Modeling Long-term Forest Carbon Spatiotemporal Dynamics With Historical Climate and Recent Remote S

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Forests have long life cycles of up to several hundred years and longer.They also have very different growth rates at different stages of their life cycles.Therefore the carbon cycle in forest ecosystems has long time scales,making it necessary to consider forest age in estimating the spatiotemporal dynamics of carbon sinks in forests.The focus of this article is to review methods for combining recent remote sensing data with historical climate data for estimating the forest carbon source and sink distribution.Satellite remote sensing provides useful data for the land surface in recent decades. The information derived from remote sensing data can be used for short-term forest growth estimation and for mapping forest stand age for longterm simulations.For short-term forest growth estimation, remote sensing can provide forest structural parameters as inputs to process-based models,including big-leaf,two-leaf,and multi-layered models. These models use different strategies to upscale from leaf to canopy,and their reliability and suitability for remote sensing applications will be examined here.For long-term forest carbon cycle estimation, the spatial distribution of the forest growth rate(net primary productivity,NPP) modeled using remote sensing data in recent years is a critical input.This input can be combined with a forest age map to simulate the historical variation of NPP under the influence of climate and atmospheric changes. Another important component of the forest carbon cycle is heterotrophic respiration in the soil,which depends on the sizes of soil carbon pools as well as climate conditions.Methods for estimating the soil carbon spatial distribution and its separation into pools are described.The emphasis is placed on how to derive the soil carbon pools from NPP estimation in current years with consideration of forest carbon dynamics associated with stand age variation and climate and atmospheric changes.The role of disturbance in the forest carbon cycle and the effects of forest regrowth after disturbance are also considered in this review.An example of national forest carbon budget estimation in Canada is given at the end.It illustrates the importance of forest stand age structure in estimating the national forest carbon budgets and the effects of climate and atmospheric changes on the forest carbon cycle.“,”Forests have long life cycles of up to several hundred years and longer.They also have very different growth rates at different stages of their life cycles.Therefore the carbon cycle in forest ecosystems has long time scales,making it necessary to consider forest age in estimating the spatiotemporal dynamics of carbon sinks in forests.The focus of this article is to review methods for combining recent remote sensing data with historical climate data for estimating the forest carbon source and sink distribution.Satellite remote sensing provides useful data for the land surface in recent decades. The information derived from remote sensing data can be used for short-term forest growth estimation and for mapping forest stand age for longterm simulations.For short-term forest growth estimation, remote sensing can provide forest structural parameters as inputs to process-based models,including big-leaf,two-leaf,and multi-layered models. These models use different strategies to upscale from leaf to canopy,and their reliability and suitability for remote sensing applications will be examined here.For long-term forest carbon cycle estimation, the spatial distribution of the forest growth rate(net primary productivity,NPP) modeled using remote sensing data in recent years is a critical input.This input can be combined with a forest age map to simulate the historical variation of NPP under the influence of climate and atmospheric changes. Another important component of the forest carbon cycle is heterotrophic respiration in the soil,which depends on the sizes of soil carbon pools as well as climate conditions.Methods for estimating the soil carbon spatial distribution and its separation into pools are described.The emphasis is placed on how to derive the soil carbon pools from NPP estimation in current years with consideration of forest carbon dynamics associated with stand age variation and climate and atmospheric changes.The role of disturbance in the forest carbon cycle and the effects of forest regrowth after disturbance are also considered in this review.An example of national forest carbon budget estimation in Canada is given at the end.It illustrates the importance of forest stand age structure in estimating the national forest carbon budgets and the effects of climate and atmospheric changes on the forest carbon cycle.
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