安徽农业大学学报2018，Vol.45Issue(1)：37-44,8.DOI:10.13610/j.cnki.1672-352x.20180302.026
基于InVEST模型的崇明岛野生蜜蜂传粉服务功能分析
Pollination service analysis of Chongming wild bee based on InVEST model
摘要
Abstract
Pollination is an important service function of ecosystem,and bees are the most important pollinators in pollination service;however,research on wild bee pollination in China is still very limited.Simulation of the wild bee abundance can protect wild bees and their habitats and save pollination costs to better protect and exploit wild bee resources.The abundance of wild bee was investigated by pollinator abundance using the crop pollination module of InVEST model and the result was analyzed by ArcGIS.The results showed that:(1) When the farmland nearby forest and has a small area of building and wetland,the wild bee abundance in this area was higher and the farmland received a better wild bee pollination service.(2)The farmland in the midwest area of Chongming Island had higher wild bee abundance than in other areas.This area should be protected and crops needing insect pollination should be cultivated and new architecture should be avoided and new development of tourism should be limited.The farmland in the east and near the border of Chongming Island has lower wild bee abundance.More trees and flowers should be planted to create a more suitable habitat for wild bees.(3) A long-term crop production plan in Chongming Island should be made based on the pattern of wild bee abundance.It is recommended that crops such as watermelon and oranges that need insect pollination service should be planted in the midwest of Chongming Island to protect and utilize the wild bee resources.And crops that need less insect pollination service should be planted in the east and border areas of Chongming Island.关键词
野生蜜蜂/InVEST模型/丰度/传粉服务/崇明岛Key words
wild bee/InVEST model/abundance/pollination service/Chongming Island分类
农业科技引用本文复制引用
张瑞峰,王多多,周梦云,蔡永立..基于InVEST模型的崇明岛野生蜜蜂传粉服务功能分析[J].安徽农业大学学报,2018,45(1):37-44,8.基金项目
国家自然科学基金面上项目(31670474)和科技部重大研发计划“长三角城市群区域生态承载力评估与提升技术研究”(2016YFC0502701)共同资助. （31670474）
