Predicting habitat suitability for lotic fish: linking statistical hydraulic models with multivariate habitat use models

Lamouroux, Nicolas; Capra, Hervé; Pouilly, Marc

doi:10.1002/(sici)1099-1646(199801/02)14:1<1::aid-rrr472>3.0.co;2-d

Cited by 82 publications

(30 citation statements)

References 19 publications

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“…We used a statistical habitat model developed by Lamouroux, Capra & Pouilly (1998), adapted to the fourteen main species of the studied reaches (Table 1). several pool-riffle successions of a running water; Newbury & Gaboury, 1993).…”

Section: Methodsmentioning

confidence: 99%

“…The biological models developed by Lamouroux et al (1998) are multivariate preference models. These models predict the effect, at the reach scale, of fish preferences for hydraulics observed at the scale of small habitat units.…”

Section: Fish Communities and Hydraulics 277mentioning

confidence: 99%

“…These models predict the effect, at the reach scale, of fish preferences for hydraulics observed at the scale of small habitat units. To calibrate the preference models, habitat units were sampled (hydraulic measurements and electric fishing; Lamouroux et al, 1998) in three reaches in the Rho Ã ne river basin over 3 years (Table 2). To calibrate the preference models, habitat units were sampled (hydraulic measurements and electric fishing; Lamouroux et al, 1998) in three reaches in the Rho Ã ne river basin over 3 years (Table 2).…”

Section: Fish Communities and Hydraulics 277mentioning

confidence: 99%

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Predicting community characteristics from habitat conditions: fluvial fish and hydraulics

et al. 1999

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1. One current approach to the prediction of community characteristics is to use models of key local‐scale processes (e.g. niche dimensions) affecting individuals and to estimate the effects of these attributes over larger scales. We tested this approach, focusing on how the hydraulic habitat structures fluvial fish communities. 2. We used a recent statistical habitat model to predict fish community characteristics in eleven reaches in the Rhône river basin in France. Predictions were made ‘blindly’ since most reaches were not used to calibrate the model. The model reflects species preferences for local hydraulics. We made predictions of the fish community from the local hydraulic conditions found in the reaches under low flow conditions. The overall abundance and the relative abundance (both as indices) of fish species, specific size classes and species traits (i.e. reproductive, trophic, morphological and others) were predicted. We summarized our predictions of the relative abundance of species as two ‘community structure indices’ using Principal Component Analysis. 3. Our predictions from low‐flow hydraulics were compared with long‐term observations of fish communities. The relative abundance of species actually observed depended largely on zoogeographic factors within the Rhône basin which could not be predicted by the model. The model predicted 13% of the variance in the indices of relative abundance at the species level and 23% of this variance at the trait level for all zoogeographic regions combined. However, when focused on reaches within a geographic region, the model explained up to 47% of the same variance. Therefore, geographic regions act as ‘filters’ on the relative abundance of species, but hydraulics do affect fish communities within a given geographical context. 4. For the synthetic ‘community structure indices’, we obtained good predictions from hydraulics independently of the geographical context (variance explained up to 95%). These indices were linked to simple key hydraulic characteristics of river reaches (Froude and/or Reynolds number). The indices enabled interpretations of the links between hydraulics, geomorphology, discharge and community patterns. These links were consistent with existing knowledge of species and their traits. 5. In addition to the above validations, the habitat model partly explained the observed effects of impoundment on fish communities. 6. The present results show that stream hydraulics strongly impact fish community structure. Consequently, our findings confirm that community characteristics can be predicted using models of the local‐scale habitat requirements of the species forming the community.

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Section: Methodsmentioning

confidence: 99%

Section: Fish Communities and Hydraulics 277mentioning

confidence: 99%

Section: Fish Communities and Hydraulics 277mentioning

confidence: 99%

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Predicting community characteristics from habitat conditions: fluvial fish and hydraulics

et al. 1999

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“…So a new drag-measuring device was developed, designed to provide accurate and repeatable hydrodynamic data (i.e. dead drag), which could serve for the elaboration of reliable hydrodynamic models and could be integrated eventually into different methods of fish habitat modelling (Nestler et al, 1989;Lamouroux et al, 1998).…”

Section: Introductionmentioning

confidence: 99%

“…It could be very useful for understanding the relations between habitat use by fish and flow conditions, either in different species or during different phases of development in a single species. To be integrated into existing models that predict physical habitat use by fish (Nestler et al, 1989;Lamouroux et al, 1998), the collection of C d values should hereafter be carried out in a homogeneous, accurate and reliable way, three conditions respected by the drag-measuring device that was used here.…”

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Shifts in drag and swimming potential during grayling ontogenesis: relations with habitat use

Sagnes

Champagne

Morel

2000

Journal of Fish Biology

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The drag coefficient (C d ) of grayling Thymallus thymallus was dependent on body surface conditions and rigidity. At comparable flow conditions, C d values of a fish preserved in formalin (high body rigidity) were 15-30% lower than those obtained on a freshly-killed fish (medium rigidity); the presence of skin mucus on fish could reduce C d by 10%. The hydrodynamic potential of grayling increased during ontogenesis, because C d values decreased (except for yolk sac larvae, which had a particular morphology) and the swimming capacities (in terms of relative muscular mass) increased. Grayling morphology evolves towards hydrodynamically efficient shape at high velocities, and there is a relationship between these shifts in hydrodynamic abilities and the different habitats (in terms of current velocity) used by five morphological groups. Therefore, the concept of hydrodynamic potential (i.e. hydrodynamics of shape and swimming capacities) could be a useful tool in fish ecomorphology and predictions of habitat use. 2000 The Fisheries Society of the British Isles

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Sampling variability in estimates of flow characteristics in coarse‐bed channels: Effects of sample size

Cienciala

Hassan

2016

Water Resources Research

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Adequate description of hydraulic variables based on a sample of field measurements is challenging in coarse‐bed streams, a consequence of high spatial heterogeneity in flow properties that arises due to the complexity of channel boundary. By applying a resampling procedure based on bootstrapping to an extensive field data set, we have estimated sampling variability and its relationship with sample size in relation to two common methods of representing flow characteristics, spatially averaged velocity profiles and fitted probability distributions. The coefficient of variation in bed shear stress and roughness length estimated from spatially averaged velocity profiles and in shape and scale parameters of gamma distribution fitted to local values of bed shear stress, velocity, and depth was high, reaching 15–20% of the parameter value even at the sample size of 100 (sampling density 1 m−2). We illustrated implications of these findings with two examples. First, sensitivity analysis of a 2‐D hydrodynamic model to changes in roughness length parameter showed that the sampling variability range observed in our resampling procedure resulted in substantially different frequency distributions and spatial patterns of modeled hydraulic variables. Second, using a bedload formula, we showed that propagation of uncertainty in the parameters of a gamma distribution used to model bed shear stress led to the coefficient of variation in predicted transport rates exceeding 50%. Overall, our findings underscore the importance of reporting the precision of estimated hydraulic parameters. When such estimates serve as input into models, uncertainty propagation should be explicitly accounted for by running ensemble simulations.

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Predicting habitat suitability for lotic fish: linking statistical hydraulic models with multivariate habitat use models

Cited by 82 publications

References 19 publications

Predicting community characteristics from habitat conditions: fluvial fish and hydraulics

Predicting community characteristics from habitat conditions: fluvial fish and hydraulics

Shifts in drag and swimming potential during grayling ontogenesis: relations with habitat use

Sampling variability in estimates of flow characteristics in coarse‐bed channels: Effects of sample size

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