Trail traffic flow prediction by contact frequency among individual ants

Ants build a trail that leads to a new location when they move their colony. The trail’s traffic flows smoothly, regardless of the density on the trail. To the best of our knowledge, such a phenomenon has been reported only for ant species. The trail’s capacity is known as trail traffic flow. In this paper, we propose a probabilistic model of trail traffic flow, which overcomes some inadequacies of the kinetic model previously proposed in the literature. Our model answers a question unsolved by the previous model, namely, how many worker ants form such a density-independent trail. We focus on ants’ responses to mutual contacts that involve individuals in trail formation. We propose a model in which contact frequency predicts the number of worker ants that form a trail. We verify that our model’s estimates match the empirical data that ant experts reported in the literature. In modeling and evaluation, we discuss an intelligent ant species, the house-hunting ant Temnothorax albipennis, which is popular among the ant experts.     

The Behavior of <Emphasis Type="Italic">Acromyrmex crassispinus</Emphasis> (Hymenoptera: Formicidae) on Trail Bifurcations and the Influence of Ant Flow on Error Rates of Nestbound Laden Workers

Ants are ordinarily faced with a succession of bifurcations along their foraging networks. Given that there is no directionality in pheromone trails, each bifurcation is potentially an opportunity for error in the trajectory of laden workers to the nest, which could entail considerable inefficiencies in the transportation of food to the colony. Leaf-cutting ants (Atta and Acromyrmex) commonly show intense traffic and complex foraging trail systems, which make them ideal organisms to study worker behavior in trail bifurcations. The behavior of leaf-cutting ants of the genus Acromyrmex in trail bifurcations is still largely unexplored. Thus, this study aimed to assess the behavior of Acromyrmex crassispinus workers on trail bifurcations and to investigate whether differences in ant flow on foraging trails influence the error rate of nestbound laden workers at trail bifurcation. There was a negative relationship between ant flow and error rate of nestbound laden workers. Most workers walked in the central part of the foraging trails but occupied a broader area of the foraging trail when the ant flow was high. The results of this study provide valuable insight into the organization of traffic flow in A. crassispinus and its impacts on the foraging strategy of the species.     

Leaf-cutting ants as road engineers: the width of trails at branching points in <Emphasis Type="Italic">Atta cephalotes</Emphasis>

We used a simple engineering principle, which suggests that the width of a road needed for a smooth traffic flow is proportional to the peak traffic volume (“engineering hypothesis”), to analyze the adaptive significance of trail width at branching points in the leaf-cutting ant Atta cephalotes. Since the flow of outgoing ants splits at trail bifurcations and merges when ants return to the nest through the same paths, the sum of branch widths should equal the width of the trail section upstream of the bifurcation. We measured the width of branches and their preceding trail section and also performed field measurements and manipulations to analyze ant flow, number of collisions, and ant speed in different trail sectors. Contrary to the prediction of the “engineering hypothesis”, the sum of branch widths was larger than the width of the trail immediately before the bifurcation. Our data contradict the “trail addition hypothesis” and support the “border effect hypothesis” to explain this pattern. First, the width of the widest branch was smaller than the width of the trail upstream of the bifurcation, an unexpected result if one branch is merely the continuation of the basal trail. Second, ants collided with obstacles more often in the margin than in the central portion of the trail, relocated ants from central to margin trail sectors reduced their speed, and ant flow was higher in the central sections of the trail. Since the delaying effect of trail margins increases as the trail width decreases, ants may build branches wider than expected to reduce the border effect. The delaying effect of trail margins should be included in the analysis of costs and benefits to fully understand the adaptive value of the design of ant trail networks.     

Traffic Experiment Reveals the Nature of Car-Following

As a typical self-driven many-particle system far from equilibrium, traffic flow exhibits diverse fascinating non-equilibrium phenomena, most of which are closely related to traffic flow stability and specifically the growth/dissipation pattern of disturbances. However, the traffic theories have been controversial due to a lack of precise traffic data. We have studied traffic flow from a new perspective by carrying out large-scale car-following experiment on an open road section, which overcomes the intrinsic deficiency of empirical observations. The experiment has shown clearly the nature of car-following, which runs against the traditional traffic flow theory. Simulations show that by removing the fundamental notion in the traditional car-following models and allowing the traffic state to span a two-dimensional region in velocity-spacing plane, the growth pattern of disturbances has changed qualitatively and becomes qualitatively or even quantitatively in consistent with that observed in the experiment.     

