Spectral model of depth‐integrated water column photosynthesis and its inhibition by ultraviolet radiation
Bibliographic record
Abstract
Depth‐integrated models of primary production (DIMs) are used to estimate water column photosynthesis as a function of chlorophyll concentration, irradiance at the surface, the penetration of photosynthetically available radiation (PAR), and parameters of the relationship between photosynthesis and PAR. These models are inherently unable to account for variability in the ratio of photosynthetically utilizable radiation (PUR) to PAR with depth and water type, and they cannot account for the inhibition of photosynthesis by ultraviolet radiation, UVR. These important spectral effects — all sensitive to climate change — are readily described with numerical models that require many computations and are unsuitable for some important applications, including the estimation of aquatic productivity from remote sensing. We present a simple DIM that accounts for the spectral effects of irradiance on photosynthesis, including inhibition by UVR. Water column photosynthesis, normalized to surface chlorophyll and scaled to the maximum rate per unit chlorophyll, is described as a function of four dimensionless derived variables: E * PUR , PUR at the surface scaled to the saturation irradiance for photosynthesis; T * PUR , water transparency, normalized to a depth scale and weighted spectrally for photosynthetic absorption; E * PIR , surface irradiance weighted spectrally for inhibition of photosynthesis; and T * PIR , scaled transparency weighted for photosynthesis‐inhibiting radiation. Simple functions of these variables closely approximate (within 6%) the results of a full‐spectral numerical model of instantaneous and daily integrated water column photosynthesis with and without UVR for a broad range of water types, solar angles, stratospheric ozone concentrations and biological properties of phytoplankton. The spectral DIM is suitable for examining patterns in global ocean productivity and can be used to assess the biological effects of variations in solar radiation (e.g., ozone depletion) and water clarity in climate‐change scenarios for lakes and oceans.
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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".