How ecology shapes exploitation: a framework to predict the behavioural response of human and animal foragers along exploration-exploitation trade-offs

Intraspecific variability of social structure and linked foraging behavior in females of a widespread bat species (Phyllostomus hastatus)

Intraspecific variation in morphology and behavior is widespread, especially in species with large distribution ranges. This includes foraging which can vary according to the local resource landscape. How this may be linked to differences in social structure, especially in socially foraging species is less known. Greater spear-nosed bats are well known for their large repertoire of often highly complex social behaviors. In Trinidad, they form stable groups of unrelated females that recruit other members to temporally unpredictable flowering balsa trees. We compared these findings with a dataset of capture data, GPS tracks, and observations collected over six years in a colony in Panamá. We found profound differences in the foraging behavior and group stability of Phyllostomus hastatus during the dry season where social behaviors were expected. Female bats did not coordinate commutes to exploit distinct foraging resources as a group. Instead, females commuted individually to very distant foraging areas which overlapped between groups. Linked to this we found groups to be unstable in size over the short and long term. Our findings highlight the large intraspecific variation and indicate a strong influence of the local resource landscape and associated benefits of social foraging on the social structure in these bats and possibly many other animals.

Consistent long-distance foraging flights across years and seasons at colony level in a neotropical bat

All foraging animals face a trade-off: how much time should they invest in exploitation of known resources versus exploration to discover new resources? For group-living central place foragers, this balance is challenging. Due to the nature of their movement patterns, exploration and exploitation are often mutually exclusive, while the availability of social information may discourage individuals from exploring. To examine these trade-offs, we GPS-tracked groups of greater spear-nosed bats (Phyllostomus hastatus) from three colonies on Isla Colón, Panamá. During the dry season, when these omnivores forage on the nectar of unpredictable balsa flowers, bats consistently travelled long distances to remote, colony-specific foraging areas, bypassing flowering trees closer to their roosts. They continued using these areas in the wet season, when feeding on a diverse, presumably ubiquitous diet, but also visited other, similarly distant foraging areas. Foraging areas were shared within but not always between colonies. Our longitudinal dataset suggests that bats from each colony invest in long-distance commutes to socially learned shared foraging areas, bypassing other available food patches. Rather than exploring nearby resources, these bats exploit colony-specific foraging locations that appear to be culturally transmitted. These results give insight into how social animals might diverge from optimal foraging.

Impact of captivity and natural habitats on gut microbiome in Epinephelus akaara across seasons

BACKGROUND

The gut microbiota significantly influences the health and growth of red-spotted grouper (Epinephelus akaara), a well-known commercial marine fish from Fujian Province in southern China. However, variations in survival strategies and seasons can impact the stability of gut microbiota data, rendering it inaccurate in reflecting the state of gut microbiota. Which impedes the effective enhancement of aquaculture health through a nuanced understanding of gut microbiota. Inspired by this, we conducted a comprehensive analysis of the gut microbiota of wild and captive E. akaara in four seasons.

RESULTS

Seventy-two E. akaara samples were collected from wild and captive populations in Dongshan city, during four different seasons. Four sections of the gut were collected to obtain comprehensive information on the gut microbial composition and sequenced using 16S rRNA next-generation Illumina MiSeq. We observed the highest gut microbial diversity in both captive and wild E. akaara during the winter season, and identified strong correlations with water temperature using Mantel analysis. Compared to wild E. akaara, we found a more complex microbial network in captive E. akaara, as evidenced by increased abundance of Bacillaceae, Moraxellaceae and Enterobacteriaceae. In contrast, Vibrionaceae, Clostridiaceae, Flavobacteriaceae and Rhodobacteraceae were found to be more active in wild E. akaara. However, some core microorganisms, such as Firmicutes and Photobacterium, showed similar distribution patterns in both wild and captive groups. Moreover, we found the common community composition and distribution characteristics of top 10 core microbes from foregut to hindgut in E. akaara.

CONCLUSIONS

Collectively, the study provides relatively more comprehensive description of the gut microbiota in E. akaara, taking into account survival strategies and temporal dimensions, which yields valuable insights into the gut microbiota of E. akaara and provides a valuable reference to its aquaculture.

