首页分享公众科学对中国鸟类物种多样性研究的贡献: 基于“鸟网”图库数据计量

公众科学对中国鸟类物种多样性研究的贡献: 基于“鸟网”图库数据计量

来源：萌宠菠菠乐园时间：2025-05-11 12:48

摘要:

公民科学能从广阔的时空尺度中获得丰富的物种信息，在生物多样性监测与持续变化研究中显得越来越重要，对全球生物多样性指标量化起到至关重要的作用。为了解中国各省份鸟种记录现状、公众贡献力、受限因素以及未来变化趋势变化，系统检索和提取了“鸟网”的鸟类照片信息，整理了各省份鸟种数与公众贡献力情况，采用累积曲线和多元线性回归方法了解公众参与数量与贡献力现状及未来变化趋势，分析了公众贡献力的相关影响因素。结果表明：具有地理信息记录的鸟类共计1 310种。在省级行政区划上，云南省鸟种记录最为丰富(813)，宁夏回族自治区鸟种记录最为匮乏(65)。在地理区域上，西南地区鸟种记录丰富度最高，各省份平均记录493种；西北地区鸟种记录丰富度最低，各省份平均记录300种。通过80/20定律分割，在照片数、记录地点和物种贡献度上，前20%观鸟者远远高于后80%观鸟者，前20%观鸟者贡献的照片数量是后者的2.2倍，占照片总数的68.98%。累积曲线显示，2018年后鸟种记录变为一条渐近线，表明鸟种数接近饱和，已记录到绝大部分中国鸟类。随时间累积观鸟者数量持续增长，未来会不断有新观鸟者加入，并且新涉足乡镇会持续增加。各省份鸟类照片数与纬度、国内生产总值(GDP)、森林覆盖率和鸟种数呈显著正相关，其中地区鸟种数是吸引观鸟者拍摄记录的主要因素。总体上，公民科学在提供关于中国鸟类物种多样性和地理分布数据方面起到重要作用，随着公众参与数量和贡献力的持续上升，未来将有更多公众为我国鸟类学相关研究提供分布数据。

关键词: 鸟类 / 公民科学 / 物种多样性

Abstract:

Citizen science (CS) generates much information over wide geographical areas and extended time scales. CS has grown increasingly important in biodiversity monitoring and sustainable change research, where it is critical in assessing global biodiversity indicators and achieving the United Nations′ sustainable development goals. This study systematically collected photographic information submitted to BirdNET (http://www.birdnet.cn) concerning birds spotted in Chinese provinces. The goals were to (1) determine the number and diversity of birds recorded by the public in each province, (2) comprehend the scope of public contributions, (3) forecast future trends in public contributions, and (4) understand the limiting factors that affect public participation. The number of species and public contributions were collated by province. Cumulative curves and multiple linear regression were used to analyze participation, contributions, future trends, and relevant factors. There were 1 310 species of birds identified using geographical information. At the provincial level, Yunnan Province had the most diverse species (813), and the Ningxia Hui Autonomous Region had the fewest (65). Geographically, the highest number of species was observed in the southwest, with an average of 493 species per province. The lowest number was observed in the northwest, averaging 300 per province. Applying the 80/20 law, the 20% high-ranking bird watchers provided much more photographs, locations, and species contributions than the other 80% (for example, contributing 68.98% of all photographs). The cumulative curve of species observations neared the asymptote after 2018, indicating that the record is close to saturation (the vast majority of Chinese birds have been recorded). The number of bird watchers will continue to increase as more individuals participate and the number of locations increases. The contributions of bird watchers are significantly and positively correlated with the latitude, GDP, forest coverage, and bird species diversity of the provinces. The local species diversity is the main factor attracting bird watchers. Despite the late start and low level of participation in bird-watching activities in China, the number of participants continues to rise, providing increasing amounts of data for ornithological studies that will play an important role in understanding bird species composition and population distribution in China.

图 1 多元线性回归模型的变量筛选与模型构建

E为经度；SM为省域面积；PM为保护区面积；PS为保护地数量；SL为森林面积；FGL为森林覆盖率；SP为省域鸟种数；PE为人口数；N为纬度；GDP为国内生产总值。

Figure 1. Variable screening and model construction of multiple linear regression model

图 2 各省份鸟类物种数和占比

Figure 2. Number and proportion of bird species in each province

图 3 观鸟者对鸟类物种多样性调查的贡献度

A指贡献度为前20%的观鸟者；B指贡献度为后80%的观鸟者。

Figure 3. Contribution of birdwatchers to the survey on bird species diversity

图 4 乡镇记录点、观鸟者和鸟类物种的时间累积曲线

Figure 4. Time cumulative curves of township record points, photographers, and bird species

图 5 省域鸟类照片数的影响因素

Figure 5. Factors affecting the number of bird photos in the provinces

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