The initial biometerology of the constructed Sandhill Fen Watershed in Alberta, Canada
Bibliographic record
Abstract
Resource extraction has led to the loss of boreal landscapes.Recently, novel integrated landscapes have been constructed to return ecological functions lost due to disturbance.The Sandhill Fen Watershed (SFW) is one of the first of two such projects in the boreal plains ecozone.The SFW is a mix of upland, midland and lowland topographical features designed to develop into integrated boreal plains ecosystems.This thesis quantifies the initial carbon cycling dynamics within the SFW and contextualizes this development with studies on conventional reclamation projects and undisturbed ecosystems.Construction, vegetation seeding and planting of the SFW was mostly completed by 2012, and an initial wetting occurred in 2013.Methane fluxes remained low over the first three years.However, mobile ions of sulphur declined over this same period and could indicate shifting reduction-oxidation conditions favourable for future rates of methanogenesis.In the lowland, biogeochemical fluxes were indicative of highly reduced soil conditions.This was confirmed in 2015 with reduction-oxidation potential monitoring.Downscaled eddy covariance flux measurements showed that vegetation increased evapotranspiration (ET) rates in the lowland relative to non-vegetated water surfaces.Since there were no other substantial outflows of water from the SFW, greater rates of ET may lower the water table in the future and limit the carbon storage potential of the ecosystem through peat accumulation.Measurements of the CO2 exchange between the surface and the atmosphere showed that, with no other substantial carbon outputs, by its third year the SFW lowland had become a net carbon sink and had daily, monthly, and annual carbon cycling behaviour similar to undisturbed boreal wetlands.Net sequestration of CO2 in the I am grateful to have had such wonderful support and guidance from my supervisor, Elyn Humphreys.Elyn was immensely helpful in the articulation, development, and completion of this thesis and was an awesome role model.The Carleton Biomet lab was my home for over four years and everyone who has passed through it has enriched my life in some way.Stacey Strilesky deserves isolated praise for humoring me in our extensive talks on mining, micrometeorology, and this new field of novel ecosystem study we have found ourselves in.I would like to thank Sean Carey, and his Watershed Hydrology Group at McMaster University.They always made me feel part of their lab.Specifically, this research would not have been possible without the efforts of Erin Nicholls, Haley Spennato, Kelly Biagi, Chelsea Thorne, Jessica Sara, and Arthur Szybalski who sacrificed one, sometimes multiple, of their summers to help collect the data I used.I would like to thank Mike Treberg, not only for building, installing and maintaining most of our field equipment, but also for passing along some skills in the fine craft of DIY field work.Mike's innovations are legendary within both lab groups, and if I only learned enough to have a fraction of his problem-solving capacity I am worlds more capable than I was before I started this project.Gord Drewitt also has my gratitude for helping with countless emails sharing his micrometeorological knowledge and helping collect some of the chamber data despite having sworn to never again touch gas flux chambers.Thanks to Brendan O'Neill, Doug Pawson and Tara Cater, who helped me struggle through more than one long day/week/month/term in the Geography PhD offices.I am grateful for the beers, coffee, lengthy chats, but mostly the friendships forged over our time iv in the Department of Geography and Environmental Studies (DGES).Special thanks to Anna Crawford, who not only helped me through the solidarity of PhDs in the DGES, but also gave me a chance to escape my research for a little while to travel into the fiords of Baffin Island to help study ice islands.I found the trip deeply inspiring and spending time with her research did wonders for thinking about my own.Natalie
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".