Elke Stehfest

Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison

Significance Agriculture is arguably the sector most affected by climate change, but assessments differ and are thus difficult to compare. We provide a globally consistent, protocol-based, multimodel climate change assessment for major crops with explicit characterization of uncertainty. Results with multimodel agreement indicate strong negative effects from climate change, especially at higher levels of warming and at low latitudes where developing countries are concentrated. Simulations that consider explicit nitrogen stress result in much more severe impacts from climate change, with implications for adaptation planning. Here we present the results from an intercomparison of multiple global gridded crop models (GGCMs) within the framework of the Agricultural Model Intercomparison and Improvement Project and the Inter-Sectoral Impacts Model Intercomparison Project. Results indicate strong negative effects of climate change, especially at higher levels of warming and at low latitudes; models that include explicit nitrogen stress project more severe impacts. Across seven GGCMs, five global climate models, and four representative concentration pathways, model agreement on direction of yield changes is found in many major agricultural regions at both low and high latitudes; however, reducing uncertainty in sign of response in mid-latitude regions remains a challenge. Uncertainties related to the representation of carbon dioxide, nitrogen, and high temperature effects demonstrated here show that further research is urgently needed to better understand effects of climate change on agricultural production and to devise targeted adaptation strategies.

Exploring global changes in nitrogen and phosphorus cycles in agriculture induced by livestock production over the 1900–2050 period

Crop-livestock production systems are the largest cause of human alteration of the global nitrogen (N) and phosphorus (P) cycles. Our comprehensive spatially explicit inventory of N and P budgets in livestock and crop production systems shows that in the beginning of the 20th century, nutrient budgets were either balanced or surpluses were small; between 1900 and 1950, global soil N surplus almost doubled to 36 trillion grams (Tg)·y−1 and P surplus increased by a factor of 8 to 2 Tg·y−1. Between 1950 and 2000, the global surplus increased to 138 Tg·y−1 of N and 11 Tg·y−1 of P. Most surplus N is an environmental loss; surplus P is lost by runoff or accumulates as residual soil P. The International Assessment of Agricultural Knowledge, Science, and Technology for Development scenario portrays a world with a further increasing global crop (+82% for 2000–2050) and livestock production (+115%); despite rapidly increasing recovery in crop (+35% N recovery and +6% P recovery) and livestock (+35% N and P recovery) production, global nutrient surpluses continue to increase (+23% N and +54% P), and in this period, surpluses also increase in Africa (+49% N and +236% P) and Latin America (+75% N and +120% P). Alternative management of livestock production systems shows that combinations of intensification, better integration of animal manure in crop production, and matching N and P supply to livestock requirements can effectively reduce nutrient flows. A shift in human diets, with poultry or pork replacing beef, can reduce nutrient flows in countries with intensive ruminant production.

Competition for land.

A key challenge for humanity is how a future global population of 9 billion can all be fed healthily and sustainably. Here, we review how competition for land is influenced by other drivers and pressures, examine land-use change over the past 20 years and consider future changes over the next 40 years. Competition for land, in itself, is not a driver affecting food and farming in the future, but is an emergent property of other drivers and pressures. Modelling studies suggest that future policy decisions in the agriculture, forestry, energy and conservation sectors could have profound effects, with different demands for land to supply multiple ecosystem services usually intensifying competition for land in the future. In addition to policies addressing agriculture and food production, further policies addressing the primary drivers of competition for land (population growth, dietary preference, protected areas, forest policy) could have significant impacts in reducing competition for land. Technologies for increasing per-area productivity of agricultural land will also be necessary. Key uncertainties in our projections of competition for land in the future relate predominantly to uncertainties in the drivers and pressures within the scenarios, in the models and data used in the projections and in the policy interventions assumed to affect the drivers and pressures in the future.

Global trends and uncertainties in terrestrial denitrification and N2O emissions

Soil nitrogen (N) budgets are used in a global, distributed flow-path model with 0.5° × 0.5° resolution, representing denitrification and N2O emissions from soils, groundwater and riparian zones for the period 1900–2000 and scenarios for the period 2000–2050 based on the Millennium Ecosystem Assessment. Total agricultural and natural N inputs from N fertilizers, animal manure, biological N2 fixation and atmospheric N deposition increased from 155 to 345 Tg N yr−1 (Tg = teragram; 1 Tg = 1012 g) between 1900 and 2000. Depending on the scenario, inputs are estimated to further increase to 408–510 Tg N yr−1 by 2050. In the period 1900–2000, the soil N budget surplus (inputs minus withdrawal by plants) increased from 118 to 202 Tg yr−1, and this may remain stable or further increase to 275 Tg yr−1 by 2050, depending on the scenario. N2 production from denitrification increased from 52 to 96 Tg yr−1 between 1900 and 2000, and N2O–N emissions from 10 to 12 Tg N yr−1. The scenarios foresee a further increase to 142 Tg N2–N and 16 Tg N2O–N yr−1 by 2050. Our results indicate that riparian buffer zones are an important source of N2O contributing an estimated 0.9 Tg N2O–N yr−1 in 2000. Soils are key sites for denitrification and are much more important than groundwater and riparian zones in controlling the N flow to rivers and the oceans.

