植物生态学报 ›› 2023, Vol. 47 ›› Issue (3): 319-330.DOI: 10.17521/cjpe.2022.0170
任培鑫1, 李鹏1,*(), 彭长辉1,2, 周晓路1, 杨铭霞1
收稿日期:
2022-04-28
接受日期:
2022-09-28
出版日期:
2023-03-20
发布日期:
2022-09-28
通讯作者:
李鹏
作者简介:
* (lipeng_gz@126.com)基金资助:
REN Pei-Xin1, LI Peng1,*(), PENG Chang-Hui1,2, ZHOU Xiao-Lu1, YANG Ming-Xia1
Received:
2022-04-28
Accepted:
2022-09-28
Online:
2023-03-20
Published:
2022-09-28
Contact:
LI Peng
Supported by:
摘要:
为研究洞庭湖流域植被春季光合物候和秋季光合物候的时空变化, 揭示其对气候变化的响应规律, 为亚热带植被物候模型的建立和碳收支评估提供有益参考, 该研究利用2000-2018年的日光诱导叶绿素荧光(SIF)遥感数据反演洞庭湖流域植被春季光合物候(春季光合作用开始的时间)和秋季光合物候(秋季光合作用停止的时间), 分析植被春季、秋季光合物候的时空变化趋势及其对气候变化的响应机制。研究结果: (1) 2000-2018年, 洞庭湖流域植被春季光合物候以0.75 d·a-1的速度显著提前, 秋季光合物候以0.17 d·a-1的速度呈延后趋势, 植被生长季长度以0.90 d·a-1的速度显著延长; (2)季前最高气温和最低气温是研究区春季光合物候提前的主要影响因素, 秋季光合物候与季前降水量、最低气温、辐射强度均呈正相关关系, 而与季前最高气温主要呈负相关关系; (3)研究区植被春季光合物候对气候变化的响应更敏感, 尤其是季前最低气温的升高导致常绿针叶林、常绿阔叶林、灌丛和草地的春季光合物候显著提前。洞庭湖流域植被春季光合物候提前对生长季延长起主导作用, 这表明在气候变暖的背景下, 植被春季光合物候对增强研究区碳汇功能扮演着比秋季光合物候更加重要的角色。研究区植被春季光合物候对气候变化响应更为敏感, 且气温是控制春季光合物候的主要因素, 这为常绿植被物候的模拟与预测提供了科学基础。
任培鑫, 李鹏, 彭长辉, 周晓路, 杨铭霞. 洞庭湖流域植被光合物候的时空变化及其对气候变化的响应. 植物生态学报, 2023, 47(3): 319-330. DOI: 10.17521/cjpe.2022.0170
REN Pei-Xin, LI Peng, PENG Chang-Hui, ZHOU Xiao-Lu, YANG Ming-Xia. Temporal and spatial variation of vegetation photosynthetic phenology in Dongting Lake basin and its response to climate change. Chinese Journal of Plant Ecology, 2023, 47(3): 319-330. DOI: 10.17521/cjpe.2022.0170
图2 2000-2018年洞庭湖流域植被光合物候的空间格局及频率分布。
Fig. 2 Spatial pattern and frequency distribution of vegetation photosynthetic phenology and growing season length in Dongting Lake basin from 2000 to 2018. EOP, the end date of photosynthesis; LOP, the length of photosynthesis; SOP, the start date of photosynthesis.
图3 2000-2018年洞庭湖流域植被光合物候和生长季长度变化趋势空间格局和年际变化。P代表系数为正的比例, 表示光合物候呈延后(延长)趋势; N代表系数为负的比例, 表示光合物候呈提前(缩短)趋势; 括号内为p < 0.05的统计比例。slope, 斜率。
Fig. 3 Spatial distribution patterns of the linear trend and annual variation of vegetation photosynthetic phenology and growing season length in Dongting Lake basin from 2000 to 2018. EOP, the end date of photosynthesis; LOP, the length of photosynthesis; SOP, the start date of photosynthesis. P indicated the percentage of positive coefficients, indicating that the photosynthetic phenology tends to delay (prolong); N indicated the percentage of negative coefficients, indicating that the photosynthetic phenology tends to advance (shorten); percentage of significant correlations in parentheses (p < 0.05) are provided.
