Spatial heterogeneity of nutrients in the Baltic Proper, Baltic Sea

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<ul><li><p>nges over time have been discernable, and also within the Sea there are</p><p>large spatial patterns. Present study analyses the spatial patterns of dissolved inorganic nitrogen and phosphorus as well as dissolved silicate(DSi) in the euphotic zone for the period 1990e2001. The focus is on the spatial heterogeneity with the aim to identify areas significantlydifferent from the overall mean.</p><p>Three regions are clearly discernible, the interior, the western and the eastern coastal zones. This is further complicated by the Gulfs ofFinland and Riga with distinct different behaviour compared to the other ones. While the coastal zones are re-supplied by their terrestrial sources,the exchange with the interior is limited by geophysical constraints. The western border shows permanently high DSi but low DIN and DIPconcentrations. The riverine loads of DIN, DIP and DSi are low but a large transport of DSi probably takes place from the Bothnian Sea tothe Kattegat along the western coast with only minor retention. The eastern region, on the other hand, is characterised by both high nutrientloads and high production. These spatial patterns agree well with a conceptual model where the spring bloom leads to an interior generallylow in DIN. This favours N-fixating cyanobacteria blooms at the expense of diatoms. This view is supported by decreasing DIP concentrationsbut unaffected DSi levels. The spatial patterns observed well reflect the riverine nutrient loads. This should be regarded in future remedy plansfor the eutrophic Baltic Sea. The terrestrial load can have very different impacts on the ecosystems depending on which coastal section isinvolved. 2007 Elsevier Ltd. All rights reserved.</p><p>Keywords: dissolved silica; inorganic nitrogen; inorganic phosphorus; probability mapping; riverine load; residual circulation; coastal zone</p><p>1. Introduction</p><p>Concern for the fate of the Baltic Sea has grown during thelast decades as numerous signs of eutrophication have beenfound (Bonsdorff et al., 2001). Today, the Baltic Sea repre-sents one of the most eutrophied coastal areas in the world(Cloern, 2001). Larsson et al. (1985) estimated an increasein phosphorous and nitrogen loads by a factor of eight andfour, respectively, since the 1950s. These increased anthropo-genic loads have gradually built up the nitrogen and phospho-rus concentrations in the water mass (Nehring and Matthaus,1991; Sanden and Rahm, 1993). Simultaneously, the dissolved</p><p>1991; Papush and Danielsson, 2006). This is assumed to bea result of increased diatom production and deposition, whichreduces the DSi stock in the water mass (Schelske et al., 1983;Conley et al., 1993). Increased terrestrial retention of DSi dueto river regulation and associated changes in weathering of soiland bedrock has also occurred (Humborg et al., 2000). Theriverine nitrogen and phosphorus loads and point sourceshave a distinct geographical pattern following population den-sity as well as agricultural and industrial activities (Sweitzeret al., 1996). The atmospheric deposition of nitrogen com-pounds also shows a large-scale NWeSE gradient with thehighest concentration in the south-eastern Baltic ProperSpatial heterogeneity of nutrients</p><p>Lars Rahm*, A</p><p>Department of Water and Environmental Studies, L</p><p>Received 3 October 2005;</p><p>Available online</p><p>Abstract</p><p>The Baltic Proper shows many signs of eutrophication. Nutrient cha</p><p>Estuarine, Coastal and Shelf Sciencsilicate (DSi) concentrations are decreasing (Sanden et al.,</p><p>* Corresponding author.</p><p>E-mail address: (L. Rahm).</p><p>0272-7714/$ - see front matter 2007 Elsevier Ltd. All rights reserved.doi:10.1016/j.ecss.2007.01.009in the Baltic Proper, Baltic Sea</p><p>sa Danielsson</p><p>inkoping University, SE-581 83 Linkoping, Sweden</p><p>accepted 18 January 2007</p><p>13 March 2007</p><p>e 73 (2007), 2001) and this, for the same reason as for the riverineloads.