Effects of neighbour location and nutrient distributions on root foraging behaviour of the common sunflower
Bibliographic record
Abstract
Plants regularly encounter patchily distributed soil nutrients. A common foraging response is to proliferate roots within high-quality patches. The influence of the social environment on this behaviour has been given limited attention, despite important fitness consequences of competition for soil resources among plants. Using the common sunflower (Helianthus annuusL.), we compared localized root proliferation in a high-quality patch by plants grown alone to that of plants in two different social environments: with a neighbouring plant sharing equal access to the high-quality patch, and with a neighbouring plant present but farther from the high-quality patch such that the focal individual was in closer proximity to the high-quality patch. Sunflowers grown alone proliferated more roots within high-nutrient patches than lower-nutrient soil. Plants decreased root proliferation within a high-nutrient patch when it was equidistant to a neighbour. Conversely, plants increased root proliferation when they were in closer proximity to the patch relative to a nearby neighbour. Such contingent responses may allow sunflowers to avoid competition in highly contested patches, but to also pre-empt soil resources from neighbours when they have better access to a high-quality patch. We also compared patch occupancy by sunflowers grown alone with two equidistant high-quality patches to occupancy by sunflowers grown with two high-quality patches and a neighbour. Plants grown with a neighbour decreased root length within shared patches but did not increase root length within high-quality patches they were in closer proximity to, perhaps because resource pre-emption may be less important for individuals when resources are more abundant. These results show that nutrient foraging responses in plants can be socially contingent, and that plants may account for the possibility of pre-empting limited resources in their foraging decisions.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".