2017-08-25T16:31:17

This study addresses and conceptualizes the possible dependence of ecosystem services on prevailing air and/or water flow processes and conditions, and particularly on the trajectories and associated spatial reach of these flows in carrying services from supply to demand areas in the landscape. The present conceptualization considers and accounts for such flow-dependence in terms of potential and actually realized service supply and demand, which may generally differ and must therefore be distinguished due to and accounting for the prevailing conditions of service carrier flows. We here concretize and quantify such flow-dependence for a specific landscape case (the Stockholm region, Sweden) and for two examples of regulating ecosystem services: local climate regulation and storm water regulation. For these service and landscape examples, we identify, quantify and map key areas of potential and realized service supply and demand, based for the former (potential) on prevailing relatively static types of landscape conditions (such as land-cover/use, soil type and demographics), and for the latter (realized) on relevant carrier air and water flows. These first-order quantification examples constitute first steps towards further development of generally needed such flow-dependence assessments for various types of ecosystem services in different landscapes over the world.

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Numerous cities in the world have to handle and support increasing populations, with questions remaining concerning good planning strategies for their growth and development. Among these questions, access to nature for urban residents has been the subject of increased scrutiny in recent years. We here propose and apply a generally applicable new approach to quantitatively investigate the role of close access to natural or nature‐based green–blue areas for the well‐being of urban populations. A key novel aspect of this approach is to use income level as a measure of people's ability to choose their nearby living environment such that it provides them with the highest affordable level of well‐being. Based on this measure, we concretely investigate possible trends in local green–blue area access with increasing local income level in the case‐study example of the Stockholm Metropolitan region in Sweden. For this regional case, we find clear relationships between income level (and related degree of nationality homogeneity) and share of natural/nature‐based green–blue areas and man‐made grey areas within walksheds of different population segments. The results point at the importance of maintaining and restoring nearby natural and nature‐based green–blue areas as key solutions for increased well‐being of urban populations and call for further testing and comparative investigations of local‐scale associations between socio‐economic descriptors and physical environment in other parts of the world.

Rapid changes in high-latitude hydroclimate have important implications for human societies and environment. Previous studies of different regions have indicated better agreement between climate model results and observation data for the thermodynamic variable of surface air temperature (T) than for the water variables of precipitation (P), evapotranspiration (ET), and runoff (R). Here we compare climate model output with observations for 64 Nordic and Arctic hydrological basins of different sizes, and for the whole region combined. We find an unexpectedly high agreement between models and observations for R, about as high as the model-observation agreement for T and distinctly higher than that for P or ET. Model-observation agreement for R and T is also consistently higher on the whole-region scale than individual basin scales. In contrast, model-observation agreement for P and ET is overall lower, and for some error measures also lower for the whole region than for individual basins of various scales. Region-specific soil freeze-thaw bias of climate models can at least partly explain the low model-observation agreement for P and ET, while leaving modeled R relatively unaffected. Thereby, model projections for this region may be similarly reliable and directly useful for large-scale average conditions of R as of T.Plain Language Summary Climate is changing more rapidly in the Arctic than in many other places on Earth. To understand and project how the Arctic climate is changing, we use computer models that simulate the climate system. Often, such models are reported to perform better for simulations of temperature than for simulations of water, such as rain, snow, or river flow. They are often also reported to be better at large scales than at small scales. In our research, we have studied how well climate model results agree with meteorological observations, by studying data for 64 different rivers in the Nordic and Arctic regions. Contrary to what we expected, we found that models were about as good in simulating river flow as they were in simulating temperature and clearly better than they were at simulating rain and snow. For simulations of river flow and temperature, models were better at larger scales than smaller scales. Our results mean that it may be possible to use these models for understanding and projecting river flows with a similar reliability as for temperature for this region, at least on large scales.

Distinction between active and legacy sources of nutrients is needed for effective reduction of waterborne nutrient loads and associated eutrophication. This study quantifies main typological differences in nutrient load behaviour versus water discharge for active and legacy sources. This quantitative typology is used for source attribution based on monitoring data for water discharge and concentrations of total nitrogen (TN) and total phosphorous (TP) from 37 catchments draining into the Baltic Sea along the coastline of Sweden over the period 2003-2013. Results indicate dominant legacy source contributions to the monitored loads of TN and TP in most (33 of the total 37) study catchments. Dominant active sources are indicated in 1 catchment for TN, and mixed sources are indicated in 3 catchments for TN, and 4 catchments for TP. The TN and TP concentration contributions are quantified to be overall higher from the legacy than the active sources. Legacy concentrations also correlate well with key indicators of human activity in the catchments, agricultural land share for TN (R 2 = 0.65) and population density for TP (R 2 = 0.56). Legacy-dominated nutrient concentrations also change more slowly than in catchments with dominant active or mixed sources. Various data-based results and indications converge in indicating legacy source contributions as largely dominant, mainly anthropogenic, and with nearzero average change trends in the present study of catchments draining into the Baltic Sea along the coastline of Sweden, as in other parts of the world. These convergent indications emphasize needs to identify and map the different types of sources in each catchment, and differentiate strategies and measures to target each source type for possible achievement of shorter-and longer-term goals of water quality improvement.

Hydroclimatic change may affect the range of some infectious diseases, including tularemia. Previous studies have investigated associations between tularemia incidence and climate variables, with some also establishing quantitative statistical disease models based on historical data, but studies considering future climate projections are scarce. This study has used and combined hydro-climatic projection outputs from multiple global climate models (GCMs) in phase six of the Coupled Model Intercomparison Project (CMIP6), and site-specific, parameterized statistical tularemia models, which all imply some type of power-law scaling with preceding-year tularemia cases, to assess possible future trends in disease outbreaks for six counties across Sweden, known to include tularemia high-risk areas. Three radiative forcing (emissions) scenarios are considered for climate change projection until year 2100, incuding low (2.6 Wm−2), medium (4.5 Wm−2), and high (8.5 Wm−2) forcing. The results show highly divergent changes in future disease outbreaks among Swedish counties, depending primarily on site-specific type of the best-fit disease power-law scaling characteristics of (mostly positive, in one case negative) sub- or super-linearity. Results also show that scenarios of steeper future climate warming do not necessarily lead to steeper increase of future disease outbreaks. Along a latitudinal gradient, the likely most realistic medium climate forcing scenario indicates future disease decreases (intermittent or overall) for the relatively southern Swedish counties Örebro and Gävleborg (Ockelbo), respectively, and disease increases of considerable or high degree for the intermediate (Dalarna, Gävleborg (Ljusdal)) and more northern (Jämtland, Norrbotten; along with the more southern Värmland exception) counties, respectively.