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森林地上生物量及其驱动因素研究进展
Advance of Forest Aboveground Biomass and Its Driving Factors

DOI: 10.12677/wjf.2024.132017, PP. 107-117

Keywords: 森林地上生物量,生物多样性,影响因素,生产力,生态系统
Forest Aboveground Biomass
, Biodiversity, Influencing Factors, Productivity, Ecosystem

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Abstract:

森林生态系统是陆地生态系统的主体,是全球碳循环的重要组成部分。森林地上生物量是森林生产力的重要衡量标准,探究森林地上生物量及其影响因素对理解陆地生态系统碳循环及应对气候变化具有重要意义。本文系统归纳了目前具有代表性的森林地上生物量研究,并对森林地上生物量估算方法及森林地上生物量影响因素的研究现状进行了梳理,总结如下:1) 目前关于森林地上生物量的研究较多,总体来说森林生物量静态储量方面研究较全面,关于生物量动态变化及其驱动因素的研究还有待补充;2) 生物量的估算方法主要包括样地调查、模型模拟和遥感,各有优缺点,后续可将多种方法结合使用,提高森林地上生物量估算的精确度和效率;3) 生物多样性与森林地上生物量的关系复杂,在研究过程中,应根据实际情况综合考虑生物和非生物因素对森林地上生物量的交互影响,以更准确理解各因素对森林地上生物量的影响机制。综上,深入探究森林地上生物量储量及动态变化,综合研究更多因素对森林地上生物量的影响机制对于在目前气候背景下制定合理的森林保护和恢复策略具有重要意义。
Forest ecosystem is the main body of terrestrial ecosystem and an important part of the global carbon cycle. Forest aboveground biomass is an important measure of forest productivity. Exploring forest aboveground biomass and its influencing factors is of great significance to understanding the carbon cycle of terrestrial ecosystems and responding to climate change. This article systematically summarizes the current representative research on forest aboveground biomass, and sorts out the research status of forest aboveground biomass estimation methods and factors affecting forest aboveground biomass. The summary is as follows: 1) Current research on forest aboveground biomass, generally speaking, research on static reserves of forest biomass is relatively comprehensive, and research on dynamic changes in biomass and its driving factors needs to be supplemented; 2) Biomass estimation methods mainly include sample plot surveys, model simulations and remote sensing, each of which has advantages and disadvantages, and multiple methods can be used in combination in the future to improve the accuracy and efficiency of forest aboveground biomass estimation; 3) The relationship between biodiversity and forest aboveground biomass is complex, and during the research process, it should be comprehensively considered based on the actual situation Interactive effects of biotic and abiotic factors on above- ground forest biomass to more accurately understand the impact mechanism of each factor on forest above-ground biomass. In summary, in-depth exploration of forest aboveground biomass reserves and dynamic changes, and comprehensive study of the impact mechanisms of more factors on forest aboveground biomass are of great significance for formulating reasonable forest protection and restoration strategies under the current climate background.

References

[1]  Pan, Y., Birdsey, R.A., Fang, J., et al. (2011) A Large and Persistent Carbon Sink in the World’s Forests. Science, 333, 988-993.
https://doi.org/10.1126/science.1201609
[2]  Beer, C., Reichstein, M., Tomelleri, E., et al. (2010) Terrestrial Gross Carbon Dioxide Uptake: Global Distribution and Covariation with Climate. Science, 329, 834-838.
https://doi.org/10.1126/science.1184984
[3]  Canadell, J.G. and Raupach, M.R. (2008) Managing Forests for Climate Change Mitigation. Science, 320, 1456-1457.
https://doi.org/10.1126/science.1155458
[4]  Montagu, K.D., Duttmer, K., Barton, C.V.M. and Cowie, A.L. (2005) Developing General Allometric Relationships for Regional Estimates of Carbon Sequestration—An Example Using ‘Eucalyptus Pilularis’ from Seven Contrasting Sites. Forest Ecology and Management, 204, 115-129.
https://doi.org/10.1016/j.foreco.2004.09.003
[5]  Houghton, R.A. (2005) Aboveground Forest Biomass and the Global Carbon Balance. Global Change Biology, 11, 945-958.