Impact: Toward a Framework for Understanding the Ecological Effects of Invaders

Although ecologists commonly talk about the impacts of nonindigenous species, little formal attention has been given to defining what we mean by impact, or connecting ecological theory with particular measures of impact. The resulting lack of generalizations regarding invasion impacts is more than an academic problem; we need to be able to distinguish invaders with minor effects from those with large effects in order to prioritize management efforts. This paper focuses on defining, evaluating, and comparing a variety of measures of impact drawn from empirical examples and theoretical reasoning. We begin by arguing that the total impact of an invader includes three fundamental dimensions: range, abundance, and the per-capita or per-biomass effect of the invader. Then we summarize previous approaches to measuring impact at different organizational levels, and suggest some new approaches. Reviewing mathematical models of impact, we argue that theoretical studies using community assembly models could act as a basis for better empirical studies and monitoring programs, as well as provide a clearer understanding of the relationship among different types of impact. We then discuss some of the particular challenges that come from the need to prioritize invasive species in a management or policy context. We end with recommendations about how the field of invasion biology might proceed in order to build a general framework for understanding and predicting impacts. In particular, we advocate studies designed to explore the correlations among different measures: Are the results of complex multivariate methods adequately captured by simple composite metrics such as species richness? How well are impacts on native populations correlated with impacts on ecosystem functions? Are there useful bioindicators for invasion impacts? To what extent does the impact of an invasive species depend on the system in which it is measured? Three approaches would provide new insights in this line of inquiry: (1) studies that measure impacts at multiple scales and multiple levels of organization, (2) studies that synthesize currently available data on different response variables, and (3) models designed to guide empirical work and explore generalities.     

Data Integration through Proximity-Based Networks Provides Biological Principles of Organization across Scales

Plant behaviors across levels of cellular organization, from biochemical components to tissues and organs, relate and reflect growth habitats. Quantification of the relationship between behaviors captured in various phenotypic characteristics and growth habitats can help reveal molecular mechanisms of plant adaptation. The aim of this article is to introduce the power of using statistics originally developed in the field of geographic variability analysis together with prominent network models in elucidating principles of biological organization. We provide a critical systematic review of the existing statistical and network-based approaches that can be employed to determine patterns of covariation from both uni- and multivariate phenotypic characteristics in plants. We demonstrate that parameter-independent network-based approaches result in robust insights about phenotypic covariation. These insights can be quantified and tested by applying well-established statistics combining the network structure with the phenotypic characteristics. We show that the reviewed network-based approaches are applicable from the level of genes to the study of individuals in a population of Arabidopsis thaliana. Finally, we demonstrate that the patterns of covariation can be generalized to quantifiable biological principles of organization. Therefore, these network-based approaches facilitate not only interpretation of large-scale data sets, but also prediction of biochemical and biological behaviors based on measurable characteristics.     

Flexibility of Individual Load-mass Selection in Relation to Foraging Trail Gradient in the Leaf-cutter Ant Acromyrmex octospinosus

The stochasticity in food quality and availability, and physical trail characteristics experienced by leaf-cutter ants, may favour individual flexibility in load-mass selection so as to forage effectively. The present study aimed to confirm previous evidence, from Atta cephaoltes foragers, of variable load-mass selection in response to steep inclines and declines in the leaf-cutter ant Acromyrmex octospinosus. The foraging trail gradient of a captive colony of Ac. octospinosus was manipulated by altering the position of a foraging platform relative to the nest box. The results indicate an effect of steep gradients on walking speed and variation in load mass in relation to gradient as a result of individual plasticity, not recruitment of different-sized individuals. Ants selected heavier loads when returning to the nest vertically downwards than when returning horizontally or vertically upwards. These results are discussed with reference to foraging performance. Walking speed was considerably reduced on upward returns to the nest, but was also slower when travelling vertically downwards compared with horizontal trails, suggesting vertical trails per se impact on the time costs of foraging. Differences in load-mass selection were evident from the onset of foraging and did not change significantly over the course of 24 h, suggesting this behaviour was based on individual experience, rather than colony-level information feedback. The present study has demonstrated that Ac. octospinosus foragers are capable of individual flexibility in load-mass selection in response to a physical trail characteristic that is pertinent to their natural habitat and is a factor seldom considered in theoretical foraging models.     

