Search

Small pelagic fish species, such as sardine and anchovy, can exhibit dramatic decadal-scale shifts in abundance in response to climate variability. Understanding the mechanisms and the relationships among the different components of the food web through which environmental forcing can drive the observed fish variability remains a challenging problem. The modelling study described herein, focusing on the Canary Current System, implements and builds on earlier modelling efforts by Rose et al. (2015) and Fiechter et al. (2015) in the California Current System. This new application of the modelling framework to the Canary Current system provides an approach that bridges a comprehensive database with end-to-end (climate-to-fish) modelling, thereby enabling the investigation of the sources of variability of sardine (Sardina pilchardus) and anchovy (Engraulis encrasicolus). The aim of the modelling effort is to gain insights into the underlying mechanisms that drive the observed biological variability. Particular attention is given to the absence of regime shifts between sardine and anchovy in the Canary Current, which is a distinctive feature among the four major eastern boundary upwelling ecosystems. A model simulation for 1958–2007 was performed and analysed. The biological traits and behaviours prescribed for sardine and anchovy for the Canary Current give rise to different spatial distribution of their populations, and in contrast with other eastern boundary upwelling ecosystems, to synchronous (rather than asynchronous) variability of their abundance and biomass. Analyses of years with anomalously high increases and declines of the adult populations implicate food availability (instead of temperature or other environmental drivers) as the main factor determining recruitment for both sardine (via spawning and survival of feeding age-0 individuals) and anchovy (via survival of feeding age-0 individuals). The common dependence of sardine and anchovy on food, together with the domain-wide response of zooplankton to climate forcing generated in the model, provides a plausible explanation for the synchronization of the two populations. Our results also point at differences between sardine and anchovy; while the two species thrive under enhanced upwelling-favourable winds, anchovy larvae become particularly vulnerable to drift mortality, and thus do better than sardine under more moderate upwelling conditions.

Many fisheries and marine science organizations are working to determine how to meet their missions in the midst of the COVID-19 outbreak. As such, it seems prudent to exchange ideas, share knowledge, and initiate a discussion among us. As the scientific leadership team for NOAA Fisheries, we wanted to offer some perspectives. Others are also evaluating the impacts of COVID-19 but from the perspective of addressing tactical, day-to-day concerns of restarting operations for various marine and fisheries-oriented organizations. Thus, it seemed appropriate to us to explore the potential challenges posed by COVID-19 and to purposefully ascertain whether there are strategic opportunities for improving how we conduct our operations. We need to find ways to mitigate the effects of COVID-19 on our mission and also to glean information from our responses while in the midst of the crisis. We offer some recommendations to that end and offer these thoughts not as having solved every problem, but to learn from each other, compare across organizations, and engage in dialogue within our discipline to advance much-needed changes.

Interdisciplinary research and collaborations are essential to disentangle complex and wicked global socio-ecological challenges. However, institutional structures and practices to support interdisciplinary research are still developing and a shared understanding on how best to develop effective interdisciplinary researchers (particularly at early career stages) is lacking. Barriers to interdisciplinary approaches, which include diverse disciplinary ‘languages’, research time constraints and limited guidance on how to achieve interdisciplinarity in practice, further challenge this understanding. To help overcome these barriers, this paper provides practical advice for early career researchers and their mentors, as well as senior researchers and lab leaders, in the form of 10 tips: ‘Develop an area of expertise’; ‘Learn new languages’; ‘Be open-minded’; ‘Be patient’; ‘Embrace complexity’; ‘Collaborate widely; ‘Push your boundaries’; ‘Consider if you will engage in interdisciplinary research’; ‘Foster interdisciplinary culture’; and ‘Champion interdisciplinary researchers’. They are presented here to empower present and future generations of interdisciplinary researchers in their endeavour to solve contemporary socio-ecological challenges worldwide.

Starting in 2011, coastal areas of the Caribbean Sea and tropical Atlantic Ocean began to experience extraordinary yearly accumulations of pelagic Sargassum brown alga. Historical reports place large quantities of Sargassum only in the North Atlantic (mostly in the Gulf of Mexico and the Sargasso Sea). Accumulations of Sargassum in the tropical Atlantic have continued. We used a numerical particle-tracking system, wind and current reanalysis data, drifting buoy trajectories, and satellite imagery to determine the origin of the Sargassum that is now found persistently in the tropical Atlantic. Our analyses suggest that during the extreme negative phase of the winter 2009–2010 North Atlantic Oscillation (NAO), unusually strong and southward-shifted westerly winds explain the transport of Sargassum from the Sargasso Sea (∼20–40°N, 80–20°W) into the far eastern North Atlantic. Our hindcast Sargassum distributions agree with surface current simulations with the inclusion of “windage”. Windage is the additional, wind-induced drift of material floating at the free surface resulting from direct wind forcing on the sea surface, as well as on floating or partially-submerged objects. In our simulations, windage is included as an added vector (speed and direction) to the model-computed surface ocean currents equivalent to 1% of surface wind velocities. Lagrangian analysis of the regional circulation suggests that (1) part of the Sargassum subsequently drifted to the southwest in the North Equatorial Current (NEC) and entered the central tropical Atlantic, arriving in the Caribbean by the spring of 2011, with (2) another portion continuing southward along the coast of Africa in the Canary Current, eventually joining the seasonally-varying system of tropical Atlantic currents and thereby delivering a large Sargassum population to the tropical Atlantic. Since then, Sargassum patches aggregate from March to September in massive windrows along the Inter-Tropical Convergence Zone (ITCZ) under the action of converging winds. The windrows follow the ITCZ in its seasonal northward migration in the central tropical Atlantic. They are stretched across the central tropical Atlantic as the ITCZ crosses the latitude of the seasonal formation of the North Equatorial Counter Current (NECC). These patches and windrows are exposed to high sunlight and open-ocean upward flux of nutrients due to eddy and wind-driven mixing in the central tropical Atlantic. During the northern spring and summer, as the Sargassum drifts farther north with the ITCZ, large portions of the population are advected into the eastern Caribbean Sea. Some of these patches remain dispersed as the ITCZ migrates southward, and re-aggregate into new windrows as the ITCZ intensifies the following March-April. If wind mixing is strong and the mixed layer is deeper than about 50–60 m in the southern tropical Atlantic at this time, the Sargassum will bloom and form a massive windrow. Otherwise, the bloom will be inhibited. The extreme 2009–2010 NAO wind anomaly could be considered as triggering a biosphere “tipping point” that caused important ocean-scale ecosystem changes in the tropical Atlantic, with significant recurrent social and economic consequences. Understanding whether this new expanded geographic range of massive Sargassum blooms is temporary or whether it will revert to its pre-2009 distribution requires sustained monitoring and research.

