logo

More info
  • ReceivedJul 26, 2020
  • AcceptedSep 8, 2020
  • PublishedNov 23, 2020

Abstract


Funded by

国家科技基础性工作专项(2015FY110303)


References

[1] Hansen M C, Defries R S, Townshend J R G, et al. Global land cover classification at 1 km spatial resolution using a classification tree approach. Int J Remote Sens, 2000, 21: 1331-1364 CrossRef ADS Google Scholar

[2] Editorial Committee of Vegetation Map of China. Vegetation Map of the People’s Republic of China (1:1000000) (in Chinese). Beijing: Science Press, 2007 [中国植被图编委会. 中华人民共和国植被图(1:1000000). 北京: 科学出版社, 2007]. Google Scholar

[3] Editorial Committee of Land Cover Atlas of the People’s Republic of China. Land Cover Atlas of the People’s Republic of China (1:1000000) (in Chinese). Beijing: China Map Publishing House, 2017 [中国土地覆被图集编委会. 中华人民共和国土地覆被地图集(1:1000000). 北京: 中国地图出版社, 2017]. Google Scholar

[4] Archer S, Boutton T W, Hibbard K A. Trees in grasslands: biogeochemical consequences of woody plant expansion. In: Schulze E D, Heimann M, Harrison S, et al., eds. Global Biogeochemical Cycles in the Climate System. San Diego: Academic Press, 2001: 115–137. Google Scholar

[5] Pacala S W, Hurtt G C, Baker D, et al. Consistent land- and atmosphere-based U.S. carbon sink estimates. Science, 2001, 292: 2316-2320 CrossRef ADS Google Scholar

[6] Frost G V, Epstein H E, Walker D A, et al. Patterned-ground facilitates shrub expansion in Low Arctic tundra. Environ Res Lett, 2013, 8: 015035 CrossRef ADS Google Scholar

[7] Tape K, Sturm M, Racine C. The evidence for shrub expansion in Northern Alaska and the Pan-Arctic. Glob Change Biol, 2006, 12: 686-702 CrossRef ADS Google Scholar

[8] Ratajczak Z, Nippert J B, Ocheltree T W. Abrupt transition of mesic grassland to shrubland: evidence for thresholds, alternative attractors, and regime shifts. Ecology, 2014, 95: 2633-2645 CrossRef Google Scholar

[9] Paritsis J, Veblen T T, Holz A. Positive fire feedbacks contribute to shifts from Nothofagus pumilio forests to fire-prone shrublands in Patagonia. J Veg Sci, 2015, 26: 89–101. Google Scholar

[10] You Y J, Wang Y X, Zhang H F, et al. Effects of different human disturbances on soil water conversation and fertility of natural secondary shrub (in Chinese). Acta Ecol Sin, 2018, 38: 1097–1105 [尤誉杰, 王懿祥, 张华锋, 等. 不同人为干扰措施对天然次生灌丛土壤肥力及蓄水能力的影响. 生态学报, 2018, 38: 1097–1105]. Google Scholar

[11] Peng H Y, Li X Y, Li G Y, et al. Shrub encroachment with increasing anthropogenic disturbance in the semiarid Inner Mongolian grasslands of China. Catena, 2013, 109: 39-48 CrossRef Google Scholar

[12] Brandt J S, Haynes M A, Kuemmerle T, et al. Regime shift on the roof of the world: Alpine meadows converting to shrublands in the southern Himalayas. Biol Conserv, 2013, 158: 116-127 CrossRef Google Scholar

[13] Liu X, Zhang W, Liu Z, et al. Changes in species diversity and above-ground biomass of shrubland over long-term natural restoration process in the Taihang Mountain in North China. Plant Soil Environ, 2011, 57: 505-512 CrossRef Google Scholar

[14] Zhang C, Xue S, Liu G B, et al. A comparison of soil qualities of different revegetation types in the Loess Plateau, China. Plant Soil, 2011, 347: 163-178 CrossRef Google Scholar

[15] Xie Z Q, Tang Z Y. Studies on carbon storage of shrubland ecosystems in China (in Chinese). Chin J Plant Ecol, 2017, 41: 5–10 [谢宗强, 唐志尧. 中国灌丛生态系统碳储量的研究. 植物生态学报, 2017, 41: 5–10]. Google Scholar

