DOI: 10.5061/dryad.ttdz08kt8
title: Marine fish traits follow fast-slow continuum across oceans

description: A fundamental challenge in ecology is to understand why species are found
 where they are and predict where they are likely to occur in the future.
 Trait-based approaches may provide such understanding, because it is the
 traits and adaptations of species that determine which environments they
 can inhabit. It is therefore important to identify key traits that
 determine species distributions and investigate how these traits relate to
 the environment. Based on scientific bottom-trawl surveys of marine fish
 abundances and traits of &gt;1,200 species, we investigate
 trait-environment relationships and project the trait composition of
 marine fish communities across the continental shelf seas of the Northern
 hemisphere. We show that traits related to growth, maturation and lifespan
 respond most strongly to the environment. This is reflected by a
 pronounced “fast-slow continuum” of fish life-histories, revealing that
 traits vary with temperature at large spatial scales, but also with depth
 and seasonality at more local scales. Our findings provide insight into
 the structure of marine fish communities and suggest that global warming
 will favour an expansion of fast-living species. Knowledge of the global
 and local drivers of trait distributions can thus be used to predict
 future responses of fish communities to environmental change.
description: We collated data from 21
 scientific bottom-trawl surveys in the North Atlantic and North-East
 Pacific. We selected the period 2005 to 2015 in order to have a similar
 temporal coverage and a consistent sampling period across surveys.
 Although gears and sampling protocols vary between surveys, they all use
 bottom trawls and identify catches at species level whenever possible.
 Abundance data were standardized according to the duration or swept area
 of the tow, depending on which information on the tows was provided with
 the survey. We verified and updated the taxonomy of reported taxa with the
 World Register of Marine Species and discarded all non-fish taxa by
 keeping only organisms from the following classes: Actinopterygii,
 Elasmobranchii, Holocephali, Myxini and Petromyzonti. The two largest
 classes are the bony fish (Actinopterygii) and elasmobranchs
 (Elasmobranchii). Finally, we only kept taxa that had been recorded at the
 family, genus or species level. Our dataset consisted of 77,824 samples,
 recording the abundance of 1,889 different taxa (1,583 taxa identified at
 species level, 203 at genus level and 103 at family level).
 To broadly represent the life
 history and ecology of fish in terms of their feeding, growth, survival
 and reproduction we selected seven commonly used traits: maximum body
 length (cm), trophic level, fecundity (number of offspring produced by a
 female per year), offspring size (egg diameter, length of egg case or
 length of pup in mm), age at maturity (year), lifespan (year) and the Von
 Bertalanffy growth coefficient K (1/year) as a proxy for individual growth
 rate. Trait information was extracted from a publicly available dataset on
 marine fish traits (Beukhof et al. 2019, DOI : 10.1594/PANGAEA.900866), for which most trait values were sourced from FishBase and collected at the level of Large Marine Ecosystems (LMEs) and FAO fishing areas in order to account for intraspecific variation in species traits across areas. We selected seven environmental variables representing hydrography, habitat, food availability and anthropogenic pressures, which are known to affect the distribution of fish species. Monthly sea bottom temperature (SBT in °C) and sea bottom salinity (SBS in psu) from 2004 to 2015 were obtained from the Global Ocean Physics Reanalysis (GLORYSs2v4) with a spatial resolution of 1/4°. Chlorophyll <i>a </i>concentration (Chl in mg/m<sup>3</sup>) served as a proxy for primary production and food availability. Data were downloaded from the GlobColour database with a spatial resolution of approximatively 4 km. To reduce computation time, sampling sites were aggregated into grid cells of 0.25 by 0.25 degree. For each grid cell the average relative species abundance and environmental condition was calculated over all sampling sites falling into the grid cell. 
description: The zip-archive contains five files:                             
                <br> 1- Labu.csv: relative abundances of fish
 species per 0.25 degree rectangle                               
  <br> 2- Qtrait.csv: traits database of fish species       
   <br> 3- Renv.csv: environmental variables per 0.25 degree
 rectangle  <br> 4- Coordinates.csv: Coordinates of the 0.25 degree
 rectangles<br> 5- scriptRLQ.R: the script to run the RLQ and Random
 Forest analysis The script has been simplified
 substantially compared to the analysis in the referred article.<br>
 For example, we removed the sensitivity tests and the complex
 implementation of random forests in order to keep the core analysis in a
 single R-script.<br> The dataset provided is an aggregation of
 72,258 stations into a grid of 0.25 degree resolution. Even with such
 simplification and due to the large size of the datasets, the R-script
 takes around 5-15 min to run.