Data from: Where and how to restore in a changing world: a demographic-based assessment of resilience

Managers are increasingly looking to apply concepts of resilience to better anticipate and understand conservation and restoration in a changing environment. In this study, we explore how information on demography (recruitment, growth and survival) and competitive effects in different environments and with different starting species abundances can be used to better understand resilience. We use observational and experimental data to better understand dynamics between native Stipa pulchra and exotic Avena barbata and fatua, grasses characteristic of native and invaded grasslands in California, at three different levels of nitrogen (N) representative of a range of pollution via atmospheric deposition. A modelling framework that incorporates this information on demography and competition allows us to forecast dynamics over time. Our results showed that resilience of native grasslands depends on N inputs, where natural recovery should be possible at low N levels whereas native persistence would be difficult at high N levels. Hysteresis was evident at moderate N levels, where the starting conditions mattered. Synthesis and applications. The resilience of both invaded and native grasslands is influenced by nitrogen inputs. Our modelling approach gives direction about how best to allocate limited management resources as baselines shift: where natural recovery is possible, where best to allocate active restoration efforts, and where native remnants may be most vulnerable.管理者正日益寻求应用恢复力（resilience）的相关理念，以在不断变化的环境中更好地预判并理解生态保护与修复工作。 本研究探讨了不同环境下、不同初始物种丰度条件下的种群统计学（种群补充、生长与存活）及竞争效应相关信息，可如何用于深化对恢复力的理解。我们通过观测与实验数据，针对加利福尼亚本土与入侵草原的典型禾本科植物——本土美针茅（Stipa pulchra）以及外来的Avena barbata与Avena fatua，在三类代表不同大气氮沉降污染梯度的氮（N）水平下，探究二者间的动态关系。本研究采用整合了种群统计学与竞争信息的建模框架，实现了对其随时间演变的动态过程预测。 研究结果表明，本土草原的恢复力取决于氮输入水平：低氮水平下可实现自然恢复，而高氮水平下本土物种则难以持续存活。在中等氮水平下存在明显的滞后效应（hysteresis），此时初始条件会对结果产生显著影响。 综合与应用。入侵与本土草原的恢复力均受氮输入水平的影响。当基线环境发生变化时，我们的建模方法可为有限管理资源的最优配置提供指引：包括可实现自然恢复的场景、主动修复工作的最优投入方向，以及本土残存群落的最脆弱位点。