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Populations of fishes provide valuable services for billions of people, but face diverse and interacting threats that jeopardize their sustainability. Human population growth and intensifying resource use for food, water, energy and goods are compromising fish populations through a variety of mechanisms, including overfishing, habitat degradation and declines in water quality. The important challenges raised by these issues have been recognized and have led to considerable advances over past decades in managing and mitigating threats to fishes worldwide. In this review, we identify the major threats faced by fish populations alongside recent advances that are helping to address these issues. There are very significant efforts worldwide directed towards ensuring a sustainable future for the world's fishes and fisheries and those who rely on them. Although considerable challenges remain, by drawing attention to successful mitigation of threats to fish and fisheries we hope to provide the encouragement and direction that will allow these challenges to be overcome in the future.

In this paper we explore the known connection among sustainability, resilience, and well-being within the framework of active inference. Initially, we revisit how the notions of well-being and resilience intersect within active inference before defining sustainability. We adopt a holistic concept of sustainability denoting the enduring capacity to meet needs over time without depleting crucial resources. It extends beyond material wealth to encompass community networks, labor, and knowledge. Using the Free Energy Principle, we can emphasize the role of fostering resource renewal, harmonious system-entity exchanges, and practices that encourage self-organization and resilience as pathways to achieving sustainability, both in an agent and in collectives. We start by connecting Active Inference with well-being, building on exsiting work. We then attempt to link resilience with sustainability, asserting that resilience alone is insufficient for sustainable outcomes. While crucial for absorbing shocks and stresses, resilience must be intrinsically linked with sustainability to ensure that adaptive capacities do not merely perpetuate existing vulnerabilities. Rather, it should facilitate transformative processes that address the root causes of unsustainability. Sustainability, therefore, must manifest across extended timescales and all system strata, from individual components to the broader system, to uphold ecological integrity, economic stability, and social well-being. We explain how sustainability manifests at the level of an agent, and then at the level of collectives and systems. To model and quantify the interdependencies between resources and their impact on overall system sustainability, we introduce the application of network theory and dynamical systems theory. We emphasize the optimization of precision or learning rates through the active inference framework, advocating for an approach that fosters the elastic and plastic resilience necessary for long-term sustainability and abundance.

Industrial producers face the task of optimizing production process in an attempt to achieve the desired quality such as mechanical properties with the lowest energy consumption. In industrial carbon fiber production, the fibers are processed in bundles containing (batches) several thousand filaments and consequently the energy optimization will be a stochastic process as it involves uncertainty, imprecision or randomness. This paper presents a stochastic optimization model to reduce energy consumption a given range of desired mechanical properties. Several processing condition sets are developed and for each set of conditions, 50 samples of fiber are analyzed for their tensile strength and modulus. The energy consumption during production of the samples is carefully monitored on the processing equipment. Then, five standard distribution functions are examined to determine those which can best describe the distribution of mechanical properties of filaments. To verify the distribution goodness of fit and correlation statistics, the Kolmogorov-Smirnov test is used. In order to estimate the selected distribution (Weibull) parameters, the maximum likelihood, least square and genetic algorithm methods are compared. An array of factors including the sample size, the confidence level, and relative error of estimated parameters are used for evaluating the tensile strength and modulus properties. The energy consumption and N2 gas cost are modeled by Convex Hull method. Finally, in order to optimize the carbon fiber production quality and its energy consumption and total cost, mixed integer linear programming is utilized. The results show that using the stochastic optimization models, we are able to predict the production quality in a given range and minimize the energy consumption of its industrial process.

Mangroves’ ability to store carbon (C) has long been recognized, but little is known about whether planted mangroves can store C as efficiently as naturally established (i.e., intact) stands and in which time frame. Through Bayesian logistic models compiled from 40 years of data and built from 684 planted mangrove stands worldwide, we found that biomass C stock culminated at 71 to 73% to that of intact stands ~20 years after planting. Furthermore, prioritizing mixed-species planting including Rhizophora spp. would maximize C accumulation within the biomass compared to monospecific planting. Despite a 25% increase in the first 5 years following planting, no notable change was observed in the soil C stocks thereafter, which remains at a constant value of 75% to that of intact soil C stock, suggesting that planting effectively prevents further C losses due to land use change. These results have strong implications for mangrove restoration planning and serve as a baseline for future C buildup assessments.