Lost in space? Searching for directions in the spatial modelling of individuals,populations and species ranges

The workshop ‘Spatial models in animal ecology, management and conservation’ held at Silwood Park (UK), 9–11 March 2010, aimed to synthesize recent progress in modelling the spatial dynamics of individuals, populations and species ranges and to provide directions for research. It brought together marine and terrestrial researchers working on spatial models at different levels of organization, using empirical as well as theory-driven approaches. Different approaches, temporal and spatial scales, and practical constraints predominate at different levels of organization and in different environments. However, there are theoretical concepts and specific methods that can fruitfully be transferred across levels and systems, including: habitat suitability characterization, movement rules, and ways of estimating uncertainty.     

The Effects of Spatial Scale on Trophic Interactions

Food chain models have dominated empirical studies of trophic interactions in the past decades, and have lead to important insights into the factors that control ecological communities. Despite the importance of food chain models in instigating ecological investigations, many empirical studies still show a strong deviation from the dynamics that food chain models predict. We present a theoretical framework that explains some of the discrepancies by showing that trophic interactions are likely to be strongly influenced by the spatial configuration of consumers and their resources. Differences in the spatial scale at which consumers and their resources function lead to uncoupling of the population dynamics of the interacting species, and may explain overexploitation and depletion of resource populations. We discuss how changed land use, likely the most prominent future stress on natural systems, may affect food web dynamics by interfering with the scale of interaction between consumers and their resource.     

To be or not to be faithful: flexible fidelity to foraging trails in the leaf‐cutting ant Acromyrmex lobicornis

1. Ants using trails to forage have to select between two alternative routes at bifurcations, using two, potentially conflicting, sources of information to make their decision: individual experience to return to a previous successful foraging site (i.e. fidelity) and ant traffic. In the field, we investigated which of these two types of information individuals of the leaf‐cutting ant Acromyrmex lobicornis Emery use to decide which foraging route to take. 2. We measured the proportion of foraging ants returning to each trail of bifurcations the following day, and for 4–7 consecutive days. We then experimentally increased ant traffic on one trail of the bifurcation by adding additional food sources to examine the effect of increased ant traffic on the decision that ants make. 3. Binomial tests showed that for 62% of the trails, ant fidelity was relatively more important than ant traffic in deciding which bifurcation to follow, suggesting the importance of previous experience. 4. When information conflict was generated by experimentally increasing ant traffic along the trail with less foraging activity, most ants relied on ant traffic to decide. However, in 33% of these bifurcations, ants were still faithful to their trail. Thus, there is some degree of flexibility in the decisions that A. lobicornis make to access food resources. 5. This flexible fidelity results in individual variation in the response of workers to different levels of ant traffic, and allows the colony to simultaneously exploit both established and recently discovered food patches, aiding efficient food gathering.     

Allometric scaling of foraging rate with trail dimensions in leaf-cutting ants

Leaf-cutting ants (Atta spp.) create physical pathways to support the transport of resources on which colony growth and reproduction depend. We determined the scaling relationship between the rate of resource acquisition and the size of the trail system and foraging workforce for 18 colonies of Atta colombica and Atta cephalotes. We examined conventional power-law scaling patterns, but did so in a multivariate analysis that reveals the simultaneous effects of forager number, trail length and trail width. Foraging rate (number of resource-laden ants returning to the nest per unit time) scaled at the 0.93 power of worker numbers, the -1.02 power of total trail length and the 0.65 power of trail width. These scaling exponents indicate that individual performance declines only slightly as more foragers are recruited to the workforce, but that trail length imposes a severe penalty on the foraging rate. A model of mass traffic flow predicts the allometric patterns for workforce and trail length, although the effect of trail width is unexpected and points to the importance of the little-known mechanisms that regulate a colony's investment in trail clearance. These results provide a point of comparison for the role that resource flows may play in allometric scaling patterns in other transport-dependent entities, such as human cities.     