[6]  Fahey, T.J., Woodbury, P.B., Battles, J.J., et al. (2010) Forest Carbon Storage: Ecology, Management, and Policy. Frontiers in Ecology and the Environment, 8, 245-252.
https://doi.org/10.1890/080169
[7]  Davidson, E.A. AND Janssens, I.A. (2006) Temperature Sensitivity of Soil Carbon Decomposition and Feedbacks to Climate Change. Nature, 440, 165-173.
https://doi.org/10.1038/nature04514
[8]  Lin, D., Lai, J., Muller-Landau, H.C., et al. (2012) Topographic Variation in Aboveground Biomass in a Subtropical Evergreen Broad-Leaved Forest in China. PLOS ONE, 7, e48244.
https://doi.org/10.1371/journal.pone.0048244
[9]  Kloeppel, B., Harmon, M. AND Fahey, T. (2007) Estimating Aboveground Net Primary Productivity in Forest-Domi-nated Ecosystems. In: Kloeppel, B., Harmon, M. and Fahey, T., Eds., Principles and Standards for Measuring Primary Production, Oxford University Press, Oxford, 63-81.
https://doi.org/10.1093/acprof:oso/9780195168662.003.0005
[10]  Houghton, R.A. (2005) Aboveground Forest Biomass and the Global Carbon Balance. Global Change Biology, 11, 945-958.
https://doi.org/10.1111/j.1365-2486.2005.00955.x
[11]  Poorter, L., Van Der Sande, M.T., Thompson, J., et al. (2015) Diversity Enhances Carbon Storage in Tropical Forests. Global Ecology and Biogeography, 24, 1314-1328.
https://doi.org/10.1111/geb.12364
[12]  Ali, A., Lin, S., He, J., et al. (2019) Elucidating Space, Climate, Edaphic, and Biodiversity Effects on Aboveground Biomass in Tropical Forests. Land Degradation & Development, 30, 918-927.
https://doi.org/10.1002/ldr.3278
[13]  Xu, Y., Franklin, S.B., Wang, Q., et al. (2015) Topographic and Biotic Factors Determine Forest Biomass Spatial Distribution in a Subtropical Mountain Moist Forest. Forest Ecology Management, 357, 95-103.
https://doi.org/10.1016/j.foreco.2015.08.010
[14]  Bordin, K.M., Esquivel-Muelbert, A., Bergamin, R.S., et al. (2021) Climate and Large-Sized Trees, but Not Diversity, Drive Above-Ground Biomass in Subtropical Forests. Forest Ecology and Management, 490, Article ID: 119126.
https://doi.org/10.1016/j.foreco.2021.119126
[15]  Glatthorn, J., Feldmann, E., Pichler, V., et al. (2018) Biomass Stock and Productivity of Primeval and Production Beech Forests: Greater Canopy Structural Diversity Promotes Productivity. Ecosystems, 21, 704-722.
https://doi.org/10.1016/j.foreco.2021.119126
[16]  Hilmers, T., Avdagi?, A., Bartkowicz, L., et al. (2019) the Productivity of Mixed Mountain Forests Comprised of Fagus sylvatica, Picea abies, and Abies alba Across Europe. Forestry: An International Journal of Forest Research, 92, 512-522.
https://doi.org/10.1093/forestry/cpz035
[17]  Yuan, Z., Wang, S., Ali, A., et al. (2018) Aboveground Carbon Storage Is Driven by Functional Trait Composition and Stand Structural Attributes Rather than Biodiversity in Temperate Mixed Forests Recovering from Disturbances. Annals of Forest Science, 75, Article No. 67.
