Spatial and temporal variability in the pelagic ecosystem of the East Sea (Sea of Japan): A review

The East Sea (Sea of Japan) is a unique marginal sea because it exhibits features of oceanic dynamics of much larger ocean basins. This semi-enclosed basin may be considered as a model or microcosm for understanding of how biological processes and distributions in pelagic ecosystem are interacting with physical processes in highly dynamic ocean regions. This overview summarizes the recent progresses concerning spatial and temporal variability of pelagic ecosystem components form an interdisciplinary point of view. Spatial characteristics of physical environments and biogeography in the region are distinguished mainly by the subpolar front. It was also found that long-term changes in biomass and community structure as well as those in the physical and biological environments are associated with climate variability in the region. We conclude by identifying main needs for the information and researches, particularly regular and long-term sampling, and permanent monitoring if possible.     

Future aspects in marine ecosystem modelling

Existing ecosystem models are briefly presented and summarised. The problem of coupling physical and biological models as well as aspects of prediction and predictability are discussed. The general perception that marine ecosystems are inherently unpredictable due to non-linearity becomes questionable if the response of climate variability in marine ecosystems is analysed. Many authors have shown correlations between climate variability and the variability of abundance or biomass of marine organisms such as phytoplankton, zooplankton, benthos or fish recruitment in different parts of the world ocean. In the northern hemisphere, certain species show a linear response to climate variability mainly during winter and spring. However, the underlying mechanisms are not well understood. Often, a phase lag can be observed between climate variability and the reaction of organisms. The identification of a plausible mediator between climate and biology is difficult, since all possible physicochemical mechanisms having a direct or indirect influence on the variability of abundance or biomass of marine organisms have to be considered as mediator.The understanding of the reason of the phase lag, which possibly implies a “biological memory”, and the identification of all possible mediators are necessary to predict the response of marine organisms to climate variability. The identification of mediators will result in an improvement of coupled models, a deeper understanding of physical–biological interaction and the improvement of predictive capability of marine ecosystem models.     

Modelling the ice-ocean-plankton interactions in the Souther Ocean

Our goal is the study of interactions between sea ice and ocean and of their influence on planktonic communities. We use a physical model which includes explicitly melting dynamics and mixed-layer physics. A one-dimensional model of the water column with a k-1 turbulent closure is applied. The sea-ice model is the one proposed by Semtner (1976); we add a parameterization of leads. We enlighten the importance, in this kind of model, of the sharing of the energy between lateral and basal meltings. The biological model comprises two state variables: phytoplankton and zooplankton biomasses. Melting induces a persistent shallow mixed layer and thus appropriate conditions for primary production. If ice melting is present, high biomasses are possible even with high losses. The absence of ice nearly forbids a massive bloom to form. Some sensitivity studies have shown that grazing pressure is a key factor governing the evolution of biomasses. The biomasses are also sensitive to little modifications of the photosynthetic production. The initial amount of phytoplankton or the presence of ice algae seems to be of lesser importance.     

Fluxes of biogenic carbon in the Southern Ocean: roles of large microphagous zooplankton

The Southern Ocean is an extreme environment, where waters are permanently cold, a seasonal ice cover extends over large areas, and the solar energy available for photosynthesis is severely restricted, either by vertical mixing to considerable depths or, especially south of the Antarctic Circle, by prolonged seasonal periods of low or no irradiance. Such conditions would normally lead to low productivity and a water column dominated by recycling processes involving microbial components of pelagic communities but this does not seem to be the case in the Southern Ocean, where there is efficient export to large apex predators and deep waters. This paper investigates the role of large microphagous zooplankton (salps, krill, and some large copepods) in the partitioning of biogenic carbon among the pools of short- and long-lived organic carbon and sequestered biogenic carbon. Large microphagous zooplankton are able to ingest microbial-sized particles and thus repackage small, non-sinking particles into both metazoan biomass and large, rapidly sinking faeces. Given the wide spatio-temporal extent of microbial trophic pathways in the Southern Ocean, large zooplankton that are omnivorous or able to ingest small food particles have a competitive advantage over herbivorous zooplankton. Krill efficiently transfer carbon to a wide array of apex predators and their faecal pellets are exported to depth during occasional brief sedimentation episodes in spring time. Salps may be a significant link towards some fish (directly) and other apex predators (indirectly) and, at some locations (especially in offshore waters) and time, they may account for most of the downward flux of biogenic carbon. Large copepods are a trophic link towards fish and at least one whale species, and their grazing activity generally impedes the export of organic particles to depth. As a result, biogenic carbon is channelled mainly towards apex predators and episodically into the deep ocean. Without these original interactions, Antarctic waters might well be dominated by microbial components and recycling processes instead of active export from the generally small primary producers towards large apex predators.     