图4 2000-2018年洞庭湖流域各类型植被光合物候变化趋势。正值代表物候指标延后, 负值代表物候指标提前。*, p < 0.05。
Fig. 4 Linear trends of vegetation photosynthetic phenology across the biomes in Dongting Lake basin from 2000 to 2018. EOP, the end date of photosynthesis; SOP, the start date of photosynthesis. DBF, deciduous broadleaf forest; EBF, evergreen broadleaf forest; ENF, evergreen needleleaf forest. Positive values represented the delay of phenological indicators, and negative values represented the advance of phenological indicators. *, p < 0.05.
图5 植被春季、秋季光合物候与季前气候因子偏相关性系数的空间格局及频率分布。P代表正相关比例, 表明气候因子的增加导致物候的延后; N代表负相关比例, 表明气候因子的增加导致物候的提前; 括号内为p < 0.05的统计比例。
Fig. 5 Spatial pattern and frequency distribution of partial correlation coefficient between the spring and autumn photosynthetic phenology of vegetation and preseason climatic factors. Pre, precipitation; Srad, radiation intensity; Tmax, maximum air temperature; Tmin, minimum air temperature. P means the proportion of positive correlation coefficients, indicating that the increase of climate factors led to the delay of phenology; N means the proportion of negative correlation coefficients, indicating that the increase of climate factors led to the advance of phenology; percentage of significant correlations in parentheses (p < 0.05) are provided. EOP, the end date of photosynthesis; LOP, the length of photosynthesis; SOP, the start date of photosynthesis.
图6 不同类型植被光合物候与季前气候因子的偏相关关系。*, p < 0.05; **, p < 0.01。
Fig. 6 Partial correlation coefficient between the photosynthetic phenology of different vegetation and preseason climatic factors. EOP, the end date of photosynthesis; SOP, the start date of photosynthesis. DBF, deciduous broadleaf forest; EBF, evergreen broadleaf forest; ENF, evergreen needleleaf forest. Pre, precipitation; Srad, radiation intensity; Tmax, maximum air temperature; Tmin, minimum air temperature. *, p < 0.05; **, p < 0.01.
气候因子 Climate factor | 变化速率 Rate of change | p |
---|---|---|
降水 Precipitation | -1.321 2 (mm·a-1) | 0.756 1 |
最高气温 Maximum air temperature | -0.080 8 (℃·a-1) | 0.603 5 |
最低气温 Minimum air temperature | -0.052 3 (℃·a-1) | 0.595 7 |
辐射强度 Radiation intensity | -1.211 8 (W·m-2·a-1) | 0.477 0 |
表1 落叶阔叶林区域气候因子的年际变化
Table 1 Interannual variation of climatic factors in deciduous broadleaf forest region
气候因子 Climate factor | 变化速率 Rate of change | p |
---|---|---|
降水 Precipitation | -1.321 2 (mm·a-1) | 0.756 1 |
最高气温 Maximum air temperature | -0.080 8 (℃·a-1) | 0.603 5 |
最低气温 Minimum air temperature | -0.052 3 (℃·a-1) | 0.595 7 |
辐射强度 Radiation intensity | -1.211 8 (W·m-2·a-1) | 0.477 0 |
[1] |
Bai Y, Liang SL, Yuan WP (2021). Estimating global gross primary production from sun-induced chlorophyll fluorescence data and auxiliary information using machine learning methods. Remote Sensing, 13, 963. DOI: 10.3390/rs13050963.
DOI |
[2] | Beier C, Emmett B, Gundersen P, Tietema A, Peñuelas J, Estiarte M, Gordon C, Gorissen A, Llorens L, Roda F, Williams D (2004). Novel approaches to study climate change effects on terrestrial ecosystems in the field: drought and passive nighttime warming. Ecosystems, 7, 583-597. |
[3] | Cao B, Zhang B, Ma B, Tang M, Wang GQ, Wu QH, Jia YQ (2018). Spatial and temporal characteristics analysis of drought based on SPEI in the Middle and Lower Yangtze Basin. Acta Ecologica Sinica, 38, 6258-6267. |
[曹博, 张勃, 马彬, 唐敏, 王国强, 吴乾慧, 贾艳青 (2018). 基于SPEI指数的长江中下游流域干旱时空特征分析. 生态学报, 38, 6258-6267.] | |
[4] |
Chen J, Jönsson P, Tamura M, Gu ZH, Matsushita B, Eklundh L (2004). A simple method for reconstructing a high- quality NDVI time-series data set based on the Savitzky- Golay filter. Remote Sensing of Environment, 91, 332-344.
