DOI: 10.5061/dryad.mn7k4
title: Data from: Offspring development and life-history variation in a water flea depends upon clone-specific integration of genetic, non-genetic and environmental cues

description: 1. Theory predicts that offspring developmental strategies involve the
 integration of genetic, non-genetic and environmental ‘cues’. But it is
 unclear how cue integration is achieved during development, and whether
 this pattern is general or genotype-specific. 2. In order to test this, we
 manipulated the maternal and offspring environments of three genetically
 distinct clones of the water flea Daphnia magna taken from different
 populations. We then quantified the effect that the genotype, maternal
 environment and the offspring environment had on the development and
 life-histories of the three different clones. 3. Mothers responded to the
 same maternal environments in different ways, resulting in clone-specific
 maternal effects on neonate size. Offspring responses to maternal cues
 varied according to the trait in question and were also clone-specific.
 The integration of these maternal effects during development was highly
 context-dependent in two clones but more consistent across environments in
 the third. 4. Genetic, non-genetic and environmental cues contributed to
 offspring phenotypic variation in all three clones, but there was no
 general pattern linking traits to specific cues. In fact, two clones used
 different combinations of cues at different points in development to
 achieve similar phenotypic outcomes. Thus different D. magna clones
 integrated different combinations of cues at different points in
 development. Our results highlight the importance of considering variation
 across development and show how genotypic variation and plasticity in
 developmental transitions help to generate phenotypic variation. 5. Our
 results support the hypothesis that phenotype determination involves the
 integration of genetic, non-genetic and environmental cues and
 demonstrates that the relative contributions of different cues is highly
 variable.
description: Dmagna_ME_alltraits_summarySummary data file containing trait information for all individuals, for use with R scripts 1, 2, 3 and 4.Dmagna_ME_growth_coefData file for calculating growth coefficients for use with R script 1 (this is optional, as the summary of growth data is included in the Dmagna_ME_alltraits_summary.txt file).Dmagna_ME_growth_PMRNData file for calculating and plotting probabilistic maturation reaction norms (PMRNs), for use with R scripts 5 and 6.DaphniaME_1of6_MANOVA-ANOVA-posthocR script 1 of 6: calculating growth coefficients, followed by multivariate analysis of variance (MANOVA), analysis of variance (ANOVA)/GLMs and post-hoc tests.DaphniaME_2of6_Univariate-figsR script 2 of 6: Plotting univariate figures (those considered in the analysis of variance /GLMs from R script 1).DaphniaME_3of6_PCA-PCV-visualR script 3 of 6: Principal component analysis, together with visualisation of phenotypic change vectors in 2D sapce.DaphniaME_4of6_PCV-statsR script 4 of 6: Statistical analysis for identifying significant differences in vector lengths and angles of phenotypic change vectors (as visualised in R script 3).DaphniaME_5of6_PMRN_GLM-selectionR script 5 of 6: Using GLMs to statistically model probabilistic maturation reaction norms, and comparing among models to identify the best fit.DaphniaME_6of6_PMRN-figsR script 6 of 6: Using best fitting GLM (identified in R script 5) in plots of probabilistic maturation reaction norms.