用生态动力学模型分析海带养殖对浮游生态系统的影响

以我国近海典型海带养殖区桑沟湾为例,建立了"浮游植物-海带-浮游动物-营养盐-有机碎屑"生态动力学模型,较好地模拟了不同养殖密度下浮游生态系统结构的变化,通过灵敏度分析,研究状态变量对模型初值和参数变化的响应,提出了参数优化的思路.     

Monitoring marine plankton ecosystems: Identification of the most relevant indicators of the state of an ecosystem

The number of variables involved in the monitoring of an ecosystem can be high and often one of the first stages in the analysis is to reduce the number of variables. We describe a method developed for geological purposes, using the information theory, that enables selection of the most relevant variables. This technique also allows the examination of the asymmetrical relationships between variables. Applied to a set of physical and biological variables (plankton assemblages in four areas of the North Sea), the method shows that biological variables are more informative than physical variables although the controlling factors are mainly physical (sea surface temperature in winter and spring). Among biological variables, diversity measures and warm-water species assemblages are informative for the state of the North Sea pelagic ecosystems while among physical variables sea surface temperature in late winter and early spring are highly informative. Although often used in bioclimatology, the utilisation of the North Atlantic Oscillation (NAO) index does not seem to provide a lot of information. The method reveals that only the extreme states of this index has an influence on North Sea pelagic ecosystems. The substantial and persistent changes that were detected in the dynamic regime of the North Sea ecosystems and called regime shift are detected by the method and corresponds to the timing of other shifts described in the literature for some European Systems such as the Baltic and the Mediterranean Sea when both physical and biological variables are considered.     

Ecology of bottom ice algae: II. Dynamics, distributions and productivity

Spring blooms of bottom ice algae are a common feature of landfast congelation ice in polar regions. Because ice algae are usually associated with a substrate, their population dynamics can be followed with considerable confidence. Although ice algal dynamics are closely related to irradiance, their dynamics and distributions are influenced by other abiotic and biotic factors. Ice algal abundance varies horizontally over all scales examined. Factors such as grazing and nutrient availability may contribute to local and geographic differences. Loss terms for most sea ice assemblages are largely unquantified. Ice algal biomass is most concentrated near the ice-water interface in spring.Environmental factors affecting ice algal abundance and productivity are considered here, emphasizing recent results from several well-studied sites. Biomass accumulation, growth rates and productivity have been documented for spring blooms of bottom interstitial and sub-ice assemblages. On an areal basis biomass accumulation in bottom ice assemblages can be comparable with planktonic systems. At low ambient temperatures and irradiances average specific growth rates (≤ 0.25 d⁻¹) and production rates (≤ 1.0 mg C mg Chl⁻¹ h⁻¹) for ice algae are low. Current methods of measuring productivity are compared. Results are consistently low but variable with little systematic difference among them. At present, apparent differences in productivity between bottom ice assemblages in the Arctic and Antarctic, or among different antarctic assemblages, are so confounded by methodological and other sources of variability that no firm differences can be detected.     