DOI URL |
[5] | Cheng LL, Li YH, Sun HY, Zhang Y, Zhan JQ, Liu M (2019). Applicability of fitting and reconstruction method of MODIS long-time enhanced vegetation index in Beijing- Tianjin-Hebei. Transactions of the Chinese Society of Agricultural Engineering, 35, 148-158. |
[程琳琳, 李玉虎, 孙海元, 张也, 詹佳琪, 刘梅 (2019). 京津冀MODIS长时序增强型植被指数拟合重建方法适用性研究. 农业工程学报, 35, 148-158.] | |
[6] |
Estiarte M, Peñuelas J (2015). Alteration of the phenology of leaf senescence and fall in winter deciduous species by climate change: effects on nutrient proficiency. Global Change Biology, 21, 1005-1017.
DOI PMID |
[7] | Fu YH, Li XX, Zhou XX, Geng XJ, Guo YH, Zhang YR (2020). Progress in plant phenology modeling under global climate change. Science China Earth Sciences, 50, 1206-1218. |
[付永硕, 李昕熹, 周轩成, 耿晓君, 郭亚会, 张雅茹 (2020). 全球变化背景下的植物物候模型研究进展与展望. 中国科学: 地球科学, 50, 1206-1218.] | |
[8] |
He J, Yang K, Tang WJ, Lu H, Qin J, Chen YY, Li X (2020). The first high-resolution meteorological forcing dataset for land process studies over China. Scientific Data, 7, 25. DOI: 10.1038/s41597-020-0369-y.
DOI |
[9] | Hu Z, Wang HJ, Dai JH, Ge QS (2021). Using controlled experiments to investigate plant phenology in response to climate change: progress and prospects. Acta Ecologica Sinica, 41, 9119-9129. |
[胡植, 王焕炯, 戴君虎, 葛全胜 (2021). 利用控制实验研究植物物候对气候变化的响应综述. 生态学报, 41, 9119-9129.] | |
[10] |
Jeong SJ, Ho CH, Gim HJ, Brown ME (2011). Phenology shifts at start vs. end of growing season in temperate vegetation over the Northern Hemisphere for the period 1982-2008. Global Change Biology, 17, 2385-2399.
DOI URL |
[11] | Ji ZX, Pei TT, Chen Y, Qin GX, Hou QQ, Xie BP, Wu HW (2021). Vegetation phenology change and its response to seasonal climate changes on the Loess Plateau. Acta Ecologica Sinica, 41, 6600-6612. |
[吉珍霞, 裴婷婷, 陈英, 秦格霞, 侯青青, 谢保鹏, 吴华武 (2021). 黄土高原植被物候变化及其对季节性气候变化的响应. 生态学报, 41, 6600-6612.] | |
[12] | Kong DD, Zhang Q, Huang WL, Gu XH (2017). Vegetation phenology change in Tibetan Plateau from 1982 to 2013 and its related meteorological factors. Acta Geographica Sinica, 72, 39-52. |
[孔冬冬, 张强, 黄文琳, 顾西辉 (2017). 1982-2013年青藏高原植被物候变化及气象因素影响. 地理学报, 72, 39-52.]
DOI |
|
[13] |
Li C, Zhuang DF, He JF, Wen KG (2021). Spatiotemporal variations in remote sensing phenology of vegetation and its responses to temperature change of boreal forest in tundra-taiga transitional zone in the Eastern Siberia. Acta Geographica Sinica, 76, 1634-1648.
DOI |
[李程, 庄大方, 何剑锋, 文可戈 (2021). 东西伯利亚苔原—泰加林过渡带植被遥感物候时空特征及其对气温变化的响应. 地理学报, 76, 1634-1648.]
