Immunochemical methods for identification of prey in freshwater zooplankton
Bibliographic record
Abstract
Abstract Large, predatory, non‐indigenous species such as the cladoceran, Bythotrephes longimanus , can have a profound effect on aquatic food webs, but determining the prey consumed by such species is problematic because they shred prey externally and consume only soft body tissues. We assessed the usefulness of an immunochemical approach, in which putative zooplankton prey were homogenized and polyclonal antibodies against total proteins were raised in rabbits and purified against predator proteins. Using either dot‐blot or enzyme‐linked immunosorbent assay‐plate formats, assays easily detected prey proteins in single B. longimanus . Issues encountered included some degree of cross‐reaction with predator proteins and among prey species for some antisera and questions concerning determination of a correct blank value for assays, however, there are feasible approaches to resolving these issues. Immunochemical assays were readily applied in to a total of 185 individual B. longimanus in the Lake Michigan pelagic ecosystem in summer of 2008 and 2009 and indicated ingestion of cladoceran and copepod species, typically described in the literature, but also dreissenid veliger larvae and the large copepod Limnocalanus macrurus , not usually considered prey for Bythotrephes . Assays results showed some degree of correlation with numerical abundances of zooplankton prey in the water column, suggesting generalist feeding. Protein immunochemical assays offer a quick, sensitive and practical approach to examining planktonic food‐web questions that are compatible with, but have certain advantages over, alternatives such as nucleic acid techniques.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".