Spatiotemporal analysis of micronekton biomass at the mouth of the River Plate

In the pelagic foodweb, micronekton at the mid-trophic level (MTL) are one of the lesser known components of the ocean ecosystem despite being a major driver of the spatial dynamics of their predators, of which many are exploited species (e.g. tunas). The Spatial Ecosystem and Population Dynamics Model is one modelling approach that includes a representation of the spatial dynamics of several epi- and mesopelagic MTL functional groups. The dynamics of these groups are driven by physical (temperature and currents) and biogeochemical (primary production, euphotic depth) variables. A key issue to address is the parameterization of the energy transfer from the primary production to these functional groups. We present a method using in situ acoustic data to estimate the parameters with a maximum likelihood estimation approach. A series of twin experiments conducted to test the behaviour of the model suggested that in the ideal case, that is, with an environmental forcing perfectly simulated and biomass estimates directly correlated with the acoustic signal, a minimum of 200 observations over several time steps at the resolution of the model is needed to estimate the parameter values with a minimum error. A transect of acoustic backscatter at 38 kHz collected during scientific cruises north of Hawaii allowed a first illustration of the approach with actual data. A discussion followed regarding the various sources of uncertainties associated with the use of acoustic data in micronekton biomass.

Quantitative modelling of the spatial dynamics of South Pacific and Atlantic albacore tuna populations

A spatial ecosystem and populations dynamics model (SEAPODYM) – Modeling of tuna and tuna-like populations

In habitat modelling, environmental variables are assumed to be proxies of lower trophic levels distribution and by extension, of marine top predator distributions. More proximal variables, such as potential prey fields, could refine relationships between top predator distributions and their environment. In situ data on prey distributions are not available over large spatial scales but, a numerical model, the Spatial Ecosystem And POpulation DYnamics Model (SEAPODYM), provides simulations of the biomass and production of zooplankton and six functional groups of micronekton at the global scale. Here, we explored whether generalised additive models fitted to simulated prey distribution data better predicted deep-diver densities (here beaked whales Ziphiidae and sperm whales Physeter macrocephalus) than models fitted to environmental variables. We assessed whether the combination of environmental and prey distribution data would further improve model fit by comparing their explanatory power. For both taxa, results were suggestive of a preference for habitats associated with topographic features and thermal fronts but also for habitats with an extended euphotic zone and with large prey of the lower mesopelagic layer. For beaked whales, no SEAPODYM variable was selected in the best model that combined the two types of variables, possibly because SEAPODYM does not accurately simulate the organisms on which beaked whales feed on. For sperm whales, the increase model performance was only marginal. SEAPODYM outputs were at best weakly correlated with sightings of deep-diving cetaceans, suggesting SEAPODYM may not accurately predict the prey fields of these taxa. This study was a first investigation and mostly highlighted the importance of the physiographic variables to understand mechanisms that influence the distribution of deep-diving cetaceans. A more systematic use of SEAPODYM could allow to better define the limits of its use and a development of the model that would simulate larger prey beyond 1,000 m would probably better characterise the prey of deep-diving cetaceans.

In habitat modelling, environmental variables are assumed to be proxies of lower trophic levels distribution and by extension, of marine top predator distributions. More proximal variables, such as potential prey fields, could refine relationships between top predator distributions and their environment. In situ data on prey distributions are not available over large spatial scales but, a numerical model, the Spatial Ecosystem And POpulation DYnamics Model (SEAPODYM), provides simulations of the biomass and production of zooplankton and six functional groups of micronekton at the global scale. Here, we explored whether generalised additive models fitted to simulated prey distribution data better predicted deep-diver densities (here beaked whales Ziphiidae and sperm whales Physeter macrocephalus) than models fitted to environmental variables. We assessed whether the combination of environmental and prey distribution data would further improve model fit by comparing their explanatory power. For both taxa, results were suggestive of a preference for habitats associated with topographic features and thermal fronts but also for habitats with an extended euphotic zone and with large prey of the lower mesopelagic layer. For beaked whales, no SEAPODYM variable was selected in the best model that combined the two types of variables, possibly because SEAPODYM does not accurately simulate the organisms on which beaked whales feed on. For sperm whales, the increase model performance was only marginal. SEAPODYM outputs were at best weakly correlated with sightings of deep-diving cetaceans, suggesting SEAPODYM may not accurately predict the prey fields of these taxa. This study was a first investigation and mostly highlighted the importance of the physiographic variables to understand mechanisms that influence the distribution of deep-diving cetaceans. A more systematic use of SEAPODYM could allow to better define the limits of its use and a development of the model that would simulate larger prey beyond 1,000 m would probably better characterise the prey of deep-diving cetaceans.

