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Chum salmon (Oncorhynchus keta) are predominantly located in the Bering Sea during summer and fall. However, several studies have recently reported a different tendency as follows. Observed densities of chum salmon were higher in the vicinity of the Bering Strait and the Chukchi Sea than the eastern Bering Sea in September 2007, and Japanese chum salmon migrated to northern areas in the Bering Sea during summer 2009. The sea surface temperature (SST) in the Arctic marginal seas has increased since the mid-1960s, and especially since 2000. We speculated that the SST increase directly promoted salmon northing from the Bering Sea to the Western Arctic. In this study, we estimated the potential habitat for chum salmon in the Western Arctic using a bioenergetics model coupled with a three-dimensional lower trophic ecosystem model (3-D NEMURO). “Potential habitat” was defined as “an area where chum salmon could grow (i.e., the growth rate was positive)”. In the bioenergetics model, the growth rate of an individual chum salmon was calculated as a function of water temperature, salinity, and prey density, which were obtained from the 3-D NEMURO model results. To evaluate the habitat responses under a global warming scenario, we used the modeled monthly change of water temperature between 2005 (averaged from 2001 to 2010) and 2095 (averaged from 2091 to 2100) under the IPCC SRES-A1B scenario. Our calculations, following the global warming scenario, suggested that the potential habitat for chum salmon would expand to the north due to the increase in water temperature and prey density. In contrast, south of 71°N during summer, the potential habitat would shrink regionally because the water temperature exceeded the optimal condition.

Akkeshi Lake is a subarctic shallow brackish lagoon located in Hokkaido, Japan. The Manila clam, Ruditapes philippinarum, is cultured in sandy sediments at the shallow, intertidal flat near the mouth of the lake. To quantitatively evaluate the effects of environmental factors such as water temperature and food availability on the growth of the Manila clam and to estimate the responses of Manila clam growth and food availability to global warming in Akkeshi Lake, we developed a numerical model by coupling a three-dimensional ecosystem model with a bioenergetics model for the growth of the Manila clam. We ran the model under two different conditions: the present condition and the global warming condition. For the global warming condition, water temperature was increased by 2 °C at the open boundary for the entire computational period. The growth of the Manila clam was limited by water temperature and food availability. The Manila clam grew up to 1.33 g dry weight ind.−1 at the lake mouth (station A) for 5 years, whereas it grew up to 1.00 g dry weight ind.−1 at the lake center (station B). The difference in the biomass of the Manila clam between two stations was due to the difference in food availability. Under the global warming condition, the water temperature limitation for the Manila clam was relaxed with a water temperature increase. The Manila clam grew up to 1.55 g dry weight ind.−1 at station A and 1.10 g dry weight ind.−1 at station B. While the growth of the Manila clam was improved in the lake under the global warming condition, its food sources, especially phytoplankton, decreased because of ingestion increases of grazers.

A lower trophic ecosystem model, which was originally developed for describing the variability in plankton distribution in the western North Pacific, is applied to the global ocean. A realistic time series of dynamically self-consistent circulation fields obtained by a 4-dimensional variational ocean data assimilation experiment is used for the environmental fields in the ecosystem model. An optimization of the bio-ecological parameter values in 40 provinces by a Green’s function approach enables the ecosystem model to represent the observed variabilities of nutrients and surface chlorophyll concentration with a relatively small number (11) of compartments. In addition, artificial trends of the ecosystem variables due to model errors are generally suppressed by the optimization. The obtained parameter values and ecosystem fields are generally consistent with observations in terms of assimilated and non-assimilated metrics. The integrated lower-trophic ecosystem and physical fields in the global ocean offer important information on the mechanisms (such as El Ninos) responsible for the seasonal–interannual variability in the lower trophic ecosystem. Our results demonstrate that, with adequate parameter sets capable of modifying indirectly the model and significance of each pathway to reflect the characteristics of local species, a simple ecosystem model can be applied in quantitative analyses to enhance our understanding of the influence of climate variations on the ocean ecosystem.