Study of the seasonal cycle of the biogeochemical processes in the Ligurian Sea using a 1D interdisciplinary model

A one-dimensional coupled physical–biogeochemical model has been built to study the pelagic food web of the Ligurian Sea (NW Mediterranean Sea). The physical model is the turbulent closure model (version 1D) developed at the GeoHydrodynamics and Environmental Laboratory (GHER) of the University of Liège. The ecosystem model contains 19 state variables describing the carbon and nitrogen cycles of the pelagic food web. Phytoplankton and zooplankton are both divided in three size-based compartments and the model includes an explicit representation of the microbial loop including bacteria, dissolved organic matter, nano-, and microzooplankton. The internal carbon/nitrogen ratio is assumed variable for phytoplankton and detritus, and constant for zooplankton and bacteria. Silicate is considered as a potential limiting nutrient of phytoplankton's growth. The aggregation model described by Kriest and Evans in (Proc. Ind. Acad. Sci., Earth Planet. Sci. 109 (4) (2000) 453) is used to evaluate the sinking rate of particulate detritus. The model is forced at the air–sea interface by meteorological data coming from the “Côte d'Azur” Meteorological Buoy. The dynamics of atmospheric fluxes in the Mediterranean Sea (DYFAMED) time-series data obtained during the year 2000 are used to calibrate and validate the biological model. The comparison of model results within in situ DYFAMED data shows that although some processes are not represented by the model, such as horizontal and vertical advections, model results are overall in agreement with observations and differences observed can be explained with environmental conditions.     

海洋生态系统及海岸工程生态影响预测模型研究进展

对海洋生态系统的研究已形成了以实验观测为基础、建立生态模型的方法。文章对已有的海洋生态模型研究成果进行了归纳总结,认为初级生产力模型是纯生态模型的主要发展方向,综合考虑物理生化作用的生态系统动力学模型将是未来海洋生态研究的必然趋势。同时,由于我国大规模海岸工程建设对近岸海域生态系统造成了较大影响,而相关的生态影响预测模型研究较少,为有效预测评价海岸工程建设对近岸海域生态系统的影响,进一步深入研究海岸工程建设对近岸海洋生态影响预测模型将显得尤为重要。     

Primary productivity and export fluxes on the Canadian shelf of the Beaufort Sea: A modelling study

We present a coupled sea ice–ocean-biological (including ice algae) model in the Arctic Ocean. The 1D model was developed and implemented on the Canadian Beaufort Sea shelf to examine the importance of different physical processes in controlling the timing and magnitude of primary production and biogenic particle export over an annual cycle (1987). Our results show that the snow and sea ice cover melt and/or break-up controls the timing of the phytoplankton bloom but primary producers (ice algae and phytoplankton) on the outer shelf are essentially nutrient limited. The total annual primary production (22.7 to 27.7 g-C m^? 2) is thus controlled by nutrient “pre-conditioning” in the previous fall and winter and by the depth of wind mixing that is controlled in part by the supply of fresh water at the end of spring (ice melt or runoff). The spring bloom represents about 40% of the total annual primary production and occurs in a period of the year when sampling is often lacking. Time interpolation of observed values to obtain total annual primary production, as done in many studies, was shown to lead to an underestimation of the actual production. Our simulated ratios of export to primary production vary between 0.42 and 0.44.     

Modelling Pseudocalanus elongatus stage-structured population dynamics embedded in a water column ecosystem model for the northern North Sea

This paper outlines an approach to couple a structured zooplankton population model with state variables for eggs, nauplii, two copepodites stages and adults adapted to Pseudocalanus elongatus into the complex marine ecosystem model ECOHAM2 with 13 state variables resolving the carbon and nitrogen cycle. Different temperature and food scenarios derived from laboratory culture studies were examined to improve the process parameterisation for copepod stage dependent development processes. To study annual cycles under realistic weather and hydrographic conditions, the coupled ecosystem–zooplankton model is applied to a water column in the northern North Sea. The main ecosystem state variables were validated against observed monthly mean values. Then vertical profiles of selected state variables were compared to the physical forcing to study differences between zooplankton as one biomass state variable or partitioned into five population state variables. Simulated generation times are more affected by temperature than food conditions except during the spring phytoplankton bloom. Up to six generations within the annual cycle can be discerned in the simulation.     

