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Abstract: Environmental targets are often used in planning for sustainable agricultural landscapes but their impacts are rarely known. In this paper we introduce landscape futures analysis as a method which combines linear programming optimisation with scenario analysis in quantifying the environmental, economic, and social impacts associated with achieving environmental targets, on a landscape scale. We applied the technique in the Lower Murray in southern Australia. Landscape futures models were used to identify specific geographic locations in the landscape for six natural resource management (NRM) actions such that regional environmental targets are achieved. The six potential NRM actions that may be undertaken to achieve environmental targets include remnant vegetation management, ecological restoration, conservation farming, deep-rooted perennials, and the production of biomass and biofuels feedstock for renewable energy generation. We developed landscape futures under four alternative spatial prioritisation policy options and four future climate and commodity price scenarios. The impacts of each landscape future were calculated across a range of environmental, economic, and social indicators. The external drivers, climate change and commodity prices, and internal decisions such as policy options for spatially prioritising NRM actions, both have a strong influence on the costs and benefits of achieving environmental targets. Illustrative results for the cleared agricultural areas in the Mallee region indicate that whilst achieving targets can have substantial environmental benefits, it requires large areas of land use and land management change, and is likely to be costly (up to $348.5 M per year) with flow-on impacts on the regional economy and communities. Environmental targets can be achieved more cost-effectively through spatial planning. Costs can be further reduced if markets are established for carbon, biomass, and biofuels to enable landholders to generate income from undertaking NRM. Landscape futures analysis is an effective tool for supporting the strategic regional NRM policy and planning decisions of how best to set and achieve environmental targets. [Copyright &y& Elsevier]

Abstract: Much effort is expended toward planning for conservation, natural resource management and sustainable land use in agricultural landscapes. Although often not explicitly stated, the aims of these efforts are often to restore natural capital for the provision of ecosystem services and stimulate multifunctionality in landscapes. However, the scarcity of resources for, and the potential economic impact of, ameliorative actions that restore natural capital necessitates the identification of cost-effective geographic priorities, or hotspots, which provide multiple ecosystem goods and services. This requires the integrated spatial modelling of multiple environmental and economic processes accompanied by clear goals and performance indicators. Identification of hotspots provides guidance for highly targeted land use change that cost-effectively adds to the stocks of natural capital in a landscape. Additionally, the multifunctionality of the landscape can be increased through the provision of multiple ecosystem goods and services. This paper begins by examining data requirements for identifying geographic hotspots for land use change. This study integrates traditionally disparate landscape-scale biophysical and economic data and models. The elements of natural capital considered here are species and ecosystems, soil and water resources, and the atmosphere. It is demonstrated that locating ameliorative actions towards hotspots will be more cost-effective at restoring natural capital and stimulating landscape multifunctionality than a random targeting approach. We calculate these efficiencies using a small set of indicators for assessing aspects of multifunctionality. The focus of this study is the agricultural landscapes of the Lower Murray region of south-eastern Australia. [Copyright &y& Elsevier]