https://doi.org/10.1007/s13595-018-0745-3
[18]  Kumar, L. and Mutanga, O. (2017) Remote Sensing of Above-Ground Biomass. Remote Sensing, 9, Article 935.
https://doi.org/10.3390/rs9090935
[19]  Su, Y., Guo, Q., Xue, B., et al. (2015) Spatial Distribution of Forest Aboveground Biomass in China: Estimation through Combination of Spaceborne Lidar, Optical Imagery, and Forest Inventory Data. Remote Sensing of Environment, 173, 187-199.
https://doi.org/10.1016/j.rse.2015.12.002
[20]  Fang, J., Chen, A., Peng, C., et al. (2001) Changes in Forest Biomass Carbon Storage in China between 1949 and 1998. Science, 292, 2320-2322.
https://doi.org/10.1126/science.1058629
[21]  Dong, L.H., Zhang, L. and Li, F. (2016) Developing Two Additive Biomass Equations for Three Coniferous Plantation Species in Northeast China. Forests, 7, Article 136.
https://doi.org/10.3390/f7070136
[22]  Tadese, S., Soromessa, T., Bekele, T., et al. (2020) Above Ground Biomass Estimation Methods and Challenges: A Review. International Journal of Energy Technology and Policy, 9, 12-25.
[23]  Návar, J. (2009) Allometric Equations for Tree Species and Carbon Stocks for Forests of Northwestern Mexico. Forest Ecology and Management, 257, 427-434.
https://doi.org/10.1016/j.foreco.2008.09.028
[24]  Picard, N., Saint-André, L. and Henry, M. (2012) Manual for Building Tree Volume and Biomass Allometric Equations: From Field Measurement to Prediction. Food and Agricultural Organization of the United Nations and Centre de Coopération Internationale en Recherche Agronomique Pour le Développement, Rome, Montpellier.
[25]  Montès, N., Gauquelin, T., Badri, W., et al. (2000) A Non-Destructive Method for Estimating Above-Ground Forest Biomass in Threatened Woodlands. Forest Ecology and Management, 130, 37-46.
https://doi.org/10.1016/S0378-1127(99)00188-7
[26]  Zeng, W., Tomppo, E., Healey, S.P., et al. (2015) The National Forest Inventory in China: History-Results-International Context. Forest Ecosystems, 2, 23-39.
https://doi.org/10.1186/s40663-015-0047-2
[27]  Tomppo, E., Gschwantner, T., Lawrence, M., et al. (2010) National Forest Inventories: Pathways for Common Reporting. Springer, Dordrecht.
https://doi.org/10.1007/978-90-481-3233-1
[28]  Lu, D., Chen, Q., Wang, G., et al. (2016) A Survey of Remote Sensing-Based Aboveground Biomass Estimation Methods in Forest Ecosystems. International Journal of Digital Earth, 9, 63-105.
https://doi.org/10.1080/17538947.2014.990526
[29]  赵敏, 周广胜. 中国森林生态系统的植物碳贮量及其影响因子分析[J]. 地理科学, 2004, 24(1): 50-54.
[30]  Lu, D. (2006) The Potential and Challenge of Remote Sensing–Based Biomass Estimation. International Journal of Remote Sensing, 27, 1297-1328.
https://doi.org/10.1080/01431160500486732
[31]  Mutanga, O., Shoko, C., Adelabu, S., et al. (2016) Remote Sensing of Aboveground Forest Biomass: A Review. Tropical Ecology, 57, 125-132.
