DOI: 10.5061/dryad.m905qftz4
title: Data from: Native drivers of fish life history traits are lost during the invasion process

description: Rapid adaptation to global change can counter vulnerability of species to
 population declines and extinction. Theoretically, under such
 circumstances both genetic variation and phenotypic plasticity can
 maintain population fitness, but empirical support for this is currently
 limited. Here, we aim to characterise the role of environmental and
 genetic diversity, and their prior evolutionary history (via haplogroup
 profiles) in shaping patterns of life history traits during biological
 invasion. Data were derived from both genetic and life history traits
 including a morphological analysis of 29 native and invasive populations
 of topmouth gudgeon Pseudorasbora parva coupled with climatic variables
 from each location. General additive models were constructed to explain
 distribution of somatic growth rate (SGR) data across native and invasive
 ranges, with model selection performed using Akaike’s Information
 Criteria. Genetic and environmental drivers that structured the life
 history of populations in their native range were less influential in
 their invasive populations. For some vertebrates at least, fitness related
 trait shifts does not seems to be dependent on the level of genetic
 diversity or haplogroup make-up of the initial introduced propagule, nor
 of the availability of local environmental conditions being similar to
 those experienced in their native range. As long as local conditions are
 not beyond the species physiological threshold, its local establishment
 and invasive potential are likely to be determined by local drivers, such
 as density dependent effects linked to resource availability or to local
 biotic resistance.
description: The dataset comprised of populations of <i>P.
 parva</i> across the native (China, Japan and Taiwan) and invasive
 range in Europe, all collected between June and August 2010. Following the
 sampling of each population (by fish trapping, seine netting or electric
 fishing, method dependent on the habitat sampled), 50 fish were randomly
 selected and euthanized (overdose of anaesthetic, 120 mg/L benzocaïne),
 with fin tissues collected and preserved in 98% ethanol prior to the whole
 fish being preserved in 10% formalin. Each sampling site was geo-located
 using a GPS and typology of the site recorded. For each
 fish, fork length (FL, mm), weight (W, g) and sex were recorded. For the
 production of all data for somatic growth rate analyses, ages of
 individual fish were obtained from ageing of scales, which were collected
 above the lateral line and below the insertion of the dorsal fin. Ageing
 was completed on a projecting microscope by counting the number of annual
 growth checks present. Each fish length was then plotted against age
 (years), and the von Bertalanffy growth model parameters length infinity
 (Linf) and k (see Sainsbury, 1980) calculated. In addition, the growth
 metrics somatic growth rate (SGR (cm/year); FL<sub> at
 capture</sub>-FL<sub>age 1</sub>)/ age at capture) and
 FL at year one (FL1) were determined, which also corresponded to the age
 at maturity in all populations (Gozlan et al., 2010a).
 Reproductive traits were assessed using fecundity and
 gonado-somatic index (GSI) of female fish. Ovaries were extracted from
 each female and weighed (to 0.01 g; Wo). A sub-sample of each ovary, cut
 from the middle of the gonad, was weighed (Ws) and the number of oocytes
 counted under a binocular microscope. Each oocyte was classified by size
 categories using a fitted micrometer (i.e. &lt;0.1; [0.4-0.5];
 [0.6-0.8]; [0.9-1]; &gt;1.1 mm ± 0.05mm) with the sum of oocytes (n)
 representing potential fecundity (oocytes &lt;0.1 mm were not included
 in counts). The potential fecundity was then calculated as [FEC =
 n*Wo/WS]. GSI was calculated as [Gonad weight / Total fish weight] x 100
 (Strum, 1978) and only females with GSI above 12 % were considered in
 reproductive state and used in analyses. To examine
 patterns of relative growth, raw data from 30 mensural characters,
 including fork length (FL; see also Záhorská et al., 2009), were measured
 from digital photographs taken by a Pentax optio S10 camera, with analysis
 using IMPOR 2.31E software.
description: The DRYAD data are self explanatory. All other information are
 provided directly in the published paper.