香港马鞍山基于三种被动式采集方法采集的甲虫标本数据集

doi:10.17520/biods.2023021

生物多样性 ›› 2023, Vol. 31 ›› Issue (7): 23021. DOI: 10.17520/biods.2023021 cstr: 32101.14.biods.2023021

所属专题：数据论文；数据论文

香港马鞍山基于三种被动式采集方法采集的甲虫标本数据集

申昊¹^,², 佟一杰², 赵淑哲³, 韩永金¹, 史晓旭³, 滕备²^,⁴, 王新谱¹^,^*(), 白明¹^,²^,⁵^,^*()

1.宁夏大学农学院, 银川 750021
2.中国科学院动物研究所动物进化与系统学重点实验室, 北京 100101
3.河北农业大学植物保护学院, 河北保定 071001
4.河北大学生命科学学院, 河北保定 071028
5.海南省崖州湾种子实验室, 海南三亚 572025

收稿日期:2023-01-31 接受日期:2023-04-23 出版日期:2023-07-20 发布日期:2023-07-12
通讯作者: *E-mail: baim@ioz.ac.cn; wangxinpu@nxu.edu.cn
作者简介:wangxinpu@nxu.edu.cn
*E-mail: baim@ioz.ac.cn;
基金资助:
国家重点研发计划(2022YFC2601200);国家科技基础资源调查专项(2022FY100500);国家科技基础资源调查专项(2022FY202100);国家自然科学基金(32200354)

A photographic dataset of the beetle specimens by three passive acquisition methods in Ma On Shan, Hong Kong

Hao Shen¹^,², Yijie Tong², Shuzhe Zhao³, Yongjin Han¹, Xiaoxu Shi³, Bei Teng²^,⁴, Xinpu Wang¹^,^*(), Ming Bai¹^,²^,⁵^,^*()

1. School of Agriculture, Ningxia University, Yinchuan 750021
2. Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101
3. College of Plant Protection, Hebei Agricultural University, Baoding, Hebei 071001
4. School of Life Sciences, Hebei University, Baoding, Hebei 071028
5. Hainan Yazhou Bay Seed Laboratory, Sanya, Hainan 572025;Database/Dataset Profile

Received:2023-01-31 Accepted:2023-04-23 Online:2023-07-20 Published:2023-07-12
Contact: *E-mail: baim@ioz.ac.cn; wangxinpu@nxu.edu.cn

摘要/Abstract

摘要：

本文提供了2017年5月27日至6月17日通过3种被动采集方法(飞行阻隔器法、马氏网法和埋罐法)在中国香港马鞍山郊野公园样地采集到的甲虫标本信息, 并生成了1个数据集。该样地包含13个样点, 每个样点的采集设备由1个飞行阻隔器、1个马氏网和10个埋罐组成, 共收集到45科325种3,011头甲虫。该数据集由5个部分组成: (1)每个样点采集的甲虫原始照片(198张); (2)标注鉴定结果的甲虫照片; (3)甲虫标本数量统计表; (4)形态物种鉴定图; (5)经度、纬度、温度、降水量和海拔高度信息表。该数据集通过3种被动采集方式采集甲虫, 为昆虫的采集提供了有效可行的方法。该数据集可以定量评估香港地区的甲虫多样性, 从而丰富相关的研究。

数据库(集)基本信息简介

数据库(集)名称	香港马鞍山基于三种被动式采集方法采集的甲虫标本数据集
作者	申昊, 佟一杰, 赵淑哲, 韩永金, 史晓旭, 滕备, 王新谱, 白明
通讯作者	白明(baim@ioz.ac.cn), 王新谱(wangxinpu@nxu.edu.cn)
时间范围	2017年5月27日至6月17日
地理区域	香港, 114°14′-114°15′ E, 22°22′-22°23′ N
文件大小	1.16 GB
数据格式	*.zip
数据链接	https://www.scidb.cn/s/iu6Fvu https://doi.org/10.57760/sciencedb.06308 https://www.biodiversity-science.net/fileup/1005-0094/DATA/2023021.zip
数据库(集)组成	该数据集由五部分组成: (1)采集的甲虫原始照片(198张); (2)标注鉴定结果的甲虫照片; (3)甲虫标本数量统计表; (4)形态物种鉴定图; (5)纬度、经度、温度、降水量和海拔高度信息表。

