Open to change but stuck in the mud: Stakeholder perceptions of adaptation options at the frontlines of climate change and protected areas management
Bibliographic record
Abstract
In recent decades, the literature on climate change and biodiversity conservation has proposed numerous climate change adaptation options; however, their effectiveness and feasibility have rarely been evaluated by those involved in frontline decision-making. In this paper, we use data from a two-day climate change adaptation workshop held at Bruce Peninsula National Park and Fathom Five National Marine Park, in Ontario, Canada, to understand stakeholder views on different types of adaptation options. We found that most (45%) adaptation options identified by participants were “conventional” (i.e., they are already in use and are relatively low risk and familiar to practitioners) and oriented towards directing change (i.e., they aim to help species and ecosystems respond to change and transition to a desired future state). These options also received higher effectiveness and feasibility ratings than “novel” ones. The remaining options (55%) were either “conventional” and aimed towards resisting change, or else were “novel.” Our results suggest that practitioners are open to working with change; however, there is some management resistance to more dynamic “novel” options (e.g., adjusting species assemblages), which in many instances will be required to effectively deal with inevitable climate change impacts. By focusing on understanding the factors that influence the prioritization and feasibility of adaptation options at the regional scale, and by providing practical recommendations to enhance organizational capacity to adapt to climate change, we address key implementation gaps identified in the literature.
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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 | 0.021 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".