ICAWA : International Conference AWA, Lanzarote, ESP, 17-/04/2018 - 20/04/2018; Small pelagic fish (SPF) species are heavily exploited in eastern boundary upwelling systems (EBUS) as their transformation products are increasingly used in the world food chain. Management relies on regular monitoring, but there is a lack of robust theories for the emergence of the populations’ traits and their evolution in highly variable environments. This work aims to address existing knowledge gaps by combining physical and biogeochemical modelling with an individual life-cycle based model applied to round sardinella (Sardinella aurita) off northwest Africa, a key species for regional food security. Our approach focused on the processes responsible for seasonal migrations, spatio-temporal size-structure, and interannual biomass fluctuations. Emergence of preferred habitat resulted from interactions between natal homing behaviour and environmental variability that impacts early life stages. Exploration of the environment by the fishes was determined by swimming capabilities, mesoscale to regional habitat structure, and horizontal currents. Fish spatio-temporal abundance variability emerged from a complex combination of distinct life-history traits. An alongshore gradient in fish size distributions is reported and validated by in situ measurements. New insights into population structure are provided, within an area where the species is abundant year-round (Mauritania) and with latitudinal migrations of variable (300 to 1200 km) amplitude. Interannual biomass fluctuations were linked to modulations of fish recruitment over the Sahara Bank driven by variability in alongshore current intensity. The identified processes constitute an analytical framework that can be implemented in other EBUS and used to explore impacts of regional climate change on SPF.

We describe and document an end-to-end model of anchovy and sardine population dynamics in the California Current as a proof of principle that such coupled models can be developed and implemented. The end-to-end model is 3-dimensional, time-varying, and multispecies, and consists of four coupled submodels: hydrodynamics, Eulerian nutrient–phytoplankton–zooplankton (NPZ), an individual-based full life cycle anchovy and sardine submodel, and an agent-based fishing fleet submodel. A predator roughly mimicking albacore was included as individuals that consumed anchovy and sardine. All submodels were coded within the ROMS open-source community model, and used the same resolution spatial grid and were all solved simultaneously to allow for possible feedbacks among the submodels. We used a super-individual approach and solved the coupled models on a distributed memory parallel computer, both of which created challenging but resolvable bookkeeping challenges. The anchovy and sardine growth, mortality, reproduction, and movement, and the fishing fleet submodel, were each calibrated using simplified grids before being inserted into the full end-to-end model. An historical simulation of 1959–2008 was performed, and the latter 45 years analyzed. Sea surface height (SSH) and sea surface temperature (SST) for the historical simulation showed strong horizontal gradients and multi-year scale temporal oscillations related to various climate indices (PDO, NPGO), and both showed responses to ENSO variability. Simulated total phytoplankton was lower during strong El Nino events and higher for the strong 1999 La Nina event. The three zooplankton groups generally corresponded to the spatial and temporal variation in simulated total phytoplankton. Simulated biomasses of anchovy and sardine were within the historical range of observed biomasses but predicted biomasses showed much less inter-annual variation. Anomalies of annual biomasses of anchovy and sardine showed a switch in the mid-1990s from anchovy to sardine dominance. Simulated averaged weights- and lengths-at-age did not vary much across decades, and movement patterns showed anchovy located close to the coast while sardine were more dispersed and farther offshore. Albacore predation on anchovy and sardine was concentrated near the coast in two pockets near the Monterey Bay area and equatorward of Cape Mendocino. Predation mortality from fishing boats was concentrated where sardine age-1 and older individuals were located close to one of the five ports. We demonstrated that it is feasible to perform multi-decadal simulations of a fully-coupled end-to-end model, and that this can be done for a model that follows individual fish and boats on the same 3-dimensional grid as the hydrodynamics. Our focus here was on proof of principle and our results showed that we solved the major technical, bookkeeping, and computational issues. We discuss the next steps to increase computational speed and to include important biological differences between anchovy and sardine. In a companion paper (Fiechter et al., 2015), we further analyze the historical simulation in the context of the various hypotheses that have been proposed to explain the sardine and anchovy cycles.