关键词: 香港, 生物多样性, 被动式采集, SITE100

Abstract

Here is a dataset offers the biodiversity information of beetles in the Ma On Shan region of Hong Kong, China. We collected beetles from various areas using three passive collection methods (flight interception trap, Malaise trap and pitfall trap) in different areas. The dataset includes beetles collected at Ma On Shan (Hong Kong) sample site from 27th May to 17th June, 2017. The sample site contains 13 sample points, each with one flight interception trap, one Malaise trap, and ten pitfall traps. In total, we collected 3,011 beetles from 45 families and 325 species. This dataset consists of five parts: (1) the original photos of collected beetles (photographed in 198 images); (2) photographs of beetles with identification results; (3) a statistical table showing the number of beetle specimens collected; (4) a morphological species identification chart; (5) an information table with latitude, longitude, temperature, precipitation and altitude of sample points. By using three passive collection methods, this study provides an effective and feasible approach for collecting insects. This dataset can be used to quantitatively assess the diversity of beetles and contribute to the diversity study of beetles in Hong Kong.

Database/Dataset Profile

Title	A photographic dataset of the beetle specimens by three passive acquisition methods in Ma On Shan, Hong Kong
Authors	Hao Shen, Yijie Tong, Shuzhe Zhao, Yongjin Han, Xiaoxu Shi, Bei Teng, Xinpu Wang, Ming Bai
Corresponding authors	Ming Bai (baim@ioz.ac.cn), Xinpu Wang (wangxinpu@nxu.edu.cn)
Time range	2017.05.27-06.17
Geographical scope	Hong Kong, 114°14′-114°15′ E, 22°22′-22°23′ N
File size	1.16 GB
Data format	*.zip
Data link	https://www.scidb.cn/s/iu6Fvu https://doi.org/10.57760/sciencedb.06308 https://www.biodiversity-science.net/fileup/1005-0094/DATA/2023021.zip
Database/Dataset composition	This dataset consists of five parts: (1) the original photos of collected beetles (photographed in 198 images); (2) photographs of beetles with identification results; (3) a statistical table showing the number of beetle specimens collected; (4) a morphological species identification chart; (5) an information table with latitude, longitude, temperature, precipitation and altitude of sample site.

Key words: Hong Kong, biological diversity, passive collecting, SITE100

申昊, 佟一杰, 赵淑哲, 韩永金, 史晓旭, 滕备, 王新谱, 白明 (2023) 香港马鞍山基于三种被动式采集方法采集的甲虫标本数据集. 生物多样性, 31, 23021. DOI: 10.17520/biods.2023021.

Hao Shen, Yijie Tong, Shuzhe Zhao, Yongjin Han, Xiaoxu Shi, Bei Teng, Xinpu Wang, Ming Bai (2023) A photographic dataset of the beetle specimens by three passive acquisition methods in Ma On Shan, Hong Kong. Biodiversity Science, 31, 23021. DOI: 10.17520/biods.2023021.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.biodiversity-science.net/CN/10.17520/biods.2023021

https://www.biodiversity-science.net/CN/Y2023/V31/I7/23021

图/表 6

图1 香港马鞍山郊野公园样地采样点分布

Fig. 1 The distribution of sample points in the Ma On Shan Country Park

图2 三种被动式采集装置。(a)飞行阻隔器; (b)马氏网; (c)埋罐。

Fig. 2 The three passive acquisition devices. (a) Flight interception trap; (b) Malaise trap; (c) Pitfall trap.

图3 三种被动式采集方法采集的甲虫照片示例。(a)飞行阻隔器; (b)马氏网; (c)埋罐。

Fig. 3 Examples of beetles collected from three passive acquisition methods. (a) Flight interception trap; (b) Malaise trap; (c) Pitfall trap.

图4 不同采样点通过不同采集方式采集的甲虫个体数量

Fig. 4 Number of beetles collected through different acquisition methods at different sample points

图5 不同采集方法采集到的甲虫科数与形态种数

Fig. 5 The number of beetles at the family level and morphological species level collected by different passive acquisition methods

