Darran King

Comparing Spatially Explicit Ecological and Social Values for Natural Areas to Identify Effective Conservation Strategies

Consideration of the social values people assign to relatively undisturbed native ecosystems is critical for the success of science-based conservation plans. We used an interview process to identify and map social values assigned to 31 ecosystem services provided by natural areas in an agricultural landscape in southern Australia. We then modeled the spatial distribution of 12 components of ecological value commonly used in setting spatial conservation priorities. We used the analytical hierarchy process to weight these components and used multiattribute utility theory to combine them into a single spatial layer of ecological value. Social values assigned to natural areas were negatively correlated with ecological values overall, but were positively correlated with some components of ecological value. In terms of the spatial distribution of values, people valued protected areas, whereas those natural areas underrepresented in the reserve system were of higher ecological value. The habitats of threatened animal species were assigned both high ecological value and high social value. Only small areas were assigned both high ecological value and high social value in the study area, whereas large areas of high ecological value were of low social value, and vice versa. We used the assigned ecological and social values to identify different conservation strategies (e.g., information sharing, community engagement, incentive payments) that may be effective for specific areas. We suggest that consideration of both ecological and social values in selection of conservation strategies can enhance the success of science-based conservation planning.

Landscape futures analysis: Assessing the impacts of environmental targets under alternative spatial policy options and future scenarios

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

Biofuels agriculture: landscape-scale trade-offs between fuel, economics, carbon, energy, food, and fiber

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.

Impacts of climate change on lower Murray irrigation

First‐generation biofuels are an existing, scalable form of renewable energy of the type urgently required to mitigate climate change. In this study, we assessed the potential benefits, costs, and trade‐offs associated with biofuels agriculture to inform bioenergy policy. We assessed different climate change and carbon subsidy scenarios in an 11.9 million ha (5.48 million ha arable) region in southern Australia. We modeled the spatial distribution of agricultural production, full life‐cycle net greenhouse gas (GHG) emissions and net energy, and economic profitability for both food agriculture (wheat, legumes, sheep rotation) and biofuels agriculture (wheat, canola rotation for ethanol/biodiesel production). The costs, benefits, and trade‐offs associated with biofuels agriculture varied geographically, with climate change, and with the level of carbon subsidy. Below we describe the results in general and provide (in parentheses) illustrative results under historical mean climate and a carbon subsidy of A

Impact of agricultural management practices on soil organic carbon: simulation of Australian wheat systems

20 t−1 CO2−e. Biofuels agriculture was more profitable over an extensive area (2.85 million ha) of the most productive arable land and produced large quantities of biofuels (1.7 GL yr−1). Biofuels agriculture substantially increased economic profit (145.8 million

Meta‐modeling soil organic carbon sequestration potential and its application at regional scale

A yr−1 or 30%), but had only a modest net GHG abatement (−2.57 million t CO2−e yr−1), and a negligible effect on net energy production (−0.11 PJ yr−1). However, food production was considerably reduced in terms of grain (−3.04 million t yr−1) and sheep meat (−1.89 million head yr−1). Wool fiber production was also substantially reduced (−23.19 kt yr−1). While biofuels agriculture can produce short‐term benefits, it also has costs, and the vulnerability of biofuels to climatic warming and drying renders it a myopic strategy. Nonetheless, in some areas the profitability of biofuels agriculture is robust to variation in climate and level of carbon subsidy and these areas may form part of a long‐term diversified mix of land‐use solutions to climate change if trade‐offs can be managed.

Contribution of site assessment toward prioritising investment in natural capital

This article evaluates irrigated agriculture sector response and resultant economic impacts of climate change for a part of the Murray Darling Basin in Australia. A water balance model is used to predict reduced basin inflows for mild, moderate and severe climate change scenarios involving 1, 2 and 4°C warming, and predict 13, 38 and 63% reduced inflows. Impact on irrigated agricultural production and profitability are estimated with a mathematical programming model using a two-stage approach that simultaneously estimates short and long-run adjustments. The model accounts for a range of adaptive responses including: deficit irrigation, temporarily following of some areas, permanently reducing the irrigated area and changing the mix of crops. The results suggest that relatively low cost adaptation strategies are available for a moderate reduction in water availability and thus costs of such a reduction are likely to be relatively small. In more severe climate change scenarios greater costs are estimated. Adaptations predicted include a reduction in total area irrigated and investments in efficient irrigation. A shift away from perennial to annual crops is also predicted as the latter can be managed more profitably when water allocations in some years are very low.

