Search

International audience; Biophysical interactions are influential in determining the scale of key ecological processes within marine ecosystems. For oceanic predators, this means foraging behaviour is influenced by processes shaping the distribution of prey. However, oceanic prey is difficult to observe and its abundance and distribution is regionally generalised. We use a spatiotemporally resolved simulation model to describe mid‐trophic prey distribution within the Southern Ocean and demonstrate insights that this modelled prey field provides into the foraging behaviour of a widely distributed marine predator, the southern elephant seal.From a five‐year simulation of prey biomass, we computed climatologies of mean prey biomass (average prey conditions) and prey biomass variability (meso‐scale variability). We also compiled spatially gridded metrics of seal density and diving behaviour from 13 yr of tracking data. We statistically modelled these metrics as non‐linear functions of prey biomass (both mean and variability) and used these to predict seal distribution and behaviour. Our predictions were consistent with observations (R2adj = 0.23), indicating that seals aggregate in regions of high mesoscale activity where eddies concentrate prey. Here, seals dived deeper (R2marg = 0.12, R2cond = 0.51) and spent less time hunting (R2marg = 0.05, R2cond = 0.56), likely targeting deep but profitable prey patches. Seals generally avoided areas of low eddy activity where prey was likely dispersed. Most seals foraged south of the Subantarctic Front, despite north of the front exhibiting consistently high simulated prey biomasses. This likely reflects seal prey or habitat preferences, but also emphasises the importance of mesoscale prey biomass variability relative to regionally high mean biomass. This work demonstrates the value of coupling mechanistic representations of prey biomass with predator observations to provide insight into how biophysical processes combine to shape species distributions. This will be increasingly important for the robust prediction of species’ responses to rapid system change.

SEAPODYM is a model developed for investigating spatiotemporal dynamics of fish populations under the influence of both fishing and the environment. The model simulates age-structured population dynamics using advection–diffusion–reaction equations describing movement, recruitment, and natural and fishing mortality. The dynamic processes are constrained by environmental data and distributions of prey species. Model parameter estimation using fishing data was implemented earlier based on a maximum likelihood estimation (MLE) approach and adjoint technique. Here, we describe the integration of tagging data into the existing MLE approach with application to skipjack tuna (Katsuwonus pelamis) in the Pacific Ocean. We find that tagging data improve estimates of species habitat parameters and movement rates and hence allow better representation of spatial dynamics of fish population. Due to estimated lower diffusion and higher advection rates, the model predicts less non-observed “cryptic” biomass, which leads to the stock sizes being closer to those estimated by stock assessment models commonly used by tuna commissions.

Climate-driven redistribution of tuna threatens to disrupt the economies of Pacific Small Island Developing States (SIDS) and sustainable management of the world’s largest tuna fishery. Here we show that by 2050, under a high greenhouse gas emissions scenario (RCP 8.5), the total biomass of three tuna species in the waters of ten Pacific SIDS could decline by an average of 13% (range = −5% to −20%) due to a greater proportion of fish occurring in the high seas. The potential implications for Pacific Island economies in 2050 include an average decline in purse-seine catch of 20% (range = −10% to −30%), an average annual loss in regional tuna-fishing access fees of US$90 million (range = −US$40 million to –US$140 million) and reductions in government revenue of up to 13% (range = −8% to −17%) for individual Pacific SIDS. Redistribution of tuna under a lower-emissions scenario (RCP 4.5) is projected to reduce the purse-seine catch from the waters of Pacific SIDS by an average of only 3% (range = −12% to +9%), indicating that even greater reductions in greenhouse gas emissions, in line with the Paris Agreement, would provide a pathway to sustainability for tuna-dependent Pacific Island economies. An additional pathway involves Pacific SIDS negotiating within the regional fisheries management organization to maintain the present-day benefits they receive from tuna, regardless of the effects of climate change on the distribution of the fish. Climate change will alter the distribution of tuna, impacting the economies of Pacific Small Island Developing States. This study finds that greater greenhouse gas emissions will worsen these impacts.

