Biogeochemical Modelling

The systematic literature search on the fertility rate was performed on articles from the Web of Science compiled by the Institute of Scientific Information (ISI) to provide major publication characteristics. All articles related to Fertility from year 1980 to 2011 were analyzed with the bibliometric approach using non-parametrics techniques. Total Citation, Citation per year and Cited References were significantly different between the 80’s, 90’s and 2000’s, with more than a 100% increase in the number of publication. The association between number of authors and citation per year were significantly weak. Number of publication in a journal posed a poor negative association with the citation per year. Similarity between Authors Keyword and KeyWords Plus® do not promote the increase in citation per year. The author’s affiliation and country of publication would be an interesting exploration for future fertility research. The bibiliometric analyses on Fertility is rather new and vital...

Zooplankton are the intermediate trophic level between phytoplankton and fish, and are an important component of carbon and nutrient cycles, accounting for a large proportion of the energy transfer to pelagic fishes and the deep ocean. Given zooplankton's importance, models need to adequately represent zooplankton dynamics. A major obstacle, though, is the lack of model assessment. Here we try and stimulate the assessment of zooplankton in models by filling three gaps. The first is that many zooplankton observationalists are unfamiliar with the biogeochemical, ecosystem, size-based and individual-based models that have zooplankton functional groups, so we describe their primary uses and how each typically represents zooplankton. The second gap is that many modelers are unaware of the zooplankton data that are available, and are unaccustomed to the different zooplankton sampling systems, so we describe the main sampling platforms and discuss their strengths and weaknesses for model assessment. Filling these gaps in our understanding of models and observations provides the necessary context to address the last gap—a blueprint for model assessment of zooplankton. We detail two ways that zooplankton biomass/abundance observations can be used to assess models: data wrangling that transforms observations to be more similar to model output; and observation models that transform model outputs to be more like observations. We hope that this review will encourage greater assessment of zooplankton in models and ultimately improve the representation of their dynamics.

The Cenomanian-Turonian oceanic anoxic event (OAE2) is characterized by large perturbations in the oxygen and sulfur cycles of the ocean, potentially resulting from changes in oxygen supply (via oxygen solubility and ocean circulation) and in marine productivity. We assess the relative impact of these mechanisms, comparing model experiments with a new compilation of observations for seafloor dysoxia/anoxia and photic-zone euxinia. The model employed is an intermediate-complexity Earth system model which accounts for the main ocean dynamics and biogeochemistry of the Cretaceous climate. The impact of higher temperature and marine productivity is evaluated in the model as a result of higher atmospheric carbon dioxide and oceanic nutrient concentrations. The model shows that temperature is not alone able to reproduce the observed patterns of oceanic redox changes associated with OAE2. Observations are reproduced in the model mainly via enhanced marine productivity due to higher nutrient content (responsible for 85% of the change). Higher phosphate content could have been sustained by increased chemical weathering and phosphorus regeneration from anoxic sediments, which in turn induced an enhanced nitrogen nutrient content of the ocean via nitrogen fixation. The model also shows that the presence of seafloor anoxia, as suggested by black-shale deposition in the proto-North Atlantic Ocean before the event, might be the result of the silled shape and lack of deep-water formation of this basin at the Late Cretaceous. Overall our model-data comparison shows that OAE2 anoxia was quasi-global spreading from 5% of the ocean volume before the event to at least 50% during OAE2.

Cobalt is an important micronutrient for ocean microbes as it is present in vitamin B 12 and is a co-factor in various metalloenzymes that catalyze cellular processes. Moreover, when seawater availability of cobalt is compared to biological demands, cobalt emerges as being depleted in seawater, pointing to a potentially important limiting role. To properly account for the potential biological role for cobalt, there is therefore a need to understand the processes driving the biogeochemical cycling of cobalt and, in particular, the balance between external inputs and internal cycling. To do so, we developed the first cobalt model within a state-of-the-art three-dimensional global ocean biogeochemical model. Overall, our model does a good job in reproducing measurements with a correlation coefficient of >0.7 in the surface and >0.5 at depth. We find that continental margins are the dominant source of cobalt, with a crucial role played by supply under low bottom-water oxygen conditions. The basin-scale distribution of cobalt supplied from margins is facilitated by the activity of manganese-oxidizing bacteria being suppressed under low oxygen and low temperatures, which extends the residence time of cobalt. Overall, we find a residence time of 7 and 250 years in the upper 250 m and global ocean, respectively. Importantly, we find that the dominant internal resupply process switches from regeneration and recycling of particulate cobalt to dissolution of scavenged cobalt between the upper ocean and the ocean interior. Our model highlights key regions of the ocean where biological activity may be most sensitive to cobalt availability. Plain Language Summary Biological activity in the sea requires cobalt, primarily due to its role in vitamin B12 but also because it is required in other cellular enzymes. While our observations of cobalt distributions in the ocean is growing, we do not have a quantitative understanding of the role of different external sources of cobalt or how it is internally processed by different biological and chemical processes in the ocean. To answer these questions, we built the first ever global ocean cobalt model that coupled the cycling of cobalt to the major biogeochemical processes occurring in the ocean. Using this model, we identified that sediments are the major cobalt source and that the combination of oxygen levels and scavenging removal by bacteria allow externally supplied cobalt to pervade the ocean as a whole. We find that in certain regions of the upper ocean, cobalt levels may be low enough to affect biological activity but that to quantify this requires further work on how we represent cellular biochemistry.

