Epilithic Algal Community Responses to Rapid Glacier Loss in the Canadian Rocky Mountains
Bibliographic record
Abstract
Global melting of mountain glaciers is altering downstream ecosystems. As glaciers disappear, downstream water temperatures are rising while turbidity and nutrient concentrations decline. Here, knowledge gaps exist concerning how these abiotic changes will affect primary producers in glacial meltwater streams. I quantified abiotic variables and rock-attached algal communities termed epilithon in 10 stream sites along an environmental gradient of glacial influence in the Canadian Rockies. I hypothesized that physical factors would be the strongest predictors of community composition due to the damage incurred by biofilms from frequent scouring and abrasion events. Turbidity best explained an observed unimodal response of epilithic algal biomass accrual to glacial influence. However, abiotic variables poorly explained variation in community composition. To further explore the impacts of glacial meltwater turbidity on epilithon, I designed a mesocosm experiment to test the effects of glacial flour, the primary determinant of turbidity in glacial streams, on algal community structure. Artificial stream channels were inoculated with algae and meltwater collected from a low turbidity glacial stream. Epilithic algal communities were then exposed to one of five turbidity levels by mixing varying amounts of glacial flour into meltwater. Moderate levels of turbidity significantly stimulated epilithic algal biomass accrual relative to the effects of low and extreme turbidity treatment levels, appearing to favor growth by chlorophytes over that of diatoms and other chromophytes. Potential explanations of low biomass accrual by epilithon to low and extreme turbidity involved nutrient limitation and physical disturbance, respectively. My findings suggest that the turbidity of glacial streams has a strong influence on the growth and diversity of algal biofilms. I expect that further glacier loss will suppress epilithic algal growth in glacial meltwater streams due to declining nutrient availability and heightened exposure to damaging levels of ultraviolet radiation. Since algal growth supports the productivity of glacial meltwater ecosystems in the absence of terrestrial subsidies from surrounding barren alpine landscapes, I anticipate that loss of glaciers could in certain cases impair the downstream productive capacity for harvestable coldwater fishes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".