Traditional plant functional groups explain variation in economic but not size‐related traits across the tundra biome
Traditional plant functional groups explain variation in economic but not size‐related traits across the tundra biome
复制标题
传统植物功能群解释了苔原生物群落中经济性状的变化，但不能解释与大小相关的性状的变化
DOI：
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发表时间：
2018
影响因子：
6.4
通讯作者：
P. V. van Bodegom
中科院分区：
文献类型：
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作者：
H. Thomas;I. Myers;Anne D. Bjorkman;S. Elmendorf;D. Blok;J. Cornelissen;B. Forbes;R. Hollister;S. Normand;J. Prevéy;C. Rixen;G. Schaepman‐Strub;M. Wilmking;S. Wipf;W. Cornwell;J. Kattge;S. Goetz;K. C. Guay;J. Alatalo;A. Anadon‐Rosell;S. Angers‐Blondin;L. Berner;R. Björk;A. Buchwal;A. Buras;M. Carbognani;K. Christie;L. Siegwart Collier;E. Cooper;A. Eskelinen;E. Frei;O. Grau;P. Grogan;M. Hallinger;M. Heijmans;L. Hermanutz;J. Hudson;K. Hülber;M. Iturrate;C. Iversen;F. Jaroszynska;J. Johnstone;E. Kaarlejärvi;A. Kulonen;L. Lamarque;E. Lévesque;C. Little;A. Michelsen;A. Milbau;J. Nabe‐Nielsen;S. Nielsen;J. Ninot;S. Oberbauer;J. Olofsson;V. Onipchenko;A. Petraglia;S. Rumpf;P. Semenchuk;N. A. Soudzilovskaia;M. Spasojevic;J. Speed;K. Tape;M. te Beest;M. Tomaselli;A. Trant;U. Treier;S. Venn;T. Vowles;S. Weijers;T. Zamin;O. Atkin;M. Bahn;B. Blonder;G. Campetella;B. Cerabolini;F. Chapin, III;M. Dainese;F. D. de Vries;S. Díaz;W. Green;R. B. Jackson;P. Manning;Ü. Niinemets;W. Ozinga;J. Peñuelas;P. Reich;B. Schamp;S. Sheremetev;P. V. van Bodegom
摘要目的植物功能群被广泛应用于群落生态学和地球系统建模中，用于描述植物群落内部和群落间的性状变异。然而，这种方法建立在功能群解释物种间大部分性状变异的假设之上。我们测试了四种常用的植物功能群是否代表了六种重要生态植物性状的变异。地理位置：苔原生物群系。数据收集于1964年至2016年之间。主要分类群研究了295种冻土带维管植物。方法对冻土带植物的株高、叶面积、比叶面积、叶片干物质含量、叶片氮含量、种子质量等6个性状进行数据库分析。我们研究了四种传统功能类群（常绿灌木、落叶灌木、禾本科植物和草本植物）解释的物种水平性状表达的变化，以及这种变化是否取决于分析中包含的性状。我们进一步比较了功能群的解释能力和物种组成，以及使用物种水平性状的事后聚类产生的替代分类。结果传统功能群解释了性状表达的显著差异，特别是与资源经济相关的性状之间的差异，这些差异在不同地点和生物群系尺度上是一致的。然而，功能群解释了19%的总体性状变异，并且很少代表与植物大小相关的性状差异。物种的事后分类与传统的功能群不一致，解释了物种水平性状表达的两倍变异。传统功能群仅粗略地代表了冻土带植物群落中已测量性状的变化，比大小相关性状更能解释资源经济性状。我们建议在使用功能群方法预测苔原植被变化或与植物大小相关的生态系统功能（如反照率或碳储量）时要谨慎。我们认为，替代分类或直接利用特定植物性状可以为生态预测和建模提供新的见解。
Abstract Aim Plant functional groups are widely used in community ecology and earth system modelling to describe trait variation within and across plant communities. However, this approach rests on the assumption that functional groups explain a large proportion of trait variation among species. We test whether four commonly used plant functional groups represent variation in six ecologically important plant traits. Location Tundra biome. Time period Data collected between 1964 and 2016. Major taxa studied 295 tundra vascular plant species. Methods We compiled a database of six plant traits (plant height, leaf area, specific leaf area, leaf dry matter content, leaf nitrogen, seed mass) for tundra species. We examined the variation in species‐level trait expression explained by four traditional functional groups (evergreen shrubs, deciduous shrubs, graminoids, forbs), and whether variation explained was dependent upon the traits included in analysis. We further compared the explanatory power and species composition of functional groups to alternative classifications generated using post hoc clustering of species‐level traits. Results Traditional functional groups explained significant differences in trait expression, particularly amongst traits associated with resource economics, which were consistent across sites and at the biome scale. However, functional groups explained 19% of overall trait variation and poorly represented differences in traits associated with plant size. Post hoc classification of species did not correspond well with traditional functional groups, and explained twice as much variation in species‐level trait expression. Main conclusions Traditional functional groups only coarsely represent variation in well‐measured traits within tundra plant communities, and better explain resource economic traits than size‐related traits. We recommend caution when using functional group approaches to predict tundra vegetation change, or ecosystem functions relating to plant size, such as albedo or carbon storage. We argue that alternative classifications or direct use of specific plant traits could provide new insights for ecological prediction and modelling.