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Community density of grassland effect on soil carbon dynamics: Field survey and analyses from a 45-year natural recovery time-sequence on the Loess Plateau, China
Land Degradation & Development ( IF 4.7 ) Pub Date : 2021-09-22 , DOI: 10.1002/ldr.4103
Zhao Fang 1 , Zengming Ke 1 , Feng Jiao 1, 2
Affiliation  

Community density of grassland has obvious impacts on the absorption, sequestration, and accumulation of soil carbon (C). However, few studies have examined the effect of community density on soil C dynamics and their internal driving forces after cropland abandonment. Here, we synthesized the responses of soil C to community density of grassland over a 45-year time-sequence along a natural restoration time sequence. The results showed that the soil C content during the late-successional period was greater than that during the early-successional period, that is, annual C storage rates for the first sequence (1–15 years) for the 0–60 cm depth profiles were −0.34, −0.27, −0.15 to 0.02 Mg-C ha−1 yr−1, in the ≤10, 11–20, 21–30, and >30 community densities. And the third sequence (31–45 years) presented values that were 79.28% and 44.60% greater than those of the initial stage of vegetation restoration (CK) for the 0–20 and 0–60 cm profiles, respectively. The increased soil C storage rates of the late-successional sequence were associated with both increased aboveground production and root biomass for this sequence and the presence of multiple species, especially Leguminosae and Gramineae species, with developed roots. Overall, the effects of community density on soil C were regulated by the recovery time, root mass, and species genera. Furthermore, our results suggest that soil may still be a carbon source even after 15 years of the abandonment restoring, and high community density may greatly increase C capture and storage rates in abandoned lands. The findings enhance the understanding of soil C sequestration and accumulation responses to community density following long-term natural vegetation succession, providing support for estimating and predicting the regional C budget and global C cycle.
更新日期:2021-09-22
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