基于摇蚊的古环境和古气候国内外研究进展与展望

doi:10.11867/j.issn.1001-8166.2016.08.0870.

地球科学进展 ›› 2016, Vol. 31 ›› Issue (8): 870 -884. doi: 10.11867/j.issn.1001-8166.2016.08.0870.

胡玉(

), 陈建徽 ^*(

), 王海鹏, 吕飞亚, 魏国英

兰州大学资源环境学院西部环境教育部重点实验室,甘肃兰州 730000

收稿日期:2016-03-17 修回日期:2016-06-20 出版日期:2016-08-20
通讯作者: 陈建徽 E-mail:huy13@lzu.edu.cn;jhchen@lzu.edu.cn
基金资助:
科技部全球变化国家重大科学计划项目课题“西北干旱区湖泊水文—生态系统演变过程与机制”(编号:2012CB956102);国家自然科学基金面上项目“中纬度西风区和季风区基于摇蚊的过去两千年高山湖泊记录及其对比研究”(编号:41471162)资助

Recent Progress and Perspectives in Paleoenvironmental and Paleoclimatic Research Based on Chironomidae (Diptera)

Yu Hu( ), Jianhui Chen ^*( ), Haipeng Wang, Feiya Lü, Guoying Wei

Key Laboratory of Western China’s Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000,China

Received:2016-03-17 Revised:2016-06-20 Online:2016-08-20 Published:2016-08-20
Contact: Jianhui Chen E-mail:huy13@lzu.edu.cn;jhchen@lzu.edu.cn
Supported by:
Project supported by the National Basic Research Program of China “Processes and mechanisms of hydrological-ecosystemic evolution in lakes over arid northwestern China”(No.2012CB956102) and the National Natural Science Foundation of China “Chironomid-based proxy records and their comparison from alpine lakes in mid-latitude China during the past 2000 years”(No.41471162)

全文 ( 11 ) 下载PDF ( 809 )

双翅目摇蚊科(Diptera:Chironomidae)昆虫生命周期相对较短,能够敏感响应环境因子变化,成为国际古湖沼学领域近20年来快速发展的代用指标,其主要近期进展可归结为以下4个方面:①样本训练集和转换函数的大量建立,以及区域数据库的对比和整合;②对湖泊水文、理化等内部因素在影响摇蚊群落方面所起的作用日益重视;③对现代间冰期以来、更为精细的时间尺度的关注;④实验技术和数值处理方法的改进,以及新指标的不断开发。国内的相关研究起步较晚,但迄今为止已经在长江中下游、青藏高原、云贵高原区、蒙新等地区开展了相应工作,并建立了摇蚊—环境数据库,同时关注湖泊内部因素对摇蚊种群的作用;古环境重建工作主要集中在西北干旱区和云贵高原区,东部地区的研究则主要反映了近期人类活动对湖泊状态的影响。就目前而言,基于摇蚊的古环境和古气候研究迫切需要:①开展更多的个体生态学工作,以广域范围内的现生调查为基础,构建属/种—环境因子之间的关系;②利用新技术手段进一步提高实验效率,提升鉴定分辨率;③注重先进的数量生态学方法以及同位素标记等新兴手段在研究中的应用;④充分重视摇蚊指标在湖泊自然状态界定和生态修复方面的作用。

