Open AccessA Process‐Based Model Integrating Remote Sensing Data for Evaluating Ecosystem Services
Author(s) -
Niu Zhongen,
He Honglin,
Peng Shushi,
Ren Xiaoli,
Zhang Li,
Gu Fengxue,
Zhu Gaofeng,
Peng Changhui,
Li Pan,
Wang Junbang,
Ge Rong,
Zeng Na,
Zhu Xiaobo,
Lv Yan,
Chang Qingqing,
Xu Qian,
Zhang Mengyu,
Liu Weihua
Publication year - 2021
Publication title -
journal of advances in modeling earth systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.03
H-Index - 58
ISSN - 1942-2466
DOI - 10.1029/2020ms002451
Subject(s) - environmental science , carbon sequestration , ecosystem , biosphere , primary production , evapotranspiration , carbon cycle , productivity , ecosystem services , ecosystem model , terrestrial ecosystem , soil carbon , environmental resource management , soil water , soil science , ecology , carbon dioxide , biology , economics , macroeconomics
Terrestrial ecosystems provide multiple services interacting in complex ways. However, most ecosystem services (ESs) models (e.g., InVEST and ARIES) ignored the relationships among ESs. Process‐based models can overcome this limitation, and the integration of ecological models with remote sensing data could greatly facilitate the investigation of the complex ecological processes. Therefore, based on the Carbon and Exchange between Vegetation, Soil, and Atmosphere (CEVSA) models, we developed a process‐based ES model (CEVSA‐ES) integrating remotely sensed leaf area index to evaluate four important ESs (i.e., productivity provision, carbon sequestration, water retention, and soil retention) at annual timescale in China. Compared to the traditional terrestrial biosphere models, the main innovation of CEVSA‐ES model was the consideration of soil erosion processes and its impact on carbon cycling. The new version also improved the carbon‐water cycle algorithms. Then, the Sobol and DEMC methods that integrated the CEVSA‐ES model with nine flux sites comprising 39 site‐years were used to identify and optimize parameters. Finally, the model using the optimized parameters was validated at 26 field sites comprising 135 site‐years. Simulation results showed good fits with ecosystem processes, explaining 95%, 92%, 76%, and 65% interannual variabilities of gross primary productivity, ecosystem respiration, net ecosystem productivity, and evapotranspiration, respectively. The CEVSA‐ES model performed well for productivity provision and carbon sequestration, which explained 96% and 81% of the spatial‐temporal variations of the observed annual productivity provision and carbon sequestration, respectively. The model also captured the interannual trends of water retention and soil erosion for most sites or basins.