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Choudhury B.I.,Concordia University at Montréal | Choudhury B.I.,Quebec Center for Biodiversity science | Khan M.L.,Dr Hari Singh Gour University | Dayanandan S.,Concordia University at Montréal | Dayanandan S.,Quebec Center for Biodiversity science
BMC Genetics | Year: 2014

Background: During the domestication of crops, individual plants with traits desirable for human needs have been selected from their wild progenitors. Consequently, genetic and nucleotide diversity of genes associated with these selected traits in crop plants are expected to be lower than their wild progenitors. In the present study, we surveyed the pattern of nucleotide diversity of two selected trait specific genes, Wx and OsC1, which regulate amylose content and apiculus coloration respectively in cultivated rice varieties. The analyzed samples were collected from a wide geographic area in Northeast (NE) India, and included contrasting phenotypes considered to be associated with selected genes, namely glutinous and nonglutinous grains and colored and colorless apiculus.Results: No statistically significant selection signatures were detected in both Wx and OsC1gene sequences. However, low level of selection that varied across the length of each gene was evident. The glutinous type varieties showed higher levels of nucleotide diversity at the Wx locus (πtot = 0.0053) than nonglutinous type varieties (πtot = 0.0043). The OsC1 gene revealed low levels of selection among the colorless apiculus varieties with lower nucleotide diversity (πtot = 0.0010) than in the colored apiculus varieties (πtot = 0.0023).Conclusions: The results revealed that functional mutations at Wx and OsC1genes considered to be associated with specific phenotypes do not necessarily correspond to the phenotypes in indigenous rice varieties in NE India. This suggests that other than previously reported genomic regions may also be involved in determination of these phenotypes. © 2014 Choudhury et al.; licensee BioMed Central Ltd.


Gravel D.,Université de Sherbrooke | Gravel D.,Quebec Center for Biodiversity Science | Albouy C.,ETH Zurich | Albouy C.,Swiss Federal Institute of forest | And 2 more authors.
Philosophical Transactions of the Royal Society B: Biological Sciences | Year: 2016

There is a growing interest in using trait-based approaches to characterize the functional structure of animal communities. Quantitative methods have been derived mostly for plant ecology, but it is now common to characterize the functional composition of various systems such as soils, coral reefs, pelagic food webs or terrestrial vertebrate communities. With the ever-increasing availability of distribution and trait data, a quantitative method to represent the different roles of animals in a community promise to find generalities that will facilitate cross-system comparisons. There is, however, currently no theory relating the functional composition of food webs to their dynamics and properties. The intuitive interpretation that more functional diversity leads to higher resource exploitation and better ecosystem functioning was brought from plant ecology and does not apply readily to food webs. Here we appraise whether there are interpretable metrics to describe the functional composition of food webs that could foster a better understanding of their structure and functioning. We first distinguish the various roles that traits have on food web topology, resource extraction (bottom-up effects), trophic regulation (top-down effects), and the ability to keep energy and materials within the community. We then discuss positive effects of functional trait diversity on food webs, such as niche construction and bottom-up effects. We follow with a discussion on the negative effects of functional diversity, such as enhanced competition (both exploitation and apparent) and top-down control. Our review reveals that most of our current understanding of the impact of functional trait diversity on food web properties and functioning comes from an over-simplistic representation of network structure with well-defined levels. We, therefore, conclude with propositions for new research avenues for both theoreticians and empiricists. © 2016 The Author(s) Published by the Royal Society. All rights reserved.


Gravel D.,University of Quebec at Rimouski | Gravel D.,Quebec Center for Biodiversity Science | Poisot T.,University of Quebec at Rimouski | Poisot T.,Quebec Center for Biodiversity Science | And 5 more authors.
Methods in Ecology and Evolution | Year: 2013

Current global changes make it important to be able to predict which interactions will occur in the emerging ecosystems. Most of the current methods to infer the existence of interactions between two species require a good knowledge of their behaviour or a direct observation of interactions. In this paper, we overcome these limitations by developing a method, inspired from the niche model of food web structure, using the statistical relationship between predator and prey body size to infer the matrix of potential interactions among a pool of species. The novelty of our approach is to infer, for any species of a given species pool, the three species-specific parameters of the niche model. The method applies to both local and metaweb scales. It allows one to evaluate the feeding interactions of a new species entering the community. We find that this method gives robust predictions of the structure of food webs and that its efficiency is increased when the strength of the body-size relationship between predators and preys increases. We finally illustrate the potential of the method to infer the metaweb structure of pelagic fishes of the Mediterranean sea under different global change scenarios. © 2013 British Ecological Society.