DOI |
|
[14] | Li P, Peng CH, Wang M, Luo YP, Li MX, Zhang KR, Zhang DL, Zhu QA (2018). Dynamics of vegetation autumn phenology and its response to multiple environmental factors from 1982 to 2012 on Qinghai-Tibetan Plateau in China. Science of the Total Environment, 637- 638, 855-864. |
[15] |
Li X, Fu YH, Chen S, Xiao J, Yin G, Li X, Zhang X, Geng X, Wu Z, Zhou X, Tang J, Hao F (2021). Increasing importance of precipitation in spring phenology with decreasing latitudes in subtropical forest area in China. Agricultural and Forest Meteorology, 304-305, 108427. DOI: 10.1016/j.agrformet.2021.108427.
DOI |
[16] |
Li X, Xiao JF (2019). A global, 0.05-degree product of solar- induced chlorophyll fluorescence derived from OCO-2, MODIS, and reanalysis data. Remote Sensing, 11, 517.
DOI URL |
[17] |
Li X, Xiao JF (2020). Global climatic controls on interannual variability of ecosystem productivity: similarities and differences inferred from solar-induced chlorophyll fluorescence and enhanced vegetation index. Agricultural and Forest Meteorology, 288-289, 108018. DOI: 10.1016/j.agrformet.2020.108018.
DOI |
[18] | Li XT, Guo W, Ni XN, Wei XY (2019). Plant phenological responses to temperature variation in an alpine meadow. Acta Ecologica Sinica, 39, 6670-6680. |
[李晓婷, 郭伟, 倪向南, 卫晓依 (2019). 高寒草甸植物物候对温度变化的响应. 生态学报, 39, 6670-6680.] | |
[19] | Li Y, Zhang CC, Luo WR, Gao WJ (2019). Summer maize phenology monitoring based on normalized difference vegetation index reconstructed with improved maximum value composite. Transactions of the Chinese Society of Agricultural Engineering, 35(14), 159-165. |
[李艳, 张成才, 罗蔚然, 郜文江 (2019). 基于改进最大值法合成NDVI的夏玉米物候期遥感监测. 农业工程学报, 35(14), 159-165.] | |
[20] | Li YB, Zhang YD, Gu FX, Liu SR (2019). Changes of spring phenology and sensitivity analysis in temperate grassland and desert zones of China. Forest Research, 32(4), 1-10. |
[李耀斌, 张远东, 顾峰雪, 刘世荣 (2019). 中国温带草原和荒漠区域春季物候的变化及其敏感性分析. 林业科学研究, 32(4), 1-10.] | |
[21] |
Liang HX, Huang JG, Ma QQ, Li JY, Wang Z, Guo XL, Zhu HX, Jiang SW, Zhou P, Yu BY, Luo DW (2019). Contributions of competition and climate on radial growth of Pinus massoniana in subtropics of China. Agricultural and Forest Meteorology, 274, 7-17.
DOI URL |
[22] | Lin SZ, Ge QS, Wang HJ (2021). Spatiotemporal variations in leaf-out phenology of typical European tree species and their responses to climate change. Chinese Journal of Applied Ecology, 32, 788-798. |
[林少植, 葛全胜, 王焕炯 (2021). 欧洲典型树种展叶始期的时空变化及其对气候变化的响应. 应用生态学报, 32, 788-798.]
DOI |
|
[23] |
Liu Q, Fu YH, Zeng Z, Huang M, Li X, Piao S (2016a). Temperature, precipitation, and insolation effects on autumn vegetation phenology in temperate China. Global Change Biology, 22, 644-655.
DOI URL |
[24] |
Liu Q, Fu YH, Zhu Z, Liu Y, Liu Z, Huang M, Janssens IA, Piao S (2016b). Delayed autumn phenology in the Northern Hemisphere is related to change in both climate and spring phenology. Global Change Biology, 22, 3702-3711.
DOI URL |
[25] |
Liu Q, Piao S, Janssens IA, Fu Y, Peng S, Lian X, Ciais P, Myneni RB, Peñuelas J, Wang T (2018). Extension of the growing season increases vegetation exposure to frost. Nature Communications, 9, 426. DOI: 10.1038/s41467-017-02690-y.
