The vegetation and ecological gradients of calcareous mires in the South Park valley, Colorado
Bibliographic record
Abstract
The vegetation, environment, and ecological gradients present on three calcareous mires in the South Park valley, Park County, Colorado, were investigated. Vegetation was classified into four habitat classes, nine subclasses, and twelve species associations using two-way species indicator analysis (TWINSPAN). Detrended correspondence analysis (DCA) was used to ordinate vegetation samples along two axes representing the three predominant ecological gradients: water table height, miremargin to expanse, and region. Canonical correspondence analysis (CCA) was used to directly relate local environmental conditions to vegetation. Water table depth, microtopographical development, soil and water pH and nutrient level, soil organic matter, and hydraulic head were significantly correlated with vegetation gradients. The mire soils consist of intermixed areas of organic and mineral soils. Mire soils and water are highly alkaline and nutrient-rich. Mean pore water calcium concentration on these mires is 115 mg/L, electrical conductivity averages 575 µS, and mean pH is 7.4. Owing to these conditions, the fen floras include a number of highly minerophilic species. Based on water chemistry and species criteria, each site was classified as rich to extremely rich fen, with the two fen types mixing in complex patterns according to local environmental conditions. The species Trichophorum pumilum, Salix candida, Salix myrtillifolia, Carex microglochin, Carex viridula, Carex scirpoidea, Eriophorum gracile, Triglochin maritimum, Triglochin palustris, Kobresia myosuroides, Kobresia simpliciuscula, Thalictrum alpinum, Scorpidium scorpioides, Scorpidium turgescens, and Calliergon trifarium were determined to be indicative of extremely rich fen conditions in the southern Rocky Mountains.Key words: Colorado, canonical correspondence analysis, detrended correspondence analysis, extremely rich fen, gradient analysis, mire.
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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 | 0.000 | 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 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".