Abiotic and biotic factors contribute to CO2 exchange variation at the hourly scale in a semiarid maize cropland
- 1. Key Laboratory of Agricultural of Things, Ministry of Agriculture, Yangling (China)
- 2. College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling, Shaanxi 712100 (China)
- 3. Institute of Soil and Water Conservation, Northwest A&F University, Yangling 712100 (China)
Description
Highlights: • Automated static and dynamic chambers measured daily CO2 exchange variations. • CO2 emission capacity increased with soil temperature and air humidity. • Most factors were negatively (daytime) and positively (nighttime) correlated with CO2 emissions. • PAR and LA most affected carbon budget in the daytime and nighttime, respectively. • Important abiotic factors had both direct and indirect effects on carbon budget. Understanding the variables influencing the carbon budget in agricultural ecosystems is crucial for the prediction of future carbon dynamics. The purpose of this study was to identify the biotic and abiotic determinants of the net ecosystem CO2 exchange (NEE) and net assimilation rate (NPP) in a semiarid maize cropland. The CO2 exchange (NEE and NPP) was measured at different growth stages of maize plants using an improved chamber methodology. Heat map clustering of the correlation coefficients between CO2 exchange and its driving factors demonstrated that soil temperature and air humidity were positively correlated with CO2 emissions regardless of daytime or nighttime, while other factors affecting CO2 exchange were negatively correlated with emissions during daytime yet positively correlated during nighttime. The machine learning algorithm random forest (RF) and structural equation modeling (SEM) were used to analyze the effects of different factors on CO2 exchange. The RF analysis results indicated that for CO2 exchange in the daytime, photosynthetically active radiation (PAR) was the most important variable and presented an importance score of 0.574 for NEE and 0.558 for NPP. The SEM results indicated that in the daytime PAR exerted significant direct and indirect effects on both NEE and NPP, and the standardized direct and indirect effects were −0.668 and 0.022, respectively, for NEE, and the effects were 0.655 and −0.011, respectively for NPP. Like PAR, soil water content also exerted significant direct and indirect effects on both NEE and NPP, but the remaining factors affecting CO2 exchange only have one of the direct or indirect effects, sometimes neither. For CO2 exchange at night, the leaf area was the most important variable and presented an importance score of 0.72 for NEE and 0.45 for NPP. At night, both the direct and indirect effects of most abiotic factors on NEE and NPP were significant.
Availability note (English)
Available from http://dx.doi.org/10.1016/j.scitotenv.2021.147170Additional details
Identifiers
- DOI
- 10.1016/j.scitotenv.2021.147170;
- PII
- S0048969721022415;
Publishing Information
- Journal Title
- Science of the Total Environment
- Journal Volume
- 784
- Journal Page Range
- vp.
- ISSN
- 0048-9697
- CODEN
- STENDL
INIS
- Country of Publication
- Netherlands
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 54059392
- Subject category
- S54: ENVIRONMENTAL SCIENCES;
- Descriptors DEI
- CARBON; CARBON DIOXIDE; COMPUTERIZED SIMULATION; ECOSYSTEMS; EMISSION; HEAT; HUMIDITY; MACHINE LEARNING; SOILS
- Descriptors DEC
- ALGORITHMS; ARTIFICIAL INTELLIGENCE; CARBON COMPOUNDS; CARBON OXIDES; CHALCOGENIDES; ELEMENTS; ENERGY; LEARNING; MATHEMATICAL LOGIC; MOISTURE; NONMETALS; OXIDES; OXYGEN COMPOUNDS; SIMULATION
Optional Information
- Copyright
- Copyright (c) 2021 Elsevier B.V. All rights reserved.