Data and Code from: Individual recognition of familiar mates informs nest defense behaviors in the corkwing wrasse.

Data and Code from: Individual recognition of familiar mates informs nest defense behaviors in the corkwing wrasse. Abstract Individual recognition underpins many complex social behaviors, yet its roles in key reproductive behaviors such as mate recognition, mate choice, and courtship are poorly studied, especially in teleost fishes. Furthermore, in situ investigations into individual recognition are often confounded by the inherent difficulty of reliably establishing recognition between individuals. Here, we leverage the ecology of the corkwing wrasse (Symphodus melops) as well as a novel in situ application of radio frequency telemetry to reliably identify intentional associations between individuals. Using this information we empirically tested how the attack latency of nesting males differed when presented with an inanimate replica depicting visual information of familiar and unfamiliar females and sneaker males. Nesting males exhibited no difference in attack latency between familiar and unfamiliar sneaker replicas. Whereas familiar females provoked a slower attack latency than unfamiliar replicas. These results provide rare evidence of individual recognition in an ecologically relevant context, demonstrating sex-specific familiar recognition based on visual cues. This suggests class-level individual recognition underpins social interactions in this species, evidencing a complex interplay between familiarity and key reproductive behaviors. Furthermore, these results highlight the important role in situ experiments play in deepening our understanding of complex cognitive abilities in a natural context. Content: Raw_Data.csv - Raw behavioural data collected via annotating videos in Behavioural Observation and Research Interactive Software (BORIS). Descriptions of behaviours and their appropriate annotations can be found in the file title "RawDataEthogram.docx". RawDataEthogram.docx - Ethogram associated with the behaviors in "Raw_Data.csv" Attack_Latency_and_Frequency2023.csv - Data derived from the raw data (including metadata) that was used for final analysis in the script "Rscript_for_morph_recogntion.rmd". R_Code_For_Familiar_Recognition.rmd - Annotated R markdown script used to conducted our analysis on the influence of model type on attack probability, latency and frequency. README.txt - Detailed breakdown of the contents above.