Using geolocator tracking data and ringing archives to validate citizen-science based seasonal predictions of bird distribution in a data-poor region
Using geolocator tracking data and ringing archives to validate citizen-science based seasonal predictions of bird distribution in a data-poor region
复制标题
DOI：
10.1016/j.gecco.2020.e01215
复制
发表时间：
2020-12-01
影响因子：
4
通讯作者：
Kamp, Johannes
中科院分区：
文献类型：
--
作者：
Heim, Wieland;Heim, Ramona J.;Kamp, Johannes
非结构化的公民科学数据越来越多地用于分析物种的丰度和分布。在这里，我们测试了这些数据在预测迁徙鸣禽的季节分布和分析迁徙连接模式方面的有用性。我们使用了来自eBird的鸟类发生数据，eBird是全球最大的公民科学数据库之一，预测了八种鸣禽分类群的全年分布（Agropsar philippensis，Calliope calliope，Cecropis daurica，Emberiza aureola，Hirundo rustica，Locustella certhiola，Oriolus chinensis，Saxicola torquatus stejnegeri），通过东亚迁徙，这是一个数据特别贫乏的地区，但对保护迁徙的陆地鸟类具有全球重要意义。建立了最大熵模型，预测春季中途停留、秋季中途停留和越冬面积。环恢复和geolocator跟踪数据，然后被用来评估，如何以及预测发生在一个给定的年度周期相匹配的网站，该物种是已知的是目前从振铃和跟踪data.Predicted冬季范围一般小于出版的范围发生地图（迄今为止唯一可用的分布信息来源）。在中途停留地区几乎没有重叠。从eBird数据预测为合适的区域和从地理定位器跟踪记录的区域之间的重叠在冬季较高，春季和秋季迁移较低。不到50%的振铃恢复来自季节性预测区域内的位置，秋季重叠最高。一个物种的季节范围大小影响的跟踪/振铃数据与预测的匹配。西伯利亚红喉燕和家燕的迁徙连接性很强。我们确定了两个迁移走廊，一个在中国大陆东部，一个沿着在太平洋的一个岛链。我们表明，不同的数据源的组合有很大的潜力，以获得更好地了解东部古北鸣禽的非繁殖分布和迁移连接。即使在偏远地区，公民科学观测数据也有助于预测迁徙物种的季节性分布，特别是在鸟类定居期间，并辅以跟踪数据。(C)2020年，任作家。由爱思唯尔公司出版
Unstructured citizen-science data are increasingly used for analysing the abundance and distribution of species. Here we test the usefulness of such data to predict the seasonal distribution of migratory songbirds, and to analyse patterns of migratory connectivity.We used bird occurrence data from eBird, one of the largest global citizen science databases, to predict the year-round distribution of eight songbird taxa (Agropsar philippensis, Calliope calliope, Cecropis daurica, Emberiza aureola, Hirundo rustica, Locustella certhiola, Oriolus chinensis, Saxicola torquatus stejnegeri) that migrate through East Asia, a region especially poor in data but globally important for the conservation of migratory land birds. Maximum entropy models were built to predict spring stopover, autumn stopover and wintering areas. Ring recovery and geolocator tracking data were then used to evaluate, how well the predicted occurrence at a given period of the annual cycle matched sites where the species were known to be present from ringing and tracking data.Predicted winter ranges were generally smaller than those on published extent-of-occurrence maps (the hitherto only available source of distribution information). There was little overlap in stopover regions. The overlap between areas predicted as suitable from the eBird data and areas that had records from geolocator tracking was high in winter, and lower for spring and autumn migration. Less than 50% of the ringing recoveries came from locations within the seasonal predicted areas, with the highest overlap in autumn. The seasonal range size of a species affected the matching of tracking/ringing data with the predictions. Strong migratory connectivity was evident in Siberian Rubythroats and Barn Swallows. We identified two migration corridors, one over the eastern mainland of China, and one along a chain of islands in the Pacific.We show that the combination of disparate data sources has great potential to gain a better understanding of the non-breeding distribution and migratory connectivity of Eastern Palearctic songbirds. Citizen-science observation data are useful even in remote areas to predict the seasonal distribution of migratory species, especially in periods when birds are sedentary and when supplemented with tracking data. (C) 2020 The Authors. Published by Elsevier B.V.