Effects of precipitation extremes on nestedness and modularity of tropical seed dispersal networks
Bibliographic record
Abstract
El Niño is a major driver of fluctuations in tropical precipitation and fruiting production, with cascading effects on frugivores. As places get wetter, mutualistic networks tend to become more modular and less nested. In order to test the impact of severe floods and droughts caused by the El Niño cycle of 2015-2016 on nestedness and modularity of mutualistic networks, we determined the links between frugivorous bats and the plants in their diets by DNA barcoding bat faeces and used null models for our network comparisons. Despite the contrasting effects of droughts and floods in the dry forest and rainforest, respectively, we observed similar changes in network structure for both forests. We found higher values of modularity, but lower of nestedness for most networks comparisons. Over all we found higher nestedness in the dry forest than the rainforest and minimal difference between wet and dry season in the dry forest. A lower nestedness might reduce the number of species supported by the habitat as well as increase species competition. Although the increase in modularity might reduce the number of coexisting species in the environment, higher network compartmentalization leads to greater stability, slower spread of disturbance and smaller chances of having trophic cascades. Therefore, changes in network structure promoted by El Niño are likely to have dual effects on networks with some effects leading to greater stability while others to increasing competition.
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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".