate how possible future socio-economic developments may affect biodiversity. Here, we evaluated the changes in terrestrial biodiversity intactness, expressed by the mean species abundance (MSA) metric, resulting from three of the shared socio-economic pathways (SSPs) combined with different levels of climate change (according to representative concentration pathways [RCPs]): a future oriented towards sustainability (SSP1xRCP2.6), a future determined by a politically divided world (SSP3xRCP6.0) and a future with continued global dependency on fossil fuels (SSP5xRCP8.5). To this end, we first updated the GLOBIO model, which now runs at a spatial resolution of 10 arc-seconds (~300 m), contains new modules for downscaling land use and for quantifying impacts of hunting in the tropics, and updated modules to quantify impacts of climate change, land use, habitat fragmentation and nitrogen pollution. We then used the updated model to project terrestrial biodiversity intactness from 2015 to 2050 as a function of land use and climate changes corresponding with the selected scenarios. We estimated a global area-weighted mean MSA of 0.56 for 2015. Biodiversity intactness declined in all three scenarios, yet the decline was smaller in the sustainability scenario (-0.02) than the regional rivalry and fossil-fuelled development scenarios (-0.06 and -0.05 respectively). We further found considerable variation in projected biodiversity change among different world regions, with large future losses particularly for sub-Saharan Africa. In some scenario-region combinations, we projected future biodiversity recovery due to reduced demands for agricultural land, yet this recovery was counteracted by increased impacts of other pressures (notably climate change and road disturbance). Effective measures to halt or reverse the decline of terrestrial biodiversity should not only reduce land demand (e.g. by increasing agricultural productivity and dietary changes) but also focus on reducing or mitigating the impacts of other pressures.

Afforestation for climate change mitigation: Potentials, risks and trade-offs.

Afforestation is considered a cost-effective and readily available climate change mitigation option. In recent studies afforestation is presented as a major solution to limit climate change. However, estimates of afforestation potential vary widely. Moreover, the risks in global mitigation policy and the negative trade-offs with food security are often not considered. Here we present a new approach to assess the economic potential of afforestation with the IMAGE 3.0 integrated assessment model framework. In addition, we discuss the role of afforestation in mitigation pathways and the effects of afforestation on the food system under increasingly ambitious climate targets. We show that afforestation has a mitigation potential of 4.9 GtCO2 /year at 200 US$/tCO2 in 2050 leading to large-scale application in an SSP2 scenario aiming for 2°C (410 GtCO2 cumulative up to 2100). Afforestation reduces the overall costs of mitigation policy. However, it may lead to lower mitigation ambition and lock-in situations in other sectors. Moreover, it bears risks to implementation and permanence as the negative emissions are increasingly located in regions with high investment risks and weak governance, for example in Sub-Saharan Africa. Afforestation also requires large amounts of land (up to 1,100 Mha) leading to large reductions in agricultural land. The increased competition for land could lead to higher food prices and an increased population at risk of hunger. Our results confirm that afforestation has substantial potential for mitigation. At the same time, we highlight that major risks and trade-offs are involved. Pathways aiming to limit climate change to 2°C or even 1.5°C need to minimize these risks and trade-offs in order to achieve mitigation sustainably.

Data for long-term marginal abatement cost curves of non-CO2 greenhouse gases.

This dataset represents long-term marginal abatement cost (MAC) curves of all major emission sources of non-CO2 greenhouse gases (GHGs); methane (CH4), nitrous oxide (N2O) and fluorinated gases (HFCs, PFCs and SF6). The work is based on existing short-term MAC curve datasets and recent literature on individual mitigation measures. The data represent a comprehensive set of MAC curves, covering all major non-CO2 emission sources for 26 aggregated world regions. They are suitable for long-term global mitigation scenario development, as dynamical elements (technological progress, removal of implementation barriers) are included. The data is related to the research article: "Long-term marginal abatement cost curves of non-CO 2 greenhouse gases" [1].

Key determinants of global land-use projections.

