Predicting anthropogenic food supplementation from individual tracking data

IF 1.8 3区 生物学 Q1 ORNITHOLOGY
Ibis Pub Date : 2024-10-08 DOI:10.1111/ibi.13359
Steffen Oppel, Nathalie Heiniger, Patrick Scherler, Valentijn S. van Bergen, Jérôme Guélat, Robert Weibel, Martin U. Grüebler
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Abstract

Many wildlife species consume food or refuse provided by humans. To understand the effect of anthropogenic food subsidies on wildlife populations, we first need to quantify where and when individuals can access such food sources. The Red Kite Milvus milvus is an opportunistic raptor species and uses both inadvertent and deliberate food subsidies provided by citizens. Here we present a new approach using global positioning system (GPS)-tracking data to predict where anthropogenic food subsidies probably occur. We tracked 497 individuals with solar-powered GPS transmitters over an average of 3.2 (range 1–9) breeding seasons in Switzerland, and combined these data with locations of 125 known feeding sites obtained through interviews. We used two sequential random forest models, at both individual movement and population levels, to predict where anthropogenic food subsidies were attended by Red Kites. The first model classified locations that were frequently and regularly revisited, and successfully predicted 85% of locations that were within 50 m of an externally validated feeding site. These predicted locations were aggregated in 500-m grid cells to calculate the proportion of individuals and locations associated with predicted food subsidy. A second model related the presence of known food subsidies to the aggregated predictions. In our study area, 80% of known anthropogenic food provision locations could be correctly identified using Red Kite tracking data, but data sparsity beyond the core range of tracked individuals limits predictions of anthropogenic food subsidies at larger geographical scales. Nonetheless, biologging data can identify ephemeral food sources, and facilitate an assessment of the importance of anthropogenic food subsidies for the fitness of individuals in tracked populations.

Abstract Image

从个人跟踪数据预测人为食物补充
许多野生动物以人类提供的食物或垃圾为食。为了了解人为食物补贴对野生动物种群的影响,我们首先需要量化个体在何时何地可以获得这些食物来源。红鸢Milvus Milvus是一种投机取巧的猛禽物种,它利用市民无意和故意提供的食物补贴。本文提出了一种利用全球定位系统(GPS)跟踪数据预测人为粮食补贴可能发生地点的新方法。我们在瑞士平均3.2个(范围1-9)繁殖季节用太阳能GPS发射器跟踪了497只个体,并将这些数据与通过访谈获得的125个已知觅食地点的位置相结合。我们在个体移动和种群水平上使用了两个顺序随机森林模型来预测红鸢参与人为食物补贴的地方。第一个模型对频繁和定期重访的地点进行了分类,并成功预测了85%的外部验证喂食地点50米内的地点。这些预测的地点被聚集在500米的网格单元中,以计算与预测的粮食补贴相关的个人和地点的比例。第二个模型将已知食品补贴的存在与汇总预测联系起来。在我们的研究区域,使用红风筝跟踪数据可以正确识别80%的已知人为食品供应地点,但超出跟踪个体核心范围的数据稀疏性限制了在更大地理尺度上对人为食品补贴的预测。尽管如此,生物学数据可以识别短暂的食物来源,并有助于评估人为食物补贴对跟踪种群中个体健康的重要性。
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来源期刊
Ibis
Ibis 生物-鸟类学
CiteScore
4.60
自引率
9.50%
发文量
118
审稿时长
6-12 weeks
期刊介绍: IBIS publishes original papers, reviews, short communications and forum articles reflecting the forefront of international research activity in ornithological science, with special emphasis on the behaviour, ecology, evolution and conservation of birds. IBIS aims to publish as rapidly as is consistent with the requirements of peer-review and normal publishing constraints.
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