Habitat Use and Selection by Brown Trout in Streams

Heggenes, Jan; Wollebæk, Jens

doi:10.1002/9781118526576.ch9

Cited by 6 publications

(8 citation statements)

References 160 publications

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“…Indeed, the dominant species found in the Oir (in average, 35% of the fish captured in the Oir are Salmonids, ORE PFC data): the Atlantic salmon, Salmo salar and the brown trout, Salmo trutta cooccur with eels (Bardonnet & Baglini ere 2000;Laffaille et al 2003;Heggenes & Wollebaek 2013) and feed on the same type of preys (macro-invertebrate and small fishes) (Maitland 1965;Stradmeyer & Thorpe 1987;Bridcut & Giller 1995;Vignes 1995). Indeed, the dominant species found in the Oir (in average, 35% of the fish captured in the Oir are Salmonids, ORE PFC data): the Atlantic salmon, Salmo salar and the brown trout, Salmo trutta cooccur with eels (Bardonnet & Baglini ere 2000;Laffaille et al 2003;Heggenes & Wollebaek 2013) and feed on the same type of preys (macro-invertebrate and small fishes) (Maitland 1965;Stradmeyer & Thorpe 1987;Bridcut & Giller 1995;Vignes 1995).…”

Section: Discussionmentioning

confidence: 99%

“…Another hypothesis comes from the potential interspecific interaction occurring in the Oir and not in the Fr emur. Indeed, the dominant species found in the Oir (in average, 35% of the fish captured in the Oir are Salmonids, ORE PFC data): the Atlantic salmon, Salmo salar and the brown trout, Salmo trutta cooccur with eels (Bardonnet & Baglini ere 2000;Laffaille et al 2003;Heggenes & Wollebaek 2013) and feed on the same type of preys (macro-invertebrate and small fishes) (Maitland 1965;Stradmeyer & Thorpe 1987;Bridcut & Giller 1995;Vignes 1995). Whatever the process of interspecific competition (predation, exclusion, segregation, etc.…”

Section: Discussionmentioning

confidence: 99%

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Difference in factors explaining growth rate variability inEuropean eel subpopulations: the possible role of habitat carrying capacity

Boulenger

Crivellì

Charrier³

et al. 2014

Ecology of Freshwater Fish

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As a key parameter in the management of fish populations, individual growth rate (GR) variations were examined in the European eel (Anguilla anguilla; > 150 mm) using extensive mark-recapture surveys in the lotic habitats of two small rivers of western France: the Fr emur, supposed to be saturated, and at the same latitude, the Oir with densities fivefold lower than those of the Fr emur. In both systems, generalised linear models were used to test whether spatiotemporal factors such as dominant habitat type or local density affect GR variability. In the presumed unsaturated system, the Oir, GR variability is mainly explained by a set of habitat suitability drivers (density, dominant habitat type). In the Fr emur, GRs appear independent of differences in habitat density or productivity. Below saturation, an increase in density will decrease the GR through intraspecific competition. At saturation, intraspecific competition reaches such high levels that regardless of eel density and productivity, the resources available by individual are similar throughout the system. In these circumstances, the effect of density on growth was presumed undetectable. Despite these contrasted results, mean GRs observed in both catchments were closed (~20 mmÁyear À1 ). This is an unexpected result as GR is expected to be higher in unsaturated systems. This similarity could be explained by the difference between the two systems in terms of: (i) sex ratio (the Fr emur is dominated by male, whereas the female is dominant in the Oir), (ii) habitat type distribution or (iii) possible interspecific competition (important salmonid populations in the Oir).

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Difference in factors explaining growth rate variability inEuropean eel subpopulations: the possible role of habitat carrying capacity

Boulenger

Crivellì

Charrier³

et al. 2014

Ecology of Freshwater Fish

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“…The premise underlying hydraulic‐habitat models is that biotic communities in rivers are limited by hydraulic‐habitat availability. Thus, these models simulate spatial and temporal variability in physical habitat characteristics, such as depth, velocity and substrate composition, which in turn are used to predict taxonomic occurrence and abundance (Ahmadi‐Nedushan et al, ; Heggenes & Wollebaek, ). The most commonly used hydraulic‐habitat models, such as PHABSIM (Bovee, ) and CASiMiR (Jorde, Chneider, Peter, & Zöllner, ), work at the microhabitat scale, referring to a single point (or river element) that is evaluated to determine its suitability as hydraulic habitat.…”

