Groundwater Adaptation in the Pacific Islands: A Transdisciplinary Review
Bibliographic record
Abstract
The Pacific Islands are among the most exposed regions to the impacts of climate change. Groundwater resources, as vital resources that are an integral part of cultures, must be preserved and protected. These resources are inherently limited and highly vulnerable to climate change across multiple time scales, including sea level rise and rising air and ocean temperatures, as well as changes in the frequency and intensity of tropical cyclones and droughts. This transdisciplinary review aims to optimize the design and implementation of effective adaptation measures to ensure sustainable water management in the Pacific Islands. The review begins with a guiding question: What approaches are most relevant and effective for investigating groundwater resources and for designing and implementing adaptation strategies on these islands? Based on a synthesis of the hydrogeological background, projected climate change impacts on groundwater, and potential adaptation strategies to support groundwater security, we identify three key considerations for ensuring effective and sustainable adaptation. First, adaptation measures must be tailored to the diverse social and cultural contexts of Pacific Island communities, including local governance structures, inter-community diversity, beliefs, and cultural practices, to avoid maladaptation and achieve culturally appropriate, socially acceptable adaptation. Second, in line with the first consideration, integrating traditional knowledge with insights from hydrological and climate sciences is essential for developing adaptation strategies. In this article, we define traditional knowledge as the cumulative, place-based, and culturally grounded ways of knowing developed through generations of lived experience and close interaction with ancestral territories, encompassing orally transmitted understandings of environmental change and human–environment relationships. Each discipline and epistemology offers complementary strengths, and transdisciplinary, inter-epistemic engagement can bridge them by linking empirical approaches that inform broader-scale observations and analytical frameworks with traditional knowledge grounded in lived experience and cultural continuity. Third, adaptation must progress despite irreducible uncertainties in climate projections and hydrogeological conditions, using frameworks such as “robust” and “collaborative” decision-making to ensure inclusivity. Overall, inclusive engagement of diverse stakeholders and inter-epistemic, transdisciplinary dialogues are crucial to achieve sustainable water management in the Pacific Islands facing climate change.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".