Large-scale distribution of tuna species in a warming ocean

Suitable habitat shifts and ecological niche overlay assessments among benthic Oplegnathus species in response to climate change

Climate change has had a significant impact on many marine organisms. To investigate the effects of environmental changes on deep-water benthic fishes, we selected the genus Oplegnathus and applied species distribution modeling and ecological niche modeling. From the last glacial maximum to the present, the three Oplegnathus species (O. conwayi, O. robinsoni, and O. peaolopesi) distributed in the Cape of Good Hope region of southern Africa experienced fitness zone fluctuations of 39.9%, 13%, and 5.7%, respectively. In contrast, O. fasciatus and O. punctatus, which were primarily distributed in the western Pacific Ocean, had fitness zone fluctuations of -6.5% and 11.7%, respectively. Neither the O. insignis nor the O. woodward varied by more than 5% over the period. Under future environmental conditions, the range of variation in fitness zones for the three southern African Oplegnathus species was expected to be between -30.8% and -26.5%, while the range of variation in fitness zones for the two western Pacific stonefish species was expected to remain below 13%. In addition, the range of variation in the fitness zones of the O. insignis was projected to be between -2.3% and 7.1%, and the range of variation in the fitness zones of the O. woodward is projected to be between -5.7% and -2%. The results indicated that O. fasciatus and O. punctatus had a wide distribution and high expansion potential, while Oplegnathus species might have originated in western Pacific waters. Our results showed that benthic fishes were highly adaptable to extreme environments, such as the last glacial maximum. The high ecological niche overlap between Oplegnathus species in the same region suggested that they competed with each other. Future research could explore the impacts of environmental change on marine organisms and make conservation and management recommendations.

Spatial distribution models for the four commercial tuna in the sea of maritime continent using multi-sensor remote sensing and maximum entropy

The dynamic of marine environmental parameters affects the distribution of commercial tuna in the sea of the maritime continent. Hence, the objectives of this study are to develop spatial distribution models for the four main tuna species in the Maritime continent's sea with reasonable accuracy, identify their correlation with marine environmental parameters, and investigate areas of interaction between those tuna species. The study develops the distribution models for albacore (Thunnus alalunga), bigeye (Thunnus obesus), yellowfin (Thunnus albacares), and skipjack (Katsuwonus pelamis) tuna species, utilizing multi-sensor satellite remote sensing and maximum entropy. The results show models have good performance, focusing on environmental factors such as sea surface temperature (SST), chlorophyll-a (CHL), and sea surface height anomalies (SSHA), combined with eddy kinetic energy (EKE). Seasonal variations in potential tuna habitats are revealed, emphasizing the influence of those marine environmental conditions. From December to May, the four commercial tuna species were distributed in conditions characterized by SST of 26-31.5 °C, CHL levels of 0-3 mg/l, SSHA of -0.3 to 0.2 m, and EKE of 0-1 m2/s2, while from June to November, they experienced SST of 23-31 °C, CHL levels of 0-4 mg/l, SSHA of -0.5 to 0.3 m, and EKE of 0-1.1 m2/s2. The spatial persistence of the four tuna species emerged mainly around the south sea of Java, with skipjack being the most common species found in the sea of the maritime continent. With sufficient and evenly distributed tuna presence records, the results indicate the potential for extrapolation beyond the training data to estimate habitat suitability for the four commercial tuna distributions. The results also suggest potential competition between tuna species sharing ecological niches and highlight possible overlapping areas where different tuna species interact with the same fishing gear.

Unidirectional trans-Atlantic gene flow and a mixed spawning area shape the genetic connectivity of Atlantic bluefin tuna

