Distinctive effects of allochthonous and autochthonous organic matter on CDOM spectra in a tropical lake
Bibliographic record
Abstract
Abstract. Despite the increasing understanding about differences in carbon cycling between temperate and tropical freshwater systems, our knowledge on the importance of organic matter (OM) pools on light absorption properties in tropical lakes is very scarce. We performed a factorial mesocosm experiment in a tropical lake (Minas Gerais, Brazil) to evaluate the effects of increased concentrations of allochthonous and autochthonous OM, and differences in light availability on the light absorption characteristics of chromophoric dissolved organic matter (CDOM). Autochthonous OM deriving from phytoplankton ( ∼ Chl a) was stimulated by addition of nutrients, while OM from degradation of terrestrial leaves increased allochthonous OM, and neutral shading was used to manipulate light availability. Effects of the additions and shading on DOC, Chl a, nutrients, total suspended solid concentrations (TSM) and spectral CDOM absorption were monitored every 3 days. CDOM quality was characterized by spectral indices (S250–450, S275–295, S350–450, SR and SUVA254). Effects of carbon sources and shading on the spectral CDOM absorption was investigated through principal component (PCA) and redundancy (RDA) analyses. The two different OM sources affected CDOM quality very differently and shading had minor effects on OM levels, but significant effects on OM quality, especially in combination with nutrient additions. Spectral indices (S250–450 and SR) were mostly affected by allochthonous OM addition. The PCA showed that enrichment by allochthonous carbon had a strong effect on the CDOM spectra in the range between 300 and 400 nm, while the increase in autochthonous carbon increased absorption at wavelengths below 350 nm. Our study shows that small inputs of allochthonous OM can have large effects on the spectral light absorption compared to large production of autochthonous OM, with important implications for carbon cycling in tropical lakes.
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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 | 0.000 | 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".