Weitz J.S.,Georgia Institute of Technology | Poisot T.,University of Quebec at Rimouski | Poisot T.,Quebec Center for Biodiversity science | Meyer J.R.,Michigan State University | And 5 more authors.
Trends in Microbiology | Year: 2013

Phage and their bacterial hosts are the most abundant and genetically diverse group of organisms on the planet. Given their dominance, it is no wonder that many recent studies have found that phage-bacteria interactions strongly influence global biogeochemical cycles, incidence of human diseases, productivity of industrial microbial commodities, and patterns of microbial genome diversity. Unfortunately, given the extreme diversity and complexity of microbial communities, traditional analyses fail to characterize interaction patterns and underlying processes. Here, we review emerging systems approaches that combine empirical data with rigorous theoretical analysis to study phage-bacterial interactions as networks rather than as coupled interactions in isolation. © 2012 Elsevier Ltd.


Hobaiter C.,University of St. Andrews | Poisot T.,University of Quebec at Rimouski | Poisot T.,Quebec Center for Biodiversity science | Zuberbuhler K.,University of St. Andrews | And 4 more authors.
PLoS Biology | Year: 2014

Social network analysis methods have made it possible to test whether novel behaviors in animals spread through individual or social learning. To date, however, social network analysis of wild populations has been limited to static models that cannot precisely reflect the dynamics of learning, for instance, the impact of multiple observations across time. Here, we present a novel dynamic version of network analysis that is capable of capturing temporal aspects of acquisition—that is, how successive observations by an individual influence its acquisition of the novel behavior. We apply this model to studying the spread of two novel tool-use variants, “moss-sponging” and “leaf-sponge re-use,” in the Sonso chimpanzee community of Budongo Forest, Uganda. Chimpanzees are widely considered the most “cultural” of all animal species, with 39 behaviors suspected as socially acquired, most of them in the domain of tool-use. The cultural hypothesis is supported by experimental data from captive chimpanzees and a range of observational data. However, for wild groups, there is still no direct experimental evidence for social learning, nor has there been any direct observation of social diffusion of behavioral innovations. Here, we tested both a static and a dynamic network model and found strong evidence that diffusion patterns of moss-sponging, but not leaf-sponge re-use, were significantly better explained by social than individual learning. The most conservative estimate of social transmission accounted for 85% of observed events, with an estimated 15-fold increase in learning rate for each time a novice observed an informed individual moss-sponging. We conclude that group-specific behavioral variants in wild chimpanzees can be socially learned, adding to the evidence that this prerequisite for culture originated in a common ancestor of great apes and humans, long before the advent of modern humans. © 2014 Hobaiter et al.


Poisot T.,University of Quebec at Rimouski | Poisot T.,Quebec Center for Biodiversity science | Mouquet N.,Montpellier University | Gravel D.,University of Quebec at Rimouski | Gravel D.,Quebec Center for Biodiversity science
Ecology Letters | Year: 2013

The biodiversity-ecosystem functioning (BEF) relationship is central in community ecology. Its drivers in competitive systems (sampling effect and functional complementarity) are intuitive and elegant, but we lack an integrative understanding of these drivers in complex ecosystems. Because networks encompass two key components of the BEF relationship (species richness and biomass flow), they provide a key to identify these drivers, assuming that we have a meaningful measure of functional complementarity. In a network, diversity can be defined by species richness, the number of trophic levels, but perhaps more importantly, the diversity of interactions. In this paper, we define the concept of trophic complementarity (TC), which emerges through exploitative and apparent competition processes, and study its contribution to ecosystem functioning. Using a model of trophic community dynamics, we show that TC predicts various measures of ecosystem functioning, and generate a range of testable predictions. We find that, in addition to the number of species, the structure of their interactions needs to be accounted for to predict ecosystem productivity. © 2013 John Wiley & Sons Ltd/CNRS.