The commercially important Atlantic bluefin tuna (Thunnus thynnus), a large migratory fish, has experienced notable recovery aided by accurate resource assessment and effective fisheries management efforts. Traditionally, this species has been perceived as consisting of eastern and western populations, spawning respectively in the Mediterranean Sea and the Gulf of Mexico, with mixing occurring throughout the Atlantic. However, recent studies have challenged this assumption by revealing weak genetic differentiation and identifying a previously unknown spawning ground in the Slope Sea used by Atlantic bluefin tuna of uncertain origin. To further understand the current and past population structure and connectivity of Atlantic bluefin tuna, we have assembled a unique dataset including thousands of genome-wide single-nucleotide polymorphisms (SNPs) from 500 larvae, young of the year and spawning adult samples covering the three spawning grounds and including individuals of other Thunnus species. Our analyses support two weakly differentiated but demographically connected ancestral populations that interbreed in the Slope Sea. Moreover, we also identified signatures of introgression from albacore (Thunnus alalunga) into the Atlantic bluefin tuna genome, exhibiting varied frequencies across spawning areas, indicating strong gene flow from the Mediterranean Sea towards the Slope Sea. We hypothesize that the observed genetic differentiation may be attributed to increased gene flow caused by a recent intensification of westward migration by the eastern population, which could have implications for the genetic diversity and conservation of western populations. Future conservation efforts should consider these findings to address potential genetic homogenization in the species.

Thermal sensitivity of field metabolic rate predicts differential futures for bluefin tuna juveniles across the Atlantic Ocean

Changing environmental temperatures impact the physiological performance of fishes, and consequently their distributions. A mechanistic understanding of the linkages between experienced temperature and the physiological response expressed within complex natural environments is often lacking, hampering efforts to project impacts especially when future conditions exceed previous experience. In this study, we use natural chemical tracers to determine the individual experienced temperatures and expressed field metabolic rates of Atlantic bluefin tuna (Thunnus thynnus) during their first year of life. Our findings reveal that the tuna exhibit a preference for temperatures 2-4 °C lower than those that maximise field metabolic rates, thereby avoiding temperatures warm enough to limit metabolic performance. Based on current IPCC projections, our results indicate that historically-important spawning and nursery grounds for bluefin tuna will become thermally limiting due to warming within the next 50 years. However, limiting global warming to below 2 °C would preserve habitat conditions in the Mediterranean Sea for this species. Our approach, which is based on field observations, provides predictions of animal performance and behaviour that are not constrained by laboratory conditions, and can be extended to any marine teleost species for which otoliths are available.

Building use-inspired species distribution models: Using multiple data types to examine and improve model performance

Species distribution models (SDMs) are becoming an important tool for marine conservation and management. Yet while there is an increasing diversity and volume of marine biodiversity data for training SDMs, little practical guidance is available on how to leverage distinct data types to build robust models. We explored the effect of different data types on the fit, performance and predictive ability of SDMs by comparing models trained with four data types for a heavily exploited pelagic fish, the blue shark (Prionace glauca), in the Northwest Atlantic: two fishery dependent (conventional mark-recapture tags, fisheries observer records) and two fishery independent (satellite-linked electronic tags, pop-up archival tags). We found that all four data types can result in robust models, but differences among spatial predictions highlighted the need to consider ecological realism in model selection and interpretation regardless of data type. Differences among models were primarily attributed to biases in how each data type, and the associated representation of absences, sampled the environment and summarized the resulting species distributions. Outputs from model ensembles and a model trained on all pooled data both proved effective for combining inferences across data types and provided more ecologically realistic predictions than individual models. Our results provide valuable guidance for practitioners developing SDMs. With increasing access to diverse data sources, future work should further develop truly integrative modeling approaches that can explicitly leverage the strengths of individual data types while statistically accounting for limitations, such as sampling biases.

Industrial fisheries have reversed the carbon sequestration by tuna carcasses into emissions

To limit climate warming to 2°C above preindustrial levels, most economic sectors will need a rapid transformation toward a net zero emission of CO2 . Tuna fisheries is a key food production sector that burns fossil fuel to operate but also reduces the deadfall of large-bodied fish so the capacity of this natural carbon pump to deep sea. Yet, the carbon balance of tuna populations, so the net difference between CO2 emission due to industrial exploitation and CO2 sequestration by fish deadfall after natural mortality, is still unknown. Here, by considering the dynamics of two main contrasting tuna species (Katsuwonus pelamis and Thunnus obesus) across the Pacific since the 1980s, we show that most tuna populations became CO2 sources instead of remaining natural sinks. Without considering the supply chain, the main factors associated with this shift are exploitation rate, transshipment intensity, fuel consumption, and climate change. Our study urges for a better global ocean stewardship, by curbing subsidies and limiting transshipment in remote international waters, to quickly rebuild most pelagic fish stocks above their target management reference points and reactivate a neglected carbon pump toward the deep sea as an additional Nature Climate Solution in our portfolio. Even if this potential carbon sequestration by surface unit may appear low compared to that of coastal ecosystems or tropical forests, the ocean covers a vast area and the sinking biomass of dead vertebrates can sequester carbon for around 1000 years in the deep sea. We also highlight the multiple co-benefits and trade-offs from engaging the industrial fisheries sector with carbon neutrality.

