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  • 1. Andersen, Hans Estrup
    et al.
    Blicher-Mathiesen, Gitte
    Thodsen, Hans
    Mejlhede Andersen, Peter
    Larsen, Søren E.
    Stålnacke, Per
    Humborg, Christoph
    Stockholm University, Faculty of Science, Stockholm University Baltic Sea Centre.
    Mörth, Carl-Magnus
    Stockholm University, Faculty of Science, Stockholm University Baltic Sea Centre.
    Smedberg, Erik
    Stockholm University, Faculty of Science, Stockholm University Baltic Sea Centre.
    Identifying Hot Spots of Agricultural Nitrogen Loss Within the Baltic Sea Drainage Basin2016In: Water, Air and Soil Pollution, ISSN 0049-6979, E-ISSN 1573-2932, Vol. 227, no 1Article in journal (Refereed)
    Abstract [en]

    Agricultural management practices are among the major drivers of agricultural nitrogen (N) loss. Legislation and management incentives for measures to mitigate N loss should eventually be carried out at the individual farm level. Consequently, an appropriate scale to simulate N loss from a scientific perspective should be at the farm scale. A data set of more than 4000 agricultural fields with combinations of climate, soils and agricultural management which overall describes the variations found in the Baltic Sea drainage basin was constructed. The soil-vegetation-atmosphere model Daisy (Hansen et al. 2012) was used to simulate N loss from the root zone of all agricultural fields in the data set. From the data set of Daisy simulations, we identified the most important drivers for N loss by multiple regression statistics and developed a statistical N loss model. By applying this model to a basin-wide data set on climate, soils and agricultural management at a 10 x 10 km scale, we were able to calculate root-zone N losses from the entire Baltic Sea drainage basin and identify N loss hot spots in a consistent way and at a level of detail not hitherto seen for this area. Further, the root-zone N loss model was coupled to estimates of nitrogen retention in catchments separated into retention in groundwater and retention in surface waters allowing calculation of the coastal N loading.

  • 2.
    Conley, Daniel J.
    et al.
    GeoBiosphere Science Centre, Department of Geology, Lund University, Sweden.
    Humborg, Christoph
    Stockholm University, Stockholm Resilience Centre.
    Smedberg, Erik
    Stockholm University, Faculty of Science, Department of Applied Environmental Science (ITM).
    Rahm, Lars
    Department of Water and Environmental Studies, Linköping University, Sweden.
    Papush, Liana
    Department of Water and Environmental Studies, Linköping University, Sweden.
    Danielsson, Åsa
    Department of Water and Environmental Studies, Linköping University, Sweden.
    Clarke, Annemarie
    Department of Marine Ecology, National Environmental Research Institute, Denmark.
    Pastuszak, Marianne
    Sea Fisheries Institute, Poland.
    Aigars, Juris
    Institute of Aquatic Ecology, University of Latvia, Latvia.
    Ciuffa, Daniele
    Department of Biology, University of Rome, Italy.
    Mörth, Carl-Magnus
    Stockholm University, Stockholm Resilience Centre.
    Past, present and future state of the biogeochemical Si cycle in the Baltic Sea.2008In: Journal of Marine Systems, Vol. 73, p. 338-346Article in journal (Refereed)
    Abstract [en]

