Biodiversity Science ›› 2015, Vol. 23 ›› Issue (5): 641-648.doi: 10.17520/biods.2015089

Special Issue: Forest Dynamics Monitoring

• Orginal Article • Previous Article     Next Article

Herb layer species abundance distribution patterns in different seasons in an old-growth temperate forest in Changbai Mountain, China

Shan Zhang1, 2, Fei Lin1, Zuoqiang Yuan1, Xu Kuang1, 2, Shihong Jia1, 2, Yunyun Wang1, 2, Yanyan Suo1, 2, Shuai Fang1, 2, Xugao Wang1, Ji Ye1, Zhanqing Hao1, *()   

  1. 1 State Key Laboratory of Forest and Soil Ecology, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016
    2 University of Chinese Academy of Sciences, Beijing 100049
  • Received:2015-04-11 Accepted:2015-05-28 Online:2015-10-12
  • Hao Zhanqing

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 performed better at explaining patterns of SADs than niche models. The metacommunity zero-sum multinomial distribution model was the best model in spring and summer and the Volkov model was the best one in autumn. This indicates that stochastic processes may play a dominant role in maintaining the herb species abundance distributions. Our study showed that although the SAD patterns varied over growing seasons for the herb layer in the broad-leaved Korean pine mixed forest, the underlying mechanisms governing these patterns are similar and neutral models always perform better than niche models in fitting the SADs.

Key words: forest herb layer, niche process, neutral process, statistical model, model fitting

Fig. 1

Species abundance histograms in different seasons in the broad-leaved Korean pine mixed forest in Changbai Mountain"

Table 1

Goodness-of-fit test of six models in different seasons"

对数正态模型 Log-normal
对数级数模型 Log-series model 断棍模型 Broken-stick model 生态位优先占领模型
Niche preemption model
复合群落零和多项式模型 Metacommunity zero-sum multinomial distribution model Volkov模型
Volkov model
901.3 0.11 885.3 0.08 1,102.9 0.51** 307,698.7 0.31** 885.5 0.08 888.9 0.11
883.2 0.08 876.8 0.08 1,038.3 0.46** 112,380.8 0.34** 877.3 0.08 938.0 0.20
801.2 0.10 789.5 0.10 981.6 0.57** 63,593.5 0.44** 790.1 0.11 789.9 0.12

Table 2

Parameters of neutral model in different seasons in the broad-leaved Korean pine mixed forest in Changbai Mountain"

复合群落零和多项式模型 Metacommunity zero-sum multinomial distribution model Volkov 模型
Volkov model
θ θ m
春季 Spring 7.78 355.00 1×10-3
夏季 Summer 10.12 75.96 0.25
秋季 Autumn 11.50 11.68 0.50

Fig. 2

Herb species abundance distributions and model fittings in different seasons in the broad-leaved Korean pine mixed forest in Changbai Mountain. Observed values are shown by points, Log-normal, Log-series, Preemption, Broken-stick, MZSM and Volkov represent log-normal model, log-series model, niche preemption model, broken-stick model, metacommunity zero-sum multinomial distribution model and Volkov model, respectively."

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