Exploration-exploitation model of moth-inspired olfactory navigation

Navigation of male moths towards females during the mating search offers a unique perspective on the exploration-exploitation (EE) model in decision-making. This study uses the EE model to explain male moth pheromone-driven flight paths. Wind tunnel measurements and three-dimensional tracking using infrared cameras have been leveraged to gain insights into male moth behaviour. During the experiments in the wind tunnel, disturbance to the airflow has been added and the effect of increased fluctuations on moth flights has been analysed, in the context of the proposed EE model. The exploration and exploitation phases are separated using a genetic algorithm to the experimentally obtained dataset of moth three-dimensional trajectories. First, the exploration-to-exploitation rate (EER) increases with distance from the source of the female pheromone is demonstrated, which can be explained in the context of the EE model. Furthermore, our findings reveal a compelling relationship between EER and increased flow fluctuations near the pheromone source. Using an olfactory navigation simulation and our moth-inspired navigation model, the phenomenon where male moths exhibit an enhanced EER as turbulence levels increase is explained. This research extends our understanding of optimal navigation strategies based on general biological EE models and supports the development of bioinspired navigation algorithms.

Visual social information use in collective foraging

Collective dynamics emerge from individual-level decisions, yet we still poorly understand the link between individual-level decision-making processes and collective outcomes in realistic physical systems. Using collective foraging to study the key trade-off between personal and social information use, we present a mechanistic, spatially-explicit agent-based model that combines individual-level evidence accumulation of personal and (visual) social cues with particle-based movement. Under idealized conditions without physical constraints, our mechanistic framework reproduces findings from established probabilistic models, but explains how individual-level decision processes generate collective outcomes in a bottom-up way. In clustered environments, groups performed best if agents reacted strongly to social information, while in uniform environments, individualistic search was most beneficial. Incorporating different real-world physical and perceptual constraints profoundly shaped collective performance, and could even buffer maladaptive herding by facilitating self-organized exploration. Our study uncovers the mechanisms linking individual cognition to collective outcomes in human and animal foraging and paves the way for decentralized robotic applications.

Collective incentives reduce over-exploitation of social information in unconstrained human groups

Collective dynamics emerge from countless individual decisions. Yet, we poorly understand the processes governing dynamically-interacting individuals in human collectives under realistic conditions. We present a naturalistic immersive-reality experiment where groups of participants searched for rewards in different environments, studying how individuals weigh personal and social information and how this shapes individual and collective outcomes. Capturing high-resolution visual-spatial data, behavioral analyses revealed individual-level gains-but group-level losses-of high social information use and spatial proximity in environments with concentrated (vs. distributed) resources. Incentivizing participants at the group (vs. individual) level facilitated adaptation to concentrated environments, buffering apparently excessive scrounging. To infer discrete choices from unconstrained interactions and uncover the underlying decision mechanisms, we developed an unsupervised Social Hidden Markov Decision model. Computational results showed that participants were more sensitive to social information in concentrated environments frequently switching to a social relocation state where they approach successful group members. Group-level incentives reduced participants' overall responsiveness to social information and promoted higher selectivity over time. Finally, mapping group-level spatio-temporal dynamics through time-lagged regressions revealed a collective exploration-exploitation trade-off across different timescales. Our study unravels the processes linking individual-level strategies to emerging collective dynamics, and provides tools to investigate decision-making in freely-interacting collectives.

Rhythm of relationships in a social fish over the course of a full year in the wild

BACKGROUND

Animals are expected to adjust their social behaviour to cope with challenges in their environment. Therefore, for fish populations in temperate regions with seasonal and daily environmental oscillations, characteristic rhythms of social relationships should be pronounced. To date, most research concerning fish social networks and biorhythms has occurred in artificial laboratory environments or over confined temporal scales of days to weeks. Little is known about the social networks of wild, freely roaming fish, including how seasonal and diurnal rhythms modulate social networks over the course of a full year. The advent of high-resolution acoustic telemetry enables us to quantify detailed social interactions in the wild over time-scales sufficient to examine seasonal rhythms at whole-ecosystems scales. Our objective was to explore the rhythms of social interactions in a social fish population at various time-scales over one full year in the wild by examining high-resolution snapshots of a dynamic social network.

