globalchange  > 全球变化的国际研究计划
项目编号: 1556842
项目名称:
Collaborative Research: A Landscape Resistance Mapping Approach to Understanding Species Invasion Patterns
作者: Jeffrey Holland
承担单位: Purdue University
批准年: 2016
开始日期: 2016-07-01
结束日期: 2019-06-30
资助金额: 165510
资助来源: US-NSF
项目类别: Standard Grant
国家: US
语种: 英语
特色学科分类: Biological Sciences - Environmental Biology
英文关键词: species ; invasion pattern ; landscape feature ; local population process ; non-native ; researcher ; local population dynamics ; gypsy moth ; invasive species ; large number ; layered map ; human traffic ; landscape connectivity ; main objective ; human traffic pattern ; natural community ; natural ecological community ; anthropogenic movement ; agricultural landscape ; spatial genetic lineage ; human-assisted movement interplay ; conservation strategy ; research test hypothesis ; north carolina ; species conservation effort ; movement parameter ; non-native species ; ecological community ; spatial covariance ; cutting-edge landscape genetics ; recreational activity ; global change ; detailed analysis ; spread pattern ; international trade ; model simulation ; large tract ; united states ; myriad habitat ; km long range edge ; spread dynamics ; knowledge gap ; genetic information ; non-native invader ; exhaustive spatiotemporal dataset ; range expansion ; complex way ; natural area ; low-density population ; average rate ; fundamental question ; human movement ; infamous north american invader ; hardwood forest
英文摘要: Global changes to natural communities are threatening biodiversity and ecosystem structure worldwide. Large numbers of species are transported globally through international trade and human traffic. Non-native species invade myriad habitats that include natural areas, agricultural landscapes, and timber forests, altering natural ecological communities, reducing ecosystem services, and causing economic losses that are estimated at up to billions of dollars annually. Damages and costs increase further as invasive species spread across larger regions. Understanding the conditions that facilitate and prevent range expansion are critical to both predicting the spread of invasive species and informing species conservation efforts. At species range edges, natural and human-assisted movement interplay with local population dynamics in complex ways to determine spread dynamics. This project centers on a fundamental question: What are the drivers of species range expansion and how do multiple processes interact to shape invasion patterns? Researchers will address this question by studying the invasion pattern of an infamous North American invader, the gypsy moth. The gypsy moth periodically defoliates large tracts of hardwood forest, negatively affecting ecological communities, timber production, and recreational activities. The gypsy moth invasion front stretches from Minnesota to North Carolina and is expanding at an average rate of approximately 10 kilometers per year. Knowledge gaps filled by this project will inform management and conservation strategies to ultimately reduce the environmental and economic costs of non-native invaders and maintain biodiversity in the United States.

The researchers will use an exhaustive spatiotemporal dataset that annually quantifies the 2000 km long range edge of the gypsy moth. This project combines cutting-edge landscape genetics with detailed analyses of local population dynamics to inform model simulations used to elucidate how local population processes, landscape connectivity, and anthropogenic movement of this species interact to drive spread patterns. The proposed research tests hypotheses associated with three main objectives: 1) quantify effects of landscape features and spatial covariance on the dynamics of low-density populations, 2) use spatial genetic lineages to understand how landscape features and human traffic patterns affect genetic structure and movement, and 3) integrate demographic and genetic information to determine how landscape features, human movement, and local population processes drive large-scale invasion patterns by simulating invasion on layered maps of population dynamic and movement parameters.
资源类型: 项目
标识符: http://119.78.100.158/handle/2HF3EXSE/91847
Appears in Collections:全球变化的国际研究计划
科学计划与规划

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Jeffrey Holland. Collaborative Research: A Landscape Resistance Mapping Approach to Understanding Species Invasion Patterns. 2016-01-01.
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