Important pollinator species for conserving rare plant species endemic to San Clemente Island, California
Bibliographic record
Abstract
Much effort has been spent on the conservation of rare, threatened, and endangered plants in the biodiversity hotspot of the California Floristic Province, however little is known about the identity of their pollinators. In this study we provide the first formal study on the identity of the invertebrate pollinators of five rare endemic island plant species from San Clemente Island, the southernmost of the California Channel Islands: Delphinium variegatum ssp kinkiense, Lithophragma maximum, Malacothamnus clementinus, Malva assurgentiflora ssp glabra, and Sibara filifolia. We surveyed plant-pollinator interactions at populations of each focal plant species using timed sweep-netting. We used pollinator capture data to compile bipartite interaction networks for each plant population, and calculated centrality indices (degree, betweenness centrality, and closeness centrality) of pollinators to identify species important to network stability. We found a significant effect of pollinator taxonomic group (fly, bee, wasp, or Lepidopteran) on some indices of pollinator centrality in interaction networks, and variation in pollinator centrality between different locations. Hoverflies, moths, and butterflies were important generalists with higher network centrality across all plant populations, while bees tended to be more specialists within their networks, except for the Malva assurgentiflora ssp glabra network, where bees were on average of higher centrality than flies. We recommend targeted restoration practices for future study that could support pollination both directly and indirectly to focal rare plant species of conservation interest across plant populations. These practices could augment general pollinator conservation best practices such as reducing pesticide use and planting native plant species to provide increased pollination to endangered plants.
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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".