Transport and aggregation of self-propelled particles in fluid flows

An analysis of the dynamics of prolate swimming particles in laminar flow is presented. It is shown that the particles concentrate around flow regions with chaotic trajectories. When the swimming velocity is larger than a threshold, dependent on the aspect ratio of the particles, all particles escape from regular elliptic regions. For thin rodlike particles the threshold velocity vanishes; thus, the arbitrarily small swimming velocity destroys all transport boundaries. We derive an expression for the minimum swimming velocity required for escape based on a circularly symmetric flow approximation of the regular elliptic regions

A Study on Discrete-Time Movement Models

Understanding animal movement is an important challenge in ecology, with improvement in tagging technology permitting the collection of data on an increasingly wide range of species. Consequently, methodologies for statistical analysis of such data has received considerable attention in recent years. Discrete-time random walks are the foundation of the movement data models. The advantages of the discrete-time movement models are that they are intuitive and easily implemented, however the specification of the discretization step is often problematic and must be done in advance. Misspecification of the discretization step might lead to a model mismatch and thus choosing an appropriate test statistic to capture the model mismatch is essential

Phototactic clustering of swimming microorganisms in a turbulent velocity field

We study the distribution of swimming microorganisms advected by a two-dimensional smooth turbulent flow and attracted towards a light source through phototaxis. It is shown that particles aggregate along a dynamical attractor with fractal measure whose dimension depends on the strength of the phototaxis. Using an effective diffusion approximation for the flow, we derive an analytic expression for the increase in light exposure over the aggregate and by extension an accurate prediction for the fractal dimension based on the properties of the advection and the statistics of the attracting field

On the evolutionary interplay between dispersal and local adaptation in heterogeneous environments

Journal ArticleCopyright © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.Dispersal, whether in the form of a dandelion seed drifting on the breeze, or a salmon migrating upstream to breed in a nonnatal stream, transports genes between locations. At these locations, local adaptation modifies the gene frequencies so their carriers are better suited to particular conditions, be those of newly disturbed soil or a quiet river pool. Both dispersal and local adaptation are major drivers of population structure; however, in general, their respective roles are not independent and the two may often be at odds with one another evolutionarily, each one exhibiting negative feedback on the evolution of the other. Here, we investigate their joint evolution within a simple, discrete-time, metapopulation model. Depending on environmental conditions, their evolutionary interplay leads to either a monomorphic population of highly dispersing generalists or a collection of rarely dispersing, locally adapted, polymorphic sub-populations, each adapted to a particular habitat type. A critical value of environmental heterogeneity divides these two selection regimes and the nature of the transition between them is determined by the level of kin competition. When kin competition is low, at the transition we observe discontinuities, bistability, and hysteresis in the evolved strategies; however, when high, kin competition moderates the evolutionary feedback and the transition is smooth.Natural Sciences and Engineering Research Council of CanadaYukon FoundationArmy Research Offic

High-predation habitats affect the social dynamics of collective exploration in a shoaling fish

Collective decisions play a major role in the benefits that animals gain from living in groups. Although the mechanisms of how groups collectively make decisions have been extensively researched, the response of within-group dynamics to ecological conditions is virtually unknown, despite adaptation to the environment being a cornerstone in biology. We investigate how within-group interactions during exploration of a novel environment are shaped by predation, a major influence on the behavior of prey species. We tested guppies (Poecilia reticulata) from rivers varying in predation risk under controlled laboratory conditions and find the first evidence of differences in group interactions between animals adapted to different levels of predation. Fish from high-predation habitats showed the strongest negative relationship between initiating movements and following others, which resulted in less variability in the total number of movements made between individuals. This relationship between initiating movements and following others was associated with differentiation into initiators and followers, which was only observed in fish from high-predation rivers. The differentiation occurred rapidly, as trials lasted 5 min, and was related to shoal cohesion, where more diverse groups from high-predation habitats were more cohesive. Our results show that even within a single species over a small geographical range, decision-making in a social context can vary with local ecological factors

Inferring the rules of social interaction in migrating caribou

Social interactions are a significant factor that influence the decision-making of species ranging from humans to bacteria. In the context of animal migration, social interactions may lead to improved decision-making, greater ability to respond to environmental cues, and the cultural transmission of optimal routes. Despite their significance, the precise nature of social interactions in migrating species remains largely unknown. Here we deploy unmanned aerial systems to collect aerial footage of caribou as they undertake their migration from Victoria Island to mainland Canada. Through a Bayesian analysis of trajectories we reveal the fine-scale interaction rules of migrating caribou and show they are attracted to one another and copy directional choices of neighbours, but do not interact through clearly defined metric or topological interaction ranges. By explicitly considering the role of social information on movement decisions we construct a map of near neighbour influence that quantifies the nature of information flow in these herds. These results will inform more realistic, mechanism-based models of migration in caribou and other social ungulates, leading to better predictions of spatial use patterns and responses to changing environmental conditions. Moreover, we anticipate that the protocol we developed here will be broadly applicable to study social behaviour in a wide range of migratory and non-migratory taxa. This article is part of the theme issue ‘Collective movement ecology’