    The Baltic Sea is one of many aquatic ecosystems that show long-term declines in dissolved silicate (DSi) concentrations due to anthropogenic alteration of the biogeochemical Si cycle. Reductions in DSi in aquatic ecosystems have been coupled to hydrological regulation reducing inputs, but also with eutrophication, although the relative significance of both processes remains unknown for the observed reductions in DSi concentrations. Here we combine present and historical data on water column DSi concentrations, together with estimates of present river DSi loads to the Baltic, the load prior to damming together with estimates of the long-term accumulation of BSi in sediments. In addition, a model has been used to evaluate the past, present and future state of the biogeochemical Si cycle in the Baltic Sea. The present day DSi load to the Baltic Sea is 855 ktons y− 1. Hydrological regulation and eutrophication of inland waters can account for a reduction of 420 ktons y− 1 less riverine DSi entering the Baltic Sea today. Using published data on basin-wide accumulation rates we estimate that 1074 ktons y− 1 of biogenic silica (BSi) is accumulating in the sediments, which is 36% higher than earlier estimates from the literature (791 ktons y− 1). The difference is largely due to the high reported sedimentation rates in the Bothnian Sea and the Bothnian Bay. Using river DSi loads and estimated BSi accumulation, our model was not able to estimate water column DSi concentrations as burial estimates exceeded DSi inputs. The model was then used to estimate the BSi burial from measured DSi concentrations and DSi load. The model estimate for the total burial of BSi in all three basins was 620 ktons y− 1, 74% less than estimated from sedimentation rates and sediment BSi concentrations. The model predicted 20% less BSi accumulation in the Baltic Proper and 10% less in the Bothnian Bay than estimated, but with significantly less BSi accumulation in the Bothnian Sea by a factor of 3. The model suggests there is an overestimation of basin-wide sedimentation rates in the Bothnian Bay and the Bothnian Sea. In the Baltic Proper, modelling shows that historical DSi concentrations were 2.6 times higher at the turn of the last century (ca. 1900) than at present. Although the DSi decrease has leveled out and at present there are only restricted areas of the Baltic Sea with limiting DSi concentrations, further declines in DSi concentrations will lead to widespread DSi limitation of diatoms with severe implications for the food web.

  • 3.
    Dahlgren Strååt, Kim
    et al.
    Stockholm University, Faculty of Science, Department of Environmental Science and Analytical Chemistry.
    Mörth, Carl-Magnus
    Stockholm University, Faculty of Science, Department of Environmental Science and Analytical Chemistry. Stockholm University, Faculty of Science, Department of Geological Sciences.
    Sobek, Anna
    Stockholm University, Faculty of Science, Department of Environmental Science and Analytical Chemistry.
    Smedberg, Erik
    Stockholm University, Faculty of Science, Stockholm University Baltic Sea Centre.
    Undeman, Emma
    Stockholm University, Faculty of Science, Department of Environmental Science and Analytical Chemistry. Stockholm University, Faculty of Science, Stockholm University Baltic Sea Centre.
    Modeling total particulate organic carbon (POC) flows in the Baltic Sea catchment2016In: Biogeochemistry, ISSN 0168-2563, E-ISSN 1573-515X, Vol. 128, no 1-2, p. 51-65Article in journal (Refereed)
    Abstract [en]

    The largest input source of carbon to the Baltic Sea catchment is river discharge. A tool for modeling riverine particulate organic carbon (POC) loads on a catchment scale is currently lacking. The present study describes a novel dynamic model for simulating flows of POC in all major rivers draining the Baltic Sea catchment. The processes governing POC input and transport in rivers described in the model are soil erosion, in-stream primary production and litter input. The Baltic Sea drainage basin is divided into 82 sub-basins, each comprising several land classes (e.g. forest, cultivated land, urban areas) and parameterized using GIS data on soil characteristics and topography. Driving forces are temperature, precipitation, and total phosphorous concentrations. The model evaluation shows that the model can predict annual average POC concentrations within a factor of about 2, but generally fails to capture the timing of monthly peak loads. The total annual POC load to the Baltic Sea is estimated to be 0.34 Tg POC, which constitutes circa 7-10 % of the annual total organic carbon (TOC) load. The current lack of field measurements of POC in rivers hampers more accurate predictions of seasonality in POC loads to the Baltic Sea. This study, however, identifies important knowledge gaps and provides a starting point for further explorations of large scale POC mass flows.

  • 4. Hong, Bongghi
    et al.
    Swaney, Dennis P.
    Mörth, Carl-Magnus
    Stockholm University, Stockholm Resilience Centre, Baltic Nest Institute.
    Smedberg, Erik
    Stockholm University, Stockholm Resilience Centre, Baltic Nest Institute.
    Hägg, Hanna Eriksson
    Stockholm University, Stockholm Resilience Centre, Baltic Nest Institute.
    Humborg, Christoph
    Stockholm University, Stockholm Resilience Centre, Baltic Nest Institute.
    Howarth, Robert W.
    Bouraoui, Faycal
    Evaluating regional variation of net anthropogenic nitrogen and phosphorus inputs (NANI/NAPI), major drivers, nutrient retention pattern and management implications in the multinational areas of Baltic Sea basin2012In: Ecological Modelling, ISSN 0304-3800, E-ISSN 1872-7026, Vol. 227, p. 117-135Article in journal (Refereed)
    Abstract [en]

