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| DOI | 10.1007/s13253-024-00616-y |
| Regularized Latent Trajectory Models for Spatio-temporal Population Dynamics | |
| 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
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| 文献类型 | 期刊论文 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/307421 |
| 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 | . Regularized Latent Trajectory Models for Spatio-temporal Population Dynamics[J],2024. |
| APA | (2024).Regularized Latent Trajectory Models for Spatio-temporal Population Dynamics.JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS. |
| MLA | "Regularized Latent Trajectory Models for Spatio-temporal Population Dynamics".JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS (2024). |
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