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Using drone imagery analysis in rare plant demographic studies

机译:在稀有植物人口研究中使用无人机图像分析

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For plant species of conservation concern, knowledge of changes in abundance through time is a minimum requirement for informed management. This information is usually acquired through on-the-ground monitoring, which entails counting individuals in defined areas over multiple years. Demographic studies, which involve tracking individual plants through time, are usually carried out at limited spatial scales and over shorter time frames than monitoring, but are more useful to management. In this study we explored the use of drone (UAV or unmanned aerial vehicle) imagery analysis as a tool for collecting demographic data for dwarf bear poppy (Arctomecon humilis), an endangered species restricted to gypsum outcrops in the northeastern Mojave Desert, USA. We obtained imagery at 15 m altitude during peak flowering at four populations in spring 2019. Each poppy plant in the imagery was georeferenced, measured and scored for flowering. To estimate reproductive output, we developed independent data sets relating plant diameter to flower number, then sampled to determine mean fruit set per flower and seeds per fruit. We used these relationships along with plant diameter and reproductive status for each plant in the drone imagery to estimate seed rain on an area basis across nine 0.6 ha demography plots at each population. This method enabled us to collect demographic data on 3,000 plants, including estimated production of ca. 3.7 million seeds, across 20 ha of habitat. We also analyzed imagery acquired in both 2018 and 2019 at two of the four populations and quantified recruitment, growth, and mortality of individual georeferenced plants. Our study is among the first to demonstrate the utility of drone imagery analysis in plant demographic studies. The method is most applicable for non-clonal perennial species with distinctive morphology that occur in habitats with low vegetative cover.
机译:对于植物物种的保护问题,通过时间的丰富变化的了解是知情管理的最低要求。此信息通常通过地面监控获取,这需要在多年内计算定义区域中的个体。涉及通过时间跟踪单个植物的人口统计学研究通常在有限的空间尺度和比监测中缩短时间框架,但对管理更有用。在这项研究中,我们探讨了无人机(无人机或无人机)图像图像图像作为收集Dwarf Bear Poppy(Arctomecon Humilis)的人口统计数据的工具,濒危物种限于美国东北部莫哈韦沙漠的石膏露头。在2019年春季的四个群体的峰值开花期间,我们在15米高度获得了图像。图像中的每个罂粟植物都被嘲弄,测量并为开花得分。为了估算生殖输出,我们开发了与花序的独立数据集将植物直径相关,然后采样以确定每朵花和种子的平均水果。我们将这些关系与植物直径和植物直径和生殖状态一起用于无人机图像中的每株植物,以估计每个人群的九个0.6哈人口摄影地区的区域基础。该方法使我们能够在&gt收集人口统计数据; 3,000家工厂,包括估计的CA生产。 370万种子,穿越& 20公顷的栖息地。我们还分析了2018年和2019年在四个群体中的两个人中获得的图像,并量化了个体地理工艺植物的招聘,增长和死亡率。我们的研究是第一个证明在植物人口研究中的无人机图像分析的效用之一。该方法对于非克隆多年生物种最适用于具有明显形态的非克隆多年生物种,其栖息地发生具有低营养覆盖物的栖息地。

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