全球历史森林数据中国区域的可靠性评估

doi:10.11821/dlxb201905007

Abstract

Abstract:

Global historical land use datasets play a quite significant role in gaining a profound understanding of the global or regional environmental change. As an important component of these global datasets, the reliability of historical forest data at the regional scale is rarely assessed. Based on the Chinese historical forest dataset (CHFD) that is reestablished by Chinese scholars using historical documents, we conducted an evaluation of the reliability of China's forest data within these global datasets (SAGE, PJ and KK10) adopting comparative analysis from three aspects, including the change tendency of forest area, the area of forestland, and the differences at grid scale. The results indicated that: (1) Although Chinese forest area from multiple datasets was decreasing, there was a large difference in the quantity of forest area. Specifically, the forest area of China from 1700-1990 in SAGE dataset was 20%-40% greater than that in CHFD, while the forest area of China in KK10 dataset from 1700-1850 was approximately 32%-46% greater than that in CHFD. Due to the adoption of regional research results, the total forest area of China within PJ dataset was closen to CHFD, and the quantitative biases of most years were less than 20%. (2) At provincial scale, in terms of the PJ dataset which was relatively close to the CHFD, the proportion of the provinces with large difference in the changing trend was 84%, and the proportion of the provinces with large difference in the quantity could be up to 92%. (3) At grid cell scale, the percentage of grid cells having biases greater than 70% accounted for up to 60%-80%. Therefore, there was an apparent discrepancy of spatiotemporal dynamic patterns between PJ and CHFD datasets. (4) These global datasets failed to reveal the process and pattern characteristics of Chinese forest dynamics in an objective way. The major reasons were that different data sources were used in reconstructing historical forest data within global and regional datasets, and different reconstruction methods at different spatial scales were adopted.

Key words: historical forest, global datasets, reliability assessment, China

YANG Fan,HE Fanneng,LI Meijiao,LI Shicheng. Reliability assessment of global historical forest data in China[J].Acta Geographica Sinica, 2019, 74(5): 923-934.

Figures/Tables 6

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References 31

[1]	Watson R T N I R, Bolin B , et al. Land use, land-use change, and forestry//IPCC Special Report-Summary for Policymakers. IPCC, 2000.
[2]	Foley J A, Defries R, Asner G P , et al. Global consequences of land use. Science, 2005,309(5734):570-574. doi: 10.1126/science.1111772
[3]	Ellis E C, Kaplan J O, Fuller D Q , et al. Used planet: A global history. Proceedings of the National Academy of Sciences of the United States of America, 2013,110(20):7978-7985. doi: 10.1073/pnas.1217241110
[4]	Darby H C. The clearing of the woodland in Europe//Thomas J W L. Man's Role in Changing the Face of the Earth. Chicago: University of Chicago Press, 1956.
[5]	Hughes J D, Thirgood J V . Deforestation, erosion, and forest management in ancient Greece and Rome. Journal of Forest History, 1982,26(2):60-75.
[6]	Werf G R V D, Morton D C, Defries R S , et al. CO₂ emissions from forest loss. Nature Geoscience, 2009,2(11):737-738. doi: 10.1038/ngeo671
[7]	Houghton R A . Carbon Flux to the Atmosphere from Land-use Changes: 1850 To 1990. Office of Scientific & Technical Information Technical Reports, 2001.
[8]	House J I, Prentice I C, Quéré C L . Maximum impacts of future reforestation or deforestation on atmospheric CO₂. Global Change Biology, 2002,8(11):1047-1052. doi: 10.1046/j.1365-2486.2002.00536.x
[9]	Clawson M . Forests in the long sweep of american history. Science, 1979,204(4398):1168-1174. doi: 10.1126/science.204.4398.1168
[10]	Kaplan J O, Krumhardt K M, Zimmermann N . The prehistoric and preindustrial deforestation of Europe. Quaternary Science Reviews, 2009,28(27/28):3016-3034. doi: 10.1016/j.quascirev.2009.09.028
[11]	Tian H, Banger K, Bo T , et al. History of land use in India during 1880-2010: Large-scale land transformations reconstructed from satellite data and historical archives. Global and Planetary Change, 2014,121:78-88. doi: 10.1016/j.gloplacha.2014.07.005
[12]	He F, Li S, Zhang X . A spatially explicit reconstruction of forest cover in China over 1700-2000. Global and Planetary Change, 2015,131:73-81. doi: 10.1016/j.gloplacha.2015.05.008
[13]	Ramankutty N, Foley J A . Estimating historical changes in global land cover: Croplands from 1700 to 1992. Global Biogeochemical Cycles, 1999,13(4):997-1027. doi: 10.1029/1999GB900046
[14]	Pongratz J, Reick C, Raddatz T , et al. A reconstruction of global agricultural areas and land cover for the last millennium. Global Biogeochemical Cycles, 2008,22(3):1-16.
[15]	Kaplan J O, Ruddiman W F, Crucifix M C , et al. Holocene carbon emissions as a result of anthropogenic land cover change. The Holocene, 2010,21(5):775-791.
[16]	Houghton R A, Hackler J L . Sources and sinks of carbon from land-use change in China. Global Biogeochemical Cycles, 2003,17(2):1034.
[17]	Brovkin V, Sitch S, Wvon B , et al. Role of land cover changes for atmospheric CO₂ increase and climate change during the last 150 years. Global Change Biology, 2004,10(8):1253-1266. doi: 10.1111/gcb.2004.10.issue-8
[18]	Kaplan J O, Krumhardt K M, Zimmermann N E . The effects of land use and climate change on the carbon cycle of Europe over the past 500 years. Global Change Biology, 2012,18(3):902-914. doi: 10.1111/j.1365-2486.2011.02580.x
[19]	He F, Vavrus S J, Kutzbach J E , et al. Simulating global and local surface temperature changes due to Holocene anthropogenic land cover change. Geophysical Research Letters, 2014,41(2):623-631. doi: 10.1002/2013GL058085
[20]	Ge Q S, Dai J H, He F N , et al. Land use changes and their relations with carbon cycles over the past 300 a in China. Science in China (Series D), 2008,51(6):871-884.
[21]	Li Beibei, Fang Xiuqi, Ye Yu , et al. Accuracy assessment of global historical cropland datasets based on regional reconstructed historical data: A case study in Northeast China. Science in China (Series D), 2010,40(8):1048-1059.
	[ 李蓓蓓, 方修琦, 叶瑜 , 等. 全球土地利用数据集精度的区域评估: 以中国东北地区为例. 中国科学(D辑), 2010,40(8):1048-1059.]
[22]	He Fanneng, Li Shicheng, Zhang Xuezhen , et al. Comparisons of reconstructed cropland area from multiple datasets for the traditional cultivated region of China in the last 300 years. Acta Geographica Sinica, 2012,67(9):1190-1200.
	[ 何凡能, 李士成, 张学珍 , 等. 中国传统农区过去300年耕地重建结果的对比分析. 地理学报, 2012,67(9):1190-1200.]
[23]	Zhang X, He F, Li S . Reconstructed cropland in the mid-eleventh century in the traditional agricultural area of China: Implications of comparisons among datasets. Regional Environmental Change, 2013,13(5):969-977. doi: 10.1007/s10113-012-0390-6
[24]	Ramankutty N, Foley J A, Hall F G , et al. ISLSCP II Historical Croplands Cover, 1700-1992. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/966. 2010.
[25]	Ramankutty N. Global Cropland and Pasture Data from 1700-2007. Available at: http://www.geog.mcgill.ca/nramankutty/Datasets/Datasets.html, 2012-06-01.
[26]	Mather A S, Fairbairn J, Needle C L . The course and drivers of the forest transition: The case of France. Journal of Rural Studies, 1999,15(1):65-90. doi: 10.1016/S0743-0167(98)00023-0
[27]	Bradshaw R H W . Past anthropogenic influence on European forests and some possible genetic consequences. Forest Ecology & Management, 2004,197(1-3):203-212.
[28]	He Fanneng, Ge Quansheng, Dai Junhu , et al. Quantitative analysis on forest dynamics of China in recent 300 years. Acta Geographica Sinica, 2007,62(1):30-40.
	[ 何凡能, 葛全胜, 戴君虎 , 等. 近300年来中国森林的变迁. 地理学报, 2007,62(1):30-40.]
[29]	Ye Y, Fang X . Spatial pattern of land cover changes across Northeast China over the past 300 years. Journal of Historical Geography, 2011,37(4):408-417. doi: 10.1016/j.jhg.2011.08.018
[30]	Wang Xiulan, Bao Yuhai . Study on the methods of land use dynamic change research. Progress in Geography, 1999,18(1):81-87. doi: 10.3969/j.issn.1007-6301.1999.01.012
	[ 王秀兰, 包玉海 . 土地利用动态变化研究方法探讨. 地理科学进展, 1999,18(1):81-87.] doi: 10.3969/j.issn.1007-6301.1999.01.012
[31]	Zhu Huiyi, Li Xiubin . Discussion on the index method of regional land use change. Acta Geographica Sinica, 2003,58(5):643-650.
	[ 朱会义, 李秀彬 . 关于区域土地利用变化指数模型方法的讨论. 地理学报, 2003,58(5):643-650.]

