Summary 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 .
Cross-pollination from fields of transgenic crops is of great public concern. Although cross-pollination in commercial canola (Brassica napus) fields has been empirically measured, field trials are expensive and do not identify the causes of cross-pollination. Therefore, theoretical models can be valuable because they can provide estimates of cross-pollination at any given site and time. We present a general analytical model of field-to-field gene flow due to the following competing mechanisms: the wind, bees, and autonomous pollination. We parameterize the model for the particular case of field-to-field cross-pollination of genetically modified (GM) canola via the wind and via bumble bees (Bombus spp.) and honey bees (Apis mellifera). We make extensive use of the large data set of bee densities collected during the recent U.K. Farm Scale Evaluations. We predict that canola approaches almost full seed set without pollinators and that autonomous pollination is responsible for > or = 25% of seed set, irrespective of pollinator abundance. We do not predict the relative contribution of bees vs. the wind in landscape-scale gene flow in canola. However, under model assumptions, we predict that the maximum field-to-field gene flow due to bumble bees is 0.04% and 0.13% below the current EU limit for adventitious GM presence for winter- and spring-sown canola, respectively. We predict that gene flow due to bees is approximately 3.1 times higher at 20% compared to 100% male-fertility, and due to the wind, 1.3 times higher at 20% compared to 100% male-fertility, for both winter- and spring-sown canola. Bumble bee-mediated gene flow is approximately 2.7 times higher and wind-mediated gene flow approximately 1.7 times lower in spring-sown than in winter-sown canola, regardless of the degree of male-sterility. The model of cross-pollination due to the wind most closely predicted three previously published observations: field-to-field gene flow is low; gene flow increases with the proportion of plants that are male-sterile; and gene flow is higher in winter- than in spring-sown canola. Our results therefore suggest that the wind, not bees, is the main vector of long-distance gene flow in canola.
The objective of general surveillance is to identify the occurrence of unanticipated adverse effects of GM crops on human health or the environment that were not covered in the environmental risk assessment. EuropaBio is harmonizing an approach to non-hypothesis driven post-market environmental monitoring relating to the cultivation of different GM crops, comprising a farmer questionnaire, existing surveillance systems as well as other data sources. As an unanticipated adverse effect is most likely to occur where the level of environmental exposure is highest, general surveillance focuses on the agricultural environment and those agronomic zones that are representative of commercial GM crop cultivation. The farmer questionnaire is one element of the general surveillance approach, and is largely based on routine observations by farmers cultivating GM crops. It aims at recording data and observations capturing the interaction of one GM event with the agricultural environment. Due to its modular structure, the farmer questionnaire can be used for different GM crops and traits as well as combinations of traits. Existing surveillance systems, which are not GM crop focused, are another element of the harmonized approach to general surveillance and provide information based on e.g. plant health and soil surveys, ecological and environmental observations. The aforementioned elements, in association with the assessment of results from research projects published in peer reviewed publications relating to the environmental safety of GM crops, individual company stewardship activities and issue alerts complete the EuropaBio approach which should allow for the identification of any potential adverse effects arising from the presence of GM crops.
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