红壤丘陵区马尾松林和湿地松林物候特征的时空变异及影响因素

doi:10.11707/j.1001-7488.LYKX20230408

摘要/Abstract

摘要：

目的: 探究马尾松林和湿地松林物候期的时空变异及影响因素，为红壤丘陵区森林碳汇时空格局精准评估与预测提供理论支撑。方法: 基于2017—2021年的数码相机时间序列数据，提取29块样地（马尾松林18块，湿地松林11块）的有效叶面积指数（LAIe）时空动态。采用有效叶面积指数的广义双重逻辑斯蒂模型确定物候期指标（生长季开始时间，SOS；生长季结束时间，EOS；生长季长度，LOS）。利用变异系数表征物候期时空变异幅度。通过皮尔逊相关分析和线性混合模型，解析气候（干旱指数、空气温度、降水量、饱和水汽压差、光合有效辐射）、土壤（土壤温湿度、土层厚度、石砾含量）和生物因子（林分密度、林下植被丰富度）对物候期的驱动作用。结果: 1) 马尾松林和湿地松林物候特征均为单峰曲线（但马尾松林无明显峰值）。与马尾松林相比，湿地松林的SOS较晚，但LAIe的季节变化幅度更大且值更高。2) 马尾松林的物候期在时空尺度上不如湿地松林稳定。马尾松林的SOS、EOS、LOS在空间上的变异系数和SOS在时间上的变异系数均大于湿地松林。3) 在年际尺度上，马尾松林的SOS和EOS分别与早春和旱季0~120 cm土层的土壤含水量呈负相关和正相关；湿地松林的EOS与旱季0~60 cm土层的土壤含水量呈正相关。4) 在空间尺度上，马尾松林物候期受林分密度、草本层物种丰富度和0~60 cm土壤石砾含量影响。结论: 马尾松林和湿地松林的物候特征在曲线峰值、SOS、LAIe变化幅度和数值大小等方面存在明显差异。湿地松林的物候期在时空尺度上更稳定。种内、种间竞争强度和土壤资源异质性共同驱动了红壤丘陵区马尾松林物候的时空变异格局。

关键词: 森林物候, 有效叶面积指数, 时空变异, 石砾含量, 竞争强度, 土壤含水量

Abstract:

Objective: The study aims to investigate the temporal-spatial variation and drivers of phenological periods in Pinus massoniana and Pinus elliottii forests, in order to provide a theoretical basis for understanding and predicting the temporal-spatial pattern of forest carbon sink in the red soil hilly region. Method: The temporal and spatial dynamics of the effective leaf area index (LAIe) were extracted from a total of 29 plots (18 for P. massoniana and 11 for P. elliottii), based on digital camera time series data collected between 2017 and 2021. A generalized double logistic model of LAIe was used to determine the phenological periods (start time of growing season, SOS; end of growing season, EOS; length of growing season, LOS). The coefficient of variation was used to characterize the spatiotemporal variation amplitude of phenological periods. Pearson correlation analysis and linear mixed model were employed to investigate the driving effects of climate (aridity index, air temperature, precipitation, saturation vapor pressure deficit, photosynthetically active radiation), soil (soil temperature and humidity, soil thickness, soil gravel content) and biological (stand density, understory vegetation richness) factors on phenological periods. Result: 1) The phenological characteristics of P. massoniana and P. elliottii forests exhibited a unimodal curve, with the former lacking an obvious peak. Compared to P. massoniana forest, the P. elliottii forest had later SOS but higher LAIe with greater amplitude of seasonal variation. 2) The phenological periods of P. massoniana forest exhibited greater variability than those of P. elliottii forest at both temporal and spatial scales. P. massoniana forest had greater spatial variation coefficients of SOS, EOS, and LOS and exhibited greate temporal variation coefficient of SOS than those in P. elliottii forest. 3) On an interannual scale, SOS and EOS in P. massoniana forest showed negative and positive correlations with soil moisture at 0–120 cm depth in early spring and dry season, while EOS in P. elliottii forest was positively correlated with soil moisture at 0–60 cm depth in dry season. 4) The spatial variation of phenological periods in P. massoniana forests was influenced by stand density, species richness in the herbaceous layer, and gravel content within the 0–60 cm soil layer. Conclusion: There are significant differences in the phenological characteristics between P. massoniana and P. elliottii forests in terms of curve peak value, SOS, and LAIe amplitude and value. The phenological period in P. elliottii forests is more stable in temporal and spatial scale. The temporal and spatial variation patterns of phenology in P. massoniana forests within the red soil hilly region are jointly influenced by intraspecific and interspecific competition intensity, as well as soil resource heterogeneity.

