城市道路特征及自然景观对动物路杀的影响: 以南京为例

doi:10.17520/biods.2024141

生物多样性 ›› 2024, Vol. 32 ›› Issue (8): 24141. DOI: 10.17520/biods.2024141 cstr: 32101.14.biods.2024141

城市道路特征及自然景观对动物路杀的影响: 以南京为例

吴琼^,^#, 赵梓羲^,^#, 孙桃柱, 赵雨梦(), 于丛, 祝芹^*()(), 李忠秋()

南京大学生命科学学院动物行为与保护实验室, 南京 210046

收稿日期:2024-04-12 接受日期:2024-08-14 出版日期:2024-08-20 发布日期:2024-08-30
通讯作者: *E-mail: qinzhu@nju.edu.cn
作者简介:^#共同第一作者
基金资助:
国家自然科学基金(32101237)

Impact of urban road characteristics and natural landscapes on animal vehicle collisions: A case study in Nanjing

Qiong Wu^,^#, Zixi Zhao^,^#, Taozhu Sun, Yumeng Zhao(), Cong Yu, Qin Zhu^*()(), Zhongqiu Li()

Laboratory of Animal Behavior and Conservation, School of Life Sciences, Nanjing University, Nanjing 210046, China

Received:2024-04-12 Accepted:2024-08-14 Online:2024-08-20 Published:2024-08-30
Contact: *E-mail: qinzhu@nju.edu.cn
About author:^#Co-first authors
Supported by:
National Natural Science Foundation of China(32101237)

1. 附录.pdf(155KB)

摘要/Abstract

摘要：

随着道路网络的快速扩张, 交通发展和生态保护的矛盾日益严重, 并逐渐受到生态学家的关注。道路网络的扩张导致动物栖息地破碎化和种群间的交流减少, 严重威胁生物多样性; 而道路交通所造成的动物道路死亡(即路杀), 是道路对动物最直接且最重要的影响。本研究以华东地区的特大城市南京市为例, 于2020年11月至2021年10月, 采用样线法对其不同行政等级道路的动物路杀情况进行调查, 使用回归分析探究路杀事件的发生概率, 并建立动物路杀探究模型, 以进一步明确道路及其周边环境因素对动物路杀发生概率的影响。结果表明: (1)调查期间共记录到21种293只路杀动物。其中兽类136只, 占比46.42%, 以猫(Felis catus)和狗(Canis lupus familiaris)最为常见; 鸟类143只, 占比48.81%, 以乌鸫(Turdus mandarinus)和麻雀(Passer montanus)最为常见。(2)自然景观特征中的耕地(旱作农田及灌溉农田)及建筑(建筑物及构筑物)的面积占比影响路杀事件的发生几率。道路周围250 m范围内, 耕地和建筑的面积占比与动物路杀的发生概率呈显著负相关关系: 其中, 随耕地面积占比的增加, 鸟类的路杀发生概率降低, 而兽类的路杀发生概率升高。(3)道路特征影响动物路杀事件的发生几率: 当道路中有隔离带时, 路杀事件的几率增加。(4)线性特征(到最近河流距离、到最近高架桥距离、到最近主干道距离)影响鸟类路杀的发生概率: 离河流越远, 鸟类相关的路杀事件越少; 而离高架桥及主干道越远, 鸟类相关的路杀事件则越多。本研究明确了南京市动物路杀的自然景观和道路特征影响因素, 相关结果可为区域内路网优化、道路升级改造、生态廊道建设和管护等提供实践性的科学依据。

关键词: 动物路杀, 鸟类, 兽类, 影响因素

Abstract

Aims: With the rapid expansion of road networks, the conflict between transportation development and ecological conservation has become increasingly prominent, garnering significant attention from ecologists. Research on road ecology has indicated that roads can fragment animal habitats, reduce connectivity between populations, and severely impact biodiversity. Among these impacts, animal vehicle collisions (i.e., roadkill) represent the most direct and significant threat to wildlife.

Methods: This research investigated the incidence of animal vehicle collisions in Nanjing, a mega city in East China. From November 2020 to October 2021, transect survey method was employed to investigate roadkill incidents across roads of different administrative levels in Nanjing. Regression analysis was used to explore the probability of roadkill incidents, and models were established to further clarify the impact of roads and surrounding environmental factors on the probability of animal roadkill.

