Assessment of spatial habitat heterogeneity by coupling data-driven habitat suitability models with a 2D hydrodynamic model in small-scale streams

Shinji Fukuda, Taichi Tanakura, Kazuaki Hiramatsu, Harada Masayoshi

研究成果: ジャーナルへの寄稿記事

18 引用 (Scopus)

抄録

Habitat assessment considering habitat quality and quantity is a key approach in conservation and restoration works for biodiversity and ecosystems. In this regard, application of hydrodynamic model for modeling instream habitat conditions and machine learning (ML) methods for modeling habitat suitability of a target species can contribute to better modeling practices in ecohydraulics. Despite the importance of small streams for aquatic ecosystems, previous studies in ecohydraulics have been conducted mainly in medium to large rivers, often disregarding small-scale streams such as agricultural canals. The aim of this study is to demonstrate the applicability of a coupled use of ML and a two-dimensional (2D) hydrodynamic model for assessing spatial habitat heterogeneity in small-scale agricultural canals in Japan. Using abundance data of Japanese medaka (Oryzias latipes), four ML methods, namely artificial neural networks (ANNs), classification and regression trees (CARTs), random forests (RF) and support vector machines (SVMs), were applied to develop habitat suitability models considering water depth and flow velocity. A 2D hydrodynamic model was developed based on field surveys in two types of agricultural canals, namely earthen and concrete-lined canals. Information entropy was used for assessing the spatial heterogeneity of instream habitat conditions. As a result, the hydrodynamic models could model instream habitat conditions in a reasonable accuracy. Despite the differences in accuracies in habitat modeling, the four ML methods illustrated similar habitat suitability information for Japanese medaka. The coupled ecohydraulics modeling approach could quantify habitat quality and its spatial heterogeneity, based on which the differences between the earthen and concrete-lined canals were quantitatively assessed. This study demonstrated the applicability of ML-based habitat suitability evaluation and a 2D hydrodynamic model for modeling the spatial distribution of habitat suitability and assessing its spatial heterogeneity. Further study, assessing the spatial heterogeneity in various types of flows including natural/artificial and small/large streams, can contribute to establish quantitative criteria for an ecologically sound habitat and improved ecofriendly construction works in small-scale rivers and streams.

元の言語英語
ページ(範囲)147-155
ページ数9
ジャーナルEcological Informatics
29
発行部数P2
DOI
出版物ステータス出版済み - 9 1 2015

Fingerprint

Spatial Heterogeneity
Hydrodynamic Model
Data-driven
hydrodynamics
Hydrodynamics
Canals
Machine Learning
Learning systems
habitat
habitats
Modeling
canals (waterways)
artificial intelligence
canal
Ecosystem
Oryzias latipes
Model
Classification and Regression Trees
modeling
Rivers

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics
  • Ecology
  • Modelling and Simulation
  • Ecological Modelling
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Applied Mathematics

これを引用

@article{8273022ee8ac4cb2a14dd023f56a1396,
title = "Assessment of spatial habitat heterogeneity by coupling data-driven habitat suitability models with a 2D hydrodynamic model in small-scale streams",
abstract = "Habitat assessment considering habitat quality and quantity is a key approach in conservation and restoration works for biodiversity and ecosystems. In this regard, application of hydrodynamic model for modeling instream habitat conditions and machine learning (ML) methods for modeling habitat suitability of a target species can contribute to better modeling practices in ecohydraulics. Despite the importance of small streams for aquatic ecosystems, previous studies in ecohydraulics have been conducted mainly in medium to large rivers, often disregarding small-scale streams such as agricultural canals. The aim of this study is to demonstrate the applicability of a coupled use of ML and a two-dimensional (2D) hydrodynamic model for assessing spatial habitat heterogeneity in small-scale agricultural canals in Japan. Using abundance data of Japanese medaka (Oryzias latipes), four ML methods, namely artificial neural networks (ANNs), classification and regression trees (CARTs), random forests (RF) and support vector machines (SVMs), were applied to develop habitat suitability models considering water depth and flow velocity. A 2D hydrodynamic model was developed based on field surveys in two types of agricultural canals, namely earthen and concrete-lined canals. Information entropy was used for assessing the spatial heterogeneity of instream habitat conditions. As a result, the hydrodynamic models could model instream habitat conditions in a reasonable accuracy. Despite the differences in accuracies in habitat modeling, the four ML methods illustrated similar habitat suitability information for Japanese medaka. The coupled ecohydraulics modeling approach could quantify habitat quality and its spatial heterogeneity, based on which the differences between the earthen and concrete-lined canals were quantitatively assessed. This study demonstrated the applicability of ML-based habitat suitability evaluation and a 2D hydrodynamic model for modeling the spatial distribution of habitat suitability and assessing its spatial heterogeneity. Further study, assessing the spatial heterogeneity in various types of flows including natural/artificial and small/large streams, can contribute to establish quantitative criteria for an ecologically sound habitat and improved ecofriendly construction works in small-scale rivers and streams.",
author = "Shinji Fukuda and Taichi Tanakura and Kazuaki Hiramatsu and Harada Masayoshi",
year = "2015",
month = "9",
day = "1",
doi = "10.1016/j.ecoinf.2014.10.003",
language = "English",
volume = "29",
pages = "147--155",
journal = "Ecological Informatics",
issn = "1574-9541",
publisher = "Elsevier",
number = "P2",