关键词: 摇蚊亚化石, 古环境, 古气候

Chironomidae (Diptera) becomes a rapid developing proxy in the international paleolimnology in the recent 20 years due to its short life cycle, strong ability to move and sensitive response to environmental change. The main progress of paleolimnological research based on chironomid can be summarized as the following four aspects: ①The establishment of a large number of sample training sets and transfer functions, as well as the comparison and integration of regional databases; ②More attention on the role of internal lacustrine factors in controlling of the chironomid population; ③Attention on finer time scales since the modern interglacial period; ④Improvement of the experimental technology and numerical methods, and constant development of new indicators. The domestic related research started late, but databases in the middle and lower reaches of the Yangtze river, the Tibetan Plateau, the Yunnan Plateau and the region of inner Mongolia and Xinjiang has been established so far, and also some researches on the internal lacustrine factors on chironomid population has been carried out; paleoenvironmental reconstruction is mainly concentrated in the northwest arid areas and the Yunnan Plateau, and the research in eastern region is primarily focused on reflecting the effects of recent state of human activities on the lakes. Paleoenvironment and paleoclimate researches based on chironomid urgently need to ①Carry out more individual ecology work to accurately understand the relationship between the species and environmental factors, combined with the investigation of a broader area; ②Further improve the efficiency of experiments by new technology to enhance the resolution of identification; ③Pay attention to the application of the advanced quantitative ecology methods and the novel tools such as isotopic analysis; ④Attach great importance to the role of chironomid in the definition of lake natural state and the ecological restoration.

Key words: Subfossil chironomid, Paleoenvironment, Paleoclimate.

中图分类号:

P532

表1 图1 中46个样本训练集的基本参数

Table 1 Basic parameter of the 46 chironomid training sets in figure 1

代码	中心位置经度	中心位置纬度	包含湖泊数量	目标环境因子	最终所用模型	决定系数 (r²)	预测误差 (RMSEP)	参考文献
1	-162.1	63.4	1	水深	PLS(2)	0.9	1.76	[22]
2	-126.9	54.9	136	温度和水深	WA-PLS(2)	0.818,0.382	1.46,0.58	[23]
3	-124.5	50.9	51	温度	WA-PLS(2)	0.7	1.98	[24]
4	-121.0	51.3	86	盐度	WA	0.72	0.52	[12]
5	-119.1	37.6	56	温度	WA-classical	0.73	1.2	[25]
6	-110.3	40.7	90	温度	WA-PLS(3)	0.66	1.4	[26]
7	-110.0	67.5	82	温度	WA-PLS(2)	0.77	1.03	[27]
8	-95.0	50.0	35	水深	PLS	0.78	0.533	[28]
9	-93.8	57.6	63	盐度	WA-PLS(2)	0.68	0.482	[29]
10	-81.3	66.1	65	温度	WA-PLS(2)	0.79	1.41	[30]
11	-78.5	44.5	54	底层滞水含氧量	WA-inverse	0.544	2.147	[19]
12	-77.5	54.7	52	温度	PLS	0.67	1.17	[31]
13	-77.4	44.6	40	底层滞水含氧量	PLS	0.58	0.032	[18]
14	-70.7	60.4	39	温度	WA-PLS(2)	0.88	2.26	[32]
15	-70.6	41.9	1	水深	PLS(3)	0.9	0.5	[33]
16	-69.5	-49.5	63	温度	WA-PLS	0.64	0.83	[34]
17	-61.0	54.0	24	温度	WA	0.79	1.32	[4]
18	-51.7	66.8	41	营养状况	WA-inverse	0.56	0.07	[16]
19	-22.3	65.3	53	温度	WA-PLS(2)	0.66	1.095	[11]
20	-3.0	52.5	44	营养状况	WA	0.6	0.34	[35]
21	-2.4	67.1	207	温度	WA-PLS	0.87	1.13	[36]
22	5.0	62.0	44	温度	WA-PLS	0.69	1.13	[37]
23	8.1	46.7	81	温度	WA-PLS(2)	0.81	1.51	[38]
24	8.1	52.7	50	温度和营养状况	WA-PLS(2)	0.849	1.37	[39,40]
25	10.5	56.4	54	营养状况	WA	0.67	0.65	[41]
26	14.0	47.0	1	水深	WA-classical	0.91	0.62	[42]
27	17.5	69.0	111	温度	WA-PLS(3)	0.94	0.9	[43]
28	18.8	68.1	100	温度	WA-PLS	0.65	1.13	[44]
29	23.0	62.0	255	温度	WA-PLS	0.87	1.4	[45]
30	23.0	68.1	62	温度和水深	Bummer model和WA-PLS(2)	0.74,0.61	0.8,0.95	[46]
31	23.3	-1.6	32	盐度	WA	0.81	0.39	[47]
32	25.7	65.1	139	温度	WA-PLS(2)	0.88	0.084	[48]
33	26.1	65.1	77	温度和水深	WA-PLS	0.78,0.68	0.721,0.78	[15]
34	30.1	64.3	1	水深	WA-PLS(2)	0.76	0.94	[49]
35	31.6	39.5	27	温度	WA-PLS	0.6	3.03	[50]
36	34.0	4.5	67	盐度	WA-PLS(2)	0.86	0.27	[13]
37	35.5	-1.5	64	温度	WMAT(3)	0.81	1.1	[51]
38	67.0	65.0	149	大陆度	WA-PLS(2)	0.73	9.88	[52]
39	91.0	66.5	81	温度	WA-PLS(2)	0.92	0.89	[52]
40	92.7	33.5	38	盐度	WA-PLS(2)	0.8	0.29	[53]
41	116.5	31.0	51	营养状况	WA-inverse	0.68	0.16	[54]
42	134.2	66.1	148	温度和水深	WA-PLS(2),WA-PLS	0.87,0.62	1.93,0.35	[55]
43	146.5	-42.3	47	温度	WA-PLS(2)	0.72	0.94	[56]
44	146.7	-34.1	33	温度	PLS	0.69	2.33	[57]
45	170.6	-43.2	60	温度	WA-PLS	0.8	1.27	[58]
46	171.8	-41.6	37	温度和营养状况	WA-PLS(2),PLS	0.77,0.49	1.31,0.46	[59]

