Foraging synchrony drives resilience in human-dolphin mutualism.

Interactions between humans and nature have profound consequences, which rarely are mutually beneficial. Further, behavioral and environmental changes can turn human-wildlife cooperative interactions into conflicts, threatening their continued existence. By tracking fine-scale behavioral interactions between artisanal fishers and wild dolphins targeting migratory mullets, we reveal that foraging synchrony is key to benefiting both predators. Dolphins herd mullet schools toward the coast, increasing prey availability within the reach of the net-casting fishers, who gain higher foraging success-but only when matching the casting behavior with the dolphins' foraging cues. In turn, when dolphins approach the fishers' nets closely and cue fishers in, they dive for longer and modify their active foraging echolocation to match the time it takes for nets to sink and close over mullets-but only when fishers respond to their foraging cues appropriately. Using long-term demographic surveys, we show that cooperative foraging generates socioeconomic benefits for net-casting fishers and ca. 13% survival benefits for cooperative dolphins by minimizing spatial overlap with bycatch-prone fisheries. However, recent declines in mullet availability are threatening these short- and long-term benefits by reducing the foraging success of net-casting fishers and increasing the exposure of dolphins to bycatch in the alternative fisheries. Using a numerical model parametrized with our empirical data, we predict that environmental and behavioral changes are pushing this traditional human-dolphin cooperation toward extinction. We propose two possible conservation actions targeting fishers' behavior that could prevent the erosion of this century-old fishery, thereby safeguarding one of the last remaining cases of human-wildlife cooperation.

Evidence from sperm whale clans of symbolic marking in non-human cultures.

Culture, a pillar of the remarkable ecological success of humans, is increasingly recognized as a powerful force structuring nonhuman animal populations. A key gap between these two types of culture is quantitative evidence of symbolic markers-seemingly arbitrary traits that function as reliable indicators of cultural group membership to conspecifics. Using acoustic data collected from 23 Pacific Ocean locations, we provide quantitative evidence that certain sperm whale acoustic signals exhibit spatial patterns consistent with a symbolic marker function. Culture segments sperm whale populations into behaviorally distinct clans, which are defined based on dialects of stereotyped click patterns (codas). We classified 23,429 codas into types using contaminated mixture models and hierarchically clustered coda repertoires into seven clans based on similarities in coda usage; then we evaluated whether coda usage varied with geographic distance within clans or with spatial overlap between clans. Similarities in within-clan usage of both "identity codas" (coda types diagnostic of clan identity) and "nonidentity codas" (coda types used by multiple clans) decrease as space between repertoire recording locations increases. However, between-clan similarity in identity, but not nonidentity, coda usage decreases as clan spatial overlap increases. This matches expectations if sympatry is related to a measurable pressure to diversify to make cultural divisions sharper, thereby providing evidence that identity codas function as symbolic markers of clan identity. Our study provides quantitative evidence of arbitrary traits, resembling human ethnic markers, conveying cultural identity outside of humans, and highlights remarkable similarities in the distributions of human ethnolinguistic groups and sperm whale clans.

Social network architecture and the tempo of cumulative cultural evolution.

The ability to build upon previous knowledge-cumulative cultural evolution-is a hallmark of human societies. While cumulative cultural evolution depends on the interaction between social systems, cognition and the environment, there is increasing evidence that cumulative cultural evolution is facilitated by larger and more structured societies. However, such effects may be interlinked with patterns of social wiring, thus the relative importance of social network architecture as an additional factor shaping cumulative cultural evolution remains unclear. By simulating innovation and diffusion of cultural traits in populations with stereotyped social structures, we disentangle the relative contributions of network architecture from those of population size and connectivity. We demonstrate that while more structured networks, such as those found in multilevel societies, can promote the recombination of cultural traits into high-value products, they also hinder spread and make products more likely to go extinct. We find that transmission mechanisms are therefore critical in determining the outcomes of cumulative cultural evolution. Our results highlight the complex interaction between population size, structure and transmission mechanisms, with important implications for future research.

