1,575 research outputs found
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The stochastic modelling of kleptoparasitism using a Markov process
Kleptoparasitism, the stealing of food items from other animals, is a common behaviour observed across a huge variety of species, and has been subjected to significant modelling effort. Most such modelling has been deterministic, effectively assuming an infinite population, although recently some important stochastic models have been developed. In particular the model of Yates and Broom (Stochastic models of kleptoparasitism. J. Theor. Biol. 248 (2007), 480–489) introduced a stochastic version following the original model of Ruxton and Moody (The ideal free distribution with kleptoparasitism. J. Theor. Biol. 186 (1997), 449–458), and whilst they generated results of interest, they did not solve the model explicitly. In this paper, building on methods used already by van der Meer and Smallegange (A stochastic version of the Beddington-DeAngelis functional response: Modelling interference for a finite number of predators. J. Animal Ecol. 78 (2009) 134–142) we give an exact solution to the distribution of the population over the states for the Yates and Broom model and investigate the effects of some key biological parameters, especially for small populations where stochastic models can be expected to differ most from their deterministic equivalents
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Kleptoparasitic melees--modelling food stealing featuring contests with multiple individuals
Kleptoparasitism is the stealing of food by one animal from another. This has been modelled in various ways before, but all previous models have only allowed contests between two individuals. We investigate a model of kleptoparasitism where individuals are allowed to fight in groups of more than two, as often occurs in real populations. We find the equilibrium distribution of the population amongst various behavioural states, conditional upon the strategies played and environmental parameters, and then find evolutionarily stable challenging strategies. We find that there is always at least one ESS, but sometimes there are two or more, and discuss the circumstances when particular ESSs occur, and when there are likely to be multiple ESSs
Management of bite injuries
Most mammalian bites are caused by dogs, cats or humans. Cat and human bites often become infected, so antibiotic prophylaxis should be considered in addition to wound management. Early referral for surgical assessment of human bites to the hand may be required. Amoxycillin with clavulanate is suitable for prophylaxis in most cases. Prophylaxis is usually continued for 5–7 days. Depending on their immunisation status, patients may need vaccination against tetanu
Non-converging hysteretic cycles in random spin networks
Behavior of hysteretic trajectories for cyclical input is investigated as a
function of the internal structure of a system modeled by the classical random
network of binary spins. Different regimes of hysteretic behavior are
discovered for different network connectivity and topology. Surprisingly,
hysteretic trajectories which do not converge at all are observed. They are
shown to be associated with the presence of specific topological elements in
the network structure, particularly with the fully interconnected spin groups
of size equal or greater than 4.Comment: 4 pages, 3 figure
A theory for investment across defences triggered at different stages of a predator-prey encounter
We introduce a general theoretical description of a combination of defences acting sequentially at different stages in the predatory sequence in order to make predictions about how animal prey should best allocate investment across different defensive stages. We predict that defensive investment will often be concentrated at stages early in the interaction between a predator individual and the prey (especially if investment is concentrated in only one defence, then it will be in the first defence). Key to making this prediction is the assumption that there is a cost to a prey when it has a defence tested by an enemy, for example because this incurs costs of deployment or tested costs as a defence is exposed to the enemies; and the assumption that the investment functions are the same among defences. But if investment functions are different across defences (e.g. the investment efficiency in making resources into defences is higher in later defences than in earlier defences), then the contrary could happen. The framework we propose can be applied to other victim-exploiter systems, such as insect herbivores feeding on plant tissues. This leads us to propose a novel explanation for the observation that herbivory damage is often not well explained by variation in concentrations of toxic plant secondary metabolites. We compare our general theoretical structure with related examples in the literature, and conclude that coevolutionary approaches will be profitable in future work
The experiences of women with polycystic ovary syndrome on a very low-calorie diet
The research was funded by an educational grant from LighterLife. Broom was the Medical Director for LighterLife at the time of the research. Johnson is the Head of Nutrition and Research at LighterLife. The authors report no other conflicts of interest in this work.Peer reviewedPublisher PD
Network topology and movement cost, not updating mechanism, determine the evolution of cooperation in mobile structured populations
Evolutionary models are used to study the self-organisation of collective
action, often incorporating population structure due to its ubiquitous presence
