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The Changbai Mountains and the Appalachian Mountains have similar spatial contexts. The elevation, latitude, and moisture gradients of both mountain ranges offer regional insight for investigating the vegetation dynamics in eastern Eurasia and eastern North America. We determined and compared the spatial patterns and temporal trends in the normalized difference vegetation index (NDVI) in the Changbai Mountains and the Appalachian Mountains using time series data from the Global Inventory Modeling and Mapping Studies 3rd generation dataset from 1982 to 2013. The spatial pattern of NDVI in the Changbai Mountains exhibited fragmentation, whereas NDVI in the Appalachian Mountains decreased from south to north. The vegetation dynamics in the Changbai Mountains had an insignificant trend at the regional scale, whereas the dynamics in the Appalachian Mountains had a significant increasing trend. NDVI increased in 55% of the area of the Changbai Mountains and in 95% of the area of the Appalachian Mountains. The peak NDVI occurred one month later in the Changbai Mountains than in the Appalachian Mountains. The results revealed a significant increase in NDVI in autumn in both mountain ranges. The climatic trend in the Changbai Mountains included warming and decreased precipitation, and whereas that in the Appalachian Mountains included significant warming and increased precipitation. Positive and negative correlations existed between NDVI and temperature and precipitation, respectively, in both mountain ranges. Particularly, the spring temperature and NDVI exhibited a significant positive correlation in both mountain ranges. The results of this study suggest that human actives caused the differences in the spatial patterns of NDVI and that various characteristics of climate change and intensity of human actives dominated the differences in the NDVI trends between the Changbai Mountains and the Appalachian Mountains. Additionally, the vegetation dynamics of both mountain ranges were not identical to those in previous broader-scale studies. [ABSTRACT FROM AUTHOR]

Monitoring forest disturbances is important for understanding changes in ecosystems. The 1986 Typhoon Vera was a serious disturbance that severely impacted the forest ecosystems of Changbai Mountain National Nature Reserve. Although the typhoon disturbance occurred more than two decades ago, the effects of the typhoon still remain within the study area. Few studies have focused on mapping and assessing disturbances across broad spatial and temporal scales. For this study, we first generated a map of forest composition prior to the typhoon disturbance, which served as a baseline data for the extraction of disturbed area. Then, the Disturbance Index (DI) method was tested for mapping the extent and magnitude of disturbance in the study area by applying a Tasseled Cap transformation to the Landsat imagery. The Landsat-based DI method estimated that an area of 13,764.78 ha of forest was disturbed by the typhoon. Based on visual assessments, these results correspond closely with the reference map derived from ground surveys. These results also revealed the influence of local topographic features on the distribution of windthrow areas. Windthrow areas were more pronounced in areas with elevations ranging from 1,000 to 2,000 m, slopes of less than 10 degrees, and southwestern to northwestern aspects. In addition, the relatively long (25 years) post-typhoon recovery period assessed by this study provided a more comprehensive analysis of the dynamics of forest recovery processes over time. Windthrow areas did not recover immediately after the typhoon, likely due to forest management practices enacted at the time. So far, forest recovery has proceeded more rapidly at elevations below 1,400 m, particularly on western slopes within the study area. Finally, a time series of DI values within the study period suggests a secondary disturbance may have occurred between 2000 and 2001. [ABSTRACT FROM AUTHOR]

The control mechanisms of topography on alpine treeline pattern are critical to understanding treeline dynamics and future changes. These mechanisms have not been understood quite well enough because of increasing human disturbance and low data resolution. In this study, the relationship between the treeline pattern and topography was analyzed based on high spatial resolution remote sensing data and a digital elevation model in an area in Changbai Mountain with little human disturbance. Future treeline patterns were also predicted. The results showed that (a) aspects with high solar radiation and low snow cover have a high coverage rate of trees, (b) the peak coverage rate of trees switches from low slopes (<5°) to medium slopes (5°∼25°) as the elevation rises because of the extreme environment, (c) the coverage rate of trees is a function that depends on environmental factors controlled by topography, (d) the future treeline pattern is controlled by new temperature mechanisms, new environmental factors and the reallocation effect of topography. Our research implies that topography controls the treeline pattern and changes in the treeline pattern associated with global warming, due to the effect of global warming on environmental factors. This study may well explain the causes of heterogeneous changes in the treeline pattern in the horizontal direction as well as differences in treeline response to climate warming. [ABSTRACT FROM AUTHOR]