Unintended Consequences of Urbanization for Aquatic Ecosystems: A Case Study from the Arizona Desert
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
Many changes wrought during the construction of “designer ecosystems” are intended to ensure—and often succeed in ensuring—that a city can provide ecosystem goods and services; but other changes have unintended impacts on the ecology of the city, impairing its ability to provide these critical functions. Indian Bend Wash, an urbanizing watershed in the Central Arizona–Phoenix (CAP) ecosystem, provides an excellent case study of how human alteration of land cover, stream channel structure, and hydrology affect ecosystem processes, both intentionally and unintentionally. The construction of canals created new flowpaths that cut across historic stream channels, and the creation of artificial lakes produced sinks for fine sediments and hotspots for nitrogen processing. Further hydrologic manipulations, such as groundwater pumping, linked surface flows to the aquifer and replaced ephemeral washes with perennial waters. These alterations of hydrologic structure are typical by-products of urban growth in arid and semiarid regions and create distinct spatial and temporal patterns of nitrogen availability.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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