PhD Opportunity: Monitoring the impacts of climate change on biodiversity

The Government of Quebec’s Biodiversity Monitoring Network is the first large-scale project in Quebec to document changes in biodiversity on a large scale. It was developed through the 2013-2020 Action Plan on Climate Change in partnership with the Ministère des Forêts de la Faune et des Parcs (MFFP) and the Ministère de l’Environnement et de la Lutte aux Changements Climatiques (MELCC). Nearly 250 sites have been monitored since 2016, using about thirty indicators and taxonomic groups in a variety of environments (forest, tundra, bog, marsh, lake and river).

We are looking for a PhD student to synthesize the observations and develop interpretation tools.

Specific objectives include

  • Identify metrics to report biodiversity changes and study their drivers;
  • Develop a methodology for an integrated assessment of biodiversity changes at the ecosystem scale;
  • Assessing the distribution of species assemblages in relation to climate envelopes and modeling the impact of climate scenarios.

This project will provide a unique opportunity to join a multidisciplinary and collaborative process that includes partners from the academic, government, parks, conservation and indigenous sectors. The student will become familiar with various sampling methods and related analytical issues. The student will be asked to develop tools to represent the information in order to communicate the results to different audiences using new approaches (e.g. dashboards, podcasts, digital stories) on the Biodiversité Québec portal. The work will be done in collaboration with specialists in biodiversity, communication, design and data science.


A M.Sc. degree in biology, forestry, ecology, environmental sciences or biostatistics is required. The candidate must have knowledge and/or previous experience in handling large databases, programming, or at least a strong interest in developing these skills.


The research activities will take place at Biodiversité Québec at the Université de Sherbrooke under the supervision of Prof. Dominique Gravel, and at the Ministère Forêts Faune et Parcs under the supervision of Anouk Simard. The environment will be enhanced by the BIOS² training program in numerical methods and its entire community of students and researchers. Biodiversité Québec values diversity, equality, equity and inclusion and invites all qualified individuals to apply. Financial support of 22 000$/year is guaranteed for four years.


Applications, including a letter describing research interests, a CV, a copy of academic transcripts and information for two references, should be sent to Dominique Gravel ( and Anouk Simard ( with “PhD Application BDQC – name” in the subject line.

The offer will be open until a candidate is selected. Target start date: September 2022.

Introduction to microbiome analysis

An Introduction to Microbiome Analysis workshop will be presented as part of the BIOS² training program by Professor Steven Kembel (UQAM) on May 19 and 20, 2022 from 1 pm to 4 pm Eastern Time .

This workshop will give an overview of the theory and practice of using metabarcoding approaches to study the diversity of microbial communities. The workshop will give participants an understanding of 1) the current methods for microbiome diversity quantification using metabarcoding/amplicon sequencing approaches and 2) the normalization and diversity analysis approaches that can be used to quantify the diversity of microbial communities.

Forecasting biodiversity: A matter of data availability

In a previous post, we briefly discussed our internship experience with GEO BON, in which we developed a forecasting model of local contributions to beta diversity (LCBD) at the regional scale, using communities of warblers species in Quebec and Colombia as a case study. The first part of our endeavor was getting access to data. As typical grad students in quantitative ecology, we used data mostly openly available on the internet. As mentioned in the previous post, for species occurrence, we used data from the eBird database, while environmental and land-use data were obtained from the CHELSA database and the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC), respectively. While these datasets are openly available, the steps required to actually use them and the digital space they occupy could represent a challenge for someone unfamiliar with such a task.