Key words: forest phenology, the effective leaf area index, temporal-spatial variation, gravel content, competitive intensity, soil moisture content

中图分类号:

陈炳楠,杨风亭,孟盛旺,戴晓琴,寇亮,陈奕帆,王辉民,付晓莉. 红壤丘陵区马尾松林和湿地松林物候特征的时空变异及影响因素[J]. 林业科学, 2024, 60(8): 67-78.

Bingnan Chen,Fengting Yang,Shengwang Meng,Xiaoqin Dai,Liang Kou,Yifan Chen,Huimin Wang,Xiaoli Fu. Temporal-Spatial Variation and Drivers of Phenology in Pinus massoniana and Pinus elliottii Forests in Hilly Regions with Red Soil[J]. Scientia Silvae Sinicae, 2024, 60(8): 67-78.

图/表 8

图1

表1

图2

表2

图3

图4

图5

图6

参考文献 0

	陈立新, 哈雪梅, 段文标, 等. 2022. 红松人工林优势木竞争指数影响因子. 生态学报, 42(5): 1777−1778.
	Chen L X, Ha X M, Duan W B, et al. 2022. Analysis on influencing factors of competitive index of dominant trees in Pinus koraiensis plantation. Acta Ecologica Sinica, 42(5): 1777−1787. ［in Chinese］
	高　伟, 叶功富, 郑兆飞, 等. 相似生境下马尾松与湿地松幼树的光合日动态. 中南林业科技大学学报, 2012, 32 (10): 34- 39.
	Gao W, Ye G F, Zheng Z F, et al. Diurnal dynamics of photosynthetic characteristics of Pinus massoniana and Pinus elliottii saplings under similar habitat. Journal of Central South University of Forestry & Technology, 2012, 32 (10): 34- 39.
	贾炜玮, 林　键. 黑龙江省主要林分类型林分碳储量预估模型. 东北林业大学学报, 2017, 45 (8): 30- 38. doi: 10.3969/j.issn.1000-5382.2017.08.007
	Jia W W, Lin J. Carbon stock predicting models of main forest types in Heilongjiang Province. Journal of Northeast Forestry University, 2017, 45 (8): 30- 38. doi: 10.3969/j.issn.1000-5382.2017.08.007
	侯光雷, 张洪岩, 郭　聃, 等. 长白山区植被生长季 NDVI 时空变化及其对气候因子敏感性. 地理科学进展, 2012, 31 (3): 285- 292. doi: 10.11820/dlkxjz.2012.03.003
	Hou G L, Zhang H Y, Guo D, et al. Spatial-temporal variation of NDVI in the growing season and its sensitivity to climatic factors in Changbai Mountains. Progress in Geography, 2012, 31 (3): 285- 292. doi: 10.11820/dlkxjz.2012.03.003
	胡婉仪. 六种国外松的早期生长、物候和适应性. 湖北林业科技, 1989, 1, 1- 4, 49.
	Hu W Y. Early growth, phenology and adaptation of six foreign pine species. Hubei Forestry Science and Technology, 1989, 1, 1- 4, 49.
	黄　鑫. 2021. 区域尺度马尾松生产力的空间分异、影响因素及模拟预测. 武汉: 华中农业大学.
	Huang X. 2021. Spatial differentiation, influencing factors, and simulation and prediction of P. Massoniana productivity at the regional scale. Wuhan: Huazhong Agricultural University. ［in Chinese］
	李　晖, 彭韧超, 李万凯, 等. 2019. 厦门典型树种的HJ-1A/B NDVI时序数据滤波算法及物候特性. 生态学杂志, 38(11): 3460–3471.
	Li H, Peng R Z, Li W K, et al. 2019. Filtering algorithms of HJ-1 A /B NDVI time series data and phenology of typical tree species in Xiamen. Chinese Journal of Ecology, 38(11): 3460–3471. ［in Chinese］
	刘　芳, 杨广斌. 2013. 基于鱼眼照片的森林郁闭度快速提取方法研究. 西南林业大学学报, 33(2): 71−74.
	Liu F, Yang G B. 2013. An efficient method for extracting forest canopy density from fisheye photos. Journal of Southwest Forestry University, 33(2): 71−74. ［in Chinese］
	马泽清, 刘琪璟, 徐雯佳, 等. 江西千烟洲人工林生态系统的碳蓄积特征. 林业科学, 2007, 43 (11): 1- 7. doi: 10.3321/j.issn:1001-7488.2007.11.001
	Ma Z Q, Liu Q J, Xu W J, et al. Carbon storage of artificial forest in Qianyanzhou, Jiangxi Province. Scientia Silvae Sinicae, 2007, 43 (11): 1- 7. doi: 10.3321/j.issn:1001-7488.2007.11.001
	王晓荣, 庞宏东, 胡文杰, 等. 武汉城市森林常见木本植物物候研究——以九峰国家森林公园为例. 中国农业通报, 2020, 36 (10): 39- 46.
	Wang X R, Pang H D, Hu W J, et al. Phenology research on the common ligneous species in Wuhan urban forest: an example of Jiufeng national forest park. Chinese Agricultural Science Bulletin, 2020, 36 (10): 39- 46.
	谢政锠, 曹小玉, 赵文菲, 等. 不同龄组杉木公益林林分空间结构与灌木物种多样性. 生态学杂志, 2022, 41 (8): 1466- 1473.
	Xie Z C, Cao X Y, Zhao W F, et al. Spatial structure and shrub species diversity of different aged stands of Chinese fir public welfare forests. Chinese Journal of Ecology, 2022, 41 (8): 1466- 1473.
	徐　珂. 2021. 千烟洲亚热带针叶林GPP模型优化及生态服务价值研究. 哈尔滨: 东北林业大学.
	Xu k. 2021. Research on GPP model optimization and ecological service value of subtropical coniferous forest in Qianyanzhou. Harbin: Northeast Forestry University. ［in Chinese］
