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Climate change poses a disproportionate risk to alpine ecosystems. Effective monitoring of forest phenological responses to climate change is critical for predicting and managing threats to alpine populations. Remote sensing can be used to monitor forest communities in dynamic landscapes for responses to climate change at the species level. Spatiotemporal fusion technology using remote sensing images is an effective way of detecting gradual phenological changes over time and seasonal responses to climate change. The spatial and temporal adaptive reflectance fusion model (STARFM) is a widely used data fusion algorithm for Landsat and MODIS imagery. This study aims to identify forest phenological characteristics and changes at the species–community level by fusing spatiotemporal data from Landsat and MODIS imagery. We fused 18 images from March to November for 2000, 2010, and 2019. (The resulting STARFM-fused images exhibited accuracies of RMSE = 0.0402 and R2 = 0.795. We found that the normalized difference vegetation index (NDVI) value increased with time, which suggests that increasing temperature due to climate change has affected the start of the growth season in the study region. From this study, we found that increasing temperature affects the phenology of these regions, and forest management strategies like monitoring phenology using remote sensing technique should evaluate the effects of climate change. [ABSTRACT FROM AUTHOR]

Forests play an important role in regulating the carbon (C) cycle. The main objective of this study was to quantify the effects of South Korean national reforestation programs on carbon budgets. We estimated the changes in C stocks and annual C sequestration in the years 1961–2014 using Korea-specific models, a forest cover map (FCM), national forest inventory (NFI) data, and climate data. Furthermore, we examined the differences in C budgets between Cool forests (forests at elevations above 700 m) and forests in lower-altitude areas. Simulations including the effects of climate conditions on forest dynamics showed that the C stocks of the total forest area increased from 6.65 Tg C in 1961 to 476.21 Tg C in 2014. The model developed here showed a high degree of spatiotemporal reliability. The mean C stocks of the Cool forests and other forests increased from 4.03 and 0.43 Mg C ha−1, respectively, to 102.43 and 73.76 Mg C ha−1 at a rate of 1.82 and 1.36 Mg C ha−1 yr−1 during the same period. These results imply that, although the total Cool forest area of South Korea occupied only about 12.3% (772,788 ha) of the total forest area, the Cool forests play important roles in C balances and forest ecosystems in South Korea. Annual C sequestration totals are projected to decrease at a low rate in the near future because the overall growth rate of a mature forest decreases as the stand ages. Our results quantified forest C dynamics in South Korean forests before and after national reforestation programs. Furthermore, our results can help in development of regional and national forest management strategies to allow for sustainable development of society and to cope with climate change in South Korea. [ABSTRACT FROM AUTHOR]

There is a growing awareness of the need to integrate climate and biodiversity policies. As forests play an important role in mitigating biodiversity loss and climate change, numerous countries have established goals and are managing their forests to achieve them. However, forest management measures and land prioritization may differ depending on the target chosen, leading to conflicts. This research aims to seek optimized national afforestation plans in the Republic of Korea by assessing trade-offs between plant biodiversity persistence and carbon stocks. To this end, afforestation scenarios were spatially established based on the national forest management plans, with a target of 5800 ha expansion by 2022. Generalized Dissimilarity Modeling (GDM) and Global Forest Model (G4M) were applied to the selected afforestable regions to obtain scenarios that maximize biodiversity and carbon, respectively. Furthermore, another afforestation scenario that considers both objectives equally, was proposed using spatial simulated annealing (SSA) optimization algorithm to mitigate trade-offs. The constructed scenarios were compared, both spatially and quantitatively. As a result, the maximization scenarios were found to have few overlapping areas, with both scenarios resulting in ~50% trade-offs. These findings reveal that there is no universal solution and different management strategies are needed to enhance biodiversity persistence and carbon stocks. Thus, to strike a balance among the various goals, forest management requires a compromise solution to minimize trade-offs. Our national-scale assessment can help to guide future planning of national forest management with the consideration of the joint goals of biodiversity and carbon enhancement. [ABSTRACT FROM AUTHOR]