Every spring, ranchers in the drought‐prone U.S. Great Plains face the same difficult challenge—trying to estimate how much forage will be available for livestock to graze during the upcoming summer grazing season. To reduce this uncertainty in predicting forage availability, we developed an innovative new grassland productivity forecast system, named Grass‐Cast, to provide science‐informed estimates of growing season aboveground net primary production (ANPP). Grass‐Cast uses over 30 yr of historical data including weather and the satellite‐derived normalized vegetation difference index (NDVI)—combined with ecosystem modeling and seasonal precipitation forecasts—to predict if rangelands in individual counties are likely to produce below‐normal, near‐normal, or above‐normal amounts of grass biomass (lbs/ac). Grass‐Cast also provides a view of rangeland productivity in the broader region, to assist in larger‐scale decision‐making—such as where forage resources for grazing might be more plentiful if a rancher’s own region is at risk of drought. Grass‐Cast is updated approximately every two weeks from April through July. Each Grass‐Cast forecast provides three scenarios of ANPP for the upcoming growing season based on different precipitation outlooks. Near real‐time 8‐d NDVI can be used to supplement Grass‐Cast in predicting cumulative growing season NDVI and ANPP starting in mid‐April for the Southern Great Plains and mid‐May to early June for the Central and Northern Great Plains. Here, we present the scientific basis and methods for Grass‐Cast along with the county‐level production forecasts from 2017 and 2018 for ten states in the U.S. Great Plains. The correlation between early growing season forecasts and the end‐of‐growing season ANPP estimate is >50% by late May or early June. In a retrospective evaluation, we compared Grass‐Cast end‐of‐growing season ANPP results to an independent dataset and found that the two agreed 69% of the time over a 20‐yr period. Although some predictive tools exist for forecasting upcoming growing season conditions, none predict actual productivity for the entire Great Plains. The Grass‐Cast system could be adapted to predict grassland ANPP outside of the Great Plains or to predict perennial biofuel grass production.

中文翻译：

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使用Grass-Cast预测美国大平原的季节性草原生产力

每年春天，干旱多发的美国大平原地区的牧场主都面临着同样艰巨的挑战-试图估计在即将到来的夏季放牧季节中有多少草料可供牲畜放牧。为了减少在预测草料供应量方面的不确定性，我们开发了一种创新的新草地生产力预测系统，名为Grass-Cast，以提供科学依据的估计的地面净初级生产（ANPP）生长季。Grass-Cast利用30多年的历史数据（包括天气和卫星归一化植被差异指数（NDVI））结合生态系统建模和季节性降水预测来预测各个县的牧场是否可能会产生低于正常水平的，接近正常或高于正常水平的草生物量（磅/英亩）。Grass-Cast还提供了更广阔地区的牧场生产力视图，以帮助进行更大范围的决策，例如，如果牧场主自己的地区面临干旱的风险，则用于放牧的草料资源可能会更多。从4月到7月，Grass-Cast大约每两周更新一次。每个Grass-Cast预报根据不同的降水前景提供了针对即将到来的生长季节的ANPP的三种方案。可以使用接近实时的8 d NDVI来补充Grass-Cast，以预测南部大平原从4月中旬开始以及中部和北部大平原从5月中旬到6月初开始的累积生长季NDVI和ANPP。在这里，我们介绍了草C的科学基础和方法，以及美国大平原十个州的2017年和2018年县级产量预测。到5月下旬或6月初，早期生长季预报与生长季末ANPP估算之间的相关性> 50％。在一项回顾性评估中，我们将格拉斯·卡斯特生长季末的ANPP结果与一个独立的数据集进行了比较，发现二者在20年的时间内达成了69％的共识。尽管存在一些预测工具来预测即将到来的生长季节状况，但没有一个工具可以预测整个大平原的实际生产力。Grass-Cast系统可用于预测大平原以外的草地ANPP或预测多年生生物燃料草的产量。我们将Grass-Cast生长季末的ANPP结果与一个独立的数据集进行了比较，发现在20年的时间里，这两个时间占69％。尽管存在一些预测工具来预测即将到来的生长季节状况，但没有一个工具可以预测整个大平原的实际生产力。Grass-Cast系统可用于预测大平原以外的草地ANPP或预测常年生物燃料草的产量。我们将Grass-Cast生长季末的ANPP结果与一个独立的数据集进行了比较，发现在20年的时间里，这两个时间占69％。尽管存在一些预测工具来预测即将到来的生长季节状况，但没有一个工具可以预测整个大平原的实际生产力。Grass-Cast系统可用于预测大平原以外的草地ANPP或预测常年生物燃料草的产量。