The 17 Sustainable Development Goals (SDGs) and 169 targets under Agenda 2030 of the United Nations map a coherent global sustainability ambition at a level of detail general enough to garner ...consensus amongst nations. However, achieving the global agenda will depend heavily on successful national-scale implementation, which requires the development of effective science-driven targets tailored to specific national contexts and supported by strong national governance. Here we assess the feasibility of achieving multiple SDG targets at the national scale for the Australian land-sector. We scaled targets to three levels of ambition and two timeframes, then quantitatively explored the option space for target achievement under 648 plausible future environmental, socio-economic, technological and policy pathways using the Land-Use Trade-Offs (LUTO) integrated land systems model. We show that target achievement is very sensitive to global efforts to abate emissions, domestic land-use policy, productivity growth rate, and land-use change adoption behaviour and capacity constraints. Weaker target-setting ambition resulted in higher achievement but poorer sustainability outcomes. Accelerating land-use dynamics after 2030 changed the targets achieved by 2050, warranting a longer-term view and greater flexibility in sustainability implementation. Simultaneous achievement of multiple targets is rare owing to the complexity of sustainability target implementation and the pervasive trade-offs in resource-constrained land systems. Given that hard choices are needed, the land-sector must first address the essential food/fibre production, biodiversity and land degradation components of sustainability via specific policy pathways. It may also contribute to emissions abatement, water and energy targets by capitalizing on co-benefits. However, achieving targets relevant to the land-sector will also require substantial contributions from other sectors such as clean energy, food systems and water resource management. Nations require globally coordinated, national-scale, comprehensive, integrated, multi-sectoral analyses to support national target-setting that prioritizes efficient and effective sustainability interventions across societies, economies and environments.
Urbanization and climate change are together exacerbating water scarcity-where water demand exceeds availability-for the world's cities. We quantify global urban water scarcity in 2016 and 2050 under ...four socioeconomic and climate change scenarios, and explored potential solutions. Here we show the global urban population facing water scarcity is projected to increase from 933 million (one third of global urban population) in 2016 to 1.693-2.373 billion people (one third to nearly half of global urban population) in 2050, with India projected to be most severely affected in terms of growth in water-scarce urban population (increase of 153-422 million people). The number of large cities exposed to water scarcity is projected to increase from 193 to 193-284, including 10-20 megacities. More than two thirds of water-scarce cities can relieve water scarcity by infrastructure investment, but the potentially significant environmental trade-offs associated with large-scale water scarcity solutions must be guarded against.
Abstract
Air pollution kills nearly 1 million people per year in China. In response, the Chinese government implemented the Air Pollution Prevention and Control Action Plan (APPCAP) from 2013 to 2017 ...which had a significant impact on reducing PM
2.5
concentration. However, the health benefits of the APPCAP are not well understood. Here we examine the spatiotemporal dynamics of annual deaths attributable to PM
2.5
pollution (DAPP) in China and the contribution from the APPCAP using decomposition analysis. Despite a 36.1% increase in DAPP from 2000 to 2017, The APPCAP-induced improvement in air quality achieved substantial health benefits, with the DAPP in 2017 reduced by 64 thousand (6.8%) compared to 2013. However, the policy is unlikely to result in further major reductions in DAPP and more ambitious policies are required to reduce the health impacts of air pollution by 2030 and meet the United Nation’s Sustainable Development Goal 3.
Land-use change alters the dynamics of freshwater ecosystem services flows by affecting both service supply (by influencing hydrological processes and runoff) and demand (via changes in human water ...use). However, few studies have considered the wide range of effects of land-use change on freshwater ecosystem services' flows. In this study, we distinguished the impacts of changing water supply and demand in the Aojiang River watershed, Fujian Province, China, an important water resource for more than seven million people. Rapid urbanization between 1991 and 2015 led to a minor increase of 2.5% in the supply of freshwater ecosystem services. However, demand increased by 96.3%, leading to a 25.7% overall decrease in freshwater ecosystem services flows. Downstream demand for freshwater increased substantially due to large shifts in agricultural, urban, and industrial activities. Our analysis provides detailed information on freshwater ecosystem services flows from supply to beneficiaries within a watershed, thus facilitating integrated watershed management and decision making. This study demonstrates how land-use change and ecosystem services' flows can be integrated both at local and regional scales for land-use management, water reallocation, and ecological compensation, thus promoting the sustainability of freshwater ecosystems.
