Benefits and trade-offs of optimizing global land use for food, water, and carbon

Current large-scale patterns of land use reflect history, local traditions, and productioncosts, much more so than they reflect biophysical potential or global supply anddemand for food and freshwater, or—more recently—climate change mitigation. Wequantified alternative land-use allocations that consider trade-offs for these demandsby combining a dynamic vegetation model and an optimization algorithm to determinePareto-optimal land-use allocations under changing climate conditions in 2090–2099and alternatively in 2033–2042. These form the outer bounds of the option spacefor global land-use transformation. Results show a potential to increase all threeindicators (+83% in crop production,+8% in available runoff, and+3% in carbonstorage globally) compared to the current land-use configuration, with clear land-use priority areas: Tropical and boreal forests were preserved, crops were produced intemperate regions, and pastures were preferentially allocated in semiarid grasslands andsavannas. Transformations toward optimal land-use patterns would imply extensivereconfigurations and changes in land management, but the required annual land-usechanges were nevertheless of similar magnitude as those suggested by established land-use change scenarios. The optimization results clearly show that large benefits couldbe achieved when land use is reconsidered under a “global supply” perspective with aregional focus that differs across the world’s regions in order to achieve the supply ofkey ecosystem services under the emerging global pressures

Web-based forest resources management decision support system

In this paper, we present a web-based decision support system (DSS)—wSADfLOR—to facilitate the access of stakeholders to tools that may contribute to enhancing forest management planning. The emphasis is on a web-based architecture and a web graphic user interface (wGUI) that may effectively support the analysis of trade-offs between ecosystem services in order to address participatory and sustainable forest management objectives. For that purpose, the wGUI provides remote access to a management information system, enabling users to analyze environmental and biometric data and topological information as well. Moreover, the wGUI provides remote access to forest simulators so that users may define and simulate prescriptions such as chronological sequences of management options and the corresponding forest ecosystem services outcomes. Remote access to management planning methods is further provided so that users may input their objectives and constraints. The wGUI delivers information about tradeoffs between ecosystem services in the form of decision maps so that users in different locations may negotiate bundles of ecosystem services as well as the plan needed to provide them. The multiple criteria programming routines provide proposals for management plans that may be assessed further, using geographical and alphanumeric information provided by the wGUI. Results for an application to a forested landscape extending to 14,388 ha are presented and discussed. This landscape provides several ecosystem services and the development of its management plan involves multiple stakeholders. Results show that the web-based architecture and the wGUI provide effective access for stakeholders to information about the forest management planning area and to decision support tools that may contribute to addressing complex multi-objective and multiple-decision-maker management planning contexts. They also highlight that the involvement and participation of stakeholders in the design of the web-based architecture contributes to assuring the quality and the usability of the systeminfo:eu-repo/semantics/publishedVersio

Economic optimization for a dual-feedstock lignocellulosic-based sustainable biofuel supply chain considering greenhouse gas emission and soil carbon stock

Environmental factors, including greenhouse gas (GHG) emissions and soil organic carbon (SOC), should be considered when building a sustainable biofuel supply chain. This work developed a three-step optimization approach integrating a geographical information system-based mixed-integer linear programming model to economically optimize the biofuel supply chain on the premise of meeting certain GHG emission criteria. The biomass supply grid cell was considered first, based on a maximum level of GHG emissions, prior to economic optimization. The optimization simultaneously considered dual-feedstock sourcing, selection between distributed and centralized configurations, and the impact of maintaining SOC balance in agricultural soil on biomass availability. The applicability of the modeling approach was demonstrated through a case study that optimized a dual-feedstock renewable jet fuel supply chain via a gasification-Fischer–Tropsch (gasification-FT) conversion pathway in 2050 under three biomass availability scenarios. The case study results show that the differences in procurement costs and GHG emissions between energy crops and agricultural residues have a large impact on the layout of the supply chain. The supply-chain configuration tends to be more centralized with large-scale biorefineries when a supply region has an intensive and centralized distribution of biomass resources. The cost-supply curves demonstrated the technical potential of biofuels that could be obtained at a certain level of cost. Additionally, sensitivity analysis shows that the GHG emission credit from producing extra electricity during the gasification-FT process will be significantly reduced with a rising share of renewable electricity generation in the future

Food security, risk management and climate change

This report identifies major constraints to the adaptive capacity of food organisations operating in Australia. This report is about food security, climate change and risk management. Australia has enjoyed an unprecedented level of food security for more than half a century, but there are new uncertainties emerging and it would be unrealistic – if not complacent – to assume the same level of food security will persist simply because of recent history. The project collected data from more than 36 case study organisations (both foreign and local) operating in the Australian food-supply chain, and found that for many businesses,  risk management practices require substantial improvement to cope with and exploit the uncertainties that lie ahead. Three risks were identified as major constraints to adaptive capacity of food organisations operating in Australia:  risk management practices; an uncertain regulatory environment – itself a result of gaps in risk management; climate change uncertainty and projections about climate change impacts, also related to risk management

