基于MaxEnt模型分析广东省鸟类多样性热点分布及保护空缺

doi:10.17520/biods.2020229

生物多样性 ›› 2021, Vol. 29 ›› Issue (8): 1097-1107. DOI: 10.17520/biods.2020229

• 研究报告: 动物多样性 • 上一篇下一篇

基于MaxEnt模型分析广东省鸟类多样性热点分布及保护空缺

马星^1#, 王浩^1#, 余蔚³^,¹, 杜勇¹, 梁健超²^,^*(), 胡慧建²^,^*(), 邱胜荣⁴, 刘璐⁴

1.广东省城乡规划设计研究院, 广州 510290
2.广东省科学院动物研究所, 广东省动物保护与资源利用重点实验室, 广东省野生动物保护与利用公共实验室, 广州 510260
3.中山大学航空航天学院, 广州 510275
4.国家林业和草原局调查规划设计院, 北京 100714

收稿日期:2021-02-07 接受日期:2021-04-15 出版日期:2021-08-20 发布日期:2021-06-12
通讯作者: 梁健超,胡慧建
作者简介:13760813102@163.com (梁健超)
* E-mail: 13570909977@139.com (胡慧建);
第一联系人：
# 共同第一作者
基金资助:
广东省科技计划项目(2019B121202004);广东省科技计划项目;2019B121202003;广东省教育厅基础研究重点项目(2017KZDXM077)

Analysis on the hotspot and conservation gaps of bird biodiversity in Guangdong Province based on MaxEnt model

Xing Ma^1#, Hao Wang^1#, Wei Yu³^,¹, Yong Du¹, Jianchao Liang²^,^*(), Huijian Hu²^,^*(), Shengrong Qiu⁴, Lu Liu⁴

1 Urban and Rural Institution in Guangdong, Guangzhou 510290
2 Institute of Zoology, Guangdong Academy of Sciences, Guangdong Key Laboratory of Animal Conservation and Resource Utilization, Guangdong Public Laboratory of Wild Animal Conservation and Utilization, Guangzhou 510260
3 School of Aeronautics and Astronautics, Sun Yat-sen University, Guangzhou 510275
4 Survey & Planning Institute of State Forestry and Grassland Administration, Beijing 100714

Received:2021-02-07 Accepted:2021-04-15 Online:2021-08-20 Published:2021-06-12
Contact: Jianchao Liang,Huijian Hu
About author:First author contact:
# Co-first authors

摘要/Abstract

摘要：

随着环境问题日益突出, 生物多样性也面临着挑战。广东省丰富的水土资源孕育了大量的生物物种, 然而快速的城市扩张又对生物多样性的保护带来了一定的压力。明确广东省生物多样性保护空缺, 以便在未来城市规划布局中更好地实施保护, 缓解城市发展与生态保护之间的矛盾。空间分布格局是生物多样性保护规划的基础, 本文以全国第二次陆生野生动物资源调查鸟类数据为基础, 基于MaxEnt模型进行空间化(空间分辨率为100 m × 100 m), 通过识别热点地区, 并与现有国土规划中三条管控线对比, 识别保护空缺。本文主要有以下结果: (1)广东省建模鸟类共有13目45科173种, 其空间丰富度格局主要呈三片区分布: ①南岭片区; ②粤东片区; ③江门、阳江、云浮片区; (2)影响鸟类空间格局的环境因子在不同物种间差异明显, 总体来看土地利用类型、高程、年均温度差等因素占主导地位; (3)保护鸟类与全部鸟类的热点地区分布相似, 但空间上更为聚集, 两者的空间重叠率达63.0%, 主要分布于南岭片区、粤东片区; (4)留鸟类和迁徙鸟类的热点地区存在明显空间差异, 重叠区域仅25.3%, 留鸟类分布相对靠北而迁徙鸟类相对趋南; (5)鸟类热点分区统计对比中, 与永久基本农田的重叠率明显高于生态保护红线, 极少量分布于城镇开发边界内部, 全部鸟类、保护鸟类、留鸟类、迁徙鸟类均存在明显的保护空缺。本研究得到了精细尺度下鸟类多样性空间分布格局与保护空缺结果, 为城镇开发边界、永久基本农田、生态保护红线三条控制线内的生物多样性分区保护、管控政策实施提供了有效支撑, 为广东省的生物多样性保护、生态规划调整提供了有益参考。

关键词: 广东省, 鸟类多样性, MaxEnt模型, 热点地区, 保护空缺, 生态保护红线, 留鸟, 迁徙鸟

Abstract

Aims: With the increasingly prominent environmental problems, biodiversity is at risk. While the rich soil and water resources in Guangdong Province, China, have given rise to a large number of species, the rapid urban expansion of the Pearl River Delta has challenged protecting biodiversity. Our goal in this study was to evaluate biodiversity conservation in Guangdong Province to better inform future urban planning so that is compatible with the protection of biodiversity and minimizes conflict between development and conservation.

Methods: We used bird spatial distribution data from the second terrestrial wildlife resources survey in China to create habitat suitability models using MaxEnt at high spatial resolution (100 m × 100 m). We then identified protection gaps by determining the locations of biodiversity hotspots that we compared to the ecological red line, permanent basic farmland and urban development boundary in existing urban plans.

