Ecosystem Traits Linking Functional Traits to Macroecology

Nianpeng He; Congcong Liu; Shilong Piao; Lawren Sack; Li Xu; Yiqi Luo; Jinsheng He; Xingguo Han; Guangsheng Zhou; Xuhui Zhou; Yi Lin; Qiang Yu; Shirong Liu; Wei Sun; Shuli Niu; Shenggong Li; Jiahui Zhang; Guirui Yu

doi:10.1016/j.tree.2018.11.004

Ecosystem Traits Linking Functional Traits to Macroecology

Trends Ecol Evol. 2019 Mar;34(3):200-210. doi: 10.1016/j.tree.2018.11.004. Epub 2018 Dec 4.

Authors

Nianpeng He¹, Congcong Liu², Shilong Piao³, Lawren Sack⁴, Li Xu⁵, Yiqi Luo⁶, Jinsheng He³, Xingguo Han⁷, Guangsheng Zhou⁸, Xuhui Zhou⁹, Yi Lin¹⁰, Qiang Yu¹¹, Shirong Liu¹², Wei Sun¹³, Shuli Niu⁵, Shenggong Li⁵, Jiahui Zhang⁵, Guirui Yu¹⁴

Affiliations

¹ Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China. Electronic address: henp@igsnrr.ac.cn.
² Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China.
³ Department of Ecology, College of Urban and Environmental Science, Peking University, Beijing, China.
⁴ Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, USA.
⁵ Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.
⁶ Department of Microbiology & Plant Biology, University of Oklahoma, Norman, OK, USA.
⁷ State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China.
⁸ Chinese Academy of Meteorological Sciences, Haidian District, Beijing, China.
⁹ School of Ecological and Environmental Science, East China Normal University, Shanghai, China.
¹⁰ Institute of Remote Sensing and GIS, School of Earth and Space Sciences, Peking University, Beijing, China.
¹¹ National Hulunber Grassland Ecosystem Observation and Research Station, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, China.
¹² Key Laboratory of Forest Ecology and Environment, China's State Forestry Administration, Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, Beijing, China.
¹³ Key Laboratory of Vegetation Ecology, Ministry of Education, Northeast Normal University, Changchun, China.
¹⁴ Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China. Electronic address: yugr@igsnrr.ac.cn.

PMID: 30527959
DOI: 10.1016/j.tree.2018.11.004

Abstract

As the range of studies on macroecology and functional traits expands, integration of traits into higher-level approaches offers new opportunities to improve clarification of larger-scale patterns and their mechanisms and predictions using models. Here, we propose a framework for quantifying 'ecosystem traits' and means to address the challenges of broadening the applicability of functional traits to macroecology. Ecosystem traits are traits or quantitative characteristics of organisms (plants, animals, and microbes) at the community level expressed as the intensity (or density) normalized per unit land area. Ecosystem traits can inter-relate and integrate data from field trait surveys, eddy-flux observation, remote sensing, and ecological models, and thereby provide new resolution of the responses and feedback at regional to global scale.

Keywords: community; ecosystem; function; macroecology; scale-up; trait; transect.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Animals
Ecosystem*
Life History Traits*
Plants*