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We investigate the interactions between anthropogenic climate change, socioeconomic developments and tuna fishery management strategies. For this purpose, we use the APECOSM-E model to map the effects of climate change and commercial fishing on the distribution of skipjack tuna biomass in the three oceans, combined with a new bioeconomic module representing the rent or profit of skipjack fisheries. For forcing, we use Representative Concentration Pathway (RCP) 8.5, the highest emission scenario for greenhouse gas concentrations presented in the IPCC’s Fifth Assessment Report (AR5), and the IPCC Socioeconomic Shared Pathway (SSP) 3, which is characterized by low economic development and a strong increase in the world population. We first investigate the impact of climate change on regional skipjack abundance, catches and profits in three oceans (Atlantic, Indian and Pacific) in 2010, 2050 and 2095. We then study the effects of three management strategies (maximum sustainable yield or MSY, maximum economic yield or MEY, and zero rent or ZR) on the future distribution of fishing fleets between oceans and on global economic rent. Our model projections for 2050 and 2095 show an increase in global skipjack biomass compared to 2010 and major changes in its distribution, impacting local and regional fishing efforts. The Pacific Ocean will continue to dominate the skipjack market. In our modeling of management strategies, the currently predominant MSY strategy would have been unprofitable in 2010, due to a decreased catch per unit effort (CPUE). In the future, however, technological developments should increase fishing efficiency and make MSY profitable. In all the scenarios, a MEY strategy is more profitable than MSY but leads to the lowest catches and the highest prices. This raises ethical questions in a world where food security may become a top priority. In the scenarios where MSY generates an economic loss (e.g. 2010), a ZR strategy allows global stocks to be exploited at high but still profitable levels. Conversely, in the scenarios where MSY is profitable, (e.g. 2095) ZR leads to overfishing and smaller global catches. We conclude that the most appropriate management strategy at any time is likely to change as environmental and socioeconomic conditions evolve. The decision to follow one or other strategy is a complex one that must be regularly reviewed and updated. [ABSTRACT FROM AUTHOR]

Climate-induced changes in the physical, chemical, and biological environment are expected to increasingly stress marine ecosystems, with important consequences for fisheries exploitation. Here, we use the APECOSM-E numerical model (Apex Predator ECOSystem Model - Estimation) to evaluate the future impacts of climate change on the physiology, spatial distribution, and abundance of skipjack tuna, the worldwide most fished species of tropical tuna. The main novelties of our approach lie in the mechanistic link between environmental factors, metabolic rates, and behavioral responses and in the fully three dimensional representation of habitat and population abundance. Physical and biogeochemical fields used to force the model are provided by the last generation of the IPSL- CM5 Earth System Model run from 1990 to 2100 under a 'business-as-usual' scenario ( RCP8.5). Our simulations show significant changes in the spatial distribution of skipjack tuna suitable habitat, as well as in their population abundance. The model projects deterioration of skipjack habitat in most tropical waters and an improvement of habitat at higher latitudes. The primary driver of habitat changes is ocean warming, followed by food density changes. Our projections show an increase of global skipjack biomass between 2010 and 2050 followed by a marked decrease between 2050 and 2095. Spawning rates are consistent with population trends, showing that spawning depends primarily on the adult biomass. On the other hand, growth rates display very smooth temporal changes, suggesting that the ability of skipjack to keep high metabolic rates in the changing environment is generally effective. Uncertainties related to our model spatial resolution, to the lack or simplification of key processes and to the climate forcings are discussed. [ABSTRACT FROM AUTHOR]

The benefits of implementing no-take Marine Protected Areas (MPAs) for the conservation of highly migratory species are not easy to assess. They depend on several factors, such as the fish mobility, fisher behaviour and the area covered by the MPA with respect to the distribution area of the species to protect. In this study, we explore the simultaneous effects of MPAs and fishing scenarios on skipjack tuna population dynamics, using the spatially-explicit APECOSM-E model. The model represents the size-structured population dynamics of skipjack tuna in the Indian Ocean and their dependence on climatic variability and exploitation by fisheries. Numerical experiments were run from the beginning of industrial fisheries in the early 1980s to the year 2030, considering different scenarios for the future development of fisheries. These scenarios combined different trends in fishing effort and technological development, either assuming a continuous increase following historical trends or a stabilization of these factors at present values. The simulations were designed to explore the effects of two MPAs of different size and location: the recently established Chagos MPA, and a hypothetical MPA covering a large part of the Western Indian Ocean, where most of the skipjack catches are presently made. We modelled the redistribution of fishing effort around the MPAs assuming that the fishers had partial knowledge of the spatial distribution of the skipjack population. The effects of the two MPAs on the population dynamics, catch and fishing mortality are shown. Our results revealed a very minor effect of the Chagos MPA on the skipjack tuna population, while the Western Indian Ocean MPA had an important impact on the fishing mortality and succeeded in stabilizing the spawning population. The simulations also showed that the effect of an MPA depends on the evolution of fisheries and it is therefore important to explore different fishery scenarios to assess the future benefits of an MPA. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents the parameter estimation and sensitivity analysis of the APECOSM-E model, which describes the basin scale 3D size-structured population dynamics of the skipjack tuna population in the Indian Ocean under the joint effect of environmental variability and fisheries exploitation. The model is presented in detail in the companion paper (Dueri et al., 2012). A common methodology based on the evaluation of a cost function that combines the negative log-likelihoods of commercial catches and size frequencies is used for both tasks. A Bayesian term representing the a priori probabilities about the model parameters is added to the cost function used for parameter estimation. The partial derivatives of the cost function with respect to the parameters are obtained by deriving the tangent linear code of the model by automatic differentiation of the direct code. A minimization algorithm is used to estimate the parameters related to fisheries and maximise the fitness of the model to the available observations. In a second step, we evaluate the local sensitivity of the non-estimated parameters and identify the model parameters that have an important effect on the output of the model and that would deserve better measurements in order to reduce the level of uncertainty in the model outputs. The comparison between the optimized simulation and the observations allows identifying the model''s strengths and limitations, in the perspective of using the model to test scenarios concerning the resilience of the population and the sustainability of its exploitation in the Indian Ocean. [Copyright &y& Elsevier]