利用基于特征的预测模型确定鸟类对自由放养的家猫的脆弱性

IF 7 2区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES
Martin Philippe-Lesaffre, Elsa Bonnaud
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引用次数: 0

摘要

我们开发了一种方法,利用来自意大利和英国公民科学的猎物偏好数据来评估鸟类易受自由放养家猫(Felis catus)捕食的脆弱性。通过结合物种特征和地理范围,我们训练了随机森林模型来预测猎物偏好并识别缺失的猎物物种。我们的分析表明,将地理范围包括在内可显著提高模型的准确性并减少猎物可探测性问题。交叉验证证实,在一个国家训练的模型可以有效预测另一个国家的猎物偏好,从而实现更广泛的应用。沙普利加法解释值分析表明,手翅指数低、地域范围大的小型通食性鸟类最有可能被捕食。我们利用这些模型创建了美国鸟类物种的易损性列表,这些列表与之前的研究有一定程度的重叠,但一致性很高,突出了其稳健性。这些结果表明,这种方法可以用来提高我们对猫科动物捕食的认识,并为有针对性的保护战略提供信息,而更好的公民科学数据对于进一步改进至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pinpointing bird species vulnerability to free-ranging domestic cats using trait-based predictive models
We developed a method to assess bird species’ vulnerability to predation by free-ranging domestic cats (Felis catus) using prey preference data from citizen science in Italy and the United Kingdom. By combining species traits and geographical range, we trained random forest models to predict prey preferences and identify missing prey species. Our analysis showed that including the geographical range significantly improved model accuracy and reduced prey detectability issues. Cross-validation confirmed that models trained in one country could effectively predict prey preferences in another, allowing for broader application. Shapley additive explanations values analysis revealed that small, generalist birds with a low hand-wing index and large geographical range were most likely to be preyed upon. We used these models to create vulnerability lists for United States bird species, which showed moderate overlap but high consistency with previous studies, highlighting their robustness. These results showed that this method could thus be used to improve our understanding of cat predation and inform targeted conservation strategies, with better citizen science data being crucial for further improvements.
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来源期刊
Ecological Indicators
Ecological Indicators 环境科学-环境科学
CiteScore
11.80
自引率
8.70%
发文量
1163
审稿时长
78 days
期刊介绍: The ultimate aim of Ecological Indicators is to integrate the monitoring and assessment of ecological and environmental indicators with management practices. The journal provides a forum for the discussion of the applied scientific development and review of traditional indicator approaches as well as for theoretical, modelling and quantitative applications such as index development. Research into the following areas will be published. • All aspects of ecological and environmental indicators and indices. • New indicators, and new approaches and methods for indicator development, testing and use. • Development and modelling of indices, e.g. application of indicator suites across multiple scales and resources. • Analysis and research of resource, system- and scale-specific indicators. • Methods for integration of social and other valuation metrics for the production of scientifically rigorous and politically-relevant assessments using indicator-based monitoring and assessment programs. • How research indicators can be transformed into direct application for management purposes. • Broader assessment objectives and methods, e.g. biodiversity, biological integrity, and sustainability, through the use of indicators. • Resource-specific indicators such as landscape, agroecosystems, forests, wetlands, etc.
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