Do invasive terrestrial invertebrates subsidize north-temperate fish populations? The case of the spongy moth (Lymantria dispar dispar)
Bibliographic record
Abstract
Invasive species can achieve incredibly high densities in invaded ecosystems, introducing a novel resource base for willing consumers. Hyperabundant invaders in one ecosystem that spillover into adjacent ecosystems (e.g. terrestrial to aquatic) create new opportunities for multichannel omnivory, whereby generalist consumers feed on prey from different trophic levels and ecosystems. However, our understanding of how invasive organisms originating in one ecosystem are utilized by consumers in adjacent ecosystems remains poorly studied. The spongy moth (Lymantria dispar dispar; LDD) is an invasive invertebrate that exhibits cyclical hyperabundance, with larvae defoliating millions of hectares of deciduous forest during regular outbreaks in eastern North America. We sought to determine if larval LDD could represent an impactful spring and early summer resource for native fish species during years of high larval abundance. Here, we quantified the diets of pond-dwelling largemouth bass (Micropterus nigricans) and pumpkinseed sunfish (Lepomis gibbosus) during 2020 and 2021 respectively, two historic outbreak years for LDD in Ontario, Canada. Both pumpkinseed and largemouth bass failed to exhibit meaningful exploitation of LDD larvae, regardless of their overwhelming abundance. Of 315 pumpkinseed sampled across four pond populations from April to August of 2021, only two contained individual LDD larvae. Of the 82 largemouth bass sampled in June 2020, only 1 individual contained a single LDD larvae. Serendipitously, we discovered one pumpkinseed population relied heavily on a different invasive terrestrial invertebrate, the earthworm (60% of all pumpkinseed stomach contents by mass in early spring). Though hyperabundant LDD larvae appeared to be largely avoided by fish predators, a less well-defended invasive invertebrate (earthworms) acted as a terrestrial subsidy for a native fish. Despite LDD larvae not being consumed by fish, the replacement of leaf litter with the carcasses and frass of LDD larvae could represent an important modification to detrital food webs in ponds and lakes. Thus, understanding how invasive species impact both resident consumers and nutrient cycling will be critical for the appropriate management of invasive species and their resident food webs moving forward.
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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) | 0.002 | 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".