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Relative contributions of offspring quality and environmental quality to adult field performance

Rolanda Lange and Dustin J. Marshall

R. Lange (rolanda.lange@monash.edu) and D. J. Marshall, School of Biological Sciences, Monash Univ., Clayton, VIC 3800, Australia.

Determinants of adult performance, such as growth and survival, are influenced by extrinsic, environmental and intrinsic, phenotypic factors. The relative importance of extrinsic and intrinsic factors, while ecologically relevant, is rarely estimated simultaneously. We estimate the relative contributions of offspring size (intrinsic) and various environmental factors (extrinsic) on adult performance in the marine colonial bryozoan Watersipora subtorquata. We used a variance partitioning approach for both new and previously published data, enabling us to examine the performance of over 1000 individuals in the field. We found offspring size to explain relatively little variation in adult performance. Of the environmental factors taken to account, temporal variation and an environmental gradient had the strongest influences.

The performance of individuals and thus the dynamics of populations are driven by both environmental and pheno-typic variation. Extrinsic factors, such as habitat condition, the presence of competitors or predators, and disturbance regime will determine individual performance and popu-lation growth rates. These extrinsic factors can be broadly considered as elements of environmental quality (Begon et al. 2006). Likewise, individual phenotypic variation (intrinsic variation) is increasingly recognised as a driver of individual performance and population dynamics (Bolnick et al. 2003, 2011). For example, resource state, individual size, and behavioural syndromes (‘personality’) are all phe-notypes that influence the likelihood of individual survival and reproduction (Dias 1996, Kingsolver et al. 2001, Biro and Post 2008, Dall et al. 2012, Van Allen and Rudolf 2013). The role of phenotypic variation in driving popula-tion dynamics can be nontrivial (Benton et al. 2005): the quality (phenotype) of individuals entering a population can be more important for subsequent dynamics than the quan-tity of individuals (Burgess and Marshall 2011). Despite the increasing recognition that both environmental quality and individual phenotype will determine subsequent individual performance and population dynamics, studies that compare their relative roles are rare.

One of the most invoked intrinsic factors to contribute to adult fitness is offspring size (Stearns 1992, Bernardo 1996, Roff 2002, Marshall and Keough 2008a). Within a wide range of taxa, offspring size affects survival, growth, reproduction and biological interactions such as preda-tion and competition (Mousseau and Fox 1998, Marshall and Keough 2008a, Krist 2011). Generally, larger offspring tend to perform better than smaller offspring, though this effect is not universal (Maranon and Grubb 1993, Paz et al.

2005, Jacobs and Sherrard 2010, Robertsen et al. 2013). The effects of offspring size on subsequent performance are context-dependent: competition, predation and environ-mental stress can alter the relationship between offspring size and performance (Marshall 2008, Giesing et al. 2011, Marshall and Monro 2013, Davis and Marshall 2014). For example, within a species, offspring size may have weak or no effects on fitness in benign environments, but strong effects in harsher environments (Einum and Fleming 1999, Fox 2000, Marshall and Keough 2008b). It is now clear that environmental variation modifies the relevance of offspring size, but whether environmental variation can exceed the relevance of offspring size remains largely unknown. Almost 20 years ago, Bernardo (1996) called for tests of the relative roles of offspring size and environmental variation and until such estimates are made, the ecological relevance of offspring size effects remains unresolved. Importantly, such studies must be conducted under field conditions as this is where relevant environmental variation occurs, yet for most organ-isms, tracking individual performance in the field remains a formidable challenge.

