5 Works

Data from: Decomposing changes in phylogenetic and functional diversity over space and time

Loïc Chalmandrier, Tamara Münkemüller, Vincent Devictor, Sébastien Lavergne & Wilfried Thuiller
1. The α, β, γ diversity decomposition methodology is commonly used to investigate changes in diversity over space or time but rarely conjointly. However, with the ever-increasing availability of large-scale biodiversity monitoring data, there is a need for a sound methodology capable of simultaneously accounting for spatial and temporal changes in diversity. 2. Using the properties of Chao's index, we adapted Rao's framework of diversity decomposition between orthogonal dimensions to a multiplicative α, β, γ...

Data from: Large chromosomal rearrangements during a long-term evolution experiment with Escherichia coli

Colin Raeside, Joël Gaffé, Daniel E. Deatherage, Olivier Tenaillon, Adam M. Briska, Ryan N. Ptashkin, Stéphane Cruveiller, Claudine Médigue, Richard E. Lenski, Jeffrey E. Barrick & Dominique Schneider
Large-scale rearrangements may be important in evolution because they can alter chromosome organization and gene expression in ways not possible through point mutations. In a long-term evolution experiment, twelve Escherichia coli populations have been propagated in a glucose-limited environment for over 25 years. We used whole-genome mapping (optical mapping) combined with genome sequencing and PCR analysis to identify the large-scale chromosomal rearrangements in clones from each population after 40,000 generations. A total of 110 rearrangement...

Data from: Genomics of the divergence continuum in an African plant biodiversity hotspot, I: drivers of population divergence in Restio capensis (Restionaceae)

Christian Lexer, Rafael O. Wüest, Sofia Mangili, Myriam Heuertz, Kai N. Stolting, Peter B. Pearman, Felix Forest, Nicolas Salamin, Niklaus E. Zimmermann & Eligio Bossolini
Understanding the drivers of population divergence, speciation and species persistence is of great interest to molecular ecology, especially for species-rich radiations inhabiting the world’s biodiversity hotspots. The toolbox of population genomics holds great promise for addressing these key issues, especially if genomic data are analyzed within a spatially and ecologically explicit context. We have studied the earliest stages of the divergence continuum in the Restionaceae, a species-rich and ecologically important plant family of the Cape...

Data from: Replication levels, false presences, and the estimation of presence / absence from eDNA metabarcoding data

Gentile Francesco Ficetola, Johan Pansu, Aurélie Bonin, Marta De Barba, Eric Coissac, Charline Giguet-Covex, Ludovic Gielly, Carla Martins Lopes, Frédéric Boyer, François Pompanon, Gilles Rayé & Pierre Taberlet
Environmental DNA (eDNA) metabarcoding is increasingly used to study the present and past biodiversity. eDNA analyses often rely on amplification of very small quantities or degraded DNA. To avoid missing detection of taxa that are actually present (false negatives), multiple extractions and amplifications of the same samples are often performed. However, the level of replication needed for reliable estimates of the presence/absence patterns remains an unaddressed topic. Furthermore, degraded DNA and PCR/sequencing errors might produce...

Data from: Modelling plant species distribution in alpine grasslands using airborne imaging spectroscopy

Julien Pottier, Zbyněk Malenovský, Achilleas Psomas, Lucie Homolová, Michael E. Schaepman, Philippe Choler, Wilfried Thuiller, Antoine Guisan & Niklaus E. Zimmermann
Remote sensing using airborne imaging spectroscopy (AIS) is known to retrieve fundamental optical properties of ecosystems. However, the value of these properties for predicting plant species distribution remains unclear. Here, we assess whether such data can add value to topographic variables for predicting plant distributions in French and Swiss alpine grasslands. We fitted statistical models with high spectral and spatial resolution reflectance data and tested four optical indices sensitive to leaf chlorophyll content, leaf water...

Registration Year

  • 2014

Resource Types

  • Dataset


  • Grenoble Alpes University
  • University of Lausanne
  • French National Centre for Scientific Research
  • Swiss Federal Institute for Forest, Snow and Landscape Research
  • Swiss Institute of Bioinformatics
  • The University of Texas at Austin
  • Royal Botanic Gardens
  • University of Fribourg
  • Genoscope
  • University of Zurich