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Journal of Arid Land  2021, Vol. 13 Issue (5): 500-515    DOI: 10.1007/s40333-021-0008-2
Research article     
Monitoring fire regimes and assessing their driving factors in Central Asia
YIN Hanmin1,2, Jiapaer GULI1,2,3,*(), JIANG Liangliang1,2, YU Tao1,2, Jeanine UMUHOZA1,2, LI Xu1,2
1State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
2University of Chinese Academy of Sciences, Beijing 100039, China
3Research Center for Ecology and Environment of Central Asia of Chinese Academy of Sciences, Urumqi 830011, China
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Abstract  

Relatively little is known about fire regimes in grassland and cropland in Central Asia. In this study, eleven variables of fire regimes were measured from 2001 to 2019 by utilizing the burned area and active fire product, which was obtained and processed from the GEE (Google Earth Engine) platform, to describe the incidence, inter-annual variability, peak month and size of fire in four land cover types (forest, grassland, cropland and bare land). Then all variables were clustered to define clusters of fire regimes with unique fire attributes using the K-means algorithm. Results showed that Kazakhstan (KAZ) was the most affected by fire in Central Asia. Fire regimes in cropland in KAZ had the frequent, large and intense characters, which covered large burned areas and had a long duration. Fires in grassland mainly occurred in central KAZ and had the small scale and high-intensity characters with different quarterly frequencies. Fires in forest were mainly distributed in northern KAZ and eastern KAZ. Although fires in grassland underwent a shift from more to less frequent from 2001 to 2019 in Central Asia, vigilance is needed because most fires in grassland occur suddenly and cause harm to humans and livestock.



Key wordsfire regime      burned area      active fire      K-means algorithm      Central Asia     
Received: 22 September 2020      Published: 10 May 2021
Corresponding Authors:
About author: *Jiapaer GULI (E-mail: glmr@ms.xjb.ac.cn)
Cite this article:

YIN Hanmin, Jiapaer GULI, JIANG Liangliang, YU Tao, Jeanine UMUHOZA, LI Xu. Monitoring fire regimes and assessing their driving factors in Central Asia. Journal of Arid Land, 2021, 13(5): 500-515.

URL:

http://jal.xjegi.com/10.1007/s40333-021-0008-2     OR     http://jal.xjegi.com/Y2021/V13/I5/500

Fig. 1 Main types of land use in Central Asia in 2018 (a) and fire burn scars based on Landsat 8 images in central KAZ (b-g, marked as A-F in Figure 1a). A, northeastern Aktobe; B, northeastern Aktobe; C, southern Qostanay; D, southern Qaraghandy; E, southern Qaraghandy; F, East Kazakhstan. KAZ, Kazakhstan; UZB, Uzbekistan; TKM, Turkmenistan; KGZ, Kyrgyzstan; TJK, Tajikistan. Abbreviations are the same as in the following figures.
No. Type Abbreviation Variable Unit
1 Fire incidence ABAY Average annual burned area hm2/a
2 AFOF Average annual active fire frequency counts/a
3 Inter-annual variability CVBA Inter-annual coefficient of variance in annual burned area
4 CVFP Inter-annual coefficient of variance in annual active fire frequency
5 Fire size GI Gini index
6 Active fire
seasonality
FPSD Seasonal duration of fires d
7 FPDT Peak month of fires
8 Vegetation type PFAF Percentage of forest active fires %
9 PGAF Percentage of grassland active fires
10 PCAF Percentage of cropland active fires
11 PBAF Percentage of bare land active fires
Table 1 List of fire variables from 2001 to 2019
Fig. 2 Average annual burned area (ABAY, a) and its inter-annual coefficient of variance (CVBA, b) in Central Asia based on FireCCI5.1 burned area data
Fig. 3 Average annual active fire frequency (AFOF, a) and its inter-annual coefficient of variance (CVFP, b) in Central Asia based on MODIS active fire data
Fig. 4 Peak month of fires (FPDT) in different months in Central Asia based on MODIS active fire data
Fig. 5 Seasonal duration of fires (FPSD, a) and Gini index (GI, b) in Central Asia based on MODIS burned area data and active fire data
Fig. 6 Vegetation types affected by fires in Central Asia based on MODIS active fire data. PFAF, percentage of forest active fires; PGAF, percentage of grassland active fires; PCAF, percentage of cropland active fires; PBAF, percentage of bare land active fires.
Fig. 7 Box plot distribution of fire variable values. The black center mark indicates the median, while the bottom and top edges of the green box and line indicate the 25th and 75th percentiles, respectively. Outliers (if any) are indicated by red plus signs.
Fig. 8 Distribution of fire regime in Central Asia
Index Fire regime
1 2 3 4 5
ABAY (hm2/a) Low (0.10) Medium (0.30) High (0.50) Medium (0.30) High (0.34)
AFOF (counts/a) Low (0.10) High (0.20) Medium (0.15) Low (0.10) High (0.30)
CVBA Low (2.00) High (4.20) Low (2.80) High (4.00) Medium (3.00)
CVFP Low (1.70) Medium (3.00) Medium (2.80) High (4.20) Low (1.90)
GI Low (0.71) High (0.85) Medium (0.82) Low (0.65) High (0.88)
FPSD (d) 0.00 Low (0.45) High (3.00) Medium (2.00) High (5.00)
FPDT - 1.00 7.00 7.00 4.00
Vegetation type Bare land Cropland Grassland Grassland Cropland
Table 2 Fire regime variables and classification of fire regimes
Fig. 9 Monthly active fires in grassland in Central Asia
Fig. 10 Monthly active fires in cropland in Central Asia
Fig. 11 Net primary productivity (NPP) of vegetation in grassland from 2016 to 2019 based on different fire regimes. A, northeastern Aktobe (25 August, 2016); B, northeastern Aktobe (15 August, 2016); C, southern Qostanay (4 September, 2016); D, southern Qaraghandy (21 August, 2016); E, southern Qaraghandy (11 August, 2016); F, East Kazakhstan (1 September, 2016).
Fig. 12 Time series of normalized difference vegetation index (NDVI) in the agricultural areas of Central Asia from 2015 to 2019 based on MOD13Q1 V6 products. KAZ1, northern Kazakhstan; KAZ2, Syr Darya Valley; KGZ1, northern Kyrgyzstan; KGZ2, Uzgen City; UZB1, Nukus Irrigation District; UZB2, southern Tashkent City; UZB3, Fergana Valley.
Fig. 13 Relationship between PSDI (Palmer Drought Severity Index) and annual burned area in grassland. (a), PDSI change from 2001 to 2018; (b), correlations of PDSI with frequency and cumulative area of fires in grassland in Kazakhstan.
Fig. 14 Relationship between PDSI (Palmer Drought Severity Index) and monthly burned area in grassland. (a), monthly PDSI from 2001 to 2018; (b) monthly burned area in grassland from 2001 to 2018 in Kazakhstan.
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