The Oyashio region in the western North Pacific supports high biological productivity and has been well monitored. We applied the NEMURO (North Pacific Ecosystem Model for Understanding Regional Oceanography) model to simulate the nutrients, phytoplankton, and zooplankton dynamics. Determination of parameters values is very important, yet ad hoc calibration methods are often used. We used the automatic calibration software PEST (model-independent Parameter ESTimation), which has been used previously with NEMURO but in a system without ontogenetic vertical migration of the large zooplankton functional group. Determining the performance of PEST with vertical migration, and obtaining a set of realistic parameter values for the Oyashio, will likely be useful in future applications of NEMURO. Five identical twin simulation experiments were performed with the one-box version of NEMURO. The experiments differed in whether monthly snapshot or averaged state variables were used, in whether state variables were model functional groups or were aggregated (total phytoplankton, small plus large zooplankton), and in whether vertical migration of large zooplankton was included or not. We then applied NEMURO to monthly climatological field data covering 1 year for the Oyashio, and compared model fits and parameter values between PEST-determined estimates and values used in previous applications to the Oyashio region that relied on ad hoc calibration. We substituted the PEST and ad hoc calibrated parameter values into a 3-D version of NEMURO for the western North Pacific, and compared the two sets of spatial maps of chlorophyll-a with satellite-derived data. The identical twin experiments demonstrated that PEST could recover the known model parameter values when vertical migration was included, and that over-fitting can occur as a result of slight differences in the values of the state variables. PEST recovered known parameter values when using monthly snapshots of aggregated state variables, but estimated a different set of parameters with monthly averaged values. Both sets of parameters resulted in good fits of the model to the simulated data. Disaggregating the variables provided to PEST into functional groups did not solve the over-fitting problem, and including vertical migration seemed to amplify the problem. When we used the climatological field data, simulated values with PEST-estimated parameters were closer to these field data than with the previously determined ad hoc set of parameter values. When these same PEST and ad hoc sets of parameter values were substituted into 3-D-NEMURO (without vertical migration), the PEST-estimated parameter values generated spatial maps that were similar to the satellite data for the Kuroshio Extension during January and March and for the subarctic ocean from May to November. With non-linear problems, such as vertical migration, PEST should be used with caution because parameter estimates can be sensitive to how the data are prepared and to the values used for the searching parameters of PEST. We recommend the usage of PEST, or other

From the 1970s to 1990s, a reduction in the body size of Japanese chum salmon (Oncorhynchus keta) was observed. To investigate this body size reduction in the North Pacific, we developed a bioenergetics model for chum salmon coupled with the results from a lower trophic ecosystem model embedded into a three-dimensional global model. In the bioenergetics model, respiration and consumption terms are assumed to be functions of water temperature and prey zooplankton density, which are the determining factors of the reduction of body size. The model reproduced the body size of the 1972 and 1991 year classes of chum salmon. The reproduced body size of the 1972 year class was larger than that of 1991 year class, and this result agrees with observations from the Bering Sea. Our model also reproduced the body size trend from l970 to 2000. The prey density, especially in the eastern North Pacific, had a greater influence on the change of body size than did the SST. This suggests that the size reduction of Japanese chum salmon in the 1990s was partly affected by changes in prey zooplankton density. In the context of the global warming scenario, we discuss changes in the migration route of chum salmon and predict that the population of Japanese chum salmon experience significant declines over this century.

Bioenergetics model is applied to Japanese common squid, Todarodes pacificus. The temporal change of wet weight of common squid, which migrates in the Sea of Japan, is simulated. The time dependent horizontal distribution of prey is calculated a priori by 3-D coupled physical–biological model. The biological model NEMURO (North Pacific Ecosystem Model for Understanding Regional Oceanography) is used to simulate the lower-trophic ecosystem including three kinds of zooplankton biomass two of which is used as prey of common squid. A bioenergetics model reproduced appropriate growth curve of common squid, migrating in the North Pacific and the Sea of Japan. The results show that the wet weight of common squid in the northern Sea of Japan is heavier than that migrating in the central Sea of Japan, because prey density of the northern Sea of Japan is higher than that of the central Sea of Japan. We also investigate the wet weight anomaly for a global warming scenario. In this case, wet weight of common squid decreases because water temperature exceeds the optimum temperature for common squid. This result indicates that migration route and spawning area of common squid might change with global warming.

