Understanding Interrelationships Among Predictors (Age, Gender, and Origin) of Local Ecological Knowledge1

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• 作者：Tamia Souto (1) (2)
  Tamara Ticktin (1)
  
• 关键词：Local ecological knowledge ; mestizo ; Venezuela ; multiple regression analysis
• 刊名：Economic Botany
• 出版年：2012
• 出版时间：June 2012
• 年：2012
• 卷：66
• 期：2
• 页码：149-164
• 全文大小：649KB
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• 作者单位：Tamia Souto (1) (2)
  Tamara Ticktin (1)
  
  1. Botany Department, University of Hawai’i at Manoa, 3190 Maile Way, Honolulu, HI, 96822, USA
  2. Center for Conservation Education and Sustainability, Smithsonian Conservation Biology Institute, National Zoological Park, P.O. Box 37012, MRC 0705, Washington, DC, 20013-7012, USA
  

文摘

Understanding Interrelationships among Predictors (Age, Gender, and Origin) of Local Ecological Knowledge. Understanding which factors predict local ecological knowledge can provide insight into how this knowledge is learned and how it may change in the future. We assess how knowledge of both useful plants and plant natural history vary according to gender, age, and origin in mestizo communities in Venezuela’s Caura Basin. Two sets of structured questionnaires were carried out with a total of 83 adults in three communities. Multiple regression analyses were used to identify the predictors of knowledge of 6 plant-use categories and natural history knowledge of 12 plant species. Gender, age, and origin (? generations in the Caura vs. foreign-born) were all important predictors of knowledge of useful plants and natural history; however, their importance differed between the two types of knowledge. Origin was a more important predictor of knowledge of useful plants, whereas age was more important in predicting knowledge of natural history. This suggests differences in how each type of knowledge is learned and transmitted. Gender was an important predictor variable in most models, reflecting gender roles in the Caura mestizo communities. Also, for most categories of plant-use knowledge, the interactions among predictors were significant, indicating that the effect of one variable depended on the level of the other. These results illustrate how overlooking interactions among variables, as most studies to date have done, can risk misinterpretation of results by simplifying complex situations.