气候变化领域集成服务门户(CCPortal): Data-centric species distribution modeling: Impacts of modeler decisions in a case study of invasive European frog-bit

CCPortal

DOI	10.1002/aps3.11573
	Data-centric species distribution modeling: Impacts of modeler decisions in a case study of invasive European frog-bit
	Hansen, Sara E.; Monfils, Michael J.; Hackett, Rachel A.; Goebel, Ryan T.; Monfils, Anna K.
发表日期	2024
ISSN	2168-0450
英文摘要	PremiseSpecies distribution models (SDMs) are widely utilized to guide conservation decisions. The complexity of available data and SDM methodologies necessitates considerations of how data are chosen and processed for modeling to enhance model accuracy and support biological interpretations and ecological applications.MethodsWe built SDMs for the invasive aquatic plant European frog-bit using aggregated and field data that span multiple scales, data sources, and data types. We tested how model results were affected by five modeler decision points: the exclusion of (1) missing and (2) correlated data and the (3) scale (large-scale aggregated data or systematic field data), (4) source (specimens or observations), and (5) type (presence-background or presence-absence) of occurrence data.ResultsDecisions about the exclusion of missing and correlated data, as well as the scale and type of occurrence data, significantly affected metrics of model performance. The source and type of occurrence data led to differences in the importance of specific explanatory variables as drivers of species distribution and predicted probability of suitable habitat.DiscussionOur findings relative to European frog-bit illustrate how specific data selection and processing decisions can influence the outcomes and interpretation of SDMs. Data-centric protocols that incorporate data exploration into model building can help ensure models are reproducible and can be accurately interpreted in light of biological questions.
英文关键词	aquatic invasive plants; data-centric; Hydrocharis morsus-ranae; machine learning; natural history collections; open data; reproducible research; species distribution model
语种	英语
WOS研究方向	Plant Sciences
WOS类目	Plant Sciences
WOS记录号	WOS:001182162600001
来源期刊	APPLICATIONS IN PLANT SCIENCES
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/297830
作者单位	Central Michigan University; Michigan State University; Central Michigan University
推荐引用方式 GB/T 7714	Hansen, Sara E.,Monfils, Michael J.,Hackett, Rachel A.,et al. Data-centric species distribution modeling: Impacts of modeler decisions in a case study of invasive European frog-bit[J],2024.
APA	Hansen, Sara E.,Monfils, Michael J.,Hackett, Rachel A.,Goebel, Ryan T.,&Monfils, Anna K..(2024).Data-centric species distribution modeling: Impacts of modeler decisions in a case study of invasive European frog-bit.APPLICATIONS IN PLANT SCIENCES.
MLA	Hansen, Sara E.,et al."Data-centric species distribution modeling: Impacts of modeler decisions in a case study of invasive European frog-bit".APPLICATIONS IN PLANT SCIENCES (2024).