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Representative diagram of the experimental behavioral arenas and monitoring equipment. (a) Experimental individuals (Sparus aurata) were from wild and reared samples. (b) Behavioral arenas were composed by a seawater aquarium with their own sump and filter system. The arena presented a sand layer bed and a refuge. (c) An integrated recording and tracking systems formed by a Raspberry Pi computer and camera was mounted in front of the arena to measure the 2-dimensional movement of the individuals in the open area.
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Fish differ consistently in behavior within the same species and population, reflecting distinct behavioral types (BTs). Comparing the behavior of wild and reared individuals provides an excellent opportunity to delve into the ecological and evolutionary consequences of BTs. In this work, we evaluated the behavioral variation of wild and reared juv...
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The bogue, Boops boops (Linnaeus, 1758), is an omnivorous fish species that often aggregates near fish farms. In addition to being attracted to food, bogues also hide from predators near floating cages. Some specimens can also be found in the cages, where they coexist for a time with farmed fish. In general, there is a relationship between food ava...
Citations
... While industrial data can enhance our understanding of physiological and behavioral processes at the individual level, it is important to recognize the selection conditions imposed by industrial and productive interests often aims to reduce variability in certain traits (e.g., growth, height, weight). Consequently, this data provides a skewed view of variability compared to wild populations, which are subject to natural selection (Cam et al., 2002), and exhibit a much greater variability of life strategies and life history traits (Sanllehi et al., 2023). Nonetheless, having access to this data will contribute to refining the methods proposed here and addressing the technical challenges associated with parameter estimation at the individual level. ...
Population dynamics is influenced by between-individual variability. Dynamic Energy Budget (DEB) theory is an appealing framework for assessing such a variability, yet DEB parameters have rarely been estimated at the individual level. Bayesian hierarchical models show promise for inferring individual variability in DEB parameters , thought computational challenges have limited their use due to the need to solve differential equations. Timely, Stan has emerged as a general-purpose statistical tool for fitting dynamic models. This paper introduces an analytical strategy using Bayesian parametric inference and hierarchical modelling to estimate individual-specific DEB parameters. Two biologically relevant DEB parameters were successfully estimated for 69 Gilt-head breams (Sparus aurata) with up to 11 measures of length and wet weight each. The estimated between-individual variability in these two DEB parameters explained well the observed patterns in length and weight at between-and within-individual levels. Moreover, data-simulation experiments highlighted the potential and limitations of our approach, suggesting that improved data collection could enable to increase precision and the number of DEB parameters that can be estimated at the individual level. This strategy can better represent between-individual variability in DEB parameters, which ultimately may improve forecasting of population dynamics after integrating DEB into population models.
A fish’s behaviors describe what it is biologically. When you know what it eats at different life stages, what eats it, where it resides at various ages and at different times during the day and year, how it reacts to other species, how it reacts to conspecifics, and its reproductive behaviors, you know its life history. This is critical in conservation management, because knowing a fish’s behaviors will tell you the bottlenecks that are hindering survival and reproduction, and that will tell you the environmental fixes that are needed for recovery. Raising fish in traditional barren fish culture units with industrial-type management produces behaviorally-naïve fish with mal-adaptive behaviors, which adversely affects post-augmentation survival. The effect that culture has on three key behaviors is discussed: reproduction, predator avoidance, and feeding/foraging. The spawning protocol that is used to produce the fish that will be cultured can alter reproductive behaviors, particularly time of spawning which can, in turn, affect survival in subsequent generations. While spawning is not an aspect of conservation aquaculture per se, the genetic changes and their subsequent impacts on fitness that can be produced by your spawning protocol shows why you must consider genetics and fitness in all aspects of management when producing fish for augmentation. Traditional, intensive fish culture management produces fish that have poor foraging behaviors and that do not know how to avoid predators, which explains why they have high post-augmentation mortality. To improve post-augmentation survival, you need to raise fish in mesocosms that resemble the wild environment and use naturalized, extensive management; do not feed fish, but make them learn how to forage and stock predators so that they are not predator-naïve. Producing fish for aquaculture-assisted fisheries programs that do not have post-augmentation mal-adaptive behaviors is accomplished by using conservation aquaculture.