[32]  Bortolot, Z.J. and Wynne, R.H. (2005) Estimating Forest Biomass Using Small Footprint LiDAR Data: An Individual Tree-Based Approach That Incorporates Training Data. ISPRS Journal of Photogrammetry and Remote Sensing, 59, 342-360.
https://doi.org/10.1016/j.isprsjprs.2005.07.001
[33]  Kumar, L., Sinha, P., Taylor, S., et al. (2015) Review of the Use of Remote Sensing for Biomass Estimation to Support Renewable Energy Generation. Journal of Applied Remote Sensing, 9, Article ID: 097696.
https://doi.org/10.1117/1.JRS.9.097696
[34]  St-Onge, B., Hu, Y. and Vega, C. (2008) Mapping the Height and Above-Ground Biomass of a Mixed Forest Using Lidar and Stereo Ikonos Images. International Journal of Remote Sensing, 29, 1277-1294.
https://doi.org/10.1080/01431160701736505
[35]  Li, D., Wang, C., Hu, Y., et al. (2012) General Review on Remote Sensing-Based Biomass Estimation. Geomatics and Information Science of Wuhan University, 37, 631-635.
[36]  Vashum, K. and Jayakumar, S. (2012) Methods to Estimate Above-Ground Biomass and Carbon Stock in Natural Forests: A Review. Journal of Ecosystem & Ecography, 2, 4-11.
https://doi.org/10.4172/2157-7625.1000116
[37]  Lefsky, M.A., Cohen, W.B., Harding, D.J., et al. (2002) Lidar Remote Sensing of Above-Ground Biomass in Three Biomes. Global Ecology and Biogeography, 11, 393-399.
https://doi.org/10.1046/j.1466-822x.2002.00303.x
[38]  Zolkos, S.G., Goetz, S.J. and Dubayah, R. (2013) A Meta-Analysis of Terrestrial Aboveground Biomass Estimation Using Lidar Remote Sensing. Remote Sensing of Environment, 128, 289-298.
https://doi.org/10.1016/j.rse.2012.10.017
[39]  Sullivan, M.J.P., Lewis, S.L., Affum-Baffoe, K., et al. (2020) Long-Term Thermal Sensitivity of Earth’s Tropical Forests. Science, 368, 869-874.
https://doi.org/10.1126/science.aaw7578
[40]  Chu, C., Bartlett, M., Wang, Y., et al. (2016) Does Climate Directly Influence NPP Globally? Global Change Biology, 22, 12-24.
https://doi.org/10.1111/gcb.13079
[41]  Coomes, D.A., Flores, O., Holdaway, R., et al. (2014) Wood Production Response to Climate Change Will Depend Critically on Forest Composition and Structure. Global Change Biology, 20, 3632-3645.
https://doi.org/10.1111/gcb.12622
[42]  O’brien, E.M. (2006) Biological Relativity to Water-Energy Dynamics. Journal of Biogeography, 33, 1868-1888.
https://doi.org/10.1111/j.1365-2699.2006.01534.x
[43]  Alvarez-Davila, E., Cayuela, L., González-Caro, S., et al. (2017) Forest Biomass Density across Large Climate Gradients in Northern South America Is Related to Water Availability but Not with Temperature. PLOS ONE, 12, e0171072.
https://doi.org/10.1371/journal.pone.0171072
[44]  Allen, C.D., Macalady, A.K., Chenchouni, H., et al. (2010) A Global Overview of Drought and Heat-Induced Tree Mortality Reveals Emerging Climate Change Risks for Forests. Forest Ecology and Management, 259, 660-684.
https://doi.org/10.1016/j.foreco.2009.09.001
[45]  Vilanova, E., Ramírez-Angulo, H., Torres-Lezama, A., et al. (2018) Environmental Drivers of Forest Structure and Stem Turnover across Venezuelan Tropical Forests. PLOS ONE, 13, e0198489.
https://doi.org/10.1371/journal.pone.0198489
[46]  乐荣武, 张娜, 王晶杰, 等. 2000-2019 年内蒙古草地地上生物量的时空变化特征[J]. 中国科学院大学学报, 2022, 39(1): 21-33.
[47]  陈德祥, 李意德, Liu Heping, 等. 尖峰岭热带山地雨林生物量及碳库动态[J]. 中国科学C辑, 2010, 40(7): 596-609.
