From headwaters to receiving waters: river dynamics in an increasingly urban world
Bibliographic record
Abstract
Rivers historically played, and continue to play, a fundamental role in supporting humanity through provisioning numerous resources and services.Through time, research has aimed at understanding rivers through hydrological, geomorphological, and energic lenses to determine how such river dynamics combine to structure aquatic ecological communities.This research has led to the development of various conceptual models to describe river dynamics and ecological community structure.However, as many urban regions are often built around water sources, rivers are heavily altered as hydrological, geomorphological, and energic dynamics changed as land use intensified and human populations increased.Such changes ultimately altered the structure of ecological communities, and the services provided by rivers in urban regions.Here, we review and synthesize natural river concepts and urban river concepts, while emphasizing the importance of considering more natural river dynamics as a guide for river restoration in urban regions.Novelly, we connect river dynamics to their terminal receiving waters, as changing dynamics in rivers can ultimately alter receiving water dynamics.Moreover, rather than focus solely on the main river channel and terminal water body, we consider river dynamics and urban impacts to river associated wetlands, riparian zones, and hyporheic zones.Through linking river dynamics from headwaters to receiving waters, we synthesize and extend historical river concepts with more modern understanding of urban river dynamics across numerous aquatic zones.In this work, we highlight broad implications of urbanization and restoration for both academic research and applied management.Finally, we emphasize the potential of urban rivers in facilitating connections to nature for urban residents.With the importance of urban blue space recognized in the recently agreed upon Kunming-Montreal Global Biodiversity Framework, increasing access to, and ecological integrity in, urban blue spaces will require understanding river energy dynamics across the entire river course, from headwaters to receiving waters.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".