5 Works

Data from: Very high resolution digital elevation models: are multi-scale derived variables ecologically relevant?

Kevin Leempoel, Christian Parisod, Céline Geiser, Lucas Daprà, Pascal Vittoz & Stéphane Joost
Digital Elevation Models (DEMs) are often used in landscape ecology to retrieve elevation or first derivative terrain attributes such as slope or aspect in the context of species distribution modelling. However, DEM-derived variables are scale-dependent and, given the increasing availability of very high resolution (VHR) DEMs, their ecological relevance must be assessed for different spatial resolutions. In a study area located in the Swiss Western Alps, we computed VHR DEMs-derived variables related to morphometry, hydrology...

Data from: Peatland vascular plant functional types affect methane dynamics by altering microbial community structure

Bjorn J. M. Robroek, Vincent E. J. Jassey, Martine A. R. Kox, Roeland L. Berendsen, Robert T. E. Mills, Lauric Cécillon, Jéremy Puissant, Marion Meima–Franke, Peter A. H. M. Bakker, Paul L. E. Bodelier & Marion Meima-Franke
1. Peatlands are natural sources of atmospheric methane (CH4), an important greenhouse gas. It is established that peatland methane dynamics are controlled by both biotic and abiotic conditions, yet the interactive effect of these drivers is less studied and consequently poorly understood. 2. Climate change affects the distribution of vascular plant functional types (PFTs) in peatlands. By removing specific PFTs, we assessed their effects on peat organic matter chemistry, microbial community composition and on potential...

Data from: Diffusion tensor imaging in patients with glioblastoma multiforme using the supertoroidal model

Choukri Mekkaoui, Philippe Metellus, William J. Kostis, Roberto Martuzzi, Fabricio R. Pereira, Jean-Paul Beregi, Timothy G. Reese, Todd R. Constable & Marcel P. Jackowski
Purpose: Diffusion Tensor Imaging (DTI) is a powerful imaging technique that has led to improvements in the diagnosis and prognosis of cerebral lesions and neurosurgical guidance for tumor resection. Traditional tensor modeling, however, has difficulties in differentiating tumor-infiltrated regions and peritumoral edema. Here, we describe the supertoroidal model, which incorporates an increase in surface genus and a continuum of toroidal shapes to improve upon the characterization of Glioblastoma multiforme (GBM). Materials and Methods: DTI brain...

Data from: The population genomics of rapid adaptation: disentangling signatures of selection and demography in white sands lizards

Stefan Laurent, Susanne P. Pfeifer, Matthew Settles, Samuel S. Hunter, Kayla M. Hardwick, Louise Ormond, Vitor C. Sousa, Jeffrey D. Jensen, Erica Bree Rosenblum & Matthew L. Settles
Understanding the process of adaptation during rapid environmental change remains one of the central focal points of evolutionary biology. The recently formed White Sands system of southern New Mexico offers an outstanding example of rapid adaptation, with a variety of species having rapidly evolved blanched forms on the dunes that contrast with their close relatives in the surrounding dark soil habitat. In this study, we focus on two of the White Sands lizard species, Sceloporus...

Data from: Diffantom: whole-brain diffusion MRI phantoms derived from real datasets of the Human Connectome Project

Oscar Esteban, Emmanuel Caruyer, Alessandro Daducci, Meritxell Bach-Cuadra, María J. Ledesma-Carbayo & Andres Santos
Diffantom is a whole-brain diffusion MRI (dMRI) phantom publicly available through the Dryad Digital Repository (doi:10.5061/dryad.4p080). The dataset contains two single-shell dMRI images, along with the corresponding gradient information, packed following the BIDS standard (Brain Imaging Data Structure, Gorgolewski et al., 2015). The released dataset is designed for the evaluation of the impact of susceptibility distortions and benchmarking existing correction methods. In this Data Report we also release the software instruments involved in generating diffantoms,...

Registration Year

  • 2015

Resource Types

  • Dataset


  • École Polytechnique Fédérale de Lausanne
  • University of Lausanne
  • Swiss Institute of Bioinformatics
  • Massachusetts General Hospital
  • University of Neuchâtel
  • Radboud University Nijmegen
  • Nederlands Instituut voor Ecologie
  • French National Centre for Scientific Research
  • University of Bern
  • University of Sao Paulo