    The NANI/NAPI (net anthropogenic nitrogen/phosphorus input) Calculator Toolbox described in this paper is designed to address the consequences to Baltic Sea nutrient loads of the significant variation in agronomic practices and dietary preferences among European countries whose watersheds comprise the Baltic Sea basin. A primary objective of this work is to develop regional parameters and datasets for this budgeting tool. A previous version of the toolbox was applied to the entire contiguous United States to calculate NANI and its components (atmospheric N deposition, fertilizer N application, agricultural N fixation and N in net food and feed imports). Here, it is modified for application to the Baltic Sea catchments, where coastal watersheds from several countries are draining to international waters. A similar accounting approach is taken for calculating NAPI, which includes fertilizer P application, P in net food and feed imports and non-food use of P by human. Regional variation of NANI/NAPI parameters (agricultural fixation rates, human intake rates and livestock intake and excretion rates) are estimated, and their impact on the regional nutrient budget and the riverine nutrient flux is evaluated. There is a distinct north-to-south gradient in NANI and NAPI across the Baltic Sea catchments, and regional nutrient inputs are strongly related to riverine nutrient fluxes. Analysis of regional nutrient retention pattern indicates that, for some countries, compliance to the Baltic Sea Action Plan would imply enormous changes in the agricultural sector.

  • 5.
    Humborg, Christoph
    et al.
    Stockholm University, Faculty of Science, Department of Applied Environmental Science (ITM).
    Smedberg, Erik
    Stockholm University, Faculty of Science, Department of Applied Environmental Science (ITM).
    Rodriguez Medina, Miguel
    Stockholm University, Faculty of Science, Department of Systems Ecology.
    Mörth, Carl-Magnus
    Stockholm University, Faculty of Science, Department of Geology and Geochemistry.
    Changes in dissolved silicate loads to the Baltic Sea: The effects of lakes and reservoirs2008In: Journal of Marine Systems, ISSN 0924-7963, E-ISSN 1879-1573, Vol. 73, no 3-4, p. 223-235Article in journal (Refereed)
    Abstract [en]

    We tested the hypothesis that dissolved silicate (DSi) yields [kg km− 2 yr− 1] of 82 major watersheds of the Baltic Sea can be expressed as a function of the hydraulic load (HL) as a measure of water residence time and the total organic carbon (TOC) concentration, both variables potentially increasing the DSi yield. Most boreal rivers fitted a linear regression model using HL as an independent variable to explain the DSi yield. Rivers with high HL, i.e., shortest residence times, showed highest DSi yields up to 2300 kg km− 2 yr− 1. This is most likely caused by an excess supply of DSi, i.e., the geochemical sources prevail over biological sinks in these boreal watersheds. The DSi yield for regulated and unregulated larger rivers of the boreal watersheds constituting about 40% of the total water discharge and of the total DSi load to the Baltic Sea, respectively, can be expressed as: DSi yield = 190 + 49.5 HL[m yr− 1] + 0.346 TOC [µM] (R2 = 0.80). Since both HL and TOC concentrations have decreased after damming, the DSi yields have decreased significantly in the regulated boreal watersheds, for the River Luleälven we estimated more than 30%. The larger eutrophic watersheds draining cultivated landscape of the southern catchment of the Baltic Sea and representing about 50% of the annual water discharge to the Baltic Sea, deviated from this pattern and showed lower DSi yields between 60–580 kg km− 2 yr− 1. DSi yields showed saturation curve like relationship to HL and it appears that DSi is retained in the watersheds efficiently through biogenic silica (BSi) production and subsequent sedimentation along the entire river network. The relationship between HL and DSi yields for all larger cultivated watersheds was best fitted by a Freundlich isotherm (DSi = 115.7HL109; R2 = 0.73), because once lake and reservoir area exceeds 10% of the watershed area, minimum DSi yields were reached. To estimate an uperturbed DSi yield for the larger eutrophic southeastern watersheds is still difficult, since no unperturbed watersheds for comparison were available. However, a rough estimate indicate that the DSi flux from the cultivated watersheds to the Baltic Sea is nowadays only half the uperturbed flux. Overall, the riverine DSi loads to the Baltic Sea might have dropped with 30–40% during the last century.