METHODS

To that end, we tracked the behaviour of 36 adult common carp, Cyprinus carpio, in a 25 ha lake and constructed temporal social networks among individuals across various time-scales, where social interactions were defined by proximity. We compared the network structure to a temporally shuffled null model to examine the importance of social attraction, and checked for persistent characteristic groups over time.

RESULTS

The clustering within the carp social network tended to be more pronounced during daytime than nighttime throughout the year. Social attraction, particularly during daytime, was a key driver for interactions. Shoaling behavior substantially increased during daytime in the wintertime, whereas in summer carp interacted less frequently, but the interaction duration increased. Therefore, smaller, characteristic groups were more common in the summer months and during nighttime, where the social memory of carp lasted up to two weeks.

CONCLUSIONS

We conclude that social relationships of carp change diurnally and seasonally. These patterns were likely driven by predator avoidance, seasonal shifts in lake temperature, visibility, forage availability and the presence of anoxic zones. The techniques we employed can be applied generally to high-resolution biotelemetry data to reveal social structures across other fish species at ecologically realistic scales.

The value of spatial experience and group size for ant colonies in direct competition

Animals often search for food more efficiently with experience. However, the contribution of experience to foraging success under direct competition has rarely been examined. Here we used colonies of an individually foraging desert ant to investigate the value of spatial experience. First, we trained worker groups of equal numbers to solve either a complex or a simple maze. We then tested pairs of both groups against one another in reaching a food reward. This task required solving the same complex maze that one of the groups had been trained in, to determine which group would exploit better the food reward. The worker groups previously trained in the complex mazes reached the food reward faster and more of these workers fed on the food than those trained in simple mazes, but only in the intermediate size group. To determine the relative importance of group size versus spatial experience in exploiting food patches, we then tested smaller trained worker groups against larger untrained ones. The larger groups outcompeted the smaller ones, despite the latter's advantage of spatial experience. The contribution of spatial experience, as found here, appears to be small, and depends on group size: an advantage of a few workers of the untrained group over the trained group negates its benefits.

A conceptual framework to predict social information use based on food ephemerality and individual resource requirements

Environmental variability poses a range of challenges to foraging animals trying to meet their energetic needs. Where food patches are unpredictable but shareable, animals can use social information to locate patches more efficiently or reliably. However, resource unpredictability can be heterogeneous and complex. The behavioural strategies animals employ to exploit such resources also vary, particularly if, when, and where animals use available social information. We reviewed the literature on social information use by foraging animals and developed a novel framework that integrates four elements - (1) food resource persistence; (2) the relative value of social information use; (3) behavioural context (opportunistic or coordinated); and (4) location of social information use - to predict and characterize four strategies of social information use - (1) local enhancement; (2) group facilitation; (3) following; and (4) recruitment. We validated our framework by systematically reviewing the growing empirical literature on social foraging in bats, an ideal model taxon because they exhibit extreme diversity in ecological niche and experience low predation risk while foraging but function at high energy expenditures, which selects for efficient foraging behaviours. Our framework's predictions agreed with the observed natural behaviour of bats and identified key knowledge gaps for future studies. Recent advancements in technology, methods, and analysis will facilitate additional studies in bats and other taxa to further test the framework and our conception of the ecological and evolutionary forces driving social information use. Understanding the links between food distribution, social information use, and foraging behaviour will help elucidate social interactions, group structure, and the evolution of sociality for species across the animal kingdom.

