“…In that regard, developing tools such as models to study and predict the tolerance limits and responses of farmed species is crucial for the aquaculture industry, as it allows predicting future impacts and making informed strategic decisions for climate change adaptation (Pham et al, 2021). In turn, this may lead to suggestions on management practices that may be favoured in the future, such as changing the timing of production initiation, selecting different commercial sizes or even changing the rearing area, thus highlighting the power of these models as both study and management tools (Varga et al, 2020;Stavrakidis-Zachou et al, 2021c). For instance, as indicated by experimental data and the simulations performed here, tolerance limits are generally negatively correlated with fish size.…”
Pinpointing thermal tolerance thresholds for commercially important species, such as aquaculture finfish, under acute and chronic thermal stress is becoming increasingly relevant in the context of climate change. While experimental research, traditionally quantified by the determination of the Critical Thermal Maximum (CTmax), offers valuable insights, it is necessary to further develop appropriate tools to provide predictions and shed light on the underlying mechanisms of thermal tolerance. Bioenergetic models have long been used to study the effects of temperature on fish metabolism under chronic, but rarely under acute, scales. In this study, we present a modelling approach based on the Dynamic Energy Budget (DEB) theory that describes the tolerance limits of fish under acute thermal stress in bioenergetics terms. It adopts the notion of an energy-dependent tolerance to stress and defines acute tolerance limits at the intersection of fundamental energy fluxes, namely those relating to the mobilization of energy and to maintenance costs. To showcase this approach, DEB models for two finfish, the European sea bass (Dicentrarchus labrax) and the meagre (Argyrosomus regius) were used to run acute thermal challenge simulations and study shifts in the critical temperature achieved by the fish. The results suggest that the model can adequately capture the general tolerance patterns observed experimentally for the two species as well as pinpoint the parameters that may influence them. In particular, the simulations showed a positive relation between acclimation temperature and tolerance while the opposite stands for the body size of the fish, with smaller fish achieving higher critical temperatures than their larger counterparts. Also, tolerance limits were affected by the state of internal reserves, with well-fed fish exhibiting higher values. Finally, the potential application of this modelling approach on higher taxonomic scales was evaluated, by running simulations on species belonging to major fish orders. The preliminary results suggest that the method can capture differences among groups that are consistent with literature, suggesting it may be a realistic mechanistic approach for studying thermal tolerance in ectotherms.
“…In that regard, developing tools such as models to study and predict the tolerance limits and responses of farmed species is crucial for the aquaculture industry, as it allows predicting future impacts and making informed strategic decisions for climate change adaptation (Pham et al, 2021). In turn, this may lead to suggestions on management practices that may be favoured in the future, such as changing the timing of production initiation, selecting different commercial sizes or even changing the rearing area, thus highlighting the power of these models as both study and management tools (Varga et al, 2020;Stavrakidis-Zachou et al, 2021c). For instance, as indicated by experimental data and the simulations performed here, tolerance limits are generally negatively correlated with fish size.…”
Pinpointing thermal tolerance thresholds for commercially important species, such as aquaculture finfish, under acute and chronic thermal stress is becoming increasingly relevant in the context of climate change. While experimental research, traditionally quantified by the determination of the Critical Thermal Maximum (CTmax), offers valuable insights, it is necessary to further develop appropriate tools to provide predictions and shed light on the underlying mechanisms of thermal tolerance. Bioenergetic models have long been used to study the effects of temperature on fish metabolism under chronic, but rarely under acute, scales. In this study, we present a modelling approach based on the Dynamic Energy Budget (DEB) theory that describes the tolerance limits of fish under acute thermal stress in bioenergetics terms. It adopts the notion of an energy-dependent tolerance to stress and defines acute tolerance limits at the intersection of fundamental energy fluxes, namely those relating to the mobilization of energy and to maintenance costs. To showcase this approach, DEB models for two finfish, the European sea bass (Dicentrarchus labrax) and the meagre (Argyrosomus regius) were used to run acute thermal challenge simulations and study shifts in the critical temperature achieved by the fish. The results suggest that the model can adequately capture the general tolerance patterns observed experimentally for the two species as well as pinpoint the parameters that may influence them. In particular, the simulations showed a positive relation between acclimation temperature and tolerance while the opposite stands for the body size of the fish, with smaller fish achieving higher critical temperatures than their larger counterparts. Also, tolerance limits were affected by the state of internal reserves, with well-fed fish exhibiting higher values. Finally, the potential application of this modelling approach on higher taxonomic scales was evaluated, by running simulations on species belonging to major fish orders. The preliminary results suggest that the method can capture differences among groups that are consistent with literature, suggesting it may be a realistic mechanistic approach for studying thermal tolerance in ectotherms.
