Source data for Paper 1 - EVALUATING METHODOLOGIES USED TO MONITOR WILDLIFE CROSSING STRUCTURES – A SYSTEMATIC REVIEW

(i) Abstract

Wildlife crossing structures are widely implemented to mitigate the detrimental effects of increasing road infrastructure. This global systematic review assessed the effectiveness of current research in evaluating the success of these structures in addressing both the immediate and long-term impacts of roads. The results indicate that despite 50 years of research, there is not enough evidence to reach definite conclusions. Many studies rely on single monitoring methods and prioritise wildlife movement over other critical measures such as population viability, genetic flow and collision reduction. Inconsistencies in definitions of effectiveness, along with lack of control sites and baseline data further limit comparability across studies. Additionally, short study durations and geographic bias of research towards the global north further limited fair evaluation. However, the increase in use of emerging technologies, particularly artificial intelligence, offers significant potential to improve monitoring practices. This review recommends prioritising the development and integration of these technologies alongside establishing standardising guidelines, encouraging global inclusivity and incorporating long-term monitoring.

(i) 摘要
野生动物通道（wildlife crossing structures）已被广泛布设，以缓解道路基础设施不断扩张所带来的不利影响。本项全球性系统综述对当前相关研究的有效性进行了评估，此类研究旨在评价此类通道在缓解道路即时与长期影响方面的实际成效。研究结果显示，尽管已有50年的研究积累，目前仍缺乏足够证据得出明确结论。诸多研究仅采用单一监测方法，且将野生动物通行活动作为优先评价对象，忽视了种群生存力、基因流以及碰撞事故减少等其他关键评价维度。有效性定义的不统一，加之缺乏对照样地与基准数据，进一步限制了不同研究之间的可比性。此外，研究周期过短以及研究区域偏向北半球的地理偏倚，进一步制约了公平合理的评价工作。不过，新兴技术的应用日渐增多，尤其是人工智能（Artificial Intelligence），为优化监测工作提供了显著潜力。本综述建议，应优先推动此类技术的开发与整合，同时制定标准化指南、倡导全球研究包容性，并将长期监测纳入研究框架。