Coastal lagoons are complex ecosystems exhibiting a high degree of non-linearity in the distribution and exchange of nutrients dissolved in the water column due to their spatio-temporal characteristics. This factor has a direct influence on the concentrations of chlorophyll-a, an indicator of the primary productivity in the water bodies as lakes and lagoons. Moreover the seasonal variability in the characteristics of large-scale basins further contributes to the uncertainties in the data on the physico-chemical and biological characteristics of the lagoons. Considering the above, modelling the distributions of the nutrients with respect to the chlorophyll-concentrations, hence requires an effective approach which will appropriately account for the non-linearity of the ecosystem as well as the uncertainties in the available data. In the present investigation, fuzzy logic was used to develop a new model of the primary production for Pulicat lagoon, Southeast coast of India. Multiple regression analysis revealed that the concentrations of chlorophyll-a in the lagoon was highly influenced by the dissolved concentrations of nitrate, nitrites and phosphorous to different extents over different seasons and years. A high degree of agreement was obtained between the actual field values and those predicted by the new fuzzy model (d = 0.881 to 0.788) for the years 2005 and 2006, illustrating the efficiency of the model in predicting the values of chlorophyll-a in the lagoon.

Coastal lagoons are complex ecosystems exhibiting a high degree of non-linearity in the distribution and exchange of nutrients dissolved in the water column due to their spatio-temporal characteristics. This factor has a direct influence on the concentrations of chlorophyll-a, an indicator of the primary productivity in the water bodies as lakes and lagoons. Moreover the seasonal variability in the characteristics of large-scale basins further contributes to the uncertainties in the data on the physico-chemical and biological characteristics of the lagoons. Considering the above, modelling the distributions of the nutrients with respect to the chlorophyll-concentrations, hence requires an effective approach which will appropriately account for the non-linearity of the ecosystem as well as the uncertainties in the available data. In the present investigation, fuzzy logic was used to develop a new model of the primary production for Pulicat lagoon, Southeast coast of India. Multiple regression analysis revealed that the concentrations of chlorophyll-a in the lagoon was highly influenced by the dissolved concentrations of nitrate, nitrites and phosphorous to different extents over different seasons and years. A high degree of agreement was obtained between the actual field values and those predicted by the new fuzzy model (d = 0.881 to 0.788) for the years 2005 and 2006, illustrating the efficiency of the model in predicting the values of chlorophyll-a in the lagoon.

Pristine peatlands have generally low nitrous oxide (N2O) emissions but drainage and management practices enhance the microbial processes and associated N2O emissions. It is assumed that leaving peat soils from intensive management, such as agriculture, will decrease their N2O emissions. In this paper we report how the annual N2O emission rates will change when agricultural peat soil is either left

ABSTRACT 1-Training Course Parts
2-Theoretical Courses
2-1-Practical Part
2-2-Determination of Irgarol in coastal waters and sea Anemone tissues by GC-MS
2-2-1-Determination of Fatty acids in fish oil using GC-MS
2-2-2-Determination of Total mercury concentrations (HgT) in marine core sediment by DMA-80
2-2-3Oceanographic Survey (BANSIC 2014)
2-2-4-Workshops and Conferences
3-AWI-SAHFOS Summer School (Germany)
4-Advanced Oxidation and Bioremediation Treatment of Mercury in Marine Sediment
5-Outputs and Conclusion
6-Future Cooperation
7-References
8-Acknowledgement