A spatially explicit ecosystem model of seston depletion in dense mussel culture

A fully-coupled biological–physical–chemical model of a coastal ecosystem was constructed to examine the impact of suspended mussel culture on phytoplankton biomass in Tracadie Bay, Prince Edward Island, Canada. Due to the extent of mussel culture there, we hypothesised that shellfish filtration would control the concentration and distribution of phytoplankton and other suspended particles in the bay. Circulation was delineated with a tidally-driven 2D numerical model and used to drive an ecosystem model with a focus on pelagic components including phytoplankton production, nutrients, detritus, and mussels. The benthos were treated as a sink. Nutrients and seston were forced by tidal exchange and river input, with phytoplankton additionally forced by light. Boundary conditions of seston and nutrients were derived from field studies with an emphasis on the contrast between spring (high river nutrients, low temperature) and summer (low river inputs and high temperatures). Model output was used to map phytoplankton carbon over the bay for each season and in the presence of mussels and river nutrient input. Results indicate severe depletion effects of mussel culture on overall phytoplankton biomass, but no spatial pattern that can be attributed to grazing alone. Primary production generated by nutrient-rich river water created a mid-bay spike in phytoplankton that dominated the spatial pattern of chlorophyll-based carbon. Model results were validated with surveys from a towed sensor array (Acrobat) that confirmed the river influence and indicated bay-wide depletion of 29% between high and low water. Our model results indicate that the farm-scale depletion emphasised in previous studies cannot simply be extrapolated to seston limitation at the ecosystem level.     

Impact of freshwater on a subarctic coastal ecosystem under seasonal sea ice (southeastern Hudson Bay, Canada). I. Interannual variability and predicted global warming influence on river plume dynamics and sea ice

Analysis of sea ice cover, runoff and air temperature observations in Hudson Bay shows marked interannual variability. This variability is thought to play a major role in determining overall productivity of the coastal ecosystem by changes to river plume extent, under-ice light conditions and nutrient levels during spring. Extensive field work off the Great Whale River in southeastern Hudson Bay has shown the importance of freshwater discharge, sea ice cover and meteorological forcing on the production of under-ice microalgae and the success of first feeding in fish larvae.Recent global climate model (GCM) results for a doubling of present atmospheric carbon dioxide indicate increases of both air temperature and precipitation in the Hudson Bay area. Predictions based on GCM results are used to estimate future changes to the sea ice and runoff regime. Sea ice breakup in the offshore is predicted to occur about one month earlier than presently. Estimates of the spring freshet in the Great Whale River indicate it will also advance by approximately one month. Onset of the spring freshet will occur about one month before Hudson Bay ice breakup, similar to present. A predicted reduction of about 35% in maximum sea ice thickness will lead to an increase in the ice-ocean interface irradiance and a decrease in melt water input to the Hudson Bay surface waters. These results are used in a discussion of potential effects of global climate change on northern coastal marine environments.     

Variability of snow and ice thermal, physical and optical properties pertinent to sea ice algae biomass during spring

Changes in the thermal, physical and optical properties of the snow–sea ice system and feedbacks between various temporal and spatial scales affect accumulation of microalgae at the sea ice bottom and are the focus of this research. During the spring transition period, May 4 to June 9, 2002, we closely monitored atmospheric conditions and properties of the snow–sea ice system, including thermal, physical and optical properties of the snow cover (e.g., temperature, grain size, light attenuation), ice thickness and salinity, and biomass of bottom ice algae. Results show that snowdrift size averaged 31.2 by 10.6 m with a depth range of 2 to 45 cm. Snowpacks also varied in age, distinguished by coincident peaks of snow salinity and grain size and a lower PAR extinction coefficient. Spatial variability of the snowpack was superimposed by temporal variability associated with seasonal snow–ice melt and wind redistribution of snow. Maximum biomass of ice algae was observed under intermediate snow covers. Under thin snow covers, algae biomass declined steadily coincident with seasonal warming and desalination of the ice cover. Under thick snow covers, algae biomass was negatively correlated with snow depth. These results suggest that thin snow covers were associated with a thermal effect causing sloughing of algae, whereas under deep snow, algae were still light limited and thermally insulated from the warming atmosphere. Our results highlight the importance of snow cover history on the sea ice system operating below. Furthermore, in the context of current climate change scenarios, shifts in snow depth would result in decreases of ice algae biomass.     

