Spatiotemporal Changes in Forest Loss and Its Linkage to Burned Areas in China
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J. For. Res. https://doi.org/10.1007/s11676-019-01062-0 ORIGINAL PAPER Spatiotemporal changes in forest loss and its linkage to burned areas in China Zhiwei Wu1,2,3 · Saijia Yan1 · Lei He1 · Yanlong Shan4 Received: 23 May 2019 / Accepted: 19 July 2019 © The Author(s) 2019 Abstract Fire-induced forest loss has substantially loss and burned areas using Spearman’s correlation. For- increased worldwide over the last decade. In China, the con- est loss increased signifcantly (264.8 km2 a−1; R2 = 0.54, nection between forest loss and frequent fres on a national p < 0.01) throughout China, with an average annual increase scale remains largely unexplored. In this study, we used a of 11.4% during 2003–2015. However, the forest loss trend data set for a time-series of forest loss from the Global For- had extensive spatial heterogeneity. Forest loss increased est Watch and for a MODIS-derived burned area for 2003– mainly in the subtropical evergreen broadleaf forest zone 2015 to ascertain variations in forest loss and to explore (315.0 km2 a−1; R2 = 0.69, p < 0.01) and tropical rainforest its relationship with forest fres (represented by burned zone (38.8 km2 a−1; R2 = 0.66, p < 0.01), but the loss of forest areas) at the country- and forest-zone levels. We quanti- decreased in the cold temperate deciduous coniferous forest fed trends in forest loss during 2003–2015 using linear zone (− 70.8 km2 year−1; R2 = 0.75, p < 0.01) and the temper- regression analysis and assessed the relation between forest ate deciduous mixed broadleaf and coniferous forest zone (− 14.4 km2 a−1; R2 = 0.45, p < 0.05). We found that 1.0% of China’s area had a signifcant positive correlation (r ≥ 0.55, Project Funding: This research was funded by the National p < 0.05) with burned areas and 0.3% had a signifcant nega- Science Foundation of China under Grant Numbers 31570462 r p and 41701514 and the Scientifc and Technological Research tive correlation ( ≤ − 0.55, < 0.05). In particular, forest Project of the Jiangxi Provincial Department of Education under loss had a signifcant positive relationship with the burned Grant Number GJJ160275. area in the cold temperate deciduous coniferous forest zone (16.9% of the lands) and the subtropical evergreen broadleaf The online version is available at http://www.sprin gerli nk.com. forest zone (7.8%). These results provide a basis for future Corresponding editor: Yanbo Hu. predictions of fre-induced forest loss in China. * Zhiwei Wu Keywords Forest loss · Forest fre · Burned area · [email protected] Spatiotemporal variability · Correlation analysis * Yanlong Shan [email protected] 1 Key Laboratory of Poyang Lake Wetland and Watershed Introduction Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, People’s Republic of China 2 Forests play a vital role in the maintenance of the Earth’s School of Geography and Environment, Jiangxi Normal ecological balance and mitigation of climate change (Bonan University, Nanchang 330022, People’s Republic of China 3 2008), but forest loss is widespread in various countries Jiangxi Provincial Key Laboratory of Poyang Lake (Hansen et al. 2013; Da Ponte et al. 2017; Harris et al. Comprehensive Management and Resource Development, Jiangxi Normal University, Nanchang 330022, 2017). Studies based on ground observations and satellite People’s Republic of China data have shown that global forest loss has been remarkably 4 Forestry College, Beihua University, Jilin 132013, high over the last decade (Hansen et al. 2013; Heino et al. People’s Republic of China 2015; Keenan et al. 2015). For example, global forest loss Vol.:(0123456789)1 3 Z. Wu et al. was ~ 0.19 million km2 a−1 during 2000–2012 (Hansen et al. vegetation conditions and fre regimes considered (Perry 2013). Forest loss has a signifcant impact on ecological pro- et al. 2012; Reilly et al. 2018). Consequently, evaluating cesses and functions of forest ecosystems (e.g., biodiversity forest loss and fre relationships at diferent spatial scales is loss and ecosystem service reduction) (Foley et al. 2007; essential. Accordingly, we conducted our study at two spatial Betts et al. 2017) and environments (e.g., greenhouse gases scales: (1) all of China and (2) six forest zones throughout emission) (van der Werf et al. 2009; Chiriaco et al. 2013). China. Thus, there is a need to elucidate the spatiotemporal pat- National-level forest and fre inventory data have not terns, trends, and drivers of forest loss (Molin et al. 2017; been freely available to the public or are often incomplete Curtis et al. 2018) because such loss is an important compo- (Lehtomaki et al. 2015; Fornacca et al. 2017), especially for nent of global changes (Trumbore et al. 2015). remote and less-populated areas. In contrast, global observa- Fire has long been considered a major driver of spati- tions using