Global assessment of aquatic <i>Isoëtes</i> species ecology
Bibliographic record
Abstract
Abstract Isoëtes are iconic but understudied wetland plants, despite having suffered severe losses globally mainly because of alterations in their habitats. We therefore provide the first global ecological assessment of aquatic Isoëtes to identify their environmental requirements and to evaluate if taxonomically related species differ in their ecology. The assessment resulted in an extensive new database on aquatic Isoëtes , ecological niche analyses, and descriptive species accounts. We compiled a global database that includes all known environmental data collected from 1935 to 2023 regarding aquatic Isoëtes. We then evaluated the environmental drivers of 16 species using 2,179 global records. Additionally, we used hypervolume analysis to quantify the ecological niches of the two species with the greatest number of records, finding significant differences and evidence that Isoëtes echinospora occupies a wider ecological niche than Isoëtes lacustris . Fifty‐nine species (30% of the c. 200 Isoëtes species known today) were categorised as aquatic and were mainly reported in the Americas and northern Europe. About 38% of the aquatic species are threatened with extinction or are endemic to a small region, according to the International Union for Conservation of Nature's Red List in 2023. Many species were determined to be sensitive to certain water physical and chemical factors, generally preferring oligotrophic conditions such as low total phosphorus, moderate total nitrogen, moderate to low pH, and low conductivity. This analysis includes ecological data in the assessment of rare/threatened aquatic plants globally. This new database and the ecological analyses completed defined the ecological requirements of several species and identified knowledge gaps, which can aid management actions and future research. This paper highlights ecological significance and environmental sensitivities of aquatic Isoëtes . The current level of knowledge is inadequate for a large proportion of known taxa. We affirm the extreme need to support global, collaborative initiatives on which to build future conservation strategies.
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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 | 0.000 | 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) | 0.004 | 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".