Ecological Indicators · 2022 · 24 citations · 26 references
Life SciencesEcologyEnvironmental SciencesFish BiologyFish EcologyFreshwater EcologyFreshwater Fish EcologyRiver EcologyEcological SuitabilityHabitat Quality ModelingHydrological EcologyRiver Fish EcologyRiver Habitat EcologyRiverine EcosystemsRiverine Fish Ecology
Fishes are at the top of the aquatic food chain, are the best indicators of the health status of aquatic ecosystems and are the organisms most sensitive to changes in the aquatic ecological environment. Given the shortcomings of the commonly used river physical habitat models that only consider hydraulic factors, a two-dimensional (2D) eco-hydrodynamic model, containing eco-hydrological elements, was constructed using the identified driving forces of the ecological evolution of rivers. The main hydrological elements are water depth and flow velocity, while the main ecological elements are NH3-N, chemical oxygen demand, and sediments. Based on field survey data, relevant studies, and a comprehensive analysis of the natural geographical characteristics of the Luanhe River Basin, the dominant fish and plant species in the study area (the river section from the Daheiting-Taolinkou Reservoir to Luanxian Hydrological Station) were determined to be Cypriniformes and reed, respectively. The habitat suitability indices (HSIs) of various target species were determined using the model simulation method and the observational statistical method, and the river habitat quality model was constructed based on the 2D eco-hydrodynamic model. The spatial distribution and dynamic change process of the habitat quality of carp in the Qianxi section downstream of the Daheiting Reservoir and reed in the Qianxi section of the Luanhe River were obtained by calculation. Comparison with existing studies and ecological monitoring data shows that the model proposed in this paper is reliable and effective, which will help with the development of ecological protection and management efforts for rivers with not enough ecological monitoring data.
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Alban Kuriqi, António N. Pinheiro, Álvaro Sordo‐Ward et al. · Renewable and Sustainable Energy Reviews · 2021 · 537 citations
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