Results: Our findings revealed that: (1) A total of 293 roadkill incidents involving 21 species were recorded during the survey period. Mammals accounted for 46.42% of the incidents, with cats (Felis catus) and dogs (Canis lupus familiaris) being the most common, while birds accounted for 48.81%, with the Chinese Blackbird (Turdus mandarinus) and Eurasian Tree Sparrow (Passer montanus) being predominant. (2) The proportion of arable land (dryland and irrigated farmland) and buildings (buildings and structures) in natural landscape significantly influenced the probability of roadkill incidents. Specifically, within a 250 m radius around the road, the coverage proportion of arable land and buildings was significantly negatively correlated with the occurrence probability of roadkill incidents. As cultivated land coverage increased, the probability of roadkill of birds decreased, while the probability of mammals’ roadkill increased, showed completely opposite trends. (3) The road characteristic affected the probability of animal vehicle collisions; roads with isolation belts were associated with an increased probability of roadkill incidents. (4) Linear features (distance to the nearest river, the nearest viaduct and the nearest main road) also affected the incidence of bird’s roadkill events. Birds had fewer vehicle collisions the farther they were from rivers, but more collisions while the farther they were from viaducts and main roads.

Conclusion: This study represents the first periodic investigation into terrestrial vertebrate roadkill in Nanjing. It preliminarily identifies the natural landscape and road factors that influence animal roadkill in Nanjing, thereby providing foundational knowledge to inform strategic decisions regarding regional road network optimization, infrastructure enhancements, ecological corridor establishment, and management strategies.

Key words: animal vehicle collisions, birds, mammals, influence factors

吴琼, 赵梓羲, 孙桃柱, 赵雨梦, 于丛, 祝芹, 李忠秋 (2024) 城市道路特征及自然景观对动物路杀的影响: 以南京为例. 生物多样性, 32, 24141. DOI: 10.17520/biods.2024141.

Qiong Wu, Zixi Zhao, Taozhu Sun, Yumeng Zhao, Cong Yu, Qin Zhu, Zhongqiu Li (2024) Impact of urban road characteristics and natural landscapes on animal vehicle collisions: A case study in Nanjing. Biodiversity Science, 32, 24141. DOI: 10.17520/biods.2024141.

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链接本文: https://www.biodiversity-science.net/CN/10.17520/biods.2024141

https://www.biodiversity-science.net/CN/Y2024/V32/I8/24141

图/表 5

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响应变量 Response variable	自变量类别 Independent variable category	所选模型 Selected model
每个取样单元内动物/鸟类/兽类路杀事件数量 Number of animal/bird/mammal roadkill incidents in each sampling unit	自然景观 Natural landscape	250 m缓冲区内耕地面积占比 + 250 m缓冲区内建筑面积占比 + 250 m缓冲区内林地面积占比 + 500 m缓冲区内草地面积占比 + 1,000 m缓冲区内草地面积占比 + 1,000 m缓冲区内林地面积占比+ 1,000 m缓冲区内耕地面积占比+ 1,000 m缓冲区内建筑面积占比 + (1 \| 取样单元所在调查样线) P_farm250 + P_build250 + P_forest250 + P_grass500 + P_grass1000 + P_forest1000 + P_farm1000 + P_build1000 + (1 \| ID)
	道路特征 Road features	海拔高度 + 道路曲折度+ 取样单元道路长度 + 车道数目 + 道路最高限速 + 道路隔离带 + 道路类型+ (1 \| 取样单元所在调查样线) Ele + Sinu + Length + Lane + Speed + Iso + Roadtype + (1 \| ID)
	线性特征 Linear features	到最近河流(线状水体)的距离 + 到最近湖泊湿地(面状水体)的距离 + 到最近高架桥的距离 + 到最近城市次干道的距离 + 到最近城市主干道的距离 + 到最近道路的距离+ (1 \| 取样单元所在调查样线) D_river + D_lake + D_trunk + D_subarte + D_arte + D_road + (1 \| ID)

