Postfire shifts in vegetation composition will have broad ecological impacts. However, information characterizing postfire recovery patterns and their drivers are lacking over large spatial extents. In this analysis, we used Landsat imagery collected when snow cover (SCS) was present, in combination with growing season (GS) imagery, to distinguish evergreen vegetation from deciduous vegetation. We sought to (1) characterize patterns in the rate of postfire, dual‐season Normalized Difference Vegetation Index (NDVI) across the region, (2) relate remotely sensed patterns to field‐measured patterns of re‐vegetation, and (3) identify seasonally specific drivers of postfire rates of NDVI recovery. Rates of postfire NDVI recovery were calculated for both the GS and SCS for more than 12,500 burned points across the western United States. Points were partitioned into faster and slower rates of NDVI recovery using thresholds derived from field plot data (n = 230) and their associated rates of NDVI recovery. We found plots with conifer saplings had significantly higher SCS NDVI recovery rates relative to plots without conifer saplings, while plots with ≥50% grass/forbs/shrubs cover had significantly higher GS NDVI recovery rates relative to plots with <50%. GS rates of NDVI recovery were best predicted by burn severity and anomalies in postfire maximum temperature. SCS NDVI recovery rates were best explained by aridity and growing degree days. This study is the most extensive effort, to date, to track postfire forest recovery across the western United States. Isolating patterns and drivers of evergreen recovery from deciduous recovery will enable improved characterization of forest ecological condition across large spatial scales.

中文翻译：

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美国西部大火后针叶树更新与落叶植被恢复的追踪率

火灾后植被组成的变化将产生广泛的生态影响。然而，在大空间范围内缺乏表征火灾后恢复模式及其驱动因素的信息。在此分析中，我们使用了当有积雪（SCS）时收集的Landsat影像，以及生长季节（GS）影像，以区分常绿植被和落叶植被。我们试图（1）表征区域内大火后速率，双季归一化植被指数（NDVI）的特征；（2）将遥感模式与野外测量的再植被模式相关联；以及（3）识别NDVI恢复后生火率的季节性特定驱动因素。计算了美国西部GS和SCS超过12500个燃烧点的NDVI恢复率。n  = 230）及其相关的NDVI恢复率。我们发现，具有针叶树苗的地块相对于没有针叶树苗的地块具有更高的SCS NDVI恢复率，而具有≥50％草地/草丛/灌木覆盖率的地块具有相对高于<50％的地块的GS NDVI恢复率。NDVI恢复的GS率可通过烧伤严重程度和大火后最高温度异常来最好地预测。干旱和生长日数可以最好地解释SCS NDVI的恢复率。迄今为止，这项研究是跟踪美国西部整个森林火灾后恢复的最广泛努力。从落叶恢复中分离常绿恢复的模式和动因，将能够改善大空间尺度上森林生态状况的特征。