Here, we partition the relative contributions of a proxy for environmental quality and offspring size on subsequent performance (colony size and survival) in the bryozoan Watersipora subtorquata. We know that in Watersipora, off-spring size affects adult performance and is an indicator of quality (Marshall and Keough 2004, Marshall and Monro 2013). We take two approaches to gain a more comprehen-sive understanding of the relative contribution of extrinsic, environmental factors and our intrinsic factor offspring size. First, we used an experimental approach to examine the performance of different-sized offspring (using a naturally occurring range of offspring size variation) across two

2015 The Authors. Oikos 2015 Nordic Society OikosSubject Editor: Sara Magalhães. Editor-in-Chief: Dries Bonte. Accepted 24 April 2015

Oikos 125: 210–217, 2016 doi: 10.1111/oik.02473

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different, arbitrarily chosen depths. These two depths are within the natural depth distribution of Watersipora at the study site. Natural settlement at 4 m is half that found at 1 m (Lange and Marshall unpubl.) and pilot data (Marshall and Chang unpubl.) indicate that 4 m represents a poor-quality habitat. This is likely because depth is correlated with tem-perature, salinity, water currents and food availability, and thus also affects community composition (Cowie 2010).

We used a variance partitioning approach to estimate the relative amounts of variation that offspring size and environ-ment explained. Second, we applied this variance partition-ing approach to previously published studies of offspring size effects in this species to partition relative importance of environmental variation and offspring size. This approach was applied for over 1000 individuals in the field spanning seven study sites, 11 degrees of latitude and over nine years of study.

Material and methods

Experimental study

Study speciesWatersipora subtorquata is an invasive, cosmopolitan bryozoan commonly found in marinas in temperate water regions. This encrusting, colonial hermaphrodite grows on hard substrates and is a prominent early coloniser of the fouling community. Its original distribution is currently unknown. The life cycle starts with a competent, lecitho-trophic larvae settling onto hard substrate and metamor-phosing into the first zooid, called the ancestrula. Colonies grow through the asexual addition of new zooids and, when unperturbed, grow into roughly circular discs. The colony consists of multiple zooids, which filter-feed by extending their lophophores (a tentacle with 15–20 arms) into the water column. Each zooid is a distinct clonal individual con-nected to the colony by pores that extend to neighbouring zooids. As zooids age they can potentially produce one egg within in an internal brood-chamber. Eggs can be internally fertilized from externally shed sperm or potentially, by self-fertilization (Ostrovsky et al. 2013). These brood chambers are visible to the human eye, such that reproduc-tive maturity can easily be scored.

Study site, spawning and animal maintenanceWe collected 24 mature Watersipora subtorquata colo-nies from artificial settlement plates located at Blairgowrie Yacht Squadron, Blairgowrie, Australia (38 21′20.16′′S, 144 46′22.82′′E) in October 2013. Reproductive matu-rity was scored on site by the presence of brooding eggs in the colony, which appear as red dots. We then transported colonies to Monash University, Clayton (Victoria, Australia) and kept them in insulated aquaria filled with seawater at 17 C in complete darkness for 5 days. We initiated spawn-ing by exposing colonies to bright, fluorescent light (2 35 W tubes) for up to two hours. Six colonies were pooled into one spawning batch, resulting in four different spawning batches. Pooling colonies ensured that there was ample supply of larvae within one batch, while the subdivision was to ensure that not one or two single colonies produced all larvae.

Release of competent larvae began 1 h after exposure to light. We placed eight randomly selected larvae on one acrylic plate (11 11 cm) with approximately equidistant spacing. Each larva was transferred with one drop of seawater within which it could settle onto the plate surface within 4 h. Plates were kept in darkness, which encour-ages settlement, and evaporation of water was prevented by ensuring high humidity. Larvae that had not settled within this time were removed. We initially placed 400 larvae onto 50 plates (batch A: 14 plates, batch B: 11 plates, batch C: 12 plates, batch D: 13 plates) of which 103 larvae successfully settled (batch A: 37 larvae and mean 3.0 SD 1.2 per plate, batch B: 15 larvae and 1.6 0.8 per plate, batch C: 13 larvae and 1.2 0.8 per plate, batch D: 38 larvae and 3.0 1.7 per plate).

We then transferred plates with freshly settled larvae to a tub of filtered seawater where they were kept for 36 h to complete settlement. We measured settler size by photo-graphing each larva at 800 magnification using a Motic 5 MP camera mounted on a Motic SMZ-168 stereomicroscope and tracing larval area using image analysis software (ImageJ ver. 1.47). Earlier studies (Marshall and Keough 2003) have previously shown that settler size is a reliable estimator of larval- and thus offspring size. Our mean tested larval size was 0.280 mm2 0.041 mm2 SE (min: 0.163 mm2, max: 0.388 mm2). Seven larvae could not be measured because of light reflections on the photograph.