Tobner C.M.,University of Quebec at Montréal | Paquette A.,University of Quebec at Montréal | Reich P.B.,University of Minnesota | Reich P.B.,University of Western Sydney | And 4 more authors.
Oecologia | Year: 2014

Increasing concern about loss of biodiversity and its effects on ecosystem functioning has triggered a series of manipulative experiments worldwide, which have demonstrated a general trend for ecosystem functioning to increase with diversity. General mechanisms proposed to explain diversity effects include complementary resource use and invoke a key role for species' functional traits. The actual mechanisms by which complementary resource use occurs remain, however, poorly understood, as well as whether they apply to tree-dominated ecosystems. Here we present an experimental approach offering multiple innovative aspects to the field of biodiversity-ecosystem functioning (BEF) research. The International Diversity Experiment Network with Trees (IDENT) allows research to be conducted at several hierarchical levels within individuals, neighborhoods, and communities. The network investigates questions related to intraspecific trait variation, complementarity, and environmental stress. The goal of IDENT is to identify some of the mechanisms through which individuals and species interact to promote coexistence and the complementary use of resources. IDENT includes several implemented and planned sites in North America and Europe, and uses a replicated design of high-density tree plots of fixed species-richness levels varying in functional diversity (FD). The design reduces the space and time needed for trees to interact allowing a thorough set of mixtures varying over different diversity gradients (specific, functional, phylogenetic) and environmental conditions (e.g., water stress) to be tested in the field. The intention of this paper is to share the experience in designing FD-focused BEF experiments with trees, to favor collaborations and expand the network to different conditions. © 2013 Springer-Verlag Berlin Heidelberg.


Poisot T.,University of Quebec at Rimouski | Poisot T.,Quebec Center for Biodiversity Science
F1000Research | Year: 2013

Measuring the modularity of networks, and how it deviates from random expectations, important to understand their structure and emerging properties. Several measures exist to assess modularity, which when applied to the same network, can return both different modularity values (i.e. different estimates of how modular the network is) and different module compositions (i.e. different groups of species forming said modules). More importantly, as each optimization method uses a different optimization criterion, there is a need to have an a posteriori measure serving as an equivalent of a goodness-of-fit. In this article, I propose such a measure of modularity, which is simply defined as the ratio of interactions established between members of the same modules vs. members of different modules. I apply this measure to a large dataset of 290 ecological networks representing host-parasite (bipartite) and predator-prey (unipartite) interactions, to show how the results are easy to interpret and present especially to a broad audience not familiar with modularity analyses, but still can reveal new features about modularity and the ways to measure it. © 2013 Poisot T.


Poisot T.,University of Quebec at Rimouski | Gravel D.,Quebec Center for Biodiversity science
PeerJ | Year: 2014

Connectance and degree distributions are important components of the structure of ecological networks. In this contribution, we use a statistical argument and simple network generating models to show that properties of the degree distribution are driven by network connectance.We discuss the consequences of this finding for (1) the generation of random networks in null-model analyses, and (2) the interpretation of network structure and ecosystem properties in relationship with degree distribution. ©2014 Poisot et al.


Moses M.,University of the West Indies | Umaharan P.,University of the West Indies | Dayanandan S.,Concordia University at Montréal | Dayanandan S.,Quebec Center for Biodiversity Science
Genetic Resources and Crop Evolution | Year: 2014

Capsicum chinense Jacq., one of the five domesticated species of pepper grown in the New World, is a major contributor to both local and international markets and the economy of the Caribbean islands. The planning and implementation of germplasm conservation and breeding programs for the sustainable use of C. chinense genetic resources are hampered by the poor understanding of the genetic structure and diversity of C. chinense in the region. In the present study, the genetic structure, diversity and relatedness of C. chinense germplasm collections within the Caribbean basin and South America were assessed using nuclear microsatellite markers. C. chinense accessions (102) representing seven geographical regions were genotyped using nine polymorphic nuclear microsatellite markers along with 16 accessions representing four other species of Capsicum. The results revealed that the highest genetic diversity (He = 0.58) was found in the Amazon region supporting the postulated center of diversity of C. chinense as the Amazon basin. The cluster analysis resulted in two distinct genetic clusters corresponding to Upper Amazon and Lower Amazon regions, suggesting two independent domestication events or two putative centers of diversity in these regions respectively. The cluster analysis further revealed that populations in Central America and the Caribbean may have been primarily derived from progenitors from Upper Amazon region and later diverged through geographical isolation. Conservation and germplasm collection programs should therefore target these genetically distinct clusters and satellite populations, towards supporting breeding programs to harness heterosis. © 2013 Springer Science+Business Media Dordrecht.

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