DOI: 10.5061/dryad.z612jm6dx
title: R_JAGS code for estimation and analysis of species-area-relationship (SAR) parameters from NEON (National Ecological Observatory Network) data on plant surveys

description: 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
 decrease in native richness is consistently associated with invasive
 species cover, but it is only at relatively high levels of invasion that
 native richness is compromised. After accounting for variation in baseline
 ecosystem diversity, net primary productivity, and human modification,
 ecoregions that are colder and wetter seem to be most vulnerable to losses
 of native plant species at the local level, while warmer and wetter areas
 seem most susceptible at the landscape level. We also document how the
 combined effects of cross-scale factors result in a heterogenous spatial
 pattern of vulnerability. This pattern cannot be predicted by analyses at
 any single scale, underscoring the importance of accounting for factors
 acting across scales. Simultaneously assessing differences in
 vulnerability between distinct plant communities at local, landscape and
 regional scales provided outputs that can be used to inform policy and
 management aimed at reducing vulnerability to the impact of plant
 invasions.
description: Code used for the analysis of species-area-relationships (ASR)
 data. Code used to estimate SAR parameter, and code to analyze SAR
 parameters as a function of net primary productivity (NPP), human
 modification index (HMI), invasive ground cover, temperature and
 precipitation. Analyses and predictions
 were run in JAGS (Plummer 2003) using the ‘rjags’ package in R (R Core
 Team 2021).
description: All data used to run this code are publicly available
 at: Plant richness,
 number of species, and plant cover data (NEON 2020) were downloaded from
 the NEON data portal application programming interface with the NEON
 Utilities package (Lunch et al. 2020). 
 NPP: http://files.ntsg.umt.edu/data/NTSG_Products/MOD17/MODIS_250/modis-250-npp/ HMI: https://doi.org/10.6084/m9.figshare.7283087.v1 Climate: https://www.wordldclim.org/data/index.html   All data sets were accessed May 2020. Lunch, C. K., C. M. Laney, and NEON (National Ecological Observatory Network). 2020. neonUtilities: Utilities for Working with NEON Data. R package version 1.3.4. . https://github.com/NEONScience/NEON-utilities. NEON (National Ecological Observatory Network). 2020. Plant presence and percent cover. DP1.10058.001. https://data.neonscience.org.