Wild Boar Survives in a Landscape That Prohibits Anthropogenic Persecution

Geopolitical borderlands are politically sensitive areas and biodiversity hotspots, strictly controlled by the government and military. How to ensure political security, while protecting the biodiversity in borderlands is a problem for ecologists and governments. In this study, the nest site selection of the wild boar Sus scrofa was a case study in the Sino-Russia borderland to understand the survival strategy of wild life under anthropogenic pressure. We investigated (a) how the spatial distribution of anthropogenic pressure and wild boar nests in the borderland and (b) how anthropogenic pressure and the border influence on the wild boars’ nest site selection. The Getis-Ord Gi* analysis was used to analyze the distribution patterns of wild boar nest sites and anthropogenic pressures in the borderland, the Structural Equation Models was used to explore the influence of border, roads, settlements, agricultural land, grassland and anthropogenic pressure on wild boars’ nest site selection. The results indicated that wild boar nest sites are close to the border, roads and agricultural land and away from settlements and grassland. Regardless of the combination of anthropogenic pressure, wild boars make the most advantageous choice and prefer to be closer to the borderland. We speculated that military control played a vital role in borderlands for animal protection under anthropogenic pressure. Wild boars benefit from the prohibition of anthropogenic persecution due to military control. Compared with existing measures, we suggest a different protection/wildlife management strategy, what we need to do may be to prohibit anthropogenic persecution rather than perform other human interventions to protect animals. However, for a species with trouble potential, we need to base our conservation strategies on the recovery of top predators, and play the community control role of top predators to avoid the occurrence of trouble.

Collective behaviour can stabilize ecosystems

Collective behaviour is common in bacteria, plants and animals, and therefore occurs across ecosystems, from biofilms to cities. With collective behaviour, social interactions among individuals propagate to affect the behaviour of groups, whereas group-level responses in turn affect individual behaviour. These cross-scale feedback loops between individuals, populations and their environments can provide fitness benefits, such as the efficient exploitation of uncertain resources, as well as costs, such as increased resource competition. Although the social mechanics of collective behaviour are increasingly well-studied, its role in ecosystems remains poorly understood. Here we introduce collective movement into a model of consumer-resource dynamics to demonstrate that collective behaviour can attenuate consumer-resource cycles and promote species coexistence. We focus on collective movement as a particularly well-understood example of collective behaviour. Adding collective movement to canonical unstable ecological scenarios causes emergent social-ecological feedback, which mitigates conditions that would otherwise result in extinction. Collective behaviour could play a key part in the maintenance of biodiversity.

Collective predator evasion: Putting the criticality hypothesis to the test

According to the criticality hypothesis, collective biological systems should operate in a special parameter region, close to so-called critical points, where the collective behavior undergoes a qualitative change between different dynamical regimes. Critical systems exhibit unique properties, which may benefit collective information processing such as maximal responsiveness to external stimuli. Besides neuronal and gene-regulatory networks, recent empirical data suggests that also animal collectives may be examples of self-organized critical systems. However, open questions about self-organization mechanisms in animal groups remain: Evolutionary adaptation towards a group-level optimum (group-level selection), implicitly assumed in the "criticality hypothesis", appears in general not reasonable for fission-fusion groups composed of non-related individuals. Furthermore, previous theoretical work relies on non-spatial models, which ignore potentially important self-organization and spatial sorting effects. Using a generic, spatially-explicit model of schooling prey being attacked by a predator, we show first that schools operating at criticality perform best. However, this is not due to optimal response of the prey to the predator, as suggested by the "criticality hypothesis", but rather due to the spatial structure of the prey school at criticality. Secondly, by investigating individual-level evolution, we show that strong spatial self-sorting effects at the critical point lead to strong selection gradients, and make it an evolutionary unstable state. Our results demonstrate the decisive role of spatio-temporal phenomena in collective behavior, and that individual-level selection is in general not a viable mechanism for self-tuning of unrelated animal groups towards criticality.

Causal evidence for the adaptive benefits of social foraging in the wild

Sociality is a fundamental organizing principle across taxa, thought to come with a suite of adaptive benefits. However, making causal inferences about these adaptive benefits requires experimental manipulation of the social environment, which is rarely feasible in the field. Here we manipulated the number of conspecifics in Trinidadian guppies (Poecilia reticulata) in the wild, and quantified how this affected a key benefit of sociality, social foraging, by investigating several components of foraging success. As adaptive benefits of social foraging may differ between sexes, we studied males and females separately, expecting females, the more social and risk-averse sex in guppies, to benefit more from conspecifics. Conducting over 1600 foraging trials, we found that in both sexes, increasing the number of conspecifics led to faster detection of novel food patches and a higher probability of feeding following detection of the patch, resulting in greater individual resource consumption. The extent of the latter relationship differed between the sexes, with males unexpectedly exhibiting a stronger social benefit. Our study provides rare causal evidence for the adaptive benefits of social foraging in the wild, and highlights that sex differences in sociality do not necessarily imply an unequal ability to profit from the presence of others.

