The optimization of microsatellite genotyping and genetic sexing of non-invasively collected polar bear tissue: Implications for monitoring and census.
Bibliographic record
Abstract
The monitoring of Polar Bears in Canada has been completed largely through management unit (MU) wide capture-mark-recapture (CMR) surveys. While this data is very useful at the time of collection, these surveys are expensive and take time to plan and execute; cannot be feasibly executed across the polar bear range at intervals that reflect the expected rapid environmental changes in the Arctic; and are disdained by the Inuit as being invasive. As part of recent efforts to explore less expensive and non-invasive methods to monitor polar bears (see Wong et al & Van Coevderden de Groot et al this conference) we are evaluating genetic information obtained from non-invasively collected polar bear tissue. In this work we report on the genetic data obtained from non-invasively collected harisnags recovered from sampling stations erected between May-June 2006-2009 in M’Clintock Channel, Nunavut. Across the 4 years 344 hair snags were collected; following Paetkau (2004) we optimized 6 microsatellite loci to reliably amplify polar bear DNA from this tissue and we modified the procedure of Pages et al (2009) to reliably genetically sex these tissues. Our estimates for two common errors with this type of tissue across all loci – allelic dropout (0.026) and false allele (0.03) - were both less than p =.05. This suggests these errors are not going to significantly affect the accuracy of the consensus genotypes collected from these data. Using consensus genotypes from relevant hairsnags, we posit a minimum of 59 (max 82) unique bears entered our sampling stations. Of these, 24% were female, 64% were male, and 12% could not be sexed. We resampled 2 bears in 2006, 1 in 2007, 0 bears in 2008 and 14 bears in 2009 – the 2009 value reflects significantly increased sampling effort in 2009. Five bears were re-sampled between the non-invasive surveys in 2006-2009. When comparing our data to a subset of cubs and subadults captured during the Taylor et al. (2006) CMR survey of M’Clintock Channel (MU), we found 6 genotype matches. Our sampling stations may have a male bias as the sex ratio from the 1998-2000 CMR study was 42.1% ♂ (Taylor et al 2006) vs. 64% ♂ (this study). We cannot accurately determine the age bias (but see Wong et al this conference). Genetic data from Polar bear faecal samples may provide an unbiased sex and age sample of polar bears in any MU. Any data from these samples will help refine hairsnag derived MKNA estimate of polar bears from any MU. Here we report on our efforts to genotype and genetically sex 95 faecals we have collected from M’Clintock Channel from 2006-2009. Finally, we discuss the implications of these findings, results from other noninvasive work (Wong et al & Van Coevderden de Groot et al this conference) and ongoing/proposed work in the context of i) a non-invasive Inuit-based polar bear activity and health survey, and ii) a more rigorous census method which may allow more precise adjustments of harvest levels than currently possible using infrequently collected CMR data only.
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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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".