[1] Lyu A-F (吕爱锋), Tian H-Q (田汉勤), Liu Y-Q (刘永强). State of the art in quantifying fire distur-bance and ecosystem carbon cycle. Acta Ecologica Sinica (生态学报), 2005, 25(10): 2734-2743 (in Chinese) [2] Melillo JM, McGuire AD, Kicklighter DW, et al. Glo-bal climate change and terrestrial net primary production. Nature, 1993, 363: 234-2401 [3] Peng C, Apps MJ. Modelling the response of net primary productivity (NPP) of boreal forest ecosystems to changes in climate and fire disturbance regimes. Ecological Modelling, 1999, 122: 175-193 [4] Kasischke ES. Fire, Climate Change, and Carbon Cycling in the Boreal Forest. New York: Springer, 2000 [5] Hicke JA, Asner GP, Kasischke ES, et al. Post-fire response of North American boreal forest net primary productivity analyzed with satellite observations. Global Change Biology, 2003, 9: 1145-1157 [6] Pratolongo P, Vicari R, Kandus P, et al. A new method for evaluating net aboveground primary production (NAPP) of Scirpus giganteus (Kunth). Wetlands, 2005, 25: 228-232 [7] Amiro BD, MacPherson JI, Desjardins RL, et al. Post-fire carbon dioxide fluxes in the western Canadian boreal forest: Evidence from towers, aircraft and remote sen-sing. Agricultural and Forest Meteorology, 2003, 115: 91-107 [8] Veroustraete F, Sabbe H, Eerens H, et al. Estimation of carbon mass fluxes over Europe using the C-Fix model and Euroflux data. Remote Sensing of Environment, 2002, 83: 376-399 [9] Potter CS, Randerson JT, Field CB, et al. Terrestrial ecosystem production: A process model based on global satellite and surface data. Global Biogeochemical Cycles, 1993, 7: 811-841 [10] Running SW, Hunt Jr ER. 8-generalization of a forest ecosystem process model for other biomes, BIOME-BGC, and an application for global-scale models/ Ehleringer JR, Field CB, eds. Scaling Physiological Processes: Leaf to Globe. San Diego, CA, USA: Academic Press, 1993: 141-158 [11] Liu J, Chen JM, Cihlar J, et al. A process-based boreal ecosystem productivity simulator using remote sensing inputs. Remote Sensing of Environment, 1997, 62: 158-175 [12] Foley JA, Prentice IC, Ramankutty N, et al. An integrated biosphere model of land surface processes, terrestrial carbon balance, and vegetation dynamics. Global Biogeochemical Cycles, 1996, 10: 603-628 [13] Coops NC, Waring RH, Landsberg JJ. Assessing forest productivity in Australia and New Zealand using a phy-siologically-based model driven with averaged monthly weather data and satellite-derived estimates of canopy photosynthetic capacity. Forest Ecology and Management, 1998, 104: 113-127 [14] Wei Y-X (卫亚星), Wang L-W (王莉雯). Scale effect of vegetation net primary productivity models based on remote sensing. Resources Science (资源科学), 2010, 32(9): 1783-1791 (in Chinese) [15] Gao K-T (高开通), Liu P-J (刘鹏举), Tang X-M (唐小明). Forecasting forest fire risk grade of forest sub-compartment. Journal of Beijing Forestry University (北京林业大学学报), 2013, 35(4): 61-66 (in Chinese) [16] Zhao G-S (赵国帅), Wang J-B (王军邦), Fan W-Y (范文义), et al. Vegetation net primary productivity in Northeast China in 2000-2008: Simulation and seasonal change. Chinese Journal of Applied Ecology (应用生态学报), 2011, 22(3): 621-630 (in Chinese) [17] Wimberly MC, Reilly MJ. Assessment of fire severity and species