Assessing Algal Community Structure and Nutrient Uptake Kinetics Across a Nutrient Gradient in Agricultural Streams
Bibliographic record
Abstract
Streams provide important ecosystem services, such as the transformation of organic matter and water purification, while transporting water from headwaters to larger receiving waterbodies downstream. Excess nutrients introduced through anthropogenic land use put stress on aquatic ecosystems and disrupt the ecosystem services we rely on. Current ecosystem health can be determined through structural and functional stream assessments to identify criteria required to maintain ecosystem services. Periphytic algal communities occupy a key position in stream ecosystems through coupling the abiotic environment with aquatic food webs, and are therefore a strong candidate for structural assessment. Nutrient cycling is a critical ecosystem service and a dynamic functional indicator of stream health as uptake saturation limits the capacity of the system to take up nutrients through biotic and abiotic processes. Ecosystem responses to anthropogenic land use and nutrient loading may differ between ecoregions such as the Grassland and Parkland ecoregions found in Alberta, Canada, due to the inherent differences in physicochemical variables affecting the biotic components. Therefore, region-specific nutrient criteria may be required to reflect these differences. Here, we explore both structural and functional metrics of stream function at 55 streams in watersheds that are agriculturally dominated, but with varying degrees of land use pressures such that a gradient in nutrient concentration is established. Periphyton samplers were deployed in each stream for one month in late-spring and again in mid-summer, and harvested algae were identified to genus. Ordination and threshold analyses were conducted to assess the impact of nutrient loading on the biotic components of the stream ecosystems and to identify bioindicator taxa. Nutrient injection experiments were performed in a subset of these streams to assess nutrient uptake kinetics and saturation dynamics, and to determine the limiting nutrient. Nitrogen was determined to be the limiting nutrient in this region by both approaches, but no threshold could be identified through either algal community shifts or uptake saturation. Algal communities appear to be resilient to the nutrient gradient sampled in this study, and continue to contribute to nutrient uptake even at the highest concentrations of nutrients. The results of this research could inform watershed management programs in Alberta's agricultural region by suggesting nutrient criteria that maintain aquatic ecosystem health.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".