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How Many Wolves (Canis lupus) Fit into Germany? The Role of Assumptions in Predictive Rule-Based Habitat Models for Habitat Generalists

机译:多少只狼(Canis lupus)可以适应德国?假设在人居通才的基于规则的人居预测模型中的作用

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摘要

Due to legislative protection, many species, including large carnivores, are currently recolonizing Europe. To address the impending human-wildlife conflicts in advance, predictive habitat models can be used to determine potentially suitable habitat and areas likely to be recolonized. As field data are often limited, quantitative rule based models or the extrapolation of results from other studies are often the techniques of choice. Using the wolf (Canis lupus) in Germany as a model for habitat generalists, we developed a habitat model based on the location and extent of twelve existing wolf home ranges in Eastern Germany, current knowledge on wolf biology, different habitat modeling techniques and various input data to analyze ten different input parameter sets and address the following questions: (1) How do a priori assumptions and different input data or habitat modeling techniques affect the abundance and distribution of potentially suitable wolf habitat and the number of wolf packs in Germany? (2) In a synthesis across input parameter sets, what areas are predicted to be most suitable? (3) Are existing wolf pack home ranges in Eastern Germany consistent with current knowledge on wolf biology and habitat relationships? Our results indicate that depending on which assumptions on habitat relationships are applied in the model and which modeling techniques are chosen, the amount of potentially suitable habitat estimated varies greatly. Depending on a priori assumptions, Germany could accommodate between 154 and 1769 wolf packs. The locations of the existing wolf pack home ranges in Eastern Germany indicate that wolves are able to adapt to areas densely populated by humans, but are limited to areas with low road densities. Our analysis suggests that predictive habitat maps in general, should be interpreted with caution and illustrates the risk for habitat modelers to concentrate on only one selection of habitat factors or modeling technique.
机译:由于立法保护,许多物种,包括大型食肉动物,目前正在重新定居欧洲。为了预先解决即将发生的人类与野生生物之间的冲突,可以使用预测性栖息地模型来确定可能合适的栖息地和可能重新定殖的地区。由于现场数据通常有限,因此基于定量规则的模型或其他研究结果的推断通常是选择的技术。我们使用德国的狼(Canis lupus)作为栖息地通才的模型,我们根据德国东部12个现有狼之家的分布范围和范围,有关狼生物学的最新知识,不同的栖息地建模技术和各种投入物,开发了栖息地模型数据来分析十种不同的输入参数集并解决以下问题:(1)先验假设和不同的输入数据或栖息地建模技术如何影响德国可能合适的狼栖息地的数量和分布以及狼群的数量? (2)在跨输入参数集的综合中,预计哪些区域最合适? (3)德国东部现有的狼群栖息地范围是否与当前有关狼生物学和栖息地关系的知识相一致?我们的结果表明,取决于在模型中应用了哪些栖息地关系假设以及选择了哪种建模技术,估计的潜在合适栖息地的数量差异很大。根据先验的假设,德国可以容纳154至1769只狼群。在德国东部,现有的狼群栖息地的位置表明,狼能够适应人口稠密的地区,但仅限于道路密度较低的地区。我们的分析表明,一般而言,预测性栖息地地图应谨慎解释,并说明栖息地建模者仅专注于一种栖息地因素或建模技术的风险。

著录项

  • 期刊名称 other
  • 作者

    Dominik Fechter; Ilse Storch;

  • 作者单位
  • 年(卷),期 -1(9),7
  • 年度 -1
  • 页码 e101798
  • 总页数 13
  • 原文格式 PDF
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  • 中图分类
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  • 入库时间 2022-08-21 11:18:13

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