Publications associées à A landscape genomics approach to understanding and predicting species distribution

From roots to canopy: Unraveling the influence of species diversity on tree water relations under warmer and drier climates

The worsening of drought events with rising air temperature alters tree water relations causing severe hydraulic impairments and widespread forest mortality. Mixing tree species with contrasting hydraulic traits could reduce forest vulnerability to extreme ...

EPFL2024

Ancestral genome reconstruction enhances transposable element annotation by identifying degenerate integrants

Didier Trono, Evaristo Jose Planet Letschert, Wayo Matsushima

Growing evidence indicates that transposable elements (TEs) play important roles in evolution by providing genomes with coding and non-coding sequences. Identification of TE-derived functional elements, however, has relied on TE annotations in individual s ...

2024

At what spatial scale does natural selection operate? Using multiscale frameworks to calibrate the effects of environmental factors across landscape continuums

Annie Sandrine Guillaume

Patterns in nature arise from processes interacting across a continuum of spatial scales, where new relationships emerge at each level of investigation. These patterns are nested features encompassing fine-scale local patterns, such as topography and geolo ...

EPFL2024

On the selection and effectiveness of pseudo-absences for species distribution modeling with deep learning

Devis Tuia, Nina Marion Aurélia Van Tiel, Robin Adrien Zbinden, Benjamin Alexander Kellenberger, Lloyd Haydn Hughes

Species distribution modeling is a highly versatile tool for understanding the intricate relationship between environmental conditions and species occurrences. However, the available data often lacks information on confirmed species absence and is limited ...

2024

Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

Mohammad Khaja Nazeeruddin

Herein, machine learning (ML) models using multiple linear regression (MLR), support vector regression (SVR), random forest (RF) and artificial neural network (ANN) are developed and compared to predict the output features viz. specific capacitance (Csp), ...

Elsevier Science Sa2024

Euclid preparation XXXVII. Galaxy colour selections with Euclid and ground photometry for cluster weak-lensing analyses

Matthias Wiesmann, Georges Meylan, Frédéric Courbin, Fabio Finelli, Richard Massey, Maurizio Martinelli, Gianluca Castignani, Marcello Farina, Yi Wang

Aims. We derived galaxy colour selections from Euclid and ground-based photometry, aiming to accurately define background galaxy samples in cluster weak-lensing analyses. These selections have been implemented in the Euclid data analysis pipelines for gala ...

Edp Sciences S A2024

The microbial genomics of glacier-fed streams: adaptations to an extreme ecosystem

Massimo Bourquin

Glacier-fed streams are the cold, ultra-oligotrophic, and unstable streams that are fed by glacial meltwater. Despite these extreme conditions, they harbour a diverse and abundant microbial diversity that develops into biofilms, covering the boulders and s ...

EPFL2024

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Paul Scharnhorst

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

EPFL2024

Seebeck Coefficient of Ionic Conductors from Bayesian Regression Analysis

We propose a novel approach to evaluating the ionic Seebeck coefficient in electrolytes from relatively short equilibrium molecular dynamics simulations, based on the Green-Kubo theory of linear response and Bayesian regression analysis. By exploiting the ...

Amer Chemical Soc2024

Tree diversity reduces variability in sapling survival under drought

Charlotte Grossiord, Xiaojuan Liu, Jingjing Liang

Enhancing tree diversity may be important to fostering resilience to drought-related climate extremes. So far, little attention has been given to whether tree diversity can increase the survival of trees and reduce its variability in young forest plantatio ...

Wiley2024

The cost of adaptability: resource availability constrains functional stability under pulsed disturbances

Hannes Markus Peter

Global change exposes ecosystems to changes in the frequency, magnitude, and concomitancy of disturbances, which impact the composition and functioning of these systems. Here, we experimentally evaluate the effects of salinity disturbances and eutrophicati ...

Amer Soc Microbiology2024

Invasive palms have more efficient and prolonged CO2 assimilation compared to native sub-Mediterranean vegetation

Marco Conedera, Thibaut Michel Georges Juillard, Charlotte Grossiord, Christoph Bachofen, Janisse Deluigi

In sub-Mediterranean ecosystems, shade-tolerant broadleaf evergreens, especially the invasive Trachycarpus fortunei, are spreading uncontrollably in the forest understorey, impeding the regeneration of the native deciduous woody vegetation. Most invasive s ...

Elsevier2024

Reproductive isolation arises during laboratory adaptation to a novel hot environment

Ana Marija Jaksic

Background: Reproductive isolation can result from adaptive processes (e.g., ecological speciation and mutation-order speciation) or stochastic processes such as "system drift" model. Ecological speciation predicts barriers to gene flow between populations ...

BMC2024

Comparison of Three Viral Nucleic Acid Preamplification Pipelines for Sewage Viral Metagenomics

Tamar Kohn, Xavier Fernandez Cassi

Viral metagenomics is a useful tool for detecting multiple human viruses in urban sewage. However, more refined protocols are required for its effective use in disease surveillance. In this study, we investigated the performance of three different preampli ...

2024

Random matrix methods for high-dimensional machine learning models

Antoine Philippe Michel Bodin

In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

EPFL2024

Organ-specific biotransformation in salmonids: Insight into intrinsic enzyme activity and biotransformation of three micropollutants

Kristin Schirmer, Juliane Hollender

Aquatic ecosystems continue to be threatened by chemical pollution. To what extent organisms are able to cope with chemical exposure depends on their ability to display mechanisms of defense across different organs. Among these mechanisms, biotransformatio ...

Elsevier2024

Iterative removal of sources to model the turbulent electromotive force

Jennifer Waltraud Schober, Abhijit Bhausaheb Bendre

We describe a novel method to compute the components of dynamo tensors from direct magnetohydrodynamic (MHD) simulations. Our method relies upon an extension and generalization of the standard H & ouml;gbom CLEAN algorithm widely used in radio astronomy to ...

Oxford Univ Press2024

Variant-specific pathophysiological mechanisms of AFF3 differently influence transcriptome profiles

Christian Iseli, Nicolas Jean Philippe Guex, Giovanna Ambrosini

Background: We previously described the KINSSHIP syndrome, an autosomal dominant disorder associated with intellectual disability (ID), mesomelic dysplasia and horseshoe kidney,caused by de novo variants in the degron of AFF3. Mouse knock-ins and overexpre ...

BMC2024

Fish Diversity in Relation to Littoral Habitats in Three Basins of Lake Kivu (East Africa)

Alfred Johny Wüest

In total, 28 of the 29 fish species reported from the Lake Kivu basin occur in the littoral zone of the lake, but information about their structure, occurrence, and the habitats affecting their distribution is largely lacking. The lake's inshore area is po ...

MDPI2023

Sulfurospirillum diekertiae sp. nov., a tetrachloroethene-respiring bacterium isolated from contaminated soil

Christof Holliger, Julien Maillard, Junxiong Wang

Two anaerobic, tetrachloroethene- (PCE-) respiring bacterial isolates, designated strain ACSDCE T and strain ACSTCE, were characterized using a polyphasic approach. Cells were Gram-stain-negative, motile, non-spore-forming and shared a vibrioid- to spirill ...

2023