Food web consequences of size‐based predation and vertical migration of an invertebrate predator (<i>Leptodora kindtii</i>)
Bibliographic record
Abstract
In an intensive study of the vertical and horizontal distribution of zooplankton in a eutrophic lake (Katepwa Lake), we found that only adult Leptodora kindtii (> 5 mm in body size) exhibited diel vertical migration (DVM), whereas juvenile Leptodora (< 5 mm) and other zooplankton species did not. Even though a longitudinal survey of five lakes (1994–2004) indicated that variation in Leptodora density was correlated with several indicators of habitat use (e.g., water temperature) and resource availability (e.g., zooplankton abundance), feeding experiments performed in both lit and unlit conditions demonstrated that a vertebrate predator (perch) strongly reduced Leptodora abundances under all conditions and always preferentially selected large‐bodied individuals. Collectively, this evidence suggests that the migratory behavior of large Leptodora is consistent with an anti‐predator defense strategy. To estimate the ecological significance of Leptodora DVM behavior, we modeled how predation rates on different zooplankton taxa differed between day and night in Katepwa Lake. We found that Leptodora had as much as five‐fold higher prey‐specific predation rates at night, particularly for intermediate‐sized prey. We conclude that ignoring the habitat use, size‐structure, and vertical migration behavior of Leptodora could considerably underestimate the significance of invertebrate predation in lake food webs, particularly in eutrophic lakes where Leptodora can coexist at high densities with planktivorous fish.
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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".