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•Land-use change of 1991–2015 was dominated by deforestation and urbanization.•Impervious surfaces slightly increased freshwater ecosystem service supply.•Agricultural, domestic and industrial activities greatly increased demand.•Freshwater ecosystem services flows decreased 25.7%.•Ecosystem services flows can inform eco-compensation schemes.
Computational and data handling limitations have constrained time-series analyses of land-cover change at high-spatial resolution over large (e.g., continental) extents. However, a new set of ...cloud-computing services offer an opportunity for improving knowledge of land change at finer grain. We constructed a historical set of seven high-resolution wall-to-wall land-cover maps at continental scale for Australia and analyzed temporal and spatial changes of land-cover from 1985 to 2015 at 5-year time-steps using Google Earth Engine (GEE). We used 281,962 Landsat scenes for producing median cloud-free composites at each time-step. We established a pseudo ground-truth dataset and used a PCA-based outlier detection method to reduce its uncertainty. A random forest model was trained at each time-step for classifying raw data into six land-cover classes: Cropland, Forest, Grassland, Built-up, Water, and Other areas, using 49 predictor datasets and nearly 20,000 training points. We further constructed uncertainty maps at each time-step as a proxy of per-pixel confidence. The average overall accuracy of the seven 30 m-resolution land-cover maps was ~93%. Built-up and Water areas displayed the highest user and producer accuracies (>93%), with Grasslands and Other areas slightly lower (~82–88%). Classification uncertainty was lower in more homogeneous landscapes (i.e., large expanses of a single land-cover class). Around 510,975 km2 (±69,877 km2) of land changed over the 30 years at an average of ~17,033 km2 yr−1 (±2329 km2 yr−1). Cropland and Forests declined by ~64,836 km2 (±16,437 km2) and ~ 152,492 km2 (±24,749 km2) over 30 years, mainly converting to Grassland. Built-up areas experienced the highest relative increases, increasing from 12,320 km2 in 1985 to 15,013 km2 in 2015 (~19.2%, ±3.1%). The sensitivity, i.e., proportion of pixels correctly classified as having changed, was over 96%, whereas the specificity, i.e., the proportion of pixels correctly classified as no-change, was over 68%. Numerous potential applications of these first-of-their-kind, detailed spatiotemporal maps of land use and land-change assessment exist spanning many areas of environmental impact assessment, policy, and management. Similarly, this methodological framework can provide a useful template for assessing continental-scale, high-resolution land dynamics more broadly.
•We mapped Australia's land-cover at 30 m resolution every 5 years from 1985 to 2015.•Overall accuracy exceeded 90% and the sensitivity for representing change was >96%.•Land-cover changed at a rate of ~17,033 km2 yr−1 (±2329 km2 yr−1).•Forests and Cropland area declined, Built-up had the highest rate of increase.•Maps provide a new high-resolution time-series land-cover product for Australia.
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► Here I synthesize the impact of incentives on ecosystem services via land use change. ► Incentives influence land use changes which affect multiple ecosystem services. ► Linkages ...vary over space and time, may be non-linear, and include feedbacks. ► Quantifying linkages are essential to capture incentive synergies and avoid tensions. ► Advancement in the modeling of linkages is required.
Incentive schemes are increasingly used to motivate the supply of ecosystem services from agro-ecosystems through changes in land use and management. Here, I synthesize the complex effects of incentives on ecosystem services through their influence on land use and management. Linkages between incentives and land use change, and between land use change and ecosystem services can be one-to-many, many-to-one, and many-to-many. Change in land use and management can affect multiple ecosystem services, with both co-benefits and trade-offs. Incentives can motivate multiple changes in land use and management and multiple incentives often interact with both synergies and tensions in their effect upon ecosystem services. These vary over both space and time, and can be non-linear. Depending on incentive design, changes in ecosystem service supply can also have a feedback effect on incentive prices. I suggest that continued quantitative development is required to further explore these linkages: in the influence of incentives on land use change; in the impact of land use change on ecosystem services, and; in ecosystem service supply feedbacks on incentive prices. Quantifying and understanding these linkages is essential to progress more comprehensive analyses of the impact of incentives on ecosystem services, and the design of incentives capable of realizing synergies and avoiding tensions.
•Global sensitivity and uncertainty analysis were applied to the APSIM-wheat model.•Sensitivities of four key outputs to cultivar parameters were assessed.•Interactions between cultivar, ...environmental and management parameters were found.•Fertilization significantly affected the sensitivities of cultivar parameters.•Cultivar parameters need to be carefully calibrated to reduce uncertainty.
