Diatoms as a tracer of hydrological connectivity: are they supply limited?
Bibliographic record
Abstract
Abstract Recent work has shown that aerial diatoms are a useful ecological tracer of hydrological connectivity in the hillslope–riparian zone–stream (HRS) system. While such work has improved both our understanding of catchment functioning and aerial diatom taxonomy, assemblages and distribution, further work is hampered by lack of data on diatom population depletion during rainfall events. We still do not know whether or not diatom tracers are supply limited. Here we test the null hypothesis that aerial diatoms exhibit infinite supply in the context of natural rainfall events. Rainfall simulation experiments were conducted in a small forested catchment in northwest Luxembourg. We extracted periodically soil surface samples and overland flow samples for diatom population size and species assemblage analyses. Diatom population size was quantified using a new approach we have developed, which involves extracting diatoms using carbonated water and an isopycnic separation technique. Our results showed that pre‐event population size was c. 96 100 diatoms per cm2 in the riparian zone. During the artificial rainfall event, the diatom population was depleted by 72% to 27 200 diatoms per cm2. The diatom assemblage was characteristic of a frequently disturbed environment. Overall, these results suggest that diatoms are supply limited, and are flushed significantly throughout rainfall events. Nevertheless, based on the data from these 1 in 10‐year rainstorm simulations, the riparian zone diatom population is unlikely to be exhausted on an event time scale. Further research is now underway to investigate the spatial and temporal variability of aerial diatom communities across a range of storm sizes. Copyright © 2015 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".