Evaluation of digital soil mapping projection in soil organic carbon change modeling
文献类型：期刊论文
| 作者 | Zhang, Tao1,3; Huang, Lai-Ming2,4; Yang, Ren-Min3 |
| 刊名 | ECOLOGICAL INFORMATICS
 |
| 出版日期 | 2024-03-01 |
| 卷号 | 79页码:12 |
| 关键词 | Soil carbon change Digital soil mapping Model projections Environmental change Temporal transferability |
| ISSN号 | 1574-9541 |
| DOI | 10.1016/j.ecoinf.2023.102394 |
| 通讯作者 | Yang, Ren-Min(yangrm@tju.edu.cn) |
| 英文摘要 | There is increasing interest in the application of digital soil mapping (DSM) projections to infer changes in soil carbon across both space and time. This approach relies on the assumption that the spatially modeled soil carbonenvironment relationship can be transferred over time. However, this assumption is rarely tested due to a lack of temporally independent validation data. This paper assesses this assumption by developing models of topsoil organic carbon stocks (SOCS) with a deep learning algorithm and data covering mainland China pertaining to the 1980s and 2010s. The temporal prediction performance of models capturing a specific period was assessed by evaluating their performance in the prediction of data during another period. The results revealed that the prediction accuracy of temporal modeling decreased, as indicated by the coefficient of determination, and was lower than that of spatial modeling. The lower prediction accuracy obtained with the DSM-projection approach may result from differences in the magnitudes of influential variables across periods. We found that different levels of environmental similarity and model projection sensitivity to dynamic variables may cause discrepancies in forecast and hindcast accuracy. Our results demonstrate that the prediction error in temporal modeling is related to the degree of environmental similarity between periods. Our findings generally support the implementation of the DSM-projection approach in soil carbon change modeling. However, caution should be exercised, as there exists much uncertainty regarding the projection of spatial models over time. |
| WOS关键词 | LAND-USE CHANGE ; PROPENSITY SCORE ; STOCKS ; CLIMATE ; SEQUESTRATION ; PREDICTION ; MAP |
| 资助项目 | National Natural Science Founda-tion of China[42171054] ; National Natural Science Founda-tion of China[42377302] |
| WOS研究方向 | Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:001132273100001 |
| 出版者 | ELSEVIER |
| 资助机构 | National Natural Science Founda-tion of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/201338]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Yang, Ren-Min |
| 作者单位 | 1.East China Univ Technol, Sch Surveying & Geoinformat Engn, Nanchang 330013, Peoples R China 2.Univ Chinese Acad Sci, Coll Resource & Environm, Beijing 100049, Peoples R China 3.Tianjin Univ, Sch Earth Syst Sci, Tianjin 300072, Peoples R China 4.Chinese Acad Sci, Key Lab Ecosyst Network Observat & Modeling, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Tao,Huang, Lai-Ming,Yang, Ren-Min. Evaluation of digital soil mapping projection in soil organic carbon change modeling[J]. ECOLOGICAL INFORMATICS,2024,79:12. |
| APA | Zhang, Tao,Huang, Lai-Ming,&Yang, Ren-Min.(2024).Evaluation of digital soil mapping projection in soil organic carbon change modeling.ECOLOGICAL INFORMATICS,79,12. |
| MLA | Zhang, Tao,et al."Evaluation of digital soil mapping projection in soil organic carbon change modeling".ECOLOGICAL INFORMATICS 79(2024):12. |
入库方式： OAI收割
来源：地理科学与资源研究所
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