Strengths and complementarity of systematic conservation planning and Key Biodiversity Area approaches for spatial planning
Bibliographic record
Abstract
Developing biodiversity-inclusive spatial plans at a national level is the focus of Target 1 of the Kunming-Montreal Global Biodiversity Framework (KMGBF). There are 2 general approaches to identifying areas of value for biodiversity plans: criteria-based, such as the Key Biodiversity Areas (KBA) process, and systematic conservation planning (SCP) approaches, which apply complementarity to efficiently achieve specific quantitative targets. We examined the benefits of both approaches and considered how the KBA approach can best complement SCP. We reviewed 200 papers articles that applied SCP to real-world data with the Marxan conservation design software. Our review showed that targets for biodiversity elements are poorly selected in many SCP publications, with more than 75% of the studies applying uniform percentage target amounts to planning elements. Uniform targets favor more widespread species and ecosystems that are likely to be more common and less important for conservation. The strengths and complementarities of KBA and SCP approaches were reviewed and we identified the elements from both approaches that should be considered for spatial planning to achieve Target 1 in the KMGBF. In particular, the global approach of KBAs (i.e., identifying sites of global significance for species or ecosystems) better complements SCP, which often has a national or subnational focus. The KMGBF will fail if conservation of globally significant sites is not targeted and these sites are not incorporated in national spatial planning.
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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) | 0.001 | 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".