[1] CAMPBELL J E, BERRY J A, SEIBT U, et al. Large historical growth in global terrestrial gross primary production[J]. Nature, 2017, 544(7648): 84 − 87. doi:  10.1038/nature22030
[2] SUN Z, WANG X, ZHANG X, et al. Evaluating and comparing remote sensing terrestrial GPP models for their response to climate variability and CO2 trends[J]. Science of the Total Environment, 2019, 668: 696 − 713. doi:  10.1016/j.scitotenv.2019.03.025
[3] BO Y, LI X, LIU K, et al. Three decades of gross primary production (GPP) in China: variations, trends, attributions, and prediction inferred from multiple datasets and time series modeling[J]. Remote Sensing, 2022, 14(11): 2564. doi:  10.3390/rs14112564
[4] 丁仲礼, 段晓男, 葛全胜, 等. 国际温室气体减排方案评估及中国长期排放权讨论[J]. 中国科学(D辑: 地球科学), 2009, 39(12): 1659 − 1671.
[5] JANSSENS I A, FREIBAUER A, CIAIS P, et al. Europe's terrestrial biosphere absorbs 7 to 12% of European anthropogenic CO2 emissions[J]. Science, 2003, 300(5625): 1538 − 1542. doi:  10.1126/science.1083592
[6] SUN Z, WANG X, YAMAMOTO H, et al. Spatial pattern of GPP variations in terrestrial ecosystems and its drivers: Climatic factors, CO2 concentration and land-cover change, 1982–2015[J]. Ecological informatics, 2018, 46: 156 − 165. doi:  10.1016/j.ecoinf.2018.06.006
[7] KNAPP A K, CIAIS P, SMITH M D. Reconciling inconsistencies in precipitation-productivity relationships: implications for climate change[J]. New Phytologist, 2017, 214(1): 41 − 47. doi:  10.1111/nph.14381
[8] HU L, FAN W, LIU S, et al. Temporal and spatial distribution and variation of GPP in MOHE, China[C]. Fort Worth, TX, USA: IEEE, 2017.
[9] MCCARTHY J K, DWYER J M, MOKANY K. Direct climate effects are more influential than functional composition in determining future gross primary productivity[J]. Landscape Ecology, 2020, 35(4): 969 − 984. doi:  10.1007/s10980-020-00994-x
[10] QIU R, HAN G, MA X, et al. CO2 concentration, A critical factor influencing the relationship between solar-induced chlorophyll fluorescence and gross primary productivity[J]. Remote Sensing, 2020, 12(9): 1377. doi:  10.3390/rs12091377
[11] WU C, NIU Z, GAO S. Gross primary production estimation from MODIS data with vegetation index and photosynthetically active radiation in maize[J]. Journal of Geophysical Research: Atmospheres, 2010, 115: D12.
[12] SUN Z, WANG X, YAMAMOTO H, et al. The effects of spatiotemporal patterns of atmospheric CO2 concentration on terrestrial gross primary productivity estimation[J]. Climatic Change, 2020, 163(2): 913 − 930. doi:  10.1007/s10584-020-02903-2
[13] HUANG X, XIAO J, WANG X, et al. Improving the global MODIS GPP model by optimizing parameters with FLUXNET data[J]. Agricultural and Forest Meteorology, 2021, 300: 108314. doi:  10.1016/j.agrformet.2020.108314
[14] VERMA M, FRIEDL M A, LAW B E, et al. Improving the performance of remote sensing models for capturing intra-and inter-annual variations in daily GPP: An analysis using global FLUXNET tower data[J]. Agricultural and Forest Meteorology, 2015, 214: 416 − 429.
[15] JOINER J, YOSHIDA Y, ZHANG Y, et al. Estimation of terrestrial global gross primary production (GPP) with satellite data-driven models and eddy covariance flux data[J]. Remote Sensing, 2018, 10(9): 1346. doi:  10.3390/rs10091346
[16] CHEN Y, FENG X, TIAN H, et al. Accelerated increase in vegetation carbon sequestration in China after 2010: A turning point resulting from climate and human interaction[J]. Global Change Biology, 2021, 27(22): 5848 − 5864. doi:  10.1111/gcb.15854
[17] DING Z, ZHENG H, LIU Y, et al. Spatiotemporal patterns of ecosystem restoration activities and their effects on changes in terrestrial gross primary production in Southwest China[J]. Remote Sensing, 2021, 13(6): 1209. doi:  10.3390/rs13061209
[18] REZENDE LUIZ F C, ANDERSON C A, CELSO V R, et al. Impacts of land use change and atmospheric CO2 on gross primary productivity (GPP), evaporation, and climate in southern Amazon[J]. Journal of Geophysical Research: Atmospheres, 2022, 127(8): e2021JD034608.