	袁再健, 马东方, 聂小东, 等. 南方红壤丘陵区林下水土流失防治研究进展. 土壤学报, 2020, 57 (1): 12- 21.
	Yuan Z J, Ma D F, Nie X D, et al. Progress in research on prevention and control of soil erosion under forest in red soil hilly region of south China. Acta Pedologica Sinica, 2020, 57 (1): 12- 21.
	张明辉, 尹昀洲, 王　珂, 等. 水曲柳人工林空间结构特征对土壤养分含量的影响. 北京林业大学学报, 2023, 45 (9): 73- 82. doi: 10.12171/j.1000-1522.20220476
	Zhang M H, Yin Y Z, Wang K, et al. Effects of spatial structure characteristics of Fraxinus mandshurica plantation on soil nutrient content. Journal of Beijing Forestry University, 2023, 45 (9): 73- 82. doi: 10.12171/j.1000-1522.20220476
	张太平, 任　海, 彭少麟, 等. 1999. 湿地松(P. elliottii Engelm.)的生态生物学特征. 生态科学, (2): 10−14.
	Zhang T P, Ren H, Peng S L, et al. 1999. The Ecological and biological characteristics of P. elliottii. Ecologic Science, (2): 10−14. ［in Chinese］
	中国植物志编辑委员会. 2004. 中国植物志(第七卷). 北京: 科学出版社, 263.
	Editorial Committee of Flora of China . Chinese Academy of Science. 2004. Flora of China (7). Beijing: Science Press, 263. ［in Chinese］
	周　蕾, 迟永刚, 刘啸添, 等. 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, 2020, 40 (12): 4114- 4125.
	Zhou L, Chi Y G, Liu X T, et al. Land surface phenology tracked by remotely sensed sun-induced chlorophyll fluorescence in subtropical evergreen coniferous forests. Acta Ecologica Sinica, 2020, 40 (12): 4114- 4125.
	Babalola O, Lal R. Subsoil gravel horizon and maize root growth. Plant and Soil, 1977, 46 (2): 337- 346. doi: 10.1007/BF00010090
	Bannari A, Morin D, Bonn F, et al. A review of vegetation indices. Remote Sensing Reviews, 1995, 13 (1/2): 95- 120.
	Bequet R, Campioli M, Kint V, et al. Leaf area index development in temperate oak and beech forests is driven by stand characteristics and weather conditions. Trees, 2011, 25 (5): 935- 946. doi: 10.1007/s00468-011-0568-4
	Brown L A, Ogutu B O, Dash J. Tracking forest biophysical properties with automated digital repeat photography: a fisheye perspective using digital hemispherical photography from below the canopy. Agricultural and Forest Meteorology, 2020, 287, 107994.
	Calinger K M, Queenborough S, Curtis P S. Herbarium specimens reveal the footprint of climate change on flowering trends across north-central North America. Ecology Letters, 2013, 16 (8): 1037- 1044. doi: 10.1111/ele.12135
	Chen H S, Liu J W, Wang K L, et al. Spatial distribution of rock fragments on steep hillslopes in karst region of northwest Guangxi, China. Catena, 2011, 84 (1/2): 21- 28.
	Chen M, Melaas E K, Gray J M, et al. A new seasonal-deciduous spring phenology submodel in the Community Land Model 4.5: impacts on carbon and water cycling under future climate scenarios. Global Change Biology, 2016, 22 (11): 3675- 3688. doi: 10.1111/gcb.13326
	Chianucci F, Bajocco S, Ferrara C. Continuous observations of forest canopy structure using low-cost digital camera traps. Agricultural and Forest Meteorology, 2021, 307, 108516. doi: 10.1016/j.agrformet.2021.108516
	Chianucci F, Cutini A. Estimation of canopy properties in deciduous forests with digital hemispherical and cover photography. Agricultural and Forest Meteorology, 2013, 168, 130- 139. doi: 10.1016/j.agrformet.2012.09.002
	Chuine I. A unified model for budburst of trees. Journal of Theoretical Biology, 2000, 207 (3): 337- 347. doi: 10.1006/jtbi.2000.2178
	Cleland E E, Chuine I, Menzel A, et al. Shifting plant phenology in response to global change. Trends in Ecology & Evolution, 2007, 22 (7): 357- 365.
	Cong N, Piao S L, Chen A P, et al. Spring vegetation green-up date in China inferred from SPOT NDVI data: a multiple model analysis. Agricultural and Forest Meteorology, 2012, 165, 104- 113. doi: 10.1016/j.agrformet.2012.06.009
	Croft H, Chen J M, Luo X Z, et al. Leaf chlorophyll content as a proxy for leaf photosynthetic capacity. Global Change Biology, 2017, 23 (9): 3513- 3524. doi: 10.1111/gcb.13599
