Management inputs, site conditions, and fire history shape outcomes of invasive plant control and native recovery

Millions of dollars and countless hours are spent on invasive plant management, and the field of invasion ecology has gained increasing attention in recent decades. Yet, despite these efforts to control and understand plant invasions, successful management is often elusive. Budgetary constraints are a common factor limiting invasive plant management programs, and therefore, optimizing control strategies are essential. However, such optimization requires data on management inputs and outcomes, and these data are often missing, lacking, or underutilized. To address this knowledge gap and identify predictors of successful weed control in natural areas, we examined nearly 20 years of invasive plant treatment data in the world’s largest urban national park – Santa Monica Mountains National Recreation Area of southern California. We resurveyed 279 sites that had undergone control in the past two decades, collecting data on the abundance of native and invasive plant species to evaluate long-term management outcomes. We used multiple statistical approaches to identify management inputs and site characteristics that are predictors of eradication, invasive plant cover, and native species recovery. We found that the greater the initial size or percent cover of an infestation, the lower the probability of eradication. We also found that weed infestations on steeper slopes and in areas that have burned more frequently are less likely to be eradicated. Promisingly, our results also showed that greater reductions in invasives generally benefited native plant communities, though not in all cases. These analyses also highlighted that persistence is key; more frequent treatments (both chemical and nonchemical) and greater investment of labor resulted in larger reductions in invasive plants. Our results highlight how site characteristics and limited resources can complicate invasive plant management, while demonstrating the value of analyzing treatment and monitoring data to identify effective control strategies and guide adaptive management decisions.

数十年来，入侵植物防治工作已累计投入数百万美元与不计其数的人力时长，入侵生态学（Invasion Ecology）领域在近几十年间也获得了日益广泛的关注。然而，尽管我们为防控与解析植物入侵付出了诸多努力，却往往难以达成理想的防治成效。预算约束是限制入侵植物防治项目推进的常见瓶颈，因此优化防治策略实属必要。但这类优化工作亟需获取防治投入与防治成效的相关数据，而此类数据往往存在缺失、不足或未被充分利用的问题。为填补这一认知空白，并识别自然区域内杂草防治成功的预测因子，我们对全球最大的城市国家公园——南加州圣莫尼卡山脉国家游乐区（Santa Monica Mountains National Recreation Area）近20年的入侵植物防治数据展开了系统性分析。我们对过去20年间已实施过防治措施的279个样地进行了重新调查，采集了本土与入侵植物物种的多度数据，以评估长期防治的实际成效。我们采用多种统计分析方法，识别出可预测入侵物种根除率、入侵植物盖度与本土物种恢复情况的防治投入与样地特征因子。研究结果显示，入侵种群的初始规模或初始盖度越高，其被成功根除的概率就越低。此外我们还发现，坡度更陡峭的区域与燃烧频次更高的区域内的杂草入侵种群，更难被彻底根除。值得欣喜的是，我们的研究还表明，对入侵植物开展更大幅度的清除通常能使本土植物群落获益，尽管并非所有场景均符合这一规律。本次分析还凸显了持续防治的核心作用：更频繁的防治措施（涵盖化学与非化学手段）以及更多的人力投入，均可更大幅度地降低入侵植物的种群规模。我们的研究结果揭示了样地特征与有限资源如何加剧入侵植物防治的实施难度，同时也证明了分析防治与监测数据的重要价值——此类数据可用于识别高效的防治策略，并为适应性管理（Adaptive Management）决策提供科学指导。