The importance of individual-to-society feedbacks in animal ecology and evolution.

The social decisions that individuals make-who to interact with and how frequently-give rise to social structure. The resulting social structure then determines how individuals interact with their surroundings-resources and risks, pathogens and predators, competitors and cooperators. However, despite intensive research on (a) how individuals make social decisions and (b) how social structure shapes social processes (e.g. cooperation, competition and conflict), there are still few studies linking these two perspectives. These perspectives represent two halves of a feedback loop: individual behaviour scales up to define the social environment, and this environment, in turn, feeds back by shaping the selective agents that drive individual behaviour. We first review well-established research areas that have captured both elements of this feedback loop-host-pathogen dynamics and cultural transmission. We then highlight areas where social structure is well studied but the two perspectives remain largely disconnected. Finally, we synthesise existing research on 14 distinct research topics to identify new prospects where the interplay between social structure and social processes are likely to be important but remain largely unexplored. Our review shows that the inherent links between individuals' traits, their social decisions, social structure and social evolution, warrant more consideration. By mapping the existing and missing connections among many research areas, our review highlights where explicitly considering social structure and the individual-to-society feedbacks can reveal new dimensions to old questions in ecology and evolution.

The role of habitat configuration in shaping animal population processes: a framework to generate quantitative predictions.

By shaping where individuals move, habitat configuration can fundamentally structure animal populations. Yet, we currently lack a framework for generating quantitative predictions about the role of habitat configuration in modulating population outcomes. To address this gap, we propose a modelling framework inspired by studies using networks to characterize habitat connectivity. We first define animal habitat networks, explain how they can integrate information about the different configurational features of animal habitats, and highlight the need for a bottom-up generative model that can depict realistic variations in habitat potential connectivity. Second, we describe a model for simulating animal habitat networks (available in the R package AnimalHabitatNetwork), and demonstrate its ability to generate alternative habitat configurations based on empirical data, which forms the basis for exploring the consequences of alternative habitat structures. Finally, we lay out three key research questions and demonstrate how our framework can address them. By simulating the spread of a pathogen within a population, we show how transmission properties can be impacted by both local potential connectivity and landscape-level characteristics of habitats. Our study highlights the importance of considering the underlying habitat configuration in studies linking social structure with population-level outcomes.

Linking structure and function in food webs: maximization of different ecological functions generates distinct food web structures.

Trophic interactions are central to ecosystem functioning, but the link between food web structure and ecosystem functioning remains obscure. Regularities (i.e. consistent patterns) in food web structure suggest the possibility of regularities in ecosystem functioning, which might be used to relate structure to function. We introduce a novel, genetic algorithm approach to simulate food webs with maximized throughput (a proxy for ecosystem functioning) and compare the structure of these simulated food webs to real empirical food webs using common metrics of food web structure. We repeat this analysis using robustness to secondary extinctions (a proxy for ecosystem resilience) instead of throughput to determine the relative contributions of ecosystem functioning and ecosystem resilience to food web structure. Simulated food webs that maximized robustness were similar to real food webs when connectance (i.e. levels of interaction across the food web) was high, but this result did not extend to food webs with low connectance. Simulated food webs that maximized throughput or a combination of throughput and robustness were not similar to any real food webs. Simulated maximum-throughput food webs differed markedly from maximum-robustness food webs, which suggests that maximizing different ecological functions can generate distinct food web structures. Based on our results, food web structure would appear to have a stronger relationship with ecosystem resilience than with ecosystem throughput. Our genetic algorithm approach is general and is well suited to large, realistically complex food webs. Genetic algorithms can incorporate constraints on structure and can generate outputs that can be compared directly to empirical data. Our method can be used to explore a range of maximization or minimization hypotheses, providing new perspectives on the links between structure and function in ecological systems.

Deep learning with self-supervision and uncertainty regularization to count fish in underwater images.