</p><p>Regional management goals to reduce the anthropogenicimpact often treat the Baltic Sea as a homogenous entity withlittle consideration to its spatial structure. These properties are</p></li><li><p>Lon ENorth Sea which lead to a limited water exchange. This resultsin a brackish Sea. The largest basin, the Baltic Proper, is an</p><p>11 15 19</p><p>54</p><p>56</p><p>58</p><p>60</p><p>Lat N</p><p>Bothnian Sea</p><p>Kattegat Baltic ProperFig. 1. Map over Baltic Proper with the mering product with major sources to the Gulf of Bothnia, thus itwill show a different distribution pattern.</p><p>23 27 31</p><p>Gulf of Riga</p><p>Gulf of Finlandessential for the understanding of the processes governing thenutrient dynamics as the key processes operate on differentspatial scales, exemplified by e.g. the patchy nature of phyto-plankton growth, localised up-welling of nutrient-rich waterfrom deeper layers, and large-scale current transports of nutri-ents between different areas.</p><p>Present study aims to characterise large-scale spatial pat-terns of nutrients in the surface layer of the Baltic Proper(BP). This is the largest basin of the Baltic Sea and is highlyaffected by eutrophication. The study is based on monitoringdata. The monitoring activity has increased substantially since1990 allowing the spatial patterns to be investigated in a betterway than before. The results of this study will be an identifi-cation of areas with significantly higher or lower concentra-tions than the overall mean. Combined with nutrient loaddata and large-scale transports, this information will shed lighton the underlying processes governing the large-scale silicatenitrogen and phosphorus patterns. This may facilitate the at-tempts to optimize future remedy actions.</p><p>2. Materials and methods</p><p>2.1. Study area</p><p>The Baltic Sea is located in the northern Europe (Fig. 1). Ithas shallow and narrow connections to the Kattegat and the</p><p>area with a well-mixed surface layer and a salinity stratifieddeeper layer. They are separated by a strong halocline. Thislimits both the rate of recycling of nutrients from the deeperlayers and the supply of oxygen to them (Pers and Rahm,2000). On the other hand, this limited supply of oxygen leadsto both hypoxia and denitrification and also facilitates the re-cycling of phosphate (Conley et al., 2002) and, to a certainamount, DSi, back to the water mass (Berner and Berner,1996; Nixon et al., 1996).</p><p>Trend tests have revealed increasing nitrate and phosphateconcentrations in the water body during 1970e90 (Sandenand Rahm, 1993) as well as significantly decreasing DSi levels(Sanden et al., 1991). During the last decade these trends are,however, decreasing (Papush and Danielsson, 2006). Spatially,there is a northesouth gradient in nitrogen and phosphorusloads with higher loads in the southern parts. These can belinked to the distribution of population, farming, industrialproduction, major rivers and point sources. Hence, the majorloads are found in the south-eastern parts (Sweitzer et al.,1996). The atmospheric deposition, corresponding to a thirdof the nitrogen load from rivers and point sources, shows a sim-ilar SEeNW pattern (Granat, 2001; Bartnicki et al., 2001).Sanden and Danielsson (1995) showed that the average nutri-ent concentrations in the major sub-basins of the BP are verysimilar irrespective of season. This is because the coastal zoneis omitted in their analysis. DSi, on the other hand, is a weath-</p><p>269L. Rahm, A. Danielsson / Estuarine, Coastal and Shelf Science 73 (2007) 268e278ajor sea areas. The 60 m isobath is shown.