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A SIMPLE SOIL ORGANIC‐MATTER MODEL FOR BIOMASS DATA ASSIMILATION IN COMMUNITY‐LEVEL CARBON CONTRACTS
Author(s) -
Traoré P. C. S.,
Bostick W. M.,
Jones J. W.,
Koo J.,
Goïta K.,
Bado B. V.
Publication year - 2008
Publication title -
ecological applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.864
H-Index - 213
eISSN - 1939-5582
pISSN - 1051-0761
DOI - 10.1890/07-1133.1
Subject(s) - environmental science , data assimilation , soil carbon , carbon sequestration , soil water , soil organic matter , organic matter , fertilizer , greenhouse gas , soil science , atmospheric sciences , ecology , agronomy , carbon dioxide , meteorology , biology , geography , geology
Soil carbon (C) sequestration has been proposed as a transitional win–win strategy to help replenish organic‐matter content in depleted agricultural soils and counter increases in atmospheric greenhouse gases. Data assimilation and remote sensing can reduce uncertainty in sequestered C mass estimates, but simple soil organic carbon (SOC) models are required to make operational predictions of tradeable amounts over large, heterogenous areas. Our study compared the performance of RothC26.3 and a reduced compartmental model on an 11‐year fertilizer trial in subhumid West Africa. Root mean square error (RMSE) differences of 0.05 Mg C/ha between models on total SOC predictions suggest that for contractual purposes, SOC dynamics can be simulated by a two‐pool structure with labile and stable components. Faster (seasonal) and slower (semicentennial and beyond) rates can be approximated by constants as instantaneous and infinite decay. In these systems, simulations indicate that cereal residue incorporation holds most potential for mitigation of transient C loss associated with recent land conversion to agriculture.