Opposing Responses to Scarcity Emerge from Functionally Unique Sociality Drivers.

AbstractFrom biofilms to whale pods, organisms across taxa live in groups, thereby accruing numerous diverse benefits of sociality. All social organisms, however, pay the inherent cost of increased resource competition. One expects that when resources become scarce, this cost will increase, causing group sizes to decrease. Indeed, this occurs in some species, but there are also species for which group sizes remain stable or even increase under scarcity. What accounts for these opposing responses? We present a conceptual framework, literature review, and theoretical model demonstrating that differing responses to sudden resource shifts can be explained by which sociality benefit exerts the strongest selection pressure on a particular species. We categorize resource-related benefits of sociality into six functionally distinct classes and model their effect on the survival of individuals foraging in groups under different resource conditions. We find that whether, and to what degree, the optimal group size (or correlates thereof) increases, decreases, or remains constant when resource abundance declines depends strongly on the dominant sociality mechanism. Existing data, although limited, support our model predictions. Overall, we show that across a wide diversity of taxa, differences in how group size shifts in response to resource declines can be driven by differences in the primary benefits of sociality.

Effects of load mass and size on cooperative transport in ants over multiple transport challenges.

Some ant species cooperatively transport a wide range of extremely large, heavy food objects of various shapes and materials. While previous studies have examined how object mass and size affect the recruitment of additional workers, less is understood about how these attributes affect the rest of the transport process. Using artificial baits with independently varying mass and size, we reveal their effects on cooperative transport in Paratrechina longicornis across two transport challenges: movement initiation and obstacle navigation. As expected, object mass was tightly correlated with number of porters as workers adjust group size to the task. Mass affected performance similarly across the two challenges, with groups carrying heavy objects having lower performance. Yet, object size had differing effects depending on the challenge. While larger objects led to reduced performance during movement initiation - groups took longer to start moving these objects and had lower velocities - there was no evidence for this during obstacle navigation, and the opposite pattern was weakly supported. If a group struggles to start moving an object, it does not necessarily predict difficulty navigating around obstacles; groups should persist in trying to move 'difficult' objects, which may be easier to transport later in the process. Additionally, groups hitting obstacles were not substantially disrupted, and started moving again sooner than at the start, despite the nest direction being blocked. Paratrechina longicornis transport groups never failed, performing well at both challenges while carrying widely varying objects, and even transported a bait weighing 1900 times the mass of an individual.

Collective strategy for obstacle navigation during cooperative transport by ants.

Group cohesion and consensus have primarily been studied in the context of discrete decisions, but some group tasks require making serial decisions that build on one another. We examine such collective problem solving by studying obstacle navigation during cooperative transport in ants. In cooperative transport, ants work together to move a large object back to their nest. We blocked cooperative transport groups of Paratrechina longicornis with obstacles of varying complexity, analyzing groups' trajectories to infer what kind of strategy the ants employed. Simple strategies require little information, but more challenging, robust strategies succeed with a wider range of obstacles. We found that transport groups use a stochastic strategy that leads to efficient navigation around simple obstacles, and still succeeds at difficult obstacles. While groups navigating obstacles preferentially move directly toward the nest, they change their behavior over time; the longer the ants are obstructed, the more likely they are to move away from the nest. This increases the chance of finding a path around the obstacle. Groups rapidly changed directions and rarely stalled during navigation, indicating that these ants maintain consensus even when the nest direction is blocked. Although some decisions were aided by the arrival of new ants, at many key points, direction changes were initiated within the group, with no apparent external cause. This ant species is highly effective at navigating complex environments, and implements a flexible strategy that works for both simple and more complex obstacles.

Alignment with neighbours enables escape from dead ends in flocking models.

Coordinated movement in animal groups (flocks, schools, herds, etc.) is a classic and well-studied form of collective behaviour. Most theoretical studies consider agents in unobstructed spaces; however, many animals move in often complicated environments and must navigate around and through obstacles. Here we consider simulated agents behaving according to typical flocking rules, with the addition of repulsion from obstacles, and study their collective behaviour in environments with concave obstacles (dead ends). We find that groups of such agents heading for a goal can spontaneously escape dead ends without wall-following or other specialized behaviours, in what we term 'flocking escapes'. The mechanism arises when agents align with one another while heading away from the goal, forming a self-stable cluster that persists long enough to exit the obstacle and avoids becoming trapped again when turning back towards the goal. Solitary agents under the same conditions are never observed to escape. We show that alignment with neighbours reduces the effective turning speed of the group while letting individuals maintain high manoeuvrability when needed. The relative robustness of flocking escapes in our studies suggests that this emergent behaviour may be relevant for a variety of animal species.