表1 图1 中46个样本训练集的基本参数

Table 1 Basic parameter of the 46 chironomid training sets in figure 1

代码	中心位置经度	中心位置纬度	包含湖泊数量	目标环境因子	最终所用模型	决定系数 (r²)	预测误差 (RMSEP)	参考文献
1	-162.1	63.4	1	水深	PLS(2)	0.9	1.76	[22]
2	-126.9	54.9	136	温度和水深	WA-PLS(2)	0.818,0.382	1.46,0.58	[23]
3	-124.5	50.9	51	温度	WA-PLS(2)	0.7	1.98	[24]
4	-121.0	51.3	86	盐度	WA	0.72	0.52	[12]
5	-119.1	37.6	56	温度	WA-classical	0.73	1.2	[25]
6	-110.3	40.7	90	温度	WA-PLS(3)	0.66	1.4	[26]
7	-110.0	67.5	82	温度	WA-PLS(2)	0.77	1.03	[27]
8	-95.0	50.0	35	水深	PLS	0.78	0.533	[28]
9	-93.8	57.6	63	盐度	WA-PLS(2)	0.68	0.482	[29]
10	-81.3	66.1	65	温度	WA-PLS(2)	0.79	1.41	[30]
11	-78.5	44.5	54	底层滞水含氧量	WA-inverse	0.544	2.147	[19]
12	-77.5	54.7	52	温度	PLS	0.67	1.17	[31]
13	-77.4	44.6	40	底层滞水含氧量	PLS	0.58	0.032	[18]
14	-70.7	60.4	39	温度	WA-PLS(2)	0.88	2.26	[32]
15	-70.6	41.9	1	水深	PLS(3)	0.9	0.5	[33]
16	-69.5	-49.5	63	温度	WA-PLS	0.64	0.83	[34]
17	-61.0	54.0	24	温度	WA	0.79	1.32	[4]
18	-51.7	66.8	41	营养状况	WA-inverse	0.56	0.07	[16]
19	-22.3	65.3	53	温度	WA-PLS(2)	0.66	1.095	[11]
20	-3.0	52.5	44	营养状况	WA	0.6	0.34	[35]
21	-2.4	67.1	207	温度	WA-PLS	0.87	1.13	[36]
22	5.0	62.0	44	温度	WA-PLS	0.69	1.13	[37]
23	8.1	46.7	81	温度	WA-PLS(2)	0.81	1.51	[38]
24	8.1	52.7	50	温度和营养状况	WA-PLS(2)	0.849	1.37	[39,40]
25	10.5	56.4	54	营养状况	WA	0.67	0.65	[41]
26	14.0	47.0	1	水深	WA-classical	0.91	0.62	[42]
27	17.5	69.0	111	温度	WA-PLS(3)	0.94	0.9	[43]
28	18.8	68.1	100	温度	WA-PLS	0.65	1.13	[44]
29	23.0	62.0	255	温度	WA-PLS	0.87	1.4	[45]
30	23.0	68.1	62	温度和水深	Bummer model和WA-PLS(2)	0.74,0.61	0.8,0.95	[46]
31	23.3	-1.6	32	盐度	WA	0.81	0.39	[47]
32	25.7	65.1	139	温度	WA-PLS(2)	0.88	0.084	[48]
33	26.1	65.1	77	温度和水深	WA-PLS	0.78,0.68	0.721,0.78	[15]
34	30.1	64.3	1	水深	WA-PLS(2)	0.76	0.94	[49]
35	31.6	39.5	27	温度	WA-PLS	0.6	3.03	[50]
36	34.0	4.5	67	盐度	WA-PLS(2)	0.86	0.27	[13]
