Nitrate source identification in the Baltic Sea using its isotopic ratios in combination with a Bayesian isotope mixing model

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Abstract

Nitrate (NO3-) is the major nutrient responsible for coastal eutrophication worldwide and its production is related to intensive food production and fossil-fuel combustion. In the Baltic Sea NO3- inputs have increased 4-fold over recent decades and now remain constantly high. NO3- source identification is therefore an important consideration in environmental management strategies. In this study focusing on the Baltic Sea, we used a method to estimate the proportional contributions of NO3- from atmospheric deposition, N2 fixation, and runoff from pristine soils as well as from agricultural land. Our approach combines data on the dual isotopes of NO3- (δ15N-NO3- and δ18O-NO3-) in winter surface waters with a Bayesian isotope mixing model (Stable Isotope Analysis in R, SIAR). Based on data gathered from 47 sampling locations over the entire Baltic Sea, the majority of the NO3- in the southern Baltic was shown to derive from runoff from agricultural land (33-100%), whereas in the northern Baltic, i.e. the Gulf of Bothnia, NO3- originates from nitrification in pristine soils (34-100%). Atmospheric deposition accounts for only a small percentage of NO3- levels in the Baltic Sea, except for contributions from northern rivers, where the levels of atmospheric NO3- are higher. An additional important source in the central Baltic Sea is N2fixation by diazotrophs, which contributes 49-65% of the overall NO3- pool at this site. The results obtained with this method are in good agreement with source estimates based upon δ15N values in sediments and a three-dimensional ecosystem model, ERGOM. We suggest that this approach can be easily modified to determine NO3- sources in other marginal seas or larger near-coastal areas where NO3- is abundant in winter surface waters when fractionation processes are minor.

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Korth, F., Deutsch, B., Frey, C., Moros, C., & Voss, M. (2014). Nitrate source identification in the Baltic Sea using its isotopic ratios in combination with a Bayesian isotope mixing model. Biogeosciences, 11(17), 4913–4924. https://doi.org/10.5194/bg-11-4913-2014

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