Hysteresis stabilizes dynamic control of self-assembled army ant constructions.

Biological systems must adjust to changing external conditions, and their resilience depends on their control mechanisms. How is dynamic control implemented in noisy, decentralized systems? Army ants' self-assembled bridges are built on unstable features, like leaves, which frequently move. Using field experiments and simulations, we characterize the bridges' response as the gaps they span change in size, identify the control mechanism, and explore how this emerges from individuals' decisions. For a given gap size, bridges were larger after the gap increased rather than decreased. This hysteresis was best explained by an accumulator model, in which individual decisions to join or leave a bridge depend on the difference between its current and equilibrium state. This produces robust collective structures that adjust to lasting perturbations while ignoring small, momentary shifts. Our field data support separate joining and leaving cues; joining is prompted by high bridge performance and leaving by an excess of ants. This leads to stabilizing hysteresis, an important feature of many biological and engineered systems.

Academic ecosystems must evolve to support a sustainable postdoc workforce.

The postdoctoral workforce comprises a growing proportion of the science, technology, engineering and mathematics (STEM) community, and plays a vital role in advancing science. Postdoc professional development, however, remains rooted in outdated realities. We propose enhancements to postdoc-centred policies and practices to better align this career stage with contemporary job markets and work life. By facilitating productivity, wellness and career advancement, the proposed changes will benefit all stakeholders in postdoc success-including research teams, institutions, professional societies and the scientific community as a whole. To catalyse reform, we outline recommendations for (1) skills-based training tailored to the current career landscape, and (2) supportive policies and tools outlined in postdoc handbooks. We also invite the ecology and evolution community to lead further progressive reform.

Transforming mentorship in STEM by training scientists to be better leaders.

Effective mentoring is a key component of academic and career success that contributes to overall measures of productivity. Mentoring relationships also play an important role in mental health and in recruiting and retaining students from groups underrepresented in STEM fields. Despite these clear and measurable benefits, faculty generally do not receive mentorship training, and feedback mechanisms and assessment to improve mentoring in academia are limited. Ineffective mentoring can negatively impact students, faculty, departments, and institutions via decreased productivity, increased stress, and the loss of valuable research products and talented personnel. Thus, there are clear incentives to invest in and implement formal training to improve mentorship in STEM fields. Here, we outline the unique challenges of mentoring in academia and present results from a survey of STEM scientists that support both the need and desire for more formal mentorship training. Using survey results and the primary literature, we identify common behaviors of effective mentors and outline a set of mentorship best practices. We argue that these best practices, as well as the key qualities of flexibility, communication, and trust, are skills that can be taught to prospective and current faculty. We present a model and resources for mentorship training based on our research, which we successfully implemented at the University of Colorado, Boulder, with graduate students and postdocs. We conclude that such training is an important and cost-effective step toward improving mentorship in STEM fields.

Consensus or Deadlock? Consequences of Simple Behavioral Rules for Coordination in Group Decisions.

Coordinated collective behaviors often emerge from simple rules governing the interactions of individuals in groups. We model mechanisms of coordination among ants during cooperative transport, a challenging task that requires a consensus on travel direction. Our goal is to determine whether groups following simple behavioral rules can reach a consensus using minimal information. Using deterministic and stochastic models, we investigate behavioral factors that affect coordination. We define and investigate three types of behavioral rules governing individual behavior that differ in the information available: individuals either 1) have no information, 2) can measure transport success, or 3) measure success while also knowing whether they are aligned with the majority. We find that groups break deadlocks only if individuals more readily give up when they are going against the majority, corresponding to rule type 3 -such groups are "informed." These behavioral rules succeed through positive and negative feedbacks that are implemented in our model via a single mechanism: individuals only need to measure the relative group sizes to make effective decisions. We also find that groups reach consensus more quickly if they have either a shared bias, high sensitivity to group behavior, or finely tuned persistence. Each of these is a potential adaptation for efficient cooperative transport. This flexibility makes the behavioral rules in the informed case relatively robust to deficiencies in the individuals' capabilities. While inspired by ants, our results are generalizable to other collective decisions with deadlocks, and demonstrate that groups of behaviorally simple individuals with no memory and extremely limited information can break symmetry and reach a consensus in a decision between two equal options.

Animal behavior: social recognition in crickets.

A recent study of social recognition in crickets shows that decorated cricket females use self-referenced recognition information in their choice of mates. This allows the polyandrous females to choose novel, diverse mates.