World's human migration patterns in 2000-2019 unveiled by high-resolution data.

Despite being a topical issue in public debate and on the political agenda for many countries, a global-scale, high-resolution quantification of migration and its major drivers for the recent decades remained missing. We created a global dataset of annual net migration between 2000 and 2019 (~10 km grid, covering the areas of 216 countries or sovereign states), based on reported and downscaled subnational birth (2,555 administrative units) and death (2,067 administrative units) rates. We show that, globally, around 50% of the world's urban population lived in areas where migration accelerated urban population growth, while a third of the global population lived in provinces where rural areas experienced positive net migration. Finally, we show that, globally, socioeconomic factors are more strongly associated with migration patterns than climatic factors. While our method is dependent on census data, incurring notable uncertainties in regions where census data coverage or quality is low, we were able to capture migration patterns not only between but also within countries, as well as by socioeconomic and geophysical zonings. Our results highlight the importance of subnational analysis of migration-a necessity for policy design, international cooperation and shared responsibility for managing internal and international migration.

Crop Yield Loss Risk Is Modulated by Anthropogenic Factors.

High crop yield variation between years-caused by extreme shocks on the food production system such as extreme weather-can have substantial effects on food production. This in turn introduces vulnerabilities into the global food system. To mitigate the effects of these shocks, there is a clear need to understand how different adaptive capacity measures link to crop yield variability. While existing literature provides many local-scale studies on this linkage, no comprehensive global assessment yet exists. We assessed reported crop yield variation for wheat, maize, soybean, and rice for the time period 1981-2009 by measuring both yield loss risk (variation in negative yield anomalies considering all years) and changes in yields during "dry" shock and "hot" shock years. We used the machine learning algorithm XGBoost to assess the explanatory power of selected gridded indicators of anthropogenic factors globally (i.e., adaptive capacity measures such as the human development index, irrigation infrastructure, and fertilizer use) on yield variation at a 0.5° resolution within climatically similar regions (to rule out the role of average climate conditions). We found that the anthropogenic factors explained 40%-60% of yield loss risk variation across the whole time period, whereas the factors provided noticeably lower (5%-20%) explanatory power during shock years. On a continental scale, especially in Europe and Africa, the factors explained a high proportion of the yield loss risk variation (up to around 80%). Assessing crop production vulnerabilities on global scale provides supporting knowledge to target specific adaptation measures, thus contributing to global food security.

Heavy metals from heavy land use? Spatio-temporal patterns of urban runoff metal loads.

Urban hydrology is characterized by increased runoff and various pollutant sources. We studied the spatio-temporal patterns of stormwater metal (Al, V, Cr, Mn, Fe, Cu, Zn, and Pb) concentrations and loads in five urbanized and one rural catchment in Southern Finland. The two-year continuous monitoring revealed a non-linear seasonal relationship between catchment urban intensity and metal export. For runoff, seasonal variation decreased with increasing imperviousness. The most urbanized catchments experienced greatest temporal variation in metal concentrations: the annual Cu and Zn loads in most of the studied urbanized catchments were up to 86 times higher compared to the rural site, whereas Fe loads in the urbanized catchments were only circa 29% of the rural load. Total metal levels were highest in the winter, whereas the winter peak of dissolved metal concentrations was less pronounced. The collection of catchment characteristics explained well the total metal concentrations, whereas for the dissolved concentrations the explanatory power was weaker. Our catchment-scale analysis revealed a mosaic of mainly diffuse pollutant sources and calls for catchment-scale management designs. As urban metal export occurred across seasons, solutions that operate also in cold conditions are needed.

Making Waves: Joining forces for better doctoral education in water research.

We argue that doctoral education in water needs an elevated focus towards educating game changers who can drive innovation and change towards more sustainable futures across academic and non-academic settings. Today's doctoral graduates in water are increasingly employed outside academia, and challenged to understand complex and interconnected systems, to integrate and synthesize information from different disciplines and to lead the way toward increasingly creative, resilient, robust, and socially sustainable solutions. Supervisors are challenged by interdisciplinary research topics and by growing diversity of objectives, too often at the cost of their wellbeing. The need to keep up with the rapid scientific and technological development and floods of big data is pressing. We synthesize key insights from higher education literature and doctoral programs in water research to identify priority actions targeted at four key actor groups: supervisors and supervisees, research group, university, and industry. The actions contribute to appropriate resourcing, enabling an environment for enhanced teamwork practices, and systematic structures for progress. Establishing supporting structures will leverage the much-needed communities of practice involved in co-creating and transforming supervision and education of doctoral students in interdisciplinary water research.

Climate change risks pushing one-third of global food production outside the safe climatic space.

