Role of morphological structure and layering of <i>Sphagnum</i> and <i>Tomenthypnum</i> mosses on moss productivity and evaporation rates
Bibliographic record
Abstract
Goetz, J. D. and Price, J. S. 2015. Role of morphological structure and layering of Sphagnum and Tomenthypnum mosses on moss productivity and evaporation rates. Can. J. Soil Sci. 95: 109–124. Morphological structures of peatland mosses control moss water relations and the rate of water loss by drainage and evaporation, thus influencing their physiological functions. While many of these mechanisms are understood for Sphagnum mosses, there is a limited understanding of how these processes operate in Tomenthypnum nitens, a dominant brown moss species in northern rich fens. This study contrasts how different hydrophysical characteristics of Tomenthypnum and Sphagnum species affect capillary water flow that supports evaporation and productivity. Laboratory investigations indicate that volumetric water content (θ), gross ecosystem productivity, and evaporation decreased with water table depth for both mosses, with Sphagnum capitula retaining 10–20% more water (θ range of 0.18–0.32 cm3 cm−3) than Tomenthypnum (0.07−0.16 cm3 cm−3). Despite lower θ and a smaller fraction of pores between 66 and 661 µm to retain water within the Tomenthypnum structure (10%) compared with Sphagnum (27%), both mosses had similar fractions of water conducting pore spaces and were able to maintain capillary rise throughout the experiment. While there was a larger difference in the bulk density and porosity of the Tomenthypnum moss compared with its underlying peat than there was in the Sphagnum profile, a layer of partially decomposed moss of intermediate properties was sufficient to provide a connection between the moss and peat under low water table conditions. In trying to characterize the soil-water pressure (ψ) in near-surface mosses of Tomenthypnum based on measurements of vapour pressure, we found disequilibrium conditions that severely underestimated ψ (i.e., very large negative pressures). It is this disequilibrium that drives evaporation and draws up capillary water to the moss surface for peatland–atmosphere carbon and water transfers.
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 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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".