Effects of forest type and environmental factors on forest carbon use efficiency assessed using MODIS and FIA data across the eastern USA

• Published in: International journal of remote sensing 2013-12, Vol.34 (23), p.8425-8448
• Main Authors: Kwon, Youngsang, Larsen, Chris P.S.
• Format: Article
• Language: English
• Subjects: Animal, plant and microbial ecology; Applied geophysics; Biological and medical sciences; Carbon; Computational efficiency; Computing time; Earth sciences; Earth, ocean, space; Exact sciences and technology; Forests; Fundamental and applied biological sciences. Psychology; General aspects. Techniques; Internal geophysics; Mathematical analysis; MODIS; Net Primary Productivity; Productivity; Teledetection and vegetation maps
• ISSN: 0143-1161; 1366-5901
• DOI: 10.1080/01431161.2013.838711

The carbon use efficiency (CUE) of a forest, calculated as the ratio of net primary productivity (NPP) to gross primary productivity (GPP), measures how efficiently a forest sequesters atmospheric carbon. Some prior research has suggested that CUE varies with environmental conditions, while other suggests that CUE is constant. Research using Moderate Resolution Imaging Spectroradiometer (MODIS) data has indicated a variable CUE, but those results are suspected because MODIS NPP data have not been well validated. We tested two questions. First, whether MODIS CUE is constant or whether it varies by forest type, climate, and geographic factors across the eastern USA. Second, whether those results occur when field-based NPP data are employed. We used MODIS model-based estimates of GPP and NPP, and forest inventory and anlaysis (FIA) field-based estimates of NPP data. We calculated two estimates of CUE for forest in 390 km 2 hexagons: (1) MODIS CUE as MODIS NPP divided by MODIS GPP and (2) F/M Z CUE as the standardized difference between FIA NPP and MODIS GPP. MODIS CUE and F/M Z CUE both varied similarly and significantly in relation to forest type, and climatic and geographic factors, strongly supporting a variable rather than a constant CUE. The CUE was significantly higher in deciduous than in mixed and evergreen forests. Regression models indicated that CUE decreased with increases in temperature and precipitation and increased with latitude and altitude. The similar trends in MODIS CUE and F/M Z CUE support the use of the more easily obtained MODIS CUE.