About
14
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Introduction
I am a physical geographer specialized in permafrost geomorphology. I am currently working on multiple projects focusing on ground ice, the permafrost thermal regime, thermo-erosional gullies, and coastal erosion.
Current institution
Additional affiliations
June 2024 - present
September 2020 - December 2020
May 2020 - April 2022
Education
September 2015 - March 2020
September 2013 - August 2015
September 2010 - August 2013
Publications
Publications (14)
Thermo-erosion gullies (TEGs) are one of the most common forms of abrupt permafrost degradation. They generally form in ice-wedge polygonal networks where the interconnected troughs can channel runoff water. Although TEGs can form within a single thawing season, it takes them several decades to stabilize completely. While the inception of TEGs has...
Ice-wedge pseudomorphs (IWPs) are thermokarst structures that form by the secondary infilling of cavities left by the slow melting of ice wedges. Contemporary IWP formation in periglacial environments informs our understanding of past processes and dynamics implied by their presence in the stratigraphic record. However, contemporary IWPs are seldom...
Thermo-erosion gullies (TEGs) are one of the most common forms of abrupt permafrost degradation. They generally form in ice-wedge polygonal networks where the interconnected troughs can channel runoff water. Although TEG can form within a single thawing season, it takes them several decades for their complete stabilization. While the inception of T...
This poster presents results of a study undertaken on Bylot Island, NU (Canada), about the long-term stabilization of thermo-erosion gullies and the resilience of permafrost.
Lack of integration between permafrost geomorphology, hydrology, ecology and biogeochemistry limits understanding of landscape resilience and vulnerability.
This study tested the efficacy of air-convection-reflective sheds (ACRS) installed along the Alaska Highway in Yukon (Canada) as a mitigation technique to reduce heat absorption during the thawing season and to increase heat loss during the freezing season. Soil surface, air, and ground temperatures were recorded under the ACRS between 2008 and 201...
Simulations with a one-dimensional heat transfer model (TONE) were performed to
reproduce the near surface ground temperature regime in the four main types of
soil profiles found in Narsajuaq River Valley (Nunavik, Canada) for the period
1990–2100. The permafrost thermal regime was simulated using climate data from a
reanalysis (1948–2002), climate...
Soils in the northern circumpolar region play a central role in the global carbon cycle because the release of carbon through permafrost thaw and geomorphological disturbances can potentially cause a feedback on climate. However, large uncertainties in estimates of permafrost carbon stocks remain, mainly because of wide gaps in the spatial coverage...
To assess the direct impact of climate change on ice‐wedge (IW) degradation, 16 sites in the Narsajuaq river valley (Nunavik, Canada) that were extensively studied between 1989 and 1991 were revisited in 2016, 2017 and 2018. In total, 109 pits were dug to record soil characteristics and IW shapes and depths. Changes in surface conditions were also...
This poster is about the first chapter of my Ph.D. thesis.
Polygonal peatlands are carbon-rich permafrost ecosystems that will likely be significantly affected by climate change. However, studies are often constrained to one measurement per day, which impedes assessments of the temporal variability in carbon fluxes. For this reason, we measured ecosystem respiration (ER) of CO2 in a polygonal peatland unde...
Questions
Questions (5)
Hi all,
I want to use the algorithm provided by Staub et al. (2016; ), but my very limited skills in R are not enough to get the script going. There seems to be a bug in the script, but I can't decipher the code.
The scripts and sample data are in the supplementary material of the paper if you want to have a crack at it. And yes, I reached out to the authors but either no answer or they don't have time to help me.
Hello,
Recently I finished analyzing a series of soil samples in order to determiner the carbon content of the samples. The samples were collected at different depths and vary in carbon content, from highly mineral (coarse sand) to organic (peat and mixture of sand and peat).
First, I did the total carbon (TC). To do so, I sent my samples to a lab, which used a LECO628 Carbon/Hydrogen/Nitrogen determinator to give my the CHN concentrations. Beforehand, I had dried and crushed all samples.
After, I used the loss on ignition (LOI) method to determine the fraction of organic carbon. The samples were heated at 475°C during 6h, then the oven was turned off and the samples were left in the oven overnight. Then, I converted the soil organic matter (SOM) to soil organic carbon (SOC) using a 58% correction factor (since SOM has conventionally been assumed to contain, on average, 58% SOC).
However, to my great surprise, all SOC values are ~22% higher than the TC values, which does not make any sense. I verified with the lab about the TC results and everything seemed normal when done (the analyses were done in two batches, so if there had be a mistake with the blanks it would have shown in half the samples). I also wondered about the 58%, thinking that the value does not fit my samples. However, the relationship between SOC and TC is consistently linear throughout all carbon concentrations, indicating a systematic error (see attached file).
Has anyone ever seen or heard about a similar problem? Any suggestions about the source of the problem or where I could have made a mistake?
I would like to create a map of vegetation based on vegetation surveys made in the field. I have 340 points spread throughout the studied area where I recorded vegetation by strata ( a % for each strata) and a multispectral satellite image of the area.
I would like to use those percentages and link them with an equation or algorithm to the pixels of the multispectral image in ArcGIS. Thus, a combination of bands will have a specific combination of percentages from the strata. I then want to use those combinations to map vegetation everywhere on my satellite image.
I am looking for way to do this on ArcGIS if possible.
I want to date gas emitted from soil (permafrost) and determine where this carbon comes from (what depth).
From what I saw in the literature, the only way to do this is to do incubations and then link the results with the field values.
Are there other ways?
Hi,
I want to calculate non-linear gas flux and to do so I was told to
1) plot [CO2] vs Time
2) fit a polynomial curve 2nd order to the plot (quadratic function y = at2 + bt + c)
and 3) use the term b in my equation as the flux (which would be my flux at t=0 if I derive the equation to y' = 2at + b).
I am a little confused because I was originally told this is linear regression, although it seems to me this is quadratic regression, which would be a good way to calculate non-linear gas flux.