[48]  郭屹立, 王斌, 向悟生, 等. 喀斯特季节性雨林木本植物胸高断面积分布格局及其对地形因子的响应[J]. 生物多样性, 2016, 24(1): 30-39.
[49]  Mcewan, R.W., Lin, Y.C., Sun, I.F., et al. (2011) Topographic and Biotic Regulation of Aboveground Carbon Storage in Subtropical Broad-Leaved Forests of Taiwan. Forest Ecology and Management, 262, 1817-1825.
https://doi.org/10.1016/j.foreco.2011.07.028
[50]  Jucker, T., Bongalov, B., Burslem, D.F.R.P., et al. (2018) Topography Shapes the Structure, Composition and Function of Tropical Forest Landscapes. Ecology Letters, 21, 989-1000.
https://doi.org/10.1111/ele.12964
[51]  Chadwick, K.D. and Asner, G.P. (2016) Tropical Soil Nutrient Distributions Determined by Biotic and Hillslope Processes. Biogeochemistry, 127, 273-289.
https://doi.org/10.1007/s10533-015-0179-z
[52]  Paoli, G.D. (2006) Divergent Leaf Traits among Congeneric Tropical Trees with Contrasting Habitat Associations on Borneo. Journal of Tropical Ecology, 22, 397-408.
https://doi.org/10.1017/S0266467406003208
[53]  Tanner, E.V.J., Rodriguez-Sanchez, F., Healey, J.R., et al. (2014) Long-Term Hurricane Damage Effects on Tropical Forest Tree Growth and Mortality. Ecology, 95, 2974-2983.
https://doi.org/10.1890/13-1801.1
[54]  Ferry, B., Morneau, F., Bontemps, J.D., et al. (2010) Higher Treefall Rates on Slopes and Waterlogged Soils Result in Lower Stand Biomass and Productivity in a Tropical Rain Forest. Journal of Ecology, 98, 106-116.
https://doi.org/10.1111/j.1365-2745.2009.01604.x
[55]  Werner, F.A. and Homeier, J. (2015) Is Tropical Montane Forest Heterogeneity Promoted by a Resource-Driven Feedback Cycle? Evidence from Nutrient Relations, Herbivory and Litter Decomposition along a Topographical Gradient. Functional Ecology, 29, 430-440.
https://doi.org/10.1111/1365-2435.12351
[56]  Quesada, C.A., Phillips, O.L., Schwarz, M., et al. (2012) Basin-Wide Variations in Amazon Forest Structure and Function Are Mediated by Both Soils and Climate. Biogeosciences, 9, 2203-2246.
https://doi.org/10.5194/bg-9-2203-2012
[57]  Wright, S.J., Yavitt, J.B., Wurzburger, N., et al. (2011) Potassium, Phosphorus, or Nitrogen Limit Root Allocation, Tree Growth, or Litter Production in a Lowland Tropical Forest. Ecology, 92, 1616-1625.
https://doi.org/10.1890/10-1558.1
[58]  Coomes, D.A., Kunstler, G., Canham, C.D., et al. (2009) A Greater Range of Shade-Tolerance Niches in Nutrient-Rich Forests: An Explanation for Positive Richness-Productivity Relationships? Journal of Ecology, 97, 705-717.
https://doi.org/10.1111/j.1365-2745.2009.01507.x
[59]  Becknell, J.M. and Powers, J.S. (2014) Stand Age and Soils as Drivers of Plant Functional Traits and Aboveground Biomass in Secondary Tropical Dry Forest. Canadian Journal of Forest Research, 44, 604-613.
https://doi.org/10.1139/cjfr-2013-0331
[60]  Yuan, Z., Ali, A., Jucker, T., et al. (2019) Multiple Abiotic and Biotic Pathways Shape Biomass Demographic Processes in Temperate Forests. Ecology, 100, e02650.
