Freshwater insect communities in urban environments around the globe: a review of the state of the field
Bibliographic record
Abstract
Urbanization is a key stressor of freshwater habitats, possibly contributing to global insect declines. However, scientific understanding of urbanization's effects on aquatic insect communities has largely been based on studies of temperate streams. We reviewed global urban freshwater macroinvertebrate community studies, classifying habitat type, location, urbanization metrics, biodiversity metrics, and focal taxa, drawing from 114 studies in 32 different countries. Our goals were to: (1) investigate the extent of research on urbanization across a variety of freshwater habitats, (2) examine the representation in empirical literature across the globe by comparing cities in different geographic regions, and (3) highlight how study approaches including taxonomic resolution and the inclusion of trait data impact interpretation of these patterns. Most studies were conducted in North America and Europe, but there is growing representation from other continents. Additionally, lentic environments were underrepresented in the literature on community responses to urbanization compared to lotic studies. Therefore, we suggest that lentic habitats should be investigated more thoroughly. We suggest that future empirical studies should incorporate traits of the taxa investigated to better predict how communities respond to urban stressors. The lack of consistent results from the reviewed studies showed that there is no single, predictable effect of urbanization, indicating that future meta-analyses and review papers should consider the potential context-dependency of freshwater insect responses to anthropogenic pressures. Our goal in highlighting understudied environmental and regional contexts is to move toward holistically addressing the ongoing challenges of urban freshwater insect conservation and freshwater ecology research.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".