Funding: This work was supported by Fundação para a Ciência eTecnologia (FCT) Azores 2020 Operational Programme and Fundo Regional da Ciência e Tecnologia (FRCT) through research projects TRACE (PTDC/MAR/74071/2006), MAPCET (M2.1.2/F/012/2011) and AWARENESS (PTDC/BIA-BMA/30514/2017), co-funded by FEDER, COMPETE, QREN, POPH, ERDF, ESF, the Lisbon Regional Operational Programme and the Portuguese Ministry for Science and Education. Okeanos R&D Centre is supported by FCT through the strategic fund (UIDB/05634/2020). M.R. was supported by a DRCT doctoral grant (M3.1.a/F/028/2015). S.P.J. was funded by EC funds (SUMMER H2020-EU.3.2.3.1), I.C. by FCT through AWARENESS–(PTDC/BIA-BMA/30514/2017). H.M. acknowledges support by CMAF-CIO (funded by FCT, Portugal, through the projects UID/MAT/00006/2013 and UIDB/04561/2020, respectively). A.P. was supported by AWARENESS project (PTDC/BIA-BMA/30514/2017) and UIDB/50019/2020–I.D.L. and T.A.M. by CEAUL and the LMR ACCURATE project (contract no. N3943019C2176). M.A.S. was funded by FCT and EC funds (IF/00943/2013, SUMMER H2020-EU.3.2.3.1, GA 817806). Animals use varied acoustic signals that play critical roles in their lives. Understanding the function of these signals may inform about key life-history processes relevant for conservation. In the case of fin whales (Balaenoptera physalus), that produce different call types associated with different behaviours, several hypotheses have emerged regarding call function, but the topic still remains in its infancy. Here, we investigate the potential function of two fin whale vocalizations, the song-forming 20-Hz call and the 40-Hz call, by examining their production in relation to season, year and prey biomass. Our results showed that the production of 20-Hz calls was strongly influenced by season, with a clear peak during the breeding months, and secondarily by year, likely due to changes in whale abundance. These results support the reproductive function of the 20-Hz song used as an acoustic display. Conversely, season and year had no effect on variation in 40-Hz calling rates, but prey biomass did. This is the first study linking 40-Hz call activity to prey biomass, supporting the previously suggested food-associated function of this call. Understanding the functions of animal signals can help identifying functional habitats and predict the negative effects of human activities with important implications for conservation. Publisher PDF

Antarctic krill (krill) are important within Southern Ocean ecosystems and support an expanding fishery. Toward understanding krill's response to environmental change, it is necessary to identify regions that support high krill larval production (spawning habitat). We develop a mechanistic model combining thermal and food requirements for krill egg production, with predation pressure post-spawning, to predict regions of high-quality spawning habitat. We optimize our model regionally and generate circumpolar predictions of spawning habitat quality. Our results indicate the southwest Atlantic accounts for almost half of all predicted high-quality spawning habitat. Small-scale management units (SSMUs) around the Antarctic Peninsula had high coverage of high-quality spawning habitat. In contrast, the remaining SSMUs (except around South Georgia) were poorly covered, suggestive of population sinks reliant on input from external sources upstream. This implies strong potential for downstream impacts of fishing in key spawning areas, with implications for management of SSMUs and the krill fishery.

WOS:000529921100010; International audience; Acoustic data are invaluable information sources for characterizing the distribution and abundance of mid-trophic-level organisms (micronekton). These organisms play a pivotal role in the ecosystem as prey of top predators and as predators of low-trophic-level organisms. Although shipboard-ADCP (acoustic Doppler current profiler) acoustic backscatter signal intensity cannot provide an absolute biomass estimate, it may be a useful proxy to investigate variability in the distribution and relative density of micro-nekton. This study used acoustic recordings data spread across 19 years (1999-2017) from 54 ADCP cruises in New Caledonia's subtropical EEZ (exclusive economic zone) to assess seasonal and interannual variabilities and spatial distribution of micro-nekton. The dataset was composed of two different ADCPs: 150 kHz for the first period, followed by 75 kHz for more recent years. We examined the 20-120 m averaged scattering layer. Using the few cruises with concurrent EK60 measurements, we proposed that the backscatter from the ADCPs and 70 kHz EK60 were sufficiently closely linked to allow the use of the backscatter signal from the ADCPs in a combined dataset over the full time series. We then designed a GAMM (generalized additive mixed model) model that takes into account the two ADCP devices as well as temporal variability. After accounting for the effect of the devices, we showed that the acoustic signal was mainly driven by diel vertical migration, season, year, and ENSO (El Nino-Southern Oscillation). In a second step, a consensus model between two statistical approaches (GAMM and SVM) (support vector machine) was constructed, linking the nighttime 20-120 m backscatter to the oceanographic and geographic environment. This model showed that sea surface temperature was the main factor driving backscatter variability in the EEZ, with intensified backscatter during the austral summer (December to May) in the northern part of the EEZ. We showed that acoustic density differed significantly, spatially and temporally from micronekton biomass predicted for the same period by the SEAPODYM-MTL (mid-trophic level) ecosystem model. The seasonal cycle given by ADCP data lagged behind the SEAPODYM-MTL seasonal cycle by around three months. Reasons to explain these differences and further needs in observation and modeling were explored in the discussion. In addition to providing new insights for micronekton dynamics in this EEZ (i.e., the science needed for ecosystem-based fisheries management), the data should help improve our ability to model this key trophic component.