Pacific herring populations at eight North Pacific Rim locations were simulated to compare basin-wide geographic variations in age-specific growth due to environmental influences on marine productivity and population-specific responses to regime shifts. Temperature and zooplankton abundance from a three-dimensional lower-trophic ecosystem model (NEMURO: North Pacific Ecosystem Model for Understanding Regional Oceanography) simulation from 1948 to 2002 were used as inputs to a herring bioenergetics growth model. Herring populations from California, the west coast of Vancouver Island (WCVI), Prince William Sound (PWS), Togiak Alaska, the western Bering Sea (WBS), the Sea of Okhotsk (SO), Sakhalin, and Peter the Great Bay (PGB) were examined. The half-saturation coefficients of herring feeding were calibrated to climatological conditions at each of the eight locations to reproduce averaged size-at-age data. The depth of averaging used for water temperature and zooplankton, and the maximum consumption rate parameter, were made specific to each location. Using the calibrated half-saturation coefficients, the 1948–2002 period was then simulated using daily values of water temperature and zooplankton densities interpolated from monthly model output. To detect regime shifts in simulated temperatures, zooplankton and herring growth rates, we applied sequential t-test analyses on the 54 years of hindcast simulation values. The detected shifts of herring age-5 growth showed closest match (69%) to the regime shift years (1957/58, 1970/71, 1976/77, 1988/89, 1998/99). We explored relationships among locations using cluster and principal component analyses. The first principal component of water temperature showed good correspondence to the Pacific Decadal Oscillation and all zooplankton groups showed a pan-Pacific decrease after the 1976/77 regime shift. However, the first principal component of herring growth rate showed decreased growth at the SO, PWS, WCVI and California locations and increased growth at the Sakhalin, WBS and Togiak locations after 1977. The SO location belonged to the same cluster as the location in with the eastern North Pacific. The calibrated half-saturation coefficients affected the degree to which growth was sensitive to interannual variation in water temperature versus zooplankton. For example, the half-saturation values for the SO location resulted in very efficient feeding that shifted the sensitivity of herring growth from food to temperature. The model results demonstrate how geographic specificity of bioenergetics parameters, coupled with location-specific variation in temperature and food, can combine to determine local and regional responses of fish growth to climate forcing.

Recent developments in global dynamical climate prediction systems have allowed for skillful predictions of climate variables relevant to living marine resources (LMRs) at a scale useful to understanding and managing LMRs. Such predictions present opportunities for improved LMR management and industry operations, as well as new research avenues in fisheries science. LMRs respond to climate variability via changes in physiology and behavior. For species and systems where climate-fisheries links are well established, forecasted LMR responses can lead to anticipatory and more effective decisions, benefitting both managers and stakeholders. Here, we provide an overview of climate prediction systems and advances in seasonal to decadal prediction of marine-resource relevant environmental variables. We then describe a range of climate-sensitive LMR decisions that can be taken at lead-times of months to decades, before highlighting a range of pioneering case studies using climate predictions to inform LMR decisions. The success of these case studies suggests that many additional applications are possible. Progress, however, is limited by observational and modeling challenges. Priority developments include strengthening of the mechanistic linkages between climate and marine resource responses, development of LMR models able to explicitly represent such responses, integration of climate driven LMR dynamics in the multi-driver context within which marine resources exist, and improved prediction of ecosystem-relevant variables at the fine regional scales at which most marine resource decisions are made. While there are fundamental limits to predictability, continued advances in these areas have considerable potential to make LMR managers and industry decision more resilient to climate variability and help sustain valuable resources. Concerted dialog between scientists, LMR managers and industry is essential to realizing this potential.

The advent of an ecosystem-based approach dramatically expanded the scope of fisheries management, creating a critical need for new kinds of data and quantitative approaches that could be integrated into the management system. Ecosystem models are needed to codify the relationships among drivers, pressures and resulting states, and to quantify the trade-offs between conflicting objectives. Incorporating ecosystem considerations requires moving from the single-species models used in stock assessments, to more complex models that include species interactions, environmental drivers and human consequences. With this increasing model complexity, model fit can improve, but parameter uncertainty increases. At intermediate levels of complexity, there is a ‘sweet spot’ at which the uncertainty in policy indicators is at a minimum. Finding the sweet spot in models requires compromises: for example, to include additional component species, the models of each species have in some cases been simplified from age-structured to logistic or bioenergetic models. In this paper, we illuminate the characteristics, capabilities and short-comings of the various modelling approaches being proposed for ecosystem-based fisheries management. We identify key ecosystem needs in fisheries management and indicate which types of models can meet these needs. Ecosystem models have been playing strategic roles by providing an ecosystem context for single-species management decisions. However, conventional stock assessments are being increasingly challenged by changing natural mortality rates and environmentally driven changes in productivity that are observed in many fish stocks. Thus, there is a need for more tactical ecosystem models that can respond dynamically to changing ecological and environmental conditions.

Ecosystem-based management (EBM) has emerged as a basic approach for managing human activities in marine ecosystems, with the aim of recovering and conserving marine ecosystems and the services they deliver. Integrated ecosystem assessments (IEAs) further the transition of EBM from principle to practice by providing an efficient, transparent means of summarizing the status of ecosystem components, screening and prioritizing potential risks, and evaluating alternative management strategies against a backdrop of environmental variability. In this paper, we draw upon lessons learned from the US National Oceanic and Atmospheric Administration's IEA programme to outline steps required for IEA implementation. We provide an overview of the conceptual framework for IEAs, the practical constraints that shape the structure of individual IEAs, and the uses and outcomes of IEAs in support of EBM.

