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Combining and competing effects between precipitation and temperature on Holocene fire regime evolution inferred from a sedimentary black carbon record in southwestern China

Published online by Cambridge University Press:  24 October 2019

Dongliang Ning
Affiliation:
State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, 73 Beijing E Rd, Xuanwu, Nanjing, Jiangsu 210008, China University of Chinese Academy of Sciences, Beijing 100049, China
Enlou Zhang*
Affiliation:
State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, 73 Beijing E Rd, Xuanwu, Nanjing, Jiangsu 210008, China
James Shulmeister
Affiliation:
School of Earth and Environmental Sciences, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia
Jie Chang
Affiliation:
State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, 73 Beijing E Rd, Xuanwu, Nanjing, Jiangsu 210008, China School of Earth and Environmental Sciences, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia
Weiwei Sun
Affiliation:
State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, 73 Beijing E Rd, Xuanwu, Nanjing, Jiangsu 210008, China
Zhenyu Ni
Affiliation:
State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, 73 Beijing E Rd, Xuanwu, Nanjing, Jiangsu 210008, China
*
*Corresponding author e-mail address: elzhang@niglas.ac.cn (E. Zhang).
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Abstract

Wildfires are sensitive to climate change, but their response to changes in temperature and precipitation on long timescales is still disputed. In this study, we present a ~9.4 ka black carbon mass sedimentation rate (BCMSR) record from Lake Ximenglongtan (XMLT), southwestern China, to elucidate the Holocene fire regime and its linkages to climatic conditions. The results indicate that the regional fire activity was low during the early Holocene (before 7.6 cal ka BP), increased notably at 7.6 cal ka BP, and continued to increase gradually during the mid- to late Holocene until 2.2 ka. The episodes of higher fire occurrence reflected by higher BCMSR over the last 2.2 ka might be more likely related to the intensified human activities. The cool and humid climate during the early Holocene limited the spread of fire, while warming and drying at ~7.6 cal ka BP triggered higher fire occurrence. Instead of temperature, changes in precipitation dominated fire regime variation during the mid- to late Holocene. On millennial timescales, we suggest that Holocene fire variability has been predominantly controlled by the combined effects of Northern Hemisphere (NH) summer and winter insolation that influenced monsoonal precipitation and fire season temperature, respectively. Indian Ocean Dipole (IOD) events may also have affected fire incidence through influencing monsoon intensity.

Information

Type
Research Article
Copyright
Copyright © University of Washington. Published by Cambridge University Press, 2019 
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Figure 1. (color online) (A) Location of Yunnan Province and the study sites mentioned in this study, including Paru Co(Morrill et al., 2006), Lake Muge (Sun et al., 2016), Liangjiacun Loess profile (Tan et al., 2015), Lake Daihai (Han et al., 2012), and Dongge Cave (Dykoski et al., 2005) as well as Lantianyan Bog and Shuizhuyang Bog (Zhao et al., 2017; Ma et al., 2018). (B) Location of Lake Ximenglongtan (XMLT) and the other paleoclimate reconstruction sites (Erhai Lake, Shen et al., 2006; Tiancai Lake, Zhang et al., 2017; Xingyun Lake, Wu et al., 2018) and fire history records (Tengchongqinghai Lake, Xiao et al., 2017a) in the region of the study site. (C) Summary climate data from Ximeng meteorological station showing monthly temperature and precipitation (http://data.cma.cn/). (D) Inter-monthly variation of lightning strikes in southwest China based on satellite observations from 1998–2007 (Wang et al., 2010a).

Figure 1

Figure 2. (color online) Age-depth model for Lake XMLT sediment core produced by Bacon software (Blaauw and Christen, 2011). The details of the age model are described in Ning et al. (2017).

Figure 2

Figure 3. Comparison of fire history recorded in Lake XMLT (A, this study) with that in ISM and EASM regions, including BC record (Zhang et al., 2015, B) and charcoal records (Xiao et al., 2017b, C) from Lake Tengchongqinghai, element carbon record from Lake Daihai (Han et al., 2012, D), and the compiled charcoal index for East Asia (Marlon et al., 2013, E). The blue line in curve A shows the 11-sample running mean. Relatively similar fire history during the Holocene has been recorded in both monsoonal areas. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Figure 3

Figure 4. Comparison of fire history recorded in Lake XMLT (A, this study) with the climatic proxies from southwestern China (B-E). (B) brGDGTs-based Mean Annual Temprature record from Lake XMLT (Ning et al., 2019); (C) Pollen-based Mean July temperature reconstruction from Lake Xingyun (Wu et al., 2018); (D) Sensitive component 2 of grain size indicating the precipitation changes from Lake XMLT (Ning et al., 2017); (E) Stalagmite δ18O variation from Dongge Cave (Dykoski et al., 2005). The blue and dark black lines in curve A and curve D as well as E is 11 and 31 samples moving average results, respectively. The cool and humid climate during the early Holocene suppressed the fire incidence, while a drier climate from the mid- to late Holocene primarily increased fire evolution instead of temperature. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Figure 4

Figure 5. Comparison of fire history recorded in Lake XMLT (A) with the possible natural and anthropogenic drivers, including (B) historical catchment erosion reflected by sediment magnetic susceptibility in Lake XMLT indicating catchment erosion; (C) Holocene population changes in Asia regions (Marlon et al., 2013); (D) the upper water vertical temperature gradient in the eastern Indian Ocean (Kwiatkowski et al., 2015); (E) Coral Sr/Ca-based Sea Surface Temperature (SST) estimation from the Mentawai Islands in the eastern Indian Ocean (Abram et al., 2009); and (F) Orbital-scale 30°N insolation changes during winter (dashed line) and summer (solid line) (Laskar et al., 2004). The blue line in curve A shows the 11-sample running mean. Both boreal summer and winter insolation are important in Holocene fire variation in this monsoonal area and the IOD events have an impact on the fire activity on multidecadal timescale. Catchment erosion cuased by increasing human activity during the late Holocene diluted the fire signal. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

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