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Staying for food by urban birds: Insights from neural network analysis into adaptive strategies.

Previous work showed that animals have demonstrated remarkable adaptability by actively integrating into urban environments. However, there is no essential difference between urban and rural areas but food availability. The behavioral mechanisms and processes by which animals adapt to cities still r...

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Published in:Environmental Management Vol. 75; no. 4; pp. 896 - 906
Main Authors: Liu, Yuran, Wei, Yidong, Liu, Qiqi, Liang, Wei
Format: Journal Article
Published: Springer Nature Apr2025
Online Access:View this record in EBSCOhost
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      dt: Apr2025
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      pub: Springer Nature
      place: New York, New York
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        184191137
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        10.1007/s00267-025-02126-0
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        atl: Staying for food by urban birds: Insights from neural network analysis into adaptive strategies.
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          Liu, Yuran
          Wei, Yidong
          Liu, Qiqi
          Liang, Wei
        affil: https://ror.org/031dhcv14 Ministry of Education Key Laboratory for Ecology of Tropical Islands, Key Laboratory of Tropical Animal and Plant Ecology of Hainan Province, College of Life Sciences, Hainan Normal University, 571158, Haikou, China
      sug:
      ab: Previous work showed that animals have demonstrated remarkable adaptability by actively integrating into urban environments. However, there is no essential difference between urban and rural areas but food availability. The behavioral mechanisms and processes by which animals adapt to cities still require further experimental validation. In this study, field surveys of the flight initiation distance (FID) of black-headed gulls (Chroicocephalus ridibundus) were performed at three scenic sites in Kunming City, Yunnan, southwest China. Our results showed that, within the same area, the FID of black-headed gulls was significantly shorter in areas with increased human activity. Moreover, in areas with earlier human contact, black-headed gulls showed shorter FID. The FID data were further analyzed by a multilayer perceptron regression model with a neural network (ANN-MLP) approach to delineate FID thresholds for black-headed gulls in different human disturbance spots. The analysis revealed that black-headed gulls exhibit a high degree of behavioral flexibility in cities, with food availability playing a key role in increasing the birds' tolerance to humans. These findings highlight the significant impact of human behaviors, such as feeding, on wildlife behavior patterns. Understanding this mechanism is essential for understanding the coexistence of humans and wildlife. The establishment of FID models for black-headed gulls will provide new possibilities and tools for animal behavior research.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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