Effective conservation actions require effective population monitoring. However, accurately counting animals in the wild to inform conservation decision-making is difficult. Monitoring populations through image sampling has made data collection cheaper, wide-reaching and less intrusive but created a need to process and analyse this data efficiently. Counting animals from such data is challenging, particularly when densely packed in noisy images. Attempting this manually is slow and expensive, while traditional computer vision methods are limited in their generalisability. Deep learning is the state-of-the-art method for many computer vision tasks, but it has yet to be properly explored to count animals. To this end, we employ deep learning, with a density-based regression approach, to count fish in low-resolution sonar images. We introduce a large dataset of sonar videos, deployed to record wild Lebranche mullet schools (Mugil liza), with a subset of 500 labelled images. We utilise abundant unlabelled data in a self-supervised task to improve the supervised counting task. For the first time in this context, by introducing uncertainty quantification, we improve model training and provide an accompanying measure of prediction uncertainty for more informed biological decision-making. Finally, we demonstrate the generalisability of our proposed counting framework through testing it on a recent benchmark dataset of high-resolution annotated underwater images from varying habitats (DeepFish). From experiments on both contrasting datasets, we demonstrate our network outperforms the few other deep learning models implemented for solving this task. By providing an open-source framework along with training data, our study puts forth an efficient deep learning template for crowd counting aquatic animals thereby contributing effective methods to assess natural populations from the ever-increasing visual data.

Safeguarding human-wildlife cooperation.

Human-wildlife cooperation occurs when humans and free-living wild animals actively coordinate their behavior to achieve a mutually beneficial outcome. These interactions provide important benefits to both the human and wildlife communities involved, have wider impacts on the local ecosystem, and represent a unique intersection of human and animal cultures. The remaining active forms are human-honeyguide and human-dolphin cooperation, but these are at risk of joining several inactive forms (including human-wolf and human-orca cooperation). Human-wildlife cooperation faces a unique set of conservation challenges, as it requires multiple components-a motivated human and wildlife partner, a suitable environment, and compatible interspecies knowledge-which face threats from ecological and cultural changes. To safeguard human-wildlife cooperation, we recommend: (i) establishing ethically sound conservation strategies together with the participating human communities; (ii) conserving opportunities for human and wildlife participation; (iii) protecting suitable environments; (iv) facilitating cultural transmission of traditional knowledge; (v) accessibly archiving Indigenous and scientific knowledge; and (vi) conducting long-term empirical studies to better understand these interactions and identify threats. Tailored safeguarding plans are therefore necessary to protect these diverse and irreplaceable interactions. Broadly, our review highlights that efforts to conserve biological and cultural diversity should carefully consider interactions between human and animal cultures. Please see AfricanHoneyguides.com/abstract-translations for Kiswahili and Portuguese translations of the abstract.

The ability of artisanal fishers to recognize the dolphins they cooperate with.

BACKGROUND: Human-animal interactions with mutual benefits in the wild are rare. Such positive interactions seem to require an intricate knowledge from the human side on the animals' behavior and their habitat. In southern Brazil, dolphins and human net-casting fishers have specialized in a cooperative foraging, in which fishers report being able to identify and name dolphins. Here, we evaluate the consensus in their ability to recognize the individual dolphins they interact with. By investigating the reliability of this recognition process, we assess the pros and cons of relying on the fishers' traditional knowledge to further understand the behavior and ecology of dolphins at the individual level. We also assess the potential role of traditional knowledge for the maintenance of this unusual interaction. METHODS: We interviewed 38 fishers using a semi-structured questionnaire. During each interview, we evaluate their recognition ability of dolphins by showing high-quality photos of dorsal fins of different dolphins, asking questions about the dolphins' behavior and traits, and about how fishers recognize each dolphin. We also evaluated information about the fishers. Different indices were used to measure the fishers' ability to recognize dolphins via photos, and their consensus on individual identification. These indices were modeled as functions of traits of both dolphins and fishers to investigate which ones influence the recognition process. RESULTS: We found that fishers can primarily recognize dolphins by natural marks in the dorsal fin but there was little consensus in recognition. Fishers also tend to repeat the name of the most "popular" dolphins for different photos, indicating low reliability in individual recognition. We also found that fishers who learned from relatives (vertical learning) how to interact with dolphins tend to be more accurate and have higher consensus in dolphin recognition than those fishers who learned from friends (horizontal learning) or individually. CONCLUSION: Artisanal fishers have a deep understanding of the dolphins and the system they are inserted in. However, the lack of consensus in identifying individual dolphins herein reported indicates that using their traditional knowledge to further understand dolphin behavior and ecology at the individual level requires caution. Our study also suggests that the transmission of this tradition from parents to sons can be crucial to preserve such a unique human-animal positive interaction in its original form.

