Interactions between zebra mussels (<i>Dreissena polymorpha</i>) and microbial communities
Bibliographic record
Abstract
Zebra mussels (Dreissena polymorpha) have had an enormous impact on aquatic environments. However, little is known concerning their interactions with microbial communities. In these studies, the ability of zebra mussels to derive nutrition from bacterioplankton and their effect on microbial community diversity were investigated in samples from the Hudson River, New York, and in laboratory studies. Clear physiological responses to starvation were observed, including decreases in respiration rates, lipid content, and total weight, that were reversed after feeding zebra mussels a diet of bacteria. Clearance rates of bacteria were correlated with bacteria size (r 2 = 0.995), with the lowest clearance rates associated with small indigenous river bacteria (size = 0.03 ± 0.04 µm 3 , clearance rate = 0.08 ± 0.02 mL·mussel -1 ·min -1 ). Comparison of the diversity of microbial communities in zebra mussel tissue extract, detritus, and pseudofecal material associated with zebra mussel colonies, surrounding water, and sediment samples revealed distinct microbial assemblages associated with these environments. The overall ecological effect and importance of bacteria - zebra mussel interactions remains unclear, but these studies indicate that these interactions occur and should be included in our efforts to better understand the impact of zebra mussels on aquatic systems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.016 | 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 teacher head, 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".