Leaf habit, phenology, and longevity of 11 forest understory plant species in Algonquin State Forest, northwest Connecticut, USA
Bibliographic record
Abstract
Many functional attributes of plant species are predicated on their leaf habit. To fully understand the way that plant species coexist and respond to future conditions, it is important to have a thorough understanding of the leaf habit, phenology, and longevity of common forest plant species. I quantified these traits in 11 forest understory species in the Algonquin State Forest of northwestern Connecticut, USA, by labeling and monitoring individual leaves of three replicates of each species over a period of 3 years. While clear patterns exist within the evergreen, wintergreen, seasonalgreen, deciduous, and spring-ephemeral groupings, significant differences exist within and among these groups, including differences in the timing of leafing and senescence, and minimum leaf longevity. Because the impact of local and global disturbance is often predicated on the phenological and life-history traits of species, these differences may be important to the responses that these species have to future disturbance. The size of leaf-supporting structures was positively correlated with leaf longevity across species, supporting a predictive connection between construction costs and leaf longevity. Additionally, the leaf habit of Oxalis acetosella L. at this study site is significantly different from that observed previously in the Catskill Mountains, New York State, USA. These differences may be due to local habitat conditions or genetic predisposition.
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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 | 0.001 |
| 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".