Clarifying ‘long-term’ for protected areas and other effective area-based conservation measures (OECMs): why only 25 years of ‘intent’ does not qualify
Bibliographic record
Abstract
The concept of ‘long-term’ is a key part of the definitions of both protected areas and other effective area-based conservation measures (OECMs). Draft principles for OECMs in Australia developed by the Australian Government propose a minimum period for OECMs of 25 years, where a landholder is not able to commit to in-perpetuity conservation. The proposal suggests this is consistent with IUCN Guidelines for Privately Protected Areas. As authors of the Guidelines for Privately Protected Areas we contend however that Australia’s proposed OECM guideline suggesting 25 years of “intention” to deliver biodiversity outcomes is ‘long-term’ is not supported by IUCN guidelines. Furthermore for protected areas, Australia has a long-established definition of ‘long-term’ – specifically a minimum timeframe of 99 years is required if permanent protection is not possible – embedded in both national policy and legal agreements. As national governments rapidly seek to define OECMs in response to the raised ambitions of the Kunming-Montreal Global Biodiversity Framework, there will be increasing interest in what counts towards Target 3. Ultimately, more land managed for conservation is good and all forms of area-based conservation should be encouraged. However, not all forms of area-based conservation qualify for inclusion in Target 3. Long-term intent and outcomes are fundamental, as outlined in the definitions of protected areas and OECMs.
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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) | 0.000 | 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".