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使用线性混合模型探索农田边缘磷素流失的管理与环境效应

Exploring management and environment effects on edge-of-field phosphorus losses with linear mixed models.

作者信息

Kruger Kelsey M, Thompson Anita M, Li Qiang, Radatz Amber M, Cooley Eric T, Stuntebeck Todd D, Winslow Christopher J, Oldfield Emily E, Ruark Matthew D

机构信息

Department of Soil Science, University of Wisconsin-Madison, Madison, Wisconsin, USA.

Department of Biological Systems Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA.

出版信息

J Environ Qual. 2025 Mar-Apr;54(2):450-464. doi: 10.1002/jeq2.20662. Epub 2025 Jan 7.

Abstract

Evaluating how weather, farm management, and soil conditions impact phosphorus (P) loss from agricultural sites is essential for improving our waterways in agricultural watersheds. In this study, rainfall characteristics, manure application timing, tillage, surface condition, and soil test phosphorus (STP) were analyzed to determine their effects on total phosphorus (TP) and dissolved phosphorus (DP) loss using 125 site-years of runoff data collected by the University of Wisconsin Discovery Farms and Discovery Farms Minnesota. Three linear mixed models (LMMs) were then used to evaluate the influence of those factors on TP and DP losses: (1) a model that included all runoff events, (2) manured sites only, and (3) precipitation events only. Results show that the timing of manure application relative to the timing of a runoff event only had a marginal association with P loads and concentrations, although the majority of the runoff events were collected after 10 days of manure application. Tillage was as influential factor, with greater DP loads and concentrations associated with no-till, especially during frozen conditions. Fields in this study had high STP values, but the model results only showed positive associations between DP load and DP flow-weighted mean concentration (FWMC) loss at the 0- to 15-cm depth. The precipitation event LMM (which included precipitation characteristics) was the model that resulted in the largest R value. While the predictive capacity of the LMMs was low, they did illuminate the relative importance of management and environmental variables on P loss, and can be used to guide future research on P loss in this region.

摘要

评估天气、农场管理和土壤条件如何影响农业用地的磷(P)流失,对于改善农业流域的水道至关重要。在本研究中,利用威斯康星大学探索农场和明尼苏达探索农场收集的125个站点年的径流数据,分析了降雨特征、粪肥施用时间、耕作方式、地表状况和土壤测试磷(STP),以确定它们对总磷(TP)和溶解磷(DP)流失的影响。然后使用三个线性混合模型(LMM)来评估这些因素对TP和DP流失的影响:(1)一个包含所有径流事件的模型,(2)仅包含施粪肥站点的模型,以及(3)仅包含降水事件的模型。结果表明,尽管大多数径流事件是在施用粪肥10天后收集的,但相对于径流事件的时间,粪肥施用时间与P负荷和浓度仅存在微弱关联。耕作是一个有影响的因素,免耕条件下DP负荷和浓度更高,尤其是在冰冻条件下。本研究中的田地STP值较高,但模型结果仅显示在0至15厘米深度处DP负荷与DP流量加权平均浓度(FWMC)流失之间存在正相关。包含降水特征的降水事件LMM是R值最大的模型。虽然LMM的预测能力较低,但它们确实阐明了管理和环境变量对P流失的相对重要性,可用于指导该地区未来关于P流失的研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bcfc/11893287/db6db6db76ef/JEQ2-54-450-g003.jpg

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