Land use is at the core of various sustainable development goals. Long-term climate foresight studies have structured their recent analyses around five socio-economic pathways (SSPs), with consistent storylines of future macroeconomic and societal developments; however, model quantification of these scenarios shows substantial heterogeneity in land-use projections. Here we build on a recently developed sensitivity approach to identify how future land use depends on six distinct socio-economic drivers (population, wealth, consumption preferences, agricultural productivity, land-use regulation, and trade) and their interactions. Spread across models arises mostly from diverging sensitivities to long-term drivers and from various representations of land-use regulation and trade, calling for reconciliation efforts and more empirical research. Most influential determinants for future cropland and pasture extent are population and agricultural efficiency. Furthermore, land-use regulation and consumption changes can play a key role in reducing both land use and food-security risks, and need to be central elements in sustainable development strategies.

Future global pig production systems according to the Shared Socioeconomic Pathways.

Global pork production has increased fourfold over the last 50 years and is expected to continue growing during the next three decades. This may have considerable implications for feed use, land requirements, and nitrogen emissions. To analyze the development of the pig production sector at the scale of world regions, we developed the IMAGE-Pig model to describe changes in feed demand, feed conversion ratios (FCRs), nitrogen use efficiency (NUE) and nitrogen excretion for backyard, intermediate and intensive systems during the past few decades as a basis to explore future scenarios. For each region and production system, total production, productive characteristics and dietary compositions were defined for the 1970-2005 period. The results show that due to the growing pork production total feed demand has increased by a factor of two (from 229 to 471Tg DM). This is despite the improvement of FCRs during the 1970-2005 period, which has reduced the feed use per kg of product. The increase of nitrogen use efficiency was slower than the improvement of FCRs due to increasing protein content in the feed rations. As a result, total N excretion increased by more than a factor of two in the 1970-2005 period (from 4.6 to 11.1 Tg N/year). For the period up to 2050, the Shared Socio-economic Pathways (SSPs) provide information on levels of human consumption, technical development and environmental awareness. The sustainability of pig production systems for the coming decades will be based not only on the expected efficiency improvements at the level of animal breeds, but also on four additional pillars: (i) use of alternative feed sources not competing with human food, (ii) reduction of the crude protein content in rations, (iii) the proper use of slurries as fertilizers through coupling of crop and livestock production and (iv) moderation of the human pork consumption.

Global projections of future cropland expansion to 2050 and direct impacts on biodiversity and carbon storage.

Cropland expansion threatens biodiversity by driving habitat loss and impacts carbon storage through loss of biomass and soil carbon (C). There is a growing concern land-use change (LUC) to cropland will result in a loss of ecosystem function and various ecosystem services essential for human health and well-being. This paper examines projections of future cropland expansion from an integrated assessment model IMAGE 3.0 under a "business as usual" scenario and the direct impact on both biodiversity and C storage. By focusing on biodiversity hotspots and Alliance for Zero Extinction (AZE) sites, loss of habitat as well as potential impacts on endangered and critically endangered species are explored. With regards to C storage, the impact on both soil and vegetation standing C stocks are examined. We show that if projected trends are realized, there are likely to be severe consequences for these resources. Substantial loss of habitat in biodiversity hotspots such as Indo-Burma, and the Philippians is expected as well as 50% of species in AZE sites losing part of their last remaining habitat. An estimated 13.7% of vegetation standing C stocks and 4.6% of soil C stocks are also projected to be lost in areas affected with Brazil and Mexico being identified as priorities in terms of both biodiversity and C losses from cropland expansion. Changes in policy to regulate projected cropland expansion, and increased measures to protect natural resources, are highly likely to be required to prevent these biodiversity and C losses in the future.

Biogeophysical Impacts of Land-Use Change on Climate Extremes in Low-Emission Scenarios: Results From HAPPI-Land.

The impacts of land use have been shown to have considerable influence on regional climate. With the recent international commitment to limit global warming to well below 2°C, emission reductions need to be ambitious and could involve major land-use change (LUC). Land-based mitigation efforts to curb emissions growth include increasing terrestrial carbon sequestration through reforestation, or the adoption of bioenergy crops. These activities influence local climate through biogeophysical feedbacks, however, it is uncertain how important they are for a 1.5° climate target. This was the motivation for HAPPI-Land: the half a degree additional warming, prognosis, and projected impacts-land-use scenario experiment. Using four Earth system models, we present the first multimodel results from HAPPI-Land and demonstrate the critical role of land use for understanding the characteristics of regional climate extremes in low-emission scenarios. In particular, our results show that changes in temperature extremes due to LUC are comparable in magnitude to changes arising from half a degree of global warming. We also demonstrate that LUC contributes to more than 20% of the change in temperature extremes for large land areas concentrated over the Northern Hemisphere. However, we also identify sources of uncertainty that influence the multimodel consensus of our results including how LUC is implemented and the corresponding biogeophysical feedbacks that perturb climate. Therefore, our results highlight the urgent need to resolve the challenges in implementing LUC across models to quantify the impacts and consider how LUC contributes to regional changes in extremes associated with sustainable development pathways.