Cycling Empirical Antibiotic Therapy in Hospitals: Meta-Analysis and Models

The rise of resistance together with the shortage of new broad-spectrum antibiotics underlines the urgency of optimizing the use of available drugs to minimize disease burden. Theoretical studies suggest that coordinating empirical usage of antibiotics in a hospital ward can contain the spread of resistance. However, theoretical and clinical studies came to different conclusions regarding the usefulness of rotating first-line therapy (cycling). Here, we performed a quantitative pathogen-specific meta-analysis of clinical studies comparing cycling to standard practice. We searched PubMed and Google Scholar and identified 46 clinical studies addressing the effect of cycling on nosocomial infections, of which 11 met our selection criteria. We employed a method for multivariate meta-analysis using incidence rates as endpoints and find that cycling reduced the incidence rate/1000 patient days of both total infections by 4.95 [9.43–0.48] and resistant infections by 7.2 [14.00–0.44]. This positive effect was observed in most pathogens despite a large variance between individual species. Our findings remain robust in uni- and multivariate metaregressions. We used theoretical models that reflect various infections and hospital settings to compare cycling to random assignment to different drugs (mixing). We make the realistic assumption that therapy is changed when first line treatment is ineffective, which we call “adjustable cycling/mixing”. In concordance with earlier theoretical studies, we find that in strict regimens, cycling is detrimental. However, in adjustable regimens single resistance is suppressed and cycling is successful in most settings. Both a meta-regression and our theoretical model indicate that “adjustable cycling” is especially useful to suppress emergence of multiple resistance. While our model predicts that cycling periods of one month perform well, we expect that too long cycling periods are detrimental. Our results suggest that “adjustable cycling” suppresses multiple resistance and warrants further investigations that allow comparing various diseases and hospital settings.     

Traffic dynamics of the leaf-cutting ant, Atta cephalotes

Colonies of Atta cephalotes (Myrmicinae: Formicidae) construct cleared paths between their nest and the vegetation sources at which they harvest leaf tissue. Here, we employ ideas from traffic engineering to study streams of laden and unladen ants on these paths. The relationship between average traffic speed and the concentration of workers on the road surface follows a relationship similar to what is expected by analogy to fluid dynamics. Although the traffic is composed of eusocial organisms with a common interest in group success, the coarse-grained behavior of Atta traffic displays little more coordination than a moving fluid. The relationship between speed and concentration implies that maximum flow rates (which are likely to be closely tied to colony-level rates of resource acquisition) occur at a relatively high concentration that keeps individual speeds well below their "free flow" maximum. We predict that this optimal concentration will characterize peak traffic throughout a trail network, and we propose a simple behavioral mechanism that would allow trails to be cleared to the correct width to provide the optimal concentration. Collisions (including encounters for antennation) are common in leaf-cutting ant traffic because traffic is not segregated into unidirectional streams. Nonetheless, we find a counterintuitive suggestion that flow rates (with concentration differences statistically removed) are higher when traffic is near a 50:50 mix of outbound and returning ants than when it contains majority flows in a single direction. Mixed-direction traffic may help disperse laden ants with reduced agility, thereby preventing inhomogeneities in the traffic stream that could clog the trail.     

Consequences of variation in foraging success among predators on numerical response

The relationship between foraging success and reproduction is commonly assumed to be linear in theoretical investigations. Although the exact relationship (e.g., linear or nonlinear) does not influence qualitative conclusions of models under some assumptions, an inclusion of individual behavioral variation can make it otherwise due to Jensen's inequality. In particular, a mechanism that stabilizes food web dynamics is generated when two conditions are satisfied: (1) the reproduction of predators experiences diminishing returns from foraging success (i.e., concave down relationship between foraging success and reproduction) and (2) foraging success variation among predator individuals increases with the predator density. However, empirical results that confirm these conditions are scarce. This study describes the mechanism as a hypothesis for stability and discusses some important considerations for empirical verifications of the mechanism.     