  • 6.
    Lind, Johan
    et al.
    Stockholm University, Faculty of Science, Department of Zoology.
    Hollén, Linda
    Stockholm University, Faculty of Science, Department of Zoology.
    Smedberg, Erik
    Stockholm University, Faculty of Science, Department of Zoology.
    Svensson, Ulrika
    Stockholm University, Faculty of Science, Department of Zoology.
    Vallin, Adrian
    Stockholm University, Faculty of Science, Department of Zoology.
    Jakobsson, Sven
    Stockholm University, Faculty of Science, Department of Zoology.
    Detection distance influencing escape behaviour in two parids (Parus major and P. caeruleus)2003In: Journal of Avian Biology, ISSN 0908-8857, E-ISSN 1600-048X, Vol. 34, no 3, p. 233-236Article in journal (Refereed)
    Abstract [en]

    When birds are attacked by aerial predators they should benefit by adjusting their escape to the prevailing attack situation. One important factor likely to affect escape decisions of prey, to our knowledge not previously studied, is the distance at which the attacking predator is detected. We investigated if great tits Parus major and blue tits P. caeruleus alter their escape behaviour to two different detection distances (2.3 m and 1m) by simulating surprise attacks using a predator model. Both species used the information about detection distance when escaping by increasing the escape angle at the shorter detection distance. In addition, blue tits adjusted to the shorter detection distance by dodging sideways more frequently. Great tits escaped initially steeper and faster than blue tits, whereas blue tits increased escape angle and speed more than great tits along the measured distance after taking wing

  • 7. Sferratore, Agata
    et al.
    Billen, Gilles
    Garnier, Josette
    Smedberg, Erik
    Stockholm University, Faculty of Science, Department of Applied Environmental Science (ITM).
    Humborg, Christoph
    Stockholm University, Faculty of Science, Department of Applied Environmental Science (ITM).
    Rahm, Lars
    Modelling nutrient fluxes from sub-arctic basin: Comparison of pristine vs. dammed rivers2008In: Journal of Marine Systems, ISSN 0924-7963, E-ISSN 1879-1573, Vol. 73, no 3-4, p. 236-249Article in journal (Refereed)
    Abstract [en]

    The deterministic Riverstrahler model of river functioning is applied for the first time to sub-arctic catchments. Seasonal nutrient (N, P, Si) deliveries to the coastal zone are simulated, and nutrient annual fluxes are established for the nearly pristine river Kalix (hereafter called Kalixälven) and the heavily dammed river Lule, (hereafter called Luleälven) both located in Northern Sweden and draining into the Bothnian Bay, Baltic Sea.

    For Kalixälven simulations are performed with a runoff calculated from precipitation, evapo-transpiration and temperature data for the period 1990–1999, using a hydrological model calibrated on observed monthly discharges at the river outlet. The same hydrological parameters are used to calculate specific runoff for the Luleälven basin in absence of dam regulation. Reservoir filling and emptying are simulated using a simplified representation of their management rules. Diffuse sources of nutrient are evaluated according to land cover of the catchment. The simulated seasonal trends are within the range of the observed data, in particular for discharge, dissolved silica, total phosphorus, inorganic nitrogen and total organic carbon. Specific runoff is 50% higher in the Luleälven than in the Kalixälven watershed due to higher altitudes and precipitations. Average silica, nitrate and phosphorus concentrations are much lower in Luleälven than in Kalixälven. Comparison of model results for the Luleälven with and without dams shows a reduction of respectively 25% and 30% in silica and phosphorus fluxes delivered at the outlet, while nitrogen delivery is increased by 10% in the dammed vs. undammed river system. The model allows assessing the respective role of reservoir trapping of nutrient in the reservoir through algal uptake and sedimentation, and of changes in the vegetation induced by flooding the valley formerly covered by forests and wetlands.