[16] Wang Y, Gao Q, Liu T, et al. The greenness of major shrublands in China increased from 2001 to 2013. Remote Sens, 2016, 8: 121 CrossRef ADS Google Scholar

[17] Illyés E, Chytrý M, Botta-Dukát Z, et al. Semi-dry grasslands along a climatic gradient across Central Europe: Vegetation classification with validation. J Veg Sci, 2007, 18: 835-846 CrossRef Google Scholar

[18] Zhao H, Guo K, Yang Y, et al. Stipa steppes in scantily explored regions of the Tibetan Plateau: classification, community characteristics and climatic distribution patterns. J Plant Ecol, 2018, 11: 585-594 CrossRef Google Scholar

[19] Li C F, Chytrý M, Zeleny D, et al. Classification of Taiwan forest vegetation. Appl Veg Sci, 2013, 16: 698–719. Google Scholar

[20] Eliáš Jr P, Sopotlieva D, Dítě D, et al. Vegetation diversity of salt-rich grasslands in Southeast Europe. Appl Veg Sci, 2013, 16: 521–537. Google Scholar

[21] Douda J, Boubl K, Doudova J. Vegetation classification and biogeography of European floodplain forests and alder carrs. Appl Veg Sci, 2015, 19: 147–163. Google Scholar

[22] Ni J. Plant functional types and climate along a precipitation gradient in temperate grasslands, north-east China and south-east Mongolia. J Arid Environ, 2003, 53: 501-516 CrossRef ADS Google Scholar

[23] Lancaster L T, Morrison G, Fitt R N. Life history trade-offs, the intensity of competition, and coexistence in novel and evolving communities under climate change. Phil Trans R Soc B, 2017, 372: 20160046 CrossRef Google Scholar

[24] Grime J P. Plant Strategies, Vegetation Processes, and Ecosystem Properties. Chichester: John Wiley & Sons, 2001. Google Scholar

[25] Wright I J, Reich P B, Westoby M, et al. The worldwide leaf economics spectrum. Nature, 2004, 428: 821-827 CrossRef ADS Google Scholar

[26] Chave J, Coomes D, Jansen S, et al. Towards a worldwide wood economics spectrum. Ecol Lett, 2009, 12: 351-366 CrossRef Google Scholar

[27] Liu X J, Ma K P. Plant functional traits—concepts, applications and future directions (in Chinese). Sci Sin Vitae, 2015, 45: 325-339 CrossRef Google Scholar

[28] Shipley B, Laughlin D C, Sonnier G, et al. A strong test of a maximum entropy model of trait-based community assembly. Ecology, 2011, 92: 507-517 CrossRef Google Scholar

[29] Muscarella R, Uriarte M. Do community-weighted mean functional traits reflect optimal strategies?. Proc R Soc B, 2016, 283: 20152434 CrossRef Google Scholar

[30] Reich P B, Oleksyn J. Global patterns of plant leaf N and P in relation to temperature and latitude. Proc Natl Acad Sci USA, 2004, 101: 11001-11006 CrossRef ADS Google Scholar

[31] Wang R L, Yu G R, He N P, et al. Latitudinal patterns and influencing factors of leaf functional traits in Chinese forest ecosystems (in Chinese). Acta Geogr Sin, 2015, 70: 1735–1746 [王瑞丽, 于贵瑞, 何念鹏, 等. 中国森林叶片功能属性的纬度格局及其影响因素. 地理学报, 2015, 70: 1735–1746]. Google Scholar

[32] Zhao G S, Liu M, Shi P L, et al. Variation of leaf and root traits and ecological adaptive strategies along a precipitation gradient on Changtang Plateau (in Chinese). Acta Ecol Sin, 2020, 40: 295–309 [赵广帅, 刘珉, 石培礼, 等. 羌塘高原降水梯度植物叶片、根系性状变异和生态适应对策. 生态学报, 2020, 40: 295–309]. Google Scholar

[33] Fick S E, Hijmans R J. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int J Climatol, 2017, 37: 4302-4315 CrossRef ADS Google Scholar

