DataSheet2.PDF

Roads impact wildlife through a range of mechanisms from habitat loss and decreased landscape connectivity to direct mortality through wildlife-vehicle collisions (roadkill). These collisions have been rated amongst the highest modern risks to wildlife. With the development of “citizen science” projects, in which members of the public participate in data collection, it is now possible to monitor the impacts of roads over scales far beyond the limit of traditional studies. However, the reliability of data provided by citizen scientists for roadkill studies remains largely untested. This study used a dataset of 2,666 roadkill reports on national and regional roads in South Africa (total length ~170,000 km) over 3 years. We first compared roadkill data collected from trained road patrols operating on a major highway with data submitted by citizen scientists on the same road section (431 km). We found that despite minor differences, the broad spatial and taxonomic patterns were similar between trained reporters and untrained citizen scientists. We then compared data provided by two groups of citizen scientists across South Africa: (1) those working in the zoology/conservation sector (that we have termed “regular observers,” whose reports were considered to be more accurate due to their knowledge and experience), and (2) occasional observers, whose reports required verification by an expert. Again, there were few differences between the type of roadkill report provided by regular and occasional reporters; both types identified the same area (or cluster) where roadkill was reported most frequently. However, occasional observers tended to report charismatic and easily identifiable species more often than road patrols or regular observers. We conclude that citizen scientists can provide reliable data for roadkill studies when it comes to identifying general patterns and high-risk areas. Thus, citizen science has the potential to be a valuable tool for identifying potential roadkill hotspots and at-risk species across large spatial and temporal scales that are otherwise impractical and expensive when using standard data collection methodologies. This tool allows researchers to extract data and focus their efforts on potential areas and species of concern, with the ultimate goal of implementing effective roadkill-reduction measures.道路可通过多种机制对野生动物造成负面影响：从栖息地丧失、景观连通性下降，到野生动物-车辆碰撞（roadkill，道路致死）引发的直接死亡。此类碰撞已被列为当今野生动物面临的最高风险之一。随着“公民科学（citizen science）”项目的发展——公众成员可参与数据收集工作——如今已能够在远超传统研究范畴的尺度上，监测道路对野生动物的影响。然而，公民科学家所提供的道路致死研究数据，其可靠性在很大程度上仍未得到验证。本研究采用了南非全国及区域道路（总长度约17万公里）上3年间的2666份道路致死报告数据集。我们首先对比了在一条主要高速公路上执行任务的专业道路巡逻队采集的道路致死数据，与公民科学家在同一路段（431公里）提交的数据。结果显示，尽管存在细微差异，但专业记录者与非专业公民科学家所记录的整体空间分布与分类学格局均较为相似。随后，我们对比了南非境内两组公民科学家提交的数据：（1）动物学/保护领域从业者（我们将其称为“常规观测者”，因其具备专业知识与实践经验，其报告被认为准确性更高）；（2）临时观测者，其提交的报告需经专家验证。结果再次表明，常规观测者与临时观测者所提交的道路致死报告类型差异极小；两类群体均准确识别出了道路致死报告最为集中的区域（或集群）。不过，相较于道路巡逻队与常规观测者，临时观测者更倾向于报告具有标志性且易于识别的物种。我们认为，在识别整体格局与高风险区域方面，公民科学家能够为道路致死研究提供可靠的数据。因此，公民科学有望成为一种极具价值的工具，用于在大空间与时间尺度上识别潜在的道路致死热点区域与受威胁物种——而若采用标准数据收集方法，这类工作既不切实际且成本高昂。该工具可帮助研究人员提取有效数据，将精力集中于潜在的关注区域与物种，最终目标是制定有效的道路致死减缓措施。