The herbaceous layer is an important component of forest ecosystems and plays an important role in maintaining forest biodiversity. To understand the mechanisms shaping the forest herb community patterns over multiple growing seasons, we used herbaceous data collected in a 25 ha broad-leaved Korean pine (Pinus koraiensis) mixed forest plot in Changbai Mountain, Northeast China and fitted species abundance distributions (SADs) using different models. We used both pure statistical models including log-normal, log-series, and mechanistic models, including two niche models (broken-stick and niche preemption) and two neutral models (metacommunity zero-sum multinomial distribution and Volkov model). Further, we applied the AIC and Kolmogorov-Smirnov tests to compare the goodness-of-fit of these models. Our results showed: (1) The observed SADs of the herb layer varied by season. While there were similar proportions of rare and common species in spring, there were more species with moderate abundances in summer and more rare species in autumn. (2) The best-fitting models of SADs were similar in different seasons. In our analyses, the log-series model was the best pure statistical model across the three seasons. For the mechanistic models, neutral models •森林动态监测样地专题•
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