How Does Climate Change Affect Emergent Properties of Aquatic Ecosystems?
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
Abstract Emergent properties of ecosystems are community attributes, such as structure and function, that arise from connections and interactions (e.g., predator–prey, competition) among populations, species, or assemblages that, when viewed together, provide a holistic representation that is more than the sum of its individual parts. Climate change is altering emergent properties of aquatic ecosystems through component responses, a combination of shifts in species range, phenology, distribution, and productivity, which lead to novel ecosystems that have no historical analog. The reshuffling, restructuring, and rewiring of aquatic ecosystems due to climate impacts are of high concern for natural resource management and conservation as these changes can lead to species extinctions and reductions in ecosystem services. Overall, we found that substantial progress has been made to advance our understanding of how climate change is affecting emergent properties of aquatic ecosystems. However, responses are incredibly complex, and high uncertainty remains for how systems will reorganize and function over the coming decades. This cross-system perspective summarizes the state of knowledge of climate-driven emergent properties in aquatic habitats with case studies that highlight mechanisms of change, observed or anticipated outcomes, as well as insights into confounding non-climate effects, research tools, and management approaches to advance the field.
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 | 0.000 | 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) | 0.001 | 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