	Du Y J, Chen J R, Willis C G, et al. 2017. Phylogenetic conservatism and trait correlates of spring phenological responses to climate change in northeast China. Ecology and Evolution, 7(17): 6747–6757.
	Filippa G, Cremonese E, Migliavacca M, et al. Phenopix: a R package for image-based vegetation phenology. Agricultural and Forest Meteorology, 2016, 220, 141- 150. doi: 10.1016/j.agrformet.2016.01.006
	Fu Y H, Piao S L, Zhao H, 2014. Unexpected role of winter precipitation in determining heat requirement for spring vegetation green-up at northern middle and high latitudes. Global Change Biology, 20(12): 3743–3755.
	Gargiulo L, Mele G, Terribile F. Effect of rock fragments on soil porosity: a laboratory experiment with two physically degraded soils. European Journal of Soil Science, 2016, 67 (5): 597- 604. doi: 10.1111/ejss.12370
	Garonna I, de Jong R, Schaepman M E. Variability and evolution of global land surface phenology over the past three decades (1982–2012). Global Change Biology, 2016, 22 (4): 1456- 1468. doi: 10.1111/gcb.13168
	Ge W Y, Han J Q, Zhang D J, et al. Divergent impacts of droughts on vegetation phenology and productivity in the Yungui Plateau, southwest China. Ecological Indicators, 2021, 127, 107743. doi: 10.1016/j.ecolind.2021.107743
	Getzin S, Dean C, He F L, et al. Spatial patterns and competition of tree species in a Douglas-fir chronosequence on Vancouver Island. Ecography, 2006, 29 (5): 671- 682. doi: 10.1111/j.2006.0906-7590.04675.x
	Goulden M L, Munger J W, Fan S M, et al. Exchange of carbon dioxide by a deciduous forest: response to interannual climate variability. Science, 1996, 271 (5255): 1576- 1578. doi: 10.1126/science.271.5255.1576
	Jeong S J, Ho C H, Gim H J, et al. Phenology shifts at start vs. end of growing season in temperate vegetation over the Northern Hemisphere for the period 1982–2008. Global Change Biology, 2011, 17 (7): 2385- 2399. doi: 10.1111/j.1365-2486.2011.02397.x
	Jiang P P, Wang H M, Fu X L, et al. Elaborate differences between trees and understory plants in the deployment of fine roots. Plant and Soil, 2018, 431 (1/2): 433- 447.
	Keeling C D, Chin J F S, Whorf T P, et al. Increased activity of northern vegetation inferred from atmospheric CO₂ measurements. Nature, 1996, 382 (6587): 146- 149. doi: 10.1038/382146a0
	Keenan T F, Williams C A. The terrestrial carbon sink. Annual Review of Environment and Resources, 2018, 43, 219- 243. doi: 10.1146/annurev-environ-102017-030204
	Kenkel N C. Pattern of self-thinning in Jack pine: testing the random mortality hypothesis. Ecology, 1988, 69 (4): 1017- 1024. doi: 10.2307/1941257
	Klosterman S T, Hufkens K, Gray J M, et al. Evaluating remote sensing of deciduous forest phenology at multiple spatial scales using PhenoCam imagery. Biogeosciences, 2014, 11 (16): 4305- 4320. doi: 10.5194/bg-11-4305-2014
	Laube J, Sparks T H, Estrella N, et al, 2014. Chilling outweighs photoperiod in preventing precocious spring development. Global Change Biology, 20(1): 170-182.
	Lian X, Piao S L, Li L Z X, et al. Summer soil drying exacerbated by earlier spring greening of northern vegetation. Science Advance, 2020, 6 (1): eaax0255.
	Liu Q, Fu Y H, Zeng Z, et al. Temperature, precipitation, and insolation effects on autumn vegetation phenology in temperate China. Global Change Biology, 2016, 22 (2): 644- 656. doi: 10.1111/gcb.13081
	Ma Z Q, Hartmann H, Wang H M, et al. 2014. Carbon dynamics and stability between native Masson pine and exotic slash pine plantations in subtropical China. European Journal of Forest Research, 133(2): 307–321.
	Margalef R. 1958. Information theory in ecology. General Systematics, 3: 36-71.
	Menzel A, Sparks T H, Estrella N, et al. European phenological response to climate change matches the warming pattern. Global Change Biology, 2006, 12 (10): 1969- 1976. doi: 10.1111/j.1365-2486.2006.01193.x
