Global change scenarios in coastal river deltas and their sustainable development implications.

Deltas play a critical role in the ambition to achieve global sustainable development given their relatively large shares in population and productive croplands, as well as their precarious low-lying position between upstream river basin development and rising seas. The large pressures on these systems risk undermining the persistence of delta societies, economies, and ecosystems. We analyse possible future development in 49 deltas around the globe under the Shared Socio-economic and Representative Concentration Pathways until 2100. Population density, urban fraction, and total and irrigated cropland fraction are three to twelve times greater in these deltas, on average, than in the rest of the world. Maximum river water discharges are projected to increase by 11-33 % and river sediment discharges are projected to decrease 26-37 % on average, depending on the scenario. Regional sea-level rise reaches almost 1.0 m by 2100 for certain deltas in the worst-case scenario, increasing to almost 2.0 m of relative rise considering land subsidence. Extreme sea levels could be much higher still-reaching over 4.0 m by 2100 for six of the 49 deltas analysed. Socio-economic conditions to support adaptation are the weakest among deltas with the greatest pressures, compounding the challenge of sustainable development. Asian and African deltas stand out as having heightened socio-economic challenges-huge population and land use pressures in most Asian deltas and the Nile delta; low capacity for adaptation in most African deltas and the Irrawaddy delta. Although, deltas in other parts of the world are not immune from these and other pressures, either. Because of unique pressures and processes operating in deltas, as in other "hotspots" such as small islands, mountains, and semi-arid areas, we recommend greater consideration and conceptualisation of environmental processes in global sustainable development agendas and in the Integrated Assessment Models used to guide global policy.

Aligning research with policy and practice for sustainable agricultural land systems in Europe.

Agriculture is widely recognized as critical to achieving the Sustainable Development Goals (SDGs), but researchers, policymakers, and practitioners have multiple, often conflicting yet poorly documented priorities on how agriculture could or should support achieving the SDGs. Here, we assess consensus and divergence in priorities for agricultural systems among research, policy, and practice perspectives and discuss the implications for research on trade-offs among competing goals. We analyzed the priorities given to 239 environmental and social drivers, management choices, and outcomes of agricultural systems from 69 research articles, the SDGs and four EU policies, and seven agricultural sustainability assessment tools aimed at farmers. We found all three perspectives recognize 32 variables as key to agricultural systems, providing a shared area of focus for agriculture's contribution to the SDGs. However, 207 variables appear in only one or two perspectives, implying that potential trade-offs may be overlooked if evaluated from only one perspective. We identified four approaches to agricultural land systems research in Europe that omit most of the variables considered important from policy and practice perspectives. We posit that the four approaches reflect prevailing paradigms of research design and data analysis and suggest future research design should consider including the 32 shared variables as a starting point for more policy- and practice-relevant research. Our identification of shared priorities from different perspectives and attention to environmental and social domains and the functional role of system components provide a concrete basis to encourage codesigned and systems-based research approaches to guide agriculture's contribution to the SDGs.

IMPROVING PREDICTIVE MODELS OF IN-STREAM PHOSPHORUS CONCENTRATION BASED ON NATIONALLY-AVAILABLE SPATIAL DATA COVERAGES.

Spatial data are playing an increasingly important role in watershed science and management. Large investments have been made by government agencies to provide nationally-available spatial databases; however, their relevance and suitability for local watershed applications is largely unscrutinized. We investigated how goodness of fit and predictive accuracy of total phosphorus (TP) concentration models developed from nationally-available spatial data could be improved by including local watershed-specific data in the East Fork of the Little Miami River, Ohio, a 1290 km2 watershed. We also determined whether a spatial stream network (SSN) modeling approach improved on multiple linear regression (nonspatial) models. Goodness of fit and predictive accuracy were highest for the SSN model that included local covariates, and lowest for the nonspatial model developed from national data. Septic systems and point source TP loads were significant covariates in the local models. These local data not only improved the models but enabled a more explicit interpretation of the processes affecting TP concentrations than more generic national covariates. The results suggest that SSN modeling greatly improves prediction and should be applied when using national covariates. Including local covariates further increases the accuracy of TP predictions throughout the studied watershed; such variables should be included in future national databases, particularly the locations of septic systems.

Towards a global sustainable development agenda built on social-ecological resilience.

