Pollen carryover, pollinator movement, and spatial context impact the delivery of pollination services in apple orchards
Bibliographic record
Abstract
Assessing the relative contributions of different pollinator taxa to pollination services is a central task in both basic eco-evolutionary research and applied conservation and agriculture. To that end, many studies have quantified single-visit pollen deposition and visitation frequency, which together determine a pollinator species' rate of conspecific pollen delivery. However, for plant species that require or benefit from outcrossing, pollination service quality further depends upon the ratio of outcross to self-pollen deposited, which is determined by two additional pollinator traits: pollen carryover and movement patterns among genetically compatible plant individuals. Here, we compare the pollination capacities of managed honey bees, native bumble bees, and native mining bees in apple-a varietally self-incompatible commercial crop-when pollen carryover and pollinator movement patterns are considered. We constructed simulation models of outcross pollen deposition parameterized using empirically measured single-visit pollen deposition, visitation frequency, and probabilities of intertree movement exhibited by each pollinator type, as well as pollen carryover patterns simulated based on parameters reported in the literature. In these models, we also explicitly specified the spatial relationships among cross-compatible trees based on field-realistic orchard layout schemes. We found that estimated pollination service delivery was considerably reduced for all pollinator types when pollen carryover and pollinator movement patterns were considered, as compared to when only single-visit pollen deposition and visitation frequency were considered. We also found that the performance of different pollinator types varied greatly across simulated orchard layout schemes and pollen carryover scenarios, including one instance where bumble and mining bees reversed their relative rankings. In all simulations, native bumble and mining bees outperformed managed honey bees in terms of both outcross pollen delivery per unit time and per flower visited, with disparities being greatest under scenarios of low pollen carryover. We demonstrate the degree to which pollination studies may reach inaccurate conclusions regarding pollination service delivery when pollen carryover and pollinator movement patterns are ignored. Our finding of the strong context dependence of pollination efficiency, even within a single plant-pollinator taxon pair, cautions that future studies in both basic and applied pollination biology should explicitly consider the ecological context in which pollination interactions take place.
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".