Up High, Hot and Dry: Individual Reproductive Output in Subalpine Bees Declines With Increasing Drought Severity
Bibliographic record
Abstract
Wild bees play indispensable ecological roles in many ecosystems, yet declines in many species have been documented in recent years. These declines have been linked to numerous anthropogenic pressures, including climate change, which can influence bee populations directly (i.e., via physiological mechanisms) and indirectly (e.g., through changes to floral resource quantity and quality). Widespread changes in the distributions and abundances of many bee species have been linked to climate change at large spatial scales; yet, the local-scale processes that generate these broad-scale patterns are little known. Specifically, it is unclear how climate change influences the fitness of individual bees, despite the fact that broad-scale patterns of decline must be driven by individual-level processes. Our study examines the individual fitness responses (i.e., reproductive output) of five solitary bee species in the genus Osmia to variations in local climate variables in subalpine habitats. Over nine years, we tracked brood cell production in over 700 individual female bees, conducted repeated surveys of floral abundance (while taking into account the specific floral host taxa used by each bee species), and recorded local precipitation and temperature at seven sites. Our data revealed both direct and indirect (floral resource-mediated) negative effects of drought: the total number of brood cells produced by nesting females decreased significantly in summers characterized by greater drought severity and high temperatures-a relationship-driven partly by significant decreases in floral host-plant availability in hotter and drier years. Our study highlights how the negative consequences of climate change for bee populations can manifest at the level of individuals and the role of floral resources in mediating these relationships. Overall, our results suggest that the increasingly warm and dry conditions forecasted for our study area will have net negative effects on the demographic success of these solitary bees.
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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 | 0.000 |
| 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) | 0.001 | 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".