	Miller F T, Guthrie R L. Classification and distribution of soils containing rock fragments in the United States. Erosion and Productivity of Soils Containing Rock Fragments, 1984, 13, 1- 6.
	Nemani R R, White M A, Thronton P, et al. Recent trends in hydrological balance have enhanced the terrestrial carbon sink in the United States. Geophysical Research Letters, 2002, 29 (10): 1468.
	Peñuelas J, Rutishauser T, Filella I. Phenology feedbacks on climate change. Science, 2009, 324 (5929): 887- 888. doi: 10.1126/science.1173004
	Piao S L, Ciais P, Friedlingstein P, et al. Net carbon dioxide losses of northern ecosystems in response to autumn warming. Nature, 2008, 451 (7174): 49- 52. doi: 10.1038/nature06444
	Piao S L, Fang J Y, Zhu B, et al. Forest biomass carbon stocks in China over the past 2 decades: estimation based on integrated inventory and satellite data. Journal of Geophysical Research, 2005, 110 (G1): G01006.
	Piao S L, Friedlingstein P, Ciais P, et al. Growing season extension and its effects on terrestrial carbon flux over the last two decades. Global Biogeochemical Cycles, 2007, 21, GB3018.
	Piao S L, Liu Q, Chen A P, et al. Plant phenology and global climate change: current progresses and challenges. Global Change Biology, 2019, 25 (6): 1922- 1940. doi: 10.1111/gcb.14619
	Poesen J, Ingelmo-Sanchez F, Mucher H. The hydrological response of soil surfaces to rainfall as affected by cover and position of rock fragments in the top layer. Earth Surface Process and Landforms, 1990, 15 (7): 653- 671. doi: 10.1002/esp.3290150707
	Poesen J, Lavee H. Rock fragments in top soils: significance and processes. Catena, 1994, 23 (1/2): 1- 28.
	Polgar C A, Primack R B. Leaf-out phenology of temperate woody plants: from trees to ecosystems. New Phytologist, 2011, 191 (4): 926- 941. doi: 10.1111/j.1469-8137.2011.03803.x
	Richardson A D, Hufkens K, Milliman T, et al. 2018. Data descriptor: tracking vegetation phenology across diverse North American biomes using PhenoCam imagery. Scientific Data, 5(1): 180028.
	Ryu Y, Sonnentag O, Nilson T, et al. How to quantify tree leaf area index in an open savanna ecosystem: a multi-instrument and multi-model approach. Agricultural and Forest Meteorology, 2010, 150 (1): 63- 76. doi: 10.1016/j.agrformet.2009.08.007
	Sakai A, Larcher W. 1987. Frost survival of plants: responses and adaptation to freezing stress. New York: Springer−Verlag.
	Sonnentag O, Hufkens K, Sterne C T, et al. Digital repeat photography for phenological research in forest ecosystems. Agricultural and Forest Meteorology, 2012, 152, 159- 177. doi: 10.1016/j.agrformet.2011.09.009
	Sparks T, Carey P. The responses of species to climate over two centuries: an analysis of the Marsham phenological record, 1736–1947. Journal of Ecology, 1995, 83 (2): 321- 329. doi: 10.2307/2261570
	Tahir M, Lv Y J, Gao L, et al. Soil water dynamics and availability for citrus and peanut along a hillslope at the Sunjia Red Soil Critical Zone Observatory (CZO). Soil & Tillage Research, 2016, 163, 110- 118.
	Walther S, Voigt M, Thum T, et al. Satellite chlorophyll fluorescence measurements reveal large-scale decoupling of photosynthesis and greenness dynamics in boreal evergreen forests. Global Change Biology, 2016, 22 (9): 2979- 2996. doi: 10.1111/gcb.13200
	Wang H J, Dai J H, Zheng J Y, et al. Temperature sensitivity of plant phenology in temperate and subtropical regions of China from 1850 to 2009. International Journal of Climatology, 2015, 35 (6): 913- 922. doi: 10.1002/joc.4026
	Wang X, Dannenberg M P, Yan D, et al. 2020. Globally consistent patterns of asynchrony in vegetation phenology derived from optical, microwave, and fluorescence satellite data. Journal of Geophysical Research: Biogeosciences, 125(7): e2020JG005732.