Social Barriers in Ecological Landscapes: The Social Resistance Hypothesis.

Across animal societies, individuals invest time and energy in social interactions. The social landscape that emerges from these interactions can then generate barriers that limit the ability of individuals to disperse to, and reproduce in, groups or populations. Therefore, social barriers can contribute to the difference between the physical capacity for movement through the habitat and subsequent gene flow. We call this contributing effect 'social resistance'. We propose that social resistance can act as an agent of selection on key life-history strategies and promote the evolution of social strategies that facilitate effective dispersal. By linking landscape genetics and social behaviour, the social resistance hypothesis generates predictions integrating dispersal, connectivity, and life-history evolution.

Multilevel Organisation of Animal Sociality.

Multilevel societies (MLSs), stable nuclear social units within a larger collective encompassing multiple nested social levels, occur in several mammalian lineages. Their architectural complexity and size impose specific demands on their members requiring adaptive solutions in multiple domains. The functional significance of MLSs lies in their members being equipped to reap the benefits of multiple group sizes. Here, we propose a unifying terminology and operational definition of MLS. To identify new avenues for integrative research, we synthesise current literature on the selective pressures underlying the evolution of MLSs and their implications for cognition, intersexual conflict, and sexual selection. Mapping the drivers and consequences of MLS provides a reference point for the social evolution of many taxa, including our own species.

Causes and consequences of female centrality in cetacean societies.

Cetaceans are fully aquatic predatory mammals that have successfully colonized virtually all marine habitats. Their adaptation to these habitats, so radically different from those of their terrestrial ancestors, can give us comparative insights into the evolution of female roles and kinship in mammalian societies. We provide a review of the diversity of such roles across the Cetacea, which are unified by some key and apparently invariable life-history features. Mothers are uniparous, while paternal care is completely absent as far as we currently know. Maternal input is extensive, lasting months to many years. Hence, female reproductive rates are low, every cetacean calf is a significant investment, and offspring care is central to female fitness. Here strategies diverge, especially between toothed and baleen whales, in terms of mother-calf association and related social structures, which range from ephemeral grouping patterns to stable, multi-level, societies in which social groups are strongly organized around female kinship. Some species exhibit social and/or spatial philopatry in both sexes, a rare phenomenon in vertebrates. Communal care can be vital, especially among deep-diving species, and can be supported by female kinship. Female-based sociality, in its diverse forms, is therefore a prevailing feature of cetacean societies. Beyond the key role in offspring survival, it provides the substrate for significant vertical and horizontal cultural transmission, as well as the only definitive non-human examples of menopause. This article is part of the theme issue 'The evolution of female-biased kinship in humans and other mammals'.

Simple foraging rules in competitive environments can generate socially structured populations.

