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首页> 外文期刊>Environmental and experimental botany >Predicting germination in semi-arid wildland seedbeds II. Field validation of wet thermal-time models
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Predicting germination in semi-arid wildland seedbeds II. Field validation of wet thermal-time models

机译:预测半干旱荒地苗床的萌发状态II。湿热时间模型的现场验证

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Accurate prediction of germination for species used for semi-arid land revegetation would support selection of plant materials for specific climatic conditions and sites. Wet thermal-time models predict germination time by summing progress toward germination subpopulation percentages as a function of temperature across intermittent wet periods or within singular wet periods. Wet periods may be defined by any reasonable seedbed water potential above which seeds are expected to imbibe sufficiently to germinate. These models may be especially applicable to the Artemisia steppe of the western U.S.A. where water availability limits germination in summer and early fall while cool temperatures limit germination in late fall, winter, and spring when soil water is available. To test accuracy of wet thermal-time models we placed seedbags with seeds of five species commonly used in wildland revegetation, as well as two collections of the invasive annual grass, Bromus tectorum L. into Artemisia tridentata Nutt. ssp. wyomin-gensis Beetle and Young zone seedbeds for 19 field incubation periods over four seasons. Hourly surface (1-3 cm) soil temperatures and soil water potentials were measured near the seedbags. These data were input into thermal-time models which predicted time to germination for each seedbag retrieval date. Binomial data representing agreement (1) or lack of agreement (0) of predicted and actual germination for each retrieval date were analyzed using logistic regression. Thermal summation method, season, water potential threshold, and species most affected accuracy of predictions (P<0.0002). A model which defined a wet period as >=-1.5 MPa soil water potential and summed progress toward germination across intermittent wet periods was most accurate in predicting actual germination by a retrieval date. Across all species, this model correctly predicted that germination would occur in seedbags 75-95% of the time over the latewinter to mid-spring seasons, but only 50-71% of the time for the fall-early winter season when time of soil water availability was least. Although the wet thermal-time model overestimated time to germination for some species and seasons, its accuracy should be high enough to evaluate germination potential by mid-spring for different species, sites, and climatic conditions. (C) 2011 Elsevier By. All rights reserved.
机译:对用于半干旱土地植被的物种的发芽的准确预测将支持针对特定气候条件和场所选择植物材料。湿热时间模型通过将间歇性湿润时期或奇异湿润时期内发芽亚群百分比的进展与温度的函数相加来预测发芽时间。湿期可以由任何合理的苗床水势来定义,在该水势以上,种子有望充分吸收以发芽。这些模型可能特别适用于美国西部的艾米干草原,那里的水可利用量限制了夏季和秋天初的发芽,而凉爽的温度限制了土壤中可用的秋末,冬季和春季的发芽。为了测试湿热时间模型的准确性,我们将装有常用于野外植被恢复的五种种子的种子袋以及两个侵入性一年生禾草(Bromus tectorum L.)的种子放入三叶蒿中。 ssp。怀俄明州的甲虫和年轻地带的苗床在四个季节中进行了19个田间孵化期。在种子袋附近测量每小时表面(1-3厘米)的土壤温度和土壤水势。这些数据被输入到热时间模型中,该模型预测每个种子袋取回日期的发芽时间。使用logistic回归分析表示每个检索日期的预测发芽率与实际发芽率的一致性(1)或不一致(0)的二项式数据。热力求和方法,季节,水势阈值和物种对预测准确性的影响最大(P <0.0002)。将湿期定义为> =-1.5 MPa的土壤水势并汇总间歇性湿期的发芽进度的模型,最准确地预测了到检索日期的实际发芽量。在所有物种中,该模型均正确地预测,从冬至春末,种子袋中发芽的发生时间为75-95%,但在秋初的土壤时间中发芽的发生时间仅为发芽的50-71%可用水最少。尽管湿热时间模型高估了某些物种和季节的发芽时间,但其准确性应足够高,以评估到春季中期针对不同物种,地点和气候条件的发芽潜力。 (C)2011 Elsevier By。版权所有。

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