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Using opportunistic citizen science data to estimate avian population trends

机译:使用机会主义公民科学数据来估算禽类趋势

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Determining population trends is critical for conservation. For most bird species, trends are based on count data gathered by institutions with formalized survey protocols. However, limited resources may prevent these types of surveys, especially in developing countries. Ecotourism growth and subsequent increases in opportunistic data from birdwatching can provide a source of population trend information if analyses control for inter-observer variation. List length analysis (LLA) controls for such variation by using the number of species recorded as a proxy for observer skill and effort. Here, we use LLA on opportunistic data gathered by eBird to estimate population trends for 574 North American bird species (48% of species declining) and compare these estimates to population trends based on 1) formal breeding bird surveys (54% of species declining) and 2) population estimates from eBird data controlled using more rigorous correction (46% of species declining). Our analyses show that eBird data produce population trends that differ on average by only 0.4%/year from formal surveys and do not differ significantly from estimates using more control metrics. We find that estimates do not improve appreciably beyond 10,000 checklists, suggesting this as the minimum threshold of opportunistic data required for population trend estimation. Lastly, we show that characteristics affecting a species' ubiquity, such as geographic and elevational range, can affect its population trend estimate. Our results suggest that opportunistic data can be used to approximate species population trends, especially for widespread species. Because our protocol uses information present in all checklists, it can be applied to a diversity of data sources including eBird, trip reports, and bird atlases.
机译:确定人口趋势对于保护至关重要。对于大多数鸟类,趋势基于由机构收集的计数数据,具有正式的调查协议。然而,有限的资源可能会阻止这些类型的调查,特别是在发展中国家。鸟类观察的生态旅游增长和随后的机会数据增加,如果分析对观察者间变异的控制,则可以提供人口趋势信息的来源。列出长度分析(LLA)通过使用被记录为观察者技能和努力的代理的物种数量来控制这种变化的控制。在这里,我们使用LLA通过欧洲核实收集的机会数据,以估算574个北美鸟类(48%的物种下降)的人口趋势,并将这些估计与1)正式育种鸟调查(54%的物种下降54%)进行比较人口趋势2)使用更严格的校正(46%的物种下降)控制的人口估计来自抗抗抗核实数据。我们的分析表明,难以识别的数据产生人口趋势,平均只有0.4%/年度从正式调查中的每年不同,并且没有使用更多控制指标的估计值。我们发现,估计不会显着提高10,000个清单,这表明这是人口趋势估计所需的机会主义数据的最小阈值。最后,我们表明影响物种的特色,例如地理和高度范围,可以影响其人口趋势估算。我们的结果表明,机会主义数据可用于近似物种人口趋势,特别是对于广泛的物种。由于我们的协议使用所有清单中存在的信息,因此它可以应用于包括识别,旅行报告和鸟atlases的数据来源的多样性。

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