Understanding the Use of Ecosystem Service Knowledge in Decision Making: Lessons from International Experiences of Spatial Planning
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The limited understanding of how ecosystem service knowledge (ESK) is used in decision making constrains our ability to learn from, replicate, and convey success stories. We explore use of ESK in decision making in three international cases: national coastal planning in Belize; regional marine spatial planning on Vancouver Island, Canada; and regional land-use planning on the island of Oahu, Hawaii. Decision makers, scientists, and stakeholders collaborated in each case to use a standardized ecosystem service accounting tool to inform spatial planning. We evaluate interview, survey, and observation data to assess evidence of ‘conceptual’, ‘strategic’, and ‘instrumental’ use of ESK. We find evidence of all modes: conceptual use dominates early planning, while strategic and instrumental uses occur iteratively in middle and late stages. Conceptual and strategic uses of ESK build understanding and compromise that facilitate instrumental use. We highlight attributes of ESK, characteristics of the process, and general conditions that appear to affect how knowledge is used. Meaningful participation, scenario development, and integration of local and traditional knowledge emerge as important for particular uses.
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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 it