## 1 Introduction
The research on the impact of tropical cyclones on mangrove ecosystems and their recovery is abundant, but there are relatively few studies on the carbon dynamics of mangroves before, during, and after tropical cyclones. Especially, there is a lack of quantitative assessments of the impacts of post-disaster mangroves on the carbon cycle at the regional ecosystem scale [36]. The loss of leaves and breakage of trunks lead to the introduction of litter, organic carbon, nitrogen, and other nutrients into the soil, which affects the activity of soil microbes and the supply of nutrients [21]. This impacts the carbon cycle of the mangrove ecosystem [37]. Thus, further research on the impacts of tropical cyclones on subtropical mangrove forest productivity and its post-disturbance is needed to enhance our understanding of the carbon cycle dynamics. In the view of the assessment process, it is first necessary to know the degree of mangrove damage and the corresponding area. The damaged area can be obtained by remote sensing techniques, but it is difficult to obtain an accurate degree of damage. Field measurements are considered to be a more accurate method, but harsh environmental conditions and high costs often limit their use to providing an estimation of mechanical damage at the quadrat scale [38; 39]. Using interpolation methods to upscale this survey to the regional-scale results in significant uncertainties in the estimated loss of GPP [40]. Additionally, using RS-based vegetation indices (VIs), such as the enhanced vegetation index (EVI) and normalized difference vegetation index (NDVI), to estimate the loss of gross primary production (GPP) may seem like a convenient approach [41], but it also presents the challenge of establishing robust and quantitative relationships between VIs and production [42; 43; 44]. Process-based models' simulations can also be utilized to estimate the effect of tropical cyclones on the GPP of the mangrove ecosystem [45]. However, currently, there is significant variability in the results among these models [46]. The functions and parameters of these models are largely based on empirical parameters from terrestrial ecosystems [47], but their applicability to mangrove ecosystems has yet to be validated. Even if using the process-based model specifically for mangroves, the complexity of the data and parameters required would still pose a challenge for the evaluation of the model [45]. The change in GPP of the mangrove ecosystem can be more accurately obtained through the use of the eddy covariance method [39]. However, the effective coverage area of the flux tower is limited to a maximum of a several km radius [48], while the impact of tropical cyclones is much wider, and the damage caused exhibits clear regional differences [23; 24]. Combining EC with RS is an effective method for evaluating the GPP of mangrove ecosystems at a regional scale [39; 49]. LUE is a more practical approach [50], and among LUEs, the mangrove vegetation photosynthesis light-use efficiency (MVP-LUE), which considers the growth limiting factors of mangrove vegetation, is the model designed to assess the mangrove ecosystem [49]. It has been applied to estimate the GPP of mangrove ecosystems in China across various latitudes and has produced good results. Climate change is expected to result in an increase in the number of stronger tropical cyclones [51; 52; 53; 54; 55]. The changes in tropical cyclone activity are difficult to predict at a regional level [19] and pose a greater threat to the carbon cycle in mangrove ecosystems [56]. Therefore, this study focuses on direct-impact tropical cyclones (excluding tropical depressions and tropical storms with no obvious damage), which have a more significant impact on mangrove ecosystems, and the sub-tropical mangrove distribution area on Hainan Island, which hosts all of China's mangrove species, 20 families and 38 species [57], located on the northern edge of the tropics, as the study area.