Ice in the intertidal: patterns and processes of freeze tolerance in intertidal invertebrates
Bibliographic record
Abstract
Many intertidal invertebrates are freeze tolerant, meaning that they can survive ice formation within their body cavity. Freeze tolerance is a fascinating trait, and understanding its mechanisms is important for predicting the survival of intertidal animals during extreme cold weather events. In this Review, we bring together current research on the ecology, biochemistry and physiology of this group of freeze-tolerant organisms. We first introduce the ecology of the intertidal zone, then highlight the strong geographic and taxonomic biases within the current body of literature on this topic. Next, we detail current knowledge on the mechanisms of freeze tolerance used by intertidal invertebrates. Although the mechanisms of freeze tolerance in terrestrial arthropods have been well-explored, marine invertebrate freeze tolerance is less well understood and does not appear to work similarly because of the osmotic differences that come with living in seawater. Freeze tolerance mechanisms thought to be utilized by intertidal invertebrates include: (1) low molecular weight cryoprotectants, such as compatible osmolytes and anaerobic by-products; (2) high molecular weight cryoprotectants, such as ice-binding proteins; as well as (3) other molecular mechanisms involving heat shock proteins and aquaporins. Lastly, we describe untested hypotheses, methods and approaches that researchers can use to fill current knowledge gaps. Understanding the mechanisms and consequences of freeze tolerance in the intertidal zone has many important ecological implications, but also provides an opportunity to broaden our understanding of the mechanisms of freeze tolerance more generally.
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 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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".