</p></li><li><p>represent the photic zone (0e20 m) of the entire Baltic Proper for the time</p><p>s2.2. Data material</p><p>Data were retrieved from the Baltic EnvironmentalDatabase at Stockholm University (Sokolov et al., 1997).These include quality checked nutrient data from the marinemonitoring programs of the riparian countries of the BalticSea, including hydrography and biochemistry. The riverine nu-trient loads are based on the period 1971e1990 and data fromthe database NEST ( This timeperiod is chosen to harmonize with the model calculationsby Wulff et al. (2001) as the latter is used in the discussionbelow. No dramatic changes have occurred during the lastdecade. In the present study, the immediately bioavailableDIN (dissolved inorganic nitrogen), DIP (dissolved inorganicphosphorus) and DSi are used to reflect the nutrient patterns.Salinity is included as a conservative tracer to indicate theorigin of the water masses. Data are averaged over the upper0e20 m, i.e. the euphotic zone, for the respective samplingevent.</p><p>To handle seasonality in data, the years were dividedinto three periods NovembereMarch, AprileJune and JulyeOctober. By this, the seasonal cycle is resolved with high winterconcentrations and decreasing levels during spring bloom,whereafter a successive restoring of the stocks occurs duringautumn until the storage is refilled. Since the spring bloomsets off earlier in the southern parts than further north, the sea-sonal division may be slightly misleading, but the time lag is atmost of the order of one month. The number of observationsused for each nutrient is 8400, 7000 and 9200 for thewinter, spring and autumn, respectively, over the time period1990e2001.</p><p>Satellite pictures were used to estimate the extension of thecyanobacteria blooms. These pictures have been compiled ona daily basis byM. Hansson (SMHI). A satellite carrying a spec-troradiometer (MODIS) with a resolution of 0.5 0.5 km hasbeen used to identify cyanobacteria blooms each day duringthe summer season. The number of days with blooms is calcu-lated for the time period 1997e2004. These data are primarilyused in the Swedish algal monitoring program (data from year2001 is lacking due to antenna problems).</p><p>2.3. Probability mapping</p><p>In the nutrient data set, some stations are visited more fre-quently than others. This will produce an unproportionallyhigh weight for certain stations in common statistical analysis.Therefore, the method of probability mapping (Choynowski,1959) was chosen as it takes into account the different numberof observations per grid cell (Cressie and Read, 1985, 1989). Arecent application of the method is found in Danielsson et al.(2004) dealing with nutrient distributions in Kattegat (BalticSea). The essence of this method is that it uses probabilitiesbased on a probability (Poisson) distribution and not on the ob-servations themselves. The mapping gives a statistical measureof spatial heterogeneity by testing the null hypothesis that all</p><p>270 L. Rahm, A. Danielsson / Estuarine, Coacells have statistically the same median value taking thedifferent number of observations into account. Median ischosen to avoid skewed representation in certain regions,e.g. close to river mouths. A rejection of the hypothesis meansthat the frequency of concentrations above or below the over-all median is either significantly higher or lower than ex-pected. A lattice with grid cells of size 1 0.5(longitude latitude) is used to aggregate stations into sub-areas, where all data within a grid cell are analysed as an en-semble. The chosen size of grid cell is a trade off betweenspatial resolution and observation frequency. Only cells withmore than nine observations over the study period are usedin order to minimise spurious results. Some cells will showa lack of data, especially during spring and autumn, due to theinfrequent sampling.</p><p>3. Results</p><p>The salinity concentration in the surface layer is in therange 6e8 PSU, with the highest salinities during winter andlowest during spring. Also this seasonality is reflected in thenutrient dynamics with typical seasonal patterns (Fig. 2).Note that this variation is more pronounced for DIN andDIP than for DSi. The DIN concentrations are in the range0.1e8 mM, the inorganic phosphorus concentrations are foundin the interval 0.0e1.0 mM while the DSi concentrations are inthe range 1e20 mM.