Since 2019, the Copernicus Marine portfolio is providing a new model-based product on Zooplankton and Micronekton, representing the low and mid-trophic levels (LMTL) of the ocean food chain (Global Ocean low and mid trophic levels biomass multi year product: ). Zooplankton are organisms in the size range of less than 1 to a few millimeters (e.g., copepods) constituting prey of all fish larvae and small pelagic fish species (e.g herring, sardines and anchovies). Micronekton are also relatively small but actively swimming organisms such as crustaceans, fish, and cephalopods that are typically about 1 to 10 centimeters in size. Micronekton are prey of large fish and other oceanic predators. They are also predators of fish larvae. Therefore, zooplankton and micronekton distributions are key explanatory variables to understand fish recruitment mechanisms, individual behaviour of satellite tracked individuals of protected species (e.g., marine turtles, seabirds, sharks and marine mammals), and dynamics of large populations of fish species either targeted by fisheries (mackerel, tuna, swordfish, etc.) or strictly controlled in by-catch (e.g., bluefin tuna or sharks). The product includes 2-dimensional (latitude-longitude) maps of biomass for zooplankton and groups of micronekton on a weekly basis from 1998 to 2018 at a 25 km horizontal resolution. It is a model-based estimation of micronekton biomass, relying on the most possible realistic forcings (temperature, currents and primary production) assimilating satellite and in situ data. Continuous progress in the development and validation of these new models and products will help to reduce our knowledge gaps and will also support the Science & Climate sector as zooplankton and micronekton are key to better quantifying the carbon uptake and storage in the ocean, known as the “biological carbon pump”.

SEAPODYM-LMTL is the Lower (zooplankton) and Mid (micronekton) Trophic levels model of the Spatial Ecosystem And POpulation DYnamic Modeling framework. Currently, there is one zooplankton and 6 micronekton functional groups defined according to their vertical behavior and development times. The model is global and spatially explicit with transport described through a system of advection-diffusion equations. The vertical dimension is simplified into three layers -- epipelagic, upper and lower mesopelagic -- defined relatively to the euphotic depth. There are three vertically migrant and three non-migrant functional groups. The model is parsimonious with only a few parameters (6 for the zooplankton and 11 for the micronekton) that control the energy transfer efficiency from the primary production and the mortality and time of development that are linked to the water temperature. A data assimilation framework has been implemented to estimate those parameters. We present briefly the latest results and future challenges of this model. They include the validation of vertical layer boundaries, the first zooplankton and micronekton parameters estimation using existing biomass observations, and the developments needed to use large global datasets of acoustic data.

With INDESO, Indonesia has implemented a system for the monitoring and management of its tuna resources. Despite increasing catch, very few is known about the dynamics and real abundance of tuna species in the Indonesian waters and adjacent oceanic regions. The SEAPODYM model was implemented in an operational chain of production for the Indonesian region to simulate tuna spatial dynamics in realtime. This challenging objective imposed developing a global scale model at coarse resolution to provide initial and boundaries conditions of the regional model. A parameter optimization approach was used to provide the best solution fitting several hundreds of thousand catch observations, over a long historical simulation at coarse resolution. Then downscaling method and regional modelling at high resolution (1/12°x day) were validated to produce realtime and forecast on a weekly basis. The architecture of this application, the approach for its parameterization and some key results are presented and discussed.

