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Importance of Flow Metrics on Modeling Macroinvertebrate Community in Dammed Rivers: An Approach With Optimized Gradient Boosting
http://hdl.handle.net/10458/0002001896
http://hdl.handle.net/10458/00020018960725e61f-e38f-48de-ae34-66083c742ae6
| 名前 / ファイル | ライセンス | アクション |
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fulltext (3 MB)
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| アイテムタイプ | 学術雑誌論文 / Journal Article(1) | |||||||||||||||
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| 公開日 | 2025-11-05 | |||||||||||||||
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| タイトル | Importance of Flow Metrics on Modeling Macroinvertebrate Community in Dammed Rivers: An Approach With Optimized Gradient Boosting | |||||||||||||||
| 言語 | en | |||||||||||||||
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| 言語 | eng | |||||||||||||||
| キーワード | ||||||||||||||||
| 言語 | en | |||||||||||||||
| キーワード | LightGBM | |||||||||||||||
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| 言語 | en | |||||||||||||||
| キーワード | XGBoost | |||||||||||||||
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| 言語 | en | |||||||||||||||
| キーワード | ecological niche modeling | |||||||||||||||
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| 言語 | en | |||||||||||||||
| キーワード | hydrological simulation | |||||||||||||||
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| 言語 | en | |||||||||||||||
| キーワード | indicators of hydrologic alteration | |||||||||||||||
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| 言語 | en | |||||||||||||||
| キーワード | random forest algorithm | |||||||||||||||
| 資源タイプ | ||||||||||||||||
| 資源タイプ | journal article | |||||||||||||||
| アクセス権 | ||||||||||||||||
| アクセス権 | open access | |||||||||||||||
| 著者 |
糠澤, 桂
× 糠澤, 桂
WEKO
33774
× Tanaka, Ryo
× Mineda, Haruki
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| 内容記述タイプ | Abstract | |||||||||||||||
| 内容記述 | Habitat models that can predict the habitat suitability for riverine organisms and their distribution along environmental gradients are helpful in watershed environmental management. However, the impacts of dams on riverine communities and their habitats have not yet been considered in such models, although dams have considerably altered important riverine habitats. In this study, we aim to develop catchment-scale habitat models of macroinvertebrate communities with predictor variables characterizing the impacts of dams. We studied the Omaru River catchment in southwest Japan, where the river flow has been altered considerably because of multiple hydropower dams. Multiple machine learning techniques, such as XGBoost and LightGBM were used to model the habitat distributions of 170 macroinvertebrate taxa observed throughout the river catchment. We used predictor variables of dam impacts derived based on geographical information system data (hereafter, dam metrics) and physically simulated flow data using a hydrological model. Among the modeling techniques, gradient boosting algorithms (XGBoost and LightGBM) with optimized tree number parameters exhibited the highest mean accuracy among the analyzed taxa, followed by the random forest algorithm. The accuracy of the habitat models for the macroinvertebrate community and habitat groups considerably improved with the integration of dam metrics and flow predictors. Of the habit groups considered, clingers showed a keen response to low-flow metrics, presumably owing to flow alteration caused by the studied dams, as the downstream sections of these dams received only residual flow. Our findings indicate that (1) variables of dam impacts greatly improve the predictive capability of macroinvertebrates and (2) gradient boosting machines with optimized parameters are favorable for habitat modeling of the biotic community. Our models are helpful when river practitioners implement conservation measures as they better understand the environmental consequences of their flood prot | |||||||||||||||
| 言語 | en | |||||||||||||||
| 書誌情報 |
en : Ecology and evolution 巻 15, 号 10, p. e72411, 発行日 2025-10 |
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| 出版者 | ||||||||||||||||
| 出版者 | British Ecological Society | |||||||||||||||
| 言語 | en | |||||||||||||||
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| 出版者 | John Wiley & Sons Ltd | |||||||||||||||
| 言語 | en | |||||||||||||||
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| 収録物識別子タイプ | PISSN | |||||||||||||||
| 収録物識別子 | 20457758 | |||||||||||||||
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| 関連タイプ | isVersionOf | |||||||||||||||
| 識別子タイプ | DOI | |||||||||||||||
| 関連識別子 | https://doi.org/10.1002/ece3.72411 | |||||||||||||||
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| 出版タイプ | VoR | |||||||||||||||
| リンク |
Supplementary Tables S1 and S2
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