Impacts of projected precipitation decline on water balance in the black land crab, (Gecarcinus ruricola) in The Bahamas
Bibliographic record
Abstract
The black land crab, Gecarcinus ruricola, is a common inhabitant in Bahamian coastal forests, and is the most terrestrial of the Caribbean land crabs. Future climate changes predict a decrease in overall rainfall for the Caribbean region. We investigated the effects of water deprivation and mechanisms of water balance in G. ruricola. When deprived of water for 10 d the crabs lost >12 % of their body water, resulting in a concomitant increase in hemolymph osmolality. G. ruricola was able to maintain hemolymph osmolality by drinking water, as well as capillary uptake from non-saturated soils. However, generation of metabolic water did not appear to contribute to the water budget. Behavioral experiments showed that G. ruricola was primarily active during the hours of darkness. The dehydration status of the individual influenced activity levels, with crabs exhibiting increased activity after moderate (4 d) dehydration, but reducing activity following severe (8 d) dehydration. In experiments where food and water were offered to crabs, there was no clear effect of dehydration time to access either of these resources, although crabs took less time to detect the water source. In the field, G. ruricola were primarily observed following rainfall events: by reducing surface activity during dry periods, they were able to maintain a relatively constant hemolymph concentration, irrespective of local environmental conditions. While G. ruricola will likely survive any future climatic drying scenarios, it might not be without cost: they are less likely to be foraging above ground and this may hamper growth and reproductive capacity.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".