Widespread habitat loss and redistribution of marine top predators in a changing ocean

The Northwest Atlantic Ocean and Gulf of Mexico are among the fastest warming ocean regions, a trend that is expected to continue through this century with far-reaching implications for marine ecosystems. We examine the distribution of 12 highly migratory top predator species using predictive models and project expected habitat changes using downscaled climate models. Our models predict widespread losses of suitable habitat for most species, concurrent with substantial northward displacement of core habitats >500 km. These changes include up to >70% loss of suitable habitat area for some commercially and ecologically important species. We also identify predicted hot spots of multi-species habitat loss focused offshore of the U.S. Southeast and Mid-Atlantic coasts. For several species, the predicted changes are already underway, which are likely to have substantial impacts on the efficacy of static regulatory frameworks used to manage highly migratory species. The ongoing and projected effects of climate change highlight the urgent need to adaptively and proactively manage dynamic marine ecosystems.

A century of mercury: Ecosystem-wide changes drive increasing contamination of a tropical seabird species in the South Atlantic Ocean

Mercury (Hg) is a highly toxic metal that adversely impacts human and wildlife health. The amount of Hg released globally in the environment has increased steadily since the Industrial Revolution, resulting in growing contamination in biota. Seabirds have been extensively studied to monitor Hg contamination in the world's oceans. Multidecadal increases in seabird Hg contamination have been documented in polar, temperate and subtropical regions, whereas in tropical regions they are largely unknown. Since seabirds accumulate Hg mainly from their diet, their trophic ecology is fundamental in understanding their Hg exposure over time. Here, we used the sooty tern (Onychoprion fuscatus), the most abundant tropical seabird, as bioindicator of temporal variations in Hg transfer to marine predators in tropical ecosystems, in response to trophic changes and other potential drivers. Body feathers were sampled from 220 sooty terns, from museum specimens (n = 134) and free-living birds (n = 86) from Ascension Island, in the South Atlantic Ocean, over 145 years (1876-2021). Chemical analyses included (i) total- and methyl-Hg, and (ii) carbon (δ¹³C) and nitrogen (δ¹⁵N) stable isotopes, as proxies of foraging habitat and trophic position, respectively, to investigate the relationship between trophic ecology and Hg contamination over time. Despite current regulations on its global emissions, mean Hg concentrations were 58.9% higher in the 2020s (2.0 μg g^-1, n = 34) than in the 1920s (1.2 μg g^-1, n = 107). Feather Hg concentrations were negatively and positively associated with δ¹³C and δ¹⁵N values, respectively. The sharp decline of 2.9 ‰ in δ¹³C values over time indicates ecosystem-wide changes (shifting primary productivity) in the tropical South Atlantic Ocean and can help explain the observed increase in terns' feather Hg concentrations. Overall, this study provides invaluable information on how ecosystem-wide changes can increase Hg contamination of tropical marine predators and reinforces the need for long-term regulations of harmful contaminants at the global scale.

Temporal change in functional rarity in marine fish assemblages

Recent research has uncovered rapid compositional and structural reorganization of ecological assemblages, with these changes particularly evident in marine ecosystems. However, the extent to which these ongoing changes in taxonomic diversity are a proxy for change in functional diversity is not well understood. Here we focus on trends in rarity to ask how taxonomic rarity and functional rarity covary over time. Our analysis, drawing on 30 years of scientific trawl data, reveals that the direction of temporal shifts in taxonomic rarity in two Scottish marine ecosystems is consistent with a null model of change in assemblage size (i.e. change in numbers of species and/or individuals). In both cases, however, functional rarity increases, as assemblages become larger, rather than showing the expected decrease. These results underline the importance of measuring both taxonomic and functional dimensions of diversity when assessing and interpreting biodiversity change.

