Species Abundance, Not Diet Breadth, Drives the Persistence of the Most Linked Pollinators as Plant-Pollinator Networks Disassemble
Bibliographic record
Abstract
Theoretical and simulation studies predict that the order of species loss from mutualist networks with respect to how linked species are to other species within the network will determine the rate at which networks collapse. However, the empirical order of species loss with respect to linkage has rarely been investigated. Furthermore, a species' linkage is a composite of its diet breadth and its abundance, yet the relative importance of these two factors in determining species loss order is poorly known. Here we explore the order of pollinator species loss in two contrasting study systems undergoing land-use intensification, using >20,000 pollinator specimens. We found that a pollinator species' linkage, as measured independently within plant-pollinator networks, positively predicted its persistence at human-disturbed sites in three of four analyses. The strongest predictor of persistence in all analyses was pollinator species abundance. In contrast, diet breadth poorly predicted persistence. Overall, our results suggest that community disassembly order buffers plant-pollinator networks against environmental change by retaining the highly linked species that make a disproportionate contribution to network robustness. Furthermore, these highly linked species likely persist because they are also the most common species, not because they are dietary generalists.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".