Shannon Entropy in a European Seabass (Dicentrarchus labrax) System during the Initial Recovery Period after a Short-Term Exposure to Methylmercury

Abstract

Methylmercury (MeHg) is an environmental contaminant of increasing relevance as a seafood safety hazard that affects the health and welfare of fish. Non-invasive, on-line methodologies to monitor and evaluate the behavior of a fish system in aquaculture may make the identification of altered systems feasible-for example, due to the presence of agents that compromise their welfare and wholesomeness-and find a place in the implementation of Hazard Analysis and Critical Control Points and Fish Welfare Assurance Systems. The Shannon entropy (SE) of a European seabass (Dicentrarchus labrax) system has been shown to differentiate MeHg-treated from non-treated fish, the former displaying a lower SE value than the latter. However, little is known about the initial evolution of the system after removal of the toxicant. To help to cover this gap, the present work aims at providing information about the evolution of the SE of a European seabass system during a recuperation period of 11 days following a two-week treatment with 4 µg¨MeHg/L. The results indicate that the SE of the system did not show a recovery trend during the examined period, displaying erratic responses with daily fluctuations and lacking a tendency to reach the initial SE values.

Reducing the Number of Individuals to Monitor Shoaling Fish Systems – Application of the Shannon Entropy to Construct a Biological Warning System Model

“…The methodology used from image acquisition to fish group centroid trajectory estimation is depicted in Figure 4 and was based on that described in Eguiraun et al (2014) with the modifications detailed in Supplementary Data Sheet S4 and already used in Eguiraun et al (2016) . It was performed using MATLAB R2014a (MathWorks Inc.).…”

“…Shannon entropy has been used because our previous work ( Eguiraun et al, 2014 ) showed it to be the most sensitive among five algorithms tested, namely: Shannon and permutation entropies, and Katz, Higuchi, and Katz-Castiglioni’s fractal dimensions, to serve as a tool for the non-invasive quantification of fish responses and has subsequently been successfully applied to the study of the effect of certain chemicals (methylmercury and sodium selenite) on the complexity of the seabass centroid trajectories ( Eguiraun et al, 2014 , 2016 , 2018 ). The Shannon entropy was initially described as an expression of the amount of missing information within a message, since the concept of entropy, within this particular context, was developed by Shannon in his works on a mathematical theory of communication ( Shannon, 1948 , 1951 ).…”

“…Accordingly, and given that previous studies ( Kadota et al, 2011 ; Liu et al, 2011 ; Spasic et al, 2011 ; Quach et al, 2013 ; Bae and Park, 2014 ; Eguiraun et al, 2014 , 2016 , 2018 ; Forlim and Pinto, 2014 ) have identified the SE of the system as a variable with the potential to serve for fish health and welfare monitoring, the present work was designed to understand how the variation in the fish number affects the system dynamics in order to answer the following research questions: (i) Does the SE of a fish system vary according to the number of fish? (ii) if it does vary, how is this relationship?…”

“…Fish cognition and behavior is a well-established research field ( Vila Pouca and Brown, 2017 and references therein), and the characterisation of fish model systems’ behavior, using behavioral measurable changes, has found several practical applications, such as the detection of leaders in a group ( Mwaffo et al, 2017 ), the identification of information flows within a school of fish ( Crosato et al, 2018 ), the presence in the aquatic environment of contaminants including caffeine ( Ladu et al, 2015 ), drugs ( Liu et al, 2011 ), hypochlorite ( Magalhães et al, 2007 ; Nimkerdphol and Nakagawa, 2008 ; Teles et al, 2015 ), methyl-mercury ( Eguiraun et al, 2014 , 2016 ), the Se:Hg molar ratio in their feeds ( Eguiraun et al, 2018 ) and alterations in environmental parameters such as hypoxia, feeding regime ( Polonschii et al, 2013 ), and high fish density ( Papoutsoglou et al, 1998 ; Di Marco et al, 2008 ).…”

“…To identify this lowest possible number is in itself a challenge, since there is usually no explanation regarding the criteria used to select the number of fish in physiological and toxicological experiments. The studies published on the effect of perturbations on fish systems, as well as behavioral studies, use different numbers of fish: some use only one fish ( Magalhães et al, 2007 ; Brodin et al, 2013 ), while others use three fish ( Teles et al, 2015 ), five fish ( Crosato et al, 2018 ), fewer than 15 fish ( Krause, 1993 ; Huth and Wissel, 1994 ; Krause and Tegeder, 1994 ; Ladu et al, 2015 ), 18–40 fish ( Sadoul et al, 2014 ), 19–26 fish ( Eguiraun et al, 2016 ), 30–300 fish ( Tunstrøm et al, 2013 ), and 81 fish ( Eguiraun et al, 2014 ). However, we have not been able to find any publication providing any scientific explanation about the reasons that led the authors to use those particular numbers of individuals.…”