Supervised by:

Alexandre Roy (Regular Member (Co-researcher))

Co-supervised by:

Esther Lévesque (Regular Member (Co-researcher))

Research project description

Greening of the Kuurujuaq Watershed: Monitoring the Evolution of Vegetation Communities via Drone

Introduction

Global warming in tundra, subarctic, and boreal regions is driving significant changes in the composition of vegetation communities (Myers-Smith et al., 2019). These transformations are characterized by an expansion of shrubs, particularly species such as birch, willow, and alder. The underlying processes behind these changes remain poorly understood (Bayle et al., 2022). For instance, the effect of this greening on the density and production of small fruits has been little studied but could be better understood with a novel index sensitive to anthocyanin pigments.

Objectives

This study aims to assess the dynamics of the vegetation covering the Koroc River valley in Kuurujuaq National Park, to examine the impact of climate change on the evolution of small-fruited species.

Study Sites

The study site is located in the Koroc River valley within Kuurujuaq National Park in Nunavik. This subarctic region, subject to marked climatic changes, exhibits a unique vegetation dynamic. In 2022, a collaboration between the Université du Québec à Trois-Rivières and Nunavik Park enabled the collection of drone imagery and ground vegetation data during two field campaigns: one in mid-July at the peak of flowering and the other in early September during senescence.

Material and methods

To achieve this, a range of data spanning a latitudinal gradient within the Koroc River watershed will be used: (1) high spatial resolution multispectral drone imagery, and (2) ground vegetation measurements from 104 plots. The study aims to develop a tool capable of mapping the distribution of key vegetation species (dwarf birch, black spruce, small fruits, and lichens) in critical areas of the park. In addition to the NDVI (Normalized Difference Vegetation Index), a Normalized Anthocyanin Reflectance Index (NARI) will be calculated to detect berry-bearing shrubs, particularly blueberries. Adapted from the Anthocyanin Reflectance Index, NARI is sensitive to the anthocyanin content of the vegetation canopy. The multispectral imagery and indices will be used to develop a high-resolution classification using advanced algorithms (optimized object-based classifications and random forests). Ground observations will calibrate and evaluate the algorithm’s performance.

References

Assmann, J. J., Myers-Smith, I. H., Kerby, J. T., Cunliffe, A. M., & Daskalova, G. N. (2020). Drone data reveal heterogeneity in tundra greenness and phenology not captured by satellites. Environmental Research Letters, 15(12). https://doi.org/10.1088/1748-9326/abbf7d Bayle, A., Roy, A., Dedieu, J.-P., Boudreau, S., Choler, P.,

Research Site Coordinates