	White M A, Running S W, Thornton P E. The impact of growing-season length variability on carbon assimilation and evapotranspiration over 88 years in the eastern US deciduous forest. International Journal of Biometeorol, 1999, 42 (3): 139- 145. doi: 10.1007/s004840050097
	White M A, Thornton P E, Running S W, et al. A continental phenology model for monitoring vegetation responses to interannual climatic variability. Global Biogeochemical Cycles, 1997, 11 (2): 217- 234. doi: 10.1029/97GB00330
	Wielgolaski F. Phenological modifications in plants by various edaphic factors. International Journal of Biometeorology, 2001, 45 (4): 196- 202. doi: 10.1007/s004840100100
	Wu C Y, Peng J, Ciais P. et al. Increased drought effects on the phenology of autumn leaf senescence. Nature Climate Change, 2022, 12 (10): 943- 949. doi: 10.1038/s41558-022-01464-9
	Wu C Y, Wang X Y, Wang H J, et al. Contrasting responses of autumn-leaf senescence to daytime and night-time warming. Nature Climate Change, 2018, 8 (12): 1092- 1096. doi: 10.1038/s41558-018-0346-z
	Xia J Y, Niu S L, Ciais P, et al. Joint control of terrestrial gross primary productivity by plant phenology and physiology. Proceedings of the National Academy of Sciences of the United States of America, 2015, 112 (9): 2788- 2793.
	Yan H, Kou L, Wang H M, et al. Contrasting root foraging strategies of two subtropical coniferous forests under an increased diversity of understory species. Plant and Soil, 2019, 436 (1/2): 427- 438.
	Yang B, Wen X F, Sun X M. Seasonal variations in depth of water uptake for a subtropical coniferous plantation subjected to drought in an East Asian monsoon region. Agricultural and Forest Meteorology, 2015, 201, 218- 228. doi: 10.1016/j.agrformet.2014.11.020
	Yang F T, Feng Z M, Wang H M, et al. 2017. Deep soil water extraction helps to drought avoidance but shallow soil water uptake during dry season controls the inter-annual variation in tree growth in four subtropical plantations. Agricultural and Forest Meteorology, 234–235: 106-114.
	Yu G R, Chen Z, Piao S L, et al. High carbon dioxide uptake by subtropical forest ecosystems in the East Asian monsoon region. Proceedings of the National Academy of Sciences of the United States of America, 2014, 111 (13): 4910- 4915.
	Yuan M X, Zhao L, Lin A W, et al. Impacts of preseason drought on vegetation spring phenology across the Northeast China Transect. Science of the Total Environment, 2020, 738, 140297. doi: 10.1016/j.scitotenv.2020.140297
	Zeng Z Q, Wu W X, Ge Q S, et al. Legacy effects of spring phenology on vegetation growth under preseason meteorological drought in the Northern Hemisphere. Agricultural and Forest Meteorology, 2021, 310, 108630. doi: 10.1016/j.agrformet.2021.108630
	Zhang L M, Yu G R, Sun X M, et al. Seasonal variations of ecosystem apparent quantum yield (α) and maximum photosynthesis rate (Pmax) of different forest ecosystems in China. Agricultural and Forest Meteorology, 2006, 137 (3/4): 176- 187.
	Zhang W J, Wang H M, Yang F T, et al. Underestimated effects of low temperature during early growing season on carbon sequestration of a subtropical coniferous plantation. Biogeosciences, 2011, 8 (6): 1667- 1678. doi: 10.5194/bg-8-1667-2011
	Zhang Y H, Zhang M X, Niu J Z, et al. Rock fragments and soil hydrological processes: significance and progress. Catena, 2016, 147, 153- 166. doi: 10.1016/j.catena.2016.07.012
	Zhao Q, Zhu Z C, Zeng H, et al. Publisher correction: seasonal peak photosynthesis is hindered by late canopy development in northern ecosystems. Nature Plants, 2023, 9 (1): 192. doi: 10.1038/s41477-023-01342-y
	Zhu W Q, Tian H Q, Xu X F, et al. Extension of the growing season due to delayed autumn over mid and high latitudes in North America during 1982–2006. Global Ecology and Biogeography, 2012, 21 (2): 260- 271. doi: 10.1111/j.1466-8238.2011.00675.x

