Latitude is an important factor that influences the carbon stock of Moso bamboo (Phyllostachys pubescens) forests. Accurate estimation of the carbon stock of Moso bamboo forest can contribute to sufficient evaluation of forests in carbon sequestration worldwide. Nevertheless, the effect of latitude on the carbon stock of Moso bamboo remains unclear. In this study, a field survey with 36 plots of Moso bamboo forests along a latitude gradient was conducted to investigate carbon stock. Results showed that the diameter at breast height (DBH) of Moso bamboo culms increased from 8.37 cm to 10.12 cm that well fitted by Weibull model, whereas the bamboo culm density decreased from 4722 culm ha−1 to 3400 culm ha−1 with increasing latitude. The bamboo biomass carbon decreased from 60.58 Mg C ha−1 to 48.31 Mg C ha−1 from north to south. The total carbon stock of Moso bamboo forests, which comprises soil and biomass carbon, ranged from 87.83 Mg C ha−1 to 119.5 Mg C ha−1 and linearly increased with latitude. As a fast-growing plant, Moso bamboo could be harvested amounts of 6.0 Mg C ha−1 to 7.6 Mg C ha−1 annually, which indicates a high potential of this species for carbon sequestration. Parameters obtained in this study can be used to accurately estimate the carbon stock of Moso bamboo forest to establish models of the global carbon balance.

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Understanding the spatial variability of soil organic carbon (SOC) must be enhanced to improve sampling design and to develop soil management strategies in terrestrial ecosystems. Moso bamboo (Phyllostachys pubescens Mazel ex Houz.) forests have a high SOC storage potential; however, they also vary significantly spatially. This study investigated the spatial variability of SOC (0-20 cm) in association with other soil properties and with spatial variables in the Moso bamboo forests of Jian’ou City, which is a typical bamboo hometown in China. 209 soil samples were collected from Moso bamboo stands and then analyzed for SOC, bulk density (BD), pH, cation exchange capacity (CEC), and gravel content (GC) based on spatial distribution. The spatial variability of SOC was then examined using geostatistics. A Kriging map was produced through ordinary interpolation and required sample numbers were calculated by classical and Kriging methods. An aggregated boosted tree (ABT) analysis was also conducted. A semivariogram analysis indicated that ln(SOC) was best fitted with an exponential model and that it exhibited moderate spatial dependence, with a nugget/sill ratio of 0.462. SOC was significantly and linearly correlated with BD (r = −0.373**), pH (r = −0.429**), GC (r = −0.163*), CEC (r = 0.263**), and elevation (r = 0.192**). Moreover, the Kriging method requires fewer samples than the classical method given an expected standard error level as per a variance analysis. ABT analysis indicated that the physicochemical variables of soil affected SOC variation more significantly than spatial variables did, thus suggesting that the SOC in Moso bamboo forests can be strongly influenced by management practices. Thus, this study provides valuable information in relation to sampling strategy and insight into the potential of adjustments in agronomic measure, such as in fertilization for Moso bamboo production.