Spider, bee, and bird communities in cities are shaped by environmental control and high stochasticity
Bibliographic record
Abstract
Spatially organized distribution patterns of species and communities are shaped by both autogenic processes (neutral mechanism theory) and exogenous processes (niche theory). In the latter, environmental variables that are themselves spatially organized induce spatial structure in the response variables. The relative importance of these processes has not yet been investigated in urban habitats. We compared the variance explained by purely spatial, spatially structured environmental, and purely environmental components for the community composition of spiders (Araneae), bees (Apidae), and birds (Aves) at 96 locations in three Swiss cities. Environmental variables (topography, climate, land cover, urban green management) were measured on four different radii around sampling points (< 10 m, 50 m, 250 m, 1000 m), while Moran's eigenvector maps (MEMs) acted as spatial variables. All three taxonomic groups showed weak spatial structure. Spider communities reacted to very fine-scaled environmental changes of lawn and meadow management and climate. Bird community composition was determined by woody plants as well as solar radiation at all radii, the scale of the influence varying among species. Bee communities were weakly explained by isolated variables only. Our results suggest that the anthropogenic structuring of urban areas has disrupted the spatial organization of environmental variables and inhibited the development of biotic spatial processes. The near absence of spatial structure may therefore be a feature typical of urban species assemblages, resulting in urban community composition mainly influenced by local environmental variables. Urban environments represent a close-knit mosaic of habitats that are regularly disturbed. Species communities in urban areas are far from equilibrium. Our analysis also suggests that urban communities need to be considered as being in constant change to adapt to disturbances and changes imposed by human activities.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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 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".