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Climate change has modified the structure and functions of ecosystems, affecting human well-being. Evergreen plants in the warm-temperate ecosystems will lose climatically suitable habitats under climate change but have not drawn much scholarly interest. Therefore, the present research aimed to predict the future climatic niches of eight coastal warm-adapted evergreen trees under climate change to provide information for an effective management practice. For this purpose, we used the ensemble species distribution models (SDMs) weighted by the TSS value in modelling the climatic niches of those evergreen trees and then ensembled their future distributions predicted under 20 future climate scenarios. Except for Neolitsea sericea (True Skill Statistic (TSS) = 0.79), all projections for the current climatic niches of evergreens showed excellent predictive powers (TSS > 0.85). The results showed that the climatic niches of the four evergreens--Castanopsis cuspidata, Pittosporum tobira, Raphiolepis indica var. umbellate, and Eurya emarginata--would expand to the northern part of the Korean Peninsula (KP) under climate change, but the ones of the remaining four--Kadsura japonica, Neolitsea sericea, Ilex integra, and Dendropanax morbiferus--would shrink. While the climatic niches of Pittosporum tobira showed the rapidest and greatest expansion under climate change, Dendropanax morbiferus was predicted to experience the greatest loss of habitat. On the other hand, regardless of whether the future distributions of climatically suitable habitats would expand or contract, the highly suitable habitats of all species were predicted to decline under climate change. This may indicate that further climate change will degrade habitat suitability for all species within the distribution boundary and restrict continuous habitat expansions of expanding species or accelerate habitat loss of shrinking species. In addition, the future distributions of most coastal evergreens were found to be confined to coastal areas; therefore, sea-level rise would accelerate their habitat loss under climate change. The present study provides primary and practical knowledge for understanding climate-related coastal vegetation changes for future conservation planning, particularly on the Korean Peninsula. [ABSTRACT FROM AUTHOR]

Alpine, subalpine and boreal tree species, of low genetic diversity and adapted to low optimal temperatures, are vulnerable to the warming effects of global climate change. The accurate prediction of these species' distributions in response to climate change is critical for effective planning and management. The goal of this research is to predict climate change effects on the distribution of red spruce (Picea rubens Sarg.) in the Great Smoky Mountains National Park (GSMNP), eastern USA. Climate change is, however, conflated with other environmental factors, making its assessment a complex systems problem in which indirect effects are significant in causality. Predictions were made by linking a tree growth simulation model, red spruce growth model (ARIM.SIM), to a GIS spatial model, red spruce habitat model (ARIM.HAB). ARIM.SIM quantifies direct and indirect interactions between red spruce and its growth factors, revealing the latter to be dominant. ARIM.HAB spatially distributes the ARIM.SIM simulations under the assumption that greater growth reflects higher probabilities of presence. ARIM.HAB predicts the future habitat suitability of red spruce based on growth predictions of ARIM.SIM under climate change and three air pollution scenarios: 10% increase, no change and 10% decrease. Results show that suitable habitats shrink most when air pollution increases. Higher temperatures cause losses of most low-elevation habitats. Increased precipitation and air pollution produce acid rain, which causes loss of both low- and high-elevation habitats. The general prediction is that climate change will cause contraction of red spruce habitats at both lower and higher elevations in GSMNP, and the effects will be exacerbated by increased air pollution. These predictions provide valuable information for understanding potential impacts of global climate change on the spatiotemporal distribution of red spruce habitats in GSMNP. [ABSTRACT FROM AUTHOR]