Is a plant truly plastic? Nutrients and neighbours induce trait‐specific responses, but performance depends on response direction
Bibliographic record
Abstract
Plants live in a heterogeneous world, where nutrient and neighbour distributions vary in space and time. Plants can respond to this variation through plastic responses in individual organs, which are assumed to be coordinated among traits to support a coherent, adaptive strategy, maintaining plant growth in varying environments. However, this assumption remains understudied. Here, we test coordination in trait plasticity and its influence on plant performance. We do so among 27 naturally co‐occurring species under four different neighbour and soil fertility contexts using data from two mesocosm experiments manipulating nutrients and neighbour presence. We focus on commonly‐studied resource‐acquisitive traits: specific leaf area (SLA), root tissue density (RTD), and specific root length (SRL). We found species exhibited plasticity in SLA, RTD and SRL 50–75% of the time and that responses to neighbours were stronger than nutrients for SLA and RTD, but not SRL. However, plastic responses were highly modular, correlated < 10% of the time, and had little coordination consistent with the trait economics paradigm. Consequences of plasticity for plant performance depended on the trait, the response direction, and whether plants were responding to nutrients or neighbours. Plasticity in RTD was unrelated to performance, but species that increased their SRL under low nutrient conditions performed worse than those showing no SRL plasticity, while SRL responses to neighbours had no effect. Similarly, species that increased SLA under low nutrients or with neighbours showed reduced performance compared to those that decreased SLA in those same conditions. Overall, plasticity in SLA, RTD and SRL rarely manifested as a correlated or coordinated response promoting growth maintenance in our study. Instead, plasticity's consequences hinged on the direction of trait shifts, sometimes incurring costs. Future studies should consider plasticity a directional phenomenon.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".