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Habitat suitability for marine fishes using presence-only modelling and multibeam sonar

机译:使用仅存在的建模和多波束声纳对海洋鱼类的栖息地适应性

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摘要

Improved access to multibeam sonar and underwater video technology is enabling scientists to use spatially-explicit, predictive modelling to improve our understanding of marine ecosystems. With the growing number of modelling approaches available, knowledge of the relative performance of different models in the marine environment is required. Habitat suitability of 5 demersal fish taxa in Discovery Bay, south-east Australia, were modelled using 10 presence-only algorithms: BIOCLIM, DOMAIN, ENFA (distance geometric mean [GM], distance harmonic mean [HM], median [M], area-adjusted median [Ma], median + extremum [Me], area-adjusted median + extremum [Mae] and minimum distance [Min]), and MAXENT. Model performance was assessed using kappa and area under curve (AUC) of the receiver operator characteristic. The influence of spatial range (area of occupancy) and environmental niches (marginality and tolerance) on modelling performance were also tested. MAXENT generally performed best, followed by ENFA-GM and -HM, DOMAIN, BIOCLIM, ENFA-M, -Min, -Ma, -Mae and -Me algorithms. Fish with clearly definable niches (i.e. high marginality) were most accurately modelled. Generally, Euclidean distance to nearest reef, HSI-b (backscatter), rugosity and maximum curvature were the most important variables in determining suitable habitat for the 5 demersal fish taxa investigated. This comparative study encourages ongoing use of presence-only approaches, particularly MAXENT, in modelling suitable habitat for demersal marine fishes.
机译:改善对多束声纳和水下视频技术的访问,使科学家能够使用空间明晰的预测模型来增进我们对海洋生态系统的了解。随着可用的建模方法越来越多,需要了解海洋环境中不同模型的相对性能。使用10种仅存在算法对澳大利亚东南部愉景湾的5种水下鱼类分类的栖息地适应性进行建模:BIOCLIM,DOMAIN,ENFA(距离几何平均值[GM],距离谐波平均值[HM],中位数[M],面积调整后的中值[Ma],中值+极值[Me],面积调整后的中值+极值[Mae]和最小距离[Min])和MAXENT。使用接收者操作员特征的Kappa和曲线下面积(AUC)评估模型性能。还测试了空间范围(占用区域)和环境生态位(边际和公差)对建模性能的影响。 MAXENT通常表现最佳,其次是ENFA-GM和-HM,DOMAIN,BIOCLIM,ENFA-M,-Min,-Ma,-Mae和-Me算法。具有明确定义的生态位(即高边缘度)的鱼是最准确的模型。通常,欧几里得距离最近的珊瑚礁,HSI-b(反向散射),皱折度和最大曲率是在确定所研究的5种水下鱼类分类的适宜生境中最重要的变量。这项比较研究鼓励继续使用仅存在的方法(尤其是MAXENT)来为海底鱼类的合适栖息地建模。

著录项

  • 来源
    《Marine ecology progress series》 |2010年第16期|p.157-174|共18页
  • 作者单位

    School Life & Environmental Sciences, Faculty of Science and Technology, Deakin University, PO Box 423, Warrnambool, Victoria 3280, Australia;

    School Life & Environmental Sciences, Faculty of Science and Technology, Deakin University, PO Box 423, Warrnambool, Victoria 3280, Australia;

    School Life & Environmental Sciences, Faculty of Science and Technology, Deakin University, PO Box 423, Warrnambool, Victoria 3280, Australia;

    School Life & Environmental Sciences, Faculty of Science and Technology, Deakin University, PO Box 423, Warrnambool, Victoria 3280, Australia;

    School of Plant Biology (Oceans Institute M470), University of Western Australia, 35 Stirling Highway, Crawley, Western Australia 6009, Australia;

    School Life & Environmental Sciences, Faculty of Science and Technology, Deakin University, PO Box 423, Warrnambool, Victoria 3280, Australia;

    School Life & Environmental Sciences, Faculty of Science and Technology, Deakin University, PO Box 423, Warrnambool, Victoria 3280, Australia;

    School Life & Environmental Sciences, Faculty of Science and Technology, Deakin University, PO Box 423, Warrnambool, Victoria 3280, Australia;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    species distribution modelling; multibeam sonar; towed-video; MAXENT; ENFA; BIOCLIM; DOMAIN;

    机译:物种分布建模;多束声纳拖视频MAXENT;ENFA;BIOCLIM;域;

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