Greenstone M H
Biological Control of Insects Research Laboratory, U.S.D.A., Agricultural Research Service, P.O. Box 7629, 65205, Columbia, MO, USA.
Oecologia. 1990 Sep;84(2):164-168. doi: 10.1007/BF00318267.
Spiders disperse by ballooning, a form of aeronautic behavior which they initiate by launching themselves into thermals. An attempt was made to define meteorological variables related to production and maintenance of thermals and use them as predictors of the number of aeronauts. Ballooning spiders were collected throughout a full growing season at an agricultural site and a native tall grass prairie 25 km distant, and numbers of ballooners were regressed against variables derived from meteorological data taken at locations near each site. The variables were the proportions of cloud cover and of possible sunshine, differences between maximum and minimum daily temperature (DT), wind speed, and a modification of the aeronautic index of Vugts and van Wingerden (1976). Ballooner numbers and meteorological variables used in the regressions were all weekly means. Significant one-step models were derived for both sites, but the addition of a second variable did not significantly increase the proportion of variation explained in either model. The modified aeronautic index explained 23% of the variation in ballooner numbers at the prairie site, while the proportion of possible sunshine explained 82% of the variation at the agricultural site. However the signs of the partial regression coefficients were contrary to expected. This may be due to the masking of short term meteorological and behavioral events by the averaging of meteorological variables and aeronaut numbers over a week. Alternatively it may indicate that the source of updrafts used by aeronauts may not always be thermals, but may sometimes be the vertical gradient in windspeed, a model which is consistent with the contrary signs of the regression coefficients.
蜘蛛通过随风飘荡进行扩散,这是一种航空行为,它们通过跃入上升热气流来启动这种行为。人们试图定义与上升热气流的产生和维持相关的气象变量,并将其用作航空蜘蛛数量的预测指标。在一个生长季节里,在一个农业用地和相距25公里的原生高草草原上收集随风飘荡的蜘蛛,并将航空蜘蛛的数量与从每个地点附近获取的气象数据得出的变量进行回归分析。这些变量包括云量比例、可能日照比例、日最高温度与最低温度之差(DT)、风速以及对武茨和范温格登(1976年)的航空指数的修正值。回归分析中使用的航空蜘蛛数量和气象变量均为每周平均值。两个地点都得出了显著的单步模型,但添加第二个变量并没有显著增加任何一个模型中所解释的变异比例。修正后的航空指数解释了草原地点航空蜘蛛数量变异的23%,而可能日照比例解释了农业用地变异的82%。然而,偏回归系数的符号与预期相反。这可能是由于气象变量和航空蜘蛛数量在一周内进行平均时掩盖了短期气象和行为事件。或者,这可能表明航空蜘蛛所利用的上升气流来源不一定总是上升热气流,有时可能是风速的垂直梯度,这一模型与回归系数的相反符号是一致的。