Food production on our planet is dominantly based on agricultural practices developed during stable Holocene climatic conditions. Although it is widely accepted that climate change perturbs these conditions, no systematic understanding exists on where and how the major risks for entering unprecedented conditions may occur. Here, we address this gap by introducing the concept of safe climatic space (SCS), which incorporates the decisive climatic factors of agricultural production: precipitation, temperature, and aridity. We show that a rapid and unhalted growth of greenhouse gas emissions (SSP5-8.5) could force 31% of the global food crop and 34% of livestock production beyond the SCS by 2081-2100. The most vulnerable areas are South and Southeast Asia and Africa's Sudano-Sahelian Zone, which have low resilience to cope with these changes. Our results underpin the importance of committing to a low-emissions scenario (SSP1-2.6), whereupon the extent of food production facing unprecedented conditions would be a fraction.

Diffuse sources dominate the sulfate load into Finnish surface waters.

Sulfate (SO42-) affects the cycling of ecologically important substances, such as carbon, nutrients and metals, but the contribution of anthropogenic activities in sulfate load entering aquatic systems is poorly known. We calculate specific sulfate loads for land cover types, atmospheric deposition and point sources, and then estimate the source-specific flux of sulfate to Finnish surface waters. The largest sulfate flux, entering mostly the Baltic Sea, originates from agricultural fields on acid sulfate soil (24% of total flux). Forests on mineral soil, which cover 67% of the country's surface area, form the second largest source (21%). Additionally, agricultural fields on non-acid soil cause noticeable sulfate flux (16%). Pulp and paper mills were the key point sources (20%) for sulfate. We find that anthropogenic activities contribute to elevated sulfate levels in waters potentially affecting the cycling of nutrients, metals and formation of greenhouse gases in naturally sulfate-poor freshwaters. Based on these findings, sulfate should be systematically included in monitoring and pollution control measures.

The Planet's Stressed River Basins: Too Much Pressure or Too Little Adaptive Capacity?

Freshwater is one of the most critical elements for sustainable development of ecosystems and societies. River basins, concomitant with administrative zones, form a common unit for freshwater management. So far, no comprehensive, global analysis exists that would link the ecological challenges of the planet's river basins to the capacity of the societies to cope with them. We address this gap by performing a geospatial resilience analysis for a global set of 541 river basins. We use the social-ecological systems approach by relating three ecological vulnerability factors (human footprint, natural hazards, and water scarcity) with three adaptive capacity factors (governance, economy, and human development), based on temporal trajectories from 1990 to 2015. Additionally, we examine resilience by subtracting ecological vulnerability from adaptive capacity. The most striking result is the fundamentally different patterns of controlling factors of the resilience in different developing regions, particularly those of Africa and Asia. Their root causes are particularly low adaptive capacity in Africa and high ecological vulnerability in Asia. Alarmingly, the difference between those continents grew within the study period. Finally, this study highlights the rapid dynamics of adaptive capacity in comparison to ecological vulnerability, the latter having more inertia. Their fragile balance is of our interest; they can either support or counteract each other depending on the geographic location.

Gridded global datasets for Gross Domestic Product and Human Development Index over 1990-2015.

An increasing amount of high-resolution global spatial data are available, and used for various assessments. However, key economic and human development indicators are still mainly provided only at national level, and downscaled by users for gridded spatial analyses. Instead, it would be beneficial to adopt data for sub-national administrative units where available, supplemented by national data where necessary. To this end, we present gap-filled multiannual datasets in gridded form for Gross Domestic Product (GDP) and Human Development Index (HDI). To provide a consistent product over time and space, the sub-national data were only used indirectly, scaling the reported national value and thus, remaining representative of the official statistics. This resulted in annual gridded datasets for GDP per capita (PPP), total GDP (PPP), and HDI, for the whole world at 5 arc-min resolution for the 25-year period of 1990-2015. Additionally, total GDP (PPP) is provided with 30 arc-sec resolution for three time steps (1990, 2000, 2015).

Variation in stream diatom communities in relation to water quality and catchment variables in a boreal, urbanized region.

Intensive anthropogenic land use such as urbanization alters the hydrological cycle, water chemistry and physical habitat characteristics, thus impairing stream physicochemical and biological quality. Diatoms are widely used to assess stream water quality as they integrate water chemistry temporally and reflect the joint influence of multiple stressors on stream biota. However, knowledge of the major community patterns of diatoms in urban streams remains limited especially in boreal regions. The aim of this study was to examine the effects of water chemistry and catchment characteristics on stream diatom communities, and to test the performance of the Index of Pollution Sensitivity (IPS) as a stream water quality indicator across an urban-to-rural gradient in southern Finland. Diatom community structure and species richness were related to local-scale variables such as water temperature, aluminium concentration, and electrical conductivity, which were in turn influenced by patterns in catchment land use and land cover. Diatoms reflected the intensity of human activities as more intensive land use increased the occurrence of pollution-tolerant species. The change in community structure along the land use intensity gradient was accompanied by a distinct decline in species richness. On the contrary, the IPS index failed to indicate differences in water quality along the urban-to-rural gradient as no consistent differences in the IPS values were found. Our results highlight the joint influence of multifaceted factors that underlie diatom patterns, and show that diatom biodiversity can be used as cost-effective metric indicating urban stream conditions. However, the IPS index turned out to be an unsuitable tool for assessing water quality among these streams.