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Ultra-Fine Scale Spatially-Integrated Mapping of Habitat and Occupancy Using Structure-From-Motion

机译:使用运动结构的超精细尺度人居和空间集成图

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摘要

Organisms respond to and often simultaneously modify their environment. While these interactions are apparent at the landscape extent, the driving mechanisms often occur at very fine spatial scales. Structure-from-Motion (SfM), a computer vision technique, allows the simultaneous mapping of organisms and fine scale habitat, and will greatly improve our understanding of habitat suitability, ecophysiology, and the bi-directional relationship between geomorphology and habitat use. SfM can be used to create high-resolution (centimeter-scale) three-dimensional (3D) habitat models at low cost. These models can capture the abiotic conditions formed by terrain and simultaneously record the position of individual organisms within that terrain. While coloniality is common in seabird species, we have a poor understanding of the extent to which dense breeding aggregations are driven by fine-scale active aggregation or limited suitable habitat. We demonstrate the use of SfM for fine-scale habitat suitability by reconstructing the locations of nests in a gentoo penguin colony and fitting models that explicitly account for conspecific attraction. The resulting digital elevation models (DEMs) are used as covariates in an inhomogeneous hybrid point process model. We find that gentoo penguin nest site selection is a function of the topography of the landscape, but that nests are far more aggregated than would be expected based on terrain alone, suggesting a strong role of behavioral aggregation in driving coloniality in this species. This integrated mapping of organisms and fine scale habitat will greatly improve our understanding of fine-scale habitat suitability, ecophysiology, and the complex bi-directional relationship between geomorphology and habitat use.
机译:生物对环境做出反应并经常同时对其进行修改。虽然这些相互作用在景观范围内很明显,但驱动机制通常发生在非常精细的空间尺度上。运动结构(SfM)是一种计算机视觉技术,可以同时绘制生物体和小规模栖息地的地图,并将极大地增进我们对栖息地适应性,生态生理学以及地貌与栖息地使用之间的双向关系的了解。 SfM可用于以低成本创建高分辨率(厘米级)三维(3D)栖息地模型。这些模型可以捕获地形形成的非生物条件,并同时记录单个生物在该地形中的位置。虽然在海鸟物种中很容易出现殖民地现象,但我们对密集的繁殖聚集在多大程度上由精细的主动聚集或有限的合适栖息地所驱动的程度了解甚少。我们通过重建gentoo企鹅殖民地的巢穴位置和明确说明特定吸引作用的拟合模型,证明了将SfM用于精细的栖息地适应性。所得的数字高程模型(DEM)在不均匀的混合点过程模型中用作协变量。我们发现金戈企鹅巢的位置选择是景观地形的一个函数,但是巢的聚集远比仅基于地形的预期要集中得多,这表明行为聚集在驱动该物种的殖民化中发挥着重要作用。这种有机体和小规模生境的综合映射将极大地增进我们对小规模生境适应性,生态生理学以及地貌和生境使用之间复杂的双向关系的理解。

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  • 年(卷),期 -1(12),1
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  • 页码 e0166773
  • 总页数 16
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