基于取食行为探究北京居民区鸟类的食源特征及多样性

doi:10.17520/biods.2022473

生物多样性 ›› 2023, Vol. 31 ›› Issue (5): 22473. DOI: 10.17520/biods.2022473

• 研究报告: 动物多样性 • 上一篇下一篇

基于取食行为探究北京居民区鸟类的食源特征及多样性

殷鲁秦¹^,², 王成¹^,²^,^*(), 韩文静¹^,²

1.中国林业科学研究院林业研究所, 北京 100091
2.国家林业和草原局城市森林研究中心, 北京 100091

收稿日期:2022-08-18 接受日期:2022-11-15 出版日期:2023-05-20 发布日期:2023-01-01
通讯作者: * E-mail: wch8361@163.com
基金资助:
中央级公益性科研院所基本科研业务费专项资金(CAFYBB2022SY006)

Food source characteristics and diversity of birds based on feeding behavior in residential areas of Beijing

Luqin Yin¹^,², Cheng Wang¹^,²^,^*(), Wenjing Han¹^,²

1. Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091
2. Urban Forest Research Center, National Forestry and Grassland Administration, Beijing 100091

Received:2022-08-18 Accepted:2022-11-15 Online:2023-05-20 Published:2023-01-01
Contact: * E-mail: wch8361@163.com

摘要/Abstract

摘要：

城市是鸟类的重要栖息地, 城市绿地中占比最大的为居住绿地, 是容纳鸟类的重要生境。对于鸟类生存来说, 食物的种类和数量是关键的限制因子。本研究从鸟类的食物偏好入手, 旨在构建北京居住区鸟类的食源关系, 探究鸟类在居住区中取食的影响因素。研究选取40个居住小区作为调查样地, 于2020年6月至2021年5月每月调查1次, 采用广义线性模型评估鸟类在居住区中取食的影响因素, 并对鸟类的食源多样性指数与多度、分布范围进行线性回归。结果表明: (1)本研究共记录到取食行为的鸟种共14科35种2,242只, 丰富度为春季 > 秋季 > 冬季 > 夏季, 多度为春季 > 冬季 > 秋季 > 夏季, Shannon-Wiener多样性指数为秋季 > 春季 > 冬季 > 夏季。(2)鸟类的食源依次为昆虫(33.87%)、翅果(18.33%)、浆果(9.77%)、球果(8.16%)、草籽(5.17%)等。(3)鸟类对植物的直接利用高达60.4%, 间接利用为39.6%, 食源植物Shannon-Wiener多样性指数为秋季(3.1612) > 冬季(2.9651) > 春季(2.9203) > 夏季(2.1763)。(4)食源树种是影响鸟类在居住区中取食最关键的外界环境因素, 食源越丰富的鸟种, 其种群数量越大, 分布范围越广泛。居住区的食源植物具有类型丰富、种类繁多、从早春到晚秋覆盖全物候的特点, 在规划设计时应多配置北京乡土树种以及金银木(Lonicera maackii)等观果植物, 减少绿篱配置, 倡导低干扰的近自然园林养护管理措施。

关键词: 鸟类食性, 居住区, 食物来源, 食源植物, 鸟类多样性, 北京

Abstract

Aims: Urban areas can provide important habitats for birds. Residential green spaces can play an important role in urban green spaces and may provide valuable resources for urban birds. Food diversity and quantity can be one of the factors that could be limiting bird survival. Therefore, by considering the food preferences of birds, this study aims to determine the relationship between birds and their food sources in Beijing residential areas. Furthermore, this study seeks to determine what factors may influence bird feeding behavior in residential areas.
Methods: Forty residential areas were selected as survey plots and surveyed monthly from June 2020 to May 2021. Shannon-Wiener diversity index was used for evaluating bird diversity, and the distribution was defined as the numbers of residential areas where birds fed. A generalized linear model was used to evaluate the influencing factors of bird feeding in residential areas, and linear regression was performed on the diversity index, abundance and the distribution of bird feeding sources.
Results: (1) The feeding behavior of 2,242 birds (35 species, 14 families) were recorded. We observed that bird richness was at its highest in spring, followed by autumn, winter and summer, then abundance was at its highest in spring, followed by winter, autumn and summer, and the Shannon-Wiener diversity index was at its highest in autumn, followed by spring, winter, summer. (2) A decrease in food sources was observed in the following: insects (33.87%), samara (18.33%), berries (9.77%), cones (8.16%) and grass seeds (5.17%). (3) The direct utilization of plants by birds was 60.4%, while the indirect utilization was 39.6%. The Shannon-Wiener diversity index of food source plants decreased in autumn (3.1612), winter (2.9651), spring (2.9203) and summer (2.1763). (4) The species of food source was the most critical environmental factor that determined birds feeding behavior in residential areas. Birds with more abundant food sources had larger populations and wider distribution ranges.
Conclusion: Plant species in residential areas can be highly diverse and can offer a wide range of food sources for multiple species of birds throughout their entire phenology between the early spring and autumn. It is necessary to plant more native tree species and fruiting plants, reduce hedgerows, and advocate near-natural management measures with low disturbance.

Key words: bird diet, residential area, food source, food source plant, bird diversity, Beijing

殷鲁秦, 王成, 韩文静 (2023) 基于取食行为探究北京居民区鸟类的食源特征及多样性. 生物多样性, 31, 22473. DOI: 10.17520/biods.2022473.

