As fire regimes shift in western North America, patches of stand-replacing fire are becoming larger. Forest succession in these patches is not well understood. There is concern that competition with rapidly reestablishing shrubs, combined with dispersal limitation, may delay or impede conifer recovery and/or shift tree composition toward shade-tolerant species. However, tree–shrub interactions and shrub neighborhood dynamics have not been closely examined. To investigate the patterns and processes determining forest recovery after severe wildfire, we developed a data-driven simulation model that we use to predict conifer emergence above the shrub canopy. Our model results showed that ponderosa pine (Pinus ponderosa) emerged at a faster rate than white fir (Abies concolor) under whitethorn ceanothus (Ceanothus cordulatus) and deerbrush (Ceanothus integerrimus), and at a similar rate under greenleaf manzanita (Arctostaphylos patula). Across all shrub species, ponderosa pine had a relative advantage over fir in the period between conifer establishment and peak shrub competition, requiring a mean of 16 years for 50% of individuals to emerge compared to 22 years for fir. Fir emergence rates then surpassed those of pine, leading to similar overall emergence by simulation end: 83% ± 7% for pine and 82% ± 7% for fir. These results show that, on balance, shrub neighborhood dynamics do not produce an ecological filter favoring firs for the initial cohort of established seedlings, but emergence patterns are sensitive to shrub species. Further applications of this data-driven simulation framework could improve understanding of other important components of post-fire succession.

随着北美西部地区火情的转变，替代林地的火势正变得越来越大。在这些斑块中的森林演替还不是很清楚。令人担忧的是，与迅速重建的灌木丛的竞争，再加上散布的限制，可能会延迟或阻碍针叶树的恢复和/或使树木组成向耐荫树种转移。但是，尚未对树木与灌木之间的相互作用和灌木邻域动态进行仔细研究。为了调查确定严重野火后森林恢复的模式和过程，我们开发了一种数据驱动的仿真模型，该模型可用于预测灌木丛上方的针叶树的出现。我们的模型结果表明，黄松（Pinus tankerosa）的出现速度快于白杉（Abies concolor）在白刺ceanothus（Ceanothus cordulatus）和deerbrush（Ceanothus integerrimus）下，并且在绿叶manzanita（Arctostaphylos patula）下以相似的速率）。在所有灌木种类中，美国黄松在针叶树建立与灌木竞争高峰之间的时间段中具有相对于冷杉的相对优势，50％的个体平均需要16年才能生长，而冷杉需要22年。然后，杉木的出苗率超过了松树，在模拟结束时导致了相似的总体出苗率：松树为83％±7％，杉木为82％±7％。这些结果表明，总的来说，灌木邻里动态不会为既定幼苗的最初队列产生有利于冷杉的生态过滤器，但是出苗方式对灌木物种很敏感。该数据驱动的模拟框架的进一步应用可以增进对后继演习其他重要组成部分的理解。