Section: Methodological Approaches To Design Eflows In Temporary Watementioning

confidence: 99%

Accounting for flow intermittency in environmental flows design

Acuña

Jordà-Capdevila

Vezza

et al. 2020

Journal of Applied Ecology

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River ecosystems world‐wide are affected by altered flow regimes, and advanced science and practice of environmental flows have been developed to understand and reduce these impacts. But most environmental flows approaches ignore flow intermittency, which is a natural feature of 30% of the global river network length. Ignoring flow intermittency when setting environmental flows in naturally intermittent rivers might lead to deleterious ecological effects. We review evidence of the ecological effects of flow intermittency and provide guidance to incorporate intermittency (non‐flow events) into existing methods judged as suitable for application in temporary waterways. To better integrate non‐flow events into hydrological methods, we propose a suite of new indicators to be used in the range of variability approach. These indicators reflect dry periods and the unpredictable nature of temporary waterways. We develop a predictability index for protecting those species adapted to temporary conditions. For hydraulic‐habitat models, we find that mesohabitat methods are particularly effective for describing complex habitat dynamics during dry phases. We present an example of the European eel to show the relationship between discharge and non‐flow days and wet area, habitat suitability and connectivity. We find that existing holistic approaches may be applied to temporary waterways without significant structural alteration to their stepwise frameworks, but new component methods are needed to address flow‐related aspects across both flow and non‐flow periods of the flow regime. Synthesis and applications. Setting environmental flow requirements for temporary waterways requires modification and enhancement of existing approaches and methodologies, most notably the explicit consideration of non‐flow events and greater integration of specific geomorphic, hydrogeologic and hydraulic elements. Temporary waterways are among the freshwater ecosystems most vulnerable to alterations in flow regimes, and they are also under great pressure. The methodological modifications recommended in this paper will aid water managers in protecting key components of temporary flow regimes, thereby preserving their unique ecology and associated services.

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“…In addition to temperature, the hydraulic habitat is key for determining the capacity of the environment to support viable trout populations (Heggenes & Wollebæk, 2013). Hydraulic habitat availability is directly related to streamflow and channel morphology; thus, the physical habitats (nonthermal) of fish can be characterised by one set of hydraulic (water velocity and depth) and related structural features (substrate and plant cover) based on both, their species‐specific and life stage ecological niches (e.g., Papadaki et al, 2016; Raleigh, Zuckerman, & Nelson, 1986; Vismara, Azzellino, Bosi, Crosa, & Gentili, 2001).…”

Section: Introductionmentioning

confidence: 99%

Effects of climate change on the life stages of stream‐dwelling brown trout (Salmo trutta Linnaeus, 1758) at the rear edge of their native distribution range

et al. 2020

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Streamflow and temperature regimes are key components of the physical habitats of instream biological communities. Iberian brown trout (Salmo trutta) populations exist in a climatic border where water scarcity and increasing water temperatures during summer could compromise their viability throughout the 21st century. We predicted climate change-induced modifications in the thermal and hydraulic habitats of both the intragravel (eggs and larvae) and free-swimming (fry, juveniles and adults) stages of brown trout in two mountain streams in central Spain. Spatial-temporal simulations of thermal and hydraulic habitats under two climate change emission scenarios-representative concentration pathway (RCP) 4.5 (mild scenario) and RCP 8.5 (pessimistic)-were conducted at 1-m altitudinal steps using daily air temperature and streamflow predictions. Increased winter temperatures will reduce embryo and larval development time by 12% (RCP 4.5) and 30% (RCP 8.5) in downstream sites by end of the 21st century, but this reduction might be insufficient to compensate for the shortening of the period with temperatures below the viability limits for survival of intragravel phase (20% and 54%, respectively). Combining streamflow and temperature data for free-swimming stages indicated that the suitable summer habitat will be reduced by between 53% and 76% (RCP 4.5) and 70%-90% (RCP 8.5) by 2099. The predicted effects for all developmental stages are critical for determining population viability at both ends of its altitudinal distribution. However, these responses are river-specific, as limiting factors differ among rivers.

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Habitat Use and Selection by Brown Trout in Streams

Cited by 6 publications

References 160 publications

Difference in factors explaining growth rate variability inEuropean eel subpopulations: the possible role of habitat carrying capacity

Difference in factors explaining growth rate variability inEuropean eel subpopulations: the possible role of habitat carrying capacity

Accounting for flow intermittency in environmental flows design

Effects of climate change on the life stages of stream‐dwelling brown trout (Salmo trutta Linnaeus, 1758) at the rear edge of their native distribution range

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