  • 8.
    Smedberg, Erik
    et al.
    Stockholm University, Stockholm Resilience Centre.
    Humborg, Christoph
    Stockholm University, Faculty of Science, Department of Applied Environmental Science (ITM).
    Jakobsson, Martin
    Stockholm University, Faculty of Science, Department of Geological Sciences.
    Mörth, Carl-Magnus
    Stockholm University, Faculty of Science, Department of Geological Sciences.
    Landscape elements and river chemistry as affected by river regulation: a 3-D perspective2009In: Hydrology and Earth System Sciences, ISSN 1027-5606, E-ISSN 1607-7938, Vol. 13, no 9, p. 1597-1606Article in journal (Refereed)
    Abstract [en]

    We tested the hypothesis whether individual land classes within a river catchment contribute equally to river loading with dissolved constituents or whether some land classes act as “hot spots” to river loading and if so, are these land classes especially affected by hydrological 5 alterations. The amount of land covered by forests and wetlands and the average soil depth of a river catchment explain 58–93% of the variability in total organic carbon (TOC) and dissolved silicate (DSi) concentrations for 22 river catchments in Northern Sweden. Whereas only 3% of the headwater areas of the Luleälven have been inundated by the creation of reservoirs, some 10% of the soils and aggregated 10 forest and wetland areas have been lost due to damming and further hydrological alteration such as bypassing entire sub-catchments by headrace tunnels. However, looking at individual forest classes, our estimates indicate that some 37% of the deciduous forests have been inundated by the four major reservoirs built in the Luleälven headwaters.These deciduous forest and wetlands formerly growing on top of alluvial deposits 15 along the river corridors forming the riparian zone play a vital role in loading river water with dissolved constituents, especially DSi. A digital elevation model draped with land classes and soil depths which highlights that topography of various land classes acting as hot spots is critical in determining water residence time in soils and biogeochemical fluxes. Thus, headwater areas of the Luleälven appear to be most sensitive 20 to hydrological alterations due to the thin soil cover (on average 2.7–4.5m) and only patchy appearance of forest and wetlands that were significantly perturbed. Moreover, since these headwater areas are characterized often by high specific discharge, this relatively minor change in the landscape when compared to the entire river catchment may indeed explain the significant lower fluxes at the river mouth.

    We tested the hypothesis whether individual land classes within a river catchment contribute equally to river loading with dissolved constituents or whether some land classes act as “hot spots” to river loading and if so, are these land classes especially affected by hydrological 5 alterations. The amount of land covered by forests and wetlands and the average soil depth of a river catchment explain 58–93% of the variability in total organic carbon (TOC) and dissolved silicate (DSi) concentrations for 22 river catchments in Northern Sweden. Whereas only 3% of the headwater areas of the Luleälven have been inundated by the creation of reservoirs, some 10% of the soils and aggregated10 forest and wetland areas have been lost due to damming and further hydrological alteration such as bypassing entire sub-catchments by headrace tunnels. However, looking at individual forest classes, our estimates indicate that some 37% of the deciduous forests have been inundated by the four major reservoirs built in the Luleälven headwaters.These deciduous forest and wetlands formerly growing on top of alluvial deposits 15 along the river corridors forming the riparian zone play a vital role in loading river water with dissolved constituents, especially DSi. A digital elevation model draped with land classes and soil depths which highlights that topography of various land classes acting as hot spots is critical in determining water residence time in soils and biogeochemicalfluxes. Thus, headwater areas of the Luleälven appear to be most sensitive 20 to hydrological alterations due to the thin soil cover (on average 2.7–4.5m) and only patchy appearance of forest and wetlands that were significantly perturbed. Moreover, since these headwater areas are characterized often by high specific discharge, this relatively minor change in the landscape when compared to the entire river catchment may indeed explain the significant lower fluxes at the river mouth.