A population dynamics model (PDM) was developed for Neocalanus cristatus, which is the dominant large copepod in the northwestern subarctic Pacific, to simulate the increase of production with developmental stage and the transfer of production by vertical migration. The PDM was coupled with a lower trophic level ecosystem model, North Pacific Ecosystem Model Used for Regional Oceanography (NEMURO, developed by the North Pacific Marine Science Organization (PICES)), by replacing the large zooplankton component (ZooL) in NEMURO with the PDM. Ecological effects in the coupled model were compared to those in the original NEMURO. In the simulations, the annual cycle of copepodite stages begins during the spring bloom, followed by a decrease in biomass during summer, then migration of Neocalanus to the deep water where they diapause during autumn and winter, and finally the simulation ends with egg production in winter. The PDM successfully described the annual life cycle of Neocalanus. During early copepodite stages (during the spring bloom), they graze small phytoplankton (PhyS) without consuming large phytoplankton (PhyL). Therefore, PhyL biomass increases greatly in spring. In summer, during the last copepodite stage, they begin to prey mostly on PhyL, causing a decrease in the PhyL biomass, while the PhyS biomass increases. Production of PhyL remains higher than that of PhyS because predatory pressure by Neocalanus gradually weakens as the last copepodite stage, near the surface, approaches its end in summer. These simulations suggest that in addition to Neocalanus we should include PDMs for the other large copepods, which consume PhyL during the summer, in order to reproduce the lower trophic ecosystems of the northwestern subarctic Pacific.

We investigated the parameter sensitivity of the NEMURO ecosystem model calibrated to field at two typical Stations (A7 and P) in the subarctic North Pacific. The NEMURO model follows various forms of nitrogen and silicon, and the daily biomasses of two phytoplankton and three zooplankton groups for multiple years. Previously calibrated versions to data at two stations provided the basis for comparing parameter sensitivities under different environmental and biological conditions. Four sensitivity analysis experiments were performed involving 72 parameters: 3 experiments used Monte Carlo methods and 1 experiment used a 1-parameter-at-a-time approach. Normalized sensitivities and correlation were used as sensitivity measures for comparison among the four experiments. Monte Carlo and one-parameter-at-a-time methods that used relatively small variations in parameter values (less than or equal to ±10%) yielded very similar rankings of the top five parameters. Parameter rankings from the Monte Carlo analysis that used relatively large variation in parameters (−50% to +100%) differed slightly from the rankings obtained with the small variations. Additional examination of the ±10% results showed that parameters deemed important differed among prognostic variables and differed between Stations A7 and P. For example, annual small phytoplankton biomass was most sensitive to the maximum grazing rate of small zooplankton at both stations, while large phytoplankton biomass was most sensitive to its own maximum photosynthetic rate parameter. While at Station A7 large phytoplankton was sensitive to zooplankton parameters, at Station P it was more sensitive to phytoplankton parameters. A few of certain phytoplankton parameters were consistently important in all sensitivity experiments. Despite sometimes complex relationships between prognostic variables and parameters, our analyses showed that the NEMURO model was generally well-behaved and was robust to parameter variation and to the method used for the sensitivity analysis. Extensions of our analysis could involve computing the sensitivity measure over time through the year, and the use other types of prognostic variables than biomass such as the timing of the phytoplankton bloom. Sensitivity analyses, such as those performed here, are useful tools for applying the NEMURO to other locations and for helping to interpret and diagnose existing NEMURO applications.

NEMURO, the North Pacific Ecosystem Model for Understanding Regional Oceanography, simulates the temporal evolution and dynamics of the North Pacific's nutrient–phytoplankton–zooplankton food web. The approach of developing a single model formulation allowed quantitative comparisons across various locations and time periods. Building on a common foundation enabled the linkages between lower trophic levels to the higher trophic (fish) components to proceed systematically. NEMURO was extended to NEMURO.FISH by using the lower trophic level output of NEMURO as input to a bioenergetic-based model of fish growth and population dynamics. This paper summarizes the contributions of individual papers that comprise this issue of Ecological Modelling and that all used the NEMURO family of models. Contributions represent a rich set of case-studies and in-depth modeling studies focused on the North Pacific that addressed: oceanic biogeochemistry, regional and seasonal variability of phytoplankton and zooplankton, reconstruction of 40–50 years of plankton dynamics, effects of climate on herring and saury growth and population dynamics, the feasibility of automatic calibration methods, the sensitivity of the model to parameter values, and projections of future states of the ecosystem under global warming. Next steps in the evolution of NEMURO are suggested and include increased resolution of the physical model underlying NEMURO, the addition of new biological state variables at the lower trophic levels to better represent the diversity of oceanic species and their potential for different responses under changing environmental conditions, and the addition of more higher trophic level species to allow for inter-specific (competition and predation) interactions. The NEMURO effort involved a diverse group of researchers working jointly on a common problem for several years. Consequently, the resulting contributions, even at the level of the individual papers, provide a broader perspective and integration of the results than would have occurred by working in isolation. The benefits of a large-scale collaborative effort to develop a common model formulation are clearly illustrated by the papers in this issue.