DOI |
[26] | Liu XT, Zhou L, Shi H, Wang SQ, Chi YG (2018). Phenological characteristics of temperate coniferous and broad-leaved mixed forests based on multiple remote sensing vegetation indices, chlorophyll fluorescence and CO2 flux data. Acta Ecologica Sinica, 38, 3482-3494. |
[刘啸添, 周蕾, 石浩, 王绍强, 迟永刚 (2018). 基于多种遥感植被指数、叶绿素荧光与CO2通量数据的温带针阔混交林物候特征对比分析. 生态学报, 38, 3482-3494.] | |
[27] |
Liu ZL, Zhang XP, Li ZX, He XG, Guan HD (2021). Relationship between droughts/floods throughout a year over the Dongting Lake Basin and atmospheric circulation and sea surface temperature over key sea areas. Tropical Geography, 41, 987-999.
DOI |
[刘仲藜, 章新平, 黎祖贤, 贺新光, 关华德 (2021). 洞庭湖流域各季节旱涝及其与大气环流和关键区海温的关系. 热带地理, 41, 987-999.]
DOI |
|
[28] |
Magney TS, Bowling DR, Logan BA, Grossmann K, Stutz J, Blanken PD, Burns SP, Cheng R, Garcia MA, Kӧhler P, Lopez S, Parazoo NC, Raczka B, Schimel D, Frankenberg C (2019). Mechanistic evidence for tracking the seasonality of photosynthesis with solar-induced fluorescence. Proceedings of the National Academy of Sciences of the United States of America, 116, 11640-11645.
DOI PMID |
[29] |
Piao S, Fang J, Zhou L, Ciais P, Zhu B (2006). Variations in satellite-derived phenology in Chinaʼs temperate vegetation. Global Change Biology, 12, 672-685.
DOI URL |
[30] |
Piao S, Tan J, Chen A, Fu YH, Ciais P, Liu Q, Janssens IA, Vicca S, Zeng Z, Jeong SJ, Li Y, Myneni RB, Peng S, Shen M, Peñuelas J (2015). Leaf onset in the northern hemisphere triggered by daytime temperature. Nature Communications, 6, 6911. DOI: 10.1038/ncomms7911.
DOI |
[31] |
Ren PX, Liu ZL, Zhou XL, Peng CH, Xiao JF, Wang SH, Li X, Li P (2021). Strong controls of daily minimum temperature on the autumn photosynthetic phenology of subtropical vegetation in China. Forest Ecosystems, 8, 31. DOI: 10.1186/s40663-021-00309-9.
DOI |
[32] |
Richardson AD, Keenan TF, Migliavacca M, Ryu Y, Sonnentag O, Toomey M (2013). Climate change, phenology, and phenological control of vegetation feedbacks to the climate system. Agricultural and Forest Meteorology, 169, 156-173.
DOI URL |
[33] | Rossi S, Burgess P, Jespersen D, Huang B (2017). Heat- induced leaf senescence associated with chlorophyll metabolism in bentgrass lines differing in heat tolerance. Crop Science, 57, S169-S178. |
[34] | Sa RG, Bao G, Bao YH, Hu RC, Jiang K (2020). Variation in the vegetation fade stage and its relationships with climate and vegetation productivity in Inner Mongolia, China. Chinese Journal of Applied Ecology, 31, 1898-1908. |
[萨日盖, 包刚, 包玉海, 胡日查, 姜康 (2020). 内蒙古植被枯黄期变化及其与气候和植被生产力的关系. 应用生态学报, 31, 1898-1908.]
DOI |
|
[35] |
Wang J, Liu DS, Ciais P, Peñuelas J (2022). Decreasing rainfall frequency contributes to earlier leaf onset in northern ecosystems. Nature Climate Change, 12, 386-392.
DOI |
[36] |
Wareing PF (1956). Photoperiodism in woody plants. Annual Review of Plant Physiology, 7, 191-214.
DOI URL |
[37] |
Wu CY, Wang XY, Wang HJ, Ciais P, Peñuelas J, Myneni RB, Desai AR, Gough CM, Gonsamo A, Black AT, Jassal RS, Ju WM, Yuan WP, Fu YS, Shen MG, et al. (2018). Contrasting responses of autumn-leaf senescence to daytime and night-time warming. Nature Climate Change, 8, 1092-1096.
