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Understory vascular plant species play a key role in natural ecosystems by maintaining nutrient balances and providing both food for wildlife and non-wood forest products. However, some such species are facing potential extirpation due to human interventions such as forest harvesting practices, land use change, and climate change. Despite their ecological and societal importance, the influence of different environmental variables on the distribution of vascular plant communities remains unclear. This study evaluated how several Acadian understory rare plant species (categorized as S1-S2 species) in New Brunswick will respond to future climate scenarios. We used presence-only occurrence records of four S1-S2 rare plant species and eight bioclimatic variables to calibrate climate suitability models using maximum entropy algorithm (MaxEnt). The key bioclimatic predictor variables for the two S1 species (Canada Honewort and Furbish Lousewort) were maximum temperature of the warmest month and precipitation of the driest quarter. The predictor variables with significant contribution for the two S2 plant species were annual precipitation (35%) for Anticosti Aster and precipitation of wettest quarter (85.7%) for Parker's Pipewort. Our models predicted that the two S1 plant species are likely to gain more suitable climate space by 2070, while the two S2 plant species are likely to lose suitable climate space and may face extirpation risk from New Brunswick. The difficulty of projecting rare plant species is very scarce occurrence data, but analyses such as ours can help indicate current locations and in-situ and ex-situ climate change refugia areas for use in biodiversity conservation planning. [ABSTRACT FROM AUTHOR]

Peatlands perform many important ecosystem functions at both the local and global scale, including hydrologic and climatic regulation. Although peatlands often act as climatic microrefugia, they have rarely been the subject of long-term microclimatic studies. In this study, we aimed to compare the local climatic conditions of a mid-forest mire to that of an open area and examine the differences in microclimates within the mire based on plant community diversity, shading, and water table depths. The peatland studied in this work was significantly cooler than the reference site, mainly due to a higher decline in nighttime air temperatures. However, the daily maximum air temperature near the ground was often higher. We also noticed that microclimates significantly differed within the studied peatland. Wet and shaded microsites were cooler than the sites having a lower water level and receiving higher amounts of solar radiation. The results of the study suggest that peatlands have locally cooler climates, and thus can serve as climate change refugia. These findings can help us interpret reconstructed data from the peat archive, and, when combined with experiments, identify tipping points for peatland ecosystems. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]