Multi-trophic metacommunity responses to habitat fragmentation in the Brazilian Atlantic Forest
Bibliographic record
Abstract
Abstract The structure of ecological communities is profoundly altered by anthropogenic disturbance to landscapes. However, most reported impacts rely on the quantification of diversity estimates for single trophic levels or impacts on key species of interest. In this analysis we integrate measures of community structure, comparisons of interaction networks and measures of β -diversity across four trophic levels: plants, bats, bat ectoparasites and bacteria within the ectoparasites. Our data show that bat, bat fly, and bacterial communities are significantly nested across forest fragments, with specialist consumers in all groups being found in fewer fragments than generalists. We found substantial β -diversity in both species richness and interaction richness across fragments but no decline in interaction redundancy with decreasing fragment size, likely because even intact forest networks had very low redundancy in our dataset. Despite the loss of species and interactions, our data provide support for the conservation value of even the smallest and most disturbed forest fragments where essential seed dispersal services are potentially maintained by Artibeus , Carollia and Sturnira and distinct sets of taxa and interactions are supported. These species may be key in the potential recovery of these habitats, but our data highlight the fragility of these communities which have contracted around these disturbance-tolerant species.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".