4.7 Article

The influence of pollinator abundance on the dynamics and efficiency of pollination in agricultural Brassica napus:: implications for landscape-scale gene dispersal

期刊

JOURNAL OF APPLIED ECOLOGY
卷 43, 期 6, 页码 1196-1202

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WILEY-BLACKWELL
DOI: 10.1111/j.1365-2664.2006.01219.x

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Apis; Bombus; canola; cross-pollination; gene flow; oilseed rape

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1. It is important to understand the pollination processes that generate landscape-scale gene dispersal in plants, particularly in crop plants with genetically modified (GM) varieties. In one such crop, Brassica napus, the situation is complicated by uncertainty over the relative importance of two pollen vectors, wind and insects. 2. We investigated pollination in two fields of B. napus that bloomed at different times of year (April vs. July) and attracted different abundances of foraging social bees. Rates of pollen transfer were quantified by counting the pollen grains deposited on stigmas and remaining in the anthers at intervals after flower opening. 3. Flowers open in April were adequately pollinated only after 5 days and only 10% received even a single bee visit. Flowers open in July received three bee visits per hour and were fully pollinated within 3 h. 4. Based on published measurements of airborne pollen dispersal, we estimate that wind-pollination from a hypothetical field 1 km distant could have fertilized up to 0.3% of the field's seed when bees were scarce in April but only up to 0.007% when bees were abundant in July. 5. The efficiency of pollination (the proportion of pollen released from anthers that landed on receptive stigmas) was seven times greater in July (1.5%) than in April (0.2%). The relatively high efficiency of insect pollination may help to explain the evolutionary maintenance of entomophily. 6. Synthesis and applications. Our results begin to resolve a long-standing inconsistency among previous studies by suggesting that the susceptibility of fields of B. napus to long-distance cross-pollination by wind depends on the level of bee activity. Models for predicting GM gene flow at the landscape-scale in this crop should take this into account.

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