After photography, we transported settlement plates with the attached settlers to Blairgowrie Yacht Squadron Marina where they were mounted upside-down onto 60 60 cm stacked backing panels (‘stacks’), which were attached to a floating pontoon by a steel cable. Each stack held a two back-ing panels, one at 1 m and one at 4 m below the sea surface. Plates were haphazardly distributed among panels, while assuring that half of the plates (and settlers) were deployed at each of the treatment depths. In total per-stack, 23 plates with settlers were deployed between two panels each at 1 m and 4 m, such that there were 11–12 plates per panel.

Effect of depth and offspring sizeFour weeks after deployment we retrieved settlement plates and brought them back to the laboratory to analyse survival and growth of settlers, now grown to colonies. To retrieve those parameters we photographed colonies at 150 magnification and analysed images using ImageJ. We esti-mated colony size by tracing the area of the flat colony. We scored survival by the presence or absence of a colony (colonies do not survive if they are removed from their sub-stratum). Two colonies were lost due to plate dislodgement.

Statistical analysisWe analysed offspring size- and environment-dependent variation in performance (colony size and survival). Colony size and offspring size were analysed in separate models. We analysed colony size in a linear mixed-model framework using R ( www.r-project.org ) and the lme4 package (Bates et al. 2013). Survival was analysed within a general linear mixed model framework with a binomial distribution. Our full models contained one dependent fitness variable, the fixed-factors panel depth, larval size, and their interac-tion, and the random-factor panel number nested within

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stack number. This model allows for random slopes and random intercepts with respect to panel depth. We then computed models without random slopes, without nesting or without a random factor, compared models and chose the model with the best model fit (lowest BIC score, see Zuur et al. 2009). We then compared models with and without the fixed interaction term. In both cases all random factor imple-mentations and our fixed factor interaction were removed from the final model. The most parsimonious model was plotted to identify whether model assumptions in terms of error distributions were satisfied. Our linear models met the assumptions.

Variance partitioning analysis

We analysed the raw data from several studies which had examined the effects of offspring size and environmen-tal variation on subsequent performance in Watersipora subtorquata (Marshall and Keough 2004, 2008b, 2009, Marshall and Monro 2013, Davis and Marshall 2014). We partitioned variance in performance into variation explained by offspring size, various environmental parameters and interactions, including our experimental study discussed herein. These environmental parameters were compo-nents of competition (interspecific: Marshall and Keough 2009, Marshall and Monro 2013, intraspecific: Davis and Marshall 2014) – therein used as a treatment effect – deployment depth – treatment effect of the current study – or spatial or temporal variation, which was the result from hav-ing several experimental blocks spread over space and time. We further defined mid-scale spatial variation as ranging from 1–1000 m and large-scale variation as ranging above 1000 m. These scales were selected arbitrarily but are likely to reflect the scales of dispersal within a single generation – Watersipora have a very short (few hours) larval period and water flows in marinas are low such that dispersal distances of 1000 m in a single generation are unlikely. We note here that temporal variation within our variance partition-ing approach also incorporates some space and space time effects because panels among runs were usually deployed on to new spaces, usually within the range of several meters from panels from earlier runs. Such temporal and spatial effects can-not be completely disentangled, but our results suggest that the temporal component of the run effect is more relevant, since mid-scale spatial effects alone explained little variation. For those studies that included multiple study sites (Marshall and Keough 2008b, 2009), we analysed each study site sepa-rately as we were interested in the relative roles of offspring size and environmental variation within populations. When a treatment was included into the study, which was either in the form of manipulating the level of competition (Marshall and Keough 2009, Marshall and Monro 2013, Davis and Marshall 2014) or manipulating deployment depth (experi-mental study herein), these were treated as environmental effects. We further included a variance partitioning analysis that was within those treatments, and then calculated mean values from those results (only within each study). This was to determine the relative importance of offspring size within treatment environments but across space and time (results in the Supplementary material Appendix 1).

