Disparate behavioral types in wild and reared juveniles of gilthead seabream

Abstract

[Methods used for collection/generation of data] Standardized behavioral tests with continuous recording was provided by a camera attached to each arena controlled by a Raspberry Pi 3 system. All the behavioral tests were analyzed using a trained deep learning algorithm.[Methods for processing the data] Deep learning algorithm and R-Studio.The tests started with wild individuals on March 11th, 2019 and ended on April 23rd, 2019. Reared individuals were tested starting on July 19th, 2019 and ending on August 22nd, 2019.Project funded by the research project FISHOBES (grant no. CTM2017-91490-EXP) funded by the Spanish Ministry of Science and Innovation (MICINN). Marco Signaroli was supported by a “Ayudas para contratos predoctorales” (grant no. PRE2020-095580) funded by MCIN/AEI /10.13039/501100011033 and the FSE “invierte en tu futuro”. Aina Pons was supported by an FPI predoctoral fellowship (ref. FPI/2269/2019) from the Balearic Islands Government General Direction of Innovation and Research. Josep Alós received funding from the CLOCKS I+D+I project (grant no. PID2019-104940GA-I00) and the JSATS PIE project (grant no. PIE202030E002) funded by MCIN/AEI/10.13039/501100011033 and the FSE “invierte en tu futuro”.Peer reviewe