Trophic flows,ecosystem structure and fishing impacts in the South Catalan Sea,Northwestern Mediterranean

An exploited ecosystem from the continental shelf and upper slope of the Northwestern Mediterranean Sea was described by means of an Ecopath mass-balance model with the aim of characterising its functioning and structure and describing the ecosystem impacts of fishing. This application included some complexities added to the general modelling methodology due to the high biodiversity of the Mediterranean Sea and the multispecific nature of the fishery, and to the difficulties of working with fishing data which are usually irregularly or imprecisely collected. The model comprised 40 functional groups including primary producers, the main species of benthic, demersal and pelagic invertebrates, fishes and non-fish vertebrates and three detritus groups. In addition, trawling, purse seine, longline and troll bait fishing fleets were included.Results showed that the functional groups were organized into four trophic levels with the highest levels corresponding to anglerfish, dolphins, large pelagic fishes and adult hake. The system was dominated by the pelagic fraction, where sardine and anchovy prevailed in terms of fish biomasses and catches. Detritus and detritivorous groups also played key roles in the ecosystem and important coupled pelagic-demersal interactions were described. Considering Odum's theory of ecosystem development, the ecosystem was placed on an intermediate-low developmental stage due, at least partially, to the impact of fishing activity. This highlighted the high intensity of fishing in the ecosystem, in accordance with the general assessment of western Mediterranean marine resources, and fishing fleets were ranked as top predators of the system. The low trophic level of the catch was in line with the long history of exploitation in the area. However, the steady decline of pelagic landings between 1994 and 2003, coupled with a decrease of the pelagic biomass within the system, underlined the low resistance of the system in front of perturbations. This decline was reproduced under Ecosim dynamic simulations combining different scenarios of moderate increase of fishing effort and an environmental forcing affecting the availability of preys to small and medium-sized pelagic fishes under wasp-waist flow control.     

Real time assimilation of HF radar currents into a coastal ocean model

A real time assimilation and forecasting system for coastal currents is presented. The purpose of the system is to deliver current analyses and forecasts on based on assimilation of high-frequency radar surface current measurements. The local Vessel Traffic Service monitoring the ship traffic to two oil terminals on the coast of Norway received the analyses and forecasts in real time.A new assimilation method based on optimal interpolation is presented where spatial covariances derived from an ocean model are used instead of simplified mathematical formulations. An array of high frequency radar antennae provides the current measurements. A suite of nested ocean models comprises the model system. The observing system is found to yield good analyses and short range forecasts that are significantly improved compared to a model twin without assimilation. The system is fast, analysis and 6-h forecasts are ready at the Vessel Traffic Service 45 min after acquisition of radar measurements.     

Primary productivity of the Palmer Long Term Ecological Research Area and the Southern Ocean