Influence of management and environment on Australian wheat: information for sustainable intensification and closing yield gaps

Quantifying soil organic carbon (SOC) dynamics at a high spatial and temporal resolution in response to different agricultural management practices and environmental conditions can help identify practices that both sequester carbon in the soil and sustain agricultural productivity. Using an agricultural systems model (the Agricultural Production Systems sIMulator), we conducted a high spatial resolution and long-term (122 years) simulation study to identify the key management practices and environmental variables influencing SOC dynamics in a continuous wheat cropping system in Australias 96 million ha cereal-growing regions. Agricultural practices included five nitrogen application rates (0-200 kg N ha(-1) in 50 kg N ha(-1) increments), five residue removal rates (0-100% in 25% increments), and five residue incorporation rates (0-100% in 25% increments). We found that the change in SOC during the 122-year simulation was influenced by the management practices of residue removal (linearly negative) and fertilization (nonlinearly positive) - and the environmental variables of initial SOC content (linearly negative) and temperature (nonlinearly negative). The effects of fertilization were strongest at rates up to 50 kg N ha(-1) , and the effects of temperature were strongest where mean annual temperatures exceeded 19 °C. Reducing residue removal and increasing fertilization increased SOC in most areas except Queensland where high rates of SOC decomposition caused by high temperature and soil moisture negated these benefits. Management practices were particularly effective in increasing SOC in south-west Western Australia - an area with low initial SOC. The results can help target agricultural management practices for increasing SOC in the context of local environmental conditions, enabling farmers to contribute to climate change mitigation and sustaining agricultural production.

Ecohydrological and socioeconomic integration for the operational management of environmental flows

Upscaling the results from process-based soil-plant models to assess regional soil organic carbon (SOC) change and sequestration potential is a great challenge due to the lack of detailed spatial information, particularly soil properties. Meta-modeling can be used to simplify and summarize process-based models and significantly reduce the demand for input data and thus could be easily applied on regional scales. We used the pre-validated Agricultural Production Systems sIMulator (APSIM) to simulate the impact of climate, soil, and management on SOC at 613 reference sites across Australias cereal-growing regions under a continuous wheat system. We then developed a simple meta-model to link the APSIM-modeled SOC change to primary drivers, i.e., the amount of recalcitrant SOC, plant available water capacity of soil, soil pH, and solar radiation, temperature, and rainfall in the growing season. Based on high-resolution soil texture data and 8165 climate data points across the study area, we used the meta-model to assess SOC sequestration potential and the uncertainty associated with the variability of soil characteristics. The meta-model explained 74% of the variation of final SOC content as simulated by APSIM. Applying the meta-model to Australias cereal-growing regions reveals regional patterns in SOC, with higher SOC stock in cool, wet regions. Overall, the potential SOC stock ranged from 21.14 to 152.71 Mg/ha with a mean of 52.18 Mg/ha. Variation of soil properties induced uncertainty ranging from 12% to 117% with higher uncertainty in warm, wet regions. In general, soils in Australias cereal-growing regions under continuous wheat production were simulated as a sink of atmospheric carbon dioxide with a mean sequestration potential of 8.17 Mg/ha.

What Actually Confers Adaptive Capacity? Insights from Agro-Climatic Vulnerability of Australian Wheat

In prioritising investment in natural capital, site-scale indicators are increasingly used to capture fine-scale variation inherent in complex ecosystems. However, site assessment is costly, has high skill demand, and is time-consuming. We assess the marginal gain associated with including site-scale indicators in metrics typically used by agri-environmental stewardship schemes and payments for ecosystem services. We developed 18 landscape-scale and 14 site-scale indicators to prioritise sites for on-ground works in a real-world conservation auction in South Australia. We used the Analytical Hierarchy Process (AHP) to weight them and multi-attribute utility theory to combine them in quantifying site priority. Bid benefit was calculated as the product of impact of the proposed works and the site priority. Cost-utility analysis was used to rank and select bids with benefits calculated using: i) landscape-scale indicators, and; ii) both landscape- and site-scale indicators. We found that the inclusion of site-scale indicators has limited influence on the ranking and selection of bids for investment when cost of investment is included in the decision-making process. We suggest that, depending on the nature of costs and benefits, and if landholder engagement, information sharing, and trust-building can be achieved in more efficient ways, site assessment may not be necessary. Thereby a significant barrier to the adoption of cost-effective agri-environment schemes and payments for ecosystem services may be eliminated.