[1] YU Yue, ZHANG Fangmin, CHEN Jingming. Comparative analysis of differences of Leaf Area Index products in China. Remote Sensing Technology and Application, 38, 1239-1249(2023).

[2] ZENG Yelu, LI Jing, LIU Qinhuo. Global LAI ground validation dataset and product validation framework： A review. Advances in Earth Science, 27, 165-174(2012).

[3] WANG Xiqun, MA Lvyi, JIA Zhongkui et al. Research and application advances in Leaf Area Index（LAI）. Chinese Journal of Ecology, 24, 537-541(2005).

[4] HE Jinyou, JIA Weiwei, ZHANG Xiaoyong et al. Remote sensing estimation of forest canopy LAI using different algorithms of PROSAIL model. Journal of Northeast Forestry University, 51, 86-94(2023).

[5] CHEN X Z, MAIGNAN F, VIOVY N et al. Novel representation of leaf phenology improves simulation of Amazonian evergreen forest photosynthesis in a land surface model. Journal of Advances in Modeling Earth Systems, 12, e2018MS001565(2020).

[6] CUI Xitian, YUAN Fenghui, WANG Anzhi et al. Research progress in changes of leave photosynthetic capacities at different leaf age. World Forestry Research, 30, 18-23(2017).

[7] CHOU Shuren. Relating crop photosynthesis to remotely sensed photochemical reflectance index and Sun-induced chlorophyll fluorescence(2018).

[8] ZHENG Lujia, HUANG Zhiqun, HE Zongming et al. Influence of forest and foliar ages on the composition of stable carbon and nitrogen isotope of cunninghamia lanceolata in subtropic China. Scientia Silvae Sinicae, 51, 22-28(2015).

[9] XU X T, MEDVIGY D, JOSEPH-WRIGHT S et al. Variations of leaf longevity in tropical moist forests predicted by a trait-driven carbon optimality model. Ecology Letters, 20, 1097-1106(2017).

[10] MENEZES J, GARCIA S, GRANDIS A et al. Changes in leaf functional traits with leaf age： When do leaves decrease their photosynthetic capacity in Amazonian trees？. Tree Physiology, 42, 922-938(2022).

[11] WU J, ALBERT L P, LOPES A P et al. Leaf development and demography explain photosynthetic seasonality in Amazon evergreen forests. Science, 351, 972-976(2016).

[12] CUI Xitian, YUAN Fenghui, WANG Anzhi et al. Leaf age-related changes in photosynthesis of Quercus mongolica leaves in relation to leaf functional traits. Chinese Journal of Ecology, 36, 3160-3167(2017).

[13] SMITH M N, STARK S C, TAYLOR T C et al. Seasonal and drought-related changes in leaf area profiles depend on height and light environment in an Amazon forest. New Phytologist, 222, 1284-1297(2019).

[14] CHEN X Z, CIAIS P, MAIGNAN F et al. Vapor pressure deficit and sunlight explain seasonality of leaf phenology and photosynthesis across Amazonian evergreen broadleaved forest. Global Biogeochemical Cycles, 35, e2020GB006893(2021).

[15] LIU Yake, JIANG Xia, SU Chunhua. Analysis on the relationship between the photosynthetic characteristics of cinnamomum Camphora at different leaf ages and its main environmental factors in rocky desertification areas. Fujian Agricultural Science and Technology, 54, 48-58(2023).

[16] YANG Liran, YANG Guangrong, MA Huijie et al. Photosynthetic characteristics and its influential factors of tea cultivars in Yunnan Province. Southwest China Journal of Agricultural Sciences, 34, 19-26(2021).

[17] ZHOU Huiping, WANG Xiaobing, XU Xin et al. Photosynthetic characteristics of photinia fraseri leaves at different ages. Journal of West China Forestry Science, 49, 39-45(2020).

[18] BI Hongyan, XU Qing, WANG BING et al. Photosynthetic characteristics on different-aged leaf of quercus franchetii. Journal of West China Forestry Science, 48, 116-121(2019).

[19] LI Quanfa, WANG Baojuan. Study on photosynthetic characteristics of leaves of cinnamomum Camphora with different ages. Journal of Fujian Forestry Science and Technology, 38, 78-80(2011).

[20] HE Mingzhu. Simulating gross primary productivity by assimilating remote sensing data with a two-leaf light use efficiency model(2013).

[21] DAVIDSON E A, DE ARAÚJO A C, ARTAXO P et al. The Amazon basin in transition. Nature, 481, 321-328(2012).

[22] DE WEIRDT M, VERBEECK H, MAIGNAN F et al. Seasonal leaf dynamics for tropical evergreen forests in a process-based global ecosystem model. Geoscientific Model Development, 5, 1091-1108(2012).

[23] FARQUHAR G D, VON CAEMMERER S, BERRY J A. A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species. Planta, 149, 78-90(1980).

[24] MA Xue. Analysis on the characteristics of forest change and runoff and sediment change in the Amazon basin(2021).

[25] ZHANG Huixian. Study on vegetation response to extreme events based on passive microwave remote sensing data(2022).

[26] SU Y X, LI X Y, ZHANG C Q et al. Carbon accumulation rate peaks at 1 000 m elevation in tropical planted and regro-wth forests. One Earth, 8, 101147(2025).

[27] YIN Siyang. Comparative analysis of NPP spatial-temporal variation and its climate response in tropical forests(2017).

[28] BOTÍA S, KOMIYA S, MARSHALL J et al. The CO2 record at the Amazon tall tower observatory： A new opportunity to study processes on seasonal and inter-annual scales. Global Change Biology, 28, 588-611(2022).

[29] DEE D P, UPPALA S M, SIMMONS A J et al. The ERA-interim reanalysis： Configuration and performance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society, 137, 553-597(2011).