Process-based crop models use many cultivar parameters to simulate crop growth. Usually, these parameters cannot be directly measured and need to be calibrated when the crop model is applied to a new environment or a new cultivar. Determining the relative importance of the cultivar parameters to the specific outputs could streamline the calibration of crop models for new cultivars. Sensitivity analysis can quantify the influence of model input parameters on model outputs. We applied the variance-based global sensitivity analysis to the wheat module of the Agricultural Production Systems sIMulator (APSIM) for the first time and calculated the sensitivity of four outputs including yield, biomass, flowering day, and maturity day to ten cultivar parameters including both the main and total effects sensitivity indices. We explored the effects of changing climate, soil, and management practices on parameter sensitivity by analyzing two fertilization rates (0 and 100kgNha−1), across five sites in Australia's cereal-growing regions. Uncertainties for the four outputs with varying cultivar parameters, climate–soil conditions and management practices were evaluated. We found that yield was most sensitive to the cultivar parameters that determine the yield component (grains per gram stem, max grain size, and potential grain filling rate) and the phenology parameters that determine length of the reproductive stages (thermal time from floral initiation to flowing and thermal time from start grain filling to maturity). All ten cultivar parameters affected biomass, amongst which the parameters of vernalization sensitivity and thermal time from floral initiation to flowering were the most influential. Fertilization influenced the rank order of parameter sensitivities more strongly than climate–soil conditions for yield and biomass outputs. Under 0kgNha−1, with the variation of cultivar parameters simulated yield varied from 64 to 3559kgha−1 (minimum and maximum), biomass from 693 to 12,864kgha−1. Fertilization of 100kgNha−1 increased the maximum yield to 9157kgha−1 and biomass to 22,057kgha−1. We conclude that to minimize cultivar-related uncertainty, cultivar parameters should be carefully calibrated when applying the APSIM-wheat model to a new cultivar in a new environment. By targeting the most influential phenological parameters for calibration first and then the yield component parameters, the calibration of APSIM can be streamlined.
Abstract
Lakes are important natural resources and carbon gas emitters and are undergoing rapid changes worldwide in response to climate change and human activities. A detailed global ...characterization of lakes and their long-term dynamics does not exist, which is however crucial for evaluating the associated impacts on water availability and carbon emissions. Here, we map 3.4 million lakes on a global scale, including their explicit maximum extents and probability-weighted area changes over the past four decades. From the beginning period (1984–1999) to the end (2010–2019), the lake area increased across all six continents analyzed, with a net change of +46,278 km
2
, and 56% of the expansion was attributed to reservoirs. Interestingly, although small lakes (<1 km
2
) accounted for just 15% of the global lake area, they dominated the variability in total lake size in half of the global inland lake regions. The identified lake area increase over time led to higher lacustrine carbon emissions, mostly attributed to small lakes. Our findings illustrate the emerging roles of small lakes in regulating not only local inland water variability, but also the global trends of surface water extent and carbon emissions.
Environmentally extended input–output analysis (EEIOA) supports environmental policy by quantifying how demand for goods and services leads to resource use and emissions across the economy. However, ...some types of resource use and emissions require spatially explicit impact assessment for meaningful interpretation, which is not possible in conventional EEIOA. For example, water use in locations of scarcity and of abundance are not environmentally equivalent. Opportunities for spatially explicit impact assessment in conventional EEIOA are limited because official input–output tables tend to be produced at the scale of political units, which are not usually well-aligned with environmentally relevant spatial units. In this study, spatially explicit water-scarcity factors and a spatially disaggregated Australian water-use account were used to develop water-scarcity extensions that were coupled with a multiregional input–output model (MRIO). The results link demand for agricultural commodities to the problem of water scarcity in Australia and globally. Important differences were observed between the water-use and water-scarcity footprint results as well as the relative importance of direct and indirect water use, with significant implications for sustainable production and consumption-related policies. The approach presented here is suggested as a feasible general approach for incorporating spatially explicit impact assessments in EEIOA.
China has responded to a national land-system sustainability emergency via an integrated portfolio of large-scale programmes. Here we review 16 sustainability programmes, which invested US$378.5 ...billion (in 2015 US$), covered 623.9 million hectares of land and involved over 500 million people, mostly since 1998. We find overwhelmingly that the interventions improved the sustainability of China's rural land systems, but the impacts are nuanced and adverse outcomes have occurred. We identify some key characteristics of programme success, potential risks to their durability, and future research needs. We suggest directions for China and other nations as they progress towards the Sustainable Development Goals of the United Nations' Agenda 2030.
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