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Spatial and spatial-temporal analysis of mountain pine beetle infestations at a landscape scale.

机译：在景观尺度上对山松甲虫侵扰的时空分析。

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The impact of the current mountain pine beetle (Dendroctonus ponderosae Hopkins) epidemic in British Columbia underscores the need for scientifically informed management practices. During an epidemic it is necessary to manage large areas and an understanding of landscape scale spatial and spatial-temporal processes is required. With the recent availability of large area, multi-temporal data sets there are new opportunities for landscape scale studies of the mountain pine beetle over space and through time.; In this thesis large area spatial and spatial-temporal patterns of lodgepole pine (Pious contorta var. Latifolia) mortality are explored using point data collected through helicopter surveys. As with all large area data sets, mountain pine beetle data are prone to uncertainty. Using field measurements collected to supplement the helicopter data set, we explore the nature and amount of error in point data. Based on error estimates, a method is presented for incorporating uncertainty when visualizing data via kernel density estimation.; Locations that are hot spots, or have the most intense infestations, are identified and used to explore dispersal behaviour. Comparing hot spots to various landscape characteristics allows investigation into how mountain pine beetle utilize the forest in space and through time. Locations of change are also identified and explored in terms of spatial-temporal patterns and associated landscape characteristics. The relatedness of hot spot and change locations is investigated.; A randomization approach is also used to supply the spatial pattern of large area infestations by evaluating observed data relative to a null expectation conditioned on a model of forests at risk to beetle attack. Investigating the landscape characteristics associated with unexpected locations enabled exploration into the cause of differences between empirical and modelled patterns.
机译：当前不列颠哥伦比亚省的山松甲虫（Dendroctonus tankerosae Hopkins）流行病的影响凸显了对科学知情管理方法的需求。在流行期间，有必要管理大面积区域，并且需要了解景观尺度的时空过程。随着近来大面积，多时间数据集的出现，在空间和时间上对山地甲虫的景观规模研究有了新的机会。在这篇论文中，使用通过直升机调查收集的点数据，探索了大面积的黑松（Pious contorta var。Latifolia）死亡率的时空格局。与所有大面积数据集一样，山松甲虫数据也容易出现不确定性。利用收集到的现场测量数据来补充直升机数据集，我们探索了点数据中误差的性质和数量。基于误差估计，提出了一种在通过核密度估计可视化数据时合并不确定性的方法。确定热点或侵扰最严重的位置，并将其用于探索传播行为。将热点与各种景观特征进行比较，可以研究松树甲虫如何在空间和时间上利用森林。还根据时空格局和相关的景观特征确定并探索变化的位置。研究热点和变化位置的相关性。随机化方法还用于通过评估相对于以甲虫袭击风险森林模型为基础的零期望的观测数据来评估大面积侵染的空间格局。调查与意外位置相关的景观特征可以探索经验模式与建模模式之间差异的原因。

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