xCO2 temporal variability above Brazilian agroecosystems: A remote sensing approach

Area of Science:

• Agricultural Science
• Atmospheric Science
• Remote Sensing

Background:

• Agricultural and soil management practices significantly influence CO2 emissions and land-atmosphere carbon exchange.
• Understanding these dynamics is crucial for assessing the impact of agroecosystems on greenhouse gas levels.

Purpose of the Study:

• To investigate the temporal variability of atmospheric CO2 (xCO2), solar-induced chlorophyll fluorescence (SIF), and NDVI in major Brazilian agroecosystems.
• To determine the association between crop cycles, agricultural management, and the observed variations in NDVI, SIF, and xCO2.

Main Methods:

• Data on air temperature, precipitation, NDVI, SIF, and xCO2 were collected over two years from sugarcane, soybean-corn, and grassland sites in Brazil.
• Time series data for NDVI, SIF, and xCO2 underwent trend removal using regression analysis.
• Correlation analysis was performed to assess relationships between SIF and xCO2 across different agroecosystems.

Main Results:

• A negative correlation between SIF and xCO2 was observed in sugarcane and cropland areas, but not in grasslands.
• Grasslands exhibited higher SIF values, while grain croplands showed lower xCO2 levels (396.8–404.2 ppm).
• Seasonal patterns in xCO2 and SIF were evident in sugarcane and annual crops, with grasslands showing unusual patterns linked to precipitation.

Conclusions:

• SIF and xCO2 show potential for identifying greenhouse gas sources and sinks in agricultural regions.
• The study highlights the distinct carbon dynamics influenced by different agroecosystem management practices.
• Remote sensing of SIF and xCO2 can aid in monitoring agricultural impacts on atmospheric CO2.