Changes in the Vegetation Cover in a Constructed Wetland at Argonne National Laboratory, Illinois
Bibliographic record
Abstract
Wetlands are valuable resources that are disappearing at an alarming rate. Land development has resulted in the destruction of wetlands for approximately 200 years. To combat this destruction, the federal government passed legislation that requires no net loss of wetlands. The United States Army Corps of Engineers (USACE) is responsible for regulating wetland disturbances. In 1991, the USACE determined that the construction of the Advanced Photon Source at Argonne National Laboratory would damage three wetlands that had a total area of one acre. Argonne was required to create a wetland of equal acreage to replace the damaged wetlands. For the first five years after this wetland was created (1992-1996), the frequency of plant species, relative cover, and water depth was closely monitored. The wetland was not monitored again until 2002. In 2003, the vegetation cover data were again collected with a similar methodology to previous years. The plant species were sampled using quadrats at randomly selected locations along transects throughout the wetland. The fifty sampling locations were monitored once in June and percent cover of each of the plant species was determined for each plot. Furthermore, the extent of standing water in the wetland was measured. In 2003, 21 species of plants were found and identified. Eleven species dominated the wetland, among which were reed canary grass (Phalaris arundinacea), crown vetch (Coronilla varia), and Canada thistle (Cirsium arvense). These species are all non-native, invasive species. In the previous year, 30 species were found in the same wetland. The common species varied from the 2002 study but still had these non-native species in common. Reed canary grass and Canada thistle both increased by more than 100% from 2002. Unfortunately, the non-native species may be contributing to the loss of biodiversity in the wetland. In the future, control measures should be taken to ensure the establishment of more desired native species.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".