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何念鹏,刘聪聪,张佳慧,徐丽,于贵瑞.植物性状研究之机遇与挑战: 从器官到群落.生态学报,2018,(19).http://dx.doi.org/10.5846/stxb201710241900  
植物性状研究之机遇与挑战: 从器官到群落
Perspectives and challenges in plant traits: From organs to communities
投稿时间:2017-10-24  修订日期:2018-04-17
DOI: 10.5846/stxb201710241900
关键词植物性状  植物功能性状  群落性状  功能  群落结构  生产力
Key Wordsplant trait  plant functional trait  community trait  functioning  community structure  productivity
基金项目国家自然科学基金项目(31770655, 41671045); 国家重点研发计划项目(2016YFC0500202)
作者单位E-mail
何念鹏 中国科学院地理科学与资源研究所 henp@igsnrr.ac.cn 
刘聪聪 中国科学院地理科学与资源研究所  
张佳慧 中国科学院地理科学与资源研究所  
徐丽 中国科学院地理科学与资源研究所  
于贵瑞 中国科学院地理科学与资源研究所  
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摘要:
植物性状(Plant trait)或植物功能性状(Plant functional trait)通常是指植物对外界环境长期适应与进化后所表现出的可量度、且与生产力优化或环境适应等密切相关的属性。近几十年来,植物性状研究在性状-生产力、性状-养分、性状间相互关系、性状-群落结构维持等方面取得了卓越成就。然而,由于大多数性状调查都是以植物群落内优势种或亚优势种为对象,使其在探讨群落尺度的性状-功能关系、性状数据如何用于改进或优化模型、性状数据如何与遥感连接等问题时,存在空间尺度和量纲不匹配的极大挑战。为了破解上述难题,亟需发展新的、基于单位土地面积的群落性状(Community trait)概念体系、数据源和计算方法等,推动植物性状数据与快速发展的宏观生态学新技术(遥感、模型和通量观测等)相结合,既拓展了植物性状研究范畴,又可推动其更好地服务于区域生态环境问题的解决。本文所定义的群落性状(如叶片氮含量、磷含量、比叶面积、气孔密度、叶绿素含量等),是在充分考虑群落内所有物种的性状实测数据,再结合比叶面积、生物量异速生长方程和群落结构数据等,推导而成的基于单位土地面积的群落性状。受测试方法的影响,传统的直接算术平均法或相对生物量加权平均法所获得的群落水平的植物性状(如叶片氮含量g/kg或%),虽然可以有效地探讨群落结构维持机制,由于无法实现对群落性状在量纲上向单位土地面积转换,使它很难与模型和遥感数据相匹配。基于单位土地面积的群落性状,可在空间尺度匹配(或量纲匹配)的前提下实现个体水平测定的植物性状数据与生态模型和遥感观测相联系,更好地探讨区域尺度下自然生态系统结构和功能的关系及其对全球变化的响应与适应。同时,它也可更好地建立群落水平的性状-功能的定量关系(非物种水平),为更好地探讨自然群落结构维持机制和生产力优化机制提供了新思路。
Abstract:
Plant traits or plant functional traits are usually measurable properties, and are closely related to optimization of plant productivity or are an adaptation to the environment that evolved due to long-term adaptation and co-evolution of plants. Currently, most studies of plant traits are carried out at the level of individual plants or organs. At the individual level, scientists have made outstanding achievements in the past few decades to understand the productivity and nutrient acquisition traits, interrelationships among these traits, and other associated features. However, systematic data on plant traits are scarce, because most of these studies were conducted on several dominant species and focused on the leaves. To a large extent, such deficiency in systematic investigation data limits the development of trait studies and their applications, such as comprehension of how plant trait data may improve or optimize ecological models, and how much of these plant trait data match new field investigation approaches, such as remote sensing and eddy flux. More importantly, the effects of global changes on terrestrial ecosystems are already present and can be resolved at different regional scales, we expect to incorporate plant trait data into ecological models and remote sensing, to better resolve these eco-environmental problems. However, most of the components of ecosystem functioning (such as gross and net primary productivity, and water use efficiency) are mainly measured using the technologies of remote sensing, eddy-flux observation systems, and ecological models. Because of mismatches in spatial-scales and units between them, plant trait data have been less used to develop or optimize these macroecological approaches (remote sensing, eddy-flux observation systems, and models). To overcome the above-mentioned bottlenecks, scientists need to carry out a systematic survey of traits, including all species within typical communities, such as leaf-branch-stem-root and leaf morphology-anatomical structure-multi-element contents. With the help of the specific leaf area, community structure, and biomass allometric equation, scientists could scientifically scale-up the plant traits measured at the organ level in species, plant functional groups (trees, shrubs, and herbs), and communities, and then establish relationships between the plant traits and components of ecosystem functioning. Moreover, systematic data of plant traits may help us to explore the mechanisms of community structure maintenance and productivity optimization in nature. Nowadays, it is imperative to integrate plant traits (from the level of organ to community) and develop a new concept of community traits on land area. This is done to match the plant traits to the macroecology parameters at a spatial scale, which are mainly measured by remote sensing, eddy flux, and ecological modeling, because most of the current ecological and environmental problems need to be solved either at ecosystem or regional scales. Furthermore, establishing real relationships between plant traits and components of ecosystem functioning in natural communities will allow us to realize the association between plant trait data and satellite remote sensing data, and construct or optimize ecological models, and therefore, understand responses and adaptations of natural ecosystems to global changes at regional scale. A new concept of community traits on land areas can surely help us to better explore real relationships between plant traits and ecosystem functioning at the scale of natural communities.
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