Spatiotemporal changes in forest loss and its linkage to burned areas in China

Abstract

Fire-induced forest loss has substantially increased worldwide over the last decade. In China, the connection between forest loss and frequent fires on a national scale remains largely unexplored. In this study, we used a data set for a time-series of forest loss from the Global Forest Watch and for a MODIS-derived burned area for 2003–2015 to ascertain variations in forest loss and to explore its relationship with forest fires (represented by burned areas) at the country- and forest-zone levels. We quantified trends in forest loss during 2003–2015 using linear regression analysis and assessed the relation between forest loss and burned areas using Spearman’s correlation. Forest loss increased significantly (264.8 km² a⁻¹; R ² = 0.54, p < 0.01) throughout China, with an average annual increase of 11.4% during 2003–2015. However, the forest loss trend had extensive spatial heterogeneity. Forest loss increased mainly in the subtropical evergreen broadleaf forest zone (315.0 km² a⁻¹; R ² = 0.69, p < 0.01) and tropical rainforest zone (38.8 km² a⁻¹; R ² = 0.66, p < 0.01), but the loss of forest decreased in the cold temperate deciduous coniferous forest zone (− 70.8 km² year⁻¹; R ² = 0.75, p < 0.01) and the temperate deciduous mixed broadleaf and coniferous forest zone (− 14.4 km² a⁻¹; R ² = 0.45, p < 0.05). We found that 1.0% of China’s area had a significant positive correlation (r ≥ 0.55, p < 0.05) with burned areas and 0.3% had a significant negative correlation (r ≤ − 0.55, p < 0.05). In particular, forest loss had a significant positive relationship with the burned area in the cold temperate deciduous coniferous forest zone (16.9% of the lands) and the subtropical evergreen broadleaf forest zone (7.8%). These results provide a basis for future predictions of fire-induced forest loss in China.

Keywords

Forest loss / Forest fire / Burned area / Spatiotemporal variability / Correlation analysis

References

[1] Abatzoglou JT, Williams AP. Impact of anthropogenic climate change on wildfire across western US forests. Proc Natl Acad Sci USA, 2016, 113(42): 11770-11775.

[2] Adams MA, Shen ZH. Introduction to the characteristics, impacts and management of forest fire in China. For Ecol Manag, 2015, 356: 1.

[3] Andela N, Morton DC, Giglio L, Paugam R, Chen Y, Hantson S, van der Werf GR, Randerson JT. The Global Fire Atlas of individual fire size, duration, speed and direction. Earth Syst Sci Data, 2019, 11(2): 529-552.

[4] Betts MG, Wolf C, Ripple WJ, Phalan B, Millers KA, Duarte A, Butchart SHM, Levi T. Global forest loss disproportionately erodes biodiversity in intact landscapes. Nature, 2017, 547(7664): 441-444.

[5] Bonan GB. Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science, 2008, 320(5882): 1444-1449.

[6] Brando PM, Balch JK, Nepstad DC, Morton DC, Putz FE, Coe MT, Silverio D, Macedo MN, Davidson EA, Nobrega CC, Alencar A, Soares BS. Abrupt increases in Amazonian tree mortality due to drought–fire interactions. Proc Natl Acad Sci USA, 2014, 111(17): 6347-6352.

[7] Broich M, Hansen M, Stolle F, Potapov P, Margono BA, Adusei B. Remotely sensed forest cover loss shows high spatial and temporal variation across Sumatera and Kalimantan, Indonesia 2000–2008. Environ Res Lett, 2011 6 1 014010

[8] Brown CD, Johnstone JF. How does increased fire frequency affect carbon loss from fire? A case study in the northern boreal forest. Int J Wildland Fire, 2011, 20(7): 829-837.

[9] Cahoon DR, Stocks BJ, Levine JS, Cofer WR, Pierson JM. Satellite analysis of the severe 1987 forest-fires in Northern China and Southeastern Siberia. J Geophys Res Atmos, 1994, 99(D9): 18627-18638.

[10] Chang Y, Zhu ZL, Bu RC, Li YH, Hu YM. Environmental controls on the characteristics of mean number of forest fires and mean forest area burned (1987–2007) in China. For Ecol Manag, 2015, 356: 13-21.

[11] Chen DM, Pereira JMC, Masiero A, Pirotti F. Mapping fire regimes in China using MODIS active fire and burned area data. Appl Geogr, 2017, 85: 14-26.

[12] Chiriaco MV, Perugini L, Cimini D, D’Amato E, Valentini R, Bovio G, Corona P, Barbati A. Comparison of approaches for reporting forest fire-related biomass loss and greenhouse gas emissions in southern Europe. Int J Wildland Fire, 2013, 22(6): 730-738.

[13] Curtis PG, Slay CM, Harris NL, Tyukavina A, Hansen MC. Classifying drivers of global forest loss. Science, 2018, 361(6407): 1108-1111.

