Exotic annual grass invasions in water‐limited systems cause degradation of native plant and animal communities and increased fire risk. The life history of invasive annual grasses allows for high sensitivity to interannual variability in weather. Current distribution and abundance models derived from remote sensing, however, provide only a coarse understanding of how species respond to weather, making it difficult to anticipate how climate change will affect vulnerability to invasion. Here, we derived germination covariates (rate sums) from mechanistic germination and soil microclimate models to quantify the favorability of soil microclimate for cheatgrass (Bromus tectorum L.) establishment and growth across 30 years at 2662 sites across the sagebrush steppe system in the western United States. Our approach, using four bioclimatic covariates alone, predicted cheatgrass distribution with accuracy comparable to previous models fit using many years of remotely‐sensed imagery. Accuracy metrics from our out‐of‐sample testing dataset indicate that our model predicted distribution well (72% overall accuracy) but explained patterns of abundance poorly (R2 = 0.22). Climatic suitability for cheatgrass presence depended on both spatial (mean) and temporal (annual anomaly) variation of fall and spring rate sums. Sites that on average have warm and wet fall soils and warm and wet spring soils (high rate sums during these periods) were predicted to have a high abundance of cheatgrass. Interannual variation in fall soil conditions had a greater impact on cheatgrass presence and abundance than spring conditions. Our model predicts that climate change has already affected cheatgrass distribution with suitable microclimatic conditions expanding 10%–17% from 1989 to 2019 across all aspects at low‐ to mid‐elevation sites, while high‐ elevation sites (>2100 m) remain unfavorable for cheatgrass due to cold spring and fall soils.

中文翻译：

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模拟 cheatgrass 的分布、丰度和对气候变化的响应与土壤小气候的函数关系


在水分受限的系统中，外来的一年生草类入侵会导致本地动植物群落退化并增加火灾风险。入侵性一年生草的生活史使其对天气的年际变化高度敏感。然而，目前从遥感得出的分布和丰度模型只能粗略地了解物种如何对天气做出反应，因此很难预测气候变化将如何影响对入侵的脆弱性。在这里，我们从机械发芽和土壤小气候模型中得出发芽协变量（速率总和），以量化土壤小气候在美国西部鼠尾草草原系统的 2662 个地点 30 年内对萱草 （Bromus tectorum L.） 建立和生长的有利性。我们的方法仅使用四个生物气候协变量，以与以前的模型相当的准确性预测了 cheatgrass 分布，使用多年的遥感图像拟合。来自样本外测试数据集的准确率指标表明，我们的模型很好地预测了分布（总体准确率为 72%），但对丰度模式的解释很差 （R2 = 0.22）。Cheatgrass 存在的气候适宜性取决于秋季和春季速率总和的空间（平均值）和时间（年度异常）变化。平均而言，具有温暖潮湿的秋季土壤和温暖潮湿的春季土壤（在此期间的高比率总和）的地点预计具有较高的 cheatgrass 丰度。与春季条件相比，秋季土壤条件的年际变化对 cheatgrass 的存在和丰度的影响更大。 我们的模型预测，气候变化已经影响了禾本科植物的分布，从 1989 年到 2019 年，适宜的小气候条件在中低海拔地点的各个方面都扩大了 10%–17%，而高海拔地区（x3E2100 m）由于春季和秋季土壤寒冷，仍然不利于禾本科植物。