Non-technical summary: The United Nations' sustainable development goals (SDGs) articulate societal aspirations for people and our planet. Many scientists have criticised the SDGs and some have suggested that a better understanding of the complex interactions between society and the environment should underpin the next global development agenda. We further this discussion through the theory of social-ecological resilience, which emphasises the ability of systems to absorb, adapt, and transform in the face of change. We determine the strengths of the current SDGs, which should form a basis for the next agenda, and identify key gaps that should be filled. Technical summary: The United Nations' sustainable development goals (SDGs) are past their halfway point and the next global development agenda will soon need to be developed. While laudable, the SDGs have received strong criticism from many, and scholars have proposed that adopting complex adaptive or social-ecological system approaches would increase the effectiveness of the agenda. Here we dive deeper into these discussions to explore how the theory of social-ecological resilience could serve as a strong foundation for the next global sustainable development agenda. We identify the strengths and weaknesses of the current SDGs by determining which of the 169 targets address each of 43 factors affecting social-ecological resilience that we have compiled from the literature. The SDGs with the strongest connections to social-ecological resilience are the environment-focus goals (SDGs 2, 6, 13, 14, 15), which are also the goals consistently under-prioritised in the implementation of the current agenda. In terms of the 43 factors affecting social-ecological resilience, the SDG strengths lie in their communication, inclusive decision making, financial support, regulatory incentives, economic diversity, and transparency in governance and law. On the contrary, ecological factors of resilience are seriously lacking in the SDGs, particularly with regards to scale, cross-scale interactions, and non-stationarity. Social media summary: The post-2030 agenda should build on strengths of SDGs 2, 6, 13, 14, 15, and fill gaps in scale, variability, and feedbacks.

A harmonized and spatially explicit dataset from 16 million payments from the European Union's Common Agricultural Policy for 2015.

The Common Agricultural Policy (CAP) is the largest budget item in the European Union, but varied data reporting hampers holistic analysis. Here we have assembled the first dataset to our knowledge to report individual CAP payments by standardized CAP funding measures and geolocation. We created this dataset by translating, geolocating to the county or province (NUTS3) level, and consistently harmonizing payment measures for over 16 million payments from 2015, originally reported by EU member states and compiled by the Open Knowledge Foundation Germany. This dataset and code allow in-depth analysis of over €60 billion in public spending by purpose and location for the first time, which enables both individual payment tracing and analysis by aggregation. These data are representative of the distribution of annual CAP payments from 2014 to 2020 and are of interest to researchers, policy makers, non-governmental organizations, and journalists for evaluating the distribution and impacts of CAP spending.

Billions in Misspent EU Agricultural Subsidies Could Support the Sustainable Development Goals.

The Common Agricultural Policy (CAP) is the guiding policy for agriculture and the largest single budget item in the European Union (EU). Agriculture is essential to meet the Sustainable Development Goals (SDGs), but the CAP's contribution to do so is uncertain. We analyzed the distribution of €59.4 billion of 2015 CAP payments and show that current CAP spending exacerbates income inequality within agriculture, while little funding supports climate-friendly and biodiverse farming regions. More than €24 billion of 2015 CAP direct payments went to regions where average farm incomes are already above the EU median income. A further €2.5 billion in rural development payments went to primarily urban areas. Effective monitoring indicators are also missing. We recommend redirecting and better monitoring CAP payments toward achieving the environmental, sustainability, and rural development goals stated in the CAP's new objectives, which would support the SDGs, the European Green Deal, and green COVID-19 recovery.

People and water: Exploring the social-ecological condition of watersheds of the United States.

A recent paradigm shift from purely biophysical towards social-ecological assessment of watersheds has been proposed to understand, monitor, and manipulate the myriad interactions between human well-being and the ecosystem services that watersheds provide. However, large-scale, quantitative studies in this endeavour remain limited. We utilised two newly developed 'big-data' sets-the Index of Watershed Integrity (IWI) and the Human Well-Being Index (HWBI)-to explore the social-ecological condition of watersheds throughout the conterminous U.S., and identified environmental and socio-economic influences on watershed integrity and human well-being. Mean county IWI was highly associated with ecoregion, industry-dependence, and state, in a spatially-explicit regression model (R2 = 0.77, P < 0.001), whereas HWBI was not (R2 = 0.31, P < 0.001). HWBI is likely influenced by factors not explored here, such as governance structure and formal and informal organisations and institutions. 'Win-win' situations in which both IWI and HWBI were above the 75th percentile were observed in much of Utah, Colorado, and New Hampshire, and lessons from governance that has resulted in desirable outcomes might be learnt from here. Eastern Kentucky and West Virginia, along with large parts of the desert southwest, had intact watersheds but low HWBI, representing areas worthy of further investigation of how ecosystem services might be utilised to improve well-being. The Temperate Prairies and Central USA Plains had widespread areas of low IWI but high HWBI, likely a result of historic exploitation of watershed resources to improve well-being, particularly in farming-dependent counties. The lower Mississippi Valley had low IWI and HWBI, which is likely related to historical (temporal) and upstream (spatial) impacts on both watershed integrity and well-being. The results emphasise the importance of considering spatial and temporal trade-offs when utilising the ecosystem services provided by watersheds to improve human well-being.