Assessing the Effects of WFD Nutrient Reductions Within an OSPAR Frame Using Trans-boundary Nutrient Modeling

Lenhart, Hermann; Große, Fabian

doi:10.3389/fmars.2018.00447

Cited by 7 publications

(5 citation statements)

References 59 publications

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“…and Table ). The marine offshore sites did not exhibit trends in nutrient concentration as they are mainly under the influence of Atlantic waters (Dulière et al ; Lenhart and Große ; Ménesguen et al ). BE offshore is an exception as it shows a decreasing trend in winter DIP.…”

Section: Discussionmentioning

confidence: 99%

Changes in chlorophyll concentration and phenology in the North Sea in relation to de‐eutrophication and sea surface warming

Desmit

Nohe

Borges

et al. 2019

Limnology & Oceanography

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At least two major drivers of phytoplankton production have changed in recent decades in the North Sea: sea surface temperature (SST) has increased by~1.6 C between 1988 and 2014, and the nitrogen and phosphorus loads from surrounding rivers have decreased from the mid-1980s onward, following reduction policies. Long time series spanning four decades of nutrients, chlorophyll (Chl), and pH measurements in the Southern and Central North Sea were analyzed to assess the impact of both the warming and the deeutrophication trends on Chl. The de-eutrophication process, detectable in the reduction of nutrient river loads to the sea, caused a decrease of nutrient concentrations in coastal waters under riverine influence. A decline in annual mean Chl was observed at 11 out of 18 sampling sites (coastal and offshore) in the period 1988-2016. Also, a shift in Chl phenology was observed around 2000, with spring bloom formation occurring earlier in the year. A long time series of pH in the Southern North Sea showed an increase until the mid-1980s followed by a rapid decrease, suggesting changes in phytoplankton production that would support the observed changes in Chl. Linear correlations, however, did not reveal significant relationships between Chl variability and winter nutrients or SST at the sampling sites. We propose that the observed changes in Chl (annual or seasonal) around 2000 are a response of phytoplankton dynamics to multiple stressors, directly or indirectly influenced by deeutrophication and climate warming.

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Section: Discussionmentioning

confidence: 99%

Changes in chlorophyll concentration and phenology in the North Sea in relation to de‐eutrophication and sea surface warming

Desmit

Nohe

Borges

et al. 2019

Limnology & Oceanography

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“…Direct field experiments with chemical tracers are unfeasible in many ways, but stable isotope techniques can be used. However, MMEMs are the most efficient way to trace river nutrients that are advected and modified by biogeochemical processes (Menesguen et al 2006, Radtke & Maar 2016, Lenhart & Große 2018 and can be used in support of management decisions (e.g. Lenhart et al 2010).…”

Section: Are Models Better Than Observations?mentioning

confidence: 99%

Disclosing the truth: Are models better than observations?

Skogen

Акимова

et al. 2021

Mar. Ecol. Prog. Ser.

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The aphorism, ‘All models are wrong, but some models are useful’, originally referred to statistical models, but is now used for scientific models in general. When presenting results from a marine simulation model, this statement effectively stops discussions about the quality of the model, as there is always another observation to mismatch, and thereby another confirmation why the model cannot be trusted. It is common that observations are less challenged and are often viewed as a ‘gold standard’ for judging models, whereas proper interpretations and the true value of models are often overlooked. Models are not perfect, and there are many examples where models are used improperly to provide misleading answers with great confidence, but to what extent does an observation represent the truth? The precision of the observational gear may be high, but what about representativeness? The interpretation of observations is simply another model, but this time not coded in a computer language but rather formed by the individual observer. We submit that it would be more productive to initiate a process where the norm is that models and observations are joined to strengthen both. In the end, neither method is the goal, but both are useful tools for disclosing the truth. Biased views on either observational or modeling approaches would limit us from achieving this goal.

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“…The isolines of DIN and DIP in general, with an exception of the E-HYPE scenario from GPM, are related to the small band of Elbe dominated water, which can be seen in the analysis from Lenhart and Große (2018;Figures 4A,B). The variability analysis for the Ems plume (Figures 6D-F) provides a similar picture, only with a reduced variability for CHL.…”

Section: Discussionmentioning

confidence: 85%

“…For this purpose, the socalled "trans-boundary nutrient transports" (TBNT) approach provides a method for the tracing of an element, like nitrogen, from individual sources throughout the entire biogeochemical cycle, including the physical transport processes (Ménesguen and Hoch, 1997). By the use of this method, the relative contribution of river loadings can be quantified for different regions (e.g., Lenhart and Große, 2018).…”

Section: Suggestions For Future Modeling Studiesmentioning

confidence: 99%

Evaluating Uncertainties in Reconstructing the Pre-eutrophic State of the North Sea

et al. 2021

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The North Sea is affected by eutrophication problems despite the decreasing riverine nutrient fluxes since the late 1980s. Formally, assessment of the eutrophication state of European marine environments is based on their historical state. Model estimates are increasingly used to support monitoring data that often do not encompass such pre-eutrophic conditions. However, various sources of uncertainties emerge when producing these estimates. In this study, we systematically quantify various sources of uncertainties in terms of variability, and assess their importance for the North Sea. For the reconstruction of the historical state, we use two coupled physical-biogeochemical model systems: ECOHAM on a 20-km grid for the European shelf and GPM on a high-resolution (1.5–4.5 km) grid for the Southern North Sea. To gain insights into the impacts due to the uncertainty in riverine loadings, we consider the historical nutrient inputs from two alternative watershed-models (MONERIS and E-HYPE). Overall, the modeled historic state based on E-HYPE shows higher nutrient concentrations compared to the state based on MONERIS, especially in the coastal regions. Assessing the degree of methodological uncertainties by an inter-comparison of different sources and against natural variabilities provides insight into the reliability of the model-based reconstruction of the historical state. We find that in regions influenced by freshwater from major rivers uncertainties owed to riverine loading scenarios exceed the natural sources of variability. For the offshore regions, natural sources of variability dominate over those caused by model- and scenario-related uncertainties. These findings are expected to assist decision makers and researchers in gaining insight into the degree of confidence in evaluating the model results, and prioritizing the need for refinement of models and scenarios for the production of reliable projections.

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Assessing the Effects of WFD Nutrient Reductions Within an OSPAR Frame Using Trans-boundary Nutrient Modeling

Cited by 7 publications

References 59 publications

Changes in chlorophyll concentration and phenology in the North Sea in relation to de‐eutrophication and sea surface warming

Changes in chlorophyll concentration and phenology in the North Sea in relation to de‐eutrophication and sea surface warming

Disclosing the truth: Are models better than observations?

Evaluating Uncertainties in Reconstructing the Pre-eutrophic State of the North Sea

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