The evolution of the North Pacific Ecosystem Model for Understanding Regional Oceanography (NEMURO) family of models to study marine ecosystems is reviewed. Applications throughout the North Pacific have shown the models to be robust and to be able to reproduce 1D, 2D and 3D components of nutrient, carbon cycle and biogeochemical cycles as well as aspects of the lower trophic levels ecosystem (phyto- and zooplankton). NEMURO For Including Saury and Herring, an extension that includes higher trophic levels, can be run uncoupled or coupled to NEMURO. In the uncoupled mode, the growth and weight of an individual fish is computed using plankton densities simulated by NEMURO but with no feedback between fish consumption and plankton mortality. In the coupled mode, the feeding, growth and weight of a representative fish are computed, and prey removals due to feeding by fish appear as mortality terms on the prey. The NEMURO family of models continues to evolve, including effects of the microbial loop and iron limitation at lower trophic levels, and full life cycle, multi-species and multi-generational simulations at higher trophic levels. We outline perspectives for future end-to-end modeling efforts that can be used to study marine ecosystems in response to global environmental change.

The study of climate impacts on Living Marine Resources (LMRs) has increased rapidly in recent years with the availability of climate model simulations contributed to the assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Collaboration between climate and LMR scientists and shared understanding of critical challenges for such applications are essential for developing robust projections of climate impacts on LMRs. This paper assesses present approaches for generating projections of climate impacts on LMRs using IPCC-class climate models, recommends practices that should be followed for these applications, and identifies priority developments that could improve current projections. Understanding of the climate system and its representation within climate models has progressed to a point where many climate model outputs can now be used effectively to make LMR projections. However, uncertainty in climate model projections (particularly biases and inter-model spread at regional to local scales), coarse climate model resolution, and the uncertainty and potential complexity of the mechanisms underlying the response of LMRs to climate limit the robustness and precision of LMR projections. A variety of techniques including the analysis of multi-model ensembles, bias corrections, and statistical and dynamical downscaling can ameliorate some limitations, though the assumptions underlying these approaches and the sensitivity of results to their application must be assessed for each application. Developments in LMR science that could improve current projections of climate impacts on LMRs include improved understanding of the multi-scale mechanisms that link climate and LMRs and better representations of these mechanisms within more holistic LMR models. These developments require a strong baseline of field and laboratory observations including long time series and measurements over the broad range of spatial and temporal scales over which LMRs and climate interact. Priority developments for IPCC-class climate models include improved model accuracy (particularly at regional and local scales), inter-annual to decadal-scale predictions, and the continued development of earth system models capable of simulating the evolution of both the physical climate system and biosphere. Efforts to address these issues should occur in parallel and be informed by the continued application of existing climate and LMR models.

A broad marine policy goal is to maintain healthy marine social–ecological systems that sustain desirable ecosystem services and support human livelihoods. Marine social–ecological systems are already stressed by a number of environmental factors and the impacts of globalisation. Climate change is an additional stress that may push marine social–ecological systems beyond the ranges of past variability to which they have become adapted. Human social systems have well-developed strategies for dealing with variability within their normal ranges of experience, although these capacities are not distributed homogeneously around the globe. This paper addresses the additional impacts of climate change on marine social–ecological systems that are focussed around fishing. For example, human social fishing systems dealing with high variability upwelling systems with rapidly reproducing fish species may have greater capacities to adjust to the additional stress of climate change than human social fishing systems focussed on longer-lived and generally less variable species. The details of local impacts of climate change and its interactions with existing stresses on marine social–ecological systems are difficult to predict but will lead to more extreme events and increased uncertainty. Management must strive to enhance the adaptive capacities of these systems to uncertainty and change. Primary challenges are to address non-climate change stresses such as overfishing and how they may interact with climate change to produce surprises, and to recognise that multiple interacting time, space and organisational scales make identification and resolution of impacts difficult. Additional challenges are to develop integrated observing and modelling systems for the full social–ecological system so as to quickly recognise changes, to enhance communications with stakeholders, and to develop flexible institutions that can adjust rapidly to new circumstances.

A B S T R A C T The management of the SEACOOS program and its evolution over a five-year period are reviewed. The topics included pertain to the mechanisms used to create a consortium, define its mission, develop and manage its annual budget and tasking cycle; and the history of its focus over a five-year period. The management of SEACOOS was complex and required significant efforts to develop new approaches and collaborative mechanisms. Changes in management were made as weaknesses were identified and to enable a more unified ap proach to the evaluation, operations, data management and outreach efforts. A number of programmatic lessons learned are summarized that may be of value for future development of regional coastal ocean observing systems. of SEACOOS and its evolution over time are described. Another significant regional coastal ocean observing effort underway when SEACOOS began was the Gulf of Maine Ocean Observing System (GoMOOS, www.gomoos.org, Bogden and Richert, 2003). Good communication was established between the SEACOOS and GoMOOS programs, with strong collaboration on data management, but their program management approaches were quite different. GoMOOS had incorporated as a not-for-profit organization. It was focused on establishing and marketing a buoy-based observing program and viewed itself as a utility. GoMOOS also drew upon a history of regional collaboration that had not been established in the considerably larger four-state SEACOOS domain. Thus, the initial focus for SEACOOS was to foster collaboration between a number of existing sub-regional observing efforts.

