Occupancy monitoring of the New England cottontail (Sylvilagus transitionalis) relies on collections of fecal pellets made following a snowfall, and subsequent genetic screening to distinguish New England cottontail pellets from those of the eastern cottontail (S. floridanus) and snowshoe hare (Lepus americanus). In years when snowy conditions are not common, less frequent sampling may result in data gaps at long‐term monitoring sites, and jeopardize ongoing field research projects that rely on genetic data from fecal pellets. Such conditions occurred in the lower Hudson Valley, New York, USA, in the winter of 2015–2016, during which we collected pellets from the ground to evaluate performance of genetic testing relative to pellet quality. Pellets were categorized on overall appearance of degradation, assigned a pellet quality score, and then genetically analyzed to identify species using mitochondrial DNA. The pellets identified as being from New England cottontail were further evaluated targeting nuclear microsatellite DNA to obtain a multilocus genotype to identify individual rabbits. Species identification was possible for 89% of the highest quality pellets from the ground, and 68% in the most degraded pellets. A complete multilocus genotype was obtained in 79% of the least degraded pellets, but only 14% of the most degraded pellets. Certain genetic loci strongly influenced this success rate, with some performing better than others. Pellets collected from snow were still most reliable with 100% identified to species, and >97% of New England cottontail with a complete multilocus genotype. Thus, if researchers are genotyping rabbit pellets for applications such as abundance estimations, only the higher quality pellets from the ground or those collected from snow will likely be useful. For occupancy monitoring, a wider range of pellets may be acceptable for species identification, with the understanding that there is a tradeoff with pellet quality and successful DNA analysis. These results indicate that sampling from the ground and qualitative assessment of pellet quality using our categorization scheme is a viable method for New England cottontail monitoring in years with less snow. © 2020 The Wildlife Society.

中文翻译：

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次优条件下收集的棉尾药丸用于DNA分析的评估

对新英格兰棉尾虫（Sylvilagus transitionalis）的占用情况监测依赖于降雪后收集的粪便颗粒，然后进行基因筛选，以区分新英格兰棉尾虫颗粒物与东部棉尾虫（S. floridanus）和雪兔（Lepus americanus））。在下雪天不常见的年份，较少的采样频率可能会导致长期监测站点的数据空白，并危及正在进行的依赖粪便颗粒遗传数据的实地研究项目。这种情况发生在2015-2016年冬天的美国纽约哈德逊河谷下游，在此期间，我们从地面上收集了颗粒，以评估相对于颗粒质量的基因测试性能。根据降解的整体外观对药丸进行分类，分配药丸质量得分，然后使用线粒体DNA进行遗传分析以鉴定物种。鉴定出的来自新英格兰棉尾的小球进一步评估了靶向核微卫星DNA的多基因座基因型，以鉴定出个别兔子。可以从地面上鉴定出质量最高的颗粒的89％，最降解的颗粒中的68％进行物种鉴定。降解程度最低的颗粒中有79％获得了完整的多基因座基因型，降解程度最高的颗粒中只有14％获得了完整的基因座基因型。某些基因位点对成功率产生了很大的影响，其中一些表现要好于其他。从雪中收集的丸粒仍然是最可靠的，已鉴定出100％的物种，并且> 97％的新英格兰棉尾有完整的多基因座基因型。因此，如果研究人员对兔子颗粒进行基因分型以用于诸如丰度估算之类的应用，则只有从地面或从雪中收集到的更高质量的颗粒才有用。为了进行占用率监控，可以使用更大范围的颗粒来进行物种识别，在了解颗粒质量和成功的DNA分析之间需要权衡取舍。这些结果表明，从地面采样和使用我们的分类方案对颗粒质量进行定性评估是在降雪较少的年份进行新英格兰棉尾监测的可行方法。©2020野生动物协会。