DOI: 10.5061/dryad.7pvmcvdt5
title: Size, connectivity and edge effects of stream habitats explain spatiotemporal variation in brown trout (Salmo trutta) density

description: Ecological theory postulates that size and isolation of habitat patches
 impact the colonization/extinction dynamics that determine community
 species richness and population persistence. Given the key role of lotic
 habitats for life history completion in rheophilic fish, evaluating how
 the distribution of swift-flowing habitats affects the abundance and
 dynamics of subpopulations is essential. Using extensive electrofishing
 data, we show that merging island biogeography with meta-population
 theory, where lotic habitats are considered as islands in a lentic matrix,
 can explain spatiotemporal variation in occurrence and density of brown
 trout (Salmo trutta). Subpopulations in larger and less isolated habitat
 patches had higher average densities and smaller between-year density
 fluctuations. Larger habitat patches also had lower predicted risk of
 excessive zero catches, indicative of lower extinction risk. Trout density
 further increased with distance from the edge of adjacent lentic habitats
 with predator (Esox lucius) presence, suggesting that edge- and
 matrix-related mortality contributes to the observed patterns. These
 results can help reduce the negative impacts that habitat loss and
 fragmentation have on biodiversity, by stressing the importance of
 suitable habitat size and connectivity, and aid in prioritization of
 habitat restoration, dam removal and reintroduction programs aimed at
 vitalizing declining and locally extinct riverine fish populations.
description: Data on fish presence and density was generated through
 electrofishing, a non-lethal fish sampling method mainly conducted in
 streams where it is possible to wade. Electric current (DC) is used to
 attract fish to swim towards a hand-held anode where they are caught with
 a dipping net. It is an established and reliable method for quantifying
 fish density. See Bohlin et al (1989) and the Swedish and European
 Standard (SIS. SS‐EN 14011:2003: Water quality – Sampling of fish with
 electricity. Stockholm: Swedish Standard Institute; 2003.) for detailed
 descriptions on the method. Bohlin, T., Hamrin, S.,
 Heggberget, T. G., Rasmussen, G., & Saltveit, S. J. (1989).
 Electrofishing - Theory and practice with special emphasis on salmonids.
 Hydrobiologia, 173(1), 9–43. https://doi.org/10.1007/BF00008596
description: <strong>Variables used</strong><br> y0plus:
 density of young-of-the-year (0+) brown trout expressed as
 round(log10(x+1)*100) where x is individuals per 100
 m<sup>2</sup>.<br> y1plus: density of older than
 young-of-the-year (1+) brown trout expressed as round(log10(x+1)*100)
 where x is individuals per 100 m<sup>2</sup>.<br>
 y_total: density of brown trout of all age classes expressed
 as round(log10(x+1)*100) where x is individuals per 100
 m<sup>2</sup>.<br> island_size: length of lotic stretch
 in meters<br> lg_size: as above but in natural log<br>
 dist_next_island: distance to next neighbouring lotic island in
 meters<br> lg_dist: as above but in natural log<br> Upstream:
 dichotomous variable (1/0) stating whether the next neighbouring lotic
 island is located upstream (1) or downstream (0)<br>
 dist_to_edge_min: distance to the edge between lotic and lentic habitat in
 meters <br> lg_edge_dist: as above but in natural log<br>
 pike01: dichotomous variable (1/0) stating whether pike has been found on
 the site at any electrofishing occasion<br> IBG: habitat category
 (A, B, C, D) as per Fig 1 in the manuscript<br> size_of_next_lot:
 the length of the next neighbouring lotic stretch in meters<br>
 lg_next_size: as above but in natural log
 <strong>Two random effects</strong><br>
 RiverIdent: River identity<br> LoticIdent: A integerised identifier
 for each unique lotic stretch used as random effect
 <strong>Data files:</strong><br>
 <em>data_trout.csv</em> with aggregated mean densities per
 site<br> <em>data_trout01.csv </em>unaggregated
 densities per site for calculation of variability over time
 <strong>Special in data_trout01:</strong><br>
 fiskedat: date in eight numbers (YYYYMMDD)<br> Öring0: density of
 young-of-the-year (0+) brown trout in individuals per 100
 m<sup>2</sup><br> Öring: density of older than
 young-of-the-year (1+) brown trout in individuals per 100
 m<sup>2</sup><br> ÖringTOT: density of brown trout of
 all age classes in individuals per 100 m<sup>2</sup>