In the marine environment, pelagic dispersal is important for determining the distribution and abundance of populations, as well as providing connections among populations. Estimates of larval dispersal from spawning grounds are important to determining temporal and spatial patterns in recruitment that may have significant influences on the dynamics of the population. We present a case study of the dispersal of Centropristis striata (black sea bass) larvae on the southeast U.S. continental shelf. We use a coupled larval behavior – 3D circulation model to compare the effects of the timing and location of spawning against that of larval vertical migration on larval dispersal. Using the results of field data on larval vertical distributions, we compare the dispersal of virtual ‘larvae’ which have ontogenetic changes in vertical behavior with that of particles fixed near the surface and near the bottom. Larvae were released at potential spawning sites four times throughout the spawning season (February through May) for 3 yr (2002–04) and tracked for the assumed larval duration (from 27 to 37 days including the egg stage). Results indicate that adult behavior, in the form of spawning time and location, may be more important than larval vertical behavior in determining larval dispersal on the inner- and mid- continental shelves of this region.

We used a nutrient-phytoplankton-zooplankton (NPZ) model coupled to a fish bioenergetics model to simulate the weight-at-age responses of Pacific herring Clupea pallasii to climate regimes. The NPZ model represents the daily dynamics of the lower trophic levels by simulating the uptake and recycling dynamics of nitrogen and silicon and the photosynthesis and grazing interactions of multiple functional groups of phytoplankton and zooplankton. The bioenergetics model simulates the number and mean weight of Pacific herring for each of 10 age-classes. Three zooplankton groups simulated in the NPZ model provide estimates of the prey used to determine the consumption component of the herring bioenergetics model. We used a spawner-recruit relationship to estimate the number of new age-1 individuals joining the herring population every year. The coupled models were applied to the coastal upwelling area off the west coast of Vancouver Island. Model simulations were performed to isolate the effects of each...

Pelagic larval dispersal is thought to be the main mechanism connecting many marine populations and is an important determinant both of an individual's success and a population's distri- bution and spatial structure. Thus, quantitative estimates of the retention or dispersion of larvae from spawning grounds is important for the determination of recruitment success in fisheries. Models can be used to study connectivity through a dispersal curve or dispersal kernel: the probability that a larva will settle at a given distance from its release location. We applied a 3-dimensional circulation model and a Lagrangian particle tracking model to the southeast US continental shelf to describe dispersal kernels in 2 dimensions. We used a fully orthogonal design to assess the importance of fac- tors that influence the dispersal kernel, including spawning time, spawning location, larval behavior (vertical position in the water column), larval duration, and turbulent dispersal. Our results indicate that adult behavior, in the form of spawning time and location, may be more important than larval behavior in determining larval dispersal on the inner- and mid-shelves in this region.

Author Posting. © Oceanography Society, 2007. This article is posted here by permission of Oceanography Society for personal use, not for redistribution. The definitive version was published in Oceanography 20, 3 (2007): 14-21.

0278-4343; The baroclinic and barotropic properties of ocean processes vary on many scales. These scales are determined by various factors such as the variations in coastline and bottom topography, the forcing meteorology, the latitudinal dependence of the Coriolis force, and the Rossby radius of deformation among others. In this paper we attempt to qualify and quantify scales of these processes, with particular attention to the horizontal resolution necessary to accurately reproduce physical processes in numerical ocean models. We also discuss approaches taken in nesting or down-scaling from global /basin- scale models to regional-scale or shelf-scale models. Finally we offer comments on how vertical resolution affects the representation of stratification in these numerical models. (c) 2007 Elsevier Ltd. All rights reserved.

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.

The infrequent occurrence of climate regime shifts and the long-lived life history of many harvested fish species imply that quantitative understanding of the effects of climate shifts on fish will require long-term data spanning decades. We use the output of the 3-dimensional (3D) NEMURO nutrient–phytoplankton–zooplankton model applied to the Northern Pacific as input to a Pacific herring (Clupea pallasi) bioenergetics model, and predict herring weights-at-age and growth from 1948 to 2000 for the West Coast Vancouver Island (WCVI), Prince William Sound (PWS), and Bering Sea (BS) locations. The feeding parameters of the bioenergetics model were calibrated from steady-state predictions of herring weights-at-age at each location compared to observed mean weights-at-age. Herring weights-at-age were then simulated from 1948 to 2000 using the 3D-NEMURO generated time series of monthly temperature and zooplankton densities. Herring growth rates, annual temperature, and zooplankton density time series were analyzed statistically for coincident shifts in their mean values. We also simulated herring growth rates using the 1948–2000 time series and averaged (climatological) temperature and zooplankton densities to determine the relative importance of temperature and zooplankton to predicted herring growth responses. All three locations showed a shift in herring growth during the mid and late 1970s. Herring growth decreased in WCVI and PWS, and increased in BS; these changes were coincident with a warming of temperature and a decrease in predatory zooplankton density. Herring growth responses in PWS and BS were more complex than those predicted for WCVI, with additional shifts predicted besides the late 1970s shift. Interannual variation in zooplankton densities caused the herring growth response for WCVI. Temperature and zooplankton densities affected the herring growth responses in both Alaskan locations, with zooplankton dominating the response for PWS and temperature dominating the response for BS. We compare our simulated herring growth responses to observed responses, and discuss the advantages and drawbacks of using the output of broadly applied lower trophic model as input to fish models in order to examine long-term responses to regime shifts at multiple locations.

