The gradients of elevations and latitudes in the Appalachian Mountains provide a unique regional perspective on landscape variations in the eastern United States and southeastern Canada. We reveal patterns and trends of landscape dynamics, land surface phenology, and ecosystem production along the Appalachian Mountains using time series data from Global Inventory Modeling and Mapping Studies and Advanced Very High Resolution Radiometer Global Production Efficiency Model datasets. We analyze the spatial and temporal patterns of the normalized difference vegetation index (NDVI), length of growing season (LOS), and net primary production (NPP) of selected ecoregions along the Appalachian Mountains regions. We compare the results in different spatial contexts, including North America and the Appalachian Trail corridor area. To reveal latitudinal variations, we analyze data and compare the results between the 30°-to-40°N and the 40°-to-50°N latitudes. The result reveal significant decreases in annual peak NDVI in the Appalachian Mountains regions. The trend for the Appalachian Mountains regions was a −0.0018 (R2=0.55, P<0.0001) NDVI unit decrease per year during 25 years from 1982 to 2006. The LOS was prolonged by 0.3 days per year−1 during the 25-year percent. The NPP increased by 2.68 g Cm−2 yr−2 from 1981 to 2000.
Human-induced land-cover and land-use change (LCLUC) has a profound impact on the magnitude and dynamics of spatial and temporal patterns of greenhouse gas emissions and regional climate change in a wetland-dominated Amur River Basin, henceforth referred to as the Three-River-Plain (TRP) region, in Northeast China. The TRP region has the largest natural wetland extent in China. Drainage of wetlands and conversion from wetland into agriculture land use may be one of the primary reasons for the regional climate change. The region's temperature experienced two sudden increases in early 1970s and late 1980s and those changes were coincident with the time frames of large-scale agricultural reclamations. The TRP region warrants a significant regional study to answer questions such as “were human-induced LCLUC significant to affect the magnitude and spatial temporal greenhouse gas emissions and further responsible for regional climate change?” Integration of satellite remotely sensed land surface conditions and in situ measurements of greenhouse gas fluxes provide a reliable information source to study the spatial-temporal patterns of greenhouse gas emissions. Integration of remote sensing detected land-cover change and patterns of greenhouse gas fluxes associated with different land-cover types allows quantification of regional greenhouse gas emission and further studies the driving factors of regional climate change. Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing data are necessary toward this effort.
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