Percorrer por autor "Palstra, Arjan P."
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- Accelerometry of seabream in a sea-cage: is acceleration a good proxy for activity?Publication . Palstra, Arjan P.; Arechavala Lopez, Pablo; Xue, Yuanxu; Roque, AnaActivity assessment of individual fish in a sea-cage could provide valuable insights into the behavior, but also physiological well-being and resilience, of the fish population in the cage. Acceleration can be monitored continuously with internal acoustic transmitter tags and is generally applied as a real-time proxy for activity. The objective of this study was to investigate the activity patterns of Gilthead seabream (Sparus aurata) by transmitter tags in a sea-cage and analyze correlations with water temperature, fish size and tissue weights. Experimental fish (N = 300) were transferred to an experimental sea-cage of which thirty fish (Standard Length SL = 18.3 1.7 cm; Body Weight BW = 174 39 g) were implanted with accelerometer tags. Accelerations were monitored for a period of 6 weeks (Nov.–Dec.) and were analyzed over the 6 weeks and 24 h of the day. At the end of the experimental period, tagged fish were again measured, weighed and dissected for tissue and filet weights, and correlations with accelerations were analyzed. Daily rhythms in accelerations under the experimental conditions were characterized by more active periods from 6 to 14 h and 18 to 0 h and less active periods from 0 to 6 h and 14 to 18 h. This W-shaped pattern remained over the experimental weeks, even with diurnal accelerations decreasing which was correlated to the dropping temperature. The increase in activity was not during, but just before feeding indicating food-anticipatory activity. Activity patterning can be useful for timing feeding events at the start of active periods, in this study between 6 and 11 h, and between 18 and 22 h. Acceleration was negatively correlated to heart and mesenteric fat mass, which was the exact contrary of our expectations for sustainedly swimming seabream. These results suggest that acceleration is a proxy for unsteady swimming activity only and research is required into the accelerations occurring during sustained swimming of seabream at various speeds.
- From signals to states: biologger-based classification of seabass welfare states in sea-cagesPublication . Hoyo-Alvarez, Esther; Cabrera-Álvarez, María José; Vanrell-Valls, Margalida; Palstra, Arjan P.; Arechavala-Lopez, PabloBackground Aquaculture has grown significantly in recent years, increasing the need for advanced monitoring techniques to ensure fish welfare and optimise management practices. Understanding how fish respond to environmental and anthropogenic factors is key for improving welfare standards, and biologgers capable of measuring heart rate (HR) and external acceleration (ACC) provide valuable insights into physiological and behavioural dynamics. Results In this study, HR and ACC were recorded from adult European seabass implanted with biologgers and monitored in sea-cages for two 14-day periods in March and July. Feeding and routine cage maintenance occurred from Monday to Friday, whereas no aquaculture-related human activity took place during weekends. A Random Forest (RF) model was developed using labelled data from controlled stress-challenge experiments to classify four welfare states: resting, regular activity, reactive response, and proactive response. Standardized ACC was identified as the main predictor for proactive responses, whereas standardized HR contributed most strongly to resting and reactive states. Application of the model to sea-cage data revealed clear diel patterns: regular activity and resting predominated at night and early morning, while proactive responses increased from midday onwards and were closely related to feeding routines. Significant differences also emerged between weekdays and weekends, with stress-related states more frequent during weekdays and resting and regular activity dominating weekends, reflecting the influence of routine operations and human activity in the farming facilities. Seasonal patterns further revealed higher HR levels and a greater prevalence of proactive responses in July, likely driven by elevated water temperatures, increased anthropogenic pressure and enhanced behavioural alertness under summer conditions. Conclusions Overall, the integration of biologgers with machine learning classification provides a robust framework for identifying welfare states in seabass reared in sea-cages, demonstrating how physiological, behavioural, and environmental data can be combined to inform management decisions, optimise operational protocols, and ultimately enhance welfare-oriented aquaculture practices.