Sezione di Biodiversità Tropicale, MUSE-Museo delle Scienze, Trento, Italy.
Moore Center for Science, Conservation International, Washington DC, USA.
Sci Total Environ. 2017 Jan 1;574:914-923. doi: 10.1016/j.scitotenv.2016.09.146. Epub 2016 Oct 14.
While there are well established early warning systems for a number of natural phenomena (e.g. earthquakes, catastrophic fires, tsunamis), we do not have an early warning system for biodiversity. Yet, we are losing species at an unprecedented rate, and this especially occurs in tropical rainforests, the biologically richest but most eroded biome on earth. Unfortunately, there is a chronic gap in standardized and pan-tropical data in tropical forests, affecting our capacity to monitor changes and anticipate future scenarios. The Tropical Ecology, Assessment and Monitoring (TEAM) Network was established to contribute addressing this issue, as it generates real time data to monitor long-term trends in tropical biodiversity and guide conservation practice. We present the Network and focus primarily on the Terrestrial Vertebrates protocol, that uses systematic camera trapping to detect forest mammals and birds, and secondarily on the Zone of Interaction protocol, that measures changes in the anthroposphere around the core monitoring area. With over 3 million images so far recorded, and managed using advanced information technology, TEAM has created the most important data set on tropical forest mammals globally. We provide examples of site-specific and global analyses that, combined with data on anthropogenic disturbance collected in the larger ecosystem where monitoring sites are, allowed us to understand the drivers of changes of target species and communities in space and time. We discuss the potential of this system as a candidate model towards setting up an early warning system that can effectively anticipate changes in coupled human-natural system, trigger management actions, and hence decrease the gap between research and management responses. In turn, TEAM produces robust biodiversity indicators that meet the requirements set by global policies such as the Aichi Biodiversity Targets. Standardization in data collection and public sharing of data in near real time are essential features of such system.
虽然已经有一些成熟的早期预警系统可用于预测多种自然现象（例如地震、灾难性火灾、海啸），但我们尚未建立针对生物多样性的早期预警系统。然而，我们正在以前所未有的速度失去物种，而这种情况尤其发生在热带雨林中，这是地球上生物多样性最丰富但受侵蚀最严重的生物群落。不幸的是，由于热带森林缺乏标准化和泛热带数据，我们监测变化和预测未来情景的能力受到了影响。热带生态、评估和监测 (TEAM) 网络的建立旨在解决这个问题，因为它生成实时数据来监测热带生物多样性的长期趋势并指导保护实践。我们介绍了该网络，并主要关注陆地脊椎动物协议，该协议使用系统相机陷阱来检测森林哺乳动物和鸟类，其次是交互区协议，该协议测量核心监测区域周围的人类活动区的变化。到目前为止，该网络已经记录了超过 300 万张图像，并使用先进的信息技术进行管理，它创建了全球最重要的热带森林哺乳动物数据集。我们提供了一些特定地点和全球分析的示例，这些示例结合了在监测点所在的更大生态系统中收集的人为干扰数据，使我们能够了解目标物种和群落在空间和时间上变化的驱动因素。我们讨论了该系统作为建立能够有效预测耦合人类-自然系统变化、触发管理行动的早期预警系统的候选模型的潜力，从而减少研究和管理响应之间的差距。反过来，TEAM 生成了符合全球政策（如爱知生物多样性目标）要求的强大生物多样性指标。数据收集的标准化和数据在接近实时的情况下的公开共享是该系统的重要特征。
