首尔北汉山国立公园野猪(Sus scrofa)的栖息地模型

Q2 Social Sciences Journal of Urban Ecology Pub Date : 2022-01-01 DOI:10.1093/jue/juac027
Ohsun Lee, P. Schlichting, Yeong-Seok Jo
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引用次数: 0

摘要

自2004年首次发现野猪后,在首尔频繁出现野猪,导致人类与野生动物之间的冲突不断增加。虽然韩国将野猪指定为“有害”物种,但关于该国最大的野生哺乳动物的栖息地偏好和使用的生态信息有限。基于213个存在点对首尔北汉山国立公园野猪栖息地偏好进行建模,并对模型进行验证。利用MaxEnt软件,利用最大熵建模算法对25个栅格数据集进行野猪分布分析。对生境模型贡献最大的因子是坡度(23.4%),其次是温度季节性(20.4%)和森林类型(16.9%),最干季降水(37.6%)是模型最重要的(归一化贡献),其次是温度季节性(18.9%)和坡度(15.4%)。模型的现场验证证实,在MaxEnt值高(大于0.7)的地区,公猪的标志和生根密度是公猪的两倍。野猪的栖息地模型将有助于栖息地管理,并进一步了解如何减轻人类与野猪的冲突。
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Habitat model for wild boar (Sus scrofa) in Bukhansan National Park, Seoul
Since the first known sighting in 2004, wild boar have frequently appeared in Seoul causing increased human–wildlife conflicts. Although South Korea designated wild boar as a ‘pest’ species, limited ecological information exists concerning habitat preference and use of the largest wild mammal in the country. Based on 213 presence points, we modeled wild boar habitat preference in Bukhansan National Park, Seoul and validated the model. We analyzed boar presence with 25 raster datasets using MaxEnt, software for species distribution model using maximum entropy modeling algorithm. Slope (23.4%) was the greatest contributing factor for the habitat model, followed by Temperature seasonality (20.4%) and forest type (16.9%), while Precipitation of driest quarter (37.6%) was the most important factor (normalized contribution) of the model, followed by Temperature seasonality (18.9%) and slope (15.4%). Field verification of the model confirmed that the density of boar signs and rooting are twice as high in the area with high MaxEnt values (over 0.7). The habitat model of wild boar will assist habitat management and further our understanding of how to mitigate human–wild boar conflict.
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来源期刊
Journal of Urban Ecology
Journal of Urban Ecology Social Sciences-Urban Studies
CiteScore
4.50
自引率
0.00%
发文量
14
审稿时长
15 weeks
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