L'Accord de Paris oblige toutes les nations à entreprendre des efforts ambitieux pour lutter contre le changement climatique, avec l'engagement de « maintenir le réchauffement bien en dessous de 2 °C dans la température moyenne mondiale (GMT), par rapport aux niveaux préindustriels, et de poursuivre les efforts pour limiter le réchauffement à 1,5 °C ». La limite de 1,5 °C constitue un objectif ambitieux pour lequel une plus grande preuve de ses avantages pour la santé aiderait à orienter les politiques et potentiellement à accroître la motivation à agir. Ici, nous contribuons à cet écart avec une évaluation des avantages potentiels pour la santé, en termes de réduction de la mortalité liée à la température, découlant du respect des objectifs de température convenus, par rapport à des scénarios de réchauffement plus extrêmes. Nous avons effectué une analyse multirégionale dans 451 sites dans 23 pays avec différentes zones climatiques, et évalué les changements dans la mortalité liée à la chaleur et au froid selon des scénarios compatibles avec les objectifs de l'Accord de Paris (1,5 et 2 °C) et des augmentations plus extrêmes de la TMG (3 et 4 °C), et en supposant qu'il n'y ait aucun changement dans la distribution démographique et la vulnérabilité. Nos résultats suggèrent que limiter le réchauffement en dessous de 2 °C pourrait empêcher de fortes augmentations de la mortalité liée à la température dans la plupart des régions du monde. La comparaison entre 1,5 et 2 °C est plus complexe et caractérisée par une plus grande incertitude, avec des différences géographiques qui indiquent des avantages potentiels limités aux zones situées dans des climats plus chauds, où les impacts directs du changement climatique seront plus perceptibles. El Acuerdo de París obliga a todas las naciones a realizar esfuerzos ambiciosos para combatir el cambio climático, con el compromiso de "mantener el calentamiento muy por debajo de 2 ° C en la temperatura media global (GMT), en relación con los niveles preindustriales, y proseguir los esfuerzos para limitar el calentamiento a 1,5 ° C". El límite de 1,5 °C constituye un objetivo ambicioso para el cual una mayor evidencia sobre sus beneficios para la salud ayudaría a guiar la política y, potencialmente, a aumentar la motivación para la acción. Aquí contribuimos a esta brecha con una evaluación de los beneficios potenciales para la salud, en términos de reducciones en la mortalidad relacionada con la temperatura, derivados del cumplimiento de los objetivos de temperatura acordados, en comparación con escenarios de calentamiento más extremos. Realizamos un análisis multirregional en 451 ubicaciones en 23 países con diferentes zonas climáticas, y evaluamos los cambios en la mortalidad relacionada con el calor y el frío en escenarios consistentes con los objetivos del Acuerdo de París (1.5 y 2 ° C) y los aumentos más extremos de GMT (3 y 4 ° C), y bajo el supuesto de que no hay cambios en la distribución demográfica y la vulnerabilidad. Nuestros resultados sugieren que limitar el calentamiento por debajo de 2 °C podría evitar grandes aumentos en la mortalidad relacionada con la temperatura en la mayoría de las regiones del mundo. La comparación entre 1.5 y 2 °C es más compleja y se caracteriza por una mayor incertidumbre, con diferencias geográficas que indican beneficios potenciales limitados a áreas ubicadas en climas más cálidos, donde los impactos directos del cambio climático serán más discernibles. The Paris Agreement binds all nations to undertake ambitious efforts to combat climate change, with the commitment to "hold warming well below 2 °C in global mean temperature (GMT), relative to pre-industrial levels, and to pursue efforts to limit warming to 1.5 °C". The 1.5 °C limit constitutes an ambitious goal for which greater evidence on its benefits for health would help guide policy and potentially increase the motivation for action. Here we contribute to this gap with an assessment on the potential health benefits, in terms of reductions in temperature-related mortality, derived from the compliance to the agreed temperature targets, compared to more extreme warming scenarios. We performed a multi-region analysis in 451 locations in 23 countries with different climate zones, and evaluated changes in heat and cold-related mortality under scenarios consistent with the Paris Agreement targets (1.5 and 2 °C) and more extreme GMT increases (3 and 4 °C), and under the assumption of no changes in demographic distribution and vulnerability. Our results suggest that limiting warming below 2 °C could prevent large increases in temperature-related mortality in most regions worldwide. The comparison between 1.5 and 2 °C is more complex and characterized by higher uncertainty, with geographical differences that indicate potential benefits limited to areas located in warmer climates, where direct climate change impacts will be more discernible. تلزم اتفاقية باريس جميع الدول ببذل جهود طموحة لمكافحة تغير المناخ، مع الالتزام "بالاحتفاظ بالاحترار أقل بكثير من درجتين مئويتين في متوسط درجة الحرارة العالمية (GMT)، مقارنة بمستويات ما قبل الصناعة، ومواصلة الجهود للحد من الاحترار إلى 1.5 درجة مئوية". يشكل حد 1.5 درجة مئوية هدفًا طموحًا من شأن وجود أدلة أكبر على فوائده للصحة أن يساعد في توجيه السياسة ويحتمل أن يزيد من الدافع للعمل. نساهم هنا في هذه الفجوة من خلال تقييم الفوائد الصحية المحتملة، من حيث التخفيضات في الوفيات المرتبطة بدرجة الحرارة، المستمدة من الامتثال لأهداف درجة الحرارة المتفق عليها، مقارنة بسيناريوهات الاحترار الأكثر شدة. أجرينا تحليلاً متعدد المناطق في 451 موقعًا في 23 دولة ذات مناطق مناخية مختلفة، وقمنا بتقييم التغيرات في الحرارة والوفيات المرتبطة بالبرد في ظل سيناريوهات تتفق مع أهداف اتفاقية باريس (1.5 و 2 درجة مئوية) وزيادات أكثر تطرفًا في توقيت جرينتش (3 و 4 درجات مئوية)، وفي ظل افتراض عدم حدوث تغييرات في التوزيع الديموغرافي والضعف. تشير نتائجنا إلى أن الحد من الاحترار دون درجتين مئويتين يمكن أن يمنع الزيادات الكبيرة في الوفيات المرتبطة بدرجة الحرارة في معظم المناطق في جميع أنحاء العالم. المقارنة بين 1.5 و 2 درجة مئوية أكثر تعقيدًا وتتميز بدرجة أعلى من عدم اليقين، مع وجود اختلافات جغرافية تشير إلى فوائد محتملة تقتصر على المناطق الواقعة في المناخات الأكثر دفئًا، حيث ستكون الآثار المباشرة لتغير المناخ أكثر وضوحًا.