Bryophyte diversity and rare species estimation in boreal forests using remote sensing

PhD Project of Carlos Cerrejon

Directors: Nicole Fenton (UQAT-FIR) and Osvaldo Valeria (UQAT-FIR)
Collaborators: Philippe Marchand (UQAT-FIR), Richard Caners (Royal Alberta Museum), France Trépanier and Marjorie Bujold (Goldcorp - Éléonore)

This project, funded by UQAT and Environment and Climate Change Canada, has as its main objective to develop predictive models at medium and high resolution for three aspects of bryophyte biodiversity (alpha diversity, beta diversity, and probability of occurrence of rare species) in remote boreal forests in northern Canada. Different modeling techniques (e.g. machine-learning technique Random Forest or Maxent) and approaches (e.g. traditional SDMs or ESMs) will be used in the development of these models. Explanatory variables from different remote sensing sources will be integrated into the models: data from the MFFP forestmapa, bands and spectral indices (e.g. NDVI, EVI, NDWI) derived from Landsat, Sentinel-2, and ALOS PALSAR satellites at 30m spatial resolution, and fromWorldview satellite at 2m resolution, dNBR), climatic variables provided by Ouranos and topographic variables derived from the digital elevation model. Response variables (e.g. richness or probability of presence) will be developed using presence/absence bryophyte field databases, includings existing data from three previous projects. In addition, new field data collected between August 7th and September 4th 2018 in the vicinity of the Goldcorp Eleonore mine will be used.

This project aims to promote the cohabitation of industrial development and biodiversity conservation in northern Canada, where bryophytes not only represent a large part of plant diversity but also constitute a key piece of boreal ecosystem functioning.