DOI |
[38] | Xu WT, Wu BF, Yan CZ, Huang HP (2005). China land cover 2000 using SPOT VGT S10 data. Journal of Remote Sensing, 9, 204-214. |
[徐文婷, 吴炳方, 颜长珍, 黄慧萍 (2005). 用SPOT-VGT数据制作中国2000年度土地覆盖数据. 遥感学报, 9, 204-214.] | |
[39] |
Yang ZY, Shen MG, Jia SG, Guo L, Yang W, Wang C, Chen XH, Chen J (2017). Asymmetric responses of the end of growing season to daily maximum and minimum temperatures on the Tibetan Plateau. Journal of Geophysical Research: Atmospheres, 122, 13278-13287.
DOI URL |
[40] |
Zhang JR, Tong XJ, Zhang JS, Meng P, Li, J, Liu PR (2021). Dynamics of phenology and its response to climatic variables in a warm-temperate mixed plantation. Forest Ecology and Management, 483, 118785. DOI: 10.1016/j.foreco.2020.118785.
DOI |
[41] |
Zhang Y, Commane R, Zhou S, Williams AP, Gentine P (2020). Light limitation regulates the response of autumn terrestrial carbon uptake to warming. Nature Climate Change, 10, 739-743.
DOI |
[42] |
Zhang Y, Joiner J, Alemohammad SH, Zhou S, Gentine P (2018). A global spatially contiguous solar-induced fluorescence (CSIF) dataset using neural networks. Biogeosciences, 15, 5779-5800.
DOI URL |
[43] |
Zhang Y, Xiao XM, Jin C, Dong JW, Zhou S, Wagle P, Joiner J, Guanter L, Zhang YG, Zhang GL, Qin YW, Wang J, Moore III B (2016). Consistency between sun-induced chlorophyll fluorescence and gross primary production of vegetation in North America. Remote Sensing of Environment, 183, 154-169.
DOI URL |
[44] | Zhang ZY, Wang SH, Qiu B, Song L, Zhang YG (2019). Retrieval of sun-induced chlorophyll fluorescence and advancements in carbon cycle application. Journal of Remote Sensing, 23, 37-52. |
[章钊颖, 王松寒, 邱博, 宋练, 张永光 (2019). 日光诱导叶绿素荧光遥感反演及碳循环应用进展. 遥感学报, 23, 37-52.] | |
[45] | Zhou L, Chi YG, Liu XT, Dai XQ, Yang FT (2020). Land surface phenology tracked by remotely sensed sun-induced chlorophyll fluorescence in subtropical evergreen coniferous forests. Acta Ecologica Sinica, 40, 4114-4125. |
[周蕾, 迟永刚, 刘啸添, 戴晓琴, 杨风亭 (2020). 日光诱导叶绿素荧光对亚热带常绿针叶林物候的追踪. 生态学报, 40, 4114-4125.] | |
[46] | Zhou LM, Tucker CJ, Kaufmann RK, Slayback D, Shabanov NV, Myneni RB (2001). Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999. Journal of Geophysical Research: Atmospheres, 106, 20069-20083. |
[47] |
Zhou W, Chi YG, Zhou L (2021). Vegetation phenology in the Northern Hemisphere based on the solar-induced chlorophyll fluorescence. Chinese Journal of Plant Ecology, 45, 345-354.
DOI URL |
[周稳, 迟永刚, 周蕾 (2021). 基于日光诱导叶绿素荧光的北半球森林物候研究. 植物生态学报, 45, 345-354.] | |
[48] | Zhu KZ, Wan MW (1999). Phenology. Hunan Education Publishing House, Changsha. |
[竺可桢, 宛敏渭 (1999). 物候学. 湖南教育出版社, 长沙.] | |
[49] |
Zhu WQ, Tian HQ, Xu XF, Pan YZ, Chen GS, Lin WP (2012). Extension of the growing season due to delayed autumn over mid and high latitudes in North America during 1982-2006. Global Ecology and Biogeography, 21, 260-271.
