The impact of plant diversity and vegetation composition on bumblebee colony fitness
Bibliographic record
Abstract
The current decline in pollinators may disrupt ecosystems and ecosystem services with potentially harmful effects on nature and human society. While the importance of habitat loss and fragmentation, pollution and increased disease risk in driving pollinator decline has been clearly demonstrated, the impact of resource diversity is less well understood. In this study, we investigated the effect of pollen diversity and composition on reproductive success and fitness of Bombus terrestris colonies. We asked the question whether a higher plant diversity results in a more diverse diet, lower pathogen incidence and a higher colony fitness. To answer these questions, colonies of lab‐reared bumblebees were placed in species‐poor heathlands and species‐rich semi‐natural grasslands that strongly differed in plant community composition and diversity. We examined pollen loads on the bodies of foragers and identified the plant taxa present in the realized diet via DNA metabarcoding of the ITS2 marker. Liquid chromatography–mass spectrometry (LC–MS) was used to compare peptide composition of pollen samples from both habitats. Colony fitness was assessed by counting the number of sexuals produced by the colony at the end of its cycle. At the same time, colonies were examined for parasite incidence. Pollen composition and diversity on pollinators' bodies differed significantly between bees foraging in grasslands and heathlands. Concomitantly, peptide composition differed significantly between pollen samples from grasslands and heathlands. Contrary to our prediction, colonies developed significantly better in heathland sites than in grasslands. In addition, the relationship between colony fitness and pollen diversity was weak and varied between the two habitats. Pathogen incidence was very low and not affected by habitat. Overall, our results indicate that plant diversity is not necessarily a good predictor of colony fitness, and that vegetation composition and associated differences in both the quantity and quality of pollen are more important than pollen diversity per se.
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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 | 0.001 | 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".