The effect of urban environments on the diversity of plants in unmanaged grasslands in Los Angeles, United States
Bibliographic record
Abstract
Urbanization is a strong driver of plant diversity and may have complex effects on developed ecosystems. Nevertheless, it remains unclear whether urban environments increase or decrease plant biodiversity compared with rural environments. Further, it is also unclear how non-native plant species contribute to spatial diversity patterns and ecosystem services. Better understanding these diversity drivers across gradients of urbanization has the potential to enhance native species conservation (e.g., targeted restoration activities), leading to positive feedbacks for broader promotion of biodiversity and societal benefits (e.g., links with native biodiversity and human health). In this study, we hypothesized that for plant species in unmanaged grasslands, urbanization would lead to declines in diversity at both small and medium scales. We established a network of remnant grassland sites across an urban to rural gradient in Los Angeles, CA, USA. Across this gradient we assessed patterns of alpha and beta diversity during the 2019 growing season. We found that local plant alpha diversity in remnant grasslands declined in urban landscapes (measured by surrounding percent development) due mostly to loss of native species. However, at intermediate scales across unmanaged parks and greenspaces, we saw increases in beta diversity at more urban locations. This was possibly due to the patchy dominance of different exotic species at urban locations; whereas, in rural locations non-native and native species were common across plots. Conservation is often informed by examinations of large scale, city-wide assessment of diversity, however, our results show that urban plant diversity, particularly native species, is affected at all spatial scales and beta-diversity can add important insights into how to manage urban ecosystems. Conservation that accounts for alpha and beta diversity may promote “virtuous cycle” frameworks where the promotion and protection of biodiversity simultaneously reduces the negative effects of invasion.
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How this classification was reachedexpand
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 | 0.001 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".