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Monitoring the world's bird populations with community science data

机译:与社区科学数据监测世界鸟类群体

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Systematic monitoring of species across their geographic ranges is a critical part of conservation but it is resource-intensive, costly, and difficult to organize and maintain in the long-term. Large-scale community science programs like eBird may improve our ability to monitor bird populations, particularly in tropical regions where formal studies are lacking. Here, we estimated population trends for nearly 9000 bird species using global eBird birdwatching data and compared our trends to the population trends designated by BirdLife International. We calculated the rate of agreement between eBird and BirdLife trends and examined the effects of latitudinal affiliation, threat status, number of eBird checklists, eBird trend, BirdLife trend and BirdLife trend derivation on the rate of agreement. We also used a randomization approach to compare observed rates of agreement with the rates of agreement expected by chance alone. We show that the rate of agreement was marginally better than expected by chance and improved significantly for temperate region species of Least Concern with more checklists, and species that eBird or BirdLife identified as increasing. Our results suggest that eBird data are not currently adequate for monitoring populations of the majority of the world's bird species, especially in the developing world where systematic surveys are essential. Increased local participation in community science initiatives like eBird may improve our ability to effectively monitor species. Furthermore, it is important to assess the accuracy of BirdLife trends and the manner in which they are derived, especially for species where BirdLife and eBird data trends disagree.
机译:系统监测其地理范围的物种是保护的关键部分,但它是资源密集,昂贵,难以长期组织和维护。像赤裸裸的大规模社区科学节目可能会提高我们监控鸟类种群的能力,特别是在缺乏正式研究的热带地区。在这里,我们利用全球抗鸟类观察数据估计了近9000只鸟物种的人口趋势,并将我们的趋势与Birdlife International指定的人口趋势进行了比较。我们计算了乌尔鸟和鸟类趋势之间的一致性率,并研究了纬度联盟,威胁状态,乌伯尔清单,抗eir趋势,鸟类趋势趋势和鸟类趋势推导的影响。我们还使用随机化方法,比较观察到的协议率与偶然的协议税率。我们表明,协议率比偶然更好地优于预期,并对温带最不关心的温带,以及更多的清单,以及识别或鸟类的物种被确定为增加的物种。我们的研究结果表明,难以识别的数据目前没有足以监测世界大多数鸟类种群,特别是在系统调查至关重要的发展中国家。增加当地参与社区科学倡议,如赤裸裸,可能会改善我们有效监测物种的能力。此外,重要的是评估鸟类生命趋势的准确性以及它们所衍生的方式,特别是对于鸟类和欧洲数据趋势不同意的物种。

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