Collaborative research: A landscape resistance mapping approach to understanding species invasion patterns

合作研究：了解物种入侵模式的景观阻力绘图方法

• 批准号: 1556767
• 负责人: Derek Johnson
• 金额: $ 46.49万
• 依托单位: Virginia Commonwealth University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-01 至 2021-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1556767&HistoricalAwards=false
• 关键词: Collaborative; research; landscape; resistance; mapping

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.

全球自然群落的变化正在威胁着全世界的生物多样性和生态系统结构。大量物种通过国际贸易和人类贩运在全球范围内运输。非本地物种入侵包括自然区域、农业景观和用材林在内的无数栖息地，改变自然生态群落，减少生态系统服务，并造成估计每年高达数十亿美元的经济损失。随着入侵物种在更大区域的扩散，损害和成本进一步增加。了解促进和防止范围扩张的条件对于预测入侵物种的传播和为物种保护工作提供信息至关重要。在物种分布范围的边缘，自然和人为辅助的运动与当地人口动态以复杂的方式相互作用，以确定传播动态。这个项目的核心是一个基本问题：物种范围扩张的驱动因素是什么？多个过程如何相互作用以形成入侵模式？研究人员将通过研究一种臭名昭著的北美入侵者吉普赛蛾的入侵模式来解决这个问题。舞毒蛾周期性地使大片阔叶林落叶，对生态群落、木材生产和娱乐活动产生负面影响。舞毒蛾的入侵前沿从明尼苏达州一直延伸到北卡罗来纳州，并以平均每年约10公里的速度扩张。该项目填补的知识空白将为管理和保护策略提供信息，最终降低非本地入侵者的环境和经济成本，并保持美国的生物多样性。研究人员将使用详尽的时空数据集，每年量化舞毒蛾2000公里长的范围边缘。该项目将尖端的景观遗传学与当地人口动态的详细分析相结合，为用于阐明当地人口过程，景观连通性和该物种的人为运动如何相互作用以驱动传播模式的模型模拟提供信息。拟议的研究测试与三个主要目标相关的假设：1）量化景观特征和空间协方差对低密度种群动态的影响，2）使用空间遗传谱系来了解景观特征和人类交通模式如何影响遗传结构和运动，3）整合人口统计和遗传信息来确定景观特征，人类运动，局部种群过程通过在种群动态和运动参数的分层图上模拟入侵来驱动大规模入侵模式。