We used the hier.part (Walsh and Mac Nally 2003) and relaimpo (Grömping 2006) packages in R to extract variance partitions from raw data. These packages produce the same partitions, but only hier.part is able to compute variance partitions from binary response variables, so we used it to analyse survival. We plotted our resulting variance partitions using the ggplot2 package (Wickham 2009) in R.

Data available from the Dryad Digital Repository: http://dx.doi.org/10.5061/dryad.8hk49 (Lange and

Marshall 2015).

Results

Experimental study

Colony size was strongly influenced by deployment depth, colonies that were deployed to 4 meters depth grew much less than colonies in 1 m depth. In contrast, offspring size influenced adult performance only slightly, such that larger offspring had a tendency to produce larger colonies (Table 1, Fig. 1).

Survival was not influenced by any of our predictors (Table 1). The majority of deployed settlers survived the first four weeks of deployment (82%).

Variance partitioning analysis

The most striking result from our analyses of colony size across experiments was how much variation in individual performance exists at temporal scales and how little of this variation can be explained by offspring size. Despite indi-viduals growing in what appears to be similar conditions (i.e. larvae experienced identical laboratory conditions and adults were deployed on identical artificial settlement plates at the same depth), individual growth rates differed by an average of 40 from the fastest to the slowest growing individuals.

Regarding the power of environmental factors to influ-ence colony size (Table 2, Fig. 2), temporal variation was the most influential. When included into the experiment it contributed up to 35% of explained variance (16% 16%). Treatment, which captured the effects of competition and deployment depth, explained an average of 10% of varia-tion ( 9%). Offspring size explained on average 6% of total variation in colony size, ranging from less than 1% in the

Table 1. Factor effects taken from linear model (on response variable colony size) and generalised linear model (on response variable survival). Sample sizes are noted in Material and methods. Statistical significance is noted by bold lettering.

Response variables and fixed effects Estimate SE

t or z value p

Colony size (mm2) - linear model(Intercept) 25.21 30.76 0.82 0.415Deployment depth (m) 14.04 2.94 4.77 0.001Offspring size (mm2) 203.05 108.76 1.87 0.066

Survival – generalized linear model (error structure: binomial)(Intercept) 2.2 1.97 1.12 0.264Deployment depth (m) 0.04 0.18 0.21 0.833Offspring size 2.52 6.78 0.37 0.711

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Figure 1. Offspring size and deployment depth effects on colony size (y-axis). Offspring size is denoted on the x-axis, deployment depth is colour- and shape- marked (red, rectangular, solid line: 1 m, blue, triangular, dashed line: 4 m).

‘Marshall 2008 Sydney’ dataset and 17% in the ‘Marshall 2009 Williamstown’ dataset (Fig. 2). Perhaps surprisingly, the contribution of large to mid-scale spatial variation, while noticeable, was comparably small, explaining on average 4% of colony size variation ( 2%). There were major differ-ences in the contribution of offspring size and environmen-tal variation on colony size among studies and even within the same study but at different sites (Table 2).

Neither environment nor offspring size strongly con-tributed to the chances of survival (Table 2, Fig. 3). Across most of the environmental treatments, both environment (2% 2%) and offspring size (3% 2%) had a similarly minor effect. When included in the study, competition seemed to have exerted the strongest environmental effect (2% 2%).

While we included only one study on colony fecundity, the observed pattern matched those for colony size: environ-mental variation had a much stronger impact on fecundity than did offspring size (Table 2).

Discussion

We compared the roles of offspring size and environmental variation in driving variation in adult performance through both an experimental study and the re-analysis of results of a number of earlier studies on Watersipora subtorquata.

Adult performance in the field (in terms of both survival and growth) varied at a number of scales. Colony size was more strongly influenced by environmental factors rather than offspring size, but survival was hardly influenced by either source of variation. The most consistent source of variation in performance was temporal, as on average around 16% of variation in performance occurred among experimental runs separated by a few days or weeks.

