Interactive effects of cover and hydraulics on brown trout habitat selection patterns

Ayllón, Daniel; Almodóvar, Ana; Nicola, Graciela G.; Elvira, Benigno

doi:10.1002/rra.1215

Cited by 68 publications

(64 citation statements)

References 109 publications

(42 reference statements)

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“…The highest number of entries occurred in the shear layers between the inflowing and outflowing water, where the most frequent velocities ranged between 0 and 0.2 m/s, reaching values up to 0.3 m/s. The distribution of the preferred velocities for the entry of the fish into the refuge corresponded to the distribution that has been observed for juvenile brown trout in rivers (Souchon et al 1989;Vismara et al 2001;Ayllón et al 2009). …”

Section: Location Of Fish Entries Into the Refugesupporting

confidence: 66%

Attractiveness of a lateral shelter in a channel as a refuge for juvenile brown trout during hydropeaking

et al. 2014

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Peak power production in hydroelectric storage power plants results in frequent and intense flow variations in the rivers downstream of the plants. Fish populations can be negatively impacted when subjected to these so-called hydropeaking phenomena. In researching mitigation solutions, shelters in the riverbanks of channelized rivers have been identified as a means of protecting fish from excessive flow velocities. These shelters were studied systematically using juvenile brown trout (Salmo trutta fario) in an experimental configuration in which a straight channel was equipped with a lateral embayment. The purpose of the experiments was to generate hydrodynamic hydropeaking conditions in the channel that are undesirable for juvenile trout, thereby causing them to enter the shelter. The flow velocity distribution in the intersection plane between the main channel and the lateral shelter was found to be a significant parameter for attracting fish to the shelter. The utilization rate of trout in the shelter was used as a performance indicator. Using a basic rectangular shelter configuration without forced water exchange between the shelter and the channel, the utilization rate was only 35 %. This rate was more than doubled by introducing a deviation groyne to force water exchange between the channel and the shelter. The position and orientation angle of this groyne were systematically varied to maximize the utilization rate. Maximum utilization rates approaching 90 % were obtained for an optimum configuration in which an island-type groyne was placed in the shelter. The results of the systematic channel tests showed the potential of the shelter to attract fish. Such a shelter could be used in channelized rivers both for morphological revitalization and to improve fish habitats. As a next step in this research, prototype shelters will be built on a natural river and monitored for 2-3 years under a hydropeaking flow regime.

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Section: Location Of Fish Entries Into the Refugesupporting

confidence: 66%

Attractiveness of a lateral shelter in a channel as a refuge for juvenile brown trout during hydropeaking

et al. 2014

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“…Studies in different regions that also develop bivariate and multivariate models approve the controlling role of depth as a hydraulic variable (Ayllon, Almodovar, Nicola, & Elvira, 2009;Vismara, Azzellino, Bosi, Crosa, & Gentili, 2001). Munoz-Mas et al (2016) study results on Salmo farioides showed that the large fish prefer low velocity and deep parts.…”

Section: Discussionmentioning

confidence: 99%

Untitled

Rezaei¹,

Şengül²

2019

Turk. J. Fish. Aquat. Sci.

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Generalized Additive Models (GAMs) are widely used statistical models for species distribution in habitat and environmental management modeling as they enable incorporation of non-linearity. The objective of this study is to develop relationships between habitat variables, fish absence/presence (logistic GAM) and abundance (Poisson GAM) for the S. rizeensis using onsite observations in Solaklı River. Logistic GAMs correctly predicted absence/presence of adult and juvenile S. rizeensis at 79.3% and 74% of sampling areas respectively. Response curves of logistic GAMs results show differences in probability of finding the adult and juvenile fish. Adult S. rizeensis were mostly found in higher velocities (0.5-0.8 m/s) than in juvenile fish (≈ 0 m/s). Also, the highest number of adult fish were recorded in deeper habitats (≈ 0.4 m) rather than in juvenile fish (≈ 0 m). Curves show adult fish are more independent to the presence of cover compared to juvenile fish. Velocity shelter and bedrock formation were the most common cover types. Chi-square test results of predicted values showed that developed Poisson GAMs of adult and juvenile S. rizeensis could not accurately represent fish abundance. The results show that while logistic GAM is applicable, Poisson GAM model is not applicable for the area.

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“…Accordingly, the ensemble model has potential to improve upon the predictive performance of all single-model SDMs [22,53]. Schweizer et al (2007) and Ayllón et al (2009) emphasized the mutual dependency between flow velocity and depth [7,9]. In this study, HSI was obtained using six species distribution models, which only considered V and D throughout simulations.…”

Section: Sdm-determined Suitability Of Habitat With Respect To Spatiamentioning

confidence: 99%

“…Mesohabitats and stream biota have been shown to be associated with distinct combinations of current velocity and water depth [7]. Some studies have elucidated the correlation between current velocity and depth [7,8], as well as their combined effects in ecological modeling and assessment [9]. Additionally, these two variables are used in species distribution models (SDMs) to estimate HSI values for fish species.…”

Section: Introductionmentioning

confidence: 99%

Uncertainty in Various Habitat Suitability Models and Its Impact on Habitat Suitability Estimates for Fish

Lin

2015

Water

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Species distribution models (SDMs) are extensively used to project habitat suitability of species in stream ecological studies. Owing to complex sources of uncertainty, such models may yield projections with varying degrees of uncertainty. To better understand projected spatial distributions and the variability between habitat suitability projections, this study uses five SDMs that are based on the outputs of a two-dimensional hydraulic model to project the suitability of habitats and to evaluate the degree of variability originating from both differing model types and the split-sample procedure. The habitat suitability index (HSI) of each species is based on two stream flow variables, including current velocity (V), water depth (D), as well as the heterogeneity of these flow conditions as quantified by the information entropy of V and D. The six SDM approaches used to project fish abundance, as represented by HSI, included two stochastic models: the generalized linear model (GLM) and the generalized additive model (GAM); as well as three machine learning models: the support vector machine (SVM), random forest (RF) and the artificial neural network (ANN), and an ensemble model (where the latter is the average of the preceding five models). The target species Sicyopterus japonicas was found to prefer habitats with high current velocities. The relationship between mesohabitat diversity and fish abundance was indicated by the trends in information entropy and weighted usable area (WUA) over the study area. This study proposes a method for quantifying habitat suitability, and for assessing the uncertainties in HSI and WUA that are OPEN ACCESSWater 2015, 7 4089 introduced by the various SDMs and samples. This study also demonstrated both the merits of the ensemble modeling approach and the necessity of addressing model uncertainty.

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Interactive effects of cover and hydraulics on brown trout habitat selection patterns

Cited by 68 publications

References 109 publications

Attractiveness of a lateral shelter in a channel as a refuge for juvenile brown trout during hydropeaking

Attractiveness of a lateral shelter in a channel as a refuge for juvenile brown trout during hydropeaking

Untitled

Uncertainty in Various Habitat Suitability Models and Its Impact on Habitat Suitability Estimates for Fish

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