https://doi.org/10.1002/ecy.2650
[61]  Malhi, Y., Wood, D., Baker, T.R., et al. (2006) The Regional Variation of Aboveground Live Biomass in Old-Growth Amazonian Forests. Global Change Biology, 12, 1107-1138.
https://doi.org/10.1111/j.1365-2486.2006.01120.x
[62]  Malhi, Y. (2012) The Productivity, Metabolism and Carbon Cycle of Tropical Forest Vegetation. Journal of Ecology, 100, 65-75.
https://doi.org/10.1111/j.1365-2745.2011.01916.x
[63]  Prado-Junior, J.A., Schiavini, I., Vale, V.S., et al. (2016) Conservative Species Drive Biomass Productivity in Tropical Dry Forests. Journal of Ecology, 104, 817-827.
https://doi.org/10.1111/1365-2745.12543
[64]  朱杰, 吴安驰, 邹顺, 等. 南亚热带常绿阔叶林树木多样性与生物量和生产力的关联及其影响因素[J]. 生物多样性, 2021, 29(11): 1435-1446.
[65]  Frank, D., Reichstein, M., Bahn, M., et al. (2015) Effects of Climate Extremes on the Terrestrial Carbon Cycle: Concepts, Processes and Potential Future Impacts. Global Change Biology, 21, 2861-2880.
https://doi.org/10.1111/gcb.12916
[66]  Huang, K., Wang, S., Zhou, L., et al. (2013) Effects of Drought and Ice Rain on Potential Productivity of a Subtropical Coniferous Plantation from 2003 to 2010 Based on Eddy Covariance Flux Observation. Environmental Research Letters, 8, Article ID: 035021.
https://doi.org/10.1088/1748-9326/8/3/035021
[67]  Zhang, C., Ju, W., Chen, J.M., et al. (2015) Disturbance-Induced Reduction of Biomass Carbon Sinks of China’s Forests in Recent Years. Environmental Research Letters, 10, Article ID: 114021.
https://doi.org/10.1088/1748-9326/10/11/114021
[68]  Yao, W., Ma, Y., Chen, F., et al. (2020) Analysis of Ice Storm Impact on and Post-Disaster Recovery of Typical Subtropical Forests in Southeast China. Remote Sensing, 12, Article 164.
https://doi.org/10.3390/rs12010164
[69]  Zhang, F., Zhou, G., Hiratsuka, M., et al. (2012) Influence of An Ice Storm on Aboveground Biomass of Subtropical Evergreen Broadleaf Forest in Lechang, Nanling Mountains of Southern China. International Journal of Forestry Research, 2012, Article ID: 467848.
https://doi.org/10.1155/2012/467848
[70]  曼兴兴, 米湘成, 马克平. 雪灾对古田山常绿阔叶林群落结构的影响[J]. 生物多样性, 2011, 19(2): 197-205.
[71]  Sun, Y., Gu, L., Dickinson, R., et al. (2012) Forest Greenness after the Massive 2008 Chinese Ice Storm: Integrated Effects of Natural Processes and Human Intervention. Environmental Research Letters, 7, Article ID: 035702.
https://doi.org/10.1088/1748-9326/7/3/035702
[72]  Song, X., Hogan, J.A., Lin, L., et al. (2018) Canopy Openness and Topographic Habitat Drive Tree Seedling Recruitment after Snow Damage in an Old-Growth Subtropical Forest. Forest Ecology and Management, 429, 493-502.
https://doi.org/10.1016/j.foreco.2018.07.038
[73]  王云泉. 雪灾对密度制约维持森林群落生物多样性的影响[D]: [硕士学位论文]. 金华: 浙江师范大学, 2015.