The PICES CCCC (North Pacific Marine Science Organization, Climate Change and Carrying Capacity program) MODEL Task Team achieved a consensus on the structure of a prototype lower trophic level ecosystem model for the North Pacific Ocean, and named it the North Pacific Ecosystem Model for Understanding Regional Oceanography, “NEMURO”. Through an extensive dialog between modelers, plankton biologists and oceanographers, an extensive review was conducted to define NEMURO's process equations and their parameter values for distinct geographic regions. We present in this paper the formulation, structure and governing equations of NEMURO as well as examples to illustrate its behavior. NEMURO has eleven state variables: nitrate, ammonium, small and large phytoplankton biomass, small, large and predatory zooplankton biomass, particulate and dissolved organic nitrogen, particulate silica, and silicic acid concentration. Several applications reported in this issue of Ecological Modelling have successfully used NEMURO, and an extension that includes fish as an additional state variable. Applications include studies of the biogeochemistry of the North Pacific, and variations of its ecosystem's lower trophic levels and two target fish species at regional and basin-scale levels, and on time scales from seasonal to interdecadal.

Regime shifts, consisting of decadal-scale oscillations in atmosphere–ocean systems, have recently been the focus of many marine ecosystem studies. These ‘regime shifts’ effect the sea surface temperature and mixed layer depth (MLD), changing the environment for marine ecosystems. We simulated changes in the marine ecosystem caused by interdecadal climate variability, using data from 1948 to 2002 to drive an ecosystem model, NEMURO, embedded in a global three-dimensional physical–biological coupled model, ‘3D-NEMURO’. The results were consistent with observations. Comparing before and after the late 1970s regime shift, primary production and biomass of phytoplankton increased in the north central Pacific but decreased in the sub-tropical northwestern and eastern Pacific. This corresponds to the Pacific decadal oscillation (PDO) index that indicates interdecadal climate variability in the sub-tropical and tropical Pacific. In the north central Pacific, biomass correlated positively with PDO while that in the north eastern and western Pacific correlated negatively with PDO.

To elucidate the interannual response of Pacific saury growth to climate variability, a simple 3-box model of NEMURO.FISH was forced by observed sea surface temperature (SST) from 1950 to 2002. In the model, fish wet weight is calculated according to a fish bioenergetics equation. The observed condition factor of Pacific saury showed large decadal variability with significant year-to-year variability. In the model, wet weight of Pacific saury also showed decadal and year-to-year variability, however the amplitude of decadal variability was much smaller than observed. The cause of the model failure is suggested to be the absence of a multi-species fish formulation in the model. The Japanese sardine population, which has a large biomass that exhibits great decadal fluctuations, is proposed as potentially affecting zooplankton density in the saury migration region. We also investigated differences of interannual growth variability between spawning seasons. Since Pacific saury spawns from autumn to the following spring, we consider three seasonal (autumn, winter and spring) cohorts in the model. The amplitude of growth variability is largest for the spring-spawned cohort and smallest in the winter-spawned cohort. This difference is caused by the difference of life history of each spawned cohort. The spring-spawned cohort spawns only once in their life-cycle, however other cohorts spawn twice. During the (autumn) fishery season, age 1 spring-spawned cohort has not yet spawned, while the other cohorts have spawned once. As a result, the spring-spawned cohorts retain the memory of the environmental influence during the early life stages while the other cohorts, through their spawning, have erased that memory. Hence, the spring-spawned cohort shows a larger fluctuation in wet weight than other cohorts.

