The organization of soil disposal by ants

Colonies of Pheidole ambigua ants excavate soil and drop it outside the nest entrance. The deposition of thousands of loads leads to the formation of regular ring-shaped piles. How is this pattern generated? This study investigated soil pile formation on level and sloping surfaces, both empirically and using an agent-based model. We found that ants drop soil preferentially in the direction in which the slope is least steeply uphill from the nest entrance, both when adding to an existing pile and when starting a new pile. Ants respond to cues from local slope to choose downhill directions. Ants walking on a slope increase the frequency and magnitude of changes in direction, and more of these changes of direction take them downhill than uphill. Also, ants carrying soil on a slope wait longer before dropping their soil compared to ants on a level plane. These mechanisms combine to focus soil dropping in the downhill direction, without the necessity of a direct relationship between slope and probability of dropping soil. These empirically determined rules were used to simulate soil disposal. The slight preference for turning downhill measured empirically was shown in the model to be sufficient to generate biologically realistic patterns of soil dumping when combined with memory of the direction of previous trips. From simple rules governing individual behaviour an overall pattern emerges, which is appropriate to the environment and allows a rapid response to changes

Local termination criteria for Swarm Intelligence: a comparison between local Stochastic Diffusion Search and ant nest-site selection

Stochastic diffusion search (SDS) is a global Swarm Intelligence optimisation technique based on the behaviour of ants, rooted in the partial evaluation of an objective function and direct communication between agents. Although population based decision mechanisms employed by many Swarm Intelligence methods can suffer poor convergence resulting in ill-defined halting criteria and loss of the best solution, as a result of its resource allocation mechanism, the solutions found by Stochastic Diffusion Search enjoy excellent stability. Previous implementations of SDS have deployed stopping criteria derived from global properties of the agent population; this paper examines new local SDS halting criteria and compares their performance with ‘quorum sensing’ (a termination criterion naturally deployed by some species of tandem-running ants). In this chapter we discuss two experiments investigating the robustness and efficiency of the new local termination criteria; our results demonstrate these to be (a) effectively as robust as the classical SDS termination criteria and (b) almost three times faster

A longitudinal study of nest occupancy, trail networks and foraging in a polydomous wood ant population

Most ant colonies live in a single nest (monodomy) or a group of nests (polydomy). However, the length of time for which nests are inhabited varies significantly between different species. Although colonies of some species frequently move nest sites, in others, colonies inhabit the same nest or group of nests for many years. Similarly, in some species foraging and resource-sharing trails are highly dynamic, while in other species trails are used for years. Wood ants are a group of keystone species that inhabit many northern hemisphere woodlands, where they are important predators of invertebrates and indirectly act as herbivores through the farming of aphids. Wood ant colonies exhibit both monodomy and polydomy, and can inhabit nests for many years. Trails in wood ant colonies are also thought to be relatively stable. However, information about colony dynamics is mostly anecdotal as, until now, no longitudinal datasets have been collected. In this study, we collected data from ten polydomous wood ant colonies annually for 8 years and a subset of four colonies 16 times over 2 years. We found that most polydomous wood ant nests are abandoned in the first 2 years after being constructed and are more likely to be abandoned in the latter part of the active season. However, the rate of nest abandonment decreases after 2 years and is lower in larger nests. We also found that wood ant trails are relatively static within an active season and become more static later in the season as trails become established.The NERC ACCE DTPhttp://link.springer.com/journal/40am2020Zoology and Entomolog

From early markers to neuro-developmental mechanisms of autism

A fast growing field, the study of infants at risk because of having an older sibling with autism (i.e. infant sibs) aims to identify the earliest signs of this disorder, which would allow for earlier diagnosis and intervention. More importantly, we argue, these studies offer the opportunity to validate existing neuro-developmental models of autism against experimental evidence. Although autism is mainly seen as a disorder of social interaction and communication, emerging early markers do not exclusively reflect impairments of the “social brain”. Evidence for atypical development of sensory and attentional systems highlight the need to move away from localized deficits to models suggesting brain-wide involvement in autism pathology. We discuss the implications infant sibs findings have for future work into the biology of autism and the development of interventions

Second order swarm intelligence

An artificial Ant Colony System (ACS) algorithm to solve general-purpose combinatorial Optimization Problems (COP) that extends previous AC models [21] by the inclusion of a negative pheromone, is here described. Several Travelling Salesman Problem (TSP) were used as benchmark. We show that by using two different sets of pheromones, a second-order co-evolved compromise between positive and negative feedbacks achieves better results than single positive feedback systems. The algorithm was tested against known NP-complete combinatorial Optimization Problems, running on symmetrical TSP's. We show that the new algorithm compares favourably against these benchmarks, accordingly to recent biological findings by Robinson [26,27], and Gruter [28] where "No entry" signals and negative feedback allows a colony to quickly reallocate the majority of its foragers to superior food patches. This is the first time an extended ACS algorithm is implemented with these successful characteristics