Stakeholder Perspectives on Triage in Wildlife Monitoring in a Rapidly Changing Arctic
Bibliographic record
Abstract
Monitoring activities provide a core contribution to wildlife conservation in the Arctic. Effective monitoring which allows changes in population status to be detected early, provides opportunities to mitigate pressures driving declines. Monitoring triage involves decisions about how and where to prioritise activities in species and ecosystem based monitoring. In particular, monitoring triage examines whether to divert resources away from species where there is high likelihood of extinction in the near-future in favour of species where monitoring activities may produce greater conservation benefits. As a place facing both rapid change with a high likelihood of population extinctions, and serious logistic and financial challenges for field data acquisition, the Arctic provides a good context in which to examine attitudes toward triage in monitoring. For effective decision-making to emerge from monitoring, multiple stakeholders must be involved in defining aims and priorities. We conducted semi-structured interviews with stakeholders in arctic wildlife monitoring (either contributing to observation and recording of wildlife, using information from wildlife observation and recording, or using wildlife as a resource) to elicit their perspectives on triage in wildlife monitoring in the Arctic. The majority (56%) of our 23 participants were predominantly in opposition to triage, 26% were in support of triage and 17% were undecided. Representatives of Indigenous organisations were more likely to be opposed to triage than scientists and those involved in decision-making showed greatest support for triage amongst the scientist participants. Responses to the concept of triage included that: 1) The species-focussed approach associated with triage did not match their more systems-based view (5 participants), 2) Important information is generated through monitoring threatened species which advances understanding of the drivers of change, responses and ecosystem consequences (5 participants), 3) There is an obligation to try to monitor and conserve threatened species (4 participants), and 4) Monitoring needs to address local people’s needs which may be overlooked under triage (3 participants). The complexity of decision-making to create monitoring programmes that maximise benefits to biodiversity and people makes prioritisation with simple models difficult. Using scenarios to identify desirable trajectories of Arctic stewardship may be an effective means of identifying monitoring needs.
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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 | 0.001 | 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 | 0.001 | 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) | 0.000 | 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".