We present a modeling approach where we use one common model formulation of a 11 state variable lower trophic level model that includes two groups of phytoplankton, three groups of zooplankton, and representations of nitrogen and silicate embedded in a three-dimensional ocean general circulation model (OGCM) and forced with a common climate forcing. Results are applied to a fish bioenergetics model for two geographically distinct ocean regions off Japan including the Oyashio, mixed, and Kuroshio subregions and off California including the subarctic, transition and subtropical subregions. The model is applied to two fish species (Pacific saury: Cololabis saira and Pacific herring: Clupea harengus pallasi) with different life histories in each region and the influence of three different “regime shift” periods was explored. With this approach, we narrow the observed biological response and model dynamics to reflect local conditions and eliminate differences related to the model formulations in each region. In general, the trend in temperature was negatively correlated with trends in the zooplankton community. Out-of-phase herring growth trends were observed between the Japan and California regions (r = −0.259, p = 0.02). In-phase growth trends between herring and saury were observed at the California region (r = 0.61, p

A one spatial-box version of the NEMURO oceanic lower trophic food web model was applied to a coastal upwelling environment typified by West Coast Vancouver Island. We used both ad hoc calibration and the automatic calibration program PEST. NEMURO was first calibrated to 1 year of monthly field data using the usual ad hoc approach of trial and error changes to 18 candidate parameters. Four PEST calibrations were then performed. The first three PEST calibrations used model predictions in year 10 from the ad hoc calibration as data in a twin experiment design; the fourth PEST calibration repeated the ad hoc procedure by having PEST calibrate NEMURO to the field data. When provided with ad hoc calibration model predictions as data, PEST accurately recovered the known 18 parameter values, even when small and large phytoplankton were lumped into total phytoplankton. When 57 parameters were allowed to vary PEST-estimated reasonable values for all 57 parameters, but they differed from the ad hoc calibrated values. However, when applied to the field data, PEST-estimated parameter values that differed greatly from the ad hoc values. The PEST calibration fitted some of the field data better than the ad hoc calibration but at the cost of unequal small and large phytoplankton concentrations. Thus, with proper and careful implementation, PEST offers a viable approach for objective calibration of NEMURO to site-specific monitoring data. We recommend that automatic calibration methods, such as PEST, be used for application of the NEMURO model to new locations. When the field data allow for specification of time series for each phytoplankton and zooplankton state variable, PEST will provide an objective, defensible, and repeatable way to calibrate the many parameters of the NEMURO model. If the available data are insufficient for specification of each state variable, then ad hoc calibration will likely be needed to allow for inclusion of qualitative decisions about model fit. Use of PEST in this situation will provide better understanding of the data-model mis-matches and will provide an alternative calibration to the necessary, but subjective, ad hoc calibration. Comparison of the ad hoc and PEST calibrations (even if unsuccessful) will help in the interpretation of the ad hoc calibration. Robust parameter estimation by any method depends on the quality and consistency of the calibration dataset.

We describe an approach to dynamically couple a fish bioenergetics-based population dynamics model to the NEMURO lower trophic level nutrient–phytoplankton–zooplankton model. The coupled models, denoted NEMURO.FISH and configured for Pacific herring (Clupea harengus pallasii) on the west coast of Vancouver Island, are capable of simulating the daily dynamics of the lower trophic levels and the daily average weight and numbers of individual herring in each of 10 age classes over multiple years. New recruits to the herring population are added each June based on either constant recruitment or dynamic recruitment generated from an environmental Ricker spawner–recruitment relationship. The dynamics of the three zooplankton groups in the NEMURO model determine the consumption rate of the herring; herring consumption affects the zooplankton, and egestion and excretion contribute to the nitrogen dynamics. NEMURO was previously calibrated to field data for the West Coast Vancouver Island. Thirty-year simulations of herring growth and population dynamics were performed that used repeated environmental conditions for the lower trophic levels of NEMURO and historical environmental variables for the herring spawner–recruit relationship. Herring dynamics were calibrated to the west coast of Vancouver Island such that the coupled models reasonably duplicated observed herring weights-at-age and total herring biomass. Additional 30-year simulations under constant recruitment with herring coupled and uncoupled from NEMURO clearly showed the effects of the feedback mechanism between the two models and also showed that herring have small to moderate effects on their prey. Monte Carlo uncertainty analysis showed the importance of feeding- and respiration-related parameters to predicted individual and population herring growth. The utility of the NEMURO.FISH framework for improving our understanding of climate change effects on marine ecosystem dynamics is discussed.

Cruises were conducted in spring 1999 to describe the interaction between tidal-front processes and the transport, retention, and growth of cod larvae and their prey during the seasonal transition to a stratified water-column along the southern flank of Georges Bank. All the physical and biological observations were integrated in coupled circulation-trophodynamic simulations. The three-dimensional circulation fields were modeled using data assimilation methods described in Aretxabaleta et al. [2005. Data assimilative hindcast on the Southern Flank of Georges Bank during May 1999: frontal circulation and implications. Continental Shelf Research 25, 849–874]. The individual-based model (IBM) of Lough et al. [2005. A general biophysical model of larval cod growth applied to populations on Georges Bank. Fisheries Oceanography 14, 241–262] was used to consider trophodynamic effects on the growth and survival of larval cod. Prey fields were specified for mixed and stratified water columns from field surveys and allowed to adjust in the circulation model. Encounter and ingestion rates of larvae were functions of prey concentration, larval search patterns, light, swimming speeds of predator and prey, and turbulence. Model outputs provide hourly depth-dependent estimates of growth rates, prey biomass ingested, and larval length and weight. Simulations were conducted along a 2-D transect across the tidal front, from mixed to stratified water columns, before and after a wind event. Pre-storm, observed larval cod growth rates, based on RNA–DNA analysis, were highest in the surface 20 m at the stratified and front stations. Post-storm, larval growth rates decreased 1–2% d −1 at the stratified and front stations, corresponding with a

Lagrangian particle tracking using three-dimensional (3D) numerical modeling approaches has become an important tool in coastal oceanography. In this note, an approach is described that can reduce the difference between observed and numerical drifter trajectories in the coastal ocean by including corrections to the water velocity due to differences between observed winds and the wind field used to drive the 3D circulation model and some specific characteristics of the observed drifters in the algorithm that estimate the numerical trajectory. Quantitative improvements are obtained whereby the separation distance between the numerical and observed drifters is almost halved (in this particular field case from 2.6 to 1.4 km day−1).

