Movements and dispersal of brown trout (<i>Salmo trutta</i> Linnaeus, 1758) in Mediterranean streams: influence of habitat and biotic factors

Aparicio, Enric; Rocaspana, Rafel; Sostoa, Adolfo de; Palau-Ibars, Antoni; Alcaraz, Carles

doi:10.7717/peerj.5730

Cited by 14 publications

(7 citation statements)

References 65 publications

(86 reference statements)

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“…These contrasting results on home range size between reaches might be due to differences in availability of complementary habitats necessary to complete their life cycle (Fausch, Torgersen, Baxter, & Li, ). In concordance with that, movement pattern in the bypassed reach was similar to brown trout populations from unregulated Mediterranean streams, characterized by restricted home range size due to the close availability of suitable habitats for shelter, feeding, and spawning (Aparicio, Rocaspana, de Sostoa, Palau, & Alcaraz, ). However, repeated flow pulses change substrate composition and distribution by altering the erosion and sedimentation patterns (Vericat, Batalla, & Gibbins, ), thus reducing the heterogeneity of the river bed and causing shifts in key habitats for fish, such as gravel beds reduction and changes in channel morphology (Gibbins et al, ; Vericat, Batalla, & Garcia, ).…”

Section: Discussionsupporting

confidence: 77%

Hydropeaking effects on movement patterns of brown trout (Salmo trutta L.)

Rocaspana

Aparicio

Palau-Ibars

et al. 2019

River Research & Apps

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Radiotelemetry was used to investigate seasonal movement and home range of brown trout Salmo trutta (size range 188-420 mm fork length, N = 30) in two reaches of the Noguera Pallaresa River (Ebro Basin, north-east Spain) subjected to different flow regulation schemes. NP-1 reach is a bypassed section with near natural flow conditions, whereas the downstream reach NP-2 is subjected to daily pulsed flow discharge (i.e., hydropeaking) from an upstream hydropower station. Significant differences in home range size (95% kernel estimates) and seasonal movement pattern between study reaches were found. Mean home range size was (μ ± SE) 112.1 ± 11.5 m in the bypassed reach NP-1 and increased significantly in the hydropeaking reach NP-2 up to 237.9 ± 37.2 m. There was a large individual variability in fish home range size within reaches. Most of the seasonal differences in fish movement among reaches were associated with the spawning season. Pulsed discharge events in NP-2 during daytime in summer (lasting about 3 hr and increasing water flow from 1 to 20 m 3 /s) did not cause significant displacements in either upstream or downstream direction during the duration of the event. Our results highlight the importance of habitat connectivity in hydropeaking streams due to the need of brown trout to move large distances among complementary habitats, necessary to complete their life cycle, compared with unregulated or more stable streams.

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Section: Discussionsupporting

confidence: 77%

Hydropeaking effects on movement patterns of brown trout (Salmo trutta L.)

Rocaspana

Aparicio

Palau-Ibars

et al. 2019

River Research & Apps

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“…The dispersalRate() function uses dispersal rate data provided by the user and applies exponential distributions to model the probability of dispersal as a function of distance per unit time. Although each species is likely to have a unique probability distribution, exponential distributions are commonly used to model dispersal across taxa, including the possibility of rare, distant dispersal events (Sutherland et al 2000, Truvé and Lemel 2003, Nathan et al 2012, Aparicio et al 2018). This dispersal probability is then applied to the continuous habitat suitability maps, based on the distance away from the modelled binary species distribution at the first time‐step.…”

Section: Model Flow and Examplementioning

confidence: 99%

megaSDM: integrating dispersal and time‐step analyses into species distribution models

