Size-dependence of food intake and mortality interact with temperature and seasonality to drive diversity in fish life histories.

Understanding how growth and reproduction will adapt to changing environmental conditions is a fundamental question in evolutionary ecology, but predicting the responses of specific taxa is challenging. Analyses of the physiological effects of climate change upon life history evolution rarely consider alternative hypothesized mechanisms, such as size-dependent foraging and the risk of predation, simultaneously shaping optimal growth patterns. To test for interactions between these mechanisms, we embedded a state-dependent energetic model in an ecosystem size-spectrum to ask whether prey availability (foraging) and risk of predation experienced by individual fish can explain observed diversity in life histories of fishes. We found that asymptotic growth emerged from size-based foraging and reproductive and mortality patterns in the context of ecosystem food web interactions. While more productive ecosystems led to larger body sizes, the effects of temperature on metabolic costs had only small effects on size. To validate our model, we ran it for abiotic scenarios corresponding to the ecological lifestyles of three tuna species, considering environments that included seasonal variation in temperature. We successfully predicted realistic patterns of growth, reproduction, and mortality of all three tuna species. We found that individuals grew larger when environmental conditions varied seasonally, and spawning was restricted to part of the year (corresponding to their migration from temperate to tropical waters). Growing larger was advantageous because foraging and spawning opportunities were seasonally constrained. This mechanism could explain the evolution of gigantism in temperate tunas. Our approach addresses variation in food availability and individual risk as well as metabolic processes and offers a promising approach to understand fish life-history responses to changing ocean conditions.

Seventy years of tunas, billfishes, and sharks as sentinels of global ocean health.

Fishing activity is closely monitored to an increasing degree, but its effects on biodiversity have not received such attention. Using iconic and well-studied fish species such as tunas, billfishes, and sharks, we calculate a continuous Red List Index of yearly changes in extinction risk over 70 years to track progress toward global sustainability and biodiversity targets. We show that this well-established biodiversity indicator is highly sensitive and responsive to fishing mortality. After ~58 years of increasing risk of extinction, effective fisheries management has shifted the biodiversity loss curve for tunas and billfishes, whereas the curve continues to worsen for sharks, which are highly undermanaged. While populations of highly valuable commercial species are being rebuilt, the next management challenge is to halt and reverse the harm afflicted by these same fisheries to broad oceanic biodiversity.

Global reconstruction of life-history strategies: A case study using tunas.

Measuring the demographic parameters of exploited populations is central to predicting their vulnerability and extinction risk. However, current rates of population decline and species loss greatly outpace our ability to empirically monitor all populations that are potentially threatened.The scale of this problem cannot be addressed through additional data collection alone, and therefore it is a common practice to conduct population assessments based on surrogate data collected from similar species. However, this approach introduces biases and imprecisions that are difficult to quantify. Recent developments in hierarchical modelling have enabled missing values to be reconstructed based on the correlations between available life-history data, linking similar species based on phylogeny and environmental conditions.However, these methods cannot resolve life-history variability among populations or species that are closely placed spatially or taxonomically. Here, theoretically motivated constraints that align with life-history theory offer a new avenue for addressing this problem. We describe a Bayesian hierarchical approach that combines fragmented, multispecies and multi-population data with established life-history theory, in order to objectively determine similarity between populations based on trait correlations (life-history trade-offs) obtained from model fitting.We reconstruct 59 unobserved life-history parameters for 23 populations of tuna that sustain some of the world's most valuable fisheries. Testing by cross-validation across different scenarios indicated that life-histories were accurately reconstructed when information was available for other populations of the same species. The reconstruction of several traits was also accurate for species represented by a single population, although credible intervals increased dramatically. Synthesis and applications. The described Bayesian hierarchical method provides access to life-history traits that are difficult to measure directly and reconstructs missing life-history information useful for assessing populations and species that are directly or indirectly affected by human exploitation of natural resources. The method is particularly useful for examining populations that are spatially or taxonomically similar, and the reconstructed life-history strategies described for the principal market tunas have immediate application to the world-wide management of these fisheries.

Overcoming the Data Crisis in Biodiversity Conservation.

How can we track population trends when monitoring data are sparse? Population declines can go undetected, despite ongoing threats. For example, only one of every 200 harvested species are monitored. This gap leads to uncertainty about the seriousness of declines and hampers effective conservation. Collecting more data is important, but we can also make better use of existing information. Prior knowledge of physiology, life history, and community ecology can be used to inform population models. Additionally, in multispecies models, information can be shared among taxa based on phylogenetic, spatial, or temporal proximity. By exploiting generalities across species that share evolutionary or ecological characteristics within Bayesian hierarchical models, we can fill crucial gaps in the assessment of species' status with unparalleled quantitative rigor.

The conservation and management of tunas and their relatives: setting life history research priorities.

Scombrids (tunas, bonitos, Spanish mackerels and mackerels) support important fisheries in tropical, subtropical and temperate waters around the world, being one of the most economically- and socially-important marine species globally. Their sustainable exploitation, management and conservation depend on accurate life history information for the development of quantitative fisheries stock assessments, and in the fishery data-poor situations for the identification of vulnerable species. Here, we assemble life history traits (maximum size, growth, longevity, maturity, fecundity, spawning duration and spawning interval) for the 51 species of scombrids globally. We identify major biological gaps in knowledge and prioritize life history research needs in scombrids based on their biological gaps in knowledge, the importance of their fisheries and their current conservation status according to the International Union for Conservation of Nature Red List. We find that the growth and reproductive biology of tunas and mackerel species have been more extensively studied than for Spanish mackerels and bonitos, although there are notable exceptions in all groups. We also reveal that reproductive biology of species, particular fecundity, is the least studied biological aspect in scombrids. We identify two priority groups, including 32 species of scombrids, and several populations of principal market tunas, for which life history research should be prioritized following the species-specific life history gaps identified in this study in the coming decades. By highlighting the important gaps in biological knowledge and providing a priority setting for life history research in scombrid species this study provides guidance for management and conservation and serves as a guide for biologists and resource managers interested in the biology, ecology, and management of scombrid species.

Global population trajectories of tunas and their relatives.

Tunas and their relatives dominate the world's largest ecosystems and sustain some of the most valuable fisheries. The impacts of fishing on these species have been debated intensively over the past decade, giving rise to divergent views on the scale and extent of the impacts of fisheries on pelagic ecosystems. We use all available age-structured stock assessments to evaluate the adult biomass trajectories and exploitation status of 26 populations of tunas and their relatives (17 tunas, 5 mackerels, and 4 Spanish mackerels) from 1954 to 2006. Overall, populations have declined, on average, by 60% over the past half century, but the decline in the total adult biomass is lower (52%), driven by a few abundant populations. The trajectories of individual populations depend on the interaction between life histories, ecology, and fishing pressure. The steepest declines are exhibited by two distinct groups: the largest, longest lived, highest value temperate tunas and the smaller, short-lived mackerels, both with most of their populations being overexploited. The remaining populations, mostly tropical tunas, have been fished down to approximately maximum sustainable yield levels, preventing further expansion of catches in these fisheries. Fishing mortality has increased steadily to the point where around 12.5% of the tunas and their relatives are caught each year globally. Overcapacity of these fisheries is jeopardizing their long-term sustainability. To guarantee higher catches, stabilize profits, and reduce collateral impacts on marine ecosystems requires the rebuilding of overexploited populations and stricter management measures to reduce overcapacity and regulate threatening trade.