响应变量 Response variable	自变量类别 Independent variable category	所选模型 Selected model
每个取样单元内动物/鸟类/兽类路杀事件数量 Number of animal/bird/mammal roadkill incidents in each sampling unit	自然景观 Natural landscape	250 m缓冲区内耕地面积占比 + 250 m缓冲区内建筑面积占比 + 250 m缓冲区内林地面积占比 + 500 m缓冲区内草地面积占比 + 1,000 m缓冲区内草地面积占比 + 1,000 m缓冲区内林地面积占比+ 1,000 m缓冲区内耕地面积占比+ 1,000 m缓冲区内建筑面积占比 + (1 \| 取样单元所在调查样线) P_farm250 + P_build250 + P_forest250 + P_grass500 + P_grass1000 + P_forest1000 + P_farm1000 + P_build1000 + (1 \| ID)
	道路特征 Road features	海拔高度 + 道路曲折度+ 取样单元道路长度 + 车道数目 + 道路最高限速 + 道路隔离带 + 道路类型+ (1 \| 取样单元所在调查样线) Ele + Sinu + Length + Lane + Speed + Iso + Roadtype + (1 \| ID)
	线性特征 Linear features	到最近河流(线状水体)的距离 + 到最近湖泊湿地(面状水体)的距离 + 到最近高架桥的距离 + 到最近城市次干道的距离 + 到最近城市主干道的距离 + 到最近道路的距离+ (1 \| 取样单元所在调查样线) D_river + D_lake + D_trunk + D_subarte + D_arte + D_road + (1 \| ID)

因变量 Dependent variable	所选模型 Selected model	自然景观变量的AIC AIC of natural landscape variables	道路特征变量的AIC AIC of road features variables	线性特征变量的AIC AIC of linear features variables
动物路杀事件 Animal vehicle collisions	负二项式模型 Negative binomial model	1,107.89	1,120.00	1,100.22
	广义线性混合模型 Generalized linear mixed model	1,194.70	1,227.10	1,162.42
	零膨胀负二项式模型 Zero expansion negative binomial model	1,110.33	1,120.01	1,092.97
鸟类路杀事件 Bird vehicle collisions	负二项式模型 Negative binomial model	693.23	717.34	690.89
	广义线性混合模型 Generalized linear mixed model	723.70	762.30	717.96
	零膨胀负二项式模型 Zero expansion negative binomial model	703.63	717.37	694.33
兽类路杀事件 Mammal vehicle collisions	负二项式模型 Negative binomial model	791.21	789.37	787.95
	广义线性混合模型 Generalized linear mixed model	848.50	843.60	827.92
	零膨胀负二项式模型 Zero expansion negative binomial model	794.04	789.40	780.92

因变量 Dependent variable	所选模型 Selected model	自然景观变量的AIC AIC of natural landscape variables	道路特征变量的AIC AIC of road features variables	线性特征变量的AIC AIC of linear features variables
动物路杀事件 Animal vehicle collisions	负二项式模型 Negative binomial model	1,107.89	1,120.00	1,100.22
	广义线性混合模型 Generalized linear mixed model	1,194.70	1,227.10	1,162.42
	零膨胀负二项式模型 Zero expansion negative binomial model	1,110.33	1,120.01	1,092.97
鸟类路杀事件 Bird vehicle collisions	负二项式模型 Negative binomial model	693.23	717.34	690.89
	广义线性混合模型 Generalized linear mixed model	723.70	762.30	717.96
	零膨胀负二项式模型 Zero expansion negative binomial model	703.63	717.37	694.33
兽类路杀事件 Mammal vehicle collisions	负二项式模型 Negative binomial model	791.21	789.37	787.95
	广义线性混合模型 Generalized linear mixed model	848.50	843.60	827.92
	零膨胀负二项式模型 Zero expansion negative binomial model	794.04	789.40	780.92

因变量 Dependent variable	解释变量 Explanatory variable	参数估计 Parameter estimation	标准误 Standard error	P值 P value
动物路杀事件 Animal vehicle collisions	截距 Intercept	‒0.203	0.138	0.141
	P_farm250	‒0.240	0.082	0.003^**
	P_build250	‒0.219	0.063	< 0.001^***
	P_farm1000	0.236	0.052	< 0.001^***
	Iso1	0.223	0.154	1.452
鸟类路杀事件 Bird vehicle collisions	截距 Intercept	‒1.560	0.252	< 0.001^***
	P_build250	‒0.303	0.100	0.002^**
	P_farm1000	0.272	0.087	0.002^**
	Iso1	0.547	0.227	0.016^*
	D_river	‒0.545	0.144	< 0.001^***
	D_trunk	0.285	0.143	0.046^*
	D_arte	0.462	0.094	< 0.001^***
兽类路杀事件 Mammal vehicle collisions	截距 Intercept	‒0.832	0.163	< 0.001^***
兽类路杀事件 Mammal vehicle collisions	P_farm250	‒0.201	0.103	0.051

城市道路特征及自然景观对动物路杀的影响: 以南京为例

Impact of urban road characteristics and natural landscapes on animal vehicle collisions: A case study in Nanjing

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