A NEMURO-based 16-compartment marine ecosystem model is applied to Stations A7 (41.5 ◦ N, 145.5 ◦ E) and KNOT (44 ◦ N, 155 ◦ E) in the subarctic western North Pacific and Station PAPA (50 ◦ N, 145 ◦ W) in the subarctic eastern North Pacific. Model results show significant west-east differences in seasonal characteristics of physical environmental conditions and biogeochemistry, such as larger seasonal amplitudes in sea surface temperature, mixed layer depth, surface nutrients, chlorophyll and partial pressure of CO2 at the sea surface (pCO2)sea, and higher primary productivity, at Stations A7 and KNOT than at Station PAPA. The modeled annual-mean e-ratios are higher at Stations A7 (0.32) and KNOT (0.33) than at Station PAPA (0.27) due to higher plankton biomass and mortality in the western North Pacific. Modeled annual-mean f-ratios are systematically higher than e-ratios under the influence of nitrification. The f-ratios are lower at Stations A7 (0.57) and KNOT (0.58) than at Station PAPA (0.64) because of higher ammonium concentrations in the western North Pacific. The e-ratio increases and f-ratio decreases with primary productivity, and the relationships can be described by exponential functions at any of the sites. The sea-to-air CO2 flux increases at Stations A7 and KNOT when calculated using daily wind data, instead of climatological wind data, which have been used in most of the previous studies. The increase is attributed to the strong winds in late winter in the daily wind data, suggesting that the sea-to-air CO2 flux was probably underestimated in previous studies and that frequent monitoring of winds and (pCO2)sea is necessary to reduce uncertainties in estimating air–sea CO2 flux. Phytoplankton growth is severely limited by light at any of the stations throughout the year. Diatom growth is regulated by silicate rather than nitrate and ammonium at each site, particularly in late summer and early autumn at Stations A7 and KNOT. We conclude that the west-east differences in the biogeochemistry are primarily caused by differences in the physical environmental conditions. The biogeochemical differences are also suggested to

NEMURO.FISH was applied to Pacific saury to study the dependence of spawning season on growth. The model was composed of three ocean domains, which corresponded to the Kuroshio, the Oyashio, and the interfrontal zone (mixed water) regions. In these three domains, a lower trophic model (NEMURO) was coupled with a simple physical model, and the time-variation of three zooplankton size classes was input as prey densities into the saury bioenergetics model. Three numerical experiments were examined using this model, which corresponded to three different spawning seasons. Results showed that in the first year winter-spawned saury showed the fastest growth, and spring-spawned showed the slowest growth, while in the second year (time to grow to 120 g wet weight), the reverse occurred, i.e., spring-spawned saury showed the fastest growth. This difference in growth, which depends on the spawning season, can explain the bimodal size distribution of early autumn catch data.

A three-dimensional ecosystem–physical-coupled model is applied to the Okhotsk Sea. Factors that determine the spatial distribution of phytoplankton in the Okhotsk Sea in autumn and spring are analyzed, and the effects of sea ice on the spring bloom are also discussed. One of the most important factors determining the spatial distribution of phytoplankton in autumn is regional variation in mixed layer depth. The model can explain the spatio-temporal variation of chlorophyll-a concentration in the Okhotsk Sea during the spring blooms in 1997 and 2001. The start of the spring bloom in the Okhotsk Sea depends on the light environment. By controlling the light intensity in sea surface water, sea ice controls the timing of the spring bloom.