diversity in the southern Appalachians using Landsat TM and ETM+ imagery. Remote Sensing of Environment, 2007, 108: 189-197 [18] Hungerford RD, Nemani RR, Running SW, et al. MTCLIM: A Mountain Microclimate Simulation Model. New York: USDA Forest Service, 1989 [19] Myneni RB, Williams DL. On the relationship between fAPAR and NDVI. Remote Sensing of Environment, 1994, 49: 200-211 [20] Huemmrich KR, Goward SN. Vegetation canopy PAR absorptance and NDVI: An assessment for ten tree species with the SAIL model. Remote Sensing of Environment, 1997, 61: 254-269 [21] Roderick ML, Noble IR, Cridland SW. Estimating woody and herbaceous vegetation cover from time series satellite observations. Global Ecology & Biogeography, 1999, 8: 501-508 [22] Li H-L (李贺丽), Luo Y (罗 毅), Xue X-P (薛晓萍), et al. Assessment of approaches for estimating fraction of photosynthetically active radiation absorbed by winter wheat canopy. Transactions of the Chinese Society of Agricultural Engineering (农业工程学报), 2011, 27(4): 201-206 (in Chinese) [23] Ruimy A, Kergoat L, Bondeau A. Comparing global models of terrestrial net primary productivity (NPP): Analysis of differences in light absorption and light-use efficiency. Global Change Biology, 1999, 5: 56-64 [24] Liu J-F (刘建峰), Xiao W-F (肖文发), Guo M-C (郭明春). Pattern analysis of net primary productivity of China terrestrial vegetation using 3-PGS model. Scientia Silvae Sinicae (林业科学), 2011, 47(5): 16-22 (in Chinese) [25] Sun L (孙 龙), Zhang Y (张 瑶), Guo Q-X (国庆喜), et al. Carbon emission and dynamic of NPP post forest fires in 1987 in Daxing’an Mountains. Scientia Silvae Sinicae (林业科学), 2009, 45(12): 100-104 (in Chinese) [26] Balzter H, Rowland CS, Saich P. Forest canopy height and carbon estimation at Monks Wood National Nature Reserve, UK, using dual-wavelength SAR interferometry. Remote Sensing of Environment, 2007, 108: 224-239 [27] Yang Q-P (杨清培), Li M-G (李鸣光), Wang B-S (王伯荪), et al. Dynamics of biomass and net primary productivity in succession of south subtropical forests in Southwest Guangdong. Chinese Journal of Applied Ecology (应用生态学报), 2003, 14(12): 2136-2140 (in Chinese) [28] Xiao S-L (肖生苓), Yang J-L (杨嘉龙). Individual tree aboveground biomass of Larix gmelinii natural forest in the northern greater Khingan mountains. Scientia Silvae Sinicae (林业科学), 2014, 50(8): 22-29 (in Chinese) [29] Meng S, Liu Q, Zhou G, et al. Aboveground tree additive biomass equations for two dominant deciduous tree species in Daxing’anling, northernmost China. Journal of Forest Research, 2017, 22: 1-8 [30] Zhao X-Y (赵晓炎), Wang C-K (王传宽), Huo H (霍 宏), et al. Variations in photosynthetic capacity and associated factors for Larix gmelinii from diverse origins. Acta Ecologica Sincica (生态学报), 2008, 28(8): 3798-3807 (in Chinese) [31] Shi L (石 磊), Sheng H-C (盛后财), Man X-L (满秀玲), et al. Rainfall redistribution and the spatial hete-rogeneity of throughfall in Larix gmelinii forest, northeast China. Journal of Nanjing Forestry University (南京林业大学学报), 2017, 41(2): 91-96 (in Chinese) [32] Wang X-W (王秀伟), Mao Z-J (毛子军). Temporal and spatial variation in gas exchange in canopy of Larix gmelinii plantation. Scientia Silvae Sinicae (林业科学), 2007, 43(11): 43-49 (in Chinese) [33] Feng X, Liu G, Chen JM, et al. Net primary