![]() ![]() ![]() Windows Repair Toolbox is a lightweight bundle that provides you with an extensive set of tools to help you monitor, clean, enhance, tweak and repair broken processes that make your system sluggish. Our approach, which simulated stand dynamics and dispersal, demonstrated that a northward shift in tree species distributions may take 300 or more years.In case you noticed that your computer has been running slow lately and its performance is consistently decreasing, then perhaps it is time to consider clean it of junk and other obsolete apps that are clogging the resources. Conclusions Climate change had positive effects on forest biomass under the two climate scenarios with greatest warming but the patterns in AGB over time were similar among climate scenarios because succession was the primary driver of AGB dynamics. Climate change effects on tree species distribution were not evident from 2000 to 2100 but by 2300 some northern hardwood and conifer species decreased in occurrence and some central hard-wood and southern tree species increased in occurrence. AGB averaged 10 % greater in the CGCM A2 and GFDL A1FI scenarios than the PCM B1 and current climate scenarios. Results AGB increased from 2000 to 2120 irrespective of climate scenario, followed by slight decline, but then increased again to 2300. ![]() We analyzed the effects of climate change on AGB and tree species distribution. Methods We used the LANDIS PRO forest landscape model to simulate forest succession and tree harvest under current climate and three climate change scenarios from 2000 to 2300. Objective We addressed how aboveground biomass (AGB) and tree species distribution changed under multiple climate change scenarios (PCM B1, CGCM A2, and GFDL A1FI) in northeastern forests. Climate change will affect forest distribution and structure and have important implications for biodiversity, carbon dynamics, and human well-being. Context Forests in the northeastern United States are currently in early-and mid-successional stages recovering from historical land use. ![]()
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