图6 甲虫形态种数量排名前10的科级阶元

Fig. 6 The top 10 families in terms of the number of morphological species

参考文献 22

[1]	Andersson G, von Proschwitz T, Fägerström C, Green M, Smith HG, Lindström Å (2022) Arthropod populations in a sub-arctic environment facing climate change over a half- century: Variability but no general trend. Insect Conserva- tion and Diversity, 15, 534-542.
[2]	Beutel RG, Leschen RAB (2011) Handbook of Zoology, Vol. 4, Part 38, Coleoptera, Beetles. Walter de Gruyter Press, Berlin.
[3]	Beutel RG, Leschen RAB (2016) Handbook of Zoology, Coleoptera, Beetles: Morphology and Systematics (Archo- stemata, Adephaga, Myxophaga, Polyphaga partim). Walter de Gruyter Press, Berlin.
[4]	Bian XN, Garner BH, Liu HX, Vogler AP (2022) The SITE-100 Project: Site-based biodiversity genomics for species discovery, community ecology, and a global tree- of-life. Frontiers in Ecology and Evolution, 10, 787560. DOI URL
[5]	Bouchard P, Bousquet Y, Davies AE, Alonso-Zarazaga MA, Lawrence JF, Lyal CHC, Newton AF, Reid CAM, Schmitt M, Slipiński SA, Smith ABT (2011) Family-group names in Coleoptera (Insecta). ZooKeys, 88, 1-972.
[6]	Cardinale BJ, Duffy JE, Gonzalez A, Hooper DU, Perrings C, Venail P, Narwani A, Mace GM, Tilman D, Wardle DA, Kinzig AP, Daily GC, Loreau M, Grace JB, Larigauderie A, Srivastava DS, Naeem S (2012) Biodiversity loss and its impact on humanity. Nature, 486, 59-67.
[7]	Costa-Silva V, Grella MD, Thyssen PJ (2019) Optimized pitfall trap design for collecting terrestrial insects (Arthropoda: Insecta) in biodiversity studies. Neotropical Entomology, 48, 50-56. DOI PMID
[8]	Hallmann CA, Sorg M, Jongejans E, Siepel H, Hofland N, Schwan H, Stenmans W, Müller A, Sumser H, Hörren T, Goulson D, de Kroon H, (2017) More than 75 percent decline over 27 years in total flying insect biomass in protected areas. PLoS ONE, 12, e0185809.
[9]	Keil P, Storch D, Jetz W (2015) On the decline of biodiversity due to area loss. Nature Communications, 6, 8837. DOI PMID
[10]	Matthews R, Matthews J (1983) Malaise traps: The Townes model catches more insects. Contributions of the American Entomological Institute, 20, 428-432.
[11]	McCormack JE, Hird SM, Zellmer AJ, Carstens BC, Brumfield RT (1802) Tenebrionidae Latreille. Zoology, 12, 11-14.
[12]	Montgomery GA, Belitz MW, Guralnick RP, Tingley MW (2021) Standards and best practices for monitoring and benchmarking insects. Frontiers in Ecology and Evolution, 8, 579193. DOI URL
[13]	Myers N, Mittermeier RA, Mittermeier CG, da Fonseca GAB, Kent J (2000) Biodiversity hotspots for conservation priorities. Nature, 403, 853-858. DOI
[14]	Nie RE, Yang MX, Xue HJ, Yang YR, Tong YJ, Qiu TF, Bai M, Yang XK (2017) The application and effectiveness of a flight interception trap for insect collecting. Chinese Journal of Applied Entomology, 54, 530-535. (in Chinese with English abstract)
	[聂瑞娥, 杨美霞, 薛怀君, 杨御儒, 佟一杰, 邱腾飞, 白明, 杨星科 (2017) 飞行阻隔器在昆虫采集中的应用探究. 应用昆虫学报, 54, 530-535.]
[15]	Pedersen Zari M, MacKinnon M, Varshney K, Bakshi N (2022) Regenerative living cities and the urban climate-biodiversity- wellbeing nexus. Nature Climate Change, 12, 601-604. DOI
[16]	Ramos-Elorduy J, Moreno JMP, Prado EE, Perez MA, Otero JL, de Guevara OL, (1997) Nutritional value of edible insects from the state of Oaxaca, Mexico. Journal of Food Composition and Analysis, 10, 142-157. DOI URL
[17]	Raven PH, Wagner DL (2021) Agricultural intensification and climate change are rapidly decreasing insect biodiversity. Proceedings of the National Academy of Sciences, USA, 118, e2002548117.
[18]	Sala OE, Stuart Chapin F, Armesto JJ, Berlow E, Bloomfield J, Dirzo R, Huber-Sanwald E, Huenneke LF, Jackson RB, Kinzig A, Leemans R, Lodge DM, Mooney HA, Oesterheld M, Poff NL, Sykes MT, Walker BH, Walker M, Wall DH (2000) Global biodiversity scenarios for the year 2100. Science, 287, 1770-1774. DOI PMID
[19]	Townes H (1972) A light-weight Malaise trap. Entomological News, 83, 239-247.
[20]	Watson R (1999) Common themes for ecologists in global issues. Journal of Applied Ecology, 36, 1-10. DOI URL
[21]	Westphal C, Bommarco R, Carré G, Lamborn E, Morison N, Petanidou T, Potts SG, Roberts SPM, Szentgyörgyi H, Tscheulin T, Vaissière BE, Woyciechowski M, Biesmeijer JC, Kunin WE, Settele J, Steffan-Dewenter I (2008) Measuring bee diversity in different European habitats and biogeographical regions. Ecological Monographs, 78, 653-671. DOI URL
[22]	Zhao SZ, Tong YJ, Teng B, Chen X, Yang XK, Li J, Bai M (2022) A species diversity dataset of beetles by three passive acquisition methods in Tei Tong Tsai (Hong Kong). Scientific Data, 9, 210. DOI PMID

