Construction costs, payback times, and the leaf economics of carnivorous plants
Bibliographic record
Abstract
Understanding how different plant species and functional types "invest" carbon and nutrients is a major goal of plant ecologists. Two measures of such investments are "construction costs" (carbon needed to produce each gram of tissue) and associated "payback times" for photosynthesis to recover construction costs. These measurements integrate among traits used to assess leaf-trait scaling relationships. Carnivorous plants are model systems for examining mechanisms of leaf-trait coordination, but no studies have measured simultaneously construction costs of carnivorous traps and their photosynthetic rates to determine payback times of traps. We measured mass-based construction costs (CC(mass)) and photosynthesis (A(mass)) for traps, leaves, roots, and rhizomes of 15 carnivorous plant species grown under greenhouse conditions. There were highly significant differences among species in CC(mass) for each structure. Mean CC(mass) of carnivorous traps (1.14 ± 0.24 g glucose/g dry mass) was significantly lower than CC(mass) of leaves of 267 noncarnivorous plant species (1.47 ± 0.17), but all carnivorous plants examined had very low A(mass) and thus, long payback times (495-1551 h). Our results provide the first clear estimates of the marginal benefits of botanical carnivory and place carnivorous plants at the "slow and tough" end of the universal spectrum of leaf traits.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".