PHABSIM modelling of Atlantic salmon spawning habitat in an upland stream: testing the influence of habitat suitability indices on model output

Moir, H. J.; Gibbins, Christopher; Soulsby, Chris; Youngson, A. F.

doi:10.1002/rra.869

Cited by 89 publications

(60 citation statements)

References 47 publications

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“…Founded on the habitat concepts of PHABSIM and River2D [17][18][19]39], the WUA and the OSI for the fish species under a given hydraulic condition were also computed [8,40,41]. The WUA is defined as follows:…”

Section: Wua and Osi Construction Proceduresmentioning

confidence: 99%

Simulating Spawning and Juvenile Rainbow Trout (Oncorhynchus mykiss) Habitat in Colorado River Based on High-Flow Effects

Yao

Liu

Chen

et al. 2017

Water

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High flow generates significant alterations in downstream river reaches, resulting in physical condition changes in the downstream regions of the river such as water depth, flow velocity, water temperature and river bed. These alterations will lead to change in fish habitat configuration in the river. This paper proposes a model system to evaluate the high flow effects on river velocity, water depth, substrates changes, temperature distribution and consequently assess the change in spawning and juvenile rainbow trout (Oncorhynchus mykiss) habitats in the downstream region of the Glen Canyon Dam. Firstly, based on the 2 dimensional (2D) depth-averaged CFD (Computational Fluid Dynamics) model and heat transfer equation applied for simulation, three indices were simulated, namely depth, flow velocity and temperature distribution. Then, the spawning and juvenile fish preference curves were obtained based on these three indices and substrates distribution. After that, the habitat model was proposed and used to simulate the high flow effects on juvenile and spawning rainbow trout habitat structure. Finally, the weighted usable area (WUA) and overall suitability index (OSI) of the spawning and juvenile fish species were quantitatively simulated to estimate the habitat sensitivity. The results illustrate that the high flow effect (HFE) increased the juvenile rainbow trout habitat quality but decreased the spawning rainbow trout habitat quality. The juvenile trout were mainly affected by the water depth while the spawning rainbow trout were dominated by the bed elevation.

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Section: Wua and Osi Construction Proceduresmentioning

confidence: 99%

Simulating Spawning and Juvenile Rainbow Trout (Oncorhynchus mykiss) Habitat in Colorado River Based on High-Flow Effects

Yao

Liu

Chen

et al. 2017

Water

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“…More individuals of target species (MESC -Midcontinent Ecological Sciences Center recommend at least 100 pieces) in a same life stage need to be collected for determination of the HSI [4]. PHABSIM was validated and used as a model for habitat requirements (spawning requirements) of Salmonid Fish [21,22], it was used for estimation of fresh-water fish habitat [23] and estimation of water fisheries resources in England and Wales [24]. For this study was PHABSIM chosen for its ability to investigate habitat availability for macrozoobenthos, observe target life form, in a range of flows, different substrate and water depth.…”

Section: Physical Habitat Simulation System (Phabsim)mentioning

confidence: 99%

Determination of Ecological Flow for Macroinvertebrate Communities in Streams Affected by Urban Drainage – Case Study of Prague

Caletkova¹,

Klímová²,

Komínková³

2012

TOEBMJ

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This article is focused on definition and identification of optimal ecological flow for macrozoobenthos communities in small urban creeks affected by urban drainage using the Physical HABitat Simulation (PHABSIM) system. It describes the process of determination of ecological flows, from field measurement to determined values. Results show that combine sewer overflows and storm water drains negatively affect urban creeks and theirs diversity. In the end it compares determined ecological flows with measured and given values. Results show that minimum ecological flows are not reached in one third of a year and determined optimal flows are not abided.

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“…This is because most habitat simulation models are heavily dependent on the monitoring data [15][16][17][18][19]. However, a significant portion of previous physical habitat simulations have used monitoring data from neighboring streams due to the lack of sufficient data.…”

Section: Introductionmentioning

confidence: 99%

“…However, only about 15% of these studies used data obtained for the actual stream being studied [20,21]. The situation is not much better in the US [18,[22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

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Transferability of Monitoring Data from Neighboring Streams in a Physical Habitat Simulation

Choi

Kang

2015

Water

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Abstract:Habitat simulation models heavily rely on monitoring data, which can have serious effects on the success of a physical habitat simulation. However, if data monitored in a study reach are not available or insufficient, then data from neighboring streams are commonly used. The problem is that the impact of using data from neighboring streams has rarely been studied before. Motivated by this, we report herein on an investigation of the transferability of data from neighboring streams in a physical habitat simulation. The study area is a 2.5 km long reach located downstream from a dam in the Dal River, Korea. Zacco platypus was selected as the target fish for the physical habitat simulation. Monitoring data for the Dal River and three neighboring streams were obtained. First, similarities in the data related to channel geometry and in the observed distribution of the target species were examined. Principal Component Analysis (PCA) was also carried out to see the characteristics of the habitat use of the target species. Habitat Suitability Curves (HSCs) were constructed using the Gene Expression Programming (GEP) model, and improved Generalized Habitat Suitability Curves (GHSCs) were proposed. The physical habitat simulations were then performed. The Composite Suitability Index (CSI) distributions were predicted, and the impact of using data from the neighboring streams was investigated. The results indicated that the use of data from a neighboring stream even in the same watershed can result in large errors in the prediction of CSI. The physical habitat simulation with the improved GHSCs was found to best predict the CSI. OPEN ACCESSWater 2015, 7 4538

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PHABSIM modelling of Atlantic salmon spawning habitat in an upland stream: testing the influence of habitat suitability indices on model output

Cited by 89 publications

References 47 publications

Simulating Spawning and Juvenile Rainbow Trout (Oncorhynchus mykiss) Habitat in Colorado River Based on High-Flow Effects

Simulating Spawning and Juvenile Rainbow Trout (Oncorhynchus mykiss) Habitat in Colorado River Based on High-Flow Effects

Determination of Ecological Flow for Macroinvertebrate Communities in Streams Affected by Urban Drainage – Case Study of Prague

Transferability of Monitoring Data from Neighboring Streams in a Physical Habitat Simulation

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