[74]  Barrufol, M., Schmid, B., Bruelheide, H., et al. (2013) Biodiversity Promotes Tree Growth during Succession in Subtropical Forest. PLOS ONE, 8, e81246.
https://doi.org/10.1371/journal.pone.0081246
[75]  Castro-Izaguirre, N., Chi, X., Baruffol, M., et al. (2016) Tree Diversity Enhances Stand Carbon Storage but Not Leaf Area in a Subtropical Forest. PLOS ONE, 11, e0167771.
https://doi.org/10.1371/journal.pone.0167771
[76]  Tilman, D. (1999) The Ecological Consequences of Changes in Biodiversity: A Search for General Principles. Ecology, 80, 1455-1474.
https://doi.org/10.2307/176540
[77]  Hooper, D.U., Chapin Iii, F.S., Ewel, J.J., et al. (2005) Effects of Biodiversity on Ecosystem Functioning: A Consensus of Current Knowledge. Ecological Monographs, 75, 3-35.
https://doi.org/10.1890/04-0922
[78]  Huston, M.A. (1997) Hidden Treatments in Ecological Experiments: Re-Evaluating the Ecosystem Function of Biodiversity. Oecologia, 110, 449-460.
https://doi.org/10.1007/s004420050180
[79]  Gamfeldt, L., Sn?ll, T., Bagchi, R., et al. (2013) Higher Levels of Multiple Ecosystem Services Are Found in Forests with More Tree Species. Nature Communications, 4, Article No. 1340.
https://doi.org/10.1038/ncomms2328
[80]  Paquette, A. and Messier, C. (2011) The Effect of Biodiversity on Tree Productivity: From Temperate to Boreal Forests. Global Ecology and Biogeography, 20, 170-180.
https://doi.org/10.1111/j.1466-8238.2010.00592.x
[81]  Vilà, M., Carrillo-Gavilán, A., Vayreda, J., et al. (2013) Disentangling Biodiversity and Climatic Determinants of Wood Production. PLOS ONE, 8, e53530.
https://doi.org/10.1371/journal.pone.0053530
[82]  Forrester, D.I. and Bauhus, J. (2016) A Review of Processes Behind Diversity—Productivity Relationships in Forests. Current Forestry Reports, 2, 45-61.
https://doi.org/10.1007/s40725-016-0031-2
[83]  Szwagrzyk, J. and Gazda, A. (2007) Above-Ground Standing Biomass and Tree Species Diversity in Natural Stands of Central Europe. Journal of Vegetation Science, 18, 555-562.
https://doi.org/10.1111/j.1654-1103.2007.tb02569.x
[84]  Seidel, D., Leuschner, C., Scherber, C., et al. (2013) the Relationship between Tree Species Richness, Canopy Space Exploration and Productivity in a Temperate Broad-Leaf Mixed Forest. Forest Ecology and Management, 310, 366-374.
https://doi.org/10.1016/j.foreco.2013.08.058
[85]  Ali, A., Yan, E., Chen, H.Y, H., et al. (2016) Stand Structural Diversity Rather than Species Diversity Enhances Aboveground Carbon Storage in Secondary Subtropical Forests in Eastern China. Biogeosciences, 13, 4627-4635.
https://doi.org/10.5194/bg-13-4627-2016
[86]  D?nescu, A., Albrecht, A.T. and Bauhus, J. (2016) Structural Diversity Promotes Productivity of Mixed, Uneven-Aged Forests in Southwestern Germany. Oecologia, 182, 319-333.
https://doi.org/10.1007/s00442-016-3623-4
[87]  Morin, X. (2015) Species Richness Promotes Canopy Packing: A Promising Step towards a Better Understanding of the Mechanisms Driving the Diversity Effects on Forest Functioning. Functional Ecology, 29, 993-994.
https://doi.org/10.1111/1365-2435.12473
[88]  Zhang, Y. and Chen, H.Y.H. (2015) Individual Size Inequality Links Forest Diversity and Above-Ground Biomass. Journal of Ecology, 103, 1245-1252.