Lagrangian characterization of continental shelf circulation provides estimates of the retention and transport of particulate and dissolved substances. In this paper, we quantify the retentive characteristics of the Southeast US Continental Shelf by comparing observed and numerical (modeled) drifters released throughout 2000 and 2001. Agreement between the observed and computed drifter trajectories shows that retention on this shelf can be up to 2 months at any point during the year. These results have important implications for ecological and fisheries applications and indicate that the populations of marine organisms in this region might be relatively closed (i.e., with weak exchange) during some periods of the year.

Cetacean-habitat modeling, although still in the early stages of development, represents a potentially powerful tool for predicting cetacean distributions and understanding the ecological processes determining these distributions. Marine ecosystems vary temporally on diel to decadal scales and spatially on scales from several meters to 1000s of kilometers. Many cetacean species are wide- ranging and respond to this variability by changes in distribution patterns. Cetacean-habitat models have already been used to incorporate this variability into management applications, including im- provement of abundance estimates, development of marine protected areas, and understanding cetacean-fisheries interactions. We present a review of the development of cetacean-habitat models, organized according to the primary steps involved in the modeling process. Topics covered include purposes for which cetacean-habitat models are developed, scale issues in marine ecosystems, cetacean and habitat data collection, descriptive and statistical modeling techniques, model selection, and model evaluation. To date, descriptive statistical techniques have been used to explore cetacean-habitat relationships for selected species in specific areas; the numbers of species and geographic areas exam- ined using computationally intensive statistic modeling techniques are considerably less, and the de- velopment of models to test specific hypotheses about the ecological processes determining cetacean distributions has just begun. Future directions in cetacean-habitat modeling span a wide range of possibilities, from development of basic modeling techniques to addressing important ecological questions.

Field-derived growth rates (RNA-DNA based) of cod (Gadus morhua) larvae collected on the southern flank of Georges Bank were higher on average in May 1993 than May 1994, despite the apparent higher abundance of potential prey in 1994. A biophysical modeling study is presented here in which factors are examined that may have led to the difference in population mean growth. A one-dimensional physical model, forced by winds and tides, was used to simulate the vertical structure (of currents, temperature field, and turbulent kinetic energy dissipation rate) following a column of water in a Lagrangian sense at a site on the southern flank of Georges Bank over 5-day periods in late May of 1993 and 1994. The biophysical model and observed zooplankton abundance allowed us to explore the vertical structure and temporal (hourly) evolution of feeding and growth for cod larvae in relation to environmental conditions. Our trophodynamic model is improved over previous versions and now includes the effect of light on larval feeding response, as well as the effect of temperature on larval metabolic costs, ingestion, and digestion. Larval prey profiles, comprising four copepod species, were used from a time series of 1/4-m 2 MOCNESS tows to define the prey field. Data from a collateral time-series of larval gut contents (1-m 2 MOCNESS tows) was used to define maximum ingestion (satiation level) and prey selection. Model outputs provide depth-dependent estimates of growth, prey biomass ingested, larval length, and larval weight. Watercolumn growth-rate profiles were made for four size classes of larvae (5, 6, 7 and 9 mm) under the environmental conditions observed in May 1993 and 1994. A weighted-mean growth rate based on the mean vertical distribution of larvae was estimated for each size class. In all cases, when using all available potential prey, the model-derived 1994 growth rates were higher (by 3‐6% day )1 ) than those for 1993. However, simulations in which 7-mm larvae followed the field-derived weighted mean depth over the sampling period, and were limited to their preferred Pseudocalanus prey, resulted in average growth of 12.2% day )1 for 1993 and 9.7% day )1 for 1994. These compared closely to the field growth means of 11.3% day )1 in 1993 and 9.8% day )1 in 1994. Thus, the lower observed growth in May 1994 may have resulted from depth-dependent food limitation and prey-selectivity coupled with the greater metabolic costs induced by the higher temperature that year.

Flushing time and residence time are studied in a small inlet in Cabrera National Park, Western Mediterranean Sea. Flushing time is studied using ADCP in situ data. Observed flushing time data are compared with the simulations from a three-dimensional coastal ocean numerical model. Residence time is assessed using virtual lagrangian particles and studying the number remaining within the analyzed domain. Results show a good agreement between observations and modeling estimations of the flushing time (i.e. 6 days from the ADCP data and 5.6 days from the numerical model). Residence time estimations yield a broad range of values, from 1 h in the Bay to over 30 days depending also on the horizontal and vertical position where particles were released. A continuous stirred tank reactor (CSTR) model for the Port yields a value of 8.7 days. Results obtained for the residence time appear to have a determinant impact over the meadows of the seagrass Posidonia oceanica, present inside the Port. Recirculation patterns and complex flows in coastal environments create a non-uniform distribution of the areas of accumulation of non-conservative properties that indicate that residence time concept is the correct approach when studying the impact of water transport over biological communities. © 2005 Elsevier Ltd. All rights reserved.

