Using multiplatform LiDAR to identify relationships between vegetation structure and the abundance and diversity of woodland reptiles and amphibians,Remote Sensing in Ecology and Conservation

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Using multiplatform LiDAR to identify relationships between vegetation structure and the abundance and diversity of woodland reptiles and amphibians
Remote Sensing in Ecology and Conservation ( IF 3.9 ) Pub Date : 2024-01-03 , DOI: 10.1002/rse2.381
Shukhrat Shokirov _{1,

2,

3} , Tommaso Jucker ₄ , Shaun R. Levick ₂ , Adrian D. Manning ₅ , Kara N. Youngentob _{1,

5}

Affiliation

Remotely sensed measures of vegetation structure have been shown to explain patterns in the occurrence and diversity of several animal taxa, including birds, mammals, and invertebrates. However, very little research in this area has focused on reptiles and amphibians (herpetofauna). Moreover, most remote sensing studies on animal–habitat associations have relied on airborne or satellite data that provide coverage over relatively large areas but may not have the resolution or viewing angle necessary to measure vegetation features at scales that are meaningful to herpetofauna. Here, we combined terrestrial laser scanning (TLS), unmanned aerial vehicle laser scanning (ULS), and fused (FLS) data to provide the first test of whether vegetation structural attributes can help explain variation in herpetofauna abundance, species richness, and diversity across a woodland landscape. We identified relationships between the abundance and diversity of herpetofauna and several vegetation metrics, including canopy height, skewedness, vertical complexity, volume of vegetation, and coarse woody debris. These relationships varied across species, groups, and sensors. ULS models tended to perform as well or better than TLS or FLS models based on the methods we used in this study. In open woodland landscapes, ULS data may have some benefits over TLS data for modeling relationships between herpetofauna and vegetation structure, which we discuss. However, for some species, only TLS data identified significant predictor variables among the LiDAR-derived structural metrics. While the overall predictive power of models was relatively low (i.e., at most R² = 0.32 for ULS overall abundance and R² = 0.32 for abundance at the individual species level [three-toed skink (Chalcides striatus)]), the ability to identify relationships between specific LiDAR structural metrics and the abundance and diversity of herpetofauna could be useful for understanding their habitat associations and managing reptile and amphibian populations.

中文翻译：

使用多平台激光雷达识别植被结构与林地爬行动物和两栖动物的丰度和多样性之间的关系

植被结构的遥感测量已被证明可以解释几种动物类群（包括鸟类、哺乳动物和无脊椎动物）的出现和多样性模式。然而，该领域的研究很少集中在爬行动物和两栖动物（爬行动物）上。此外，大多数关于动物-栖息地关联的遥感研究都依赖于机载或卫星数据，这些数据提供了相对较大区域的覆盖范围，但可能不具备测量对爬行动物有意义的尺度植被特征所需的分辨率或视角。在这里，我们结合了地面激光扫描（TLS）、无人机激光扫描（ULS）和融合（FLS）数据，首次测试植被结构属性是否有助于解释爬行动物丰度、物种丰富度和多样性的变化。林地景观。我们确定了爬行动物的丰度和多样性与几个植被指标之间的关系，包括树冠高度、倾斜度、垂直复杂性、植被体积和粗木本碎片。这些关系因物种、群体和传感器而异。根据我们在本研究中使用的方法，ULS 模型的性能往往与 TLS 或 FLS 模型一样好甚至更好。在开阔的林地景观中，ULS 数据可能比 TLS 数据更有利于对爬行动物和植被结构之间的关系进行建模，我们对此进行了讨论。然而，对于某些物种，只有 TLS 数据在 LiDAR 衍生的结构指标中识别出重要的预测变量。虽然模型的总体预测能力相对较低（即 ULS 总体丰度至多R ^{2 = 0.32，单个物种水平的丰度}R ² = 0.32 [三趾石龙子 ( Chalcides striatus )]），但确定特定激光雷达结构指标与爬行动物丰富度和多样性之间的关系可能有助于了解其栖息地关联以及管理爬行动物和两栖动物种群。

更新日期：2024-01-04

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