香港马鞍山基于三种被动式采集方法采集的甲虫标本数据集

A photographic dataset of the beetle specimens by three passive acquisition methods in Ma On Shan, Hong Kong

RichHTML

PDF (PC)

数据集

可视化

被引次数

摘要/Abstract

引用本文

使用本文

图/表 6

参考文献 22

相关文章 15

编辑推荐

Metrics

本文评价

[1]	梁竣策, 李开枝, 谭烨辉. 南海翼足类物种多样性与分布[J]. 生物多样性, 2026, 34(5): 25487-.
[2]	周丽洁, 郝珉辉, 何怀江, 程艳霞, 张春雨, 赵秀海. 小兴安岭森林β多样性格局、组分及其影响因素[J]. 生物多样性, 2026, 34(4): 25443-.
[3]	彭昀月, 彭奎, 刘昕然, 孙天怡, 张小全. 生物多样性信用的企业参与途径、市场发展障碍与建议[J]. 生物多样性, 2026, 34(4): 26031-.
[4]	李伯尧, 盛天成, 幸小云. 生物多样性风险对企业财务绩效的影响: 来自中国上市公司的证据[J]. 生物多样性, 2026, 34(4): 25330-.
[5]	刘昊, 张玉霄, 刘冰, 李飞飞, 马洪峥, 覃海宁, 李德铢, 陈文俐. 中国禾本科植物多样性及其物种名录[J]. 生物多样性, 2026, 34(4): 25438-.
[6]	孔孜亦, 王德港, 王建涛, 裴志永, 孙晶, 张长春, 张军国. 基于SCD-HRNet模型的野生动物姿态估计及其在生物多样性监测中的应用: 以内蒙古赛罕乌拉地区为例[J]. 生物多样性, 2026, 34(4): 25287-.
[7]	朱浩友, 周友兵, 罗怡, 周昭敏. 南充市城区繁殖鸟类群落20年前后的变化[J]. 生物多样性, 2026, 34(3): 24560-.
[8]	侯姝彧, 刘盈盈, 杨锐. 《昆蒙框架》背景下国际OECMs体系构建实践进展及中国化思路[J]. 生物多样性, 2026, 34(3): 25264-.
[9]	程晓帆, 李青媛, 李媛辉, 张明祥. 外来入侵物种治理政策体系的困境与出路[J]. 生物多样性, 2026, 34(2): 25332-.
[10]	陈璐露, 汤皓婷, 冷红, 袁青, 杨昕悦. 城市街区建成环境对生物多样性的影响[J]. 生物多样性, 2026, 34(2): 25286-.
[11]	高雯琪, 向景荣, 赵耀, 范灵霜, 谷圆, 邵韦涵, 李高俊, 赵光军, 陈明斌, 蔡杏伟, 陈凯. 海南热带雨林国家公园黎母山和尖峰岭溪流鱼类群落特征及其对土地利用的响应[J]. 生物多样性, 2026, 34(2): 25374-.
[12]	卢晓强, 芮丹, 张江峰, 尹冰鑫, 王雨露, 岑雨婷, 崔怡晨, 杨万霞. 氮输入驱动的关键生态过程对生物多样性的影响及其管理启示[J]. 生物多样性, 2026, 34(2): 25368-.
[13]	谭廷鸿, 高帆, 杨雨, 肖群英, 吴春芳, 邱娜, 赵宁宁, 周敏, 康公平, 卢志宏, 高健强, 杨红, 杨传东, 邓春英. 中国西南喀斯特地区大型真菌物种编目[J]. 生物多样性, 2026, 34(2): 25281-.
[14]	章旭日, 罗标, 赵彤, 黄丹, 艾为明. 浙江鱼类多样性: 编目、分布与保护[J]. 生物多样性, 2026, 34(2): 25225-.
[15]	刘海鸥, 郝志明, 杜乐山, 刘文慧, 李子圆, 刘蕾. 全球生物多样性框架基金运行进展、挑战与启示[J]. 生物多样性, 2026, 34(2): 25463-.