productivity of China’s terrestrial ecosystems from a process model driven by remote sensing. Journal of Environmental Management, 2007, 85: 563-573 [34] White JD, Ryan KC, Key CC, et al. Remote sensing of forest fire severity and vegetation recovery. International Journal of Wildland Fire, 1996, 6: 125-136 [35] Lozano FJ, Suárez-Seoane S, Luis ED, et al. Assessment of several spectral indices derived from multi-temporal Landsat data for fire occurrence probability modelling. Remote Sensing of Environment, 2007, 107: 533-544 [36] Li M-Z (李明泽), Kang X-R (康祥瑞),Fan W-Y (范文义), et al. Burned area extraction in Huzhong forests based on remote sensing and the spatial analysis of the burned severity. Scientia Silvae Sinicae (林业科学), 2017, 53(3): 163-174 (in Chinese) [37] Liu W-G (刘卫国), Lü M-L (吕鸣伦). The method of mountain environment gradient analysis based on geographic information system and remote sensing technology. Geographical Research (地理研究), 1997, 16(3): 63-69 (in Chinese) [38] Hu H-Q (胡海清), Su Z-J (苏志杰), Wei S-J (魏书精), et al. Estimation of net primary productivity of northern great Xing’an Mountain after fire disturbance using multi-temporal remote sensing images. Forest Engineering (森林工程), 2013, 29(2): 1-7 (in Chinese) [39] Zhou GS, Wang YH, Jiang YL, et al. Estimating biomass and net primary production from forest inventory data: A case study of China’s Larix forests. Forest Ecology and Management, 2002, 169: 149-157 [40] Piao S-L (朴世荣), Fang J-Y (方精云), Guo Q-H (郭庆华). Application of CASA model to the estimation of Chinese terrestrial net primary productivity. Acta Phytoecologica Sinica (植物生态学报), 2001, 25(5): 603-608 (in Chinese) [41] Li M-Z (李明泽), Wang B (王 斌), Fan W-Y (范文义), et al. Simulation of forest net primary production and the effects of fire disturbance in northeast China. Chinese Journal of Plant Ecology (植物生态学报), 2015, 39(4): 322-332 (in Chinese) [42] Guo Z-X (国志兴), Wang Z-M (王宗明), Zhang B (张 柏), et al. Analysis of temporal-spatial characteri-stics and factors influencing vegetation NPP in northeast China from 2000 to 2006. Resources Science (资源科学), 2008, 30(8): 1226-1235 (in Chinese) [43] Ni J, Zhang XS, Scurlock MO. Synthesis and analysis of biomass and net primary productivity in Chinese forests. Annals of Forest Science, 2001, 58: 351-384 [44] Miller JD, Thode AE. Quantifying burn severity in a hete-rogeneous landscape with a relative version of the delta Normalized Burn Ratio (dNBR). Remote Sensing of Environment, 2007, 109: 66-80 [45] Han F-L (韩风林), Bu R-C (布仁仓), Chang Y (常禹), et al. Dynamics of recovery process of understory vegetation of Betula platyphylla-Larix gmelinii forest in Daxing’an Mountains after fire disturbance. Chinese Journal of Ecology (生态学杂志), 2015, 34(2): 312-318 (in Chinese) [46] Shen Z-H (沈泽昊), Zhang X-S (张新时), Jin Y-X (金义兴). Gradient analysis of the influence of mountain topography on vegetation pattern. Acta Phytoecologica Sinica (植物生态学报), 2000, 24(4): 430-435 (in Chinese) [47] Xie F-J (解伏菊), Xiao D-N (肖笃宁), Li X-Z (李秀珍), et al. Forest landscape restoration and its affec-ting factors in burned area of northern Great Xing’an Mountains: Taking forest coverage as an example. Chinese Journal of Applied Ecology (应用生态学报), 2005, 16(9): 1711-1718 (in Chinese) |