DOI URL |
[1] | 邓文婕 吴华征 李添翔 周丽娜 胡仁勇 金鑫杰 张永普 张永华 刘金亮. 洞头国家级海洋公园主要植被类型及其特征[J]. 植物生态学报, 2024, 48(预发表): 0-0. |
[2] | 杨宇萌 来全 刘心怡. 气候变化和人类活动对内蒙古植被总初级生产力的定量影响分析[J]. 植物生态学报, 2024, 48(预发表): 0-0. |
[3] | 张慧玲, 张耀艺, 彭清清, 杨静, 倪祥银, 吴福忠. 中亚热带同质园不同生活型树种微量元素重吸收效率的差异[J]. 植物生态学报, 2023, 47(7): 978-987. |
[4] | 仲琦, 李曾燕, 马炜, 况雨潇, 邱岭军, 黎蕴洁, 涂利华. 氮添加和凋落物处理对华西雨屏区常绿阔叶林凋落叶分解的影响[J]. 植物生态学报, 2023, 47(5): 629-643. |
[5] | 李杰, 郝珉辉, 范春雨, 张春雨, 赵秀海. 东北温带森林树种和功能多样性对生态系统多功能性的影响[J]. 植物生态学报, 2023, 47(11): 1507-1522. |
[6] | 万春燕, 余俊瑞, 朱师丹. 喀斯特与非喀斯特森林乔木叶性状及其相关性网络的差异[J]. 植物生态学报, 2023, 47(10): 1386-1397. |
[7] | 魏瑶, 马志远, 周佳颖, 张振华. 模拟增温改变青藏高原植物繁殖物候及植株高度[J]. 植物生态学报, 2022, 46(9): 995-1004. |
[8] | 党宏忠, 张学利, 韩辉, 石长春, 葛玉祥, 马全林, 陈帅, 刘春颖. 樟子松固沙林林水关系研究进展及对营林实践的指导[J]. 植物生态学报, 2022, 46(9): 971-983. |
[9] | 袁春阳, 李济宏, 韩鑫, 洪宗文, 刘宣, 杜婷, 游成铭, 李晗, 谭波, 徐振锋. 树种对土壤微生物生物量碳氮的影响: 同质园实验[J]. 植物生态学报, 2022, 46(8): 882-889. |
[10] | 李肖, PIALUANG Bounthong, 康文辉, 冀晓东, 张海江, 薛治国, 张志强. 近几十年来冀西北山地白桦次生林径向生长对气候变化的响应[J]. 植物生态学报, 2022, 46(8): 919-931. |
[11] | 苏启陶, 杜志喧, 周兵, 廖永辉, 王呈呈, 肖宜安. 牯岭凤仙花及其传粉昆虫在中国的潜在分布区域分析[J]. 植物生态学报, 2022, 46(7): 785-796. |
[12] | 甘子莹, 王浩, 丁驰, 雷梅, 杨晓刚, 蔡敬琰, 丘清燕, 胡亚林. 亚热带森林不同植物及器官来源的可溶性有机质输入对土壤激发效应的影响及其作用机理[J]. 植物生态学报, 2022, 46(7): 797-810. |
[13] | 胡潇飞, 魏临风, 程琦, 吴星麒, 倪健. 青藏高原地区气候图解数据集[J]. 植物生态学报, 2022, 46(4): 484-492. |
[14] | 原媛, 母艳梅, 邓钰洁, 李鑫豪, 姜晓燕, 高圣杰, 查天山, 贾昕. 植被覆盖度和物候变化对典型黑沙蒿灌丛生态系统总初级生产力的影响[J]. 植物生态学报, 2022, 46(2): 162-175. |
[15] | 丛楠, 张扬建, 朱军涛. 北半球中高纬度地区近30年植被春季物候温度敏感性[J]. 植物生态学报, 2022, 46(2): 125-135. |
阅读次数 | ||||||
全文 |
|
|||||
摘要 |
|
|||||
Copyright © 2022 版权所有 《植物生态学报》编辑部
地址: 北京香山南辛村20号, 邮编: 100093
Tel.: 010-62836134, 62836138; Fax: 010-82599431; E-mail: apes@ibcas.ac.cn, cjpe@ibcas.ac.cn
备案号: 京ICP备16067583号-19