Bethwell Claudia, Müller Hans-Jürgen, Eulenstein Frank, Graef Frieder
Leibniz-Centre for Agricultural and Landscape Research, Institute of Land Use Systems, Müncheberg, Germany.
J Environ Monit. 2012 May;14(5):1453-61. doi: 10.1039/c2em10822d. Epub 2012 Apr 12.
EU legislation stipulates that GM crops have to be monitored for potential adverse environmental effects. Monitoring preferably should take place in the most exposed areas-the cultivated fields and their neighbouring environment. Current monitoring designs do not give detailed consideration to the different exposure intensities in agricultural practice. At the same time, the selection of specific, more exposed sites is difficult considering the dynamic and diversity of crop cultivation and rotation systems and their environments. We developed an approach for prioritising the monitoring of on-farm and neighbouring sites based on differing exposure levels using a minimum dataset of cultivation and land use information. Applying a Bt-maize cultivation scenario to Brandenburg, Germany, where presently no GM crops are cultivated, we systemised and categorised areas with different spatio-temporal exposure intensities including 50 m, 200 m and 1000 m buffers. These categories correspond to different suitabilities to serve as monitoring sites. Sites are prioritised using a sequential scheme. This yields an improved and objective spatial monitoring design providing detailed exposure information. This methodology is flexible and transferable to any agricultural setting, therefore enabling superior statistical comparisons between locations and regions and thus enhancing monitoring data quality.
欧盟立法规定,必须对转基因作物进行监测,以评估其可能产生的不利环境影响。监测最好在受影响最大的区域进行,即耕地及其周边环境。目前的监测设计没有充分考虑农业实践中不同的暴露强度。同时,考虑到作物种植和轮作系统及其环境的动态性和多样性,选择特定的、暴露程度更高的地点也很困难。我们开发了一种方法,利用最少的种植和土地利用信息数据集,根据不同的暴露水平对农场及其周边地点的监测进行优先级排序。将一种转基因玉米种植方案应用于德国勃兰登堡州(目前该地区未种植转基因作物),我们对具有不同时空暴露强度的区域进行了系统化和分类,包括50米、200米和1000米缓冲区。这些类别对应于作为监测地点的不同适宜性。通过顺序方案对地点进行优先级排序。这产生了一个改进的、客观的空间监测设计,提供了详细的暴露信息。这种方法具有灵活性,可应用于任何农业环境,因此能够在不同地点和区域之间进行更优的统计比较,从而提高监测数据质量。