Seminar

POSTPONED – Due to unforeseen circumstances today’s seminar has been postponed.

We will let you know as soon as we have a new date for the seminar.

Thank you for your understanding.

Léa Cornette will be presenting Tundra Firescape : Vegetation Succession and Perceptions.

Please note that the seminar will be presented in French, with slides provided in English.

Veuillez noter que le séminaire sera présenté en français, avec des diapositives en anglais.

Date: POSTPONED
Time: 13:00-14:00 Eastern Time
Location: Zoom (details are posted in our Teams site).

Increased wildfire activity regimes in the Arctic tundra is a growing concern owing to their ecological and human impacts. This study explores the long-term effects of wildfires on soil physical properties, nutrients availability and vegetation succession, using a fire scar chronosequence (EV034-68, EV014-12, EV014-23) in the Inuvialuit Settlement Region (ISR) around Inuvik. Using a mixed approach, this study also aims to understand the perceptions of community members from the ISR of how wildfires, but also weather and climate variations, modify the landscape and their relationship with it.

Muhammad Umair will be presenting Characterizing carbon and water fluxes in the arctic boreal forest using plant hydraulics parameterization in the presence and absence of permafrost: a modelling approach.

Date: 16 July 2025
Time: 13:00-14:00 Eastern Time
Location: Zoom (details are posted in our Teams site).

Stomatal conductance in terrestrial biosphere models (TBMs) plays a critical role in accurately simulating carbon and water fluxes, and for evaluating the impacts of climate change on land surface-atmosphere interactions. Climate change impacts such as more frequent heat waves and drought conditions challenge TBMs and need to be investigated thoroughly, especially in the rapidly changing arctic boreal forest. Terrestrial biosphere models such as the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) often employ empirical formulations that link soil moisture to stomatal conductance. These soil moisture-based empirical approaches typically perform poorly under drought conditions.

Our study implemented an explicit plant hydraulics parameterization in CLASSIC to connect the soil-plant-atmosphere continuum through plant hydraulic traits, i.e., stomatal optimization based on xylem hydraulics (SOX), resulting in CLASSIC_SOX. Model performance was evaluated at eight arctic boreal forest sites; three are permafrost-free, four are in the discontinuous permafrost zone, and one is in the continuous permafrost zone. Compared to the default CLASSIC, simulated gross primary production (GPP) improved at all eight sites with CLASSIC_SOX. Drought conditions at the eight sites were identified using the Palmer Drought Severity Index, and the results showed improvement in simulated GPP during drought conditions. Overall, the SOX parameterization achieved improved results compared to CLASSIC by-default at all sites, specifically for the sites located at the continuous and discontinuous permafrost zone.

Adeleh Moqadam will be presenting Flood Susceptibility Assessment of the Hudson Bay Railway.

Date: 2 July 2025
Time: 13:00-14:00 Eastern Time
Location: Zoom (details are posted in our Teams site).

The Hudson Bay Railway (HBR) is a critical transportation link in northern Manitoba, providing access to the Port of Churchill. Its location across a permafrost region and extensive wetlands poses ongoing drainage challenges, especially under changing climate conditions. Washouts along the railway over the past decade, caused by excessive water flow, have highlighted its vulnerability to flooding events.

In this seminar, Adeleh will present two studies that preliminarily assess flood risk potential along the HBR using GIS analysis and hydrological modeling. The first study involves developing a flood susceptibility map to identify segments of the track that are more prone to flooding. The second study quantifies potential increases in runoff due to climate change at a railway bridge in the Weir River basin, which was previously identified as a highly flood-prone area. This is done by developing a semi-distributed hydrological model using the Raven Hydrological Modelling Framework. After calibrating the model under current climate conditions, it was forced with climate change projections to simulate future peak flows. Findings from these studies aim to support decision-makers in improving the HBR drainage system and enhancing its long-term resilience to climate change.

Niek Jesse Speetjens will be presenting Beyond Frozen Ground: Seeing Ground Ice and Terrain Through a Different Lens.

Date: 18 June 2025
Time: 13:00-14:00 Eastern Time
Location: Zoom (details are posted in our Teams site).

Permafrost science spans a wide range of disciplines and landscapes, united by a common goal: understanding the impacts of climate change on sensitive permafrost regions. Yet, there is little consensus on how to classify terrain units with similar responses to change—making cross-disciplinary and cross-study synthesis a persistent challenge. This is further complicated by the multi-scale nature of the processes we study, from fine-resolution field observations to global-scale Earth system models. To meaningfully connect these scales, we need a shared framework that unifies how we view and classify permafrost terrain across scales and disciplines.

Lucas Fuertes will be presenting A terrain-based method for snow depth prediction applied in Svalbard, Norway.

Date: 11 June 2025
Time: 13:00-14:00 Eastern Time
Location: Zoom (details are posted in our Teams site).

Snow is an effective insulator, mediating the effects of climate on the ground thermal regime. Snow is also an important part of the hydrologic cycle, storing and releasing water which influences the functioning of arctic ecosystems as well as energy exchanges with the ground surface. Crucial to both processes are the properties of the snow, topography, and climate, however, models that account for all these variables are data intensive. This presentation suggests a machine learning methodology that leverages terrain-based parameters to estimate snow depths and outlines its applicability in the glacial forefield of Scott Turnerbreen, Svalbard, Norway. Such a model has potential to improve estimates of snow water equivalence across the study site and aid in quantifying the effects of snow on the underlying permafrost.

Liam Carson will be presenting Proglacial Retrogressive Thaw Slumping, Svalbard.

Date: 4 June 2025
Time: 13:00-14:00 Eastern Time
Location: Zoom (details are posted in our Teams site).

The Arctic is warming rapidly, driving cryospheric changes like glacial retreat and permafrost thaw that transform proglacial landscapes. This study examines ice-cored moraine dynamics in Scott Turnerbreen (STB) and Longyearbreen (LYB) in central Spitsbergen using UAV surveys, satellite imagery, and Ground Penetrating Radar. Since 2018, STB lost 67,350 m³ of material, while LYB lost 115,252 m³, driven by larger Retrogressive Thaw Slumps (RTS). The findings highlight the impacts of ice-cored moraine thaw on geomorphology, sediment release, and hydrology, emphasizing the need for continued monitoring and predictive modelling.