参数 Parameter	马尾松 P. massoniana		湿地松 P. elliottii
参数 Parameter	平均值 Mean	变异系数 CV (%)	平均值 Mean	变异系数 CV (%)
林分密度 Stand density/(tree·hm^?2)	1 089.51±65.40a	25.47	532.32±19.45b	12.12
林龄 Age/a	37a	—	37a	—
透光度 Light transmission (%)	38.07±1.18a	13.20	41.54±1.36a	10.86
胸径 Diameter at breast height/cm	15.97±0.13a	34.26	22.31±0.26b	26.69
灌木层物种丰富度 Shrubs richness	5.65±0.30a	22.39	5.35±0.31 a	19.17
草本层物种丰富度 Herbs richness	1.55±0.15a	40.13	1.45±0.20a	45.80
土层厚度 Soil thickness/cm	111±7a	24.94	141±11b	25.52
0~60 cm土层石砾含量 Soil gravel content at 0-60cm depth (%)	10.86±2.12a	89.89	3.88±1.05b	82.92

变异 Variation	马尾松 P. massoniana			湿地松 P. elliottii
变异 Variation	SOS	EOS	LOS	SOS	EOS	LOS
时间变异 Temporal variation	15.21	19.33	30.78	5.69	19.79	31.24
空间变异 Spatial variation	42.93	8.98	24.01	9.81	3.18	6.13

