Department of Agro-Ecology, Rothamsted Research, Harpenden, Hertfordshire, United Kingdom.
PLoS One. 2013;8(1):e54202. doi: 10.1371/journal.pone.0054202. Epub 2013 Jan 24.
Insect migration needs to be quantified if spatial and temporal patterns in populations are to be resolved. Yet so little ecology is understood above the flight boundary layer (i.e. >10 m) where in north-west Europe an estimated 3 billion insects km(-1) month(-1) comprising pests, beneficial insects and other species that contribute to biodiversity use the atmosphere to migrate. Consequently, we elucidate meteorological mechanisms principally related to wind speed and temperature that drive variation in daytime aerial density and insect displacements speeds with increasing altitude (150-1200 m above ground level). We derived average aerial densities and displacement speeds of 1.7 million insects in the daytime convective atmospheric boundary layer using vertical-looking entomological radars. We first studied patterns of insect aerial densities and displacements speeds over a decade and linked these with average temperatures and wind velocities from a numerical weather prediction model. Generalized linear mixed models showed that average insect densities decline with increasing wind speed and increase with increasing temperatures and that the relationship between displacement speed and density was negative. We then sought to derive how general these patterns were over space using a paired site approach in which the relationship between sites was examined using simple linear regression. Both average speeds and densities were predicted remotely from a site over 100 km away, although insect densities were much noisier due to local 'spiking'. By late morning and afternoon when insects are migrating in a well-developed convective atmosphere at high altitude, they become much more difficult to predict remotely than during the early morning and at lower altitudes. Overall, our findings suggest that predicting migrating insects at altitude at distances of ≈ 100 km is promising, but additional radars are needed to parameterise spatial covariance.
如果要解决种群的时空格局，就需要对昆虫的迁移进行量化。然而，在飞行边界层（即 >10 m）以上，人们对生态学的了解还很少，在欧洲西北部，估计有 30 亿只昆虫/公里/月，其中包括害虫、有益昆虫和其他有助于生物多样性的物种，它们利用大气进行迁移。因此，我们阐明了与风速和温度主要相关的气象机制，这些机制驱动着日间空中密度和昆虫位移速度随海拔高度（距地面 150-1200 米）的增加而变化。我们使用垂直昆虫雷达得出了白天对流层大气边界层中 170 万只昆虫的平均空中密度和位移速度。我们首先研究了昆虫空中密度和位移速度的模式超过十年，并将这些模式与数值天气预报模型中的平均温度和风速联系起来。广义线性混合模型表明，平均昆虫密度随风速的增加而下降，随温度的增加而增加，而位移速度与密度之间的关系是负相关的。然后，我们试图通过配对站点的方法来研究这些模式在空间上的一般性，在这种方法中，使用简单的线性回归来检查站点之间的关系。平均速度和密度都可以从 100 公里以外的站点远程预测，尽管由于局部“峰值”，昆虫密度的噪声要大得多。到了上午晚些时候和下午，当昆虫在高空高度发达的对流层中迁移时，它们比清晨和较低高度时更难以远程预测。总的来说，我们的研究结果表明，在距离约 100 公里的高空远距离预测迁移昆虫是有希望的，但需要额外的雷达来参数化空间协方差。