[19] MA J, XIAO X, MIAO R, et al. Trends and controls of terrestrial gross primary productivity of China during 2000–2016[J]. Environmental Research Letters, 2019, 14(8): 084032. doi:  10.1088/1748-9326/ab31e4
[20] ZHANG Y, ZHANG C, WANG Z, et al. Vegetation dynamics and its driving forces from climate change and human activities in the Three-River Source Region, China from 1982 to 2012[J]. Science of the Total Environment, 2016, 563/564: 210 − 220.
[21] YOU N, MENG J, ZHU L, et al. Isolating the impacts of land use/cover change and climate change on the GPP in the Heihe River Basin of China[J]. Journal of Geophysical Research: Biogeosciences, 2020, 125(10): e2020JG005734.
[22] ICHII K, HASHIMOTO H, NEMANI R, et al. Modeling the interannual variability and trends in gross and net primary productivity of tropical forests from 1982 to 1999[J]. Global and Planetary Change, 2005, 48(4): 274 − 286. doi:  10.1016/j.gloplacha.2005.02.005
[23] ZHANG Y, XIAO X, GUANTER L, et al. Precipitation and carbon-water coupling jointly control the interannual variability of global land gross primary production[J]. Scientific reports, 2016, 6: 39748. doi:  10.1038/s41598-016-0001-8
[24] PAU S, DETTO M, KIM Y, et al. Tropical forest temperature thresholds for gross primary productivity[J]. Ecosphere, 2018, 9(7): e02311.
[25] ZENG Z, ESTES L, ZIEGLER A D, et al. Highland cropland expansion and forest loss in Southeast Asia in the twenty-first century[J]. Nature Geoscience, 2018, 11(8): 556 − 562. doi:  10.1038/s41561-018-0166-9
[26] QUESADA B, ARNETH A, ROBERTSON E, et al. Potential strong contribution of future anthropogenic land-use and land-cover change to the terrestrial carbon cycle[J]. Environmental Research Letters, 2018, 13(6): 064023. doi:  10.1088/1748-9326/aac4c3
[27] 覃艳. 自贸港建设背景下海南金融与外贸的关系研究[J]. 中国商论, 2021(19): 4 − 6.
[28] 熊坚, 冯婉吉, 朱罗娜. 海南自贸港建设的理论探索与实践创新——基于“双循环”新发展格局视角[J]. 管理现代化, 2021, 41(5): 61 − 67. doi:  10.19634/j.cnki.11-1403/c.2021.05.015
[29] SULLA-MENASHE D, FRIEDL M A. User guide to collection 6 MODIS land cover (MCD12Q1 and MCD12C1) product[J]. Usgs:Reston, Va, Usa, 2018, 1: 18.
[30] ZHANG Y, WANG Q, WANG Z, et al. Impact of human activities and climate change on the grassland dynamics under different regime policies in the Mongolian Plateau[J]. Science of the Total Environment, 2020, 698: 134304. doi:  10.1016/j.scitotenv.2019.134304
[31] RUNNING S W, ZHAO M. Daily GPP and annual NPP (MOD17A2/A3) products NASA Earth Observing System MODIS land algorithm[J]. MOD17 User′s Guide, 2015: 1-28.
[32] LI Y, ZHANG Y, LV J. Interannual variations in GPP in forest ecosystems in Southwest China and regional differences in the climatic contributions[J]. Ecological Informatics, 2022, 69: 101591. doi:  10.1016/j.ecoinf.2022.101591
[33] SUN W, MU X, SONG X, et al. Changes in extreme temperature and precipitation events in the Loess Plateau (China) during 1960–2013 under global warming[J]. Atmospheric Research, 2016, 168: 33 − 48. doi:  10.1016/j.atmosres.2015.09.001
[34] SUN W, SHAO Q, LIU J, et al. Assessing the effects of land use and topography on soil erosion on the Loess Plateau in China[J]. CATENA, 2014, 121: 151 − 163. doi:  10.1016/j.catena.2014.05.009
[35] ALDUCHOV O A, ESKRIDGE R E. Improved magnus form approximation of saturation vapor pressure[J]. Journal of Applied Meteorology, 1996, 35(4): 601 − 609. doi:  10.1175/1520-0450(1996)035<0601:IMFAOS>2.0.CO;2
[36] LIANG S, ZHAO X, LIU S, et al. A long-term global land surface satellite (GLASS) data-set for environmental studies[J]. 国际数字地球学报(英文), 2013, 6(S1): 5 − 33. doi:  10.1080/17538947.2013.805262

LIANG S, ZHAO X, LIU S, et al. A long-term global land surface satellite (GLASS) data-set for environmental studies[J]. International Journal of Digital Earth, 2013, 6(sup1): 5-33. doi:  10.1080/17538947.2013.805262
[37] DING Z, ZHENG H, LI H, et al. Afforestation-driven increases in terrestrial gross primary productivity are partly offset by urban expansion in Southwest China[J]. Ecological Indicators, 2021, 127: 107641. doi:  10.1016/j.ecolind.2021.107641
[38] ZHENG J, WU W, YU L, et al. Coconut trees detection on the tenarunga using high-resolution satellite images and deep learning[C]//2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS. IEEE, 2021: 6512-6515.