Social vertebrates commonly form foraging groups whose members repeatedly interact with one another and are often genetically related. Many species also exhibit within-population specializations, which can range from preferences to forage in particular areas through to specializing on the type of prey they catch. However, within-population structure in foraging groups, behavioral homogeneity in foraging behavior, and relatedness could be outcomes of behavioral interactions rather than underlying drivers. We present a simple process by which grouping among foragers emerges and is maintained across generations. We introduce agent-based models to investigate (1) whether a simple rule (keep foraging with the same individuals when you were successful) leads to stable social community structure, and (2) whether this structure is robust to demographic changes and becomes kin-structured over time. We find the rapid emergence of kin-structured populations and the presence of foraging groups that control, or specialize on, a particular food resource. This pattern is strongest in small populations, mirroring empirical observations. Our results suggest that group stability can emerge as a product of network self-organization and, in doing so, may provide the necessary conditions for the evolution of more sophisticated processes, such as social learning. This taxonomically general social process has implications for our understanding of the links between population, genetic, and social structures.

Interaction paths promote module integration and network-level robustness of spliceosome to cascading effects.

The functionality of distinct types of protein networks depends on the patterns of protein-protein interactions. A problem to solve is understanding the fragility of protein networks to predict system malfunctioning due to mutations and other errors. Spectral graph theory provides tools to understand the structural and dynamical properties of a system based on the mathematical properties of matrices associated with the networks. We combined two of such tools to explore the fragility to cascading effects of the network describing protein interactions within a key macromolecular complex, the spliceosome. Using S. cerevisiae as a model system we show that the spliceosome network has more indirect paths connecting proteins than random networks. Such multiplicity of paths may promote routes to cascading effects to propagate across the network. However, the modular network structure concentrates paths within modules, thus constraining the propagation of such cascading effects, as indicated by analytical results from the spectral graph theory and by numerical simulations of a minimal mathematical model parameterized with the spliceosome network. We hypothesize that the concentration of paths within modules favors robustness of the spliceosome against failure, but may lead to a higher vulnerability of functional subunits, which may affect the temporal assembly of the spliceosome. Our results illustrate the utility of spectral graph theory for identifying fragile spots in biological systems and predicting their implications.

Nestedness across biological scales.

Biological networks pervade nature. They describe systems throughout all levels of biological organization, from molecules regulating metabolism to species interactions that shape ecosystem dynamics. The network thinking revealed recurrent organizational patterns in complex biological systems, such as the formation of semi-independent groups of connected elements (modularity) and non-random distributions of interactions among elements. Other structural patterns, such as nestedness, have been primarily assessed in ecological networks formed by two non-overlapping sets of elements; information on its occurrence on other levels of organization is lacking. Nestedness occurs when interactions of less connected elements form proper subsets of the interactions of more connected elements. Only recently these properties began to be appreciated in one-mode networks (where all elements can interact) which describe a much wider variety of biological phenomena. Here, we compute nestedness in a diverse collection of one-mode networked systems from six different levels of biological organization depicting gene and protein interactions, complex phenotypes, animal societies, metapopulations, food webs and vertebrate metacommunities. Our findings suggest that nestedness emerge independently of interaction type or biological scale and reveal that disparate systems can share nested organization features characterized by inclusive subsets of interacting elements with decreasing connectedness. We primarily explore the implications of a nested structure for each of these studied systems, then theorize on how nested networks are assembled. We hypothesize that nestedness emerges across scales due to processes that, although system-dependent, may share a general compromise between two features: specificity (the number of interactions the elements of the system can have) and affinity (how these elements can be connected to each other). Our findings suggesting occurrence of nestedness throughout biological scales can stimulate the debate on how pervasive nestedness may be in nature, while the theoretical emergent principles can aid further research on commonalities of biological networks.

Cultural turnover among Galápagos sperm whales.