The strong temporal variation in adult performance we observed may have been caused by cohort effects. Such effects occur when past environmental variation, especially when experienced during early life-history stages (Lindström 1999), influences and characterizes cohorts within a popula-tion. The logical conclusion of such effects is overall increased variability between individuals, especially when sampling among cohorts. Climatic, temporal variation is a common source of cohort effects in populations (Lindström 1999, Forchhammer et al. 2001, Stenseth et al. 2002). Variation in average temperatures and food availability is a common property of seasonal environments, which strongly influ-ences individual growth (Lindström 1999, Post and Stenseth 1999, Wittmer et al. 2007). Furthermore, cohort effects can be caused by temporal shifts in the genetic composition of a population, and such shifts have indeed been found for several marine invertebrates and terrestrial animals. These can be created by environmental variation (Lessios et al. 1994, Barshis et al. 2011, Kesäniemi et al. 2014), selection (Grant and Grant 1993, 2006, Altizer et al. 2003, Jokela et al. 2009), genetic drift (Hedgecock 1994, Planes and Lenfant 2002), and gene flow (Barber et al. 2002, Robainas-Barcia et al. 2008).

Offspring size generally contributed little to adult performance. This does not necessarily negate earlier find-ings which have shown that offspring size is a statistically significant predictor of success as an adult – it merely suggests that its effect size is relatively smaller than envi-ronmental effects. Moreover, its contribution varied among studies, and thus between populations or across time. While the between-studies variation we found for offspring size and environmental effects could have been caused by differences in performance measures (for instance, colony size and survival was measured at different times), we did find some of the strongest differences in patterns between studies that used consistent methods (the Melbourne and Sydney dataset published in in Marshall and Keough 2008b and the St. Kilda and Williamstown datasets published in Marshall and Keough 2009). The differences in the impor-tance of offspring size among those dataset are likely caused by large-scale spatial variation, such that offspring size is a relevant predictor of adult performance under some circum-stances.

We want to note that the magnitude of environmental effects will strongly depend on the type and strength of the environmental gradient analysed. For instance, if a small or irrelevant environmental gradient or factor is included into the analysis, its effects on adult performance may be small and vice versa. Therefore, how we interpret environmental effects relies on the discretion of the authors and will always be taken with a grain of salt. In our case, we included envi-ronmental factors that we think constitute a range that can be encountered within a population. For instance, temporal

214

Tabl

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Var

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ns (%

) for

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size

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ent

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Dav

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size

986

76.0

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10%

3.15

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9.66

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61%

13.6

7%Su

rviv

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2009

Mod

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incl

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th s

ites:

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ony

size

806

62.0

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80%

14.1

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94%

11.0

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697

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only

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446

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253

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290

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873

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Lang

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475

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101

497

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58%

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%1.

69%

215

Figure 2. Colony size variance partitions of extracted from previous studies and the current study (see Methods for sources). Each block represents one study or one major site. Blocks are subdivided into bars representing (1) a complete variance partitioning and bar (2) a partitioning of the proportion of explained variance excluding error. OS offspring size. Environmentally derived variance is represented by grey shades, offspring size by yellow and residual by white. Specific partitions can be derived from the legend on the right.

Figure 3. Survival variance partitions of extracted from previous studies and the current study (see Methods for sources). Design otherwise similar to Fig. 2.

variation was within one season of growth and most spatial variation we included, unless specified, was within a population. Levels of competition also constitute what these animals naturally encounter, for instance when arriving early on newly formed habitat or late. Furthermore, these measures represent one of the few systematic attempts to investigate the relevance of offspring size variation to adult performance relative to any environmental variation.