Progress in Oceanography 119 (2013) 1–3 Contents lists available at ScienceDirect Progress in Oceanography journal homepage: www.elsevier.com/locate/pocean Preface Introduction: Sensitivities of marine food webs and biogeochemical cycles to enhanced ocean stratification This issue contains papers from a workshop on ‘‘Sensitivities of food webs and biogeochemical cycles to enhanced ocean stratifica- tion’’, one of the topic areas explored at the second international meeting (IMBIZO II) of the Integrated Biogeochemistry and Ecosys- tem Research (IMBER) Program. IMBER has the general goals of advancing understanding and predictive capacity for the ocean’s ecological and biogeochemical responses to global change. As one approach to moving this agenda forward, IMBIZOs (imbizo is a Zulu word for gathering of people) are held approximately biennially, bringing scientists together to review current knowledge and iden- tify key questions for future research in three concurrent but inter- active topical workshops. IMBIZO II, broadly focused on regional oceanographic studies, was hosted in October 2010 at the Cretaquarium and Hellenic Center for Marine Research in Crete, Greece (Fig. 1). It involved 120 participating scientists from 26 countries who presented re- sults and discussed outstanding issues relating to three areas: (1) the effects of varying elemental ratios and food quality in mar- ine food webs; (2) large-scale regional comparisons of marine bio- geochemistry and ecosystem processes; and (3) stratification effects on marine food webs and biogeochemical cycles. Contribu- tions to Workshop #2 on research approaches and results of com- parative ecosystem studies have recently been published as a special issue of Journal of Marine Systems (Hood et al., 2013). Here, we provide an introduction to the contributions from Workshop Increased stratification of the upper oceans is a predicted gen- eral consequence of global climate warming. The implications for food webs and biogeochemical cycling, however, remain poorly quantified and inadequately understood on regional to global scales. Enhanced thermal stratification can directly impact nutrient fluxes, metabolic rates and balances in the euphotic zone. Changes in the onset and strength of stratification can both increase or de- crease the magnitude of seasonal production cycles, depending on environmental context. Possible ecological and biogeochemical sensitivities include: altered biomass, size structure, composition and diversity of the plankton community; timing effects on the coupling of production and grazing processes, trophic controls and reproductive cycles of key species; alterations in the ratios of nutrient availability, utilization and remineralization within the euphotic zone; and modified rates and pathways (particle flux, DOC, active migrations) of carbon and nutrient export out of the euphotic zone and through the underlying deep-sea water column. Significant uncertainties on many levels, including changing boundary inputs from adjacent systems (e.g. Rykaczewski and Dunn, 2010), make the net effects of such alterations, positive or negative, poorly resolved on regional bases. 0079-6611/$ - see front matter O 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.pocean.2013.10.001 The stratification workshop drew together perspectives from re- gional comparisons in the contemporary ocean, from paleo-recon- structions of past ocean conditions, and from models extending to future scenarios. Participants considered general organizing princi- ples, major unknowns, and strategies for further study. Resulting recommendations emphasized the continuing need to improve understanding of regional ocean ecology and biogeochemistry and their interactions, but they also noted a need to focus attention on organisms/strategies that may be selected for by enhanced strat- ification (e.g. diazotrophs, mixotrophs, specialized niche diatoms, gelatinous suspension feeders and predators) and that can impact ocean biogeochemistry in significant ways. To better anticipate sys- tem responses, feedbacks and regional linkages associated with cli- mate change, global models need to account explicitly for such unconventional strategies and more accurately reflect the coupled physical processes (land–ocean–air) that drive critical resource and population exchanges among and within regions. Kemp and Villareal (2013) lead off the volume by challenging conventional wisdom that diatoms will greatly decrease with in- creased warming and stratification, leading to replacement by smaller phytoplankton and diminished productivity and carbon export. Their counter-argument considers specific diatom adapta- tions to low-light growth in the deep euphotic zone and diatom– diazotroph symbioses that afford niche advantages that maintain seed populations for opportunistic blooms. Evidence is presented from paleo-oceanographic as well as contemporary studies that diatoms with such strategies are often bloom and export domi- nants, even under strong stratification and oligotrophic conditions. Currently, such strategies are inadequately represented in param- eterizations of diatom capabilities that go into most models of ocean ecosystems. Schmoker and Hernandez-Leon (2013) provide another exam- ple of marine food web response to increased stratification that runs counter to expectation. Their study region, the Canary Cur- rent, has experienced progressive warming and decreased produc- tivity in recent decades. The surprising result of their fine-scale temporal sampling over two years of differing seasonal stratifica- tion is that picophytoplankton decease, rather than increase, in rel- ative importance to total phytoplankton during the periods of water-column stability. Food-web path analysis, based on correla- tions among organisms occupying adjacent trophic levels, support, in part, a top-down explanation for this finding – picophytoplank- ton are controlled by microzooplankton grazers when they, in turn, are released from grazing pressure by reduced mesozooplankton predation during oligotrophy. Overall, results of the study indicate that small inter-annual differences in temperature and stratifica- tion can lead to important changes in pelagic community structure

We have applied a data assimilation technique to determine biological parameters in the PICES (North Pacific Marine Science Organization) proto type lower trophic level model (NEMURO). North Pacific Ecosystem Model for Understanding Regional Oceanography (NEMURO) has about 80 biological parameters and 11 initial values. We used a sensitivity analysis to choose eight parameters which mostly impacted the simulated values of interest. These parameters were selected as control variables for the data assimilation. Using an adjoint method, we assimilated biological and chemical data from Stn.A7 (off Hokkaido, Japan) into the model. Twin experiments were conducted to determine whether the data constrain those eight control variables. Model output, using optimum parameter values determined by the assimilation, agreed with the data better than those obtained with the first guess parameter values. But some problems still remain even in the simulations using the optimum parameters: namely a large discrepancy is seen between the simulation and data for small zooplankton and the simulated bloom of large phytoplankton that is too large.

