Root Foraging Influences Plant Growth Responses to Earthworm Foraging
Bibliographic record
Abstract
Interactions among the foraging behaviours of co-occurring animal species can impact population and community dynamics; the consequences of interactions between plant and animal foraging behaviours have received less attention. In North American forests, invasions by European earthworms have led to substantial changes in plant community composition. Changes in leaf litter have been identified as a critical indirect mechanism driving earthworm impacts on plants. However, there has been limited examination of the direct effects of earthworm burrowing on plant growth. Here we show a novel second pathway exists, whereby earthworms (Lumbricus terrestris L.) impact plant root foraging. In a mini-rhizotron experiment, roots occurred more frequently in burrows and soil cracks than in the soil matrix. The roots of Achillea millefolium L. preferentially occupied earthworm burrows, where nutrient availability was presumably higher than in cracks due to earthworm excreta. In contrast, the roots of Campanula rotundifolia L. were less likely to occur in burrows. This shift in root behaviour was associated with a 30% decline in the overall biomass of C. rotundifolia when earthworms were present. Our results indicate earthworm impacts on plant foraging can occur indirectly via physical and chemical changes to the soil and directly via root consumption or abrasion and thus may be one factor influencing plant growth and community change following earthworm invasion. More generally, this work demonstrates the potential for interactions to occur between the foraging behaviours of plants and soil animals and emphasizes the importance of integrating behavioural understanding in foraging studies involving plants.
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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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".