[1]	包广道,刘婷,张忠辉,任志彬,翟畅,丁铭铭,姜雪菲. 长白山区4种针叶林有效叶面积指数遥感精细反演及空间分布规律[J]. 林业科学, 2024, 60(5): 127-138.
[2]	艾萨迪拉·玉苏甫,玉米提·哈力克,巴比尔江·迪力夏提,雷诚,魏建新,阿不都拉·阿不力孜,崔健泺,何熙祥. 基于激光雷达数据的塔里木河下游胡杨种群空间分布格局和种内竞争关系[J]. 林业科学, 2024, 60(4): 31-39.
[3]	胡靓,邢蒙恩,房鸿嫄,刘瀚予,杜志琦,王楠,孙艳梅,范文忠,冯立超. 入侵性害虫桦潜叶蜂生活史及土壤生态适应性[J]. 林业科学, 2023, 59(5): 121-127.
[4]	李润东,田文东,于海群,李鑫豪,靳川,刘鹏,查天山,田赟. 基于数字影像的北京松山森林物候模拟及其与气象因子的关系[J]. 林业科学, 2022, 58(1): 89-97.
[5]	吴项乾,曹林,申鑫,汪贵斌,曹福亮. 基于无人机激光雷达的银杏人工林有效叶面积指数估测[J]. 林业科学, 2020, 56(1): 74-86.
[6]	沈一凡, 钱进芳, 郑小平, 袁紫倩, 黄坚钦, 温国胜, 吴家森. 山核桃中心产区林地土壤肥力的时空变化特征[J]. 林业科学, 2016, 52(7): 1-12.
[7]	周靖靖, 赵忠, 刘金良, 赵君, 赵青侠, 刘俊. 不同方法提取的快鸟影像信息估算刺槐林有效叶面积指数的精度比较[J]. 林业科学, 2015, 51(9): 24-34.
[8]	米娜, 温学发, 蔡福, 王阳, 张玉书. 季节性干旱对千烟洲人工林水分利用效率的影响[J]. 林业科学, 2014, 50(12): 24-31.
[9]	刘志理, 戚玉娇, 金光泽. 小兴安岭谷地云冷杉林叶面积指数的季节动态及空间格局[J]. 林业科学, 2013, 49(8): 58-64.
[10]	程杰;王吉斌;程积民;罗宗宽. 黄土高原柠条锦鸡儿灌木林生长的时空变异特征[J]. , 2013, 49(1): 14-20.
[11]	朱雅娟;贾志清. 秋季巴丹吉林沙漠东南缘人工梭梭林水分来源[J]. 林业科学, 2012, 48(8): 1-5.
[12]	庄家尧;杨静;李垚;张金池. 南京城郊栎林与草地不同层次土壤含水量的变化规律[J]. 林业科学, 2012, 48(12): 101-108.
[13]	王迪海;赵忠;李剑;. 黄土高原不同气候区刺槐细根表面积的差异[J]. 林业科学, 2010, 46(5): 70-76.
[14]	聂立水李吉跃戴伟. 北京西山油松栓皮栎混交林的土壤水分特征[J]. , 2007, 43(zk): 43-47.
[15]	管伟熊伟王彦辉于澎涛何常清杜阿朋刘海龙. 六盘山北侧华北落叶松树干直径生长变化及其对环境因子的响应^*[J]. 林业科学, 2007, 43(9): 1-6.