Evaluation of soil organic matter models using existing long-term datasets Libro electrónico
Soil organic matter (SOM) represents a major pool of carbon within the biosphere, roughly twice than in atmospheric CO2. SOM models embody our best understanding of soil carbon dynamics and are needed to predict how global environmental change will influence soil carbon stocks. These models are also required for evaluating the likely effectiveness of different mitigation options. The first important step towards systematically evaluating the suitability of SOM models for these purposes is to test their simulations against real data. Since changes in SOM occur slowly, long-term datasets are required. This volume brings together leading SOM model developers and experimentalists to test SOM models using long-term datasets from diverse ecosystems, land uses and climatic zones within the temperate region.
Main Authors: | , , |
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Format: | Texto biblioteca |
Language: | eng |
Published: |
New York, New York, United States Springer
c199
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Subjects: | Humus, |
Online Access: | http://link.springer.com/openurl?genre=book&isbn=978-3-642-64692-8 |
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Summary: | Soil organic matter (SOM) represents a major pool of carbon within the biosphere, roughly twice than in atmospheric CO2. SOM models embody our best understanding of soil carbon dynamics and are needed to predict how global environmental change will influence soil carbon stocks. These models are also required for evaluating the likely effectiveness of different mitigation options. The first important step towards systematically evaluating the suitability of SOM models for these purposes is to test their simulations against real data. Since changes in SOM occur slowly, long-term datasets are required. This volume brings together leading SOM model developers and experimentalists to test SOM models using long-term datasets from diverse ecosystems, land uses and climatic zones within the temperate region. |
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