and long-known impact on emerging phenomena. We investigate the evolution of
multiplayer cooperation in mobile structured populations, where individuals
move strategically on networks and interact with those they meet in groups of
variable size. We find that the evolution of multiplayer cooperation primarily
depends on the network topology and movement cost while using different
stochastic update rules seldom influences evolutionary outcomes. Cooperation
robustly co-evolves with movement on complete networks and structure has a
partially detrimental effect on it. These findings contrast an established
wisdom in evolutionary graph theory that cooperation can only emerge under some
update rules and if the average degree is low. We find that group-dependent
movement erases the locality of interactions, suppresses the impact of
evolutionary structural viscosity on the fitness of individuals, and leads to
assortative behaviour that is much more powerful than viscosity in promoting
cooperation. We analyse the differences remaining between update rules through
a comparison of evolutionary outcomes and fixation probabilities.Comment: 26 pages, 12 figures, 1 tabl
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Evolutionary dynamics of general group interactions in structured populations
The evolution of populations is influenced by many factors, and the simple classical models have been developed in a number of important ways. Both population structure and multiplayer interactions have been shown to significantly affect the evolution of important properties, such as the level of cooperation or of aggressive behavior. Here we combine these two key factors and develop the evolutionary dynamics of general group interactions in structured populations represented by regular graphs. The traditional linear and threshold public goods games are adopted as models to address the dynamics. We show that for linear group interactions, population structure can favor the evolution of cooperation compared to the well-mixed case, and we see that the more neighbors there are, the harder it is for cooperators to persist in structured populations. We further show that threshold group interactions could lead to the emergence of cooperation even in well-mixed populations. Here population structure sometimes inhibits cooperation for the threshold public goods game, where depending on the benefit to cost ratio, the outcomes are bistability or a monomorphic population of defectors or cooperators. Our results suggest, counterintuitively, that structured populations are not always beneficial for the evolution of cooperation for nonlinear group interactions
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The effect of fight cost structure on fighting behaviour involving simultaneous decisions and variable investment levels
In the “producer–scrounger” model, a producer discovers a resource and is in turn discovered by a second individual, the scrounger, who attempts to steal it. This resource can be food or a territory, and in some situations, potentially divisible. In a previous paper we considered a producer and scrounger competing for an indivisible resource, where each individual could choose the level of energy that they would invest in the contest. The higher the investment, the higher the probability of success, but also the higher the costs incurred in the contest. In that paper decisions were sequential with the scrounger choosing their strategy before the producer. In this paper we consider a version of the game where decisions are made simultaneously. For the same cost functions as before, we analyse this case in detail, and then make comparisons between the two cases. Finally we discuss some real examples with potentially variable and asymmetric energetic investments, including intraspecific contests amongst spiders and amongst parasitoid wasps. In the case of the spiders, detailed estimates of energetic expenditure are available which demonstrate the asymmetric values assumed in our models. For the wasps the value of the resource can affect the probabilities of success of the defender and attacker, and differential energetic investment can be inferred. In general for real populations energy usage varies markedly depending upon crucial parameters extrinsic to the individual such as resource value and intrinsic ones such as age, and is thus an important factor to consider when modelling
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Evolutionary graph theory revisited: when is an evolutionary process equivalent to the Moran process?
Evolution in finite populations is often modelled using the classical Moran process. Over the last 10 years, this methodology has been extended to structured populations using evolutionary graph theory. An important question in any such population is whether a rare mutant has a higher or lower chance of fixating (the fixation probability) than the Moran probability, i.e. that from the original Moran model, which represents an unstructured population. As evolutionary graph theory has developed, different ways of considering the interactions between individuals through a graph and an associated matrix of weights have been considered, as have a number of important dynamics. In this paper, we revisit the original paper on evolutionary graph theory in light of these extensions to consider these developments in an integrated way. In particular, we find general criteria for when an evolutionary graph with general weights satisfies the Moran probability for the set of six common evolutionary dynamics
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