Impact of future land use and land cover changes on atmospheric chemistry-climate interactions

annual soil NO emissions by ∼1.2 TgN yr −1 (9%), whereas isoprene emissions decrease by ∼50 TgC yr −1 (−12%). The analysis shows increases in simulated boundary layer ozone mixing ratios up to ∼9 ppbv and more than a doubling in hydroxyl radical concentrations over deforested areas in Africa. Small changes in global atmosphere‐biosphere fluxes of NOx and ozone point to compensating effects. Decreases in soil NO emissions in deforested regions are counteracted by a larger canopy release of NOx caused by reduced foliage uptake. Despite this decrease in foliage uptake, the ozone deposition flux does not decrease since surface layer mixing ratios increase because of a reduced oxidation of isoprene by ozone. Our study indicates that the simulated impact of land cover and land use changes on atmospheric chemistry depends on a consistent representation of emissions, deposition, and canopy interactions and their dependence on meteorological, hydrological, and biological drivers to account for these compensating effects. It results in negligible changes in the atmospheric oxidizing capacity and, consequently, in the lifetime of methane. Conversely, we expect a pronounced increase in oxidizing capacity as a consequence of anthropogenic emission increases. Citation: Ganzeveld, L., L. Bouwman, E. Stehfest, D. P. van Vuuren, B. Eickhout, and J. Lelieveld (2010), Impact of future land use and land cover changes on atmospheric chemistry‐climate interactions, J. Geophys. Res., 115, D23301,

A land-use systems approach to represent land-use dynamics at continental and global scales

Most of the current global land cover datasets and global scale land-use models use a classification of land cover based on the dominant land cover type within a distinct region or pixel. Such a classification disregards the diversity and intensity of human influence on land systems. In this paper we propose a novel way of classification and modeling land-use using a classification based on land-use systems (LUSs) that represent specific combinations of human-environment interactions. A cluster analysis was used to identify and map these LUSs. The analysis accounted for population density, accessibility to market places, land-use/cover types and livestock densities. A conceptual framework was developed to model dynamics in LUSs accounting for both land cover and land management changes. LUSs changes were simulated based on changes in both local socio-economic and biophysical conditions and regional-scale changes in demand for agricultural products. The new land-use systems change model was used in the context of the integrated assessment model IMAGE.

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

Abstract 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.

The representation of landscapes in global scale assessments of environmental change

Landscape ecology has provided valuable insights in the relations between spatial structure and the functioning of landscapes. However, in most global scale environmental assessments the representation of landscapes is reduced to the dominant land cover within a 0.5 degree pixel, disregarding the insights about the role of structure, pattern and composition for the functioning of the landscape. This paper discusses the contributions landscape ecology can make to global scale environmental assessments. It proposes new directions for representing landscape characteristics at broad spatial scales. A contribution of landscape ecologists to the representation of landscape characteristics in global scale assessments will foster improved information and assessments for the design of sustainable earth system governance strategies.

Including CO 2 implications of land occupation in LCAs—method and example for livestock products

PurposeUntil recently, life cycle assessments (LCAs) have only addressed the direct greenhouse gas emissions along a process chain, but ignored the CO2 emissions of land-use. However, for agricultural products, these emissions can be substantial. Here, we present a new methodology for including the implications of land occupation for CO2 emissions to realistically reflect the consequences of consumers’ decisions.MethodIn principle, one can distinguish five different approaches of addressing the CO2 consequences of land occupation: (1) assuming constant land cover, (2) land-use change related to additional production of the product under consideration, (3) historic land-use change, assuming historical relations between existing area and area expansion (4) land-use change related to less production of the product under consideration (“missed potential carbon sink” of land occupation), and (5) an approach of integrating land conversion emissions and delayed uptake due to land occupation. Approach (4) is presented in this paper, using LCA data on land occupation, and carbon dynamics from the IMAGE model. Typically, if less production occurs, agricultural land will be abandoned, leading to a carbon sink when vegetation is regrowing. This carbon sink, which does not occur if the product would still be consumed, is thus attributed to the product as “missed potential carbon sink”, to reflect the CO2 implications of land occupations.ResultsWe analyze the missed potential carbon sink by relating land occupation data from LCA studies to the potential carbon sink as calculated by an Integrated Global Assessment Model and its process-based, spatially explicit carbon cycle model. Thereby, we account for regional differences, heterogeneity in land-use, and different time horizons. Example calculations for several livestock products show that the CO2 consequences of land occupation can be in the same order of magnitude as the other process related greenhouse gas emissions of the LCA, and depend largely on the production system. The highest CO2 implications of land occupation are calculated for beef and lamb, with beef production in Brazil having a missed potential carbon sink more than twice as high as the other GHG emissions.ConclusionsGiven the significant contribution of land occupation to the total GHG balance of agricultural products, they need to be included in life cycle assessments in a realistic way. The new methodology presented here reflects the consequences of producing or not producing a certain commodity, and thereby it is suited to inform consumers fully about the consequences of their choices.

Projections of the availability and cost of residues from agriculture and forestry

By‐products of agricultural and forestry processes, known as residues, may act as a primary source of renewable energy. Studies assessing the availability of this resource offer little insight on the drivers and constraints of the available potential as well as the associated costs and how these may vary across scenarios. This study projects long‐term global supply curves of the available potential using consistent scenarios of agriculture and forestry production, livestock production and fuel use from the spatially explicit integrated assessment model IMAGE. In the projections, residue production is related to agricultural and forestry production and intensification, and the limiting effect of ecological and alternative uses of residues are accounted for. Depending on the scenario, theoretical potential is projected to increase from approximately 120 EJ yr−1 today to 140–170 EJ yr−1 by 2100, coming mostly from agricultural production. To maintain ecological functions approximately 40% is required to remain in the field, and a further 20–30% is diverted towards alternative uses. Of the remaining potential (approximately 50 EJ yr−1 in 2100), more than 90% is available at costs <10