Algal primary production in prairie wetlands : the effects of nutrients, irradiance, temperature and aquatic macrophytes
Bibliographic record
Abstract
I studied algal primary production in prairie wetlands, and impacts of anthropogenic nutrient loading, changes in light and temperature, and the presence or absence of macrophytes in the water column. I manipulated nitrogen and phosphorus loading, macrophyte abundance, temperature, and photosynthetically active radiation. My study sites were two Ramsar wetlands, Delta Marsh, an 18,500 ha lacustrine marsh, and Oak Hammock Marsh, a 2,400 ha diked marsh. I hypothesized that algae would contribute significantly to primary production in prairie wetlands, on a scale comparable to or exceeding macrophyte production. The objective in Delta Marsh was to promote a shift from an epiphyton- and submersed macrophyte-dominated marsh (clear water state) to a phytoplankton-dominated turbid state by manipulating macrophyte abundance and inorganic nutrient loading in large enclosures. One objective of my survey of algal and macrophyte abundance in Oak Hammock Marsh was to quantify the contribution of all algal and macrophyte communities to total wetland primary production. Other objectives were to develop a photosynthesis model for each wetland algal assemblage based on photosynthesis-irradiance relationships, and to determine the major limiting resource for algal primary production. I found that algae contribute significantly to primary production in prairie wetlands. In Delta Marsh, algae contributed 34% to standing crop in unmanipulated mesocosms, and 57% to standing crop in nutrient enriched mesocosms. In Oak Hammock Marsh, algae contributed 62% and 68% of total annual primary production in two consecutive years. Phytoplankton responded to nutrient addition, both in the presence of macrophytes and when they were absent. Therefore, the nutrient addition treatments did promote a more turbid state, but the likelihood of a complete switch from clear water to a turbid state in the enclosures was equivocal. This is because periphyton and epiphyton showed a similar magnitude of response to nutrient addition as phytoplankton did, providing an important buffering mechanism within the enclosures by sequestering large amounts of added nutrients. The photosynthesis model, developed from experimentally determined photosynthesis parameters, was able to predict accurate daily productivity estimates when compared with in situ measurements. Light was the single most limiting resource for algae in Oak Hammock Marsh.
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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) | 0.000 | 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".