[30] ZHAO P, GAO L, WEI J H et al. Evaluation of ERA-interim air temperature data over the Qilian Mountains of China. Advances in Meteorology, 2020, 7353482(2020).

[31] MUÑOZ-SABATER J, DUTRA E, AGUSTÍ-PANAREDA A et al. ERA5-Land： A state-of-the-art global reanalysis dataset for land applications. Earth System Science Data, 13, 4349-4383(2021).

[32] LI B L, JIANG C Y et al. BESSv2.0： A satellite-based and coupled-process model for quantifying long-term global land–atmosphere fluxes. Remote Sensing of Environment, 295, 113696(2023).

[33] LI X, XIAO J F. Mapping photosynthesis solely from solar-induced chlorophyll fluorescence： A global， fine-resolution dataset of gross primary production derived from OCO-2. Remote Sensing, 11, 2563(2019).

[34] LIN Xiaofeng, CHEN Baozhang. Seasonal parameterization scheme of key photosynthetic parameter and simulation effect evaluation of DLM-FvCB Model. Scientia Geographica Sinica, 42, 1260-1271(2022).

[35] BERNACCHI C J, BAGLEY J E, SERBIN S P et al. Modelling C3 photosynthesis from the chloroplast to the ecosystem. Plant, 36, 1641-1657(2013).

[36] TANG Xinglin. Physiological and ecological characteristics of photosynthes is in plants based on FvCB model(2017).

[37] MEDLYN B E, DUURSMA R A, EAMUS D et al. Reconciling the optimal and empirical approaches to modelling stomatal conductance. Global Change Biology, 17, 2134-2144(2011).

[38] LIN Y S, MEDLYN B E, DUURSMA R A et al. Optimal stomatal behaviour around the world. Nature Climate Change, 5, 459-464(2015).

[39] WEISS A, NORMAN J M. Partitioning solar radiation into direct and diffuse， visible and near-infrared components. Agricultural and Forest Meteorology, 34, 205-213(1985).

[40] KIMBALL J S, THORNTON P E, WHITE M A et al. Simulating forest productivity and surface-atmosphere carbon exchange in the BOREAS study region. Tree Physiology, 17, 589-599(1997).

[41] HE M Z, JU W M, ZHOU Y L et al. Development of a two-leaf light use efficiency model for improving the calculation of terrestrial gross primary productivity. Agricultural and Forest Meteorology, 173, 28-39(2013).

[42] LIU Ying, ZHOU Shijie, JIN Jiaxin et al. A dataset of LAI and APAR based on the two-leaf model in Guizhou Province during 2001~2016. China Scientific Data, 7, 179-189(2022).

[43] LIU Jingyi, TANG Xuguang, CHANG Shouzhi et al. Application of remote sensing to inverse the forest leaf area index and regional estimation. Remote Sensing Technology and Application, 29, 18-25(2014).

[44] LI Yong, HAN Hairong, KANG Fengfeng et al. Spatial heterogeneity of photosynthetic characterisitics of pinus tabulaeformis canopy. Journal of Northeast Forestry University, 41, 32-35(2013).

[45] MA Xudong, ZHANG Sujun, SU Zhiyao et al. Community structure in relation to microtopography in a montane evergreen broadleaved forest in Chebaling National Nature Reserve. Acta Ecologica Sinica, 30, 5151-5160(2010).

[46] ZENG Xiaoyan, ZHOU Bengeng, CAO Zurong et al. Effects of different site conditions on the growth and photosynthetic characteristics of two species of Phoebe seedlings. Journal of Gansu Agricultural University, 59, 179-186(2024).

[47] YANG Yongchuan. Differentiation and maintenance of vegetation patterns along the topographical gradients in mid-subtropical hilly and lower mountainous area in East China(2005).

[48] SHENG Yanling, ZHANG Yin, QIAO Jigang. Changes of fire and the relationship with precipitation in Amazon ecological area based on GEE. Chinese Journal of Ecology, 40, 2553-2562(2021).

[49] YANG X Q, WU J P, CHEN X Z et al. A comprehensive framework for seasonal controls of leaf abscission and productivity in evergreen broadleaved tropical and subtropical forests. The Innovation, 2, 100154(2021).

[50] LI Q, CHEN X Z, YUAN W P et al. Remote sensing of seasonal climatic constraints on leaf phenology across pantropical evergreen forest biome. Earth’s Future, 9, e2021EF002160(2021).

[51] LIU L Y, CIAIS P, MAIGNAN F et al. Solar radiation triggers the bimodal leaf phenology of central African evergreen broadleaved forests. Journal of Advances in Modeling Earth Systems, 16, e2023MS004014(2024).

[52] DOUGHTY C E, GOULDEN M L. Seasonal patterns of tropical forest leaf area index and CO2 exchange. Journal of Geophysical Research： Biogeosciences, 113(2008).

[53] SALESKA S R, DIDAN K, HUETE A R et al. Amazon forests green-up during 2005 drought. Science, 318, 612(2007).

[54] CLARK D B, MERCADO L M, SITCH S et al. The Joint UK Land Environment Simulator （JULES），model description–part 2： Carbon fluxes and vegetation dynamics. Geoscientific Model Development, 4, 701-722(2011).

[55] HARPER A B, COX P M, FRIEDLINGSTEIN P et al. Improved representation of plant functional types and physiology in the Joint UK Land Environment Simulator（JULES v4.2） using plant trait information. Geoscientific Model Development, 9, 2415-2440(2016).

[56] TIAN J, YANG X Q, YUAN W P et al. A leaf age-dependent light use efficiency model for remote sensing the gross primary productivity seasonality over pantropical evergreen broadleaved forests. Global Change Biology, 30(2024).