five

Data from: Life-stage differences in spatial genetic structure in an irruptive forest insect: implications for dispersal and spatial synchrony

收藏
DataONE2014-12-03 更新2024-06-27 收录
下载链接:
https://search.dataone.org/view/null
下载链接
链接失效反馈
官方服务:
资源简介:
Dispersal determines the flux of individuals, energy, and information and is therefore a key determinant of ecological and evolutionary dynamics. Yet, it remains difficult to quantify its importance relative to other factors. This is particularly true in cyclic populations in which demography, drift, and dispersal contribute to spatio-temporal variability in genetic structure. Improved understanding of how dispersal influences spatial genetic structure is needed to disentangle the multiple processes that give rise to spatial synchrony in irruptive species. In this study, we examined spatial genetic structure in an economically important irruptive forest insect, the spruce budworm (Choristoneura fumiferana) to better characterize how dispersal, demography, and ecological context interact to influence spatial synchrony in a localized outbreak. We characterized spatial variation in microsatellite allele frequencies using 231 individuals and 7 geographic locations. We show that: (1) gene flow among populations is likely very high (Fst ≈ 0); (2) despite an overall low level of genetic structure, important differences exist between adult (moth) and juvenile (larvae) life-stages; and (3) the localized outbreak is the likely source of moths captured elsewhere in our study area. This study demonstrates the potential of using molecular methods to distinguish residents from migrants and for understanding how dispersal contributes to spatial synchronization. In irruptive populations, the strength of genetic structure depends on the timing of data collection (e.g., trough vs. peak), location, and dispersal. Taking into account this ecological context allows us to make more general characterizations of how dispersal can affect spatial synchrony in irruptive populations.
创建时间:
2014-12-03
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作