Costs of colour change in fish: food intake and behavioural decisions

Many animals, particularly reptiles, amphibians, fish and cephalopods, have the ability to change their body colour, for functions including thermoregulation, signalling and predator avoidance. Many fish plastically darken their body colouration in response to dark visual backgrounds, and this functions to reduce predation risk. Here, we tested the hypotheses that colour change in fish (1) carries with it an energetic cost and (2) affects subsequent shoal and habitat choice decisions. We demonstrate that guppies (Poecilia reticulata) change colour in response to dark and light visual backgrounds, and that doing so carries an energetic cost in terms of food consumption. By increasing food intake, however, guppies are able to maintain growth rates and meet the energetic costs of changing colour. Following colour change, fish preferentially choose habitats and shoals that match their own body colouration, and maximise crypsis, thus avoiding the need for further colour change but also potentially paying an opportunity cost associated with restriction to particular habitats and social associates. Thus, colour change to match the background is complemented by behavioural strategies, which should act to maximise fitness in variable environments. © 2013. Published by The Company of Biologists Ltd

An MCMC Fitting Method for Triaxial Dark Matter Haloes

Measuring the 3D distribution of mass on galaxy cluster scales is a crucial test of the LCDM model, providing constraints on the behaviour of dark matter. Recent work investigating mass distributions of individual galaxy clusters (e.g. Abell 1689) using weak and strong gravitational lensing has revealed potential inconsistencies between the predictions of structure formation models relating halo mass to concentration and those relationships as measured in massive clusters. However, such analyses employ simple spherical halo models while a growing body of work indicates that triaxial 3D halo structure is both common and important in parameter estimates. The very strong assumptions about the symmetry of the lensing halo implied with circular or perturbative elliptical NFW models are not physically motivated and lead to incorrect parameter estimates with significantly underestimated error bars. We here introduce a Markov Chain Monte Carlo (MCMC) method to fit fully triaxial models to weak lensing data that gives parameter and error estimates that fully incorporate the true uncertainty present in nature. Applying the MCMC triaxial fitting method to a population of NFW triaxial lenses drawn from the shape distribution of structure formation simulations, we find that including triaxiality cannot explain a population of massive, highly concentrated clusters within the framework of LCDM, but easily explains rare cases of apparently massive, highly concentrated, very efficient lensing clusters. Our MCMC triaxial NFW fitting method is easily expandable to include constraints from additional data types, and its application returns model parameters and errors that more accurately capture the true (and limited) extent of our knowledge of the structure of galaxy cluster lenses. (abridged)Comment: 18 pages, 15 figures. Updated to match published versio

A Result On Implicit Consensus with Application to Emissions Control

This paper is concerned with a class of decentralised control problems that arise in contemporary applications where agents cooperate to control and regulate a global quantity, are limited in the manner in which they communicate with each other, and are required to reach consensus on some implicit variable (for instance, CO2 emissions). An algorithm is presented for achieving this goal. A simplified application of the algorithm to emissions control for a fleet of Plug-in Hybrid Electric Vehicles (PHEVs) is given

A New Look at Massive Clusters: weak lensing constraints on the triaxial dark matter halos of Abell 1689, Abell 1835, & Abell 2204

Measuring the 3D distribution of mass on galaxy cluster scales is a crucial test of the LCDM model, providing constraints on the nature of dark matter. Recent work investigating mass distributions of individual galaxy clusters (e.g. Abell 1689) using weak and strong gravitational lensing has revealed potential inconsistencies between the predictions of structure formation models relating halo mass to concentration and those relationships as measured in massive clusters. However, such analyses employ simple spherical halo models while a growing body of work indicates that triaxial 3D halo structure is both common and important in parameter estimates. We recently introduced a Markov Chain Monte Carlo (MCMC) method to fit fully triaxial models to weak lensing data that gives parameter and error estimates that fully incorporate the true shape uncertainty present in nature. In this paper we apply that method to weak lensing data obtained with the ESO/MPG Wide-Field Imager for galaxy clusters A1689, A1835, and A2204, under a range of Bayesian priors derived from theory and from independent X-ray and strong lensing observations. For Abell 1689, using a simple strong lensing prior we find marginalized mean parameter values M_200 = (0.83 +- 0.16)x10^15 M_solar/h and C=12.2 +- 6.7, which are marginally consistent with the mass-concentration relation predicted in LCDM. The large error contours that accompany our triaxial parameter estimates more accurately represent the true extent of our limited knowledge of the structure of galaxy cluster lenses, and make clear the importance of combining many constraints from other theoretical, lensing (strong, flexion), or other observational (X-ray, SZ, dynamical) data to confidently measure cluster mass profiles. (Abridged)Comment: 21 pages, 10 figures, accepted for publication in MNRA