https://doi.org/10.1111/1365-2745.12425
[89]  Chen, G., Cai, Q., Ma, S., et al. (2023) Climate and Forest Attributes Influence Above-Ground Biomass of Deciduous Broadleaf Forests in China. Journal of Ecology, 111, 495-508.
https://doi.org/10.1111/1365-2745.14042
[90]  Macgillivray, C.W., Grime, J.P. and the Integrated Screening Programme (ISP) Team (1995) Testing Predictions of the Resistance and Resilience of Vegetation Subjected to Extreme Events. Functional Ecology, 9, 640-649.
https://doi.org/10.2307/2390156
[91]  Lep?, J., Osbornová-Kosinová, J. and Rejmánek, M. (1982) Community Stability, Complexity and Species Life History Strategies. Vegetatio, 50, 53-63.
https://doi.org/10.1007/BF00120678
[92]  Lian, Z., Wang, J., Fan, C., et al. (2022) Structure Complexity Is the Primary Driver of Functional Diversity in the Temperate Forests of Northeastern China. Forest Ecosystems, 9, Article ID: 100048.
https://doi.org/10.1016/j.fecs.2022.100048
[93]  Chiu, C.H. and Chao, A. (2014) Distance-Based Functional Diversity Measures and Their Decomposition: A Framework Based on Hill Numbers. PLOS ONE, 9, e100014.
https://doi.org/10.1371/journal.pone.0100014
[94]  Petchey, O.L. and Gaston, K.J. (2002) Functional Diversity (FD), Species Richness and Community Composition. Ecology Letters, 5, 402-411.
https://doi.org/10.1046/j.1461-0248.2002.00339.x
[95]  Huang, Y., Chen, Y., Castro-Izaguirre, N., et al. (2018) Impacts of Species Richness on Productivity in a Large-Scale Subtropical Forest Experiment. Science, 362, 80-83.
https://doi.org/10.1126/science.aat6405
[96]  Wu, X., Wang, X., Wu, Y., et al. (2015) Forest Biomass Is Strongly Shaped by Forest Height across Boreal to Tropical Forests in China. Journal of Plant Ecology, 8, 559-567.
https://doi.org/10.1093/jpe/rtv001
[97]  Webb, C.O. (2000) Exploring the Phylogenetic Structure of Ecological Communities: An Example for Rain Forest Trees. American Society of Naturalists, 156, 145-155.
https://doi.org/10.1086/303378
[98]  Cadotte, M.W., Cardinale, B.J. and Oakley, T.H. (2008) Evolutionary History and the Effect of Biodiversity on Plant Productivity. Proceedings of the National Academy of Sciences of the United States of America, 105, 17012-17017.
https://doi.org/10.1073/pnas.0805962105
[99]  Srivastava, D.S., Cadotte, M.W., Macdonald, A.A.M., et al. (2012) Phylogenetic Diversity and the Functioning of Ecosystems. Ecology Letters, 15, 637-648.
https://doi.org/10.1111/j.1461-0248.2012.01795.x
[100]  Cadotte, M.W., Cavender-Bares, J., Tilman, D., et al. (2009) Using Phylogenetic, Functional and Trait Diversity to Understand Patterns of Plant Community Productivity. PLOS ONE, 4, e5695.
https://doi.org/10.1371/journal.pone.0005695
[101]  Venail, P., Gross, K., Oakley, T.H., et al. (2015) Species Richness, but Not Phylogenetic Diversity, Influences Community Biomass Production and Temporal Stability in a Re-Examination of 16 Grassland Biodiversity Studies. Functional Ecology, 29, 615-626.
https://doi.org/10.1111/1365-2435.12432
[102]  Maherali, H. and Klironomos, J.N. (2007) Influence of Phylogeny on Fungal Community Assembly and Ecosystem Functioning. Science, 316, 1746-1748.
https://doi.org/10.1126/science.1143082

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