School of BioSciences, University of Melbourne, Parkville, Victoria, Australia.
Arthur Rylah Institute, Department of Environment, Land, Water and Planning, Heidelberg, Victoria, Australia.
Conserv Biol. 2022 Jun;36(3):e13888. doi: 10.1111/cobi.13888. Epub 2022 Jan 31.
Surveys aimed at finding threatened and invasive species can be challenging due to individual rarity and low and variable individual detection rates. Detection rate in plant surveys typically varies due to differences among observers, among the individual plants being surveyed (targets), and across background environments. Interactions among these 3 components may occur but are rarely estimated due to limited replication and control during data collection. We conducted an experiment to investigate sources of variation in detection of 2 Pilosella species that are invasive and sparsely distributed in the Alpine National Park, Australia. These species are superficially similar in appearance to other yellow-flowered plants occurring in this landscape. We controlled the presence and color of flowers on target Pilosella plants and controlled their placement in plots, which were selected for their variation in cover of non-target yellow flowers and dominant vegetation type. Observers mimicked Pilosella surveys in the plots and reported 1 categorical and 4 quantitative indicators of their survey experience level. We applied survival analysis to detection data to model the influence of both controlled and uncontrolled variables on detection rate. Orange- and yellow-flowering Pilosella in grass- and heath-dominated vegetation were detected at a higher rate than nonflowering Pilosella. However, this detection gain diminished as the cover of other co-occurring yellow-flowering species increased. Recent experience with Pilosella surveys improved detection rate. Detection experiments are a direct and accessible means of understanding detection processes and interpreting survey data for threatened and invasive species. Our detection findings have been used for survey planning and can inform progress toward eradication. Interaction of target and background characteristics determined detection rate, which enhanced predictions in the Pilosella eradication program and demonstrated the difficulty of transferring detection findings into untested environments.
由于个体稀有且个体检测率低且变化，针对受威胁和入侵物种的调查可能具有挑战性。植物调查中的检测率通常因观察者之间、被调查的单个植物（目标）之间以及背景环境之间的差异而有所不同。这三个组成部分之间可能会发生相互作用，但由于在数据收集过程中有限的复制和控制，很少对其进行估计。我们进行了一项实验，以调查澳大利亚阿尔卑斯国家公园入侵和稀疏分布的两种 Pilosella 物种的检测变化来源。这些物种在外貌上与该景观中出现的其他黄色花朵植物相似。我们控制了目标 Pilosella 植物上花朵的存在和颜色，并控制了它们在斑块中的位置，这些斑块是根据非目标黄色花朵和主要植被类型的覆盖变化选择的。观察者在斑块中模拟了 Pilosella 的调查，并报告了他们调查经验水平的 1 个分类和 4 个定量指标。我们应用生存分析来检测数据，以模拟控制和非控制变量对检测率的影响。在草地和石南为主的植被中，橙色和黄色开花的 Pilosella 的检测率高于不开花的 Pilosella。然而，随着其他共存的黄色开花物种的覆盖增加，这种检测增益会减少。最近对 Pilosella 调查的经验提高了检测率。检测实验是一种直接且易于理解的方法，可以了解检测过程并解释受威胁和入侵物种的调查数据。我们的检测结果已用于调查规划，并为根除计划提供了信息。目标和背景特征的相互作用决定了检测率，这增强了在 Pilosella 根除计划中的预测，并表明将检测结果转移到未经测试的环境中具有挑战性。
