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Modelling habitat requirements of bullhead (Cottus gobio) in Alpine streams

机译：模拟高山溪流中的head头（Cottus gobio）的栖息地需求

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摘要

In the context of water resources planning and management, the prediction of fish distribution related to habitat characteristics is fundamental for the definition of environmental flows and habitat restoration measures. In particular, threatened and endemic fish species should be the targets of biodiversity safeguard and wildlife conservation actions. The recently developed meso-scale habitat model (MesoHABSIM) can provide solutions in this sense by using multivariate statistical techniques to predict fish species distribution and to define habitat suitability criteria. In this research, Random Forests (RF) and Logistic Regressions (LR) models were used to predict the distribution of bullhead {Cottus gobio) as a function of habitat conditions. In ten reference streams of the Alps (NW Italy), 95 mesohabitats were sampled for hydro-morphologic and biological parameters, and RF and LR were used to distinguish between absence/presence and presence/abundance of fish. The obtained models were compared on the basis of their performances (model accuracy, sensitivity, specificity, Cohen's kappa and area under ROC curve). Results indicate that RF outperformed LR, for both absence/presence (RF: 84 % accuracy, k = 0.58 and AUC = 0.88; LR: 78 % accuracy, k = 0.54 and AUC = 0.85) and presence/abundance models (RF: 79 % accuracy, k = 0.57 and AUC = 0.87; LR: 69 % accuracy, k = 0.43 and AUC = 0.81). The most important variables, selected in each model, are discussed and compared to the available literature. Lastly, results from models' application in regulated sites are presented to show the possible use of RF in predicting habitat availability for fish in Alpine streams.
机译：在水资源规划和管理的背景下，与生境特征有关的鱼类分布预测对于定义环境流量和生境恢复措施至关重要。特别是受威胁和特有的鱼类应成为生物多样性保护和野生动植物保护行动的目标。最近开发的中尺度生境模型（MesoHABSIM）可以通过使用多元统计技术预测鱼类物种分布并定义生境适宜性标准来提供这种解决方案。在这项研究中，随机森林（RF）和Logistic回归（LR）模型被用来预测作为栖息地条件的函数的牛头（Cottus gobio）的分布。在阿尔卑斯山（意大利西北部）的十个参考河流中，取样了95个中栖息地的水文形态和生物学参数，并使用RF和LR区分了鱼类的有无和有无。根据获得的模型的性能（模型的准确性，敏感性，特异性，Cohenκ和ROC曲线下的面积）对模型进行比较。结果表明，无论是否存在（RF：84％准确度，k = 0.58和AUC = 0.88; LR：78％准确度，k = 0.54和AUC = 0.85）和存在/丰度模型（RF：79），RF均优于LR。 ％精度，k = 0.57，AUC = 0.87； LR：69％精度，k = 0.43，AUC = 0.81）。在每个模型中选择的最重要变量将进行讨论，并与现有文献进行比较。最后，介绍了模型在受管制地点的应用结果，显示了RF在预测高山河流鱼类栖息地可用性方面的可能用途。

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  • 来源
    《Aquatic Sciences》 |2014年第1期|1-15|共15页
  • 作者

    Paolo Vezza; P. Parasiewicz; O. Calles; M. Spairani; C. Comoglio;

  • 作者单位

    Institut d'Investigacio per a la Gestio Integrada de Zones Costaneres, Universitat Politecnica de Valencia, C/Paranimf, 1, 46730 Grau de Gandia (Valencia), Spain,Department of Environment, Land and Infrastructure Engineering, Politecnico di Torino, Turin, Italy;

    Rushing Rivers Institute, Amherst, MA, USA S. Sakowicz Inland Fisheries Institute, Zabieniec, Poland;

    Department of Environment, Land and Infrastructure Engineering, Politecnico di Torino, Turin, Italy,Department of Biology, Karlstad University, Karlstad, Sweden;

    FLUME s.r.l. Aosta, Italy;

    Department of Environment, Land and Infrastructure Engineering, Politecnico di Torino, Turin, Italy;

  • 收录信息 美国《科学引文索引》(SCI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Mesohabitat; MesoHABSIM; Alpine streams; Cottus gobio; Habitat suitability;

    机译：中生境MesoHABSIM;高山溪流;哥斯达黎加人居适宜性;

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