How reproductive strategies contribute to patterns of senescence in natural populations remains contentious. We studied reproductive senescence in the dimorphic white-throated sparrow, an excellent species for exploring this issue. Within both sexes the morphs use distinct reproductive strategies, and disassortative pairing by morph results in pair types with distinct parental systems. White morph birds are more colorful and aggressive than tan counterparts, and white males compete for extrapair matings, whereas tan males are more parental. Tan males and white females share parental care equally, whereas white males provide little parental support to tan females. We found morph-specific patterns of reproductive senescence in both sexes. White males exhibited greater reproductive senescence than tan males. This result likely reflects the difficulty of sustaining a highly competitive reproductive strategy as aging progresses rather than high physiological costs of competitiveness, since white males were also long-lived. Moreover, morph was not consistently related to reproductive senescence across the sexes, arguing against especially high costs of the traits associated with white morph identity. Rather, tan females exhibited earlier reproductive senescence than white females and were short-lived, perhaps reflecting the challenges of unsupported motherhood. Results underscore the importance of social dynamics in determining patterns of reproductive senescence.

Despite their potential to generate high-quality positioning data, the use of high-resolution acoustic telemetry systems (HRATS) has been neglected in coastal marine areas due to the limitations that these environments pose to the transmission of acoustic signals. In this work, we applied a HRATS and social network analysis (SNA) to study the social interactions of the pearly razorfish (Xyrichtys novacula), a small coastal wrasse, in a Mediterranean marine reserve. Our analysis was based on proximity measures estimated from high-resolution trajectories from 232 individuals tracked during 55 days within a marine protected area. Associations were defined as the proportion of 5-min intervals in which two individuals were observed within 1 m from each other, and social networks were generated for the overall tracking period and for each particular day. The obtained network parameters were contrasted against 1,000 null association models obtained by randomly redistributing individual trajectories within the study area. The obtained networks showed a harem-like social structure, with agonistic behavior between males and larger association indices between individuals of different sex. Occasionally, sporadic associations of large groups of females were observed conducting excursions along the study area. By providing a comprehensive view of the organizational structure of the pearly razorfish, our study demonstrates the potential of HRATS to efficiently produce high-throughput tracking data from large numbers of individuals and of proper null social model formulation to reconstruct the social networks in wild-living marine fish populations. The combination of HRATS and SNA represents a powerful tool to study key ecological processes regarding the social interactions of individuals, including social dynamics, collective movements, and the response to environmental perturbations.

It is often hypothesized that intra-sexual competition accelerates actuarial senescence, or the increase in mortality rates with age. However, an alternative hypothesis is that parental investment is more important to determining senescence rates. We used a unique model system, the white-throated sparrow (Zonotrichia albicollis), to study variation in actuarial senescence. In this species, genetically determined morphs display discrete mating strategies and disassortative pairing, providing an excellent opportunity to test the predictions of the above hypotheses. Compared to tan-striped males, white-striped males are more polygynous and aggressive, and less parental. Tan-striped females receive less parental support, and invest more into parental care than white-striped females, which are also more aggressive. Thus, higher senescence rates in males and white-striped birds would support the intra-sexual competition hypothesis, whereas higher senescence rates in females and tan-striped birds would support the parental investment hypothesis. White-striped males showed the lowest rate of actuarial senescence. Tan-striped females had the highest senescence rate, and tan-striped males and white-striped females showed intermediate, relatively equal rates. Thus, results were inconsistent with sexual selection and competitive strategies increasing senescence rates, and instead indicate that senescence may be accelerated by female-biased parental care, and lessened by sharing of parental duties.

Motorboat noise is recognized as a major source of marine pollution, however little is known about its ecological consequences on coastal systems. We developed a State Space Model (SSM) that incorporates an explicit dependency on motorboat noise to derive its effects on the movement of resident fish that transition between two behavioural states (swimming vs. hidden). To explore the performance of our model, we carried out an experiment where free-living Serranus scriba were tracked with acoustic tags, while motorboat noise was simultaneously recorded. We fitted the generated tracking and noise data into our SSM and explored if the noise generated by motorboats passing at close range affected the movement pattern and the probability of transition between the two states using a Bayesian approach. Our results suggest high among individual variability in movement patterns and transition between states, as well as in fish response to the presence of passing motorboats. These findings suggest that the effects of motorboat noise on fish movement are complex and require the precise monitoring of large numbers of individuals. Our SSM provides a methodology to address such complexity and can be used for future investigations to study the effects of noise pollution on marine fish.

