Contrasting determinants for the introduction and establishment success of exotic birds in Taiwan using decision trees models

PeerJ

article

Shih-Hsiung Liang¹  Bruno Andreas Walther²  Bao-Sen Shieh³ 

[1] Department of Biotechnology, National Kaohsiung Normal University;Master Program in Global Health and Development, College of Public Health, Taipei Medical University;Department of Biomedical Science and Environmental Biology, Kaohsiung Medical University;Department of Medical Research, Kaohsiung Medical University Hospital

关键词: Biological invasion;    Alien birds;    Model comparison;    Gradient boosting;    Random forest;   

DOI  :  10.7717/peerj.3092

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

BackgroundBiological invasions have become a major threat to biodiversity, and identifying determinants underlying success at different stages of the invasion process is essential for both prevention management and testing ecological theories. To investigate variables associated with different stages of the invasion process in a local region such as Taiwan, potential problems using traditional parametric analyses include too many variables of different data types (nominal, ordinal, and interval) and a relatively small data set with too many missing values.MethodsWe therefore used five decision tree models instead and compared their performance. Our dataset contains 283 exotic bird species which were transported to Taiwan; of these 283 species, 95 species escaped to the field successfully (introduction success); of these 95 introduced species, 36 species reproduced in the field of Taiwan successfully (establishment success). For each species, we collected 22 variables associated with human selectivity and species traits which may determine success during the introduction stage and establishment stage. For each decision tree model, we performed three variable treatments: (I) including all 22 variables, (II) excluding nominal variables, and (III) excluding nominal variables and replacing ordinal values with binary ones. Five performance measures were used to compare models, namely, area under the receiver operating characteristic curve (AUROC), specificity, precision, recall, and accuracy.ResultsThe gradient boosting models performed best overall among the five decision tree models for both introduction and establishment success and across variable treatments. The most important variables for predicting introduction success were the bird family, the number of invaded countries, and variables associated with environmental adaptation, whereas the most important variables for predicting establishment success were the number of invaded countries and variables associated with reproduction.DiscussionOur final optimal models achieved relatively high performance values, and we discuss differences in performance with regard to sample size and variable treatments. Our results showed that, for both the establishment model and introduction model, the number of invaded countries was the most important or second most important determinant, respectively. Therefore, we suggest that future success for introduction and establishment of exotic birds may be gauged by simply looking at previous success in invading other countries. Finally, we found that species traits related to reproduction were more important in establishment models than in introduction models; importantly, these determinants were not averaged but either minimum or maximum values of species traits. Therefore, we suggest that in addition to averaged values, reproductive potential represented by minimum and maximum values of species traits should be considered in invasion studies.

【 授权许可】

CC BY