“…However, it also faces a variety of challenges, both natural and human-induced. As most aquaculture operations take place in the sea with little control over environmental conditions, the industry is susceptible to threats from changes such as reduced oxygen or extreme temperatures that affect the growth and survivability of farmed species and increased costs, events that are more frequent due to climate change [1]. Greece is one of the main producers of European seabass (Dicentrarchus labrax) and gilthead sea bream (Sparus aurata) in Europe, representing over 60% of the total European production according to the FEAP [2].…”
Section: Introductionmentioning
confidence: 99%
“…The significant expansion of aquaculture poses both risks and opportunities that require careful evaluation and appropriate measures for adaptation. Aquaculture procedures are complex due to the presence of numerous environmental drivers, such as temperature, extreme events, and harmful algal blooms, their interactions with production systems, and knowledge gaps about fish responses [1,12]. To support and facilitate decision making in this context, Decision Support Systems (DSSs) have been proposed as appropriate tools.…”
Marine aquaculture has been expanding rapidly in recent years, driven by the growing demand for marine products. However, this expansion has led to increased competition for space and resources with other coastal zone activities, which has resulted in the need for larger facilities and the relocation of operations to offshore areas. Moreover, the complex environment and exposure to environmental conditions and external threats further complicate the sustainable development of the sector. To address these challenges, new and innovative technologies are needed, such as the incorporation of remote sensing and in-situ data for comprehensive and continuous monitoring of aquaculture facilities. This study aims to create an integrated monitoring and decision support system utilizing both satellite and in-situ data to monitor aquaculture facilities on various scales, providing information on water quality, fish growth, and warning signs to alert managers and producers of potential hazards. This study focuses on identifying and estimating parameters that affect aquaculture processes, establishing indicators that can act as warning signs, and evaluating the system’s performance in real-life scenarios. The resulting monitoring tool, called “Aquasafe”, was evaluated for its effectiveness and performance by test users through real-life scenarios. The results of the implemented models showed high accuracy, with an R2 value of 0.67. Additionally, users were generally satisfied with the usefulness of the tool, suggesting that it holds promise for efficient management and decision making in marine aquaculture.
“…Sustainable management of fisheries is difficult due to the high demand for fish, illegal uncontrolled fishing and also because population dynamical models can hardly be called reliable (see below). Better knowledge of fish biology could not only help resolve this deep and complex problem, but also optimize aquaculture of fish ( Chary et al , 2020 , Sarà et al , 2018 , 2014 , Stavrakidis-Zachou et al , 2021 ). A proper understanding of eco-physiological properties is key to understanding population dynamics ( Kooijman et al , 2020 ).…”
To address challenges in management and conservation of fishes and fisheries it is essential to understand their life histories and energetics. The Add-my-Pet (AmP) collection of data on energetics and Dynamic Energy Budget (DEB) parameters currently contains 1150 of the 40000 extant species of fish. It gives 250–280 traits per species, depending on the model type that was applied, such as maximum reserve capacity, lifespan, specific respiration and precociality index, based on which the ray-finned fish (Actinopterygii) was compared with the four other fish classes (Cyclostomata, Chondrichthyes, Actinistia, Dipnoi) and the Tetrapoda. The Actinopterygii are the only vertebrate class that shows metabolic acceleration, and clearly so in only three sub-clades. Different from chondrichthyans, quite a few species follow the waste-to-hurry strategy, especially small bodied freshwater fish such as tropical annual killifish, but also in small minnows and darters in continental climates. We briefly discuss links between waste-to-hurry, which is associated with a large specific somatic maintenance, and sensitivity for pesticides. We discuss why this interferes with the physical co-variation between maximum reserve capacity and ultimate structural length or weight and explains why maximum reserve capacity increases with body length in chondrichthyans, but not in actinopterygians. Reserve capacity has relevance, e.g. mass-specific maintenance, starvation and the kinetics of lipophyllic compounds (such as pesticides), since reserve is relatively rich in lipids in fish. Also, unlike chondrichthyans, the size at birth is very small and not linked to ultimate size; we discuss the implications. Actinopterygians allocate more to soma, compared with chondrichthyans; the latter allocate more to maturity or reproduction. Actinopterygians, Actinistia and Dipnoi are near the supply-end of the supply–demand spectrum, while chondrichthyans clearly show demand properties.
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