Biomass and its allocation of Chinese forest ecosystems

Forest biomass and its allocation have long been considered important in forest ecosystem structure and function. However, discrete forest biomass data and its allocation to various forest components must be standardized to explore many ecological questions, e.g., plant allometric scaling laws, biomass allocation theory, and terrestrial carbon cycling. Currently, available data sets focus either on regions other than China, or studies in China are spatially and/or temporally limited, e.g., specific habitats and/or time periods. Therefore, the applicability of conclusions to world or China forests might be problematic. Consequently, in the present study, published studies (during the 1978–2008 period) on biomass and its allocations in China's forests (excluding Hong Kong, Macao, and Taiwan) were collected and critically reviewed, and a comprehensive forest biomass data set of China was developed. The data set included the following biomass data: tree overstory components (stems, branches, leaves, and roots, among all other plant material), the understory vegetation (saplings, shrubs, herbs, and mosses), woody liana vegetation, and the necromass components of dead organic matter (litterfall, suspended branches, and dead trees). Moreover, associated information was also included, i.e., geographical location, climate, soil fertility, stand description, sampling regime (the dimension and sample size of plots), and biomass measurement methods. The data set included 1607 entries for 348 study sites, which exhibited a broad spatial distribution, and covered broad climatic gradients (−5.1°C to 23.8°C in mean annual temperature and 223–2515 mm in mean annual precipitation). Our data set can be used to verify the accuracy of models used to budget China's forest carbon dynamics, and also provides an opportunity to further elucidate and confirm general principles and patterns in ecology. Finally, the data set is freely available for noncommercial scientific applications.