Fisheries-induced selection against schooling behaviour in marine fishes

Group living is a common strategy used by fishes to improve their fitness. While sociality is associated with many benefits in natural environments, including predator avoidance, this behaviour may be maladaptive in the Anthropocene. Humans have become the dominant predator in many marine systems, with modern fishing gear developed to specifically target groups of schooling species. Therefore, ironically, behavioural strategies which evolved to avoid non-human predators may now actually make certain fish more vulnerable to predation by humans. Here, we use an individual-based model to explore the evolution of fish schooling behaviour in a range of environments, including natural and human-dominated predation conditions. In our model, individual fish may leave or join groups depending on their group-size preferences, but their experienced group size is also a function of the preferences of others in the population. Our model predicts that industrial fishing selects against individual-level behaviours that produce large groups. However, the relationship between fishing pressure and sociality is nonlinear, and we observe discontinuities and hysteresis as fishing pressure is increased or decreased. Our results suggest that industrial fishing practices could be altering fishes' tendency to school, and that social behaviour should be added to the list of traits subject to fishery-induced evolution.

Ecological impacts of human-induced animal behaviour change

A growing body of literature has documented myriad effects of human activities on animal behaviour, yet the ultimate ecological consequences of these behavioural shifts remain largely uninvestigated. While it is understood that, in the absence of humans, variation in animal behaviour can have cascading effects on species interactions, community structure and ecosystem function, we know little about whether the type or magnitude of human-induced behavioural shifts translate into detectable ecological change. Here we synthesise empirical literature and theory to create a novel framework for examining the range of behaviourally mediated pathways through which human activities may affect different ecosystem functions. We highlight the few empirical studies that show the potential realisation of some of these pathways, but also identify numerous factors that can dampen or prevent ultimate ecosystem consequences. Without a deeper understanding of these pathways, we risk wasting valuable resources on mitigating behavioural effects with little ecological relevance, or conversely mismanaging situations in which behavioural effects do drive ecosystem change. The framework presented here can be used to anticipate the nature and likelihood of ecological outcomes and prioritise management among widespread human-induced behavioural shifts, while also suggesting key priorities for future research linking humans, animal behaviour and ecology.

Foraging decisions as multi-armed bandit problems: Applying reinforcement learning algorithms to foraging data

Finding resources is crucial for animals to survive and reproduce, but the understanding of the decision-making underlying foraging decisions to explore new resources and exploit old resources remains lacking. Theory predicts an 'exploration-exploitation trade-off' where animals must balance their effort into either stay and exploit a seemingly good resource or move and explore the environment. To date, however, it has been challenging to generate flexible yet tractable statistical models that can capture this trade-off, and our understanding of foraging decisions is limited. Here, I suggest that foraging decisions can be seen as multi-armed bandit problems, and apply deterministic (i.e., the Upper-Confidence-Bound or 'UCB') and Bayesian algorithms (i.e., Thompson Sampling or 'TS') to demonstrate how these algorithms generate testable a priori predictions from simulated data. Next, I use UCB and TS to analyse empirical foraging data from the tephritid fruit fly larvae Bactrocera tryoni to provide a qualitative and quantitative framework to quantify animal foraging behaviour. Qualitative analysis revealed that TS display shorter exploration period than UCB, although both converged to similar qualitative results. Quantitative analysis demonstrated that, overall, UCB is more accurate in predicting the observed foraging patterns compared with TS, even though both algorithms failed to quantitatively estimate the empirical foraging patterns in high-density groups (i.e., groups with 50 larvae and, more strikingly, groups with 100 larvae), likely due to the influence of intraspecific competition on animal behaviour. The framework proposed here demonstrates how reinforcement learning algorithms can be used to model animal foraging decisions.