In several Pacific Island countries and territories (PICTs), rapid population growth and inadequate management of coastal fish habitats and stocks is causing a gap to emerge between the amount of fish recommended for good nutrition and sustainable harvests from coastal fisheries. The effects of ocean warming and acidification on coral reefs, and the effects of climate change on mangrove and seagrass habitats, are expected to widen this gap. To optimise the contributions of small-scale fisheries to food security in PICTs, adaptations are needed to minimise and fill the gap. Key measures to minimise the gap include community-based approaches to: manage catchment vegetation to reduce sedimentation; maintain the structural complexity of fish habitats; allow landward migration of mangroves as sea level rises; sustain recruitment and production of demersal fish by managing ‘source’ populations; and diversify fishing methods to increase catches of species favoured by climate change. The main adaptions to help fill the gap in fish supply include: transferring some fishing effort from coral reefs to tuna and other large pelagic fish by scaling-up the use of nearshore fish aggregating devices; developing fisheries for small pelagic species; and extending the shelf life of catches by improving post-harvest methods. Modelling the effects of climate change on the distribution of yellowfin tuna, skipjack tuna, wahoo and mahi mahi, indicates that these species are likely to remain abundant enough to implement these adaptations in most PICTs until 2050. We conclude by outlining the policies needed to support the recommended adaptations.

Since the 1970s, South Pacific jack mackerel (Trachurus murphyi) is one of the world’s most important commercial exploited fish stock. The peak in the catch was achieved in the 1990s, after which the catch for all fleets steadily decreased due to strong fishing mortality and potentially unfavourable environmental conditions. An application of the ecosystem and fish population model SEAPODYM was developed for this species in the South Pacific Ocean to determine the extent of environmental and fisheries drivers on the stock dynamics. We combined publicly available fishing data, acoustic biomass estimates and expert knowledge to optimise fish population dynamics parameters (habitats, movements, natural and fishing mortality). Despite a large proportion of missing catch over the simulation period, the model provides realistic distributions of biomass, a good fit-to-data and is in agreement with the literature. The feeding habitat is predicted to be delineated by water temperature between 15°C for the first cohorts and 8.5°C for the oldest and dissolved oxygen concentration above 1.8 ml/L. Optimal spawning temperature is estimated to 15.57°C (S.E.: 0.75°C). The core habitat is predicted off Central Chile which is also the main fishing ground. There are other areas of higher fish concentration east of New Zealand, in the eastern part of the southern convergence and off Peru and northern Chile. However, there is a clear continuity between these different large sub-populations. Fishing is predicted to have by far the highest impact, a result that should be reinforced if all fishing mortality could be included.

WOS:000660310900002; International audience; Ecosystem models forced by future climate simulations outputs from the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulate a substantial decline of tropical marine animal biomass over the course of the 21st century. Regional projections are however far more uncertain because of well-known biases common to most CMIP5 historical simulations that propagate within the food web. Moreover, the model outputs for high trophic levels marine fauna suffer from lack of validation based on in situ data. In this study, we implement a "bias-mitigation" strategy to reduce the physical oceanography and biogeochemical biases simulated by three CMIP5 models under the future RCP8.5 scenario. We force two very different micronekton models with these "bias-mitigated" outputs to infer the future micronekton changes in the Coral Sea: a 3-D deterministic population dynamics model; and a 3-D statistical model based on in situ hydro-acoustic data. These two models forecast a consistent pattern of micronekton abundance changes in the epipelagic layer (0-150 m) by 2100 for three different climate forcing used, with a marked decrease south of 22 degrees S and a smaller increase further north mostly related to temperature and chlorophyll changes. In contrast, changes in the vertical patterns of micronekton predicted by the two models considerably differ in the upper mesopelagic layers (150-450 m) and lower mesopelagic layer (450-1000 m), highlighting the structural sensitivity in model type. Since micronekton are prey of all larger marine predators, those discrepancies in vertical structures of micronekton may hamper our potential to predict how top predators may evolve in the future.

Geo-referenced catch and fishing effort data of the bigeye tuna fisheries in the Indian Ocean over 1952–2014 were analyzed and standardized to facilitate population dynamics modeling studies. During this 62-year historical period of exploitation, many changes occurred both in the fishing techniques and the monitoring of activity. This study includes a series of processing steps used for standardization of spatial resolution, conversion and standardization of catch and effort units, raising of geo-referenced catch into nominal catch level, screening and correction of outliers, and detection of major catchability changes over long time series of fishing data, i.e., the Japanese longline fleet operating in the tropical Indian Ocean. A total of 30 fisheries were finally determined from longline, purse seine and other-gears data sets, from which 10 longline and 4 purse seine fisheries represented 96 % of the whole historical geo-referenced catch. Nevertheless, one-third of total nominal catch is still not included due to a total lack of geo-referenced information and would need to be processed separately, accordingly to the requirements of the study. The geo-referenced records of catch, fishing effort and associated length frequency samples of all fisheries are available at doi:10.1594/PANGAEA.864154.

