Use of faecal pellet size to differentiate age classes in female Svalbard reindeer <i>Rangifer tarandus platyrhynchus</i>
Bibliographic record
Abstract
Abstract Proper management of threatened populations requires prior knowledge of population sizes and structures, however, current techniques to gather this information are generally impractical, costly, and can be physically stressful for the animals. Non‐invasive methods (e.g. faecal sampling) that can produce high quality and accurate results are better alternatives. Using faecal samples collected from a Svalbard reindeer Rangifer tarandus platyrhynchus population in the winters of 2008 (N = 158) and 2009 (N = 161), we investigated and validated the feasibility of using faecal pellet sizes to differentiate between female calves, yearlings and adults. We found that pellets from adult females were longer than those from calves, and pellets from adults and yearlings were clearly wider than those from calves. With an accuracy of 91% correct classification, we did show that a combination of faecal pellet dimensions (length, width and depth), rather than a single dimension alone, can allow managers to clearly differentiate between age classes if pellets already identified as being from females are used. We also found a positive relationship between live weight and pellet size of the reindeer. Combined with DNA analysis to identify the gender of the animal that produced the faecal pellet, this information may provide important population parameters and be a valuable tool for the monitoring of various ungulate species including wild reindeer.
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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 | 0.000 | 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) | 0.002 | 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 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".