Results: We recorded 173 species of birds belonging to 45 families and 13 orders in Guangdong Province. Regions with high species richness were mainly distributed in three areas: Nanling, Eastern Guangdong, and Jiangmen-Yangjiang-Yunfu. The environmental factors affecting the bird richness patterns significantly differed among species. In general, land use, altitude, and annual average temperature difference were dominant factors. The spatial locations of hotspots of protected birds were similar to those of all birds, with a spatial overlap rate of 63.0%. The overlap was mainly distributed in Nanling and Eastern Guangdong. By contrast, we found large apparent differences between hotspot locations of resident and migratory birds, which overlapped by only 25.3%. Most resident birds were distributed relatively close to the north, while most migratory birds tended towards the south. The overlap of hotspots with permanent basic farmland was significantly higher than the ecological red line. Only a small portion of the hotspots were distributed within the urban development boundary. Altogether, we found obvious protection gaps for all groups of birds we considered.

Conclusions: Our high-resolution bird richness maps enabled a critical evaluation of where biodiversity hotspots conflict with urban developments. Our results provide urgent support for the implementation of biodiversity zoning protection and the development of management policies within the three control lines of the urban development boundary, permanent basic farmland, and ecological red line. Ultimately, our results provide a useful reference and roadmap for biodiversity protection and ecological planning adjustment in Guangdong Province.

Key words: Guangdong Province, bird diversity, MaxEnt model, hotspot, conservation vacancies, ecological red line, resident birds, migratory birds

马星, 王浩, 余蔚, 杜勇, 梁健超, 胡慧建, 邱胜荣, 刘璐 (2021) 基于MaxEnt模型分析广东省鸟类多样性热点分布及保护空缺. 生物多样性, 29, 1097-1107. DOI: 10.17520/biods.2020229.

Xing Ma, Hao Wang, Wei Yu, Yong Du, Jianchao Liang, Huijian Hu, Shengrong Qiu, Lu Liu (2021) Analysis on the hotspot and conservation gaps of bird biodiversity in Guangdong Province based on MaxEnt model. Biodiversity Science, 29, 1097-1107. DOI: 10.17520/biods.2020229.

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链接本文: https://www.biodiversity-science.net/CN/10.17520/biods.2020229

https://www.biodiversity-science.net/CN/Y2021/V29/I8/1097

图/表 7

图1 研究区域与调查样区、样线分布

Fig. 1 Study area and the distribution of sample area and line transect

表1 用于物种分布模型的环境因子

Table 1 Environmental factors used in species distribution models

环境因子 Environmental factors	缩写 Abbreviation	单位 Unit
高程 Altitude	ALT	m
年均降水量 Annual precipitation	AP	mm
年均温 Annual mean temperature	AMT	℃
年均湿度 Annual mean humidity	AMH	%
年均温度差 Annual average temperature difference	AMTD	℃
土地利用类型 Land use	LU	/
归一化植被指数 Normalized difference vegetation index	NDVI	/
人口密度 Population density	PD	人/km²
距离城镇距离 Distance from urban land	DUL	m
距离水源距离 Distance from water	DW	m

图2 影响鸟类分布的环境因子。a: 高程; b: 年均降水量; c: 年均温; d: 年均湿度; e: 年均温度差; f: 土地利用类型; g: 归一化植被指数; h: 人口密度; i: 距离城镇距离; j: 距离水源距离。

Fig. 2 Environmental factors affecting the distribution of birds. a, Altitude; b, Annual precipitation; c, Annual mean temperature; d, Annual mean humidity; e, Annual average temperature difference; f, Land use; g, Normalized difference vegetation index; h, Population density; i, Distance from urban land; j, Distance from water.

图3 环境因子的平均贡献度。缩写含义见表1。

Fig. 3 Contribution rate of environmental factors. See Table 1 for abbreviations.

图4 广东省全部鸟类(a)、保护鸟类(b)、留鸟类(c)、迁徙鸟类(d)多样性空间分布格局

Fig. 4 Spatial patterns of all birds (a), protected birds (b), resident birds (c), migratory birds (d) biodiversity in Guangdong Province

表2 鸟类热点地区与生态保护红线、永久基本农田和城镇开发边界的空间关系

Table 2 The relationship between species richness and the ecological red line, permanent basic farmland and the urban development boundary

		生态保护红线 Ecological red line	永久基本农田 Permanent basic farmland	城镇开发边界 Urban development boundary	“三线”之外 Outside the three lines
全部鸟类 All birds	相交面积 Intersecting areas (km²)	1,618.79	4,009.49	24.01	8,258.52
全部鸟类 All birds	热点地区占比 Proportion (%)	11.6	28.8	0.2	59.4
保护鸟类 Protected birds	相交面积 Intersecting areas (km²)	218.44	1,880.32	65.95	2,618.58
保护鸟类 Protected birds	热点地区占比 Proportion (%)	4.6	39.3	1.4	54.8
留鸟类 Resident birds	相交面积 Intersecting areas (km²)	1,776.68	2,856.25	3.17	6,654.16
留鸟类 Resident birds	热点地区占比 Proportion (%)	15.7	25.3	0.1	59.0
迁徙鸟类 Migratory birds	相交面积 Intersecting areas (km²)	445.13	3,103.25	210.07	5,872.09
迁徙鸟类 Migratory birds	热点地区占比 Proportion (%)	4.6	32.2	2.2	61.0

图5 全部鸟类(a)、保护鸟类(b)、留鸟类(c)、迁徙鸟类(d)与生态保护红线、城镇开发边界、永久基本农田的空间关系

Fig. 5 The spatial relationship between all birds (a), protected birds (b), resident birds (c), migratory birds (d) and ecological red line, urban development boundary and permanent basic farmland

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基于MaxEnt模型分析广东省鸟类多样性热点分布及保护空缺

Analysis on the hotspot and conservation gaps of bird biodiversity in Guangdong Province based on MaxEnt model

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