Building ecosystem resilience for climate change adaptation in the Asian highlands
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 Asian Highlands, the vast mountainous area from Pakistan to China including the Hindu‐Kush Himalaya and Tibetan Plateau, have considerable global importance; they are the source of most of the major rivers of Asia, which sustain billions of downstream dwellers, are part of four Global Biodiversity Hotspots, and support rich cultural diversity. However, climate warming in the Himalaya–Tibetan Plateau has been greater than two times the global average, and regional climate appears to be shifting with potential to trigger large‐scale ecosystem regime shifts (‘landscape traps’). A host of other drivers—urbanization/infrastructure development, land‐use/agricultural practices, upstream/downstream water management and ongoing nation‐state security conflicts—interact with climate signals to produce complex changes across ecological and social systems. In response, highlands people are evolving hybrid forms of adaptive capacity where ‘bottom‐up’ behaviors are mixing with ‘top‐down’ state and market policies. To increase ecosystem and livelihood resilience to future change, there is a need to link upstream and downstream conservation action with local climate adaptation. While the key problem is that institutional and government capacity for coordination is low, we present four general strategies to move forward: application of cross‐sector coordinated planning, strategic integration of science‐based conservation with developing local‐level hybrid knowledge, recognition of the critical role of governance in support of change, and increased emphasis on environmental security. We discuss these strategies for each driver of change in the region. WIREs Clim Change 2014, 5:709–718. doi: 10.1002/wcc.302 This article is categorized under: Climate, Ecology, and Conservation > Conservation Strategies Climate and Development > Social Justice and the Politics of Development
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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