Designing a Long-term Ecological Change Monitoring Program for BC Parks
Bibliographic record
Abstract
Global climate changes are impacting the entire landscape and although intended as ecological reservoirs and refugia, parks and protected areas are not immune to these changes. Provincially, BC Parks’ staff identify stressors and threats in conservation risk assessments and have identified myriad challenges amplified by climate change. The role of monitoring in protected areas management in general, and with respect to climate change in particular, is identified as central to most assessment and adaptation strategies. This paper describes our work in the development and implementation of a province-wide long-term ecological change monitoring (LTEM) program that can be conducted using a hybrid scientific/citizen-science model. The intent is to help understand a) the state of ecological integrity of BC Parks on a provincial scale and b) long-term ecological change of which climate change is one of the leading causes. Although still in the preliminary stages of implementation, we reflect on some of the lessons we are learning along the way from discussions with field staff, scientists and managers in the protected areas field.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".