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Frontiers in invasive species distribution modeling (iSDM): Assessing effects of absence data, dispersal constraints, stage of invasion and spatial dependence.

机译：入侵物种分布建模（iSDM）的前沿领域：评估缺勤数据，扩散限制，入侵阶段和空间依赖性的影响。

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摘要

Successful management of biological invasions depends heavily on our ability to predict their geographic ranges and potential habitats. Species distribution modeling (SDM) provides a methodological framework to predict spatial distributions of organisms but the unique aspects of modeling invasive species have been largely ignored in previous applications. Here, three unresolved challenges facing invasive species distribution modeling (iSDM) were examined in an effort to increase prediction accuracy and improve ecological understanding of actual and potential distributions of biological invasions. The effects of absence data and dispersal constraints, stage of invasion, and spatial dependence were assessed, using an extensive collection of field-based data on the invasive forest pathogen Phytophthora ramorum. Spatial analyses were based on a range of statistical techniques (generalized linear models, classification trees, maximum entropy, ecological niche factor analysis, multicriteria evaluation) and four groups of environmental parameters that varied in space and time: atmospheric moisture and temperature, topographic variability, abundance and susceptibility of host vegetation, and dispersal pressure. Results show that incorporating data on species absence and dispersal limitations is crucial not only to avoid overpredictions of the actual invaded range in a specific period of time but also for ecologically meaningful evaluation of iSDMs. When dispersal and colonization cannot be estimated explicitly, e.g. via dispersal kernels of propagule pressure, spatial dependence measured as spatial autocorrelation at multiple scales can serve as an important surrogate for dynamic processes that explain ecological mechanisms of invasion. If the goal is to identify habitats at potential risk of future spread, the stage of invasion should be considered because it represents the degree to which an organism is at equilibrium with its environment and limits the extent to which occurrence observations provide a sample of the species ecological niche. This research provides insight into several key principles of the SDM discipline, with implications for practical management of biological invasions.
机译：生物入侵的成功管理在很大程度上取决于我们预测其地理范围和潜在栖息地的能力。物种分布模型（SDM）提供了一种方法框架来预测生物的空间分布，但是在以前的应用中，对入侵物种进行建模的独特方面已被很大程度上忽略。在这里，研究了入侵物种分布模型（iSDM）面临的三个未解决的挑战，目的是提高预测准确性并提高对生物入侵的实际和潜在分布的生态理解。利用大量有关入侵森林病原菌疫霉的实地数据，评估了缺乏数据和扩散限制，入侵阶段以及空间依赖性的影响。空间分析基于一系列统计技术（广义线性模型，分类树，最大熵，生态位因子分析，多准则评估）和四组随时间和空间变化的环境参数：大气湿度和温度，地形变异性，寄主植被的丰度和敏感性，以及分散压力。结果表明，纳入有关物种缺乏和传播限制的数据不仅对于避免在特定时间段内对实际入侵范围的过度预测至关重要，而且对于iSDM的生态意义评估也至关重要。当无法明确估计扩散和定殖时，例如通过传播压力的扩散核，在多个尺度上以空间自相关度量的空间依赖性可以作为解释入侵生态机制的动态过程的重要替代。如果目标是确定具有未来传播潜在风险的栖息地，则应考虑入侵阶段，因为它代表了生物与其环境达到平衡的程度，并限制了发生观测提供物种样本的程度。生态位。这项研究提供了对SDM学科的几个关键原理的深刻见解，并对生物入侵的实际管理产生了影响。

著录项

  • 作者

    Vaclavik, Tomas.;

  • 作者单位

    The University of North Carolina at Charlotte.;

  • 授予单位 The University of North Carolina at Charlotte.;
  • 学科 Biology Ecology.;Geodesy.;Physical Geography.
  • 学位 Ph.D.
  • 年度 2011
  • 页码 154 p.
  • 总页数 154
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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