The circulation of the tidal front along the Southern Flank of the Georges Bank region during May 1999 is examined for the purpose of understanding the transport of larval fish for periods of days to a week. Assimilation of shipboard ADCP data from several Georges Bank cruises into 3-D models is used to produce the hindcast circulation. Adjustments to boundary nodal elevations are estimated to minimize the misfit between model and observations both in frequency and time domains as described in Lynch and Hannah (J. Atmos. Oceanic Technol 18 (2001) 962) and Lynch and Naimie (Cont. Shelf Res. 22 (2002) 2191). An intercomparison of different methods of applying the adjustments is completed using drifter records and dye patch trajectories to provide a measure of skill. The computed flow fields show a skill of 2.4 km day - 1 when compared to (unassimilated) drifter trajectories. The tracking of a dye-patch recovers an observed near-bottom cross-bank flow component that is not present without assimilation. Using these flow fields we then investigate the importance of the front as a retention mechanism using passive particle simulations. Wind, heat flux, and tides control the circulation across and along the tidal mixing front. Three 3-day time periods, before, during and after a wind event during May 1999 were studied. Model simulations suggest a highly variable cell-like circulation in the frontal region (onshore near the bottom, upwelling shoalward of the front, offshore at mid-depth and downwelling seaward of the front) that controls the exchange and retention of particles. During the periods when the cell-like circulation is active the highest accumulation of particles occurs in the areas surrounding the front.

A fish bioenergetics model coupled with an ecosystem model was developed to reproduce the growth of Pacific saury. The model spatially covers three different oceanographic spatial domains corresponding to the Kuroshio, Oyashio, and interfrontal (mixed water) regions. In this coupled model, three (small, large, and predatory) zooplankton densities which were derived from the lower trophic level ecosystem model were input to the bioenergetics model of saury as the prey densities. Although certain model parameters were imposed from other species’ bioenergetics, several model parameters were estimated from observational data specific to Pacific saury. The integrated model results reproduced appropriate growth rates of Pacific saury. Model sensitivities to water temperature and prey density are examined and observational methods to evaluate the model parameters are discussed.

This paper addresses shelf-scale simulation with dominant open-water boundary conditions obtained by inversion of interior data. Important, established operational data streams are located along the shore of the study area, in areas influenced strongly by the local geometry. Failure to properly resolve the modeled near field surrounding these data results in their incorrect interpretation, causing invalid inversions and erroneous field estimates far across the shelf. Specifically, improving the model fit to the unresolved data leads to skill degeneration farther offshore and generally unacceptable field estimates remarkably far from shore. Proper near-field resolution leads to valid interpretation and inversion of the same data, with high inverse skill apparent across the shelf. The resolution required is within reach of today's technology.

The utility of individual based models (IBMs) is that properties of ecological systems can be derived by considering the properties of individuals constituting them. Individual differences may be physiological, behavioral or may arise from interactions among individuals. The differences result in unique life histories, which when considered as a whole give rise to growth and size distributions that provide a measure of the state of the population. Early IBMs generally did not consider the effect of a spatially variable physical environment. Recent advances in ocean circulation models that include realistic temporal and spatial variation of currents, turbulence, light, prey, etc., have enabled IBMs to be embedded in model flow fields and for unique, sometimes behaviorally modified, Lagrangian trajectories to be computed. The explicit consideration of realistic spatial heterogeneity provides an additional factor that contributes to the differentiation among individuals, to variances in population s...

A simple conceptual model is developed for larval fish feeding on stage-structured prey populations, in an Eulerian framework. The model combines simplified contemporary models of larval fish trophodynamics, zooplankton population dynamics, and hydrodynamic turbulence. The Eulerian view allows instructive maps of larval feeding and growth rates for individual prey species, alone or in combination. Decadally averaged MARMAP surveys of Calanus finmarchicus and Pseudocalanus spp. are analyzed for the March–April period. Quasi-static population dynamics are used to infer the abundance of the smallest stages from adult female abundance. Computed growth rates show that Calanus alone is insufficient to support the smallest cod larvae (4 and 6 mm), but provides good growth (⩾10%/day) for large larvae (10, 12 mm). Pseudocalanus alone provides generally good growth for all larvae but is mismatched spatially with observed cod spawning and subsequent larval advection. Both species together provide good growth, matched spatially with larval cod, for 6 mm and larger larvae. A dietary supplement beyond these two species is needed for the smallest larvae. The procedure provides a general method for mapping observations of zooplankton abundance, distribution and reproductive status, and their relevance to larval fish survival, when the smallest stages are not observable.

Discussion 1960 In a rece t article, Leising and Franks (1999) presented detailed individual-based models (IBMs) for larval Atlantic cod (Gadus morhua) and haddock (Melanogrammus aeglefinus) based on the bioenergetic models of Laurence (1985) for the same species. Using these models, they drew conclusions on the effects of varying prey density, turbulence, and temperature on larval growth rate. However, an error in calculation of metabolism and their choice of a scalar for the effect of temperature on assimilation (Qa, their table 1) may require a revision of Leising and Franks’ (1999) conclusions. The error in estimation of daily metabolic rates originated in Laurence (1985) and was repeated in Werner et al. (1996). In this comment, we provide revisions for the estimation of metabolic costs and suggest that Qa for marine fish larvae should fall in the range of 1.06–1.14 based on our analysis of available literature. We also point to components of the model where compensating errors may occur and additional research is needed.