Mundt Christopher C, Wallace Larae D, Allen Tom W, Hollier Clayton A, Kemerait Robert C, Sikora Edward J
Department of Botany and Plant Pathology, 2082 Cordley Hall, Oregon State University, Corvallis, OR 97331-2902, USA.
Biol Invasions. 2013 Jul 1;15(7):1431-1438. doi: 10.1007/s10530-012-0381-z.
Hosts of soybean rust () are sensitive to low temperatures, limiting this obligate parasite in the United States to overwintering sites in a restricted area along the Gulf Coast. This temperature sensitivity of soybean rust hosts allowed us to study spatial spread of epidemic invasions over similar territory for seven sequential years, 2005-2011. The epidemic front expanded slowly from early April through July, with the majority of expansion occurring from August through November. There was a 7.4-fold range of final epidemic extent (0.4 to 3.0 million km) from the year of smallest final disease extent (2011) to that of the largest (2007). The final epidemic area of each year was regressed against epidemic areas recorded at one-week intervals to determine the association of final epidemic extent with current epidemic extent. Coefficients of determination for these regressions varied between 0.44 to 0.62 during April and May. The correlation coefficients varied between 0.70 and 0.96 from early June through October, and then increased monotonically to 1.0 by year's end. Thus, the spatial extent of disease when the epidemics began rapid expansion may have been a crucial contributor to subsequent spread of soybean rust. Our analyses used presence/absence data at the county level to evaluate the spread of the epidemic front only; the subsequent local intensification of disease could be strongly influenced by other factors, including weather.
大豆锈病的寄主对低温敏感，这使得这种专性寄生菌在美国仅限于墨西哥湾沿岸有限区域内越冬。大豆锈病寄主的这种温度敏感性使我们能够连续七年（2005年至2011年）研究类似区域内疫情入侵的空间扩散情况。疫情前沿从4月初到7月缓慢扩展，大部分扩展发生在8月到11月。从最终病害程度最小的年份（2011年）到最大的年份（2007年），最终疫情范围有7.4倍的差异（0.4至300万平方公里）。将每年的最终疫情面积与每周记录的疫情面积进行回归分析，以确定最终疫情范围与当前疫情范围之间的关联。在4月和5月期间，这些回归分析的决定系数在0.44至0.62之间变化。从6月初到10月，相关系数在0.70至0.96之间变化，然后在年底单调增加到1.0。因此，疫情开始快速扩展时疾病的空间范围可能是大豆锈病后续传播的关键因素。我们的分析仅使用县级的存在/不存在数据来评估疫情前沿的扩散；随后疾病的局部加剧可能受到其他因素的强烈影响，包括天气。