Climate Change and Dispersal Ability Jointly Affects the Future Distribution of Crocodile Lizards

Crocodile lizards (Shinisaurus crocodilurus) are an endangered, 'living fossil' reptile from a monophyletic family and therefore, a high priority for conservation. We constructed climatic models to evaluate the potential impact of climate change on the distribution of crocodile lizards for the period 2000 to 2100 and determined the key environmental factors that affect the dispersal of this endangered species. For the construction of climatic models, we used 985 presence-only data points and 6 predictor variables which showed excellent performance (AUC = 0.974). The three top-ranked factors predicting crocodile lizard distribution were precipitation of the wettest month (bio13, 37.1%), precipitation of the coldest quarter (bio19, 17.9%), and temperature seasonality (bio4, 14.3%). Crocodile lizards were, just as they are now, widely distributed in the north of Guangdong Province in China and Quảng Ninh Province in Vietnam at the last glacial maximum (LGM). Since the LGM, there has been an increase in suitable habitats, particularly in east-central Guangxi Province, China. Under future global warming scenarios, the potential habitat for crocodile lizards is expected to decrease significantly in the next 100 years. Under the most optimistic scenario, only 7.35% to 6.54% of suitable habitat will remain, and under the worst climatic scenario, only 8.34% to 0.86% of suitable habitat will remain. Models for no dispersal and limited dispersal showed that all crocodile lizards would lose habitat as temperatures increase. Our work contributes to an increased understanding of the current and future spatial distribution of the species, supporting practical management and conservation plans.

Fishing for the Microbiome of Tropical Tuna

Although tunas represent a significant part of the global fish economy and a major nutritional resource worldwide, their microbiome still remains poorly documented. Here, we conducted an analysis of the taxonomic composition of the bacterial communities inhabiting the gut, skin, and liver of two most consumed tropical tuna species (skipjack and yellowfin), from individuals caught in the Atlantic and Indian oceans. We hypothesized that each organ harbors a specific microbial assemblage whose composition might vary according to different biotic (sex, species) and/or abiotic (environmental) factors. Our results revealed that the composition of the tuna microbiome was totally independent of fish sex, regardless of the species and ocean considered. Instead, the main determinants of observed diversity were (i) tuna species for the gut and (ii) sampling site for the skin mucus layer and (iii) a combination of both parameters for the liver. Interestingly, 4.5% of all amplicon sequence variants (ASV) were shared by the three organs, highlighting the presence of a core-microbiota whose most abundant representatives belonged to the genera Mycoplasma, Cutibacterium, and Photobacterium. Our study also revealed the presence of a unique and diversified bacterial assemblage within the tuna liver, comprising a substantial proportion of potential histamine-producing bacteria, well known for their pathogenicity and their contribution to fish poisoning cases. These results indicate that this organ is an unexplored microbial niche whose role in the health of both the host and consumers remains to be elucidated.

Effects of decadal climate variability on spatiotemporal distribution of Indo-Pacific yellowfin tuna population

Spatial variations in tuna population and abundance are strongly linked to large-scale climate fluctuations, such as the Pacific decadal oscillation (PDO) and Atlantic multidecadal oscillation (AMO). However, the mechanisms underlying the association of climate indices with yellowfin tuna (YFT) abundance and habitat preference remain unclear. We analysed long-term longline fishery data for YFT and oceanic climate variability index data for 1971–2018. The standardized catch per unit effort (CPUE) of Indo-Pacific Ocean YFT was higher during negative AMO and positive PDO phases. In tropical Pacific Ocean, the trend of YFT habitat preference exhibited seesaw patterns because of the distinct environmental factors influenced by the PDO phase. The PDO changed the environmental parameters throughout the tropical Indian Ocean such that the habitat preference of YFT remained consistent throughout. However, the variations in habitat suitability did not correspond to the distribution or standardized CPUE of YFT throughout the Pacific Ocean during AMO events. Moreover, the changes in habitat suitability had a positive periodicity of 8–16 years with AMO in the Indian Ocean, but revealed opposite trends with the distribution or standardized CPUE of YFT. Our results provide sufficient information to distinguish the variations between PDO phase changing and YFT standardized CPUE/ habitat preference. Furthermore, the AMO phase shift period 60–100 years longer than that of the PDO (20–30 years), and models employing time series of fishery and environmental data must be extended the time period of our study to make the AMO match the fishery data more complete.

