气候变化领域集成服务门户(CCPortal): Regularized Latent Trajectory Models for Spatio-temporal Population Dynamics

CCPortal

DOI	10.1007/s13253-024-00616-y
	Regularized Latent Trajectory Models for Spatio-temporal Population Dynamics
	Lu, Xinyi; Kanno, Yoichiro; Valentine, George P.; Kulp, Matt A.; Hooten, Mevin B.
发表日期	2024
ISSN	1085-7117
EISSN	1537-2693
英文摘要	Climate change impacts ecosystems variably in space and time. Landscape features may confer resistance against environmental stressors, whose intensity and frequency also depend on local weather patterns. Characterizing spatio-temporal variation in population responses to these stressors improves our understanding of what constitutes climate change refugia. We developed a Bayesian hierarchical framework that allowed us to differentiate population responses to seasonal weather patterns depending on their sensitive or resilient states. The framework inferred these sensitivity states based on latent trajectories delineating dynamic state probabilities. The latent trajectories are composed of linear initial conditions, functional regression models, and additive random effects representing ecological mechanisms such as topological buffering and effects of legacy weather conditions. Further, we developed a Bayesian regularization strategy that promoted temporal coherence in the inferred states. We demonstrated our hierarchical framework and regularization strategy using simulated examples and a case study of native brook trout (Salvelinus fontinalis) count data from the Great Smoky Mountains National Park, southeastern USA. Our study provided insights into ecological processes influencing brook trout sensitivity. Our framework can also be applied to other species and ecosystems to facilitate management and conservation.
英文关键词	Bayesian hierarchical model; State-space model; Functional analysis; Climate change refugia; Brook charr
语种	英语
WOS研究方向	Life Sciences & Biomedicine - Other Topics ; Mathematical & Computational Biology ; Mathematics
WOS类目	Biology ; Mathematical & Computational Biology ; Statistics & Probability
WOS记录号	WOS:001194878400001
来源期刊	JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/307422
作者单位	Utah System of Higher Education; Utah State University; Colorado State University; Colorado State University; Colorado State University; United States Department of the Interior; University of Texas System; University of Texas Austin
推荐引用方式 GB/T 7714	Lu, Xinyi,Kanno, Yoichiro,Valentine, George P.,et al. Regularized Latent Trajectory Models for Spatio-temporal Population Dynamics[J],2024.
APA	Lu, Xinyi,Kanno, Yoichiro,Valentine, George P.,Kulp, Matt A.,&Hooten, Mevin B..(2024).Regularized Latent Trajectory Models for Spatio-temporal Population Dynamics.JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS.
MLA	Lu, Xinyi,et al."Regularized Latent Trajectory Models for Spatio-temporal Population Dynamics".JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS (2024).