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From headwaters to receiving waters: river dynamics in an increasingly urban world 

2023· preprint· en· W4381332885 on OpenAlexafffundabout
Lauren Lawson, Rachel K Giles, Lauren Emily Barth, Ian A. Richter, E. Todd Howell, Donald A. Jackson

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicFlood Risk Assessment and Management
Canadian institutionsMinistry of the Environment, Conservation and ParksUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Toronto
KeywordsRiparian zoneWetlandPatch dynamicsNatural (archaeology)UrbanizationChannel (broadcasting)ProvisioningRiver ecosystemEcologyEnvironmental scienceGeographyHydrology (agriculture)Environmental resource managementEcosystemHabitatGeology

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.004
Scholarly communication0.0040.006
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.022
GPT teacher head0.269
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes3
Has abstractyes

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