Using individual tracking data to validate the predictions of species distribution models

The authors would like to thank the College of Life Sciences of Aberdeen University and Marine Scotland Science which funded CP's PhD project. Skate tagging experiments were undertaken as part of Scottish Government project SP004. We thank Ian Burrett for help in catching the fish and the other fishermen and anglers who returned tags. We thank José Manuel Gonzalez-Irusta for extracting and making available the environmental layers used as environmental covariates in the environmental suitability modelling procedure. We also thank Jason Matthiopoulos for insightful suggestions on habitat utilization metrics as well as Stephen C.F. Palmer, and three anonymous reviewers for useful suggestions to improve the clarity and quality of the manuscript.Peer reviewedPostprintPostprintPostprintPostprintPostprin

Validating Sample Average Approximation Solutions with Negatively Dependent Batches

Sample-average approximations (SAA) are a practical means of finding approximate solutions of stochastic programming problems involving an extremely large (or infinite) number of scenarios. SAA can also be used to find estimates of a lower bound on the optimal objective value of the true problem which, when coupled with an upper bound, provides confidence intervals for the true optimal objective value and valuable information about the quality of the approximate solutions. Specifically, the lower bound can be estimated by solving multiple SAA problems (each obtained using a particular sampling method) and averaging the obtained objective values. State-of-the-art methods for lower-bound estimation generate batches of scenarios for the SAA problems independently. In this paper, we describe sampling methods that produce negatively dependent batches, thus reducing the variance of the sample-averaged lower bound estimator and increasing its usefulness in defining a confidence interval for the optimal objective value. We provide conditions under which the new sampling methods can reduce the variance of the lower bound estimator, and present computational results to verify that our scheme can reduce the variance significantly, by comparison with the traditional Latin hypercube approach

A model of meta-population dynamics for North Sea and West of Scotland cod - the dynamic consequences of natal fidelity

It is clear from a variety of data that cod (Gadus morhua) in the North Sea do not constitute a homogeneous population that will rapidly redistribute in response to local variability in exploitation. Hence, local exploitation has the potential to deplete local populations, perhaps to the extent that depensation occurs and recovery is impossible without recolonisation from other areas, with consequent loss of genetic diversity. The oceanographic, biological and behavioural processes which maintain the spatial population structures are only partly understood, and one of the key unknown factors is the extent to which codexhibit homing migrations to natal spawning areas. Here, we describe a model comprising 10 interlinked demes of cod in European waters, each representing groups of fish with a common natal origin. The spawning locations of fish in each deme are governed by a variety of rules concerning oceanographic dispersal, migration behaviour and straying. We describe numerical experiments with the model and comparisons with observations, which lead us to conclude that active homing is probably not necessary to explain some of the population structures of European cod. Separation of some sub-populations is possible through distance and oceanographic processes affecting the dispersal of eggs and larvae. However, other evidence suggests that homing may be a necessary behaviour to explain the structure of other sub-populations. Theconsequences for fisheries management of taking into account spatial population structuring are complicated. For example, recovery or recolonisation strategies require consideration not only of mortality rates in the target area for restoration, but also in the source areas for the recruits which may be far removed depending on the oceanography. The model has an inbuilt capability to address issues concerning the effects of climate change, including temperature change, on spatial patterns of recruitment, development and population structure in cod

The enigma of facial asymmetry:is there a gender specific pattern of facedness?

Although facial symmetry correlates with facial attractiveness, human faces are often far from symmetrical with one side frequently being larger than the other (Kowner, 1998). Smith (2000) reported that male and female faces were asymmetrical in opposite directions, with males having a larger area on the left side compared to the right side, and females having a larger right side compared to the left side. The present study attempted to replicate and extend this finding. Two databases of facial images from Stirling and St Andrews Universities, consisting of 180 and 122 faces respectively, and a third set of 62 faces collected at Abertay University, were used to examine Smith's findings. Smith's unique method of calculating the size of each hemiface was applied to each set. For the Stirling and St Andrews sets a computer program did this automatically and for the Abertay set it was done manually. No significant overall effect of gender on facial area asymmetry was found. However, the St Andrews sample demonstrated a similar effect to that found by Smith, with females having a significantly larger mean area of right hemiface and males having a larger left hemiface. In addition, for the Abertay faces handedness had a significant effect on facial asymmetry with right-handers having a larger left side of the face. These findings give limited support for Smith's results but also suggest that finding such an asymmetry may depend on some as yet unidentified factors inherent in some methods of image collection

The EGNoG Survey: Gas Excitation in Normal Galaxies at z~0.3

As observations of molecular gas in galaxies are pushed to lower star formation rate galaxies at higher redshifts, it is becoming increasingly important to understand the conditions of the gas in these systems to properly infer their molecular gas content. The rotational transitions of the carbon monoxide (CO) molecule provide an excellent probe of the gas excitation conditions in these galaxies. In this paper we present the results from the gas excitation sample of the Evolution of molecular Gas in Normal Galaxies (EGNoG) survey at the Combined Array for Research in Millimeter-wave Astronomy (CARMA). This subset of the full EGNoG sample consists of four galaxies at z~0.3 with star formation rates of 40-65 M_Sun yr^-1 and stellar masses of ~2x10^11 M_Sun. Using the 3 mm and 1 mm bands at CARMA, we observe both the CO(1-0) and CO(3-2) transitions in these four galaxies in order to probe the excitation of the molecular gas. We report robust detections of both lines in three galaxies (and an upper limit on the fourth), with an average line ratio, r_31 = L'_CO(3-2) / L'_CO(1-0), of 0.46 \pm 0.07 (with systematic errors \lesssim 40%), which implies sub-thermal excitation of the CO(3-2) line. We conclude that the excitation of the gas in these massive, highly star-forming galaxies is consistent with normal star-forming galaxies such as local spirals, not starbursting systems like local ultra-luminous infrared galaxies. Since the EGNoG gas excitation sample galaxies are selected from the main sequence of star-forming galaxies, we suggest that this result is applicable to studies of main sequence galaxies at intermediate and high redshifts, supporting the assumptions made in studies that find molecular gas fractions in star forming galaxies at z~1-2 to be an order of magnitude larger than what is observed locally.Comment: Accepted for publication in the Astrophysical Journal, to appear January 2013; 18 pages, 10 figures, 6 table

High-throughput Binding Affinity Calculations at Extreme Scales

Resistance to chemotherapy and molecularly targeted therapies is a major factor in limiting the effectiveness of cancer treatment. In many cases, resistance can be linked to genetic changes in target proteins, either pre-existing or evolutionarily selected during treatment. Key to overcoming this challenge is an understanding of the molecular determinants of drug binding. Using multi-stage pipelines of molecular simulations we can gain insights into the binding free energy and the residence time of a ligand, which can inform both stratified and personal treatment regimes and drug development. To support the scalable, adaptive and automated calculation of the binding free energy on high-performance computing resources, we introduce the High- throughput Binding Affinity Calculator (HTBAC). HTBAC uses a building block approach in order to attain both workflow flexibility and performance. We demonstrate close to perfect weak scaling to hundreds of concurrent multi-stage binding affinity calculation pipelines. This permits a rapid time-to-solution that is essentially invariant of the calculation protocol, size of candidate ligands and number of ensemble simulations. As such, HTBAC advances the state of the art of binding affinity calculations and protocols