We present a modelling approach to estimate and predict the dynamics of highly migratory albacore tuna populations in the South Pacific and Atlantic oceans. We use the previously developed model SEAPODYM (Spatial Ecosystem And POpulation DYnamics Model) with its parameter estimation approach based on the maximum likelihood estimation and adjoint method. The model describes temporal and spatial population dynamics using continuous advection-diffusion-reaction equations with an ageing term. We introduce a method to account for seasonal spawning migrations as movements of population density modelled in a Eulerian framework. The aim of this study is to explore the capacity of SEAPODYM to predict complex spatial dynamics of highly migratory species that are consistent with available data and existing knowledge on albacore biology. The geo-referenced fisheries dataset used for model calibration includes effort, catch and length-frequency distributions, constituting the total fishing pressure on the South Pacific albacore population over more than thirty years of exploitation. The model is then validated on the fishing data for Atlantic albacore, thus providing evidence of estimated model parameter invariance with respect to space and time. Given the robustness of the results, the quantitative approach presented here could be used to assist stock assessment and to improve management advice.

An application of the Spatial Ecosystem And POpulation DYnamics Model (SEAPODYM) is developed for the North Atlantic albacore (Thunnus alalunga) population. We investigate the spatiotemporal dynamics of this species, distinguishing the influences of environment and international fishing. Incorporating historical data (1960–2008), a maximum likelihood approach allows the estimation of biological parameters (thermal and oxygen tolerance) and stock spatial distribution varying over time. Juvenile albacore are predicted in warm surface waters, whereas adults inhabit cooler and deeper waters. Positive correlations between juveniles and tropical large-scale climate indices highlight the importance of environmental drivers when estimating stock recruitment biology and spatiotemporal distribution. A methodology is proposed to use SEAPODYM outputs to estimate stock abundance and maximum sustainable yield (MSY). MSY is computed taking into account the spatial dynamics of the species and the environmental variability and is based on a mechanistic modelling of larval recruitment. MSY estimates converge towards an asymptotic value (15 997 t) of the same magnitude than standard stock assessment estimates conducted for the international tuna commission. In agreement with all assessment studies, the stock status is estimated from overfished in the 1990s to recovered in the 2000s. Our results show that the stock recovery results both from fishing actions, including total allowable catches established in the 2000s, and from the beginning of a North Atlantic Oscillation warm phase, leading to more favourable recruitment conditions. Following a parsimonious ecosystemic approach, SEAPODYM offers a faithful and spatially dynamic modelling framework that now includes direct tools for spatialized management advice and for distinction between environmental and fishing effects.

The potential impact of climate change under the IPCC AR4–A2 scenario (close to the AR5-RCP8.5 scenario) on south Pacific albacore tuna (Thunnus alalunga) is simulated with the Spatial Ecosystem And Population Dynamics Model (SEAPODYM) and environmental forcing variables provided by the Earth Climate model IPSL-CM4. Parameters controlling the habitat and dynamics of the population were optimized by fitting the model, using maximum likelihood, to a complete fishing data set for the historical fishing period since 1950. Albacore undertake clear seasonal migrations between feeding and spawning grounds, as evidenced by seasonal catch and size composition changes. This seasonality was well predicted by the SEAPODYM albacore simulations. The total biomass estimate of south Pacific albacore was predicted to have decreased from ~1.8 million tonnes (Mt) at the beginning of industrial fisheries in 1950 to 1.25 Mt in 2006, in good agreement with an independent estimate from stock assessment analysis. A simulation without fishing indicated an equivalent contribution of environmental variability and fishing to the historical decrease of the stock biomass. The parameterized SEAPODYM model was used to project the dynamics of the population until the end of the 21st century with an average fishing effort based on recent years. Under this fishing and climate change scenario, the population was predicted to decrease and to stabilize after 2035 just below 0.8 Mt, i.e., 55% below the initial biomass of 1960. After 2080 however, the trend was reversed when a new spawning ground emerged in the north Tasman Sea. A test simulation highlighted the sensitivity of the model results to projected dissolved oxygen concentration for which there is large uncertainty in the tropical region. A second test simulation showed that genetic selection favouring albacore with preferences for higher optimal ambient spawning temperature would maintain a reduced level of spawning in current tropical spawning areas, suppress the emergence of an area of spawning in the north Tasman Sea and therefore keep stock abundance at low 2035 levels.

