Symbiotic endolithic microbes alter host morphology and reduce host vulnerability to high environmental temperatures
Bibliographic record
Abstract
Abstract Thermal stresses, such as those associated with global warming, have the potential to change the strength and even the direction of interspecific interactions. On rocky shores, bio‐eroding microbial endoliths infect the mussel Mytilus californianus . Infestation by microbial endoliths can weaken the shell and lead to mechanical failure and death, increased vulnerability to predation, mechanical damage, etc. However, endolith infestation is associated with the loss of the dark‐colored periostracum, exposing the underlying light gray prismatic layer of the shell and potentially reducing stressful heat gain during low tide. We explore the consequences of the mussel–endolith relationship on mussel tolerance to high environmental temperature through a series of experimental manipulations and comparative observations. Experimental sterilization of the shell surface reduces the rate of periostracum loss, suggesting that the change in shell surface color is indeed caused by microbes residing on/in the shell. Eroded shells absorbed less solar energy than shells with their periostracum intact, and mussel mimics with infested shells remained cooler on sunny days. Manipulation of shell color in the field resulted in higher mortality in black‐painted mussels relative to gray‐painted or naturally eroded mussels. Furthermore, following exceedingly hot weather, mortality was significantly lower for heavily infested, light‐colored mussels than for lightly infested, dark‐colored mussels. Thus, although shell‐boring microbes have the potential to act as parasites under the majority of conditions experienced by mussels, they may be critical mutualists during periods of intense thermal stress. This context‐dependent symbiosis may allow mussels to occupy higher shore levels than would otherwise be possible, and thus indirectly benefit the hundreds of species which use mussel beds as habitat.
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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".