Modelling large herbivore movement decisions: Beyond food availability as a predictor of ranging patterns

The ability of animals to adapt to their changing environment will depend in part on shifts in their ranging patterns, but when and why individuals choose to move requires detailed understanding of their decision‐making processes. We develop a simple decision‐making model accounting for resource availability in habitually used ranges. We suggest that disparities between model predictions and animal tracking data indicate additional factors influencing movement decisions, which may be identified given detailed system‐specific knowledge. The model was evaluated using movement data from satellite‐tracked elephants (Loxodonta africana) inhabiting the Amboseli basin in Kenya, moving from savannah areas with low quality but constant resource availability, to areas with temporally constrained higher nutrient availability. Overall, the model fits the data well: There was a good correlation between predicted and observed locations for the combined data from all elephants, but variation between individuals in how well the model fits. For those elephants where model predictions were less successful, additional factors likely to affect movement decisions, including reproduction, anthropogenic threats, memory and perception are suggested. This protocol for building and testing decision‐making models should contribute to success in attempts to preserve sufficient space for large herbivores in their increasingly human‐dominated ecosystems.     

Niches of two polysaccharide-degrading Polaribacter isolates from the North Sea during a spring diatom bloom

Members of the flavobacterial genus Polaribacter thrive in response to North Sea spring phytoplankton blooms. We analyzed two respective Polaribacter species by whole genome sequencing, comparative genomics, substrate tests and proteomics. Both can degrade algal polysaccharides but occupy distinct niches. The liquid culture isolate Polaribacter sp. strain Hel1_33_49 has a 3.0-Mbp genome with an overall peptidase:CAZyme ratio of 1.37, four putative polysaccharide utilization loci (PULs) and features proteorhodopsin, whereas the agar plate isolate Polaribacter sp. strain Hel1_85 has a 3.9-Mbp genome with an even peptidase:CAZyme ratio, eight PULs, a mannitol dehydrogenase for decomposing algal mannitol-capped polysaccharides but no proteorhodopsin. Unlike other sequenced Polaribacter species, both isolates have larger sulfatase-rich PULs, supporting earlier assumptions that Polaribacter take part in the decomposition of sulfated polysaccharides. Both strains grow on algal laminarin and the sulfated polysaccharide chondroitin sulfate. For strain Hel1_33_49, we identified by proteomics (i) a laminarin-induced PUL, (ii) chondroitin sulfate-induced CAZymes and (iii) a chondroitin-induced operon that likely enables chondroitin sulfate recognition. These and other data suggest that strain Hel1_33_49 is a planktonic flavobacterium feeding on proteins and a small subset of algal polysaccharides, while the more versatile strain Hel1_85 can decompose a broader spectrum of polysaccharides and likely associates with algae.     

Head-to-Head Comparison of Two Popular Cortical Thickness Extraction Algorithms: A Cross-Sectional and Longitudinal Study

Background and Purpose

The measurement of cortical shrinkage is a candidate marker of disease progression in Alzheimer’s. This study evaluated the performance of two pipelines: Civet-CLASP (v1.1.9) and Freesurfer (v5.3.0).

Methods

Images from 185 ADNI1 cases (69 elderly controls (CTR), 37 stable MCI (sMCI), 27 progressive MCI (pMCI), and 52 Alzheimer (AD) patients) scanned at baseline, month 12, and month 24 were processed using the two pipelines and two interconnected e-infrastructures: neuGRID (https://neugrid4you.eu) and VIP (http://vip.creatis.insa-lyon.fr). The vertex-by-vertex cross-algorithm comparison was made possible applying the 3D gradient vector flow (GVF) and closest point search (CPS) techniques.

Results

The cortical thickness measured with Freesurfer was systematically lower by one third if compared to Civet’s. Cross-sectionally, Freesurfer’s effect size was significantly different in the posterior division of the temporal fusiform cortex. Both pipelines were weakly or mildly correlated with the Mini Mental State Examination score (MMSE) and the hippocampal volumetry. Civet differed significantly from Freesurfer in large frontal, parietal, temporal and occipital regions (p<0.05). In a discriminant analysis with cortical ROIs having effect size larger than 0.8, both pipelines gave no significant differences in area under the curve (AUC). Longitudinally, effect sizes were not significantly different in any of the 28 ROIs tested. Both pipelines weakly correlated with MMSE decay, showing no significant differences. Freesurfer mildly correlated with hippocampal thinning rate and differed in the supramarginal gyrus, temporal gyrus, and in the lateral occipital cortex compared to Civet (p<0.05). In a discriminant analysis with ROIs having effect size larger than 0.6, both pipelines yielded no significant differences in the AUC.

Conclusions

Civet appears slightly more sensitive to the typical AD atrophic pattern at the MCI stage, but both pipelines can accurately characterize the topography of cortical thinning at the dementia stage.     

Group-based variant calling leveraging next-generation supercomputing for large-scale whole-genome sequencing studies

Motivation

Next-generation sequencing (NGS) technologies have become much more efficient, allowing whole human genomes to be sequenced faster and cheaper than ever before. However, processing the raw sequence reads associated with NGS technologies requires care and sophistication in order to draw compelling inferences about phenotypic consequences of variation in human genomes. It has been shown that different approaches to variant calling from NGS data can lead to different conclusions. Ensuring appropriate accuracy and quality in variant calling can come at a computational cost.

Results

We describe our experience implementing and evaluating a group-based approach to calling variants on large numbers of whole human genomes. We explore the influence of many factors that may impact the accuracy and efficiency of group-based variant calling, including group size, the biogeographical backgrounds of the individuals who have been sequenced, and the computing environment used. We make efficient use of the Gordon supercomputer cluster at the San Diego Supercomputer Center by incorporating job-packing and parallelization considerations into our workflow while calling variants on 437 whole human genomes generated as part of large association study.