Anthropogenic carbon dioxide (CO2) emissions are resulting in increasing absorption of CO2 by the earth׳s oceans, which has led to a decline in ocean pH, a process known as ocean acidification (OA). Evidence suggests that OA may have the potential to affect the distribution and population dynamics of many marine organisms. Early life history processes (e.g. fertilization) and stages (eggs, larvae, juveniles) may be relatively more vulnerable to potential OA impacts, with implications for recruitment in marine populations. The potential impact of OA upon tuna populations has not been investigated, although tuna are key components of pelagic ecosystems and, in the Pacific Ocean, form the basis of one of the largest and most valuable fisheries in the world. This paper reviews current knowledge of potential OA impacts on fish and presents results from a pilot study investigating how OA may affect eggs and larvae of yellowfin tuna, Thunnus albacares. Two separate trials were conducted to test the impact of pCO2 on yellowfin egg stage duration, larval growth and survival. The pCO2 levels tested ranged from present day (~400 μatm) to levels predicted to occur in some areas of the spawning habitat within the next 100 years (

This paper reviews the current knowledge on the ecology of widely distributed pelagic fish stocks in the North Atlantic basin with emphasis on their role in the food web and the factors determining their relationship with the environment. We consider herring (Clupea harengus), mackerel (Scomber scombrus), capelin (Mallotus villosus), blue whiting (Micromesistius poutassou), and horse mackerel (Trachurus trachurus), which have distributions extending beyond the continental shelf and predominantly occur on both sides of the North Atlantic. We also include albacore (Thunnus alalunga), bluefin tuna (Thunnus thynnus), swordfish (Xiphias gladius), and blue marlin (Makaira nigricans), which, by contrast, show large-scale migrations at the basin scale. We focus on the links between life history processes and the environment, horizontal and vertical distribution, spatial structure and trophic role. Many of these species carry out extensive migrations from spawning grounds to nursery and feeding areas. Large oceanographic features such as the North Atlantic subpolar gyre play an important role in determining spatial distributions and driving variations in stock size. Given the large biomasses of especially the smaller species considered here, these stocks can exert significant top-down pressures on the food web and are important in supporting higher trophic levels. The review reveals commonalities and differences between the ecology of widely distributed pelagic fish in the NE and NW Atlantic basins, identifies knowledge gaps and modelling needs that the EURO-BASIN project attempts to address.

Model intercomparison studies in the climate and earth sciences communities have been crucial to build credibility and coherence for future projections. They have quantified variability among models, spurred model development, contrasted within- and among-model uncertainty, assessed model fits to historical data, and provided ensemble projections of future change under specified scenarios. Given the speed and magnitude of anthropogenic change in the marine environment, and consequent effects on food security, biodiversity, marine industries and society, the time is ripe for similar comparisons among models of fisheries and marine ecosystems. Here, we describe the Fisheries and Marine Ecosystem Model Intercomparison Project protocol version 1.0 (Fish-MIP v1.0), part of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), a cross-sectoral network of climate impact modellers. Given the complexity of the marine ecosystem, this class of models has substantial heterogeneity of purpose, scope, theoretical underpinning, processes considered, parameterizations, resolution (grain size) and spatial extent. This heterogeneity reflects the lack of a unified understanding of the marine ecosystem, and implies that the assemblage of all models is more likely to include a greater number of relevant processes than is any single model. The current Fish-MIP protocol is designed to allow these heterogeneous models to be forced with common Earth System Model (ESM) CMIP5 outputs under prescribed scenarios for historic (from 1950s) and future (to 2100) time periods; it will be adapted to CMIP6 in future iterations. It also describes a standardized set of outputs for each participating Fish-MIP model to produce. This enables the broad characterization of differences between, and uncertainties within, models and projections when assessing climate and fisheries impacts on marine ecosystems and the services they provide. The systematic generation, collation and comparison of results from Fish-MIP will inform understanding of the range of plausible changes in marine ecosystems, and improve our capacity to define and convey strengths and weaknesses of model-based advice on future states of marine ecosystems and fisheries. Ultimately, Fish-MIP represents a step towards bringing together the marine ecosystem modelling community to produce consistent ensemble medium- and long-term projections of marine ecosystems.