Our experimental results were consistent with our re-analysis of previous data in that the contribution of off-spring size to adult performance was low. While there was a tendency for offspring size to positively correlate with colony size, the high level of noise (Fig. 1) prevented this from reaching statistical significance and the overall contribution was low (Table 1). Furthermore, the studied range may have been too small to detect effects, if especially small or large larvae did not settle and were therefore excluded from our experiment. Similar to our other analyses an environmental parameter – deployment depth – contributed most of the explained variance. We here want to stress that this depth gradient – along which Watersipora naturally occurs – did not reflect any distinctly different habitat types: settlers were all deployed within shallow subtidal habitats on hard sub-strate under no or low competition, yet only 3 m of depth difference accounted for almost one quarter of colony size variation. While this does not seem like a great distance, depth strongly influences many different environmental parameters, which often change almost abruptly within the first few meters (Cowie 2010). Our experiment was not

designed to pinpoint what exact parameters are relevant to Watersipora, but we speculate that differences in tempera-ture, food availability, or levels of competition were influ-ential. Interestingly, other studies in marine environments have found vertical distance to cause greater genetic differ-entiation than longitudinal distance when comparing within natural range distributions (Mokhtar-Jamaï et al. 2011, van Oppen et al. 2011). This suggests that depth and the changes it brings can be an agent of population differentiation.

Within natural populations, where temporal and spatial variation are inevitable, offspring size effects may play a limited ecological role and be overpowered by environmen-tal effects. Because many marine organisms are mobile only as a larvae and then settle to become sessile adults, colonising an appropriate habitat must be one of the most important fitness-determining factors in sessile organisms and selec-tion on this behaviour should be strong. Indeed, a growing number of studies report on the occurrence and pervasive-ness of habitat-selection behaviour in sessile marine organ-isms (McQuaid and Miller 2010). Larvae have been found to choose between 1) different types of biofilms whose com-position gives inference on average temperatures (Sneed et al. 2014, Whalan and Webster 2014), 2) inclination of the settlement surface (Burgess et al. 2012), 3) presence of conspecifics (Crisp 1985), 4) chemical cues (Pawlik 1992, Clare et al. 1994, Dreanno et al. 2006), 5) and acoustic cues (McDonald et al. 2014). When larvae are allowed to move freely, their size may influence settlement success. Indeed, previous studies have shown that small larvae settle faster,

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are less choosy about their habitat and more likely to settle in suboptimal habitats (Marshall and Steinberg 2014), which may explain a correlation between offspring size and performance under natural settlement conditions.

As discussed earlier, there are many possible reasons to explain our findings of small offspring size and large envi-ronmental effects, which of course represent only a small fraction of possible environmental and intrinsic effects on population dynamics. Of course, scrutiny has to go into the choice of environmental parameters to study and we advise to try choosing them according to levels experienced within a population – which may often be difficult to determine. Moreover, offspring size is only one of many potentially important intrinsic factors to influence adult performance and we think genetic variation or chemical composition to be important drivers of adult performance.

Partitioning the proportion of explained variation, as done herein, is a useful measure to put statistical analyses into the context of ecological and evolutionary relevance and can point at gaps in our understanding (Bernardo 1996, Quinn and Keough 2002). Using this approach we found that within populations, which will always be sub-ject to temporal and spatial variation, offspring size effects may often be negligible and overpowered by environmental effects. Seemingly small environmental differences can have strong effects on populations.

Acknowledgements – We would like to thank Keyne Monro and Theodore Chang for valuable insight during manuscript prepara-tion. The Blairgowrie Yacht Squadron kindly permitted us to use sheltered piers as our experimental arena. The German Academic Exchange Service (DAAD) and the Australian Research Council provided funds for field work and manuscript preparation.

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Supplementary material (available online as Appendix oik-02473 at www.oikosjournal.org/appendix/oik-02473 ). Appendix 1.

Oikos OIK-02473

Lange, R. and Marshall, D. J. 2015. Relative contributions of offspring quality and environmental quality

to adult field performance. – Oikos doi: 10.1111/oik.02473

Appendix 1 The exclusion of treatment effects had only minor effect on the effect size of other variables (Fig. A and B).

Figure A. Colony size variance partitions of extracted from previous studies and the current study (see Methods for sources). Each block represents one study or one major site. Blocks are subdivided into bars representing (1) a complete variance partitioning and bar (2) a partitioning of the proportion of explained variance excluding error. OS = offspring size. Environmentally derived variance is represented by grey shades, offspring size by yellow and error by white. Specific partitions can be derived from the legend on the right.

Figure B. Survival variance partitions of extracted from previous studies and the current study (see Methods for sources). Design otherwise similar to Fig. A.