Citizen science can complement professional invasive plant surveys and improve estimates of suitable habitat

Aim: Citizen science is a cost-effective potential source of invasive species occurrence data. However, data quality issues due to unstructured sampling approaches may discourage the use of these observations by science and conservation professionals. This study explored the utility of low-structure iNaturalist citizen science data in invasive plant monitoring. We first examined the prevalence of invasive taxa in iNaturalist plant observations and sampling biases associated with those data. Using four invasive species as examples, we then compared iNaturalist and professional agency observations and used the two datasets to model suitable habitat for each species. Location: HawaiÊ»i, USA Methods: To estimate the prevalence of invasive plant data, we compared the number of species and observations recorded in iNaturalist to botanical checklists for HawaiÊ»i. Sampling bias was quantified along gradients of site accessibility, protective status, and vegetation disturbance using a bias index...., , , # Data from: Citizen science can complement professional invasive plant surveys and improve estimates of suitable habitat Diversity and Distributions, 00, 1–16. [https://doi.org/10.1111/ddi.13749](https://doi.org/10.1111/ddi.13749) Access this dataset on Dryad: [https://doi.org/10.5068/D1769Q](https://doi.org/10.5068/D1769Q) ## R Scripts and Data Tables ### Scripts #### File: bias\_index.R Description: R script for calculating bias in: 1) all iNaturalist plant observations and 2) iNaturalist and professional observations of the 4 study species, Hedychium gardnerianum, Lantana camara, Leucaena leucocephala, and Psidium cattleianum. #### File: hsm.R Description: R script for: 1) producing Hedychium gardnerianum, Lantana camara, Leucaena leucocephala, and Psidium cattleianum habitat suitability models and 2) calculating overlap among model series with Schoener's D. ### Tables \[biasclasses folder] #### File: area\_disturb\_iv.txt Description: Comma-delimited file containing the ...### 研究目的 公民科学是获取入侵物种出现数据的高性价比潜在途径。然而，因采样方式非结构化引发的数据质量问题，可能阻碍科研与保护从业者使用这类观测数据。本研究探讨了低结构化的iNaturalist（iNaturalist）公民科学数据在入侵植物监测中的应用价值。我们首先分析了iNaturalist植物观测记录中入侵类群的占比，以及这些数据存在的采样偏差。以4种入侵植物为研究案例，我们对比了iNaturalist数据与专业机构观测数据，并利用两类数据集分别建模预测各物种的适宜生境。 ### 研究地点 美国夏威夷州 ### 研究方法 为估算入侵植物数据的占比，我们将iNaturalist平台收录的物种与观测数量与夏威夷植物名录进行了对比。我们通过偏差指数，沿着站点可达性、保护等级以及植被干扰度的梯度量化了采样偏差。…… ### 数据来源 《公民科学可辅助专业入侵植物调查并优化适宜生境估算》，发表于《Diversity and Distributions》（生物多样性与分布），第00卷，第1–16页，DOI：10.1111/ddi.13749。 可在Dryad平台获取本数据集：https://doi.org/10.5068/D1769Q --- ## R脚本与数据表 ### 脚本 #### 文件：bias_index.R 描述：该R脚本用于计算两类数据的采样偏差：1）所有iNaturalist植物观测记录；2）本研究涉及的4个物种——姜花（Hedychium gardnerianum）、马缨丹（Lantana camara）、银合欢（Leucaena leucocephala）及草莓番石榴（Psidium cattleianum）的iNaturalist观测数据与专业机构观测数据的采样偏差。 #### 文件：hsm.R 描述：该R脚本用于：1）构建姜花、马缨丹、银合欢及草莓番石榴的生境适宜性模型；2）利用Schoener's D指数计算模型序列间的重叠度。 ### 数据表（biasclasses文件夹） #### 文件：area_disturb_iv.txt 描述：该文件为逗号分隔格式，包含……