Temporal Dynamics of the Goose Habitat in the Middle and Lower Reaches of the Yangtze River

The middle and lower reaches of the Yangtze River are the most important areas for geese to overwinter in the East Asian–Australasian Flyway, where about 180,000 geese fly to overwinter each year. Over the past 20 years, the region has experienced extensive and rapid land cover changes that may have exceeded the adaptability of geese, and have led to suitable goose habitat area loss, thereby, reducing the stability of the geese population. In order to identify the suitable goose habitat areas in this region, based on ensemble modeling and satellite tracking data, in this study, we simulated the spatial distribution changes in the suitable goose habitat areas over the past 20 years. The results showed that the suitable goose habitat areas had suffered varying degrees of loss, among which, the lesser white-fronted goose had the greatest suitable goose habitat area loss of over 50%. Moreover, we found that wetlands, lakes, and floodplains were the key components of suitable goose habitat areas, and the categories (land use) showed significant differences in different periods (p < 0.01). This may be one of the main reasons for the decrease in suitable goose habitat areas. The results of this study provide an important reference for the adaptive management and protection of geese in the middle and lower reaches of the Yangtze River.

Assessing the exposure risk of large pelagic fish to oil spills scenarios in the deep waters of the Gulf of Mexico

Exposure risk is assessed based on modeling suitable habitat of large pelagic fish and oil spill scenarios originating at three wells located in the western GM's deep waters. Since the fate of the oil depends on the oceanographic conditions present during the accident, as well as the magnitude and duration of the spill, which are not known a priori, the scenarios used are a statistical representation of the area in which oil spilled from the well could be found, given all possible outcomes. The ecological vulnerability assessment identified a subset of bony fish with low-medium vulnerability and elasmobranchs with medium-high vulnerability. The oiling probability and exposure risk of both bony fish and elasmobranchs hotspots vary by well analyzed. Thus, these results provide essential information for a risk management plan for the assessed species and others with economic or conservation importance distributed in the GM and worldwide.

The concentration and health risk assessment of radionuclides in the muscle of tuna fish: A worldwide systematic review and meta-analysis

Exposure to radionuclides, especially in food, can endanger the health of consumers. In this study, a systematic review and meta-analysis were performed regarding the concentration of radionuclides in tuna fish muscle. International databases including PubMed, Scopus, and Embase were searched to find articles regarding the concentration of radionuclides in tuna fish muscle from 1 January 2000 to 20 February 2021. The lowest and highest concentration of radionuclides was related to Caesium-137 (¹³⁷Cs) and Potassium-40 (⁴ K), respectively. The rank order of radionuclides based on their pooled concentration was ⁴ K (370.157 Bq/kg) > ²¹⁰Po Polonium-210 (26.312 Bq/kg) > ²¹⁰Pb (5.339 Bq/kg) > ²²⁶Ra (4.005 Bq/kg) > ¹³⁷Cs (0.415 Bq/kg). The health risk assessment based on annual effective dose indicates that consumers are at the safe range of health risk (H < 1 mSv/y). The continuous monitoring concentration of radionuclides in seafood and health risk assessment should be recommended.

Fishing trip cost modeling using generalized linear model and machine learning methods - A case study with longline fisheries in the Pacific and an application in Regulatory Impact Analysis

Fishing trip cost is an important element in evaluating economic performance of fisheries, assessing economic effects from fisheries management alternatives, and serving as input for ecosystem and bioeconomic modeling. However, many fisheries have limited trip-level data due to low observer coverage. This article introduces a generalized linear model (GLM) utilizing machine learning (ML) techniques to develop a modeling approach to estimate the functional forms and predict the fishing trip costs of unsampled trips. GLM with Lasso regularization and ML cross-validation of model are done simultaneously for predictor selection and evaluation of the predictive power of a model. This modeling approach is applied to estimate the trip-level fishing costs using the empirical sampled trip costs and the associated trip-level fishing operational data and vessel characteristics in the Hawaii and American Samoa longline fisheries. Using this approach to build models is particularly important when there is no strong theoretical guideline on predictor selection. Also, the modeling approach addresses the issue of skewed trip cost data and provides predictive power measurement, compared with the previous modeling efforts in trip cost estimation for the Hawaii longline fishery. As a result, fishing trip costs for all trips in the fishery can be estimated. Lastly, this study applies the estimated trip cost model to conduct an empirical analysis to evaluate the impacts on trip costs due to spatial regulations in the Hawaii longline fishery. The results show that closing the Western and Central Pacific Ocean (WCPO) could induce an average 14% increase in fishing trip costs, while the trip cost impacts of the Eastern Pacific Ocean (EPO) closures could be lower.

