Estimation of global soil respiration by accounting for land-use changes derived from remote sensing data. (15th September 2017)

• Record Type: Journal Article
• Authors: Adachi, Minaco; Ito, Akihiko; Yonemura, Seiichiro; Takeuchi, Wataru
• Is Part Of: Journal of environmental management. Volume 200(2017)
• Page Start: 97
• Page End: 104
• Publication Date: 2017-09-15
• Subjects: Soil temperature -- MODIS -- Land-use change; Environmental policy -- Periodicals; Environmental management -- Periodicals; Environment -- Periodicals; Ecology -- Periodicals; 363.705
• DOI: 10.1016/j.jenvman.2017.05.076
• Languages: English
• ISSNs: 0301-4797

Abstract

Abstract: Soil respiration is one of the largest carbon fluxes from terrestrial ecosystems. Estimating global soil respiration is difficult because of its high spatiotemporal variability and sensitivity to land-use change. Satellite monitoring provides useful data for estimating the global carbon budget, but few studies have estimated global soil respiration using satellite data. We provide preliminary insights into the estimation of global soil respiration in 2001 and 2009 using empirically derived soil temperature equations for 17 ecosystems obtained by field studies, as well as MODIS climate data and land-use maps at a 4-km resolution. The daytime surface temperature from winter to early summer based on the MODIS data tended to be higher than the field-observed soil temperatures in subarctic and temperate ecosystems. The estimated global soil respiration was 94.8 and 93.8 Pg C yr −1 in 2001 and 2009, respectively. However, the MODIS land-use maps had insufficient spatial resolution to evaluate the effect of land-use change on soil respiration. The spatial variation of soil respiration (Q10 ) values was higher but its spatial variation was lower in high-latitude areas than in other areas. However, Q10 in tropical areas was more variable and was not accurately estimated (the values were >7.5 or <1.0) because of the low seasonal variation in soil respiration in tropical ecosystems. To solve these problems, it will be necessary to validate our results using a combination of remote sensing data at higher spatial resolution and field observations for many different ecosystems, and it will be necessary to account for the effects of more soil factors in the predictive equations. Highlights: We estimated the global soil respiration using empirical equations based on field observation and climate data and land-use maps obtained via remote sensing. The global soil respiration was estimated to be 94.8 and 93.8 Pg C yr -1 in 2001 and 2009, respectively. The spatial variation of soil respiration (Q10 ) values was higher but its spatial variation was lower in high-latitude areas than in other areas. It will be necessary to develop more accurate estimates of global soil respiration by input data and land-use maps at higher spatial resolution.