Annual Summer Submersed Macrophyte Standing Stocks Estimated From Long-Term Monitoring Data in the Upper Mississippi River
Bibliographic record
Abstract
Abstract System-scale restoration efforts within the Upper Mississippi River National Wildlife and Fish Refuge have included annual monitoring of submersed aquatic vegetation (SAV) since 1998 in four representative reaches spanning ∼ 440 river kilometers. We developed predictive models relating monitoring data (site-scale SAV abundance indices) to diver-harvested SAV biomass, used the models to back-estimate annual standing stock biomass between 1998 and 2018, and compared biomass estimates with previous abundance measures. We modeled two morphologically distinct groups of SAV with differing sampling efficiencies and estimated each separately: the first category included only wild celery Vallisneria americana, which has long, unbranched leaves and dominates lotic environments, while the second category included 17 branched morphology species (e.g., hornwort Ceratophyllum demersum and Canadian water weed Elodea canadensis) and dominates lentic environments. Wild celery accounted for approximately half of total estimated total biomass in the four reaches, combined branched species accounted for half, and invasive species (Eurasian watermilfoil Myriophyllum spicatum and curly-leaf pondweed Potamogeton crispus), a fraction of the branched species, accounted for < 1.5%. Site-scale SAV estimates ranged from 0 to 535 g·m−2 (dry mass). We observed increases in biomass in most areas between 1998 and 2009 and substantial increases (e.g., from < 10 g·m−2 to ∼ 125 g·m−2) in wild celery in extensive impounded areas between 2002 and 2007. Analyses also indicate a transitional period in 2007–2010 during which changes in biomass trajectories were evident in all reaches and included the start of a 9-y, ∼ 70% decrease in wild celery biomass in the southernmost impounded area. Biomass estimates provided new insights and illustrated scales of change that were not previously apparent using traditional metrics. The ability to estimate biomass from Long Term Resource Monitoring data improves conservation efforts through better understanding of changes in habitat and food resources for biota, improved goal setting for restoration projects and improved quantification of SAV-mediated structural effects such as anchoring of sediments and feedbacks with water quality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.001 |
| 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 teacher head, 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".