}

TY - JOUR

T1 - Assessment of spatial habitat heterogeneity by coupling data-driven habitat suitability models with a 2D hydrodynamic model in small-scale streams

AU - Fukuda, Shinji

AU - Tanakura, Taichi

AU - Hiramatsu, Kazuaki

AU - Masayoshi, Harada

PY - 2015/9/1

Y1 - 2015/9/1

N2 - Habitat assessment considering habitat quality and quantity is a key approach in conservation and restoration works for biodiversity and ecosystems. In this regard, application of hydrodynamic model for modeling instream habitat conditions and machine learning (ML) methods for modeling habitat suitability of a target species can contribute to better modeling practices in ecohydraulics. Despite the importance of small streams for aquatic ecosystems, previous studies in ecohydraulics have been conducted mainly in medium to large rivers, often disregarding small-scale streams such as agricultural canals. The aim of this study is to demonstrate the applicability of a coupled use of ML and a two-dimensional (2D) hydrodynamic model for assessing spatial habitat heterogeneity in small-scale agricultural canals in Japan. Using abundance data of Japanese medaka (Oryzias latipes), four ML methods, namely artificial neural networks (ANNs), classification and regression trees (CARTs), random forests (RF) and support vector machines (SVMs), were applied to develop habitat suitability models considering water depth and flow velocity. A 2D hydrodynamic model was developed based on field surveys in two types of agricultural canals, namely earthen and concrete-lined canals. Information entropy was used for assessing the spatial heterogeneity of instream habitat conditions. As a result, the hydrodynamic models could model instream habitat conditions in a reasonable accuracy. Despite the differences in accuracies in habitat modeling, the four ML methods illustrated similar habitat suitability information for Japanese medaka. The coupled ecohydraulics modeling approach could quantify habitat quality and its spatial heterogeneity, based on which the differences between the earthen and concrete-lined canals were quantitatively assessed. This study demonstrated the applicability of ML-based habitat suitability evaluation and a 2D hydrodynamic model for modeling the spatial distribution of habitat suitability and assessing its spatial heterogeneity. Further study, assessing the spatial heterogeneity in various types of flows including natural/artificial and small/large streams, can contribute to establish quantitative criteria for an ecologically sound habitat and improved ecofriendly construction works in small-scale rivers and streams.

AB - Habitat assessment considering habitat quality and quantity is a key approach in conservation and restoration works for biodiversity and ecosystems. In this regard, application of hydrodynamic model for modeling instream habitat conditions and machine learning (ML) methods for modeling habitat suitability of a target species can contribute to better modeling practices in ecohydraulics. Despite the importance of small streams for aquatic ecosystems, previous studies in ecohydraulics have been conducted mainly in medium to large rivers, often disregarding small-scale streams such as agricultural canals. The aim of this study is to demonstrate the applicability of a coupled use of ML and a two-dimensional (2D) hydrodynamic model for assessing spatial habitat heterogeneity in small-scale agricultural canals in Japan. Using abundance data of Japanese medaka (Oryzias latipes), four ML methods, namely artificial neural networks (ANNs), classification and regression trees (CARTs), random forests (RF) and support vector machines (SVMs), were applied to develop habitat suitability models considering water depth and flow velocity. A 2D hydrodynamic model was developed based on field surveys in two types of agricultural canals, namely earthen and concrete-lined canals. Information entropy was used for assessing the spatial heterogeneity of instream habitat conditions. As a result, the hydrodynamic models could model instream habitat conditions in a reasonable accuracy. Despite the differences in accuracies in habitat modeling, the four ML methods illustrated similar habitat suitability information for Japanese medaka. The coupled ecohydraulics modeling approach could quantify habitat quality and its spatial heterogeneity, based on which the differences between the earthen and concrete-lined canals were quantitatively assessed. This study demonstrated the applicability of ML-based habitat suitability evaluation and a 2D hydrodynamic model for modeling the spatial distribution of habitat suitability and assessing its spatial heterogeneity. Further study, assessing the spatial heterogeneity in various types of flows including natural/artificial and small/large streams, can contribute to establish quantitative criteria for an ecologically sound habitat and improved ecofriendly construction works in small-scale rivers and streams.

UR - http://www.scopus.com/inward/record.url?scp=84940791458&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84940791458&partnerID=8YFLogxK

U2 - 10.1016/j.ecoinf.2014.10.003

DO - 10.1016/j.ecoinf.2014.10.003

M3 - Article

VL - 29

SP - 147

EP - 155

JO - Ecological Informatics

JF - Ecological Informatics

SN - 1574-9541

IS - P2

ER -