Biodiversity Science ›› 2017, Vol. 25 ›› Issue (9): 966-971.doi: 10.17520/biods.2017019

• Original Papers: Plant Diversity • Previous Article     Next Article

Predicting modes of seed dispersal using plant life history traits

Zhiwen Guo, Jingming Zheng*()   

  1. College of Forestry, Beijing Forestry University, Beijing 100083
  • Received:2017-01-17 Accepted:2017-06-09 Online:2017-10-04
  • Zheng Jingming
  • About author:# Co-first authors

Mode of seed dispersal is an important trait for understanding geographical distributions, population dynamics, and community composition of plant species. However, data of dispersal modes are scarce for Chinese plant species. Previous studies have shown that growth form, plant height, fruit type, and seed mass have strong correlations with seed dispersal modes, thus predictions using modelling could be an alternative to gain this information. We collected information on growth forms, plant height, fruit types, seed mass, and dispersal modes from 360 kinds of Chinese angiosperm plants, and built a neural network model (NNET), decision tree (TREE), Fisher linear discriminant model (LDA), and support vector machine model (SVM) to predict seed syndromes from these four traits. For each model, an 80% sample (288 species) was randomly drawn from dataset as the training sample, with remaining 20% of data was used as a test sample. Results showed that all four models achieved rather good predictions, and the average total correctness rate for the NNET, TREE, LDA, and SVM was 78.90%, 77.09%, 77.81%, 78.14%, respectively. The neural network model had the highest correctness rates for different dispersal modes, i.e., zoochory (81.32%), autochory (74.90%), and anemochory (81.45%). This paper establishes the basis for the prediction of seed dispersal modes.

Key words: dispersal modes, fruit type, growth form, plant height, seed mass, prediction model

Table 1

The protocol of classification level in five life history traits of plant"

生活史性状 Life history trait 分类水平 Class level 参考文献 Reference
生长型 Growth form 草本; 灌木; 藤本; 乔木 Herb; Shrub; Vine; Tree Flora Reipublicae Popularis Sinicae, 1979
株高 Plant height < 0.5 m; 0.5-2.0 m; 2.0-5.0 m; > 5.0 m Westoby et al, 1990
果实类型 Fruit type 裂果; 闭果; 肉质果 Dehisce; Achene; Fruit Flora Reipublicae Popularis Sinicae, 1979
种子质量 Seed mass < 0.1 mg; 0.1-100 mg; > 100 mg Westoby et al, 1996
扩散方式 Dispersal mode 无助力扩散; 风扩散; 动物扩散 Autochory; Anemochory; Zoochory Baskin & Baskin, 1998,2014

Table 2

Correlations between five life history traits of plants"

Gamma 系数
Gamma index
Growth form
Plant height
Fruit type
Seed mass
株高 Plant height 0.96**
果实类型 Fruit type 0.55** 0.47**
种子质量 Seed mass 0.69** 0.64** 0.49**
扩散方式 Dispersal mode 0.70** 0.63** 0.87** 0.50**

Fig. 1

The discriminant rates of four models to seed dispersal modes. NNET, Neural network model; TREE, Decision tree model; LDA, Fisher linear discriminant model; SVM, Support vector machine model."

Fig. 2

The discriminant rates of neural network model to three dispersal modes"

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