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The Allometry of Bee Proboscis Length and Its Uses in Ecology

机译:蜜蜂鼻长的异速生长及其在生态学中的应用

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摘要

Allometric relationships among morphological traits underlie important patterns in ecology. These relationships are often phylogenetically shared; thus quantifying allometric relationships may allow for estimating difficult-to-measure traits across species. One such trait, proboscis length in bees, is assumed to be important in structuring bee communities and plant-pollinator networks. However, it is difficult to measure and thus rarely included in ecological analyses. We measured intertegular distance (as a measure of body size) and proboscis length (glossa and prementum, both individually and combined) of 786 individual bees of 100 species across 5 of the 7 extant bee families (Hymenoptera: Apoidea: Anthophila). Using linear models and model selection, we determined which parameters provided the best estimate of proboscis length. We then used coefficients to estimate the relationship between intertegular distance and proboscis length, while also considering family. Using allometric equations with an estimation for a scaling coefficient between intertegular distance and proboscis length and coefficients for each family, we explain 91% of the variance in species-level means for bee proboscis length among bee species. However, within species, individual-level intertegular distance was a poor predictor of individual proboscis length. To make our findings easy to use, we created an R package that allows estimation of proboscis length for individual bee species by inputting only family and intertegular distance. The R package also calculates foraging distance and body mass based on previously published equations. Thus by considering both taxonomy and intertegular distance we enable accurate estimation of an ecologically and evolutionarily important trait.
机译:形态特征之间的异形关系是生态学中重要的模式。这些关系通常在系统发育上共享。因此,量化异形关系可以允许估计物种之间难以测量的性状。一种这样的特性,即蜜蜂的鼻长,被认为在构建蜜蜂群落和植物传粉媒介网络中很重要。但是,它很难测量,因此很少包含在生态分析中。我们测量了7个现存的蜜蜂家族中的5个物种(膜翅目:Apodea:Anthophila)中100种786头个体蜜蜂的椎间距离(作为衡量体形的大小)和长舌长度(光泽和舌前毛,单独和合并的)。使用线性模型和模型选择,我们确定了哪些参数提供了鼻长的最佳估计。然后,我们使用系数来估计椎间距离和长鼻之间的关系,同时还要考虑家庭。使用异位方程估算出齿间距离和象鼻长度之间的缩放系数以及每个科的系数,我们解释了蜜蜂物种中蜂象鼻长度的物种水平平均值的91%的变化。但是,在物种内,个体水平的齿间距离不能很好地预测个体长鼻的长度。为了使我们的发现易于使用,我们创建了一个R程序包,该程序包通过仅输入家族和间节距即可估算单个蜜蜂物种的鼻长。 R软件包还根据以前发布的方程式计算觅食距离和体重。因此,通过同时考虑分类法和节间距离,我们可以对生态和进化上重要的特征进行准确的估计。

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