From single steps to mass migration: the problem of scale in the movement ecology of the Serengeti wildebeest

A central question in ecology is how to link processes that occur over different scales. The daily interactions of individual organisms ultimately determine community dynamics, population fluctuations and the functioning of entire ecosystems. Observations of these multiscale ecological processes are constrained by various technological, biological or logistical issues, and there are often vast discrepancies between the scale at which observation is possible and the scale of the question of interest. Animal movement is characterized by processes that act over multiple spatial and temporal scales. Second-by-second decisions accumulate to produce annual movement patterns. Individuals influence, and are influenced by, collective movement decisions, which then govern the spatial distribution of populations and the connectivity of meta-populations. While the field of movement ecology is experiencing unprecedented growth in the availability of movement data, there remain challenges in integrating observations with questions of ecological interest. In this article, we present the major challenges of addressing these issues within the context of the Serengeti wildebeest migration, a keystone ecological phenomena that crosses multiple scales of space, time and biological complexity. This article is part of the theme issue ’Collective movement ecology’

Context-dependent interaction leads to emergent search behavior in social aggregates

Locating the source of an advected chemical signal is a common challenge facing many living organisms. When the advecting medium is characterized by either high Reynolds number or high Peclet number the task becomes highly non-trivial due to the generation of heterogenous, dynamically changing filamental concentrations which do not decrease monotonically with distance to the source. Defining search strategies which are effective in these environments has important implications for the understanding of animal behavior and for the design of biologically inspired technology. Here we present a strategy which is able to solve this task without the higher intelligence required to assess spatial gradient direction, measure the diffusive properties of the flow field or perform complex calculations. Instead our method is based on the collective behavior of autonomous individuals following simple social interaction rules which are modified according to the local conditions they are experiencing. Through these context-dependent interactions the group is able to locate the source of a chemical signal and in doing so displays an awareness of the environment not present at the individual level. Our model demonstrates the ability of decentralized information processing systems to solve real world problems and also illustrates an alternative pathway to the evolution of higher cognitive capacity via the emergent, group level intelligence which can result from local interactions.Comment: 3 figure

PENGARUH TINGKAT PENDIDIKAN DAN PEKERJAAN TERHADAP ORAL HYGIENE PADA IBU HAMIL DI RSUD MEURAXA BANDA ACEH

ABSTRAKNama: Muhammad AdriansyahProgram Studi: Kedokteran GigiJudul:Pengaruh Tingkat Pendidikan dan Pekerjaan Terhadap Oral Hygiene pada Ibu Hamil di RSUD Meuraxa Banda AcehPendidikan adalah faktor sosial ekonomi yang mempengaruhi status kesehatan. Pekerjaan dihubungkan dengan tingkat pendidikan dan penghasilan, dimana pekerjaan membutuhkan latar belakang pendidikan yang tinggi, dan penghasilan dimana seseorang mempunyai penghasilan lebih besar maka akan mampu memenuhi kebutuhan dalam menjaga kesehatan gigi dan mulut. Selama masa kehamilan, wanita mengalami beberapa perubahan fisiologis yang menyebabkan terjadinya perubahan hormonal. Perubahan fisiologis juga berdampak pada perubahan menjaga kesehatan gigi dan mulut, sehingga wanita hamil lebih rentan terkena masalah gigi dan mulut. Tujuan penelitian ini adalah untuk mengetahui pengaruh tingkat pendidikan dan pekerjaan terhadap oral hygiene pada ibu hamil di RSUD Meuraxa Banda Aceh. Jenis penelitian ini bersifat analitik dengan metode cross sectional untuk melihat hubungan antar dua variabel. Penelitian ini melibatkan 48 subjek yang memenuhi kriteria inklusi. Subjek penelitian mengisi kuisioner yang diberikan serta diperiksa tingkat kebersihan rongga mulutnya. Data dianalisis dengan SPSS menggunakan Korelasi Spearman. Hasil uji menunjukkan ada pengaruh yang signifikan antara tingkat pendidikan (

Modelling multiscale collective behavior with Gaussian processes

Collective behavior is characterized by the emergence of large-scale phenomena from local interactions. It is found in many contexts, including political movements, fads and fashions, and animal grouping. In this paper, we aim to elucidate the mechanisms that underlie observed collective behavior by developing a novel mathematical framework based on equation-free modelling procedures and Gaussian process regression. This allows us to circumvent the possible lack of formal mathematical links between scales and instead use statistical emulation to learn an empirical Fokker-Planck equation. Our approach advances our ability to understand how complex systems function at both the individual and collective level when a formal mathematical description of macroscale dynamics is unavailable