[39] YI Z F, CANNON C H, CHEN J, et al. Developing indicators of economic value and biodiversity loss for rubber plantations in Xishuangbanna, southwest China: a case study from Menglun township[J]. Ecological Indicators, 2014, 36: 788 − 797. doi:  10.1016/j.ecolind.2013.03.016
[40] 王雪芳. 海南省霸王岭国有林场生态保护对策研究[D]. 长沙: 中南林业科技大学, 2016
[41] 胡会峰, 刘国华. 中国天然林保护工程的固碳能力估算[J]. 生态学报, 2006, 26(1): 291 − 296. doi:  10.3321/j.issn:1000-0933.2006.01.035
[42] 许涵, 李意德, 骆土寿, 等. 达维台风对海南尖峰岭热带山地雨林群落的影响[J]. 植物生态学报, 2008, 32(6): 1323. doi:  10.3773/j.issn.1005-264x.2008.06.013
[43] DELGADO R C, PEREIRA M G, TEODORO P E, et al. Seasonality of gross primary production in the Atlantic Forest of Brazil[J]. Global Ecology and Conservation, 2018, 14: e00392. doi:  10.1016/j.gecco.2018.e00392
[44] CUI W, XIONG Q, ZHENG Y, et al. A study on the vulnerability of the gross primary production of rubber plantations to regional short-term flash drought over Hainan Island[J]. Forests, 2022, 13(6): 893. doi:  10.3390/f13060893
[45] NIU Z, YAN H, LIU F. Decreasing cropping intensity dominated the negative trend of cropland productivity in southern China in 2000–2015[J]. Sustainability, 2020, 12(23): 10070. doi:  10.3390/su122310070
[46] YAN H, LIU F, QIN Y, et al. Tracking the spatio-temporal change of cropping intensity in China during 2000–2015[J]. Environmental Research Letters, 2019, 14(3): 035008. doi:  10.1088/1748-9326/aaf9c7
[47] GUO Z, ZHANG Y, DEEGEN P, et al. Economic analyses of rubber and tea plantations and rubber-tea intercropping in Hainan, China[J]. Agroforestry systems, 2006, 66(2): 117 − 127. doi:  10.1007/s10457-005-4676-2
[48] YU B, CHAO X, ZHANG J, et al. Effectiveness of nature reserves for natural forests protection in tropical Hainan: a 20 year analysis[J]. Chinese Geographical Science, 2016, 26(2): 208 − 215. doi:  10.1007/s11769-016-0800-7
[49] OLSSON P O, HELIASZ M, JIN H, et al. Mapping the reduction in gross primary productivity in subarctic birch forests due to insect outbreaks[J]. Biogeosciences, 2017, 14(6): 1703 − 1719. doi:  10.5194/bg-14-1703-2017
[50] ZHAO M, HEINSCH F A, NEMANI R R, et al. Improvements of the MODIS terrestrial gross and net primary production global data set[J]. Remote sensing of Environment, 2005, 95(2): 164 − 176. doi:  10.1016/j.rse.2004.12.011
[51] SULLA-MENASHE D, GRAY J M, ABERCROMBIE S P, et al. Hierarchical mapping of annual global land cover 2001 to present: The MODIS Collection 6 Land Cover product[J]. Remote Sensing of Environment, 2019, 222: 183 − 194. doi:  10.1016/j.rse.2018.12.013
[52] LI X, LIANG S, YU G, et al. Estimation of gross primary production over the terrestrial ecosystems in China[J]. Ecological Modelling, 2013, 261/262: 80 − 92.
[53] LI G, ZHANG F, JING Y, et al. Response of evapotranspiration to changes in land use and land cover and climate in China during 2001–2013[J]. Science of the Total Environment, 2017, 596/597: 256 − 265.