A vertically one-dimensional ecosystem model is applied to Station KNOT (Kyodo North Pacific Ocean Time series; 44°N, 155°E). This model has 15 compartments, including two categories of phytoplankton (diatoms and non-diatom small phytoplankton) and three categories of zooplankton (small, large and predatory zooplankton). Observed seasonal cycles of ecosystem dynamics at Station KNOT, such as surface nutrient concentrations and column-integrated chlorophyll-a, are successfully reproduced by the model. Observed significant seasonality of a total primary production is also reproduced, but its amount is overestimated by more than 50%, especially during summer. The simulated spring diatom bloom seems to occur 1 month earlier than in reality, considering dramatic decreases in the observed surface silicate in May and June, but it is impossible to determine the time of the actual bloom more precisely because of lack of data in April. Sensitivity studies for several important parameters are described. The Ekman upwelling velocity strongly affects the amount of the total primary production. Stoichiometry of silicon to nitrogen for diatoms strongly determines the amount of the primary production by small phytoplankton. Maximum photosynthetic rate for diatoms contributes to set both the timing and strength of the spring diatom bloom. Maximum rate of grazing on diatoms by large zooplankton controls the timing of the end of the spring diatom bloom and the strength of the autumn diatom bloom. While most of the parameters can be set to the same values as those for Station A7 (41.5°N, 145.5°E), in the Northwestern Pacific like Station KNOT, some values need to be modified. The modification of the parameter values may be partly caused by the difference in the ecosystem dynamics between Stations KNOT and A7. Observations of the mixed-layer depth and surface nutrient concentrations in March and April, when they reach their maxima, are strongly required to reduce uncertainty of the parameter values.

An ecosystem model is embedded in an ocean general circulation model (OGCM) and the ecosystem–physical combined model is applied to the North Pacific. The OGCM yields realistic physical environments concerning the mixed layer depth (MLD) and vertical flow except for MLD off Sanriku coast, Japan, and on both sides of the equator. The modeled nitrate, chlorophyll zooplankton, net primary production, and total organic nitrogen are within the order of magnitude of the observations. The biological activities are low in the subtropical region and high in the subpolar and the equatorial region as observations show. The modeled primary production rate shows a local maximum along the subpolar front, which seems to have a counterpart in the observation. There, the temperature and the nutrient condition are best combined for photosynthesis. The modeled concentrations differ from the observations in some respects: chlorophyll concentration is low in the subpolar region and high in the subtropical and the equatorial region compared with the Coastal Zone Color Scanner observation; the equatorial net primary production rate is higher than the observed. Part of the disagreement may be ascribed to the photoadaptation process, which is not included in the model and/or the simple extrapolation of the temperature dependence of photosynthesis.

Several types of ecosystem models have been used to explore aspects of the seasonal, geographical, and interannual variation of plankton abundance and production in the open subarctic Pacific Ocean. We review the main results of these models, identify problems that limit the use of models as diagnostic and prognostic tools, and suggest challenges for future modelling work.

Seagrass bed has an important role in the marine ecosystem of estuarine areas. To conserve and manage these seagrass beds, understanding the system and the role of seagrass is necessary. A three-dimensional physical-biological coupled model (MK-3) was modified to include a seagrass bed and it was applied to Akkeshi lake, on the Pacific coast of Hokkaido in the northern part of Japan. Nitrogen and phosphorus fluxes were evaluated to investigate the role of seagrass on the nutrient cycle. First, a simple box model was developed. We divided the lake into three boxes to estimate the characteristics of the nutrient cycle from observed data. The box model revealed that nitrate is supplied to the lake through physical processes, i.e. river discharge and advection from outer regions and is consumed biologically inside the lake. On the other hand, phosphate is supplied from inside the lake and flows out. Second, to explain this different behavior of nitrate and phosphate, the three-dimensional physical–biological coupled model was applied. The model was run under average meteorological conditions of April for 10 days, then a calculation was continued using actual conditions (wind, precipitation, etc.) during 16–27 April 1996. The calculation was carried out for two cases: (1) with eelgrass; and (2) without eelgrass. In the case without eelgrass, nitrate and phosphate were both reduced by biological and chemical processes inside the lake. In the case with eelgrass, nitrate was reduced, but phosphate was produced inside the lake, which was estimated by the box model. Furthermore, the eelgrass was more important than phytoplankton to produce particulate organic matter. The daily variation in chlorophyll a and nitrate, which was observed during 16–27 April 1996, could not be reproduced in the model results, although the average values coincided with the observed values. This may be because of the effect of melting snow in the river discharge (data not shown).

