Variation in the effects of larval history on juvenile performance of a temperate reef fishaec_

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1 Austral Ecology (2011), Variation in the effects of larval history on juvenile performance of a temperate reef fishaec_ ANNA C. SMITH* AND JEFFREY S. SHIMA School of Biological Sciences and the Coastal Ecology Laboratory, P.O. Box 600,Victoria University of Wellington,Wellington 6023, New Zealand ( anna.smith@vuw.ac.nz) Abstract For organisms with complex life cycles, the transition between life stages can act as a significant demographic and selective bottleneck. Variation in developmental and growth rates among individuals present in one stage (e.g. larvae), due to initial differences in parental input and/or environmental conditions experienced, can propagate to future stages (e.g. juveniles), and such carry-over effects can shape fitness and phenotypic distributions within a population. However, variation in the strength of carry-over effects between life stages and the intensity of selective mortality acting on intrinsic variation, and how these might be mediated by environmental variability in natural systems, is poorly known. Here, we evaluate variation in the strength to which larval growth histories can mediate juvenile performance (growth and survival), for a reef fish (Forsterygion lapillum) common to rocky reefs of New Zealand. We used otoliths to reconstruct demographic histories of recently settled fish that were sampled across cohorts, sites and microhabitats. We quantified sources of variation in the strength of carry-over effects and selective mortality that operate on larval growth histories. We found overall that individuals that grew fast as larvae tended to experience proportional growth advantages as juveniles. However, the strength of growth advantages being maintained into the juvenile period varied among cohorts, sites and microhabitats. Specifically, a stronger growth advantage was found on some microhabitats (e.g. mixed stands of macroalgae) relative to others (e.g. monocultures of Carpophyllum maschalocarpum) for some cohorts and sites only. For other cohorts and sites, the degree of coupling between larval and juvenile growth rates was either indistinguishable between microhabitats or else not evident. Similarly, the intensity of growth-based selective mortality varied among cohorts, sites and microhabitats: for the cohort and site where carry-over effects differed between microhabitats, we also observed difference in the intensity to which fish with rapid larval growth rates were favoured. Overall, our results highlight how this spatial and temporal patchiness in extrinsic factors can interact with intrinsic variation of recruiting individuals to have a major influence on the resulting distribution of juveniles and their phenotypic traits. Key words: individual variation, larval condition, post-settlement performance, reef fish. INTRODUCTION Many organisms undergo discrete stages of development, punctuated by major life history transformations (e.g. tadpoles to frogs, caterpillars to butterflies), which frequently coincide with a major shift in habitat use. Entry to a new habitat is often associated with periods of high mortality and newly transformed individuals are typically subject to high mortality rates (Hunt & Scheibling 1997; Pechenik 2006). As the highest levels of mortality occur on naïve individuals, factors that have relatively minor effects on mortality levels during the period immediately following transition can have a major influence on the total number of individuals