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 development of the ecosystem approach and models for the management of ocean marine resources requires easy access to standard validated data sets of historical catch data for the main exploited species. They are used to measure the impact of biomass removal by fisheries and to evaluate the models outputs, while the use of a standard data set facilitates models inter-comparison. Unlike standard stock assessment models, new state-of-the-art ecosystem models require geo-referenced fishing data with the highest possible spatial resolution. This study presents an application to the North Atlantic albacore tuna stock with a careful definition and validation of a spatially explicit fishing data set prepared from publicly available sources (ICCAT) for its use in a spatial ecosystem and population dynamics model (SEAPODYM) to provide the first spatially explicit estimate of albacore density in the North Atlantic by life stage. Density distributions together with the fishing data used for the estimates are provided at http://doi.pangaea.de/ (see section Source Data References) ( doi:10.1594/PANGAEA.828115 ; doi:10.1594/PANGAEA.828226 ; doi:10.1594/PANGAEA.828227 ; doi:10.1594/PANGAEA.828228 ; doi:10.1594/PANGAEA.828229 ; doi:10.1594/PANGAEA.828230 ; doi:10.1594/PANGAEA.828231 ; doi:10.1594/PANGAEA.828232 ; doi:10.1594/PANGAEA.828232 ; doi:10.1594/PANGAEA.828233 ; doi:10.1594/PANGAEA.828234 ; doi:10.1594/PANGAEA.828235 ; doi:10.1594/PANGAEA.828236 ; doi:10.1594/PANGAEA.828237 ; doi:10.1594/PANGAEA.828238 ; doi:10.1594/PANGAEA.828168 ; doi:10.1594/PANGAEA.828170 ; doi:10.1594/PANGAEA.828171 ).

Geo-referenced catch and fishing ­effort data of the bigeye tuna fisheries in the Indian Ocean over 1952–2014 were analysed and standardized to facilitate population dynamics modelling studies. During this sixty-two years historical period of exploitation, many changes occurred both in the fishing techniques and the monitoring of activity. This study includes a series of processing steps used for standardization of spatial resolution, conversion and standardization of catch and effort units, raising of geo-referenced catch into nominal catch level, screening and correction of outliers, and detection of major catchability changes over long time series of fishing data, i.e., the Japanese longline fleet operating in the tropical Indian Ocean. A total of thirty fisheries were finally determined from longline, purse seine and other-gears data sets, from which 10 longline and four purse seine fisheries represented 96 % of the whole historical catch. The geo-referenced records of catch, fishing effort and associated length frequency samples of all fisheries are available at doi.pangaea.de/10.1594/PANGAEA.864154.

The four species of tuna that underpin oceanic fisheries in the tropical Pacific (skipjack, yellowfin, bigeye and albacore tuna) deliver great economic and social benefits to Pacific Island countries and territories (PICTs). Domestic tuna fleets and local fish processing operations contribute 3–20 % to gross domestic product in four PICTs and licence fees from foreign fleets provide an average of 3–40 % of government revenue for seven PICTs. More than 12,000 people are employed in tuna processing facilities and on tuna fishing vessels. Fish is a cornerstone of food security for many PICTs and provides 50–90 % of dietary animal protein in rural areas. Several PICTs have plans to (1) increase the benefits they receive from oceanic fisheries by increasing the amount of tuna processed locally, and (2) allocate more tuna for the food security of their rapidly growing populations. The projected effects of climate change on the distribution of tuna in the tropical Pacific Ocean, due to increases in sea surface temperature, changes in velocity of major currents and decreases in nutrient supply to the photic zone from greater stratification, are likely to affect these plans. PICTs in the east of the region with a high dependence on licence fees for government revenue are expected to receive more revenue as tuna catches increase in their exclusive economic zones. On the other hand, countries in the west may encounter problems securing enough fish for their canneries as tuna are redistributed progressively to the east. Changes in the distribution of tuna will also affect the proportions of national tuna catches required for food security. We present priority adaptations to reduce the threats to oceanic fisheries posed by climate change and to capitalise on opportunities.

IPCC-type climate models have produced simulations of the oceanic environment that can be used to drive models of upper trophic levels to explore the impact of climate change on marine resources. We use the Spatial Ecosystem And Population Dynamics Model (SEAPODYM) to investigate the potential impact of Climate change under IPCC A2 scenario on Pacific skipjack tuna (Katsuwonus pelamis). IPCC-type models are still coarse in resolution and can produce significant anomalies, e.g., in water temperature. These limitations have direct and strong effects when modeling the dynamics of marine species. Therefore, parameter estimation experiments based on assimilation of historical fishing data are necessary to calibrate the model to these conditions before exploring the future scenarios. A new simulation based on corrected temperature fields of the A2 simulation from one climate model (IPSL-CM4) is presented. The corrected fields led to a new parameterization close to the one achieved with more realistic environment from an ocean reanalysis and satellite-derived primary production. Projected changes in skipjack population under simple fishing effort scenarios are presented. The skipjack catch and biomass is predicted to slightly increase in the Western Central Pacific Ocean until 2050 then the biomass stabilizes and starts to decrease after 2060 while the catch reaches a plateau. Both feeding and spawning habitat become progressively more favourable in the eastern Pacific Ocean and also extend to higher latitudes, while the western equatorial warm pool is predicted to become less favorable for skipjack spawning.