Large-scale, no-take marine protected areas (MPAs) have been established in several locations in the Pacific and expansion of such areas to reach 30% of the ocean area is actively promoted in some quarters. Justification for the establishment of large oceanic MPAs often includes the conservation benefits that they would bring for tuna stocks, which are the subject of important commercial fisheries in the Pacific. The aim of this paper was to evaluate the conservation efficacy of an existing MPA, the Phoenix Islands Protected Area (PIPA) and a series of large hypothetical MPAs each constituting approximately 33% of the western and central Pacific Ocean, for two important and contrasting tuna species, skipjack and bigeye tuna. The evaluation was conducted by comparing control and counterfactual simulations in which the estimated population and fishery dynamics of the species were modelled using a high-resolution modelling framework known as SEAPODYM (Spatial Ecosystem And Population DYnamics Model). We found that stock-wide conservation benefits of the PIPA for these species, assuming that total fishing effort is maintained, to be weak to non-existent, and only modest increases in spawning biomass of both species occur within and in the near vicinity of the PIPA itself. For the larger 33% hypothetical MPAs, changes in stock-wide spawning biomass were estimated to be -0.1% to +5.8% for skipjack tuna and +4.8% to +12.0% for bigeye tuna. Conservation efficacy of MPAs for species such as tropical tunas is limited by their wide larval dispersal and high mobility of later life stages, which spatially dissipate the protective effects of MPAs. Also, the displacement of fishing effort from MPAs to areas remaining open can have negative consequences for stocks and fisheries performance in those areas. We conclude that large oceanic MPAs are not likely to be effective frontline management tools for tropical tunas and other species having similar life history characteristics.

An individual-based model of skipjack tuna (Katsuwonus pelamis) movement in the tropical Pacific ocean

AimUnderstanding the environmental drivers of movement and habitat use of highly migratory marine species is crucial to implement appropriate management and conservation measures. However, this requires quantitative information on their spatial and temporal presence, which is limited in the high seas. Here, we aimed to gain insights of the essential habitats of three baleen whale species around the mid‐North Atlantic (NA) region, linking their large‐scale movements with information on oceanographic and biological processes.LocationMid‐NA Ocean.MethodsWe present the first study combining data from 31 satellite tracks of baleen whales (15, 10 and 6 from fin, blue and sei whales, respectively) from March to July (2008–2016) with data on remotely sensed oceanography and mid‐ and lower trophic level biomass derived from the spatial ecosystem and population dynamics model (SEAPODYM). A Bayesian switching state‐space model was applied to obtain regular tracks and correct for location errors, and pseudo‐absences were created through simulated positions using a correlated random walk model. Based on the tracks and pseudo‐absences, we applied generalized additive mixed models (GAMMs) to determine the probability of occurrence and predict monthly distributions.ResultsThis study provides the most detailed research on the spatio‐temporal distribution of baleen whales in the mid‐NA, showing how dynamic biophysical processes determine their habitat preference. Movement patterns were mainly influenced by the interaction of temperature and the lower trophic level biomass; however, this relationship differed substantially among species. Best‐fit models suggest that movements of whales migrating towards more productive areas in northern latitudes were constrained by depth and eddy kinetic energy.Main conclusionsThese novel insights highlight the importance of integrating telemetry data with spatially explicit prey models to understand which factors shape the movement patterns of highly migratory species across large geographical scales. In addition, our outcomes could contribute to inform management of anthropogenic threats to baleen whales in sparsely surveyed region.