数据集	主要覆被类型	重建时段	时间分辨率(a)	空间分辨率
SAGE	耕地、森林、草地	1700-1992	1~50	0.5°×0.5°
PJ	耕地、牧草地、森林	800-1992	1	0.5°×0.5°
KK10	森林	8000-1850	1	5′×5′
CHFD	森林	1700-2000	5~50	10 km×10 km

年份	CHFD森林面积(万km²)	SAGE		PJ		KK10
年份	CHFD森林面积(万km²)	森林面积(万km²)	数量差异率 (%)	森林面积(万km²)	数量差异率 (%)	森林面积(万 km²)	数量差异率 (%)
1700	241.27	296.00	20.44	265.23	9.47	333.04	32.23
1720	235.58	286.40	19.53	256.30	8.43	339.63	36.58
1740	229.89	276.80	18.57	246.37	6.92	318.04	32.46
1760	222.81	267.20	18.17	236.41	5.92	311.20	33.41
1780	214.34	257.60	18.38	226.41	5.48	303.65	34.83
1800	205.87	248.00	18.62	216.35	4.97	299.10	37.35
1820	194.99	238.00	19.93	206.22	5.60	294.55	41.25
1840	184.11	228.00	21.38	195.91	6.21	292.50	46.29
1860	172.74	218.00	23.27	185.66	7.21
1880	160.88	208.00	25.69	176.21	9.10
1900	149.02	200.00	29.42	167.80	11.87
1920	133.48	190.00	35.31	158.20	16.99
1940	117.94	177.00	40.60	144.44	20.27
1960	87.88	169.00	65.39	143.98	49.37
1980	111.92	167.00	40.02	144.86	25.80

相对差异率绝对值(%)	1720年	1780年	1840年	1900年	1960年
< 10	9.32	7.59	6.47	4.81	3.05
10~30	17.14	14.51	11.73	9.47	7.18
30~50	7.97	9.70	9.85	8.05	5.04
50~70	5.71	6.39	6.24	7.14	4.81
70~90	4.66	4.81	4.74	4.21	4.66
> 90	55.19	56.99	60.98	66.32	75.27

Reliability assessment of global historical forest data in China

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