A time-dependent, three-dimensional model simulates some important biological and physical processes in Otsuchi Bay in the northern part of Japan during the spring bloom in 1990. The spatial distribution of chlorophyll and primary productivity in the model is determined primarily by light condition and secondarily by the strength of vertical advection which is caused by a compensated current of strong westerly wind induced by the surface current. Nutrients are not the limiting factors during the spring bloom and zooplankton does not have an important influence on chlorophyll levels.

A modeling study was conducted to investigate the effects of interaction between two warm-core rings on the phytoplankton distribution. Using a quasi-geostrophic reduced-gravity model, the interaction between two vortices was calculated to reproduce the partial vortex merger between two warm-core rings, 86B and OR. On the calculated flow field, the three-dimensional model of plankton dynamics generated high phytoplankton biomass at the edge of the merged vortex. In the model, phytoplankton grew due to nutrient transport into the euphotic zone by upward motion of water caused by meanders of the current followed by the partial vortex merger. Further, the model reproduced the horizontal distribution of phytoplankton observed in 86B.

A numerical model is developed for aquaculture management, which consists of four parts: (1) a current simulation model, which calculates tidal and wind-induced currents, (2) a chemical oxygen demand (COD) diffusion model, which calculates spatial distribution of COD using the simulated current, (3) a dissolved oxygen (DO) diffusion model, which calculates the spatial distribution of DO, and (4) an accumulation model, which calculates the distribution of deposits from fish aquaculture. Our model is capable of calculating the detailed spatial distribution of COD and DO by dividing the bay into many grid points. It also takes into consideration the effects of feed and fish in each raft, and the loading of COD from rivers. Using this model, we can assess the influence of the location or the area of aquaculture rafts on the ecological and/or environmental system. It is also of practical use in order to obtain a better distribution of rafts in bay areas, or to calculate the basic data for the renewal of licenses of an aquaculture business. The model is applied to Mikame Bay in Ehime Pref., west Japan, as a case study.

On the basis of the existing physiological and ecological information, a biomass-based ecosystem model of sand lance ( Ammodytes personatus ) in Seto Inland Sea, Japan, was developed for studying the important biological parameters for stock fluctuation and the role of harvest of sand lance. The model shows that the natural mortality rate of the young sand lance, the biomass of zooplankton, and/or aestivation of sand lance play important roles in the stock fluctuation. These results are supported by sensitivity analysis.

In this paper, focusing on the recruitment processes, we synthesize the results of our recent analytical and numerical studies on the population ecology of the Japanese sand lance in the eastern part of the Seto Inland Sea. Among physical processes, the wind-induced current has a significant effect on the transport and distribution of the larvae. Prey-predator interactions, competion for the specific habitats, and other ecological processes could affect the recruitment. In addition to the year to year variability of the larval hatching and apparent survival rates, some recent trends of the variation in the larval population are also discussed.

A numerical model is developed for mariculture management, which consists of four parts: (1)current simulaton model which calculates tidal and wind induced currents, (2)COD diffusion model which calculates spatial distribution of COD using simulated current, (3)DO diffusion model which calculates spatial distribution of dissolved oxigen, and (4)accumulation model which calculates distribution of deposits from mariculture of fish. Our model is capable of (1) calculating the detailed spatial distribution of COD and DO by dividing the bay area in to many grid points, (2) taking into consideration the effects of feed and fish in each raft, and the loading of COD from rivers. Using this model, we can assess the influence of the location or the area of the mariculture rafts on the ecological and/or environmental system. It is also of practical use in order to obtain a better distribution of rafts in bay areas, or to calculate the basic data for the renewal of licenses. Application is made to Mikame Bay in Ehime Pref., west part of Japan, as a case study.

A system of simulation models on the outbreak of ‘red tide’, a large-scale phytoplankton bloom, is developed by identifying a model structure based on the marine ecological and hydrological conditions in the East Seto Inland Sea, Japan. The models consists of two parts: one is to determine hydraulic conditions of water movements in the sea, and the other is to calculate biological interactions among red tide organisms and nutrients under the diffusive and advective transportation associated with the calculated water movement. The comparison between the results simulated by our models and the observed biological or physical data on ‘red tide’ has shown: (a) the amount of nutrients and oceanographic characteristics are basic factors influencing the rapid increase in phytoplankton population; (b) the alternate migration of both phyto- and zooplanktons in the vertical direction according to a light/dark cycle causes a dense phytoplankton population in the upper layer; and (c) the tidal current plus water movement induced by the wind has a great impact on phytoplankton dynamics.