Ecology of testate amoebae in a North Carolina pocosin and their potential use as environmental and paleoenvironmental indicators
Bibliographic record
Abstract
Testate amoebae inhabiting Sphagnum peatlands are sensitive indicators of substrate-moisture content. However, ecological data from a range of peatland types is needed to assess their indicator-value in other peatland systems. We examined testate amoeba communities and species—environment relationships at 40 locations within a pocosin of North Carolina. Primary objectives were to provide baseline data on the ecology of testate amoebae in pocosins, compare communities with those of northern peatlands, and assess the potential of using testate amoebae as environmental indicators in these systems. Results indicated that pH, substrate-moisture content, and conductivity were important controls on community composition. Communities that were relatively similar and dissimilar to those of northern peatlands were encountered, and the ecology of species with respect to water-table depth was similar in both peatland types. Cross validation of transfer functions for pH and water-table depth suggests that pocosin testate amoebae can be used as indicators for these variables. However, water-table depth was poorly inferred from communities at several dry sites characterized by high bulk density. These sites may experience large seasonal or interannual variability in moisture conditions because of differences in peat structure, suggesting that research is needed on the influence of short-term variability in shaping community structure.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".