Department of Environmental Science, Policy and Management, University of California, Berkeley, California, 94703, USA.
USDA Forest Service, Pacific Southwest Research Station, Albany, California, 94710, USA.
Ecol Appl. 2018 Sep;28(6):1626-1639. doi: 10.1002/eap.1756. Epub 2018 Jul 9.
Shifting disturbance regimes can have cascading effects on many ecosystems processes. This is particularly true when the scale of the disturbance no longer matches the regeneration strategy of the dominant vegetation. In the yellow pine and mixed conifer forests of California, over a century of fire exclusion and the warming climate are increasing the incidence and extent of stand-replacing wildfire; such changes in severity patterns are altering regeneration dynamics by dramatically increasing the distance from live tree seed sources. This has raised concerns about limitations to natural reforestation and the potential for conversion to non-forested vegetation types, which in turn has implications for shifts in many ecological processes and ecosystem services. We used a California region-wide data set with 1,848 plots across 24 wildfires in yellow pine and mixed conifer forests to build a spatially explicit habitat suitability model for forecasting postfire forest regeneration. To model the effect of seed availability, the critical initial biological filter for regeneration, we used a novel approach to predicting spatial patterns of seed availability by estimating annual seed production from existing basal area and burn severity maps. The probability of observing any conifer seedling in a 60-m area (the field plot scale) was highly dependent on 30-yr average annual precipitation, burn severity, and seed availability. We then used this model to predict regeneration probabilities across the entire extent of a "new" fire (the 2014 King Fire), which highlights the spatial variability inherent in postfire regeneration patterns. Such forecasts of postfire regeneration patterns are of importance to land managers and conservationists interested in maintaining forest cover on the landscape. Our tool can also help anticipate shifts in ecosystem properties, supporting researchers interested in investigating questions surrounding alternative stable states, and the interaction of altered disturbance regimes and the changing climate.
干扰体系的转变可能会对许多生态系统过程产生级联效应。当干扰的规模不再与优势植被的再生策略相匹配时，尤其如此。在加利福尼亚州的黄松和混交针叶林，一个多世纪的防火措施和气候变暖正在增加林分更替野火的发生率和范围；这种严重程度模式的变化通过显著增加与活树种子源的距离，改变了再生动态。这引起了人们对自然更新造林的限制以及向非森林植被类型转化的潜在可能性的关注，这反过来又对许多生态过程和生态系统服务产生了影响。我们使用了一个加利福尼亚地区范围的数据，该数据包含 24 个野火的 1848 个样本，这些样本位于黄松和混交针叶林中，以建立一个空间明确的适合度模型，用于预测火灾后森林再生。为了模拟种子供应的影响，即再生的关键初始生物学筛选，我们使用了一种新颖的方法来预测种子供应的空间模式，方法是根据现有基面积和燃烧严重程度图估计每年的种子产量。在 60 米区域（实地样本规模）中观察到任何针叶树苗的概率高度依赖于 30 年平均年降水量、燃烧严重程度和种子供应。然后，我们使用该模型预测整个“新”火灾（2014 年国王火灾）范围的再生概率，这突出了火灾后再生模式中的空间变异性。这种对火灾后再生模式的预测对关注在景观上保持森林覆盖的土地管理者和自然资源保护主义者很重要。我们的工具还可以帮助预测生态系统特性的变化，支持对替代稳定状态和改变的干扰体系与气候变化的相互作用等问题感兴趣的研究人员。
