Conservation Science Group, Department of Zoology, University of Cambridge, The David Attenborough Building, Pembroke Street, Cambridge, CB2 3QZ, UK.
Centre for the Study of Existential Risk, University of Cambridge, 16 Mill Lane, Cambridge, CB2 1SG, UK.
Nature. 2018 Jan 11;553(7687):199-202. doi: 10.1038/nature25139. Epub 2017 Dec 20.
Understanding global patterns of biodiversity change is crucial for conservation research, policies and practices. However, for most ecosystems, the lack of systematically collected data at a global level limits our understanding of biodiversity changes and their local-scale drivers. Here we address this challenge by focusing on wetlands, which are among the most biodiverse and productive of any environments and which provide essential ecosystem services, but are also amongst the most seriously threatened ecosystems. Using birds as an indicator taxon of wetland biodiversity, we model time-series abundance data for 461 waterbird species at 25,769 survey sites across the globe. We show that the strongest predictor of changes in waterbird abundance, and of conservation efforts having beneficial effects, is the effective governance of a country. In areas in which governance is on average less effective, such as western and central Asia, sub-Saharan Africa and South America, waterbird declines are particularly pronounced; a higher protected area coverage of wetland environments facilitates waterbird increases, but only in countries with more effective governance. Our findings highlight that sociopolitical instability can lead to biodiversity loss and undermine the benefit of existing conservation efforts, such as the expansion of protected area coverage. Furthermore, data deficiencies in areas with less effective governance could lead to underestimations of the extent of the current biodiversity crisis.
了解全球生物多样性变化格局对于保护研究、政策和实践至关重要。然而，对于大多数生态系统而言，由于缺乏全球范围内系统收集的数据，我们对生物多样性变化及其局部驱动因素的理解受到限制。在这里，我们关注湿地，湿地是生物多样性和生产力最高的环境之一，提供了重要的生态系统服务，但也是受到严重威胁的生态系统之一。我们使用鸟类作为湿地生物多样性的指示分类群，对全球 25769 个调查点的 461 种水鸟的时间序列丰度数据进行建模。我们发现，水鸟丰度变化的最强预测因子，以及保护工作产生有益效果的最强预测因子，是一个国家的有效治理。在治理平均效果较差的地区，如西亚和中亚、撒哈拉以南非洲和南美洲，水鸟的减少尤为明显；湿地环境的保护区覆盖率较高有助于水鸟数量的增加，但这仅在治理效果更好的国家中成立。我们的研究结果表明，社会政治不稳定可能导致生物多样性丧失，并破坏现有保护工作的效益，例如保护区覆盖范围的扩大。此外，治理效果较差地区的数据不足可能导致对当前生物多样性危机程度的低估。
