Measurement and modelling of bryophyte evaporation in a boreal forest chronosequence
Bibliographic record
Abstract
Abstract The effects of changing climate and disturbance on forest water cycling are not well understood. In particular, bryophytes contribute significantly to forest evapotranspiration in poorly drained boreal forests, but few studies have directly measured this flux and how it changes with stand age and soil drainage. We measured bryophyte evaporation (E) in the field (in CanadianPicea marianaforests of varying ages and soil drainages) and under controlled laboratory conditions, and modelled dailyEusing site‐specific meteorological data to drive a Penman–Monteith‐based model. Field measurements ofEaveraged 0·37 mm day−1and ranged from 0·03 (Pleurozium schreberiiin a 77‐year‐old dry stand) to 1·43 mm day−1(Sphagnum ripariumin a 43‐year‐old bog). In the laboratory, moss canopy resistance (which ranged from ∼0 to 1500 s m−1) was constant until a moss water content of ∼6 g g−1and then climbed sharply with further drying; unexpectedly, no difference was observed between the three moss groups (feather mosses, hollow mosses and hummock mosses) tested. Modelled annualEranged from 0·4 mm day−1, in the well‐drained stands, to ∼1 mm day−1in the 43‐year‐old bog. The Penman–Monteith modelling approach used was relatively insensitive to most parameters but only explained 35% of the variability in field measurements. BryophyteEwas greater in bogs than in upland stands, was driven by low‐lying mosses and varied with stand age only in the poorly drained stands; this suggests that bryophytes may provide a buffering effect to fire‐driven changes in tree transpiration. Copyright © 2010 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".