[34] Bacelar E A, Correia C M, Moutinho-Pereira J M, et al. Sclerophylly and leaf anatomical traits of five field-grown olive cultivars growing under drought conditions. Tree Physiol, 2004, 24: 233-239 CrossRef Google Scholar

[35] Mediavilla S, Garcia-Ciudad A, Garcia-Criado B, et al. Testing the correlations between leaf life span and leaf structural reinforcement in 13 species of European Mediterranean woody plants. Funct Ecol, 2008, 22: 787-793 CrossRef Google Scholar

[36] Wright I J, Ackerly D D, Bongers F, et al. Relationships among ecologically important dimensions of plant trait variation in seven Neotropical forests. Ann Bot, 2007, 99: 1003-1015 CrossRef Google Scholar

[37] Wang H, Harrison S P, Prentice I C, et al. The China Plant Trait Database: toward a comprehensive regional compilation of functional traits for land plants. Ecology, 2018, 99: 500 CrossRef Google Scholar

[38] Kattge J, Díaz S, Lavorel S, et al. TRY—a global database of plant traits. Glob Change Biol, 2011, 17: 2905-2935 CrossRef ADS Google Scholar

[39] Schrodt F, Kattge J, Shan H, et al. BHPMF—a hierarchical Bayesian approach to gap-filling and trait prediction for macroecology and functional biogeography. Glob Ecol Biogeogr, 2015, 24: 1510-1521 CrossRef Google Scholar

[40] Bruelheide H, Dengler J, Purschke O, et al. Global trait-environment relationships of plant communities. Nat Ecol Evol, 2018, 2: 1906-1917 CrossRef Google Scholar

[41] Díaz S, Kattge J, Cornelissen J H C, et al. The global spectrum of plant form and function. Nature, 2016, 529: 167-171 CrossRef ADS Google Scholar

[42] Borcard D, Gillet F, Legendre P. Numerical ecology with R. New York: Springer Science & Business Media, 2011. Google Scholar

[43] Dufrêne M, Legendre P. Species assemblages and indicator species: the need for a flexible asymmetrical approach. Ecol Monogr, 1997, 67: 345-366 CrossRef Google Scholar

[44] R core team. R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing, 2019. Google Scholar

[45] Roberts D W. labdsv: Ordination and multivariate analysis for ecology. 2019. Google Scholar

[46] Oksanen J, Blanchet F G, Friendly M, et al. vegan: Community ecology package. 2018. Google Scholar

[47] Fazayeli F, Banerjee A, Schrodt F, et al. Package BHPMF: Uncertainty quantified matrix completion using Bayesian hierarchical matrix factorization. 2017. Google Scholar

[48] Castro-Díez P, Puyravaud J P, Cornelissen J H C. Leaf structure and anatomy as related to leaf mass per area variation in seedlings of a wide range of woody plant species and types. Oecologia, 2000, 124: 476–486. Google Scholar

[49] Cornelissen J H C. An experimental comparison of leaf decomposition rates in a wide range of temperate plant species and types. J Ecol, 1996, 84: 573–582. Google Scholar

[50] Cornelissen J H C, Cerabolini B, Castro-Díez P, et al. Functional traits of woody plants: correspondence of species rankings between field adults and laboratory-grown seedlings? J Veg Sci, 2003, 14: 311–322. Google Scholar

[51] Han W H, Chen Y H, Zhao F J, et al. Floral, climatic and soil pH controls on leaf ash content in China's terrestrial plants. Glob Ecol Biogeogr, 2012, 21: 376–382. Google Scholar

[52] Kleyer M, Bekker R M, Knevel I C, et al. The LEDA Traitbase: a database of life-history traits of the Northwest European flora. J Ecol, 2008, 96, 1266–1274. Google Scholar

[53] Zerihun W, Backéus I. The shrubland vegetation in western Shewa, Ethiopia and its possible recovery. J Veg Sci, 1991, 2: 173-180 CrossRef Google Scholar

[54] Wu N. The community types and biomass of Sibiraea angustata scrub and their relationship with environmental factors in northwestern Sichuan (in Chinese). Acta Bot Sin, 1998, 40: 860–870 [吴宁. 川西北窄叶鲜卑花灌丛的类型和生物量及其与环境因子的关系. 植物学报, 1998, 40: 860–870]. Google Scholar

