Inverse responses of species richness and niche specialization to human development
Bibliographic record
Abstract
Abstract Aim Humans impact biodiversity by altering land use and introducing nonnative species. Yet the extent to which coexistence processes, such as competition and niche shifts, mediate these relationships is not clear. This study compares how human development influences wetland plant diversity by examining patterns of species richness, niche specialization and nonnative species occurrences along a human development gradient. Location Alberta, Canada. Taxon Plants. Methods We computed species richness and niche specialization (a measure of the range of human development extents over which a species occurs) from species occurrence data across 1582 wetlands. We tested associations between human development extent and species richness, niche specialization and nonnative species using linear mixed models. We used nonmetric multidimensional scaling ordination to examine whether community composition differed among wetlands surrounded by different human development extents. Results Species richness and niche specialization show contrasting relationships with human development: richness was highest and niche specialization was lowest at intermediate human development extents, suggesting that competitive ability and environmental filtering may contribute to low richness at low and high development extents, respectively. Wetlands surrounded by the highest and lowest human development extents had similar levels of richness and niche specialization, but differed in community composition. The proportion of nonnative species increased with increasing human development, alternatively suggesting that the substitution of native species by nonnatives in developed areas may contribute to reduced richness and influence community assembly. Main conclusions These findings demonstrate that human land development plays a major role in shaping species richness by influencing the number of nonnative species and the niche specialization of species inhabiting a wetland. Furthermore, these findings suggest that the proportion of nonnative species is an overlooked factor potentially influencing plant richness; including this variable may help clarify the inconsistent responses of diversity to human development over large spatiotemporal scales.
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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 | 0.000 | 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 | 0.000 |
| 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".