## 1 Introduction  
The increasing trend of greenhouse gases (GHGs) in the atmosphere over the past 100 years has been reported by the Intergovernmental Panel on Climate Change (IPCC) [1]. As one of the largest sources of GHGs between the terrestrial ecosystems and the atmosphere [2], the soil CO\({}_{2}\) efflux (FCO\({}_{2}\)), composed of belowground autotrophic respiration (i.e., plant roots and rhizosphere microbial respiration) and heterotrophic respiration (including soil microbial and animal respiration), is the major carbon source to the atmosphere [3; 4; 5] and plays a vital role in the global carbon cycle and biogeochemical processes [6; 7]. Previous studies suggested that FCO\({}_{2}\) accounted for nearly 10% of annual atmospheric CO\({}_{2}\) and constitutes about 45-80% of the total ecosystem respiration, which is considered as the second-largest carbon flux pathway in the terrestrial carbon cycle with magnitude next to gross primary productivity [8; 9; 10]. Since the influence of FCO\({}_{2}\) is critical in the global carbon cycle, a small change in FCO\({}_{2}\) may severely affect the atmospheric CO\({}_{2}\) concentration and the terrestrial carbon balance, leading to crucial positive or negative feedbacks to the global climate system [11; 12]. Therefore, accurately assessing the spatiotemporal variations of FCO\({}_{2}\) will make a great contribution to the global carbon budgets, the mitigation of global warming, and the precise prediction of future climate change [5; 13; 14]. Several methods have been developed and applied to estimate the FCO\({}_{2}\) from forest ecosystems. Traditionally, FCO\({}_{2}\) is obtained through in-situ measurement methods, such as the automated closed chamber method is the most popular pathway to measure the carbon flux in forests, and has been proved to be effective in capturing the high-temporal resolution of FCO\({}_{2}\)[8; 15]. However, in-situ measurement is time-consuming and costly, and extremely hard in remote areas or harsh environments such as the subtropical and tropical forests. In addition, the topographic effects of subtropical forest soil CO\({}_{2}\) flux over large scales can not be well explored based on the in-situ studies [16]. To compensate for these disadvantages, based on the nature of the study site, empirical models are widely developed and used to estimate the FCO\({}_{2}\)[8]. The parameterization of empirical models is often based on site-based observations; parameters in models, however, are characterized by non-linear changes over time and space, and thus the initial parameters are spatially constrained. Accordingly, both the chamber methods and empirical models are limited in providing sufficient information about FCO\({}_{2}\) and thus in capturing the spatial variations of FCO\({}_{2}\) at a large spatial scale. Although hundreds of worldwide CO\({}_{2}\) observation networks can help overcome the limitations of spatial information to a certain extent, the in-situ measurements of CO\({}_{2}\) are mainly distributed in middle- and high-latitude regions such as Europe and North America. For the low-latitude regions such as the tropical and subtropical forested areas of Africa and China, they are quite scarce. This not only resulted in large uncertainties in global carbon budgets [15; 17] but also hinder us to accurately estimate the contribution of FCO\({}_{2}\) from low-latitude regions [5; 18]. Recently, although some studies dedicated to investigating the temporal variations of FCO\({}_{2}\) and its driving forces in subtropical and tropical forested regions based on the field measurements [19; 20; 21], they are mostly plot-level studies. The spatiotemporal variations of FCO\({}_{2}\) at large-spatial scales (e.g., the watershed scale) in dry seasons are rarely explored [22; 23; 24]. Moreover, studies have indicated that the FCO\({}_{2}\) in the dry season may offset most of the carbon fixed during the growing season.