[55] Jiang M, Deng H, Cai Q. Characteristics, classification and ordination of riparian plant communities in the Three-Gorges areas. J Forry Res, 2002, 13: 111-114 CrossRef Google Scholar

[56] Wang Y Q, Nie E B. Quantitative analysis of the Vitex negundo var. heterophylla communities in Taihang Mountain, Shanxi Province (in Chinese). Pratacult Sci, 2009, 26: 32–36 [王煜倩, 聂二保. 山西太行山南段峡谷区荆条灌丛数量分析. 草业科学, 2009, 26: 32–36]. Google Scholar

[57] De Sanctis M, Adeeb A, Farcomeni A, et al. Classification and distribution patterns of plant communities on Socotra Island, Yemen. Appl Veg Sci, 2013, 16: 148–165. Google Scholar

[58] Zhao P, Xu X Y, Jin H X, et al. Quantitative classification and ordination analysis on vegetation in the Minqin oasis-desert ecotone (in Chinese). Acta Bot Boreali-Occident Sin, 2014, 34: 364–371 [赵鹏, 徐先英, 金红喜, 等. 民勤绿洲荒漠过渡带植物群落数量分类和排序研究. 西北植物学报, 2014, 34: 364–371]. Google Scholar

[59] Zhang J T, Yang H X. Application of self-organizing neural networks to classification of plant communities in Pangquangou Nature Reserve, North China (in Chinese). Acta Ecol Sin, 2007, 27: 1005–1010 [张金屯, 杨洪晓. 自组织特征人工神经网络在庞泉沟自然保护区植物群落分类中的应用. 生态学报, 2007, 27: 1005–1010]. Google Scholar

[60] Zhang Y M, Chen Y N, Pan B R. Distribution and floristics of desert plant communities in the lower reaches of Tarim River, southern Xinjiang, People’s Republic of China. J Arid Environ, 2005, 63: 772-784 CrossRef ADS Google Scholar

[61] Bai Y, Wu J, Xing Q, et al. Primary production and rain use efficiency across a precipitation gradient on the Mongolia Plateau. Ecology, 2008, 89: 2140-2153 CrossRef Google Scholar

[62] Ma W, He J S, Yang Y, et al. Environmental factors covary with plant diversity-productivity relationships among Chinese grassland sites. Glob Ecol Biogeogr, 2010, 19: 233-243 CrossRef Google Scholar

[63] Zhang L, Zheng Y R. Simulation on the seasonal growth patterns of grassland plant communities in northern China (in Chinese). Chin J Appl Ecol, 2008, 19: 2161–2167 [张莉, 郑元润. 中国北方草地植物群落季节生长格局模拟. 应用生态学报, 2008, 19: 2161–2167]. Google Scholar

[64] Westoby M, Wright I J. Land-plant ecology on the basis of functional traits. Trends Ecol Evol, 2006, 21: 261-268 CrossRef Google Scholar

[65] Reich P B. The world-wide ‘fast–slow’plant economics spectrum: a traits manifesto. J Ecol, 2014, 102: 275–301. Google Scholar

[66] Rosbakh S, Römermann C, Poschlod P. Specific leaf area correlates with temperature: new evidence of trait variation at the population, species and community levels. Alp Bot, 2015, 125: 79-86 CrossRef Google Scholar

[67] Paine C E T, Stahl C, Courtois E A, et al. Functional explanations for variation in bark thickness in tropical rain forest trees. Funct Ecol, 2010, 24: 1202-1210 CrossRef Google Scholar

[68] Murray B R, Brown A H D, Dickman C R, et al. Geographical gradients in seed mass in relation to climate. J Biogeogr, 2004, 31: 379-388 CrossRef Google Scholar

[69] Bjorkman A D, Myers-Smith I H, Elmendorf S C, et al. Plant functional trait change across a warming tundra biome. Nature, 2018, 562: 57-62 CrossRef ADS Google Scholar

