Current climate and latitude shape the structure of bat-fruit interaction networks throughout the Neotropical region
Bibliographic record
Abstract
How ecological interactions vary across spatial and environmental gradients has received increasing attention in recent years, contributing to the revelation of the drivers of biodiversity. However, it is still unclear how the structure of ecological interactions varies across large spatial scales and which climatic factors are associated with such variation. Here, specific predictions were derived and tested to evaluate how climatic factors and latitude are associated with the structure of bat-fruit interaction networks throughout the Neotropical region. For each study site (n = 44 sites, encompassing 48 degrees of latitude), four metrics were used to describe the network structure (i.e., network size, connectance, modularity, and nestedness). In general, an increase in modularity and a decrease in connectance and nestedness was observed towards lower latitudes and in sites with lower precipitation seasonality. Moreover, plant richness within networks increased towards lower latitudes and in sites with higher annual precipitation, whereas bat richness increased at lower latitudes and in sites with lower precipitation seasonality. These findings partially confirm both energy and seasonality hypotheses and suggest that fruit-bearing plant richness and fruit availability associated with annual precipitation and precipitation seasonality can be important correlates shaping the structure of ecological interactions throughout the Neotropical region.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".