Luqin Yin, Cheng Wang, Wenjing Han (2023) Food source characteristics and diversity of birds based on feeding behavior in residential areas of Beijing. Biodiversity Science, 31, 22473. DOI: 10.17520/biods.2022473.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.biodiversity-science.net/CN/10.17520/biods.2022473

https://www.biodiversity-science.net/CN/Y2023/V31/I5/22473

图/表 10

图1 研究点位置分布图

Fig. 1 Distribution of study sites

图2 北京居住区鸟类食源关系图。图中的数字表示取食行为频次。

Fig. 2 Relationship between birds and food sources in residential areas of Beijing. The number indicates the feeding frequency.

图3 北京居住区不同季节鸟类食源关系图。图中的数字表示取食行为频次。

Fig. 3 Relationship between birds and food sources in residential areas of Beijing in different seasons. The number indicates the feeding frequency.

图4 不同季节不同类型食物的取食频次

Fig. 4 Feeding frequency of different food types in different seasons

表1 北京居住区不同季节食源植物、鸟类的Bray-Curtis相似性系数

Table 1 Bray-Curtis similarity coefficients of food source plants or birds during different seasons in residential areas of Beijing

季节 Season	食源植物 Food source plant			鸟类 Bird
季节 Season	夏季 Summer	秋季 Autumn	冬季 Winter	夏季 Summer	秋季 Autumn	冬季 Winter
春季 Spring	0.0738	0.4725	0.4655	0.1389	0.5756	0.4789
夏季 Summer		0.1524	0.1115		0.2641	0.2027
秋季 Autumn			0.4291			0.4789

图5 不同季节鸟类对不同生活型植物的利用方式关系图。图中的数字刻度表示取食行为的频次。

Fig. 5 Plant utilization of different life forms by birds in different seasons. The numerical scale in the figure indicates the feeding frequency.

表2 基于取食行为的鸟类多样性与环境因子的模型选择

Table 2 Model selection relating bird diversity based on feeding behavior and environmental factors

响应变量 Response variables	模型 Model	自由度 df	ΔAICc	权重 Weight	R²
物种丰富度 Species richness	CFST + SFST	3	0	0.1518	0.5729
	CFST + SFST + PAR	4	0.0188	0.1504	0.5936
	CFST + SFST + CY	4	1.2920	0.0796	0.5786
	CFST + SFST + AREA	4	1.3209	0.0784	0.5692
物种密度 Species density	CFST	3	0	0.1447	0.2352
	CFST + SFST	4	0.5466	0.1101	0.2516
	CFST + SFST + AREA	5	1.7703	0.0597	0.2572
Shannon-Wiener多样性指数 Shannon-Wiener diversity index	CFST + SFST	4	0	0.1129	0.2516
	CFST + SFST + CY	5	0.9647	0.0697	0.2516
	SFST	3	1.1036	0.0650	0.0358
	CFST + SFST + PAR	5	1.2596	0.0601	0.2431
	CFST + SFST + CY	5	1.9831	0.0419	0.2431
	CFST + SFST + BD	6	1.9843	0.0419	0.2253

表3 基于取食行为的鸟类多样性与环境因子平均模型的参数估计

Table 3 Parameter estimation of the average model relating bird diversity based on feeding behavior to environmental factors

响应变量 Response variables	环境因子 Environmental factors	参数估计 Estimate	标准误 SE	P
物种丰富度 Species richness	CFST	0.3885	0.1141	< 0.001***
	SFST	0.5979	0.1749	< 0.001***
	PAR	-0.0918	0.1684	0.5909
	CY	0.0227	0.0707	0.7528
	AREA	0.0248	0.0776	0.7538
物种密度 Species density	CFST	8.9247	2.5447	< 0.001***
	SFST	2.1968	2.9115	0.4577
	AREA	-0.6399	1.8525	0.7342
Shannon-Wiener多样性指数 Shannon-Wiener diversity index	CFST	0.2340	0.1696	0.1768
	SFST	0.5013	0.1594	0.0023**
	CY	0.0322	0.0928	0.7326
	PAR	-0.0665	0.1527	0.6672
	AREA	0.0138	0.0681	0.8434
	BD	0.0282	0.1034	0.7877

图6 基于取食行为的北京居住区鸟种排序图。图中数字表示前10位的取食地点, 椭圆表示95%的置信区间。1: 元宝枫; 2: 国槐; 3: 草地; 4: 榆树; 5: 绦柳; 6: 白蜡; 7: 裸土地; 8: 侧柏; 9: 重瓣粉海棠; 10: 栾树。

Fig. 6 Ranking map of bird species based on feeding behavior in residential areas of Beijing. Number indicates top 10 feeding sites, and ovals indicate 95% confidence intervals. 1, Acer truncatum; 2, Styphnolobium japonicum; 3, Lawn; 4, Ulmus pumila; 5, Salix matsudana ?Pendula?; 6, Fraxinus chinensis; 7, Bare land; 8, Platycladus orientalis; 9, Malus spectabilis var. riversii; 10, Koelreuteria paniculata.

图7 北京居住区鸟类多度(A)、分布小区数(B)与食源多样性指数的线性回归。灰色区域表示拟合线的置信区间。

Fig. 7 Relationship between bird abundance (A), number of residential areas (B) and Shannon-Wiener diversity index of food source in residential areas of Beijing. Gray areas indicate confidence intervals for the fitted lines.

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基于取食行为探究北京居民区鸟类的食源特征及多样性

Food source characteristics and diversity of birds based on feeding behavior in residential areas of Beijing

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