[14] Da Ponte E, Roch M, Leinenkugel P, Dech S, Kuenzer C. Paraguay’s Atlantic Forest cover loss Satellite-based change detection and fragmentation analysis between 2003 and 2013. Appl Geogr, 2017, 79: 37-49.

[15] Dennis RA, Colfer CP. Impacts of land use and fire on the loss and degradation of lowland forest in 1983–2000 in East Kutai District, East Kalimantan, Indonesia. Singap J Trop Geogr, 2006, 27(1): 30-48.

[16] Fanin T, van der Werf GR. Relationships between burned area, forest cover loss, and land cover change in the Brazilian Amazon based on satellite data. Biogeosciences, 2015, 12(20): 6033-6043.

[17] Foley JA, Asner GP, Costa MH, Coe MT, DeFries R, Gibbs HK, Howard EA, Olson S, Patz J, Ramankutty N, Snyder P. Amazonia revealed: forest degradation and loss of ecosystem goods and services in the Amazon Basin. Front Ecol Environ, 2007, 5(1): 25-32.

[18] Fornacca D, Ren GP, Xiao W. Performance of three MODIS fire products (MCD45A1, MCD64A1, MCD14ML), and ESA Fire_CCI in a mountainous area of Northwest Yunnan, China, characterized by frequent small fires. Remote Sens Basel, 2017 9 11 1131

[19] Giglio L, Randerson JT, van der Werf GR, Kasibhatla PS, Collatz GJ, Morton DC, DeFries RS. Assessing variability and long-term trends in burned area by merging multiple satellite fire products. Biogeosciences, 2010, 7(3): 1171-1186.

[20] Guo FT, Su ZW, Wang GY, Sun L, Tigabu M, Yang XJ, Hu HQ. Understanding fire drivers and relative impacts in different Chinese forest ecosystems. Sci Total Environ, 2017, 605: 411-425.

[21] Hansen MC, DeFries RS, Townshend JRG, Carroll M, Dimiceli C, Sohlberg RA. Global percent tree cover at a spatial resolution of 500 meters: first results of the MODIS vegetation continuous fields algorithm. Earth Interact, 2003, 7: 1-15.

[22] Hansen MC, Egorov A, Roy DP, Potapov P, Ju JC, Turubanova S, Kommareddy I, Loveland TR. Continuous fields of land cover for the conterminous United States using Landsat data: first results from the Web-Enabled Landsat Data (WELD) project. Remote Sens Lett, 2011, 2: 279-288.

[23] Hansen MC, Potapov PV, Moore R, Hancher M, Turubanova SA, Tyukavina A, Thau D, Stehman SV, Goetz SJ, Loveland TR, Kommareddy A, Egorov A, Chini L, Justice CO, Townshend JRG. High-resolution global maps of 21st-century forest cover change. Science, 2013, 342(6160): 850-853.

[24] Harris NL, Goldman E, Gabris C, Nordling J, Minnemeyer S, Ansari S, Lippmann M, Bennett L, Raad M, Hansen M, Potapov P. Using spatial statistics to identify emerging hot spots of forest loss. Environ Res Lett, 2017 12 2 024012

[25] Heino M, Kummu M, Makkonen M, Mulligan M, Verburg PH, Jalava M, Rasanen TA. Forest loss in protected areas and intact forest landscapes: a global analysis. PLoS ONE, 2015 10 10 e0138918

[26] Jia MM, Wang ZM, Zhang YZ, Ren CY, Song KS. Landsat-based estimation of mangrove forest loss and restoration in Guangxi Province, China, influenced by human and natural factors. IEEE J Stars, 2015, 8(1): 311-323.

[27] Keenan RJ, Reams GA, Achard F, de Freitas JV, Grainger A, Lindquist E. Dynamics of global forest area: results from the FAO global forest resources assessment 2015. For Ecol Manag, 2015, 352: 9-20.

[28] Lehtomaki J, Tuominen S, Toivonen T, Leinonen A. What data to use for forest conservation planning? A comparison of coarse open and detailed proprietary forest inventory data in Finland. PLoS ONE, 2015 10 8 e0135926

[29] Li JF, Song Y, Huang X, Li MM. Comparison of forest burned areas in mainland China derived from MCD45A1 and data recorded in yearbooks from 2001 to 2011. Int J Wildland Fire, 2015, 24(1): 103-113.

[30] Liu YQ, Stanturf J, Goodrick S. Trends in global wildfire potential in a changing climate. For Ecol Manag, 2010, 259: 685-697.

[31] Molin PG, Gergel SE, Soares BS, Ferraz SFB. Spatial determinants of atlantic forest loss and recovery in Brazil. Landsc Ecol, 2017, 32(4): 857-870.

[32] Perry GLW, Wilmshurst JM, McGlone MS, Napier A. Reconstructing spatial vulnerability to forest loss by fire in pre-historic New Zealand. Glob Ecol Biogeogr, 2012, 21(10): 1029-1041.

