论文标题

阿拉斯加生态系统中时空动力学的潜在轨迹模型

Latent trajectory models for spatio-temporal dynamics in Alaskan ecosystems

论文作者

Lu, Xinyi, Hooten, Mevin B., Raiho, Ann M., Swanson, David K., Roland, Carl A., Stehn, Sarah E.

论文摘要

近几十年来,阿拉斯加的景观发生了重大变化,最著名的是灌木和树木在北极的扩张。我们开发了一个动态统计模型,以使用远程感知的图像来量化气候变化对生态系统结构转化的影响。我们在分层框架中使用潜在轨迹过程来建模每年发展的动态状态概率,从中我们从中得出了生态型之间的过渡概率。我们的潜在轨迹模型在调查间隔中适应时间不规则,并使用时空异质气候驱动因素来推断土地覆盖率的过渡速率。我们表征了我们的研究系统中的情节和子图布置引起的多尺度空间相关性。我们还制定了一种Polya-Gamma采样策略来改善计算。我们的模型促进了生态系统对气候变化的反应的推断,可用于预测各种气候场景下未来的土地覆盖过渡。

The Alaskan landscape has undergone substantial changes in recent decades, most notably the expansion of shrubs and trees across the Arctic. We developed a dynamic statistical model to quantify the impact of climate change on the structural transformation of ecosystems using remotely sensed imagery. We used latent trajectory processes in a hierarchical framework to model dynamic state probabilities that evolve annually, from which we derived transition probabilities between ecotypes. Our latent trajectory model accommodates temporal irregularity in survey intervals and uses spatio-temporally heterogeneous climate drivers to infer rates of land cover transitions. We characterized multi-scale spatial correlation induced by plot and subplot arrangement in our study system. We also developed a Polya-Gamma sampling strategy to improve computation. Our model facilitates inference on the response of ecosystems to shifts in the climate and can be used to predict future land cover transitions under various climate scenarios.

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