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Record W2523916885

Water Storage Dynamics in Peat-Filled Depressions of the Canadian Shield Rock Barrens: Implications for Primary Peat Formation

2016· dissertation· en· W2523916885 on OpenAlexaboutno aff
Benjamin Didemus

Bibliographic record

VenueMacSphere (McMaster University) · 2016
Typedissertation
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsPeatShieldGeologyGeomorphologyEarth scienceGeochemistryPetrologyGeographyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

Northern peatlands have acted as persistent sinks of CO2 throughout the Holocene largely owing to their ability to maintain shallow water table depths that limit decomposition rates and supports the growth of keystone vegetation including Sphagnum mosses. There is concern, however, that the future success and ecosystem function of these northern peat deposits may be at risk to climate change, where temperatures and evaporation rates are predicted to increase substantially in the next century. While numerous studies have examined the hydrology and carbon dynamics in large expansive peatland systems where a water table (WT) is ever-present, relatively little research has been done on small scale peat-accumulating systems where their vulnerability remains unknown. One region where a broad spectrum in the scale of peat accumulation is present is in the bedrock depressions of Canadian Shield rock barrens, which are of special importance as many peat deposits here provide habitat to species at risk including the Blanding’s Turtle and the Massassauga Rattlesnake. This study examines the controls that govern water storage dynamics and moss water availability in 18 different peat-accumulating depressions that vary in size, catchment area, and sediment composition. The magnitude of WT variability was often several times greater in shallower bedrock depressions (<50 cm deep) as compared to deeper ‘bogs’ (>60 cm deep). The magnitude of depression WT variability appeared to be closely linked to the WT depth (WTD), the relative proportions of different sediment types within the depression, and the depth dependant specific yield (Sy) of each sediment type. Sites which contained large fractions of Polytrichum moss or mineral soil – which were more common in shallow depressions ¬¬– had the greatest WT variability due to the lower porosity and Sy of this sediment as compared to Sphagnum peat. Sphagnum dominated ‘vernal pools’ (30-50 cm deep) had a WT variability two to three times greater than Sphagnum dominated bogs at WTDs > 20-25 cm, which may be related to exceptionally high ash concentrations near the base of vernal pools which reduced peat porosity and Sy as compared to more organic-rich peat. As compared to bogs, pits (<15 cm deep) and vernal pools had greater rates of WT decline during drying intervals, deeper average WTDs when a WT was present, and extended periods of WT absence during the summer months. As such, moss growing in pits and vernal pools generally had lower near-surface water availability as compared to bogs, though the importance of depression depth in determining the timing of moss stress is also dependant on the hydrophysical properties (Kunsat and moisture retention) of the moss species in question. WT dynamics and moss water availability were generally weakly correlated to depression catchment size, although during wetter periods of the year the rate of WT recession was moderated in pits and vernal pools which had an upslope depression that could provide sustained water inputs for multiple days after rainfall. The results of this study suggest that depression depth may be a first order control in determining peatland vulnerability to future regime shifts induced by external forcings or disturbances. Furthermore, this study suggests that systematic differences may exist between the hydrophysical properties of peat in shallow vs. large bedrock depressions, potentially resulting from contrasts in fire frequency/severity, and/or the degree of humification/compression among geological settings.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.834
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.000

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.

Opus teacher head0.007
GPT teacher head0.191
Teacher spread0.184 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreOther

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".

Quick stats

Citations2
Published2016
Admission routes1
Has abstractyes

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