Latent trajectory models for spatio-temporal dynamics in Alaskan ecosystems.

The Alaskan landscape has undergone substantial changes in recent decades, most notably the expansion of shrubs and trees across the Arctic. We developed a Bayesian hierarchical model to quantify the impact of climate change on the structural transformation of ecosystems using remotely sensed imagery. We used latent trajectory processes 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 arrangements in our study system. We also developed a Pólya-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.

Multivariate Bayesian clustering using covariate-informed components with application to boreal vegetation sensitivity.

Climate change is impacting both the distribution and abundance of vegetation, especially in far northern latitudes. The effects of climate change are different for every plant assemblage and vary heterogeneously in both space and time. Small changes in climate could result in large vegetation responses in sensitive assemblages but weak responses in robust assemblages. But, patterns and mechanisms of sensitivity and robustness are not yet well understood, largely due to a lack of long-term measurements of climate and vegetation. Fortunately, observations are sometimes available across a broad spatial extent. We develop a novel statistical model for a multivariate response based on unknown cluster-specific effects and covariances, where cluster labels correspond to sensitivity and robustness. Our approach utilizes a prototype model for cluster membership that offers flexibility while enforcing smoothness in cluster probabilities across sites with similar characteristics. We demonstrate our approach with an application to vegetation abundance in Alaska, USA, in which we leverage the broad spatial extent of the study area as a proxy for unrecorded historical observations. In the context of the application, our approach yields interpretable site-level cluster labels associated with assemblage-level sensitivity and robustness without requiring strong a priori assumptions about the drivers of climate sensitivity.

Variability in the expansion of trees and shrubs in boreal Alaska.

The expansion of shrubs and trees across high-latitude ecosystems is one of the most dramatic ecological manifestations of climate change. Most of the work quantifying these changes has been done in small areas and over relatively recent time scales. These land-cover transitions are highly spatially variable, and we have limited understanding of the factors underlying this variation. We use repeat photography to generate a data set of land-cover changes in Denali National Park and Preserve, Alaska, stretching back a century and spanning a range of edaphic, topographic, and climatic conditions. Most land-cover classes were quite stable, with low probabilities of transitioning to other land-cover types. The advance of woody vegetation into low-stature tundra, and the spread of conifer trees into shrub-dominated areas, were both more likely at low elevations and in areas without permafrost. Permafrost also reduced the likelihood of herbaceous vegetation transitioning to woody cover. Exceptions to the general trend of relative stability included nearly all (96%) of the broadleaf forest-dominated areas being invaded by conifers, an expected successional trajectory, and many open gravel river bars (17.8%) transitioning to thick shrubs. These floodplain areas were distinctly not at equilibrium, as only 0.1% of shrub-dominated areas converted to gravel. Warming temperatures in coming decades and concomitant declines in the extent of permafrost are predicted to enhance the spread of woody vegetation in Denali further, but only by ~3%. Land-cover transitions, notably the rapid advance of trees and shrubs observed in other studies, could be less likely and more spatially heterogeneous here than in other high-latitude systems.