[70] Shen L, Shi S L, Li J J, et al. Numerical classification, ordination and species diversity along elevation gradients of Potentilla parvifolia community in Qomolangma National Nature Reserve (in Chinese). Acta Bot Boreali-Occident Sin, 2014, 34: 2092–2100 [沈丽, 石松林, 李景吉, 等. 珠穆朗玛峰自然保护区小叶金露梅灌丛群落数量分类和排序及其多样性垂直格局. 西北植物学报, 2014, 34: 2092–2100]. Google Scholar

[71] Wu X P, Wang Z H, Cui H T, et al. Community structures and species composition of oak forest in mountainous area of Beijing (in Chinese). Biodivers Sci, 2004, 12: 155–163 [吴晓莆, 王志恒, 崔海亭, 等. 北京山区栎林的群落结构与物种组成. 生物多样性, 2004, 12: 155–163]. Google Scholar

[72] Burke A. Classification and ordination of plant communities of the Naukluft Mountains, Namibia. J Veg Sci, 2001, 12: 53-60 CrossRef Google Scholar

[73] Gallego Fernández J B, Rosario García Mora M, García Novo F. Vegetation dynamics of Mediterranean shrublands in former cultural landscape at Grazalema Mountains, South Spain. Plant Ecol, 2004, 172: 83-94 CrossRef Google Scholar

[74] Buffum B, McWilliams S R, August P V. A spatial analysis of forest management and its contribution to maintaining the extent of shrubland habitat in southern New England, United States. For Ecol Manage, 2011, 262: 1775-1785 CrossRef Google Scholar

[75] Rubiano K, Clerici N, Norden N, et al. Secondary forest and shrubland dynamics in a highly transformed landscape in the Northern Andes of Colombia (1985–2015). Forests, 2017, 8: 216 CrossRef Google Scholar

[76] Schulz J J, Cayuela L, Rey-Benayas J M, et al. Factors influencing vegetation cover change in Mediterranean Central Chile (1975-2008). Appl Veg Sci, 2011, 14: 571-582 CrossRef Google Scholar

[77] De Cáceres M, Font X, Oliva F. The management of vegetation classifications with fuzzy clustering. J Veg Sci, 2010, 21: 1138-1151 CrossRef Google Scholar

[78] Tichý L, Chytrý M, Botta-Dukát Z. Semi-supervised classification of vegetation: preserving the good old units and searching for new ones. J Veg Sci, 2014, 25: 1504–1512. Google Scholar

  • Figure 1

    The variations in Pearson correlation coefficients between the original distance matrix of the species composition and the binary matrix of k-means clustering with different numbers of clusters (k) in pre-experiments. A: The results of the first pre-experiment based on 2,034 shrubland communities. The vertical dashed line indicates the number of clusters with the highest value of correlation coefficients. B: The results of the second pre-experiment based on 1,119 shrubland communities. The vertical dashed lines denote the numbers of clusters with the first three peak values

  • Figure 2

    Geographic distribution of typical shrubland alliances in northern China

  • Figure 3

    Relationships between habitat conditions and community structures of typical shrubland alliances in northern China (See Figure 2 for the corresponding shrubland alliances represented by different symbols). The error bar denotes standard error. The solid lines imply significant relationships (P<0.05)

  • Figure 4

    Ordinations of 29 typical shrubland alliances in northern China. A: CCA results. Table 3 shows the corresponding variables represented by red arrows. Points with different symbols denote sites, and the coordinates of the abbreviations signify the average locations in the two-dimensional space formed by CCA1 and CCA2. Error bar means standard deviation. B: Ordination of alliances along the first axis of CCA (CCA1). C: Ordination of alliances along annual precipitation (Figure 2 shows the corresponding shrubland alliances represented by different symbols, and Table 1 shows the corresponding alliance names represented by different abbreviations. Some abbreviations are not shown due to overlap). The dashed lines in (B) and (C) denote the approximate dividing points for the gradients of water availability. TDS, temperate desert shrublands; TDBS, temperate deciduous broadleaf shrublands; StDBS, subtropical deciduous broadleaf shrublands; SaEBS, subalpine evergreen broadleaf shrublands

  • Figure 5

    Relationships between the average CCA1 score and leaf thickness (A), the average CCA1 score and specific leaf area (B), and the specific leaf area and leaf thickness (C) for indicator species of different shrubland alliances. The solid lines denote significant correlations (P<0.001) (Figure 2 shows the corresponding shrubland alliances represented by different symbols)

