| Home | << 1 2 3 4 5 6 >> |
|
Weindl, I., Bodirsky, B. L., Rolinski, S., Biewald, A., Lotze-Campen, H., Muller, C., et al. (2017). Livestock production and the water challenge of future food supply: Implications of agricultural management and dietary choices. Global Environmental Change-Human and Policy Dimensions, 47, 121–132.
Abstract: Human activities use more than half of accessible freshwater, above all for agriculture. Most approaches for reconciling water conservation with feeding a growing population focus on the cropping sector. However, livestock production is pivotal to agricultural resource use, due to its low resource-use efficiency upstream in the food supply chain. Using a global modelling approach, we quantify the current and future contribution of livestock production, under different demand-and supply-side scenarios, to the consumption of “green” precipitation water infiltrated into the soil and “blue” freshWater withdrawn from rivers, lakes and reservoirs. Currently, cropland feed production accounts for 38% of crop water consumption and grazing involves 29% of total agricultural water consumption (9990 km(3) yr(-1)). Our analysis shows that changes in diets and livestock productivity have substantial implications for future consumption of agricultural blue water (19-36% increase compared to current levels) and green water (26-69% increase), but they can, at best, slow down trends of rising water requirements for decades to come. However, moderate productivity reductions in highly intensive livestock systems are possible without aggravating water scarcity. Productivity gains in developing regions decrease total agricultural water consumption, but lead to expansion of irrigated agriculture, due to the shift from grassland/green water to cropland/blue water resources. While the magnitude of the livestock water footprint gives cause for concern, neither dietary choices nor changes in livestock productivity will solve the water challenge of future food supply, unless accompanied by dedicated water protection policies.
|
|
Riahi, K., van Vuuren, D. P., Kriegler, E., Edmonds, J., O’Neill, B. C., Fujimori, S., et al. (2017). The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview. Glob. Environ. Change, 42, 153–168.
Abstract: Abstract This 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 long-term 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. The associated annual CO2 emissions of the baseline scenarios range from about 25 GtCO2 to more than 120 GtCO2 per year by 2100. With respect to mitigation, we find that associated costs strongly depend on three factors: (1) the policy assumptions, (2) the socio-economic narrative, and (3) the stringency of the target. The carbon price for reaching the target of 2.6 W/m2 that is consistent with a temperature change limit of 2 °C, differs in our analysis thus by about a factor of three across the SSP marker scenarios. Moreover, many models could not reach this target from the SSPs with high mitigation challenges. While the SSPs were designed to represent different mitigation and adaptation challenges, the resulting narratives and quantifications span a wide range of different futures broadly representative of the current literature. This allows their subsequent use and development in new assessments and research projects. Critical next steps for the community scenario process will, among others, involve regional and sectoral extensions, further elaboration of the adaptation and impacts dimension, as well as employing the SSP scenarios with the new generation of earth system models as part of the 6th climate model intercomparison project (CMIP6).
Keywords: Shared Socioeconomic Pathways; SSP; Climate change; RCP; Community scenarios; Mitigation; Adaptation
|
|
Dietrich, J. P., Popp, A., & Lotze-Campen, H. (2013). Reducing the loss of information and gaining accuracy with clustering methods in a global land-use model. Ecol. Model., 263, 233–243.
Abstract: Global land-use models have to deal with processes on several spatial scales, ranging from the global scale down to the farm level. The increasing complexity of modern land-use models combined with the problem of limited computational resources represents a challenge to modelers. One solution of this problem is to perform spatial aggregation based on a regular grid or administrative units such as countries. Unfortunately this type of aggregation flattens many regional differences and produces a homogenized map of the world. In this paper we present an alternative aggregation approach using clustering methods. Clustering reduces the loss of information due to aggregation by choosing an appropriate aggregation pattern. We investigate different clustering methods, examining their quality in terms of information conservation. Our results indicate that clustering is always a good choice and preferable compared to grid-based aggregation. Although all the clustering methods we tested delivered a higher degree of information conservation than grid-based aggregation, the choice of clustering method is not arbitrary. Comparing outputs of a model fed with original data and a model fed with aggregated data, bottom-up clustering delivered the best results for the whole range of numbers of clusters tested. (C) 2013 Elsevier B.V. All rights reserved.
Keywords: aggregation; downscaling; clustering; information conservation; land use model; scale; scales; agriculture; simulation; dynamics; pattern
|
|
Dietrich, J. P., Schmitz, C., Lotze-Campen, H., Popp, A., & Muller, C. (2014). Forecasting technological change in agriculture-An endogenous implementation in a global, and use model. Technological Forecasting and Social Change, 81, 236–249.
Abstract: Technological change in agriculture plays a decisive role for meeting future demands for agricultural goods. However, up to now, agricultural sector models and models on land use change have used technological change as an exogenous input due to various information and data deficiencies. This paper provides a first attempt towards an endogenous implementation based on a measure of agricultural land use intensity. We relate this measure to empirical data on investments in technological change. Our estimated yield elasticity with respect to research investments is 029 and production costs per area increase linearly with an increasing yield level. Implemented in the global land use model MAgPIE (”Model of Agricultural Production and its Impact on the Environment”) this approach provides estimates of future yield growth. Highest future yield increases are required in Sub-Saharan Africa, the Middle East and South Asia. Our validation with FAO data for the period 1995-2005 indicates that the model behavior is in line with observations. By comparing two scenarios on forest conservation we show that protecting sensitive forest areas in the future is possible but requires substantial investments into technological change. (C) 2013 Elsevier Inc. All rights reserved.
|
|
Dietrich, J. P., Schmitz, C., Lotze-Campen, H., Popp, A., & Müller, C. (2014). Forecasting technological change in agriculture—An endogenous implementation in a global land use model. Technological Forecasting and Social Change, 81, 236–249.
Abstract: ► Endogenous technological change in an economic land use model ► Estimation of yield elasticity with respect to investments in technological change ► Projections of future agricultural productivity rates ► Validation with observed data and historic trends ► Trade-off between required technological change and forest protection objectives Technological change in agriculture plays a decisive role for meeting future demands for agricultural goods. However, up to now, agricultural sector models and models on land use change have used technological change as an exogenous input due to various information and data deficiencies. This paper provides a first attempt towards an endogenous implementation based on a measure of agricultural land use intensity. We relate this measure to empirical data on investments in technological change. Our estimated yield elasticity with respect to research investments is 0.29 and production costs per area increase linearly with an increasing yield level. Implemented in the global land use model MAgPIE (“Model of Agricultural Production and its Impact on the Environment”) this approach provides estimates of future yield growth. Highest future yield increases are required in Sub-Saharan Africa, the Middle East and South Asia. Our validation with FAO data for the period 1995–2005 indicates that the model behavior is in line with observations. By comparing two scenarios on forest conservation we show that protecting sensitive forest areas in the future is possible but requires substantial investments into technological change.
|