Non-native earthworms increase the abundance and diet quality of a common woodland salamander in its northern range
Bibliographic record
Abstract
Abstract Non-native earthworms found in Eastern Canada substantially affect soil properties and plant diversity, but less is known about their impacts on higher faunal species. We investigated the effects of non-native earthworms on populations of Plethodon cinereus, a common woodland salamander. We hypothesized that earthworms could adversely affect P. cinereus by consuming the forest floor, thereby decreasing soil moisture and the abundance of native preys. Conversely, earthworms could positively affect P. cinereus by providing refuge in their abandoned burrows and by being a novel prey. We installed 25 coverboards in 38 mature sugar maple (Acer saccharum) forests, 24 of which were earthworm-free. Over the next two years, we monitored earthworm and salamander populations using hot mustard extractions and visible implant elastomers, respectively. At a subset of four sites, two with and two without earthworms, we determined salamander diets in the spring (May–June), summer (July–August) and fall (September–October) seasons, using gastric lavage techniques. Forest floor depth decreased, whereas population density, body size and total prey volume of P. cinereus increased, with earthworm abundance. Earthworms, which are soft-bodied and nutritious prey, composed most of the salamander diet at sites with earthworms, volumetrically accounting for > 50% of total prey volume. Despite this, we found fewer prey items in the stomach of salamanders at earthworm-invaded sites, indicating that salamanders are getting a higher caloric intake per feeding while expending less energy. We conclude that non-native earthworms have a net beneficial effect on P. cinereus populations in Eastern Canada, mainly by improving diet quality.
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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 | 0.000 |
| 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".