Can meteorological data and normalized difference vegetation index be used to quantify soil pH in grasslands?
文献类型：期刊论文
| 作者 | Dai, Erfu; Zhang, Guangyu; Fu, Gang; Zha, Xinjie |
| 刊名 | FRONTIERS IN ECOLOGY AND EVOLUTION
 |
| 出版日期 | 2023-07-12 |
| 卷号 | 11页码:1206581 |
| 关键词 | soil quality soil degradation random-forest global change alpine region |
| ISSN号 | 2296-701X |
| DOI | 10.3389/fevo.2023.1206581 |
| 产权排序 | 1 |
| 文献子类 | Article |
| 英文摘要 | Quantifying soil pH at manifold spatio-temporal scales is critical for examining the impacts of global change on soil quality. It is still unclear whether meteorological data and normalized difference vegetation index (NDVI) can be used to quantify soil pH in grasslands. Here, nine methods (i.e., RF: random-forest, GLR: generalized-linear-regression, GBR: generalized-boosted-regression, MLR: multiple-linear-regression, ANN: artificial-neural-network, CIT: conditional-inference-tree, SVM: support-vector-machine, eXGB: eXtreme-gradient-boosting, RRT: recursive-regression-tree) were applied to quantify soil pH. Three independent variables (i.e., AP: annual precipitation, AT: annual temperature, ARad: annual radiation) were used to quantify potential soil pH (pH(p)), and four independent variables (i.e., AP, AT, ARad and NDVImax: maximum NDVI during growing season) were applied to quantify actual soil pH (pH(a)). Overall, the developed eXGB models performed the worst (linear regression slope < 0.60; R-2 = 0.99; relative deviation & LE; -43.54%; RMSE & GE; 3.14), but developed RF models performed the best (linear regression slope: 0.99-1.01; R-2 = 1.00; relative deviation: from -1.26% to 0.65%; RMSE & LE; 0.28). The linear regression slope, R-2, absolute value of relative deviation and RMSE between modelled and measured soil pH were 0.96-1.03, 0.99-1.00, & LE; 3.87% and & LE; 0.88 for the other seven methods, respectively. Accordingly, except the developed eXGB approach, the developed other eight methods can have relative greater accuracies in quantifying soil pH. However, the developed RF had the uppermost quantification accuracy for soil pH. Whether or not meteorological data and normalized difference vegetation index can be used to quantify soil pH was dependent on the chosen models. The RF developed by this study can be used to quantify soil pH from measured meteorological data and NDVImax, and may be conducive to scientific studies related to soil quality and degradation (e.g., soil acidification and salinization) at manifold spatial-temporal under future globe change. |
| WOS关键词 | TIBETAN PLATEAU ; NITROGEN ; PHOSPHORUS ; BACTERIAL ; CHINA |
| WOS研究方向 | Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:001035840800001 |
| 出版者 | FRONTIERS MEDIA SA |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/194553]  |
| 专题 | 拉萨站高原生态系统研究中心_外文论文 |
| 作者单位 | 1.Xi'an University of Finance & Economics 2.Institute of Geographic Sciences & Natural Resources Research, CAS 3.Chinese Academy of Sciences |
| 推荐引用方式 GB/T 7714 | Dai, Erfu,Zhang, Guangyu,Fu, Gang,et al. Can meteorological data and normalized difference vegetation index be used to quantify soil pH in grasslands?[J]. FRONTIERS IN ECOLOGY AND EVOLUTION,2023,11:1206581. |
| APA | Dai, Erfu,Zhang, Guangyu,Fu, Gang,&Zha, Xinjie.(2023).Can meteorological data and normalized difference vegetation index be used to quantify soil pH in grasslands?.FRONTIERS IN ECOLOGY AND EVOLUTION,11,1206581. |
| MLA | Dai, Erfu,et al."Can meteorological data and normalized difference vegetation index be used to quantify soil pH in grasslands?".FRONTIERS IN ECOLOGY AND EVOLUTION 11(2023):1206581. |
入库方式： OAI收割
来源：地理科学与资源研究所
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