  • 9. Stalnacke, P.
    et al.
    Pengerud, A.
    Vassiljev, A.
    Smedberg, Erik
    Stockholm University, Faculty of Science, Stockholm University Baltic Sea Centre.
    Mörth, Carl-Magnus
    Stockholm University, Faculty of Science, Stockholm University Baltic Sea Centre.
    Hägg, H. E.
    Stockholm University, Faculty of Science, Stockholm University Baltic Sea Centre.
    Humborg, Christop
    Stockholm University, Faculty of Science, Stockholm University Baltic Sea Centre.
    Andersen, H. E.
    Nitrogen surface water retention in the Baltic Sea drainage basin2015In: Hydrology and Earth System Sciences, ISSN 1027-5606, E-ISSN 1607-7938, Vol. 19, no 2, p. 981-996Article in journal (Refereed)
    Abstract [en]

    In this paper, we estimate the surface water retention of nitrogen (N) in all the 117 drainage basins to the Baltic Sea with the use of a statistical model (MESAW) for source apportionment of riverine loads of pollutants. Our results show that the MESAW model was able to estimate the N load at the river mouth of 88 Baltic Sea rivers, for which we had observed data, with a sufficient degree of precision and accuracy. The estimated retention parameters were also statistically significant. Our results show that around 380 000 t of N are annually retained in surface waters draining to the Baltic Sea. The total annual riverine load from the 117 basins to the Baltic Sea was estimated at 570 000 t of N, giving a total surface water N retention of around 40 %. In terms of absolute retention values, three major river basins account for 50% of the total retention in the 117 basins; i.e. around 104 000 t of N are retained in Neva, 55 000 t in Vistula and 32 000 t in Oder. The largest retention was found in river basins with a high percentage of lakes as indicated by a strong relationship between N retention (%) and share of lake area in the river drainage areas. For example in Gota alv, we estimated a total N retention of 72 %, whereof 67% of the retention occurred in the lakes of that drainage area (Lake Vanern primarily). The obtained results will hopefully enable the Helsinki Commission (HELCOM) to refine the nutrient load targets in the Baltic Sea Action Plan (BSAP), as well as to better identify cost-efficient measures to reduce nutrient loadings to the Baltic Sea.

  • 10.
    Wulff, Fredrik
    et al.
    Stockholm University, Faculty of Science, Department of Ecology, Environment and Plant Sciences. Stockholm University, Faculty of Science, Stockholm University Baltic Sea Centre, Baltic Nest Institute.
    Humborg, Christoph
    Stockholm University, Faculty of Science, Department of Applied Environmental Science (ITM). Stockholm University, Faculty of Science, Stockholm University Baltic Sea Centre, Baltic Nest Institute.
    Andersen, Hans Estrup
    Blicher-Mathiesen, Gitte
    Czajkowski, Mikolaj
    Elofsson, Katarina
    Fonnesbech-Wulff, Anders
    Hasler, Berit
    Hong, Bongghi
    Jansons, Viesturs
    Mörth, Carl-Magnus
    Stockholm University, Faculty of Science, Department of Geological Sciences.
    Smart, James C. R.
    Smedberg, Erik
    Stockholm University, Faculty of Science, Stockholm University Baltic Sea Centre, Baltic Nest Institute.
    Stålnacke, Per
    Swaney, Dennis P.
    Thodsen, Hans
    Was, Adam
    Zylicz, Tomasz
    Reduction of Baltic Sea Nutrient Inputs and Allocation of Abatement Costs Within the Baltic Sea Catchment2014In: Ambio, ISSN 0044-7447, E-ISSN 1654-7209, Vol. 43, no 1, p. 11-25Article in journal (Refereed)
    Abstract [en]

    The Baltic Sea Action Plan (BSAP) requires tools to simulate effects and costs of various nutrient abatement strategies. Hierarchically connected databases and models of the entire catchment have been created to allow decision makers to view scenarios via the decision support system NEST. Increased intensity in agriculture in transient countries would result in increased nutrient loads to the Baltic Sea, particularly from Poland, the Baltic States, and Russia. Nutrient retentions are high, which means that the nutrient reduction goals of 135 000 tons N and 15 000 tons P, as formulated in the BSAP from 2007, correspond to a reduction in nutrient loadings to watersheds by 675 000 tons N and 158 000 tons P. A cost-minimization model was used to allocate nutrient reductions to measures and countries where the costs for reducing loads are low. The minimum annual cost to meet BSAP basin targets is estimated to 4.7 billion a,not sign.

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