Natural Environment Management and Applied Systems Analysis

This volume contains papers from the NEMASA Konan-IIASA Joint Workshop on Natural Environment Management and Applied Systems Analysis, which took place at IIASA September 6-8, 2000. The workshop was an activity of the research project "Modeling by Computational Intelligence and its Application to Natural Environment Management." The project is being supported by the Hirao Taro Foundation of the Konan University Association for Academic Research, Kobe, Japan. The management of the natural environment -- in particular, the use of advanced agricultural practices -- poses a major challenge to modern society, but perhaps applied systems analysis can help. The workshop set was about to: present new concepts and methodologies for managing the environment, and offer an open forum for the exchange of ideas among research disciplines, especially between agro-environmental and applied systems analysis research and between researchers and practitioners. The paper deal with a range of topics. The editors have arranged them into the following categories: (1) modeling methodologies, (2) data analysis, (3) land use, (4) water management, and (5) applications

Studies on factors affecting the evolution of agroecosystems in the Dakotas

This dissertation combines remote sensing and applied economics tools to study land use conversions in North Dakota and South Dakota that are tied to this region’s overall socio-economic welfare. Specifically, the region’s corn and soybeans cultivation expanded significantly over the past decade replacing the region’s grasslands and grain crops. In paper I, we estimate the localized impacts of the advent of corn-based ethanol plants on the Dakotas’ corn acreage. We implement a Difference-in-Difference framework through more flexible assumptions as the Parallel Paths assumption of the standard model fails to hold. We find strong trends in the Dakotas’ corn acreage over the past decade, but surprisingly some ethanol plants were found to have a negative impact on local corn acreage. In paper II, we evaluate crop competitiveness due to heterogeneous weather impacts on crop yields, and then test whether annual weather fluctuations explain land allocations among the Dakotas’ major land uses. Our integrated framework suggests that annual weather variability is an important determinant of regional land use decisions. Under the A1B emissions scenario of climate change, we find that the yields of all of the Dakotas’ major crops will decline by 2031-2060 relative to 1981-2010, leading to lower (higher) spring wheat (alfalfa) acres in Eastern (Western) Dakotas. In paper III, we develop and implement a satellite image-processing algorithm to estimate historical land use acres using raw Landsat sensor data, thereby extending the existing Cropland Data Layers back to 1984 in eastern Dakotas. We demonstrate that the availability of a longer time-series is useful as the rate of land use change may differ among different time-spans. In paper IV, we evaluate the cost-effectiveness of grassland conservation easements when spatial spillovers are present among private landowners. We first develop a conceptual model to incorporate social spillovers in evaluating the role of easements in inhibiting grassland conversions. We empirically test whether social spillovers are present by estimating hazard rates of conversion as a function of neighborhood density of grasslands and easements. Our findings suggest that easements are strategic complements to existing grasslands in preventing grassland conversions in the Dakotas

The Impact of Domestic and Global Biofuel Mandates on the German Agricultural Sector

The aim of this work is to evaluate the impact of domestic and global biofuel policies on Germany's agricultural sector. The central part of our study is divided into four sections. Section 2 presents in detail the issues that make biofuels a debated topic in today's economic policies. Fundamental aspects of our energy consumption patterns and the geographic location of our natural resources are highlighted together with a quantitative analysis of the recent surge in biofuels output capacity and estimates of their near-future deployment. An introduction to current and future biofuels production technologies is coupled with an overview of recent studies that assess their net contribution to harmful gaseous emissions and energy efficiency. The concerns associated with rising food prices and their likely causes are then briefly examined. Section 3 provides a thorough description of the subsidy, taxation and protection measures granted to biofuels across the world. Current governmental policies in the EU and its member states are given special attention. Section 4 presents the current literature on economic modelling and focuses on partial equilibrium (AGLINK-COSIMO, Impact, Esim, etc.) and general equilibrium frameworks (EPPA, GTAP, etc.). Section 5 simulates the impact of domestic and global biofuel policies in Germany within a Computable General Equilibrium framework. The LEITAP model is introduced. A description of the analysed scenarios is given on the basis of the envisaged biofuel blending mandates described in section 3. The simulation results are then evaluated with respect to production, prices, international trade and land use of the relevant commodities. The outcome clearly indicates that current biofuels policies significantly affect food markets as well as land allocation. The conclusion summarizes the main findings of our study and draws a comparison with results of other publications.

Multi-objective Allocation Optimization of Soil Conservation Measures Under Data Uncertainty

Many regions worldwide face soil loss rates that endanger future food supply. Constructing soil and water conservation measures reduces soil loss but comes with high labor costs. Multi-objective optimization allows considering both soil loss rates and labor costs, however, required spatial data contain uncertainties. Spatial data uncertainty has not been considered for allocating soil and water conservation measures. We propose a multi-objective genetic algorithm with stochastic objective functions considering uncertain soil and precipitation variables to overcome this gap. We conducted the study in three rural areas in Ethiopia. Uncertain precipitation and soil properties propagate to uncertain soil loss rates with values that range up to 14%. Uncertain soil properties complicate the classification into stable or unstable soil, which affects estimating labor requirements. The obtained labor requirement estimates range up to 15 labor days per hectare. Upon further analysis of common patterns in optimal solutions, we conclude that the results can help determine optimal final and intermediate construction stages and that the modeling and the consideration of spatial data uncertainty play a crucial role in identifying optimal solutions