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MODIS‐Based Estimates of Global Terrestrial Ecosystem Respiration
Author(s) -
Ai Jinlong,
Jia Gensuo,
Epstein Howard E.,
Wang Hesong,
Zhang Anzhi,
Hu Yonghong
Publication year - 2018
Publication title -
journal of geophysical research: biogeosciences
Language(s) - English
Resource type - Journals
eISSN - 2169-8961
pISSN - 2169-8953
DOI - 10.1002/2017jg004107
Subject(s) - biome , environmental science , moderate resolution imaging spectroradiometer , ecosystem respiration , terrestrial ecosystem , atmospheric sciences , vegetation (pathology) , ecosystem , respiration , carbon cycle , soil respiration , atmosphere (unit) , primary production , carbon flux , latitude , flux (metallurgy) , ecology , meteorology , soil science , satellite , geography , geology , biology , chemistry , botany , aerospace engineering , pathology , engineering , geodesy , soil water , medicine , organic chemistry
Terrestrial ecosystem respiration ( R eco ) represents a large carbon source from land to atmosphere and is highly spatiotemporally heterogeneous across scales. Upscaling of field‐measured respiration data using remote sensing information is urgently needed for understanding regional and global patterns of ecosystem respiration. Using Moderate Resolution Imaging Spectroradiometer (MODIS) data with resolutions of 1 km and 8 days and flux measurements from 171 sites (total of 812 site years) across the world from 2000 to 2014, we developed a semiempirical, yet physiologically based, remote sensing model, which can simulate R eco observed across most biomes with a small margin of error ( R 2 = 0.55, root‐mean‐square error = 1.67 gCm −2 d −1 , efficiency = 0.46, and mean bias error = 0.18 gCm −2 d −1 ). The reference respiration at the annual mean nighttime land surface temperature (LST) can be well represented by MODIS enhanced vegetation index and LST. A comprehensive comparison of six respiration‐temperature ( R ‐ T ) models shows that the more physiologically based R ‐ T model (extended Arrhenius model) may be most suitable for estimating the respiration rate at higher latitudes. Integrating an effect of vegetation change on R eco in different biomes effectively improves estimates of R eco in almost all of the biomes.