sensors on space-borne satellites have provided otemporal changes in forest loss (Curtis et al. 2018; Reilly multiple regional or global thematic forest and fre data sets et al. 2018). For example, about 67 × 106 ha of forests burned (e.g., the Global Forest Change products and MODIS fre annually worldwide during 2003–2012 (van Lierop et al. products) (Giglio et al. 2010; Hansen et al. 2013), which are 2015). Moreover, studies have suggested that fre frequency usually freely available to the public. Consequently, satellite and the area burned could substantially increase with the imagery data have been widely used to monitor forests and prolonged growing seasons predicted with warming climates fre dynamics at large spatial and temporal scales (Sannier (Liu et al. 2010; Wotton et al. 2010; Abatzoglou and Wil- et al. 2016), especially in areas where spatial and tempo- liams 2016). Such altered fre regimes will likely increase ral forest and fre inventory data are lacking or not publicly forest loss because the efects of fres will be amplifed in available (Fornacca et al. 2017), as is the case for China. warmer, drier climates (Stephens et al. 2013; Brando et al. In this study, we combined multi-sensor satellite observa- 2014). Thus, in this study, we focused on the role of fre in tions to estimate trends in forest loss and its linkage to fre shaping spatiotemporal patterns of forest loss, which may (herein represented by the burned area) during 2003–2015 help to elucidate the vulnerability of forests to fre and their across China and in six forest zones, including a group of resilience after a fre event (Tepley et al. 2017). vegetation zones not dominated by forests, in China. Spe- Forest fres occur frequently in China (Adams and Shen cifcally, the aims of this study were to (1) investigate spati- 2015; Chen et al. 2017). For example, about 78.6% of the otemporal patterns of forest loss in China, (2) analyze rela- land in China was afected by fre during 2001–2016 (Chen tionships between forest loss and burned area, and (3) assess et al. 2017). Fires have caused substantial loss of forests variations in the forest loss–burned area relationships among in China. For example, on 6 May 1987, a fre in the boreal forest zones. forests of northeastern China burned ~ 1.3 × 106 ha and signifcantly afected forest resources and the environment (Xiao et al. 1988; Cahoon et al. 1994). Although the pat- Materials and methods terns and drivers (e.g., urban expansion) of forest loss have been examined in some regions of China (Jia et al. 2015; Forest zones and fre regimes in China Zhai et al. 2017; Zhou et al. 2017), an understanding of the efects of fres on forest loss on a national scale for China is China has fve forest zones: (I) cold temperate deciduous still lacking. Filling this gap in our knowledge will increase coniferous forest zone (low fre frequency but high aver- the accuracy of predictions of future trends in forest change age burned area); (II) temperate deciduous mixed broadleaf (loss or gain) in China. and coniferous forest zone; (III) warm temperate deciduous China’s climate ranges from tropical to arctic and from broadleaf-mixed forest zone (low forest coverage and low rainy to extremely dry, and forest ecosystems range from forest fre frequency); (IV) subtropical evergreen broadleaf subtropical to boreal forests (Piao et al. 2004), resulting in forest zone (high coverage and fre frequency, but low aver- diverse fre regimes (Chen et al. 2017). For example, smaller age burned area); and (V) tropical rainforest zone (high for- fres occur most frequently in the hot, humid subtropical est coverage, but low fre frequency). There are three other evergreen broadleaf forests of southern China. In contrast, vegetation zones in China that are not typically dominated fres in the cold temperate deciduous coniferous forests of by forests: temperate grasslands (low fre frequency, but high northeastern China usually account for the majority of the average burned area), temperate steppes and desert region, burned area in the country (Tian et al. 2013; Chang et al. and Qinghai–Xizang plateau alpine region (very low forest 2015). Studies have shown that forest loss to fres may be coverage and rare fres) (Guo et al. 2017). Because these positive, negative, or unrelated, depending largely on the three vegetation zones have also experienced forest loss 1 3 Spatiotemporal changes in forest loss and its linkage to burned areas in China Fig. 1 Spatial distribution of forest zones and types in China. Zones: I, cold temper- ate deciduous coniferous forest zone; II, temperate deciduous mixed broadleaf and coniferous forest zone; III, warm temper- ate deciduous broadleaf-mixed forest zone; IV, subtropical evergreen broadleaf forest zone; V, tropical rainforest zone; VI, vegetation zones in China that are not typically dominated by forests during our study period (2003–2015), we included them Data sources in our data analyses.