Environmental filtering and dispersal as drivers of metacommunity composition: complex spider webs as habitat patches
Bibliographic record
Abstract
Abstract Metacommunity theory has advanced the understanding of the patterns and processes shaping community structure at multiple scales. Various models have been put forward to explain the relative effects of environmental filtering, dispersal, and species traits on community composition. Here, we focus on complex, three‐dimensional webs of two social and two solitary spider species as habitat patches for associated communities of arthropods in a tropical rainforest in Ecuador. We used variance partitioning, constrained ordination, coherence analyses, and a colonization experiment to assess the role of environmental filtering and dispersal in this system. We found that the composition of communities associated with the four host species was mostly differentiated along two ordination axes, with the first axis roughly corresponding to level of sociality (solitary vs. social) and the other to web size. Associate abundance increased, but their density per unit volume decreased with host web size for all host species. Webs of social spider species had more variable communities and proportionally more aggressive (i.e., predatory) associates. After rarefaction to control for larger samples in larger webs, only one of the species showed a significant increase of species richness as a function of web size. The relatively quick colonization of experimentally established webs suggests high dispersal of more generalist species, but their lower proportion in older webs provides some evidence of a colonization–competition trade‐off at longer temporal scales. The distinctness of the communities associated with the four host species, and the eventual change in proportion of associates in newly founded vs. old webs, despite high dispersal, is consistent with environmental filtering and species traits playing a major role in determining patterns of species distribution in this system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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 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".