Evidence of Atlantic bluefin tuna spawning in the Bay of Biscay, north-eastern Atlantic

The spawning grounds of the Atlantic bluefin tuna (Thunnus thynnus) are traditionally considered to be the Gulf of Mexico (Gulf of Mexico) and the Mediterranean Sea (Mediterranean Sea). However, for the western Atlantic, unequivocal evidence of bluefin spawning outside the Gulf of Mexico has been shown. In this study we present the first records of genetically confirmed bluefin larvae in the southern Bay of Biscay (eastern Atlantic). These findings provide evidence of bluefin spawning activity outside the Mediterranean Sea, in the north-eastern Atlantic. However, our results suggest that the bluefin spawning in the Bay of Biscay is a sporadic phenomenon.

Adaptive markers distinguish North and South Pacific Albacore amid low population differentiation

Albacore (Thunnus alalunga) support an economically valuable global fishery, but surprisingly little is known about the population structure of this highly migratory species. Physical tagging data suggest that Albacore from the North and South Pacific Ocean are separate stocks, but results from previous genetic studies did not support this two stock hypothesis. In addition, observed biological differences among juveniles suggest that there may be population substructure in the North Pacific. We used double-digest restriction site-associated DNA sequencing to assess population structure among 308 Albacore caught in 12 sample areas across the Pacific Ocean (10 North, 2 South). Since Albacore are highly migratory and spawning areas are unknown, sample groups were not assumed to be equivalent to populations and the genetic data were analyzed iteratively. We tested for putatively adaptive differences among groups and for genetic variation associated with sex. Results indicated that Albacore in the North and South Pacific can be distinguished using 84 putatively adaptive loci, but not using the remaining 12,788 presumed neutral sites. However, two individuals likely represent F1 hybrids between the North and South Pacific populations, and 43 Albacore potentially exhibit lower degrees of mixed ancestry. In addition, four or five cross-hemisphere migrants were potentially identified. No genetic evidence was found for population substructure within the North Pacific, and no loci appeared to distinguish males from females. Potential functions for the putatively adaptive loci were identified, but an annotated Albacore genome is required for further exploration. Future research should try to locate spawning areas so that life history, demography, and genetic population structure can be linked and spatiotemporal patterns can be investigated.

Climate change and marine turtles: recent advances and future directions

Climate change is a threat to marine turtles that is expected to affect all of their life stages. To guide future research, we conducted a review of the most recent literature on this topic, highlighting knowledge gains and research gaps since a similar previous review in 2009. Most research has been focussed on the terrestrial life history phase, where expected impacts will range from habitat loss and decreased reproductive success to feminization of populations, but changes in reproductive periodicity, shifts in latitudinal ranges, and changes in foraging success are all expected in the marine life history phase. Models have been proposed to improve estimates of primary sex ratios, while technological advances promise a better understanding of how climate can influence different life stages and habitats. We suggest a number of research priorities for an improved understanding of how climate change may impact marine turtles, including: improved estimates of primary sex ratios, assessments of the implications of female-biased sex ratios and reduced male production, assessments of the variability in upper thermal limits of clutches, models of beach sediment movement under sea level rise, and assessments of impacts on foraging grounds. Lastly, we suggest that it is not yet possible to recommend manipulating aspects of turtle nesting ecology, as the evidence base with which to understand the results of such interventions is not robust enough, but that strategies for mitigation of stressors should be helpful, providing they consider the synergistic effects of climate change and other anthropogenic-induced threats to marine turtles, and focus on increasing resilience.