37	35.5	-1.5	64	温度	WMAT(3)	0.81	1.1	[51]
38	67.0	65.0	149	大陆度	WA-PLS(2)	0.73	9.88	[52]
39	91.0	66.5	81	温度	WA-PLS(2)	0.92	0.89	[52]
40	92.7	33.5	38	盐度	WA-PLS(2)	0.8	0.29	[53]
41	116.5	31.0	51	营养状况	WA-inverse	0.68	0.16	[54]
42	134.2	66.1	148	温度和水深	WA-PLS(2),WA-PLS	0.87,0.62	1.93,0.35	[55]
43	146.5	-42.3	47	温度	WA-PLS(2)	0.72	0.94	[56]
44	146.7	-34.1	33	温度	PLS	0.69	2.33	[57]
45	170.6	-43.2	60	温度	WA-PLS	0.8	1.27	[58]
46	171.8	-41.6	37	温度和营养状况	WA-PLS(2),PLS	0.77,0.49	1.31,0.46	[59]

图1 世界范围内基于摇蚊的样本训练集分布、包涵湖泊数量和目标环境因子示意图(各样点具体情况见表1 )

Fig.1 Location of the published datasets documenting the distribution of chironomid training sets, the number of lake and the aiming environmental factor(detailed information of each dataset is in Table 1 )

图2 晚冰期和早全新世摇蚊重建夏季温度与气候模式(ECHAM-4)输出结果对比(据参考文献[67]修改)
(a)晚冰期早期/博令—阿勒罗德间冰段过渡时期;(b)新仙女木期/早全新世过渡时期;(c)所有涉及的冷期和暖期

Fig.2 Comparison of Chironomid-inferred July temperatures with the ECHAM-4 climate model runs(modified after reference[67])
(a) Early late-glacial/Bølling-Allerød Interstadial transition; (b) Younger Dryas/early Holocene transition; (c) All the investigated cold and warm periods

图3 近千年来摇蚊重建瑞士温度记录及其与邻近区域树轮和生物硅综合重建温度记录的对比(据参考文献[117]修改)
(a)瑞士东部(黑线)和西部(灰线)湖泊基于摇蚊的过去千年7月温度重建;(b)瑞士东部树轮和生物硅综合夏季温度重建

Fig.3 Comparison between the chironomid-inferred temperature records and the tree-ring and biogenic silica-based temperature record during the last millennium in Switzerland (modified after reference[117])
(a)Chironomid-inferred mean July temperature anomalies from western (gray line) and eastern Switzerland (black line); (b) A composite of June-July-August temperature reconstruction based on six tree-ring records and a biogenic silica record from eastern Switzerland

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