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The quality and contribution of volunteer collected animal vehicle collision data in ecological research

机译:志愿者收集的动物车辆碰撞数据在生态研究中的质量和贡献

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Volunteer-collected data are increasingly important for research, and the accuracy and applications of such data needs evaluation. We utilized the California Roadkill Observation System (CROS) to assess the quality of and potential contribution that volunteer-collected animal-vehicle collision (AVC) data to understand species ranges. We classified volunteers as professional biologists or non-professional users, and compared their rates of species observation and identification accuracy. Seventeen percent of the volunteers were professionals, but they provided 35% of the observations, and they observed a more diverse set of species than non-professionals. The accuracy of species identification was similar for both groups. We compared species' ranges estimated from CROS data with ranges derived from the largest available database of animal observations (Global Biodiversity Information Facility; GBIF). CROS observations expanded GBIF data-derived ranges for 139 of 411 species. Average range expansion was 8.2% for all species, including species with no range expansion, or 24.3% for species with range expansion. We also used species distribution models to estimate range sizes. Adding CROS observations to GBIF records expanded the average predicted species-range by 5%. Professional observers expanded previously-estimated ranges by an average of 1.1%, while non-professional observers expanded ranges by an average of 5.3%, reflecting their larger spatial coverage. While non-professional users observe fewer species, their larger number of observations and occurrence over a larger area improves our knowledge of the ranges of a number of species. Volunteer-collected AVC data from both professional and non-professional users can be an important data source for augmenting conventional databases of wildlife observations to create species range maps.
机译:志愿人员收集的数据对于研究越来越重要,需要评估此类数据的准确性和应用。我们利用加利福尼亚道路杀伤观察系统(CROS)评估了自愿收集的动物-车辆碰撞(AVC)数据的质量和潜在贡献,以了解物种范围。我们将志愿者分类为专业生物学家或非专业用户,并比较了他们的物种观察和识别准确率。 17%的志愿者是专业人士,但是他们提供了35%的观察结果,并且他们观察到的物种比非专业人员更多。两组的物种识别准确性相似。我们将根据CROS数据估算的物种范围与从最大的动物观察数据库(全球生物多样性信息基金; GBIF)得出的范围进行了比较。 CROS观测扩大了GBIF数据衍生的范围,涵盖411个物种中的139个。所有物种的平均范围扩展为8.2%,包括没有范围扩展的物种,或范围扩展的物种为24.3%。我们还使用物种分布模型来估计范围大小。在GBIF记录中添加CROS观测值可使平均预测物种范围扩大了5%。专业观察员将以前估计的范围平均扩大了1.1%,而非专业观察员将范围平均扩大了5.3%,反映了他们更大的空间覆盖范围。尽管非专业用户观察到的物种较少,但他们的观察次数增多且在更大的区域内发生,提高了我们对许多物种范围的了解。来自专业用户和非专业用户的志愿者收集的AVC数据可以成为重要的数据源,用于扩充野生动植物观测的常规数据库以创建物种范围图。

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