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Rotation and the temporal stability of landscape defined management zones: a time series analysis

机译:旋转和景观定义管理区的时间稳定性:时间序列分析

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Yield and landscape position are used to delineate management zones, but this approach is confounded by yield's weather dependence, causing yield to evidence temporal variability/lack of yield stability. Management options also influence yield stability, and among these, crop rotation is important. Our objective was to describe the influence of crop rotation on the temporal yield stability of landscape defined management zones. Corn (Zea mays L.) yield data for two rotations, monoculture corn (C-C) and corn alternating yearly (W/S-C) with winter wheat (Triticum aestivum L.)/double-crop soybean (Glycine max L. Merr.), taken in four landscape (shoulder, upper backslope, lower backslope, footslope) management zones, were obtained from a 21-year rotation study established near Lexington, Kentucky. Yields were evaluated for spatial and temporal stability by ANOVA, Spearman rank correlation, and time series analysis, using Box-Jenkins methodology. The 21-year average yields were lower for C-C (8.3?.6 Mg/ha) than for W/S-C (9.6?.7 Mg/ ha). A plot of yield versus time for individual landscape zones exhibited slightly positive linear trend (0.13 Mg/ha/yr) for both rotations. The rank correlations among landscape positions, for each rotation, were generally high (above 0.80), and rotation choice determined which positions were most, and least, similar. After removing linear yield trend, Box-Jenkins time series analysis found that C-C yield exhibited greater temporal lag (less yield stability) than W/S-Cyield, though this trend was not equally true across the four zones. The lag predicting C-C yield was greatest (5 years) in the upper backslope, while upper backslope and footslope W/S-C yields exhibited maximal autocorrelation at lags of one to three years in length. These 21-year time series models indicate that similar management zones would require a minimum of three prior years of yield data in order to forecast their yield response behavior.
机译:产量和景观地位用于描绘管理区,但这种方法被收益率的天气依赖混淆,导致效率达到证据时间变异性/缺乏产量稳定性。管理选择也影响产量稳定性,其中,作物旋转很重要。我们的目标是描述作物旋转对景观定义管理区时态产量稳定性的影响。玉米(Zea mays L.)冬小麦(Triticum aestivum L.)/双作物大豆(Glycine Max L. Merr)的两次旋转,单殖民玉米(CC)和玉米交替(w / sc)的单殖民玉米(cc)和玉米交替的数据拍摄于四个景观(肩膀,上篮,较低的斜坡,鞋子)管理区,从肯塔基州雷克林顿附近建立的21年旋转研究获得。使用Box-Jenkins方法,评估Anova,Spearman等级相关性和时间序列分析的空间和时间稳定性的产量。对于C-C(8.3?.6mg / ha)的21年平均产率低于w / s-c(9.6?.7mg / ha)。对于各个景观区的产量与时间的曲线图表现出略微正线性趋势(0.13mg / ha / yr),用于两个旋转。每个旋转的景观位置之间的等级相关性通常高(0以上0.80),并且确定哪个位置最多,最不相似。去除线性产量趋势后,Box-Jenkins时间序列分析发现,C-C产量比W / S-COIDE表现出更大的时间滞后(较少的收益率稳定性),尽管这种趋势在四个区域上并不同样真实。预测C-C产量的滞后是最大的(5年)在上后隙中,上后壁和鞋面的产量为1至3年的滞后表现出最大自相关。这21年的时间序列模型表明,类似的管理区域需要至少三年的产量数据,以预测其产量响应行为。

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