R_JAGS code for estimation and analysis of species-area-relationship (SAR) parameters from NEON (National Ecological Observatory Network) data on plant surveys

Invasive species science is heavily geared toward the invasive agent. However, management to protect native species also requires a proactive approach focused on understanding the features affecting community vulnerability to invasion impacts. Vulnerability is likely the result of factors acting across spatial scales, from local to regional, and it is the combined effects of these factors that will determine the magnitude of vulnerability. We introduce an analytical framework that quantifies the scale-dependent impact of biological invasions from the shape of the native species-area-relationship (SAR). We leverage newly available, biogeographically extensive vegetation data from the US National Ecological Observatory Network to assess plant community vulnerability to invasion impact as a function of factors acting across scales. We analyzed more than 1000 SARs widely distributed across the USA along environmental gradients and under different levels of invasion. Results show that a decr...

入侵物种研究长期以来高度聚焦于入侵物种本身。然而，旨在保护本地物种的入侵管理工作，同样需要采取前瞻性策略，聚焦于解析影响群落对入侵影响易感性的各类特征。群落易感性大概率是多空间尺度（从局地到区域）下多种因子共同作用的结果，而这些因子的综合效应将决定易感性的强弱程度。本研究提出了一种分析框架，可基于本地物种-面积关系（native species-area-relationship, SAR）的曲线形态，量化生物入侵的尺度依赖性影响。我们利用美国国家生态观测站网络（US National Ecological Observatory Network）新近发布的、覆盖生物地理范围极广的植被数据，以跨尺度作用的各类因子为关联变量，评估植物群落对入侵影响的易感性。我们分析了全美范围内沿环境梯度分布、且处于不同入侵程度下的1000余条物种-面积关系曲线。研究结果显示，[原文此处存在截断，仅显示至“a decr...”]