Energetics and Water Flux in the Subterranean Rodent Family Bathyergidae
Bibliographic record
Abstract
The doubly labeled water (DLW) technique and indirect calorimetry enable measurement of an animal’s daily energy expenditure (DEE, kJ/day), resting metabolic rate (RMR, kJ/d), sustained metabolic scope (SusMS), body fat content (BF, %) as well as water turnover (WTO, ml/day), and water economy index (ml/kJ). Small mammals have been the primary focus of many of the DLW studies to date. From large multi-species analyses of the energetics and water flux of aboveground small mammals, well-defined trends have been observed. These trends mainly refer to an adaptive advantage for lower RMR, DEE, SusMS, WTO and WEI in more ariddwelling animals to increase water and energy savings under low and unpredictable resource availability. The study of the subterranean rodent family Bathyergidae (African mole-rats) has been of particular interest with regards to field metabolic rate and metabolic studies. Although a great deal of research has been conducted on the Bathyergidae, a complete overview and multi-species analysis of the energetics and water flux of this family is lacking. Consequently, we assessed DEE, RMR, SusMS, BF, WTO and WEI across several different species of bathyergids from various climatic regions, and compared these to the established patterns of energetics and water flux for aboveground rodents. There was notable variation across the Bathyergidae inhabiting areas with different aridities, often contrary to the variations observed in above-ground species. These include increased DEE and WEI in arid-dwelling bathyergid species. While the climate was not a clear factor when predicting the SusMS of a bathyergid species, rather the degree of group living was a strong driver of SusMS, with solitary species possessing the highest SusMS compared to the socially living species. We conclude that the constraints of the underground lifestyle and the consequent spectrum of social behaviors possessed by the family Bathyergidae are most likely to be more crucial to their energetics and water flux than their habitat; however other important unstudied factors may still be at play. More so, this study provides evidence that often unreported parameters, measured through use of the DLW technique (such as BF and WEI) can enable species to be identified that might be at particular risk to climate change.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".