Abstract. Females from polymorphic species could theoretically benefit by adjusting offspring morph composition, since morphs often differ in ecological and behavioral traits, and may be differentially susceptible to environmental conditions. Although offspring sex ratio adjustments have been increasingly supported, whether, and in which contexts, genetically determined morph ratios are adjusted has not been established. We used a long-term dataset to examine whether broad-scale climatic patterns characterized by teleconnection indices, population composition, and other environmental factors affect offspring sexmorph ratios in the white-throated sparrow (Zonotrichia albicollis), a species with chromosomal morph determination. We predicted that females might overproduce the underrepresented sex or morph, since pairing is disassortative by morph, and might also produce more white morph male offspring given favorable climatic conditions, because white males (WMs) are large, promiscuous, and expensive to produce. The proportion of WM-by-tan female breeding pairs and recruitment of WMs declined following winters with high Pacific North American teleconnection indices, and females of both morphs produced more WM offspring after these relatively cold winters. These winters and the following springs were also associated with low Southern Oscillation indices, indicating El Niño. Females of both morphs also produced fewer males late in asynchronously hatching broods. Adjustment of brood composition in response to climatically mediated changes in population composition could stabilize the white-throated sparrow's disassortative breeding system and genetic polymorphism.

Behavioural types (i.e., personalities or temperament) are defined as among individual differences in behavioural traits that are consistent over time and ecological contexts. Behavioural types are widespread in nature and play a relevant role in many ecological and evolutionary processes. In this work, we studied for the first time the consistency of individual aggressiveness in the pearly razorfish, Xyrichtys novacula, using a mirror test: a classic method to define aggressive behavioural types. The experiments were carried out in semi-natural behavioural arenas and monitored through a novel Raspberry Pi-based recording system. The experimental set up allowed us to obtain repeated measures of individual aggressivity scores during four consecutive days. The decomposition of the phenotypic variance revealed a significant repeatability score (R) of 0.57 [0.44–0.60], suggesting high predictability of individual behavioural variation and the existence of different behavioural types. Aggressive behavioural types emerged irrespective of body size, sex and the internal condition of the individual. Razorfishes are a ubiquitous group of fish species that occupy sedimentary habitats in most shallow waters of temperate and tropical seas. These species are known for forming strong social structures and playing a relevant role in ecosystem functioning. Therefore, our work provides novel insight into an individual behavioural component that may play a role in poorly known ecological and evolutionary processes occurring in this species.

Parents can have profound effects on offspring fitness. Little, however, is known about the mechanisms through which parental genetic variation influences offspring physiology in natural systems. White‐throated sparrows (Zonotrichia albicollis, WTSP) exist in two genetic morphs, tan and white, controlled by a large polymorphic supergene. Morphs mate disassortatively, resulting in two pair types: tan male × white female (T × W) pairs, which provide biparental care and white male × tan female (W × T) pairs, which provide female‐biased care. To investigate how parental composition impacts offspring, we performed RNA‐seq on whole blood of WTSP nestlings sampled from nests of both pair types. Parental pair type had a large effect on nestling gene expression, with 881 genes differentially expressed (DE) and seven correlated gene coexpression modules. The DE genes and modules expressed at higher levels in W × T nests with female‐biased parental care function in metabolism and stress‐related pathways resulting from the overrepresentation of proteolysis and stress‐response genes (e.g., SOD2, NR3C1). These results show that parental genotypes and/or associated behaviours influence nestling physiology, and highlight avenues of further research investigating the ultimate implications for the maintenance of this polymorphism. Nestlings also exhibited morph‐specific gene expression, with 92 differentially expressed genes, comprising immunity genes and genes encompassed by the supergene. Remarkably, we identified the same regulatory hub genes in these blood‐derived expression networks as were previously identified in adult WTSP brains (EPM2A, BPNT1, TAF5L). These hub genes were located within the supergene, highlighting the importance of this gene complex in structuring regulatory networks across diverse tissues.

Deep learning allows us to automatize the acquisition of large amounts of behavioural animal data with applications for fisheries and aquaculture. In this work, we have trained an image-based deep learning algorithm, the Faster R-CNN (Faster region-based convolutional neural network), to automatically detect and track the gilthead seabream, Sparus aurata, to search for individual differences in behaviour. We collected videos using a novel Raspberry Pi high throughput recording system attached to individual experimental behavioural arenas. From the continuous recording during behavioural assays, we acquired and labelled a total of 14,000 images and used them, along with data augmentation techniques, to train the network. Then, we evaluated the performance of our network at different training levels, increasing the number of images and applying data augmentation. For every validation step, we processed more than 52,000 images, with and without the presence of the gilthead seabream, in normal and altered (i.e., after the introduction of a non-familiar object to test for explorative behaviour) behavioural arenas. The final and best version of the neural network, trained with all the images and with data augmentation, reached an accuracy of 92,79% ± 6.78% [89.24–96.34] of correct classification and 10.25 ± 61.59 pixels [6.59-13.91] of fish positioning error. Our recording system based on a Raspberry Pi and a trained convolutional neural network provides a valuable non-invasive tool to automatically track fish movements in experimental arenas and, using the trajectories obtained during behavioural tests, to assay behavioural types.