漁業-資源-環境の関係を探る―海洋生態系・空間資源動態モデル SEAPODYM によるアプローチ―

Robust prediction of population responses to changing environments requires the integration of factors controlling population dynamics with processes affecting distribution. This is true everywhere but especially in polar pelagic environments. Biological cycles for many polar species are synchronised to extreme seasonality, while their distributions may be influenced by both the prevailing oceanic circulation and sea-ice distribution. Antarctic krill (krill, Euphausia superba) is one such species exhibiting a complex life history that is finely tuned to the extreme seasonality of the Southern Ocean. Dependencies on the timing of optimal seasonal conditions have led to concerns over the effects of future climate on krill’s population status, particularly given the species’ important role within Southern Ocean ecosystems. Under a changing climate, established correlations between environment and species may breakdown. Developing the capacity for predicting krill responses to climate change therefore requires methods that can explicitly consider the interplay between life history, biological conditions, and transport. The Spatial Ecosystem And Population Dynamics Model (SEAPODYM) is one such framework that integrates population and general circulation modelling to simulate the spatial dynamics of key organisms. Here, we describe a modification to SEAPODYM, creating a novel model – KRILLPODYM – that generates spatially resolved estimates of krill biomass and demographics. This new model consists of three major components: (1) an age-structured population consisting of five key life stages, each with multiple age classes, which undergo age-dependent growth and mortality, (2) six key habitats that mediate the production of larvae and life stage survival, and (3) spatial dynamics driven by both the underlying circulation of ocean currents and advection of sea-ice. We present the first results of KRILLPODYM, using published deterministic functions of population processes and habitat suitability rules. Initialising from a non-informative uniform density across the Southern Ocean our model independently develops a circumpolar population distribution of krill that approximates observations. The model framework lends itself to applied experiments aimed at resolving key population parameters, life-stage specific habitat requirements, and dominant transport regimes, ultimately informing sustainable fishery management.

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.

Modelling the impact of climate change on South Pacific albacore tuna

The Sangihe Islands is located in the Republic of Indonesia Fisheries Management Area (WPPNRI) 716, which has an area of about 52.5 million hectares. The potential productions for small and large pelagic fish in WPP NRI 716 are 332,635 tons/year and 181,491 tons/year, respectively, with utilization rates of 0.48 and 0.63. The dominant fish species caught were skipjack, mackerel, yellowfin tuna, and anchovies. In order to estimate fish biomass around the Sangihe Islands waters, acoustic data has been collected in several locations using a 120 kHz BIOSONIC DT-X echo sounder mounted on fishing vessels with purse seine gear. In addition, an analysis of the data from the results of the Spatial Ecosystem and Population Dynamics Model (SEAPODYM) from INDESO Project was also carried out. This model has a resolution of 1/12° and applied in Indonesian waters for 3 types of tuna, namely yellowfin, bigeye, and skipjack. Acoustic data showed that the largest fish biomass along the survey tracks was found at depths between 126 and 150 m, with a total biomass of 21,418 tons. Meanwhile, from the model results, it was found that skipjack biomass was the largest. The average biomass around the Sangihe Islands waters was around 1,340 tons.

Parameter estimation for basin-scale ecosystem-linked population models of large pelagic predators: Application to skipjack tuna

The North Pacific Subtropical Frontal Zone (STFZ) seasonally aggregates economically important fish and protected species. The aggregation of top predators is hypothesized to be a response to convergent flow at the prominent thermohaline Subtropical Front (STF) in the STFZ and a sharp northward increase in primary productivity, the Transition Zone Chlorophyll Front (TZCF), which is thought to link primary productivity to top predators via secondary and tertiary consumers. Given existing data gaps in our knowledge on forage biomass, distribution, and composition in the area, characteristics of micronekton, forage for top predators, were investigated using in situ multi-frequency active acoustics from three springtime shipboard surveys conducted along the 158°W meridional. The effects of STF and TZCF on micronekton was accessed using in situ CTD profiles. Results of this study showed a significant positive effect of the STF on micronekton biomass. The acoustic data implied that the STF also acted as a boundary for the distribution of micronekton with differing taxonomic composition from south to its north. The TZCF, as well as Chl-a concentrations, did not show a significant effect on micronekton relative biomass or composition that might be due to effects of larger-scale variability masked in the in situ data. Contrary to expectation, significantly higher relative micronekton biomass was associated with higher temperatures, the mechanisms of which still need to be determined.