</p><p>Dec.</p><p>Nov.Oc</p><p>t.Se</p><p>p.Au</p><p>g.Jul.</p><p>Jun.</p><p>May</p><p>Apr.</p><p>Mar.</p><p>Feb.</p><p>Jan.</p><p>Mea</p><p>n co</p><p>ncen</p><p>tratio</p><p>n</p><p>20</p><p>15</p><p>10</p><p>5</p><p>0</p><p>DSiDINDIP</p><p>Fig. 2. Nutrient seasonal changes. Bar charts presenting monthly average con-</p><p>centrations of DIN and DSi [mmol l1] as well as DIP [mmol l1]. The data</p><p>tal and Shelf Science 73 (2007) 268e278period 1990e2001.</p></li><li><p>13 15 17 19 21 23 25 27 2954</p><p>Salinity (Autumn)</p><p>Fig. 3. Seasonal probability maps for (a) salinity, (b) DSi, (c) DIN and (d) DIP. Grwith significantly lower concentrations than the overall median (dark p&lt; 0.01;(i.e.&lt; 10).13 15 17 19 21 23 25 27 2954</p><p>DSi (Autumn)</p><p>een denotes a cell with significantly higher concentrations and blue denotes a cell3.1. Salinity</p><p>The salinity maps present the main hydrographical struc-tures of the basin (Fig. 3a). In the interior, there are a largenumber of cells with salinities significantly higher than the</p><p>overall median. Lower concentrations are found along thecoasts with large freshwater discharge from rivers, in the Gulfof Riga (GoR), and to some extent in the Gulf of Finland(GoF). Overlaying this pattern is a marked northesouth gradi-ent, with higher concentrations in the south.</p><p>13 15 17 19 21 23 25 27 2954</p><p>56</p><p>58</p><p>60</p><p>Salinity (winter)</p><p>13 15 17 19 21 23 25 27 2954</p><p>56</p><p>58</p><p>60</p><p>Salinity (Spring)</p><p>56</p><p>58</p><p>60</p><p>54</p><p>56</p><p>58</p><p>60</p><p>DSi (winter)</p><p>13 15 17 19 21 23 25 27 29</p><p>13 15 17 19 21 23 25 27 29</p><p>54</p><p>56</p><p>58</p><p>60</p><p>DSi (Spring)</p><p>56</p><p>58</p><p>60</p><p>271L. Rahm, A. Danielsson / Estuarine, Coastal and Shelf Science 73 (2007) 268e278light p&lt; 0.05). Grey represents cells without sufficient number of observations</p></li><li><p>3.2. Dissolved silica</p><p>The DSi concentrations are significantly higher in thecoastal zone along the western border than elsewhere</p><p>The eastern part, including GoR and GoF, has significantlylow concentrations. During spring, the concentration in the in-terior is significantly higher than the overall median. Later on,in the autumn, the conditions become more similar to the win-</p><p>13 15 17 19 21 23 25 27 2954</p><p>56</p><p>58</p><p>DIN (winter)</p><p>13 15 17 19 21 23 25 27 2954</p><p>56</p><p>58</p><p>60</p><p>DIN (Spring)</p><p>13 15 17 19 21 23 25 27 29</p><p>54</p><p>56</p><p>58</p><p>60</p><p>DIN (Autumn)</p><p>13 15 17 19 21 23 25 27 2954</p><p>56</p><p>58</p><p>DIP (winter)</p><p>13 15 17 19 21 23 25 27 2954</p><p>56</p><p>58</p><p>60</p><p>DIP (Spring)</p><p>13 15 17 19 21 23 25 27 2954</p><p>56</p><p>58</p><p>60</p><p>DIP (Autumn)</p><p>Fig. 3 (continued).60</p><p>272 L. Rahm, A. Danielsson / Estuarine, Coas(Fig. 3b). This high-concentration region reaches up into thesouthern part of the Bothnian Sea irrespective of season.60</p><p>tal and Shelf Science 73 (2007) 268e278ter conditions with an interior close to the median but highconcentrations in the southern parts.</p></li><li><p>3.3. Dissolved inorganic nitrogen</p><p>The DIN concentrations are generally lower in the interiorthan in the coastal areas (Fig. 3c). Significantly high concen-trations are found, for all seasons, in the eastern and southerncoastal areas and are further enhanced in the GoR. Signifi-cantly low concentrations are located to the interior andthe GoF. During spring, cells with significantly high concen-trations are reduced to only a few along the eastern coastclose to major river outlets. At the same time, the numberof cells with significantly low concentrations increases, espe-cially in the interior. This structure remains during autumnalthough the interior generally approaches the overal...</p></li></ul>


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