Comparing approaches to quantify urbanization on a multicontinental scale
Bibliographic record
Abstract
Urbanization is an increasingly prevalent driver of environmental, ecological, and evolutionary change in both terrestrial and aquatic systems, and it is important that our sampling designs accurately capture this urban environmental change. Common approaches to sampling urban environments include: urban-nonurban transects, which sample along urbanization gradients; random points, which sample locations at random within an area of interest; and systematic points, which sample locations based on a regularly-spaced grid from a predetermined starting point within the area of interest. Presently, we lack a comparative analysis of the efficacy of these different sampling designs in capturing variation in urban environments. Here, we compare the environmental variation captured by transect- and point-based sampling designs in 136 cities across six continents. We quantified and compared a common set of environmental variables for each sampling design, with variables capturing landcover, climate, and socioeconomic facets of urban environments. Mean landcover and socioeconomic metrics consistently differed among sampling designs, in contrast to climate variables that primarily varied among cities. Additionally, changes in environmental variables with distance from the city centre depended on the sampling design, with this distance-by-sampling design interaction present in 27%-51% of cities, depending on the environmental variable. This implies that the rate of environmental change along urban-nonurban gradients frequently depends on the sampling design used. We also examined potential causes of deviations between transect- and point-based sampling designs and identified human population density and city area as common predictors of deviations between transect- and point-sampling designs. Our results show that sampling design can dictate how the urban environment is characterized, with sampling design as important - or more important - as the selected environmental variable. We further developed R code so researchers can implement these methods as they develop and validate sampling designs in novel or unstudied urban environments.
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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 | 0.016 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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 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".