Shifting seas, shifting boundaries: Dynamic marine protected area designs for a changing climate

Marine protected areas (MPAs) are valuable tools for marine conservation that aim to limit human impacts on marine systems and protect valuable species or habitats. However, as species distributions shift due to ocean warming, acidification, and oxygen depletion from climate change, the areas originally designated under MPAs may bear little resemblance to their past state. Different approaches have been suggested for coping with species on the move in conservation. Here, we test the effectiveness of different MPA designs, including dynamic, network, and different directional orientations on protecting shifting species under climate change through ecosystem modeling in a theoretical ecosystem. Our findings suggest that dynamic MPAs may benefit some species (e.g., whiting and anchovy) and fishing fleets, and these benefits can inform the design or adaptation of MPAs worldwide. In addition, we find that it is important to design MPAs with specific goals and to account for the effects of released fishing pressure and species interactions in MPA design.

Ensemble Modelling of Skipjack Tuna (Katsuwonus pelamis) Habitats in the Western North Pacific Using Satellite Remotely Sensed Data; a Comparative Analysis Using Machine-Learning Models

To examine skipjack tuna’s habitat utilization in the western North Pacific (WNP) we used an ensemble modelling approach, which applied a fisher- derived presence-only dataset and three satellite remote-sensing predictor variables. The skipjack tuna data were compiled from daily point fishing data into monthly composites and re-gridded into a quarter degree resolution to match the environmental predictor variables, the sea surface temperature (SST), sea surface chlorophyll-a (SSC) and sea surface height anomalies (SSHA), which were also processed at quarter degree spatial resolution. Using the sdm package operated in RStudio software, we constructed habitat models over a 9-month period, from March to November 2004, using 17 algorithms, with a 70:30 split of training and test data, with bootstrapping and 10 runs as parameter settings for our models. Model performance evaluation was conducted using the area under the curve (AUC) of the receiver operating characteristic (ROC), the point biserial correlation coefficient (COR), the true skill statistic (TSS) and Cohen’s kappa (k) metrics. We analyzed the response curves for each predictor variable per algorithm, the variable importance information and the ROC plots. Ensemble predictions of habitats were weighted with the TSS metric. Model performance varied across various algorithms, with the Support Vector Machines (SVM), Boosted Regression Trees (BRT), Random Forests (RF), Multivariate Adaptive Regression Splines (MARS), Generalized Additive Models (GAM), Classification and Regression Trees (CART), Multi-Layer Perceptron (MLP), Recursive Partitioning and Regression Trees (RPART), and Maximum Entropy (MAXENT), showing consistently high performance than other algorithms, while the Flexible Discriminant Analysis (FDA), Mixture Discriminant Analysis (MDA), Bioclim (BIOC), Domain (DOM), Maxlike (MAXL), Mahalanobis Distance (MAHA) and Radial Basis Function (RBF) had lower performance. We found inter-algorithm variations in predictor variable responses. We conclude that the multi-algorithm modelling approach enabled us to assess the variability in algorithm performance, hence a data driven basis for building the ensemble model. Given the inter-algorithm variations observed, the ensemble prediction maps indicated a better habitat utilization map of skipjack tuna than would have been achieved by a single algorithm.

Southward re-distribution of tropical tuna fisheries activity can be explained by technological and management change

There is broad evidence of climate change causing shifts in fish distribution worldwide, but less is known about the response of fisheries to these changes. Responses to climate-driven shifts in a fishery may be constrained by existing management or institutional arrangements and technological settings. In order to understand how fisheries are responding to ocean warming, we investigate purse seine fleets targeting tropical tunas in the east Atlantic Ocean using effort and sea surface temperature anomaly (SSTA) data from 1991 to 2017. An analysis of the spatial change in effort using a centre of gravity approach and empirical orthogonal functions is used to assess the spatiotemporal changes in effort anomalies and investigate links to SSTA. Both analyses indicate that effort shifts southward from the equator, while no clear pattern is seen northward from the equator. Random forest models show that while technology and institutional settings better explain total effort, SSTA is playing a role when explaining the spatiotemporal changes of effort, together with management and international agreements. These results show the potential of management to minimize the impacts of climate change on fisheries activity. Our results provide guidance for improved understanding about how climate, management and governance interact in tropical tuna fisheries, with methods that are replicable and transferable. Future actions should take into account all these elements in order to plan successful adaptation.