Contrasts between habitat generalists and specialists: an empirical extension to the basic metacommunity framework
Bibliographic record
Abstract
Emergence of the metacommunity concept has made a substantial contribution to better understanding of the community composition and dynamics in a regional context. However, long-term field data for testing of available metacommunity models are still scarce, and the extent to which these models apply to the real world remains unknown. Tests conducted so far have largely sought to fit data on the entire regional set of species to one of several metacommunity models, implicitly assuming that all species operate similarly over the same set of sites. However, species differ in their habitat use. These differences can, in the most general terms, be expressed as a gradient of habitat specialization (ranging from habitat specialists to habitat generalists). We postulate that such differences in habitat specialization will have implications for metacommunity dynamics. Specifically, we predict that specialists respond more to local processes and generalists respond to regional spatial processes. We tested these predictions using natural microcosm communities for which long-term (nine-year) environmental and population dynamics data were available. We used redundancy analysis to determine the proportion of variation explained by environmental and spatial factors. We repeated this analysis to explain variation in the entire regional set of species, in generalist species only, and in specialists only. We further used ANOVA to test for differences in the proportions of explained variation. We found that habitat specialists responded primarily to environmental factors and habitat generalists responded mainly to spatial factors. Thus, from the metacommunity perspective, the dynamics of habitat specialists are best explained by a combination of species sorting and mass effects, while that of habitat generalists are best explained by patch dynamics and neutral models. Consequently, we infer that a natural metacommunity can exhibit complicated dynamics, with some groups of species (e.g., habitat specialists) governed according to environmental processes and other groups (e.g., habitat generalists) governed mainly by dispersal processes.
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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 | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".