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利用历史数据库估算美国中西部土壤有机碳的空间分布。

Estimating spatial distribution of soil organic carbon for the Midwestern United States using historical database.

机构信息

Department of Plant Science, South Dakota State University, Brookings, SD 57007, USA.

出版信息

Chemosphere. 2015 May;127:49-57. doi: 10.1016/j.chemosphere.2014.12.027. Epub 2015 Feb 2.

DOI:10.1016/j.chemosphere.2014.12.027
PMID:25655697
Abstract

Soil organic carbon (SOC) is the most important parameter influencing soil health, global climate change, crop productivity, and various ecosystem services. Therefore, estimating SOC at larger scales is important. The present study was conducted to estimate the SOC pool at regional scale using the historical database gathered by the National Soil Survey Staff. Specific objectives of the study were to upscale the SOC density (kg C m(-2)) and total SOC pool (PgC) across the Midwestern United States using the geographically weighted regression kriging (GWRK), and compare the results with those obtained from the geographically weighted regression (GWR) using the data for 3485 georeferenced profiles. Results from this study support the conclusion that the GWRK produced satisfactory predictions with lower root mean square error (5.60 kg m(-2)), mean estimation error (0.01 kg m(-2)) and mean absolute estimation error (4.30 kg m(-2)), and higher R(2) (0.58) and goodness-of-prediction statistic (G=0.59) values. The superiority of this approach is evident through a substantial increase in R(2) (0.45) compared to that for the global regression (R(2)=0.28). Croplands of the region store 16.8 Pg SOC followed by shrubs (5.85 Pg) and forests (4.45 Pg). Total SOC pool for the Midwestern region ranges from 31.5 to 31.6 Pg. This study illustrates that the GWRK approach explicitly addresses the spatial dependency and spatial non-stationarity issues for interpolating SOC density across the regional scale.

摘要

土壤有机碳(SOC)是影响土壤健康、全球气候变化、作物生产力和各种生态系统服务的最重要参数。因此,在更大的尺度上估计 SOC 非常重要。本研究旨在利用国家土壤调查人员收集的历史数据库,估算美国中西部地区的 SOC 储量。该研究的具体目标是使用地理加权回归克里金(GWRK)将 SOC 密度(kg C m(-2))和总 SOC 储量(PgC)从 3485 个地理参考剖面扩展到区域尺度,并将结果与使用该数据获得的地理加权回归(GWR)的结果进行比较。本研究的结果支持以下结论:GWRK 产生了令人满意的预测结果,其均方根误差(5.60 kg m(-2))、平均估计误差(0.01 kg m(-2))和平均绝对估计误差(4.30 kg m(-2))较低,R(2)(0.58)和预测统计量(G=0.59)较高。与全局回归(R(2)=0.28)相比,这种方法的优势在于 R(2)显著增加(0.45)。该地区的耕地储存了 16.8 Pg SOC,其次是灌木(5.85 Pg)和森林(4.45 Pg)。中西部地区的总 SOC 储量范围为 31.5 至 31.6 Pg。本研究表明,GWRK 方法明确解决了在区域尺度上插值 SOC 密度时的空间依赖性和空间非平稳性问题。

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