While populations may wax and wane, it is rare for an entire population to be replaced by a completely different set of individuals. We document the large-scale relocation of cultural groups of sperm whale off the Galápagos Islands, in which two sympatric vocal clans were entirely replaced by two different ones. Between 1985 and 1999, whales from two clans (called Regular and Plus-One) defined by cultural dialects in coda vocalizations were repeatedly photo-identified off Galápagos. Their occurrence in the area declined through the 1990s; by 2000, none remained. We reassessed Galápagos sperm whales in 2013-2014, identifying 463 new females. However, re-sighting rates were low, with no matches with the Galápagos 1985-1999 population, suggesting an eastward shift to coastal areas. Their vocal repertoires matched those of two other clans (called Short and Four-Plus) found across the Pacific but previously rare or absent around Galápagos. The mechanisms behind this cultural turnover may include large-scale environmental regime shifts favouring clan-specific foraging strategies, and a response to heavy whaling in the region involving redistribution of surviving whales into high-quality habitats. The fall and rise of sperm whale cultures off Galápagos reflect the structuring of the Pacific population into large, enduring clans with dynamic ranges. Long-lasting clan membership illustrates how culture can be bound up in the structure and dynamics of animal populations and so how tracking cultural traits can reveal large-scale population shifts.

The missing metric: quantifying contributions of reviewers.

The number of contributing reviewers often outnumbers the authors of publications. This has led to apathy towards reviewing and the conclusion that the peer-review system is broken. Given the trade-offs between submitting and reviewing manuscripts, reviewers and authors naturally want visibility for their efforts. While study after study has called for revolutionizing publication practices, the current paradigm does not recognize reviewers' time and expertise. We propose the R-index as a simple way to quantify scientists' contributions as reviewers. We modelled its performance using simulations based on real data to show that early-mid career scientists, who complete high-quality reviews of longer manuscripts within their field, can perform as well as leading scientists reviewing only for high-impact journals. By giving citeable academic recognition for reviewing, R-index will encourage more participation with better reviews, regardless of the career stage. Moreover, the R-index will allow editors to exploit scores to manage and improve their review team, and for journals to promote high average scores as signals of a practical and efficient service to authors. Peer-review is a pervasive necessity across disciplines and the simple utility of this missing metric will credit a valuable aspect of academic productivity without having to revolutionize the current peer-review system.

Multilevel animal societies can emerge from cultural transmission.

Multilevel societies, containing hierarchically nested social levels, are remarkable social structures whose origins are unclear. The social relationships of sperm whales are organized in a multilevel society with an upper level composed of clans of individuals communicating using similar patterns of clicks (codas). Using agent-based models informed by an 18-year empirical study, we show that clans are unlikely products of stochastic processes (genetic or cultural drift) but likely originate from cultural transmission via biased social learning of codas. Distinct clusters of individuals with similar acoustic repertoires, mirroring the empirical clans, emerge when whales learn preferentially the most common codas (conformism) from behaviourally similar individuals (homophily). Cultural transmission seems key in the partitioning of sperm whales into sympatric clans. These findings suggest that processes similar to those that generate complex human cultures could not only be at play in non-human societies but also create multilevel social structures in the wild.

The network organization of protein interactions in the spliceosome is reproduced by the simple rules of food-web models.

The network structure of biological systems provides information on the underlying processes shaping their organization and dynamics. Here we examined the structure of the network depicting protein interactions within the spliceosome, the macromolecular complex responsible for splicing in eukaryotic cells. We show the interactions of less connected spliceosome proteins are nested subsets of the connections of the highly connected proteins. At the same time, the network has a modular structure with groups of proteins sharing similar interaction patterns. We then investigated the role of affinity and specificity in shaping the spliceosome network by adapting a probabilistic model originally designed to reproduce food webs. This food-web model was as successful in reproducing the structure of protein interactions as it is in reproducing interactions among species. The good performance of the model suggests affinity and specificity, partially determined by protein size and the timing of association to the complex, may be determining network structure. Moreover, because network models allow building ensembles of realistic networks while encompassing uncertainty they can be useful to examine the dynamics and vulnerability of intracelullar processes. Unraveling the mechanisms organizing the spliceosome interactions is important to characterize the role of individual proteins on splicing catalysis and regulation.