Climate extremes, land-climate feedbacks and land-use forcing at 1.5°C.

This article investigates projected changes in temperature and water cycle extremes at 1.5°C of global warming, and highlights the role of land processes and land-use changes (LUCs) for these projections. We provide new comparisons of changes in climate at 1.5°C versus 2°C based on empirical sampling analyses of transient simulations versus simulations from the 'Half a degree Additional warming, Prognosis and Projected Impacts' (HAPPI) multi-model experiment. The two approaches yield similar overall results regarding changes in climate extremes on land, and reveal a substantial difference in the occurrence of regional extremes at 1.5°C versus 2°C. Land processes mediated through soil moisture feedbacks and land-use forcing play a major role for projected changes in extremes at 1.5°C in most mid-latitude regions, including densely populated areas in North America, Europe and Asia. This has important implications for low-emissions scenarios derived from integrated assessment models (IAMs), which include major LUCs in ambitious mitigation pathways (e.g. associated with increased bioenergy use), but are also shown to differ in the simulated LUC patterns. Biogeophysical effects from LUCs are not considered in the development of IAM scenarios, but play an important role for projected regional changes in climate extremes, and are thus of high relevance for sustainable development pathways.This article is part of the theme issue 'The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'.

Large uncertainty in carbon uptake potential of land-based climate-change mitigation efforts.

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.

Assessing uncertainties in land cover projections.

Understanding uncertainties in land cover projections is critical to investigating land-based climate mitigation policies, assessing the potential of climate adaptation strategies and quantifying the impacts of land cover change on the climate system. Here, we identify and quantify uncertainties in global and European land cover projections over a diverse range of model types and scenarios, extending the analysis beyond the agro-economic models included in previous comparisons. The results from 75 simulations over 18 models are analysed and show a large range in land cover area projections, with the highest variability occurring in future cropland areas. We demonstrate systematic differences in land cover areas associated with the characteristics of the modelling approach, which is at least as great as the differences attributed to the scenario variations. The results lead us to conclude that a higher degree of uncertainty exists in land use projections than currently included in climate or earth system projections. To account for land use uncertainty, it is recommended to use a diverse set of models and approaches when assessing the potential impacts of land cover change on future climate. Additionally, further work is needed to better understand the assumptions driving land use model results and reveal the causes of uncertainty in more depth, to help reduce model uncertainty and improve the projections of land cover.

Hotspots of uncertainty in land-use and land-cover change projections: a global-scale model comparison.

Model-based global projections of future land-use and land-cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global-scale LULC change models representing a wide range of assumptions of future biophysical and socioeconomic conditions. We attribute components of uncertainty to input data, model structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios, we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g., boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process and improving the allocation mechanisms of LULC change models remain important challenges. Current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches, and many studies ignore the uncertainty in LULC projections in assessments of LULC change impacts on climate, water resources or biodiversity.

Reducing emissions from agriculture to meet the 2 °C target.

More than 100 countries pledged to reduce agricultural greenhouse gas (GHG) emissions in the 2015 Paris Agreement of the United Nations Framework Convention on Climate Change. Yet technical information about how much mitigation is needed in the sector vs. how much is feasible remains poor. We identify a preliminary global target for reducing emissions from agriculture of ~1 GtCO2 e yr-1 by 2030 to limit warming in 2100 to 2 °C above pre-industrial levels. Yet plausible agricultural development pathways with mitigation cobenefits deliver only 21-40% of needed mitigation. The target indicates that more transformative technical and policy options will be needed, such as methane inhibitors and finance for new practices. A more comprehensive target for the 2 °C limit should be developed to include soil carbon and agriculture-related mitigation options. Excluding agricultural emissions from mitigation targets and plans will increase the cost of mitigation in other sectors or reduce the feasibility of meeting the 2 °C limit.