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Spatiotemporal patterns of carbon storage in forest ecosystems in Hunan Province, China

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国家林业和草原科学数据中心2022-10-27 更新2024-03-06 收录
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https://www.forestdata.cn/dataDetail.html?id=CSTR:17575.11.0220221027011.040001.V1
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productivity. A comprehensive scientific evaluation of soil fertility is helpful for sustainable forest management. There are many uncertainties in traditional evaluation methods, that is fuzziness and randomness, which often lead to a large deviation of the evaluation results. In order to comprehensively consider the fuzziness and randomness of soil fertility evaluation, the cloud model was introduced to evaluate the soil fertility of Chinese fir plantations. The cloud model is an uncertain transformation model which can combine a qualitative description with a quantitative calculation as well as reflect the randomness and fuzziness of the principle. It is an effective tool for realizing qualitative and quantitative conversion. The accuracy of the model was evaluated with the Namerow integrated index method, and the results were compared with previous studies. The results showed that the soil fertility was grade II (Ex = 0.653), medium; soil pH was grade II (Ex = 4.59), strongly acidic; soil organic matter (OM) was grade V (Ex = 33.40), rich; total nitrogen (TN) was grade V(Ex = 1.53), rich; total phosphorus (TP) was grade III (Ex = 0.49), poor; total potassium (TK) was grade IV (Ex = 17.10), medium; available nitrogen (AN) was grade V (Ex = 128.30), rich; available phosphorus (AP) was grade II (Ex = 4.10), very poor; and available potassium (AK) was grade III (Ex = 52.73), poor. TThe soil fertility of the Chinese fir plantation was comprehensively evaluated by the cloud model and the evaluation results were unbiased and reliable. This method makes up for the shortcomings of traditional methods and provides new ideas for soil fertility evaluation. We suggest that this cloud model could be extended to other regions in the future and hope that there will be an article to compare several different statistical techniques.
提供机构:
国家林业和草原科学数据中心
创建时间:
2022-10-27
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