Conclusions

We ultimately find that our workflow resulted in high-quality variant calls in a computationally efficient manner. We argue that studies like ours should motivate further investigations combining hardware-oriented advances in computing systems with algorithmic developments to tackle emerging ‘big data’ problems in biomedical research brought on by the expansion of NGS technologies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0736-4) contains supplementary material, which is available to authorized users.     

MDAT- Aligning multiple domain arrangements

Background

Proteins are composed of domains, protein segments that fold independently from the rest of the protein and have a specific function. During evolution the arrangement of domains can change: domains are gained, lost or their order is rearranged. To facilitate the analysis of these changes we propose the use of multiple domain alignments.

Results

We developed an alignment program, called MDAT, which aligns multiple domain arrangements. MDAT extends earlier programs which perform pairwise alignments of domain arrangements. MDAT uses a domain similarity matrix to score domain pairs and aligns the domain arrangements using a consistency supported progressive alignment method.

Conclusion

MDAT will be useful for analysing changes in domain arrangements within and between protein families and will thus provide valuable insights into the evolution of proteins and their domains. MDAT is coded in C++, and the source code is freely available for download at http://www.bornberglab.org/pages/mdat.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0442-7) contains supplementary material, which is available to authorized users.     

Design of concrete : Setting a new basis for improving both durability and environmental performance

CO₂ emissions from cement production currently represent around 6% of global CO₂ emissions. However, cement concrete absorbs CO₂ from the atmosphere because of carbonation (i.e., penetration of atmospheric CO₂ inside bulk concrete). Carbonation has beneficial effects on the mechanical resistance of cement concrete. However, carbonation also has adverse effects because it provokes a decrease in pH that favors later corrosion of reinforcing bars and thus reduces service life. Current European standards provide recommendations concerning reinforcing concrete covers, but these are not based on actual service‐life durations. Thanks to a previously developed carbonation model combined with sensitivity analysis and LCA, we compare Climate Change indicators of 1 m² of reinforced concrete cover over a 100‐years service life exposed to XC4 conditions in Madrid, obtained on one hand by using current standards and on the other hand with concrete‐cover depths calculated with our carbonation model. Our results show that cement strength class is a key parameter to both increase durability and decrease climate‐change impacts. When the carbonation model is used to optimize both durability and climate‐change impacts, it drives to considerable and significant improvements. Finally, climate‐change indicators predicted from our carbonation model are not linearly linked to carbon intensity of cements, which is a current argument of so‐called “green cements.” The values of indicators presented in this article cannot be generalized: They mainly depend on the geographical location. However, the model and key action levers are general. Using high cement strength classes and low water‐to‐cement ratios allows use of lower concrete‐cover depths and thus save amounts of concrete compared to the standard. This generates an important benefit in terms of climate‐change impacts for identical service lives and improved mechanical resistance. Thus, considering the huge impact of cement and construction industry on climate change, we plead for a revision of standards which, instead of thresholds based on simplified models, should provide certified tools enabling the best design for every situation. This article met the requirements for a gold/gold JIE data openness badge described at http://jie.click/badges.     

Using intra‐individual variation in shrub architecture to explain population cover

Plant architecture is related to the performance of long‐lived plants; its role in promoting species coexistence and in successional patterns is now widely recognized. However, because plant architecture involves branching processes, it is highly variable at the intra‐specific level. In this paper, we address two questions: what is the best way to describe plant architecture to obtain meaningful information for explaining population cover: at the whole‐plant level, or at the level of its unitary constituent parts? Further, are there architectural designs related to populations’ success? We evaluated the relative impact of ontogeny and whole‐plant traits on the cover achieved by the populations of five shrub species developing on 25 abandoned farmlands in southwestern Québec (Canada). We compared four ways of analyzing plant architecture: 1–2) using morphological traits described at the scale of a module (an elementary architectural unit made up of all the different types of shoots), with or without taking into account the ontogeny of the whole organism, 3) using the rate of changes during ontogeny as traits, and 4) using whole‐plant traits describing branching processes at a scale larger than modules. We then used variation partitioning to discriminate the actual effects of these traits on percent cover of the species from hidden effects due to plant ontogenesis and population spatial structure. Our results suggest that the predominant variables that effectively describe population cover vary from one species to another. At the same time, whole‐plant architectural traits and the rate of change of morphological traits during ontogeny both have an important effect on population cover. These findings suggest that acknowledging the developmental pattern of woody species can clarify the impact of intra‐specific trait variation on population cover.     

The definition,recognition, and interpretation of convergent evolution,and two new measures for quantifying and assessing the significance of convergence

Convergent evolution is an important phenomenon in the history of life. Despite this, there is no common definition of convergence used by biologists. Instead, several conceptually different definitions are employed. The primary dichotomy is between pattern‐based definitions, where independently evolved similarity is sufficient for convergence, and process‐based definitions, where convergence requires a certain process to produce this similarity. The unacknowledged diversity of definitions can lead to problems in evolutionary research. Process‐based definitions may bias researchers away from studying or recognizing other sources of independently evolved similarity, or lead researchers to interpret convergent patterns as necessarily caused by a given process. Thus, pattern‐based definitions are recommended. Existing measures of convergence are reviewed, and two new measures are developed. Both are pattern based and conceptually minimal, quantifying nothing but independently evolved similarity. One quantifies the amount of phenotypic distance between two lineages that is closed by subsequent evolution; the other simply counts the number of lineages entering a region of phenotypic space. The behavior of these measures is explored in simulations; both show acceptable Type I and Type II error. The study of convergent evolution will be facilitated if researchers are explicit about working definitions of convergence and adopt a standard toolbox of convergence measures.