Recent years have seen a decline in herbage production and tiller populations in New Zealand's perennial ryegrass (Lolium perenne) dairy pastures. One hypothesis is that modern genotypes are less suited to the warmer, drier weather experienced under changing climate patterns. In this study, a combination of long‐term trial data (2011–2017) and a process‐based pasture model (BASGRA) was used to explore the causes and possible mitigation of the observed production and population loss at three sites (dryland sites in Northland and Waikato and an irrigated site in Canterbury). Bayesian calibration was used to identify the model parameter sets that were consistent with the trial data and to identify differences in plant morphology and responses between sites. The model successfully simulated the observed differences in tiller numbers between the dryland sites, where populations and production declined rapidly after the second year and the irrigated site where populations and production were maintained. Analysis of the model calibrations along with preliminary scenario simulations suggests that increased tiller mortality associated with drought was the main cause of persistence failure at the dryland sites and that decreasing grazing pressure or breeding for tolerance to higher temperatures may not be successful in preventing this.

中文翻译：

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使用基本草原模型（BASGRA）确定多年生黑麦草（Lolium perenne）奶牛场持久性低的原因

近年来，新西兰多年生黑麦草（黑麦草）的牧草产量和分till种群下降）奶牛场。一种假设是，现代基因型不太适合在气候模式变化下经历的更温暖，更干燥的天气。在这项研究中，结合了长期试验数据（2011-2017年）和基于过程的牧场模型（BASGRA），探讨了三个地点（干旱地区的干旱地区）的观测到的生产和人口流失的原因和可能的缓解方法。 Northland和Waikato以及Canterbury的灌溉地）。贝叶斯校准用于识别与试验数据一致的模型参数集，并识别植物形态和位点之间的响应差异。该模型成功模拟了旱地站点之间观察到的分till数差异，在第二年之后人口和产量迅速下降，在灌溉地点维持了人口和产量。对模型校准的分析以及初步的情景模拟表明，与干旱相关的分increased死亡率增加是干旱地区持久性耕种持续失败的主要原因，降低放牧压力或育种耐高温可能无法成功地防止这种情况。