A major objective of the Palmer Long Term Ecological Research (Palmer LTER) project is to obtain a comprehensive understanding of the various components of the Antarctic marine ecosystem. Phytoplankton production plays a key role in this so-called high nutrient, low chlorophyll environment, and factors that regulate production include those that control cell growth (light, temperature, and nutrients) and those that control cell accumulation rate and hence population growth (water column stability, grazing, and sinking). Sea ice mediates several of these factors and frequently conditions the water column for a spring bloom which is characterized by a pulse of production restricted in both time and space. This study models the spatial and temporal variability of primary production within the Palmer LTER area west of the Antarctic Peninsula and discusses this production in the context of historical data for the Southern Ocean. Primary production for the Southern Ocean and the Palmer LTER area have been computed using both light-pigment production models [Smith, R.C., Bidigare, R.R., Prézelin, B.B., Baker, K.S., Brooks, J.M., 1987. Optical characterization of primary productivity across a coastal front. Mar. Biol. (96), 575–591; Bidigare, R.R., Smith, R.C., Baker, K.S., Marra, J., 1987. Oceanic primary production estimates from measurements of spectral irradiance and pigment concentrations. Global Biogeochem. Cycles (1), 171–186; Morel, A., Berthon, J.F., 1989. Surface pigments, algal biomass profiles and potential production of the euphotic layer—relationships reinvestigated in view of remote-sensing applications. Limnol. Oceanogr. (34), 1545–1562] and an ice edge production model [Nelson, D.M., Smith, W.O., 1986. Phytoplankton bloom dynamics of the western Ross Sea ice edge: II. Mesoscale cycling of nitrogen and silicon. Deep-Sea Res. (33), 1389–1412; Wilson, D.L., Smith, W.O., Nelson, D.M., 1986. Phytoplankton bloom dynamics of the Western Ross Sea ice edge: I. primary productivity and species-specific production. Deep-Sea Res., 33, 1375–1387; Smith, W.O., Nelson, D.M., 1986. Importance of ice edge phytoplankton production in the Southern Ocean. BioScience (36), 251–257]. Chlorophyll concentrations, total photosynthetically available radiation (PAR) and sea ice concentrations were derived from satellite data. These same parameters, in addition to hydrodynamic conditions, have also been determined from shipboard and Palmer Station observations during the LTER program. Model results are compared, sensitivity studies evaluated, and productivity of the Palmer LTER region is discussed in terms of its space time distribution, seasonal and interannual variability, and overall contribution to the marine ecology of the Southern Ocean.     

The role of copepods in the Baikal ecosystem

This describes a study of the pelagic zone of Lake Baikal with particular reference to copepods. In addition the cycling of matter and energy in lacustrine basins is described.     

A generalized model of pelagic biogeochemistry for the global ocean ecosystem. Part II: Numerical simulations

This paper presents a global ocean implementation of a multi-component model of marine pelagic biogeochemistry coupled on-line with an ocean general circulation model forced with climatological surface fields (PELAgic biogeochemistry for Global Ocean Simulations, PELAGOS). The final objective is the inclusion of this model as a component in an Earth System model for climate studies. The pelagic model is based on a functional stoichiometric representation of marine biogeochemical cycles and allows simulating the dynamics of C, N, P, Si, O and Fe taking into account the variation of their elemental ratios in the functional groups. The model also includes a parameterization of variable chlorophyll/carbon ratio in phytoplankton, carrying chl as a prognostic variable. The first part of the paper analyzes the contribution of non-local advective–diffusive terms and local vertical processes to the simulated chl distributions. The comparison of the three experiments shows that the mean chl distribution at higher latitudes is largely determined by mixing processes, while vertical advection controls the distribution in the equatorial upwelling regions. Horizontal advective and diffusive processes are necessary mechanisms for the shape of chl distribution in the sub-tropical Pacific. In the second part, the results have been compared with existing datasets of satellite-derived chlorophyll, surface nutrients, estimates of phytoplankton community composition and primary production data. The agreement is reasonable both in terms of the spatial distribution of annual means and of the seasonal variability in different dynamical oceanographic regions. Results indicate that some of the model biases in chl and surface nutrients distributions can be related to deficiencies in the simulation of physical processes such as advection and mixing. Other discrepancies are attributed to inadequate parameterizations of phytoplankton functional groups. The model has skill in reproducing the overall distribution of large and small phytoplankton but tends to underestimate diatoms in the northern higher latitudes and overestimate nanophytoplankton with respect to picoautotrophs in oligotrophic regions. The performance of the model is discussed in the context of its use in climate studies and an approach for improving the parameterization of functional groups in deterministic models is outlined.