MSA: Understanding biological invasions across spatial scales using Phylogenetic Generalized Linear Mixed Models (PGLMM)

非本地物种入侵正在造成全球生态系统退化和经济损失，在过去50年里，全球平均经济成本每年超过270亿美元。更为紧迫的是，预计在未来几十年，非本土物种的数量及其影响都将增加。例如，到2050年，大约有1500种非本地物种可能在北美建立。此外，生物入侵的经济成本预计每十年增加三倍。政府机构、保护组织和个人已经花费了大量资源来减轻物种入侵的影响，但结果远非令人满意。一个主要原因是我们仍然没有一个整体的和预测性的物种入侵的尺度理解。该项目将以国家生态观测站网络（NEON）收集的数据集为中心，编制一个开放获取的、跨尺度的物种入侵数据库。该数据库将使用先进的统计方法进行分析，以验证在不同空间尺度上，繁殖压力、非生物变量和生物变量对多个分类类群（植物、鸟类和甲虫）入侵的相对作用的理论。模型结果将通过建立一个在线交互式应用程序来传播，该应用程序可以动态地呈现和预测所有NEON站点的入侵者风险。此应用程序将自动更新新数据，以提供实时管理建议。一名博士后研究员和两名本科生将在项目期间接受宏观系统生物学、统计学和数据科学技能的培训。该项目的目标是测试繁殖压力、非生物变量（如气候、土地利用历史）和生物变量（如物种相互作用）在群落聚集背景下跨空间尺度驱动物种入侵的相对重要性。为了实现这一目标，本项目将改进系统发育广义线性混合模型（PGLMM）处理大数据集的能力，并将其应用于基于NEON的物种入侵综合数据库，在空间尺度上研究不同分类类群的生物入侵模式和机制。本项目将解决以下问题：1)非本地物种的功能性状是否与非生物变量相互作用以决定其分布？2)外来物种和本地物种之间的生物相互作用是否会影响外来物种的分布？3)繁殖体压力、非生物变量和生物变量在决定从本地到大陆尺度的非本地物种分布中的相对重要性是什么？该项目由环境生物学/宏观系统生物学部门、NEON使能科学计划和促进竞争研究的既定计划（EPSCoR）共同资助。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Non-native species invasions are causing worldwide ecosystem degradation and economic loss, with average global economic costs exceeding 27 billion dollars per year over the past five decades. More urgently, both the number of non-native species and their impacts are projected to increase over the coming decades. For example, approximately an additional 1,500 non-native species are likely to establish in North America by 2050. Furthermore, the economic costs of biological invasions are predicted to increase threefold per decade. Government agencies, conservation organizations, and private citizens have spent significant resources to mitigate the impacts of species invasions, but the outcomes are far from satisfactory. One main reason is that we still do not have a holistic and predictive understanding of species invasion across scales. This project will compile an open-access, cross-scale database of species invasion centered around the datasets collected by the National Ecological Observatory Network (NEON). This database will be analyzed using advanced statistical methods to test theory on the relative roles propagule pressure, abiotic variables, and biotic variables on invasions for multiple taxonomic groups (plants, birds, and beetles) across spatial scales. Model results will be disseminated by building an online interactive application that can dynamically present and forecast risks of invaders at all NEON sites. This application will be updated automatically with new data to provide real-time management recommendations. One postdoctoral researcher and two undergraduate students will be trained in macrosystem biology, statistical, and data science skills during the project.The goal of this project is to test the relative importance of propagule pressure, abiotic variables (e.g., climate, land-use history), and biotic variables (e.g., species interactions) in driving species invasions across spatial scales in the context of community assembly. To achieve this goal, this project will improve the ability of phylogenetic generalized linear mixed model (PGLMM) to work with large datasets and then apply it to the integrated database of species invasions based on NEON to investigate patterns and mechanisms of biological invasions of different taxonomic groups across spatial scales. This project will address the following questions: 1) Do functional traits of non-native species interact with abiotic variables to determine their distributions? 2) Do biotic interactions between non-native and native species in the recipient communities affect the distribution of non-native species? 3) What is the relative importance of propagule pressure, abiotic variables, and biotic variables in determining the distribution of non-native species from local to continental scales?This project is jointly funded by the Division of Environmental Biology/Macrosystem Biology and NEON Enabled Science program and the Established Program to Stimulate Competitive Research (EPSCoR).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.