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首页> 外文期刊>The Open Ornithology Journal >Spatially Predictive Habitat Modeling of a White Stork (Ciconia Ciconia) Population in Former East Prussia in 1939
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Spatially Predictive Habitat Modeling of a White Stork (Ciconia Ciconia) Population in Former East Prussia in 1939

机译：1939年前东普鲁士白鹳（Ciconia Ciconia）种群的空间预测栖息地模型

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Historic information is often crucial for assessing changes and drivers for wildlife and habitat changes although it is often plagued with statistically poor quality. Here we developed three habitat models on two different scales for 1939 for the white stork (Ciconia ciconia) in the region of former East Prussia. We used a geographical information system and a statistical modeling algorithm that comes from the disciplines of machine-learning and data mining (TreeNet). The occurrence of white stork nesting grounds is mainly defined by the variables - distance to forest - , - distance to/density of settlement - , - distance to pasture - and - distance to coastline - . The models present for the first time a quantitative predictive distribution estimate for East Prussia. They are a sound foundation but could be further improved by more data regarding the structure of the habitat and more exact spatially explicit information on the location of white stork nesting sites.
机译：历史信息通常对于评估变化以及野生动植物和栖息地变化的驱动因素至关重要，尽管它经常受到统计质量差的困扰。在这里，我们为前东普鲁士地区的白鹳（Ciconia ciconia）在1939年开发了两种不同比例的三种生境模型。我们使用了来自机器学习和数据挖掘（TreeNet）学科的地理信息系统和统计建模算法。白鹳筑巢地的发生主要由以下变量定义：到森林的距离-，到居民点的距离/密度-，到牧场的距离-到海岸线的距离-。这些模型首次提出了对东普鲁士的定量预测分布估计。它们是一个良好的基础，但是可以通过更多有关栖息地结构的数据以及有关白鹳筑巢点位置的更精确的空间明确信息来进一步改善它们。

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