[33] Piao SL, Fang JY, Ji W, Guo QH, Ke JH, Tao S. Variation in a satellite-based vegetation index in relation to climate in China. J Veg Sci, 2004, 15(2): 219-226.

[34] Potapov P, Hansen MC, Stehman SV, Loveland TR, Pittman K. Combining MODIS and Landsat imagery to estimate and map boreal forest cover loss. Remote Sens Environ, 2008, 112(9): 3708-3719.

[35] Potapov P, Hansen MC, Stehman SV, Pittman K, Turubanova S. Gross forest cover loss in temperate forests: biome-wide monitoring results using MODIS and Landsat data. J Appl Remote Sens, 2009, 3(1): 1-23.

[36] Reiche J, Verhoeven R, Verbesselt J, Hamunyela E, Wielaard N, Herold M. Characterizing tropical forest cover loss using dense sentinel-1 data and active fire alerts. Remote Sens Basel, 2018 10 5 rs10050777

[37] Reilly MJ, Elia M, Spies TA, Gregory MJ, Sanesi G, Lafortezza R. Cumulative effects of wildfires on forest dynamics in the eastern Cascade Mountains, USA. Ecol Appl, 2018, 28(2): 291-308.

[38] Sannier C, McRoberts RE, Fichet LV. Suitability of global forest change data to report forest cover estimates at national level in Gabon. Remote Sens Environ, 2016, 173: 326-338.

[39] Stephens SL, Agee JK, Fule PZ, North MP, Romme WH, Swetnam TW, Turner MG. Managing forests and fire in changing climates. Science, 2013, 342(6154): 41-42.

[40] R Core Team (2018) R: a language and environment for statistical computing. R foundation for statistical computing, Vienna, Austria. https://www.R-project.org

[41] Tepley AJ, Thompson JR, Epstein HE, Anderson-Teixeira KJ. Vulnerability to forest loss through altered postfire recovery dynamics in a warming climate in the Klamath Mountains. Glob Change Biol, 2017, 23(10): 4117-4132.

[42] Tian XR, Zhao FJ, Shu LF, Wang MY. Distribution characteristics and the influence factors of forest fires in China. For Ecol Manag, 2013, 310: 460-467.

[43] Trumbore S, Brando P, Hartmann H. Forest health and global change. Science, 2015, 349(6250): 814-818.

[44] van der Werf GR, Morton DC, DeFries RS, Olivier JGJ, Kasibhatla PS, Jackson RB, Collatz GJ, Randerson JT. CO₂ emissions from forest loss. Nat Geosci, 2009, 2(11): 737-738.

[45] van Lierop P, Lindquist E, Sathyapala S, Franceschini G. Global forest area disturbance from fire, insect pests, diseases and severe weather events. For Ecol Manag, 2015, 352: 78-88.

[46] Wang QH, Shu LF, Dai XA, Wang MY, Tian XR. Effects of snow and ice disasters on forest fuel and fire behaviors in the Southern China. Sci Silva Sin, 2008, 44(11): 171-176. (in Chinese with English abstract)

[47] Wang H, Lü Z, Gu L, Wen C. Observations of China’s forest change (2000–2013) based on global forest watch dataset. Biodivers Sci, 2015, 23(5): 575-582. (in Chinese with English abstract)

[48] Wotton BM, Nock CA, Flannigan MD. Forest fire occurrence and climate change in Canada. Int J Wildland Fire, 2010, 19(3): 253-271.

[49] Wu Z, Dai EF, Wu ZF, Lin MZ. Future forest dynamics under climate change, land use change, and harvest in subtropical forests in Southern China. Landsc Ecol, 2019, 34(4): 843-863.

[50] Xiao DN, Tao DL, Xu ZB. Impacts of an extra-ordinarily disastrous fire on forest resources and environment. Chin J Ecol, 1988, 7(Suppl.): 5-9.

[51] Yang FW, Lu SW, Wang B. Value estimation of service function of forest ecosystem damaged by frozen rain and snow in the South China. Sci Silva Sin, 2008, 44(11): 101-110. (in Chinese with English abstract)

[52] Zhai D, Xu J, Dai Z, Schmidt-Vogt D. Lost in transition: forest transition and natural forest loss in tropical China. Plant Divers, 2017, 39(3): 149-153.

[53] Zhang ZQ, Zhong JJ, Lv XG, Tong SZ, Wang GP. Climate, vegetation, and human influences on late-Holocene fire regimes in the Sanjiang plain, northeastern China. Palaeogeogr Palaeocl, 2015, 438: 1-8.

[54] Zhou WQ, Zhang S, Yu WJ, Wang J, Wang WM. Effects of urban expansion on forest loss and fragmentation in six megaregions, China. Remote Sens Basel, 2017 9 10 rs9100991