  • Table 1   Typical shrubland alliances in northern China

    群系名称

    植被型

    中国植被图[2]群系

    中国植被图植被型

    指示种拉丁名

    缩写

    样地数

    骆驼刺灌丛

    温带荒漠灌丛

    疏叶骆驼刺盐生草甸

    温带禾草、杂类草盐生草甸

    Alhagi sparsifolia

    AS

    14

    黑沙蒿灌丛

    温带荒漠灌丛

    黑沙蒿荒漠

    温带半灌木、矮半灌木荒漠

    Artemisia ordosica

    AO

    66

    柠条锦鸡儿灌丛

    温带荒漠灌丛

    锦鸡儿灌丛

    温带落叶阔叶灌丛

    Caragana korshinskii

    CK

    123

    小叶锦鸡儿灌丛

    温带荒漠灌丛

    锦鸡儿灌丛

    温带落叶阔叶灌丛

    Caragana microphylla

    CM

    28

    马桑灌丛

    亚热带落叶阔叶灌丛

    马桑灌丛

    亚热带、热带常绿阔叶、落叶阔叶灌丛

    Coriaria nepalensis

    CN

    12

    榛灌丛

    温带落叶阔叶灌丛

    榛子灌丛

    温带落叶阔叶灌丛

    Corylus heterophylla

    CH

    61

    黄栌灌丛

    温带落叶阔叶灌丛

    黄栌灌丛

    温带落叶阔叶灌丛

    Cotinus coggygria

    CC

    39

    沙棘灌丛

    温带落叶阔叶灌丛

    沙棘灌丛

    温带落叶阔叶灌丛

    Elaeagnus rhamnoides

    ER

    170

    野皂荚灌丛

    温带落叶阔叶灌丛

    野皂荚灌丛

    温带落叶阔叶灌丛

    Gleditsia microphylla

    GM

    23

    盐节木灌丛

    温带荒漠灌丛

    盐节木荒漠

    温带多汁盐生矮半灌木荒漠

    Halocnemum strobilaceum

    HS

    6

    盐穗木灌丛

    温带荒漠灌丛

    盐穗木荒漠

    温带多汁盐生矮半灌木荒漠

    Halostachys belangeriana

    HB

    5

    胡枝子灌丛

    温带落叶阔叶灌丛

    二色胡枝子灌丛

    温带落叶阔叶灌丛

    Lespedeza bicolor

    LB

    34

    蚂蚱腿子灌丛

    温带落叶阔叶灌丛

    Myripnois dioica

    MD

    31

    白刺灌丛

    温带荒漠灌丛

    唐古特白刺荒漠

    温带灌木荒漠

    Nitraria tangutorum

    NT

    30

    虎榛子灌丛

    温带落叶阔叶灌丛

    虎榛子灌丛

    温带落叶阔叶灌丛

    Ostryopsis davidiana

    OD

    177

    山杏灌丛

    温带落叶阔叶灌丛

    山杏灌丛

    温带落叶阔叶灌丛

    Prunus sibirica

    PS

    89

    红砂灌丛

    温带荒漠灌丛

    红砂荒漠

    温带半灌木、矮半灌木荒漠

    Reaumuria soongarica

    RS

    60

    头花杜鹃灌丛

    亚高山常绿阔叶灌丛

    头花杜鹃、百里香杜鹃灌丛

    亚高山硬叶常绿阔叶灌丛

    Rhododendron capitatum

    RC

    14

    黄刺玫灌丛

    温带落叶阔叶灌丛

    蔷薇、栒子灌丛

    温带落叶阔叶灌丛

    Rosa xanthina

    RX

    100

    黄柳灌丛

    温带荒漠灌丛

    柳灌丛

    温带落叶阔叶灌丛

    Salix gordejevii

    SG

    7

    北沙柳灌丛

    温带荒漠灌丛

    柳灌丛

    温带落叶阔叶灌丛

    Salix psammophila

    SP

    10

    白刺槐灌丛

    温带落叶阔叶灌丛

    白刺花灌丛

    温带落叶阔叶灌丛

    Sophora davidii

    SD

    57

    土庄绣线菊灌丛

    温带落叶阔叶灌丛

    绣线菊灌丛

    温带落叶阔叶灌丛

    Spiraea pubescens

    SPU

    42

    绣线菊灌丛

    温带落叶阔叶灌丛

    绣线菊灌丛

    温带落叶阔叶灌丛

    Spiraea salicifolia

    SS

    119

    三裂绣线菊灌丛

    温带落叶阔叶灌丛

    绣线菊灌丛

    温带落叶阔叶灌丛

    Spiraea trilobata

    ST

    44

    甘蒙柽柳灌丛

    温带荒漠灌丛

    Tamarix austromongolica

    TA

    6

    柽柳灌丛

    温带落叶阔叶灌丛

    柽柳灌丛

