Simulation of annual plankton productivity cycle in the Black Sea by a one‐dimensional physical‐biological model

Abstract

The annual cycle of the plankton dynamics in the central Black Sea is studied by a one-dimensional vertically resolved physical-biological upper ocean model, coupled with the Mellor-Yamada level 2.5 turbulence closure scheme. The biological model involves interactions between the inorganic nitrogen (nitrate, ammonium), phytoplankton and herbivorous zooplankton biomasses, and detritus. Given a knowledge of physical forcing, the model simulates main observed seasonal and vertical characteristic features, in particular, formation of the cold intermediate water mass and yearly evolution of the upper layer stratification, the annual cycle of production with the fall and the spring blooms, and the subsurface phytoplankton maximum layer in summer, as well as realistic patterns of particulate organic carbon and nitrogen. The computed seasonal cycles of the chlorophyll and primary production distributions over the euphotic layer compare reasonably well with the data. Initiation of the spring bloom is shown to be critically dependent on the water column stability. It commences as soon as the convective mixing process weakens and before the seasonal stratification of surface waters begins to develop. It is followed by a weaker phytoplankton production at the time of establishment of the seasonal thermocline in April. While summer nutrient concentrations in the mixed layer are low enough to limit production, the layer between the thermocline and the base of the euphotic zone provides sufficient light and nutrient to support subsurface phytoplankton development. The autumn bloom takes place some time between October and December depending on environmental conditions. In the case of weaker grazing pressure to control the growth rate, the autumn bloom shifts to December-January and emerges as the winter bloom or, in some cases, is connected with the spring bloom to form one unified continuous bloom structure during the January-March period. These bloom structures are similar to the year-to-year variabilities present in the data. isms due to the hypoxia/anoxia have currently become common phenomena [Zaitsev, 1992]. The effect of pollution is, however, relatively less severe in the central Black Sea because of its isolation from coastal and shelf waters by the Rim Current frontal zone [Sapozhnikov, 1991;Oguz et al., 1994].In this study we examine the basic physical and biological processes controlling the seasonal cycle of the plankton productivity in the Black Sea. Using a series of numerical experiments, our aim is specifically to explore the conditions and the biological processes which may account for the observed bloom structures (see section 3). The model is restricted to two dimensions (time and depth) and is applied for the conditions appropriate to the central Black Sea. As compared with the northwestern shelf and the Rim Current frontal zone around the basin, horizontal variabilities and contributions of antropogenic inputs from rivers are less important, and this simplified approach might be justifiable for the interio...

Modeling the response of top‐down control exerted by gelatinous carnivores on the Black Sea pelagic food web

“…The March to early April period corresponded to the formation of major phytoplankton and subsequent mesozooplankton blooms. As noted previously by Oguz et al [1996Oguz et al [ , 1998aOguz et al [ , 1999 Figure 3b indicates that the peaks of phytoplankton, Noctiluca, A urelia, and omnivorous zooplankton biomass march sequentially during the year as a resuit of their prey-predator interactions. After the early spring diatom bloom, the omnivorous mesozooplankton biomass starts increasing as they assimilate diatoms.…”

“…There have been some attempts to model pelagic food web structure in the Black Sea using externally specified yearly cycles of the mixed layer depth and temperature from the available climatological data [Lebedeva and The structure and functioning of the plankton community, coupled with biogeochemical processes taking place within the deeper parts of the upper layer water column of the interior Black Sea are studied by means of vertically resolved coupled physical-biological models [Oguz et al, 1996[Oguz et al, , 1998a[Oguz et al, , 1999[Oguz et al, , 2000 …”

Mixing in the Black Sea detected from the temporal and spatial variability of oxygen and sulfide – Argo float observations and numerical modelling

“…The presentation of the Black Sea hydrochemical properties in density coordinates (Vinogradov and Nalbandov, 1990;Konovalov et al, 2005) reduces the data scatter seen in geopotential coordinates, and renders analyses less dependent on the specific location (Stanev et al, 2004). Analyses in density coordinate have also been extensively used to evaluate the variability of physical and biogeochemical fields in 1-D models (Oguz et al, 1996(Oguz et al, , 2000(Oguz et al, , 2001(Oguz et al, , 2002aYakushev and Neretin, 1997;Yakushev et al, 2007). However, under the assumption that simple tracer-density relationships are valid basin-wide (e.g.…”

“…In the following decades two important developments happened: (1) the 1-D modelling gained larger maturity (Oguz et al, 1996(Oguz et al, , 2000(Oguz et al, , 2001(Oguz et al, , 2002aYakushev, 1992;Yakushev and Neretin, 1997;Yakushev et al, 2007;Lancelot et al, 2002, Gregoire et al, 2008Gregoire and Soetaert, 2010), and (2) the quality of 3-D modelling improved substantially by using more complex and realistic models and much better resolution (Gregoire et al, 1997(Gregoire et al, , 1998Staneva et al, 1998Oguz et al, 2002b;Gregoire andLacroix, 2003, Capet et al, 2013).…”

Modeling the nitrogen fluxes in the Black Sea using a 3D coupledhydrodynamical-biogeochemical model: transport versus biogeochemicalprocesses, exchanges across the shelf break and comparison of the shelf anddeep sea ecodynamics

“…Cokacar and Ozsoy, 1998;Ozsoy et al, 1998) or to one-dimensional (vertical) coupled physical biogeochemical models usually describing the nitrogen cycling (e.g. Lebedeva and Shushkina, 1994;Oguz et al, 1996Oguz et al, , 1999Staneva et al, 1998;Lancelot et al, 2002). Models applied in the suboxic zone and describing the nitrogen and sulfur cycles coupled with oxygen dynamics (e.g.…”