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Capturing Spatiotemporal Patterns in Presence-Absence Data to Inform Monitoring and Sampling Designs for the Threatened Dakota Skipper (Lepidoptera: Hesperiidae) in the Great Plains of the United States
Environmental Entomology ( IF 1.8 ) Pub Date : 2020-08-14 , DOI: 10.1093/ee/nvaa081
Max Post van der Burg 1 , Jane E Austin 1 , Mark T Wiltermuth 1 , Wesley Newton 1 , Garrett MacDonald 1
Affiliation  

Abstract Declines among species of insect pollinators, especially butterflies, has garnered attention from scientists and managers. Often these declines have spurred governments to declare some species as threatened or endangered. We used existing presence–absence data from surveys for the threatened Dakota skipper Hesperia dacotae (Skinner) to build statistical maps of species presence that could be used to inform future monitoring designs. We developed a hierarchical Bayesian modeling approach to estimate the spatial distribution and temporal trend in Dakota skipper probability of presence. Our model included a spatial random effect and fixed effects for the proportion of two grassland habitat types: those on well-drained soils and those on poorly drained soils; as well as the topographic slope. The results from this model were then used to assess sampling strategies with two different monitoring objectives: locating new Dakota skipper colonies or monitoring the proportion of historically (pre-2000) extant colonies. Our modeling results suggested that the distribution of Dakota skippers followed the distribution of remnant grasslands and that probabilities of presence tended to be higher in topographically diverse grasslands with well-drained soils. Our analysis also showed that the probability of presence declined throughout the northern Great Plains range. Our simulations of the different sampling designs suggested that new detections were expected when sampling where Dakota skippers likely occurred historically, but this may lead to a tradeoff with monitoring existing sites. Prior information about the extant sites may help to ameliorate this tradeoff.

中文翻译:

捕获存在-不存在数据中的时空模式,为美国大平原受威胁的达科他鲣(鳞翅目:Hesperiidae)的监测和采样设计提供信息

摘要 授粉昆虫物种,尤其是蝴蝶的数量减少,引起了科学家和管理者的关注。通常,这些下降促使政府宣布某些物种受到威胁或濒临灭绝。我们使用来自受威胁的达科他州船长 Hesperia dacotae (Skinner) 调查的现有存在-不存在数据来构建物种存在的统计地图,可用于为未来的监测设计提供信息。我们开发了一种分层贝叶斯建模方法来估计达科他州船长存在概率的空间分布和时间趋势。我们的模型包括两种草地栖息地类型比例的空间随机效应和固定效应:排水良好的土壤和排水不良的土壤;以及地形坡度。然后使用该模型的结果来评估具有两个不同监测目标的采样策略:定位新的达科他州船长菌落或监测历史上(2000 年之前)现存菌落的比例。我们的建模结果表明,达科他州船长的分布遵循残余草原的分布,并且在具有排水良好的土壤的地形多样的草原中,存在的概率往往更高。我们的分析还表明,存在于整个大平原北部地区的可能性都在下降。我们对不同采样设计的模拟表明,在历史上可能发生达科他州船长的地方进行采样时,预计会出现新的检测结果,但这可能会导致与监控现有站点的权衡。
更新日期:2020-08-14
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