A Machine Learning Approach in Analyzing Bioaccumulation of Heavy Metals in Turbot Tissues.

Metals are considered to be one of the most hazardous substances due to their potential for accumulation, magnification, persistence, and wide distribution in water, sediments, and aquatic organisms. Demersal fish species, such as turbot (Psetta maxima maeotica), are accepted by the scientific communities as suitable bioindicators of heavy metal pollution in the aquatic environment. The present study uses a machine learning approach, which is based on multiple linear and non-linear models, in order to effectively estimate the concentrations of heavy metals in both turbot muscle and liver tissues. For multiple linear regression (MLR) models, the stepwise method was used, while non-linear models were developed by applying random forest (RF) algorithm. The models were based on data that were provided from scientific literature, attributed to 11 heavy metals (As, Ca, Cd, Cu, Fe, K, Mg, Mn, Na, Ni, Zn) from both muscle and liver tissues of turbot exemplars. Significant MLR models were recorded for Ca, Fe, Mg, and Na in muscle tissue and K, Cu, Zn, and Na in turbot liver tissue. The non-linear tree-based RF prediction models (over 70% prediction accuracy) were identified for As, Cd, Cu, K, Mg, and Zn in muscle tissue and As, Ca, Cd, Mg, and Fe in turbot liver tissue. Both machine learning MLR and non-linear tree-based RF prediction models were identified to be suitable for predicting the heavy metal concentration from both turbot muscle and liver tissues. The models can be used for improving the knowledge and economic efficiency of linked heavy metals food safety and environment pollution studies.

Ecophysiological and life-history adaptations of Gammarus balcanicus (Schäferna, 1922) in a sinking-cave stream from Western Carpathians (Romania).

Freshwater gammarids are known to colonise occasionally sinking-cave streams, providing contrasting morphological, life-history and ecophysiological adaptations compared to their surface conspecifics. In this study, a subterranean and a surface population of the species Gammarus balcanicus was surveyed for one year in a sinking-cave stream from the Western Carpathians (Romania). The results showed that the cave-dwelling population comprised individuals that were significantly larger compared to their surface conspecifics, had larger body-size at sexual maturity and that the females produced fewer, but larger eggs, compared to the population situated outside the cave. The trophic position and the omnivory were significantly higher for the cave-dwelling compared to surface population and the elemental imbalance for C:P molar ratios lower, but similar for C:N. However, the subterranean population did not present troglomorphic characters or longer lifespan as known for other cave-surface paired crustaceans. This, together with the rather extensive hydrological connection of the habitats, suggests active gene-flow between populations and similar response to seasonality for body-size distributions, indicating that the observed ecophysiological and life-history differences are rather the consequence of phenotypic plasticity than the result of genetic adaptation.