Shipley

Bach

et al. 2021

Ecography

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Understanding how species ranges shift as climates rapidly change informs us how to effectively conserve vulnerable species. Species distribution models (SDMs) are an important method for examining these range shifts. The tools for performing SDMs are ever improving. Here, we present the megaSDM R package. This package facilitates realistic spatiotemporal SDM analyses by incorporating dispersal probabilities, creating time‐step maps of range change dynamics and efficiently handling large datasets and computationally intensive environmental subsampling techniques. Provided a list of species and environmental data, megaSDM synthesizes GIS processing, subsampling methods, MaxEnt modelling, dispersal rate restrictions and additional statistical tools to create a variety of outputs for each species, time period and climate scenario requested. For each of these, megaSDM generates a series of distribution maps and outputs visual representations of statistical data. megaSDM offers several advantages over other commonly used SDM tools. First, many of the functions in megaSDM natively implement parallelization, enabling the package to handle large amounts of data efficiently without the need for additional coding. megaSDM also implements environmental subsampling of occurrences, making the technique broadly available in a way that was not possible before due to computational considerations. Uniquely, megaSDM generates maps showing the expansion and contraction of a species range across all considered time periods (time‐maps), and constrains both presence/absence and continuous suitability maps of species ranges according to species‐specific dispersal constraints. The user can then directly compare non‐dispersal and dispersal‐limited distribution predictions. This paper discusses the unique features and highlights of megaSDM, describes the structure of the package and demonstrates the package's features and the model flow through examples.

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“…In relation to dispersal, salmonid populations are composed of both stationary and mobile individuals (e.g. Bridcut & Giller, 1993), the former being the predominant proportion (Aparicio, Rocaspana, De Sostoa, Palau-Ibars, & Alcaraz, 2018) and the latter less abundant (Young, Wilkinson, Hay, & Hayes, 2010), or even a very reduced proportion (i.e. <5%; Rocaspana, Jové, Manau, & Palau, 2013).…”

Section: Model Calibrationmentioning

confidence: 99%

Effects of altered river network connectivity on the distribution of Salmo trutta: Insights from a metapopulation model

et al. 2019

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Network connectivity is a key feature of rivers that affects patterns and processes in lotic ecosystems. Few studies have considered how changes in river reach connectivity might affect ecosystem attributes at a whole river network scale. The use of population dynamics models of keystone species at a river network scale allows exploration of how the effects of altered natural connectivity patterns might propagate through a river network. In this study, we present a metapopulation model to estimate the spatial distribution of the population density of brown trout (Salmo trutta), an ecologically and socioeconomically important top predator, in a river network in northern Spain. The model accounts for the presence of barriers that limit longitudinal connectivity in upstream and downstream directions. The model estimates the spatial distribution of densities of three age‐classes (young‐of‐the‐year, juveniles, and adults) in all river reaches that make up the network based on topology, connectivity and population dynamics (e.g. age‐class specific mortality, spawning, age‐class dispersal, and spawning migration patterns). Seventy‐five percent of the modelled population densities fell within the 95% confidence intervals of the empirical data (84.6% for young‐of‐the‐year, 69.2% for juveniles, and 69.2% for adults) collected in 13 reaches. The simulated removal of all longitudinal barriers to migration in the river network (re‐naturalisation of the whole catchment) produced a modelled increase in brown trout density in the most downstream reaches of the river network and lowered fish densities in the upstream portion of the network when bias in juvenile and adult movement direction was assumed. Furthermore, the simulated removal of a single obstacle affected fish density even in distant tributaries. The proposed model is an appropriate tool for the evaluation of spatial patterns of brown trout density at a river network scale and for the assessment of the impact of altered connectivity. This might help simulate the results of management strategies regarding river connectivity and show where population decreases or increases could be expected, although empirical knowledge of overall trout movement in the studied river networks is required for drawing realistic scenarios.

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Movements and dispersal of brown trout (Salmo trutta Linnaeus, 1758) in Mediterranean streams: influence of habitat and biotic factors

Cited by 14 publications

References 65 publications

Hydropeaking effects on movement patterns of brown trout (Salmo trutta L.)

Hydropeaking effects on movement patterns of brown trout (Salmo trutta L.)

megaSDM: integrating dispersal and time‐step analyses into species distribution models

Effects of altered river network connectivity on the distribution of Salmo trutta: Insights from a metapopulation model

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