    温带落叶阔叶灌丛

    Tamarix chinensis

    TC

    21

    荆条灌丛

    温带落叶阔叶灌丛

    荆条、酸枣灌丛

    温带落叶阔叶灌丛

    Vitex negundo

    VN

    449

    酸枣灌丛

    温带落叶阔叶灌丛

    荆条、酸枣灌丛

    温带落叶阔叶灌丛

    Ziziphus jujuba var. spinosa

    ZJ

    175

  • Table 2   Species composition, habitat conditions, and physiognomic characteristics of typical shrubland alliances in northern China

    群系名称

    指示种出现频率

    指示种平均相对盖度

    常见种(频率≥60%)

    较常见种(60%>频率≥30%)

    海拔a)(m)

    坡度(°)

    坡向b)(°)

    灌木层高度(m)

    灌木层盖度(%)

    草本层高度(m)

    草本层盖度(%)

    骆驼刺灌丛

    100%

    100%

    −208~1111

    0~0

    0.4~0.7

    22~63

    0.3~0.5

    5~9

    黑沙蒿灌丛

    96%

    58%

    1083~1459

    0~31

    0~317

    0.3~2.5

    17~90

    0.0~1.1

    1~60

    柠条锦鸡儿灌丛

    100%

    78%

    514~1748

    0~40

    0~332

    0.3~2.0

    15~80

    0.0~0.7

    2~80

    小叶锦鸡儿灌丛

    100%

    70%

    698~1908

    0~35

    3~274

    0.2~1.8

    10~68

    0.0~0.6

    3~82

    马桑灌丛

    100%

    61%

    胡枝子, 盐肤木(Rhuschinensis), 荆条, 栓皮栎Quercus variabilis)

    273~1150

    8~42

    3~287

    1.3~2.7

    75~95

    0.3~0.9

    15~89

    榛灌丛

    100%

    72%

    胡枝子, 蒙古栎(Quercus mongolica), 鼠李(Rhamnus davurica), 山刺玫(Rosa davurica)

    108~1266

    0~40

    7~352

    0.8~2.0

    30~100

    0.2~0.9

    5~88

    黄栌灌丛

    100%

    36%

    细梗胡枝子(Lespedeza virgata), 荆条

    422~2330

    2~48

    15~331

    0.9~3.8

    50~100

    0.1~0.9

    5~90

    沙棘灌丛

    100%

    78%

    黄刺玫

    1062~2342

    0~38

    0~351

    0.8~2.5

    26~100

    0.0~0.7

    10~95

    野皂荚灌丛

    100%

    63%

    荆条

    酸枣

    178~986

    2~57

    16~333

    1.0~3.3

    46~99

    0.1~1.7

    1~84

    盐节木灌丛

    100%

    100%

    −169~1204

    0~0

    0.3~0.6

    16~44

    盐穗木灌丛

    100%

    100%

    498~1357

    0~0

    0.6~0.9

    46~64

    0.1~0.4

    6~42

    胡枝子灌丛

    100%

    44%

    牛叠肚(Rubus crataegifolius)

    98~1496

    0~35

    4~333

    0.5~1.8

    14~83

    0.2~1.0

    17~99

    蚂蚱腿子灌丛

    100%

    42%

    三裂绣线菊, 荆条, 绣线菊

    255~1405

    11~43

    17~307

    0.5~1.7

    29~96

    0.1~0.7

    8~73

    白刺灌丛

    100%

    52%

    红砂

    838~1451

    0~15

    0~298

    0.3~2.1

    10~49

    0.0~0.6

    0~30

    虎榛子灌丛

    100%

    62%

    土庄绣线菊, 三裂绣线菊

    748~1841

    5~35

    0~353

    0.5~1.8

    30~100

    0.1~0.6

    5~85

    山杏灌丛

    100%

    54%

    多花胡枝子(Lespedeza floribunda)

