Targeting in-stream habitat suitability with a multi-criteria mapping framework
多基準マッピングフレームワークによる河川内生息地の適合性評価 (AI 翻訳)
Corey Dawson, Gavin Scott, James Veres, L. C. Smith
🤖 gxceed AI 要約
日本語
本研究は、水理モデリング、地形分類、河畔林被覆評価を統合した多基準マッピングフレームワークを提案し、魚類の産卵に適した河川内生息地を特定する。ノバスコシア州のフォリー川でケーススタディを行い、高流量・低流量条件下での安定した産卵場所の選定手法を実証した。このフレームワークは、気候変動下での河川管理や生息地復元に応用可能である。
English
This study presents a multi-criteria mapping framework integrating hydraulic modeling, geomorphic classification, and riparian canopy cover to identify suitable in-stream habitat for fish spawning. Tested in Folly River, Nova Scotia, the framework identifies stable redd sites under high and low flow conditions, supporting climate-resilient river restoration and conservation planning.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本では河川改修やサケ・マスの産卵環境保全が重要課題であり、本フレームワークは気候変動に適応した河川管理計画の策定に示唆を与える。ただし、直接的な脱炭素やGX関連ではないため、応用には適切な文脈理解が必要。
In the global GX context
This framework offers a transferable approach for habitat assessment and restoration planning under changing climate conditions, relevant to global river management. It aligns with climate adaptation goals but does not directly address decarbonization or green transformation.
👥 読者別の含意
🔬研究者:Provides a replicable methodology for mapping habitat suitability that integrates multiple environmental layers and stress-testing under extreme flows.
🏢実務担当者:Useful for river restoration planners and fisheries managers seeking data-driven site selection for spawning habitat enhancement.
🏛政策担当者:Illustrates how climate-resilient river management can be operationalized through integrated modeling, informing adaptation policy.
📄 Abstract（原文）
Abstract Techniques for identifying stable, high-quality in-stream habitat are increasingly needed to support fish conservation and river restoration under changing flow and sediment regimes. This study presents a multi-criteria mapping framework that integrates hydraulic modelling, geomorphic form and unit classification, and riparian canopy cover assessment to identify suitable redd conditions for egg incubation planning. The framework was tested in the Folly River, Nova Scotia, using an inner Bay of Fundy Atlantic salmon egg incubation project as a case study. High flow and low flow hydraulic conditions were simulated in HEC-RAS to derive flow velocity and water depth layers, while the Geomorphic Form Variation approach and Geomorphic Unit Tool were used to map geomorphic complexity and unit assemblages. Riparian canopy cover derived from LiDAR-based canopy height models provided an additional habitat condition layer. These outputs were spatially overlaid using criteria associated with a stable incubation site to map alternative locations with suitable incubation conditions and wetted extents under low flow were then used to assess longitudinal connectivity. Extreme fluctuations in weather patterns pose additional challenges for selecting suitable egg incubation sites. Therefore, we stress-tested our suitable sites in BASEMENT software to evaluate morphodynamic stability under high flow. The framework identified targeted redd sites and provides a transferable approach for habitat assessment, restoration planning, and climate-resilient river management.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1088/2515-7620/ae85e3first seen 2026-07-08 05:05:29
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