Analysis of emergent patterns in crossing flows of pedestrians reveals an invariant of ‘stripe’ formation in human data

When two streams of pedestrians cross at an angle, striped patterns spontaneously emerge as a result of local pedestrian interactions. This clear case of self-organized pattern formation remains to be elucidated. In counterflows, with a crossing angle of 180°, alternating lanes of traffic are commonly observed moving in opposite directions, whereas in crossing flows at an angle of 90°, diagonal stripes have been reported. Naka (1977) hypothesized that stripe orientation is perpendicular to the bisector of the crossing angle. However, studies of crossing flows at acute and obtuse angles remain underdeveloped. We tested the bisector hypothesis in experiments on small groups (18-19 participants each) crossing at seven angles (30° intervals), and analyzed the geometric properties of stripes. We present two novel computational methods for analyzing striped patterns in pedestrian data: (i) an edge-cutting algorithm, which detects the dynamic formation of stripes and allows us to measure local properties of individual stripes; and (ii) a pattern-matching technique, based on the Gabor function, which allows us to estimate global properties (orientation and wavelength) of the striped pattern at a time T. We find an invariant property: stripes in the two groups are parallel and perpendicular to the bisector at all crossing angles. In contrast, other properties depend on the crossing angle: stripe spacing (wavelength), stripe size (number of pedestrians per stripe), and crossing time all decrease as the crossing angle increases from 30° to 180°, whereas the number of stripes increases with crossing angle. We also observe that the width of individual stripes is dynamically squeezed as the two groups cross each other. The findings thus support the bisector hypothesis at a wide range of crossing angles, although the theoretical reasons for this invariant remain unclear. The present results provide empirical constraints on theoretical studies and computational models of crossing flows.     

Fire ant trail pheromones: Analysis of species specificity after gas chromatographic fractionation

The specificity of the trail pheromones of four Solenopsis species was determined using natural trails. Dufour's gland extracts, and purified fractions from Dufour's gland extracts collected after gas-chromatographic separation. S. richteri and S. invicta possess species-specific major trail pheromones, while S. geminata and S. xyloni appear to have a common trail pheromone. Preliminary chemical characterization of the main trail pheromone of S. richteri indicates a M.W. of 218 and empirical formula of C₁₆H₂₆. The trail pheromone system of S. richteri consists of a blend of compounds and this phenomenon may also occur in the other species. The lowest concentration of their trail pheromone that workers of S. richteri could detect was about 10 fg per cm. The significance of blends of pheromones being utilized to generate chemical trails is discussed.     

Head-on encounter rates and walking speed of foragers in leaf-cutting ant traffic

Summary. Trail traffic of the leaf-cutting ant Atta cephalotes involves intermingled flows of outbound and returning foragers. Head-on encounters between workers from the opposite flows are a common occurrence in this traffic. Each encounter momentarily delays the two ants involved, and these small delays might pose a significant cost to the colony's foraging performance when summed over thousands of workers along many metres of trail. We videotaped outbound and returning foragers over a 1 m course, and measured the encounter rates they experienced and their velocity. Our analysis indicates that locomotion speed is diminished by increasing encounter rate, but that the effect is small relative to the effects of ant body size and load mass. Head-on encounters allow exchange of information and leaf fragments between workers, and we consider how the benefits of such encounters may make this form of traffic organization superior to segregated outbound and returning lanes, despite the measurable c ost of encounters in mixed traffic.     

Expert-based versus habitat-suitability models to develop resistance surfaces in landscape genetics

Landscape genetics aims to investigate functional connectivity among wild populations by evaluating the impact of landscape features on gene flow. Genetic distances among populations or individuals are generally better explained by least-cost path (LCP) distances derived from resistance surfaces than by simple Euclidean distances. Resistance surfaces reflect the cost for an organism to move through particular landscape elements. However, determining the effects of landscape types on movements is challenging. Because of a general lack of empirical data on movements, resistance surfaces mostly rely on expert knowledge. Habitat-suitability models potentially provide a more objective method to estimate resistance surfaces than expert opinions, but they have rarely been applied in landscape genetics so far. We compared LCP distances based on expert knowledge with LCP distances derived from habitat-suitability models to evaluate their performance in landscape genetics. We related all LCP distances to genetic distances in linear mixed effect models on an empirical data set of wolves (Canis lupus) from Italy. All LCP distances showed highly significant (P ≤ 0.0001) standardized β coefficients and R ² values, but LCPs from habitat-suitability models generally showed higher values than those resulting from expert knowledge. Moreover, all LCP distances better explained genetic distances than Euclidean distances, irrespective of the approaches used. Considering our results, we encourage researchers in landscape genetics to use resistance surfaces based on habitat suitability which performed better than expert-based LCPs in explaining patterns of gene flow and functional connectivity.