    314~1750

    0~42

    27~350

    0.3~2.8

    16~80

    0.2~1.0

    10~80

    红砂灌丛

    100%

    46%

    珍珠猪毛菜(Salsola passerina)

    653~1691

    0~25

    17~352

    0.1~0.6

    10~48

    0.0~1.2

    0~55

    头花杜鹃灌丛

    100%

    43%

    高山绣线菊(Spiraea alpine), 杯腺柳(Salix cupularis)

    3368~3689

    14~40

    70~324

    0.1~0.5

    30~83

    0.1~0.3

    10~49

    黄刺玫灌丛

    100%

    68%

    928~2281

    2~48

    0~334

    0.8~2.9

    30~98

    0.0~0.5

    10~90

    黄柳灌丛

    100%

    100%

    1046~1460

    0~30

    68~299

    1.8~2.3

    15~58

    0.4~0.9

    1~85

    北沙柳灌丛

    100%

    100%

    1177~1680

    0~5

    0~284

    1.5~2.2

    26~68

    0.1~1.4

    20~88

    白刺槐灌丛

    100%

    44%

    黄刺玫, 酸枣, 荆条

    164~1492

    0~40

    40~329

    0.7~2.2

    20~93

    0.1~0.8

    5~88

    土庄绣线菊灌丛

    100%

    52%

    535~2350

    2~38

    0~354

    0.5~2.0

    20~95

    0.1~0.5

    15~80

    绣线菊灌丛

    100%

    26%

    虎榛子

    蚂蚱腿子, 芫花(Daphnegenkwa), 雀儿舌头(Leptopus chinensis), 鼠李

    719~1590

    9~45

    0~345

    0.5~1.7

    30~95

    0.2~0.5

    7~64

    三裂绣线菊灌丛

    100%

    54%

    荆条

    335~2178

    2~69

    0~320

    0.5~3.4

    20~95

    0.1~0.5

    5~90

    甘蒙柽柳灌丛

    100%

    100%

    1260~1528

    0~0

    0.8~2.0

    20~49

    0.4~0.8

    21~49

    柽柳灌丛

    100%

    100%

    −2~22

    0~0

    0.7~2.1

    30~82

    0.4~1.4

    17~56

    荆条灌丛

    100%

    62%

    酸枣

    115~1170

    0~46

    11~340

    0.5~2.5

    20~100

    0.1~0.9

    5~91

    酸枣灌丛

    100%

    40%

    荆条

    扁担杆(Grewia biloba)

    101~1307

    0~51

    10~340

    0.5~3.0

    15~95

    0.1~0.8

    5~86

    表中所有范围均为原始数据的第2.5个百分位数至97.5个百分位数; b) 正北方坡向为0°, 沿顺时针方向增加. 坡度为0°时没有坡向.

  • Table 3   Correlation coefficients between climate variables and CCA1 and CCA2

    CCA1

    CCA2

    年均温(Bio 1)

    −0.03

    −0.92

    温度季节性(Bio 4)

    −0.41

    0.06

    最冷季均温(Bio 11)

    0.16

    −0.72

    年降水量(Bio 12)

    0.86

    −0.28

    降水季节性(Bio 15)

    0.23

    −0.13

    最旱季降水量(Bio 17)

    0.45

    −0.29

    年均太阳辐射(MSR)

    −0.60

    0.04

    年均水汽压(MVP)

    0.43

    −0.79

  • Table 4   Correlation coefficients between leaf functional traits and average CCA1 and CCA2 scores of indicator speciesa)

    CCA1

    CCA2

    log叶厚度

    −0.63***

    −0.32

    log比叶面积

    0.71***

    0.44*

    log叶干物质含量

    0.19

    0.05

    log叶氮含量

    0.24

    0.29

    log叶磷含量

    −0.14

    0.13

    *, P<0.05; ***, P<0.001

qqqq

Contact and support