Relationships between albacore tuna (Thunnus alalunga) longline catch per unit effort (CPUE) and environmental variables from model outputs in New Caledonia’s Exclusive Economic Zone (EEZ) were examined through generalized linear models at a 1° spatial resolution and 10-day temporal resolution. At a regional (EEZ) scale, the study demonstrated that a large part of albacore CPUE variability can be explained by seasonal, interannual and spatial variation of the habitat. Results of the generalized linear models indicated that catch rates are higher than average in the northwestern part of the EEZ at the beginning of the year (January) and during the second half of the year (July–December). In the northwestern region of the EEZ, high CPUEs are associated with waters

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.

The distribution of marine species is often modeled using Eulerian approaches, in which changes to population density or abundance are calculated at fixed locations in space. Conversely, Lagrangian, or individual-based, models simulate the movement of individual particles moving in continuous space, with broader-scale patterns such as distribution being an emergent property of many, potentially adaptive, individuals. These models offer advantages in examining dynamics across spatiotemporal scales and making comparisons with observations from individual-scale data. Here, we introduce and describe such a model, the Individual-based Kinesis, Advection and Movement of Ocean ANimAls model (Ikamoana), which we use to replicate the movement processes of an existing Eulerian model for marine predators (the Spatial Ecosystem and Population Dynamics Model, SEAPODYM). Ikamoana simulates the movement of either individual or groups of animals by physical ocean currents, habitat-dependent stochastic movements (kinesis), and taxis movements representing active searching behaviours. Applying our model to Pacific skipjack tuna (Katsuwonus pelamis), we show that it accurately replicates the evolution of density distribution simulated by SEAPODYM with low time-mean error and a spatial correlation of density that exceeds 0.96 at all times. We demonstrate how the Lagrangian approach permits easy tracking of individuals’ trajectories for examining connectivity between different regions, and show how the model can provide independent estimates of transfer rates between commonly used assessment regions. In particular, we find that retention rates in most assessment regions are considerably smaller (up to a factor of 2) than those estimated by this population of skipjack’s primary assessment model. Moreover, these rates are sensitive to ocean state (e.g. El Nino vs La Nina) and so assuming fixed transfer rates between regions may lead to spurious stock estimates. A novel feature of the Lagrangian approach is that individual schools can be tracked through time, and we demonstrate that movement between two assessment regions at broad temporal scales includes extended transits through other regions at finer-scales. Finally, we discuss the utility of this modeling framework for the management of marine reserves, designing effective monitoring programmes, and exploring hypotheses regarding the behaviour of hard-to-observe oceanic animals.

The modeling of mid-trophic organisms of the pelagic ecosystem is a critical step in linking the coupled physical–biogeochemical models to population dynamics of large pelagic predators. Here, we provide an example of a modeling approach with definitions of several pelagic mid-trophic functional groups. This application includes six different groups characterized by their vertical behavior, i.e., occurrence of diel migration between epipelagic, mesopelagic and bathypelagic layers. Parameterization of the dynamics of these components is based on a temperature-linked time development relationship. Estimated parameters of this relationship are close to those predicted by a model based on a theoretical description of the allocation of metabolic energy at the cellular level, and that predicts a species metabolic rate in terms of its body mass and temperature. Then, a simple energy transfer from primary production is used, justified by the existence of constant slopes in log–log biomass size spectrum relationships. Recruitment, ageing, mortality and passive transport with horizontal currents, taking into account vertical behavior of organisms, are modeled by a system of advection–diffusion-reaction equations. Temperature and currents averaged in each vertical layer are provided independently by an Ocean General Circulation Model and used to drive the mid-trophic level (MTL) model. Simulation outputs are presented for the tropical Pacific Ocean to illustrate how different temperature and oceanic circulation conditions result in spatial and temporal lags between regions of high primary production and regions of aggregation of mid-trophic biomass. Predicted biomasses are compared against available data. Data requirements to evaluate outputs of these types of models are discussed, as well as the prospects that they offer both for ecosystem models of lower and upper trophic levels.