Spectrally weighted transparency in models of water-column photosynthesis and photoinhibition by ultraviolet radiation
Bibliographic record
Abstract
MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 269:101-110 (2004) - doi:10.3354/meps269101 Spectrally weighted transparency in models of water-column photosynthesis and photoinhibition by ultraviolet radiation Moritz K. Lehmann*, Richard F. Davis, Yannick Huot, John J. Cullen Centre for Marine Environmental Prediction (CMEP), Department of Oceanography, Dalhousie University, Halifax, Nova Scotia B3H 4J1, Canada *Email: mlehmann@dal.ca ABSTRACT: We present a simple method for describing the influence of variable attenuation of spectral irradiance, Kd(λ), on water-column photosynthesis and its inhibition by ultraviolet radiation (UV). The approach is based on weighted water transparency, a calculation introduced by Vincent et al. 1998 (Ann Glaciol 27:691-696). Key results of a depth- and spectrally-resolved model of photosynthesis can be reproduced for a broad range of water types by simple parameterizations using a reference solar irradiance spectrum at the surface and water transparency [1/Kd(λ)] weighted spectrally for biological effectiveness. Transparency that has been weighted spectrally by the normalized product of irradiance and photosynthetic absorption (PUR-weighted transparency, TWPUR) describes spectral effects on photosynthesis in the water column. An empirical parameterization of transparency weighted by the product of surface irradiance and the biological weighting function for inhibition of photosynthesis (TWPIR), along with TWPUR, describes the inhibition of water-column photosynthesis relative to the uninhibited rate. Our approach is directly compared with an analysis that used weighted transparency as an indicator of the potential for inhibition of photosynthesis by UV as influenced by variations in chromophoric dissolved organic matter associated with climate change over the past 6000 yr (Pienitz & Vincent 2000, Nature 404:484-487). Results demonstrate how weighted transparency, used as an indicator of potential inhibition, can be transformed into a predictor of biological effects. KEY WORDS: Weighted transparency · Photosynthesis model · Photoinhibition · Attenuation · Optical properties · CDOM Full text in pdf format PreviousNextExport citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 269. Online publication date: March 25, 2004 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2004 Inter-Research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".