Role of Bacteria in the Carbon and Nitrogen Flow between Water-Column and Sediment in a Shallow Marine Bay (Bay of Piran, Northern Adriatic Sea)

Abstract. The interdependences between phytoplankton standing crop, bacterial biomass and the dissolved organic matter (DOM) pool in the water column were investigated and related to sediment parameters in a shallow marine bay (Bay of Piran, Northern Adriatic Sea) over an annual cycle. Bacterioplankton density varied between 1–10 × 10⁵ cells ml^-1, with lowest density observed in March corresponding to the low Chi a concentrations during this period. Generation times as determined by dialysis incubations ranged between 4h (June) and 82 h (March). Mean bacterial secondary production rates during summer were about 40 mg C m^-1 d^-1 and 5mg C m^-3.d^-1 during winter. With a short time lag, DOM concentrations followed the fluctuation in Chi a.
Sediment oxygen demand measurements revealed a mean mineralization rate of about 260 mg C m^-2 d^-1 during summer and 100–200 mg C m^-2 d^-1 in winter. Sediment bacterial density varied between 10⁸ - 10⁹ cells g (sediment dry wt)^-1 in the top 5 cm sediment layer or, in terms of biomass, 4.3 g C m^-l during summer and 0.6 g C m^-2 during winter. Highest concentrations of DOM in pore waters were measured in September, coinciding with high rates of sediment oxygen demand.     

Design sea state assessment using genetic algorithm approach

Two major statistical issues can be distinguished in the procedure of wave extreme prediction. The first issue is that predicted extreme values must be based on data collected in a relatively short time. The second issue is extrapolation of the observed data into its extreme region, typically lying well beyond from even the most extreme available observation. The process of extrapolation plays a fundamental role in this area of analysis and therefore it is essential to fit empirically a convenient probability distribution that describes the available data as closely as possible. Determination of extreme values probability distribution parameters by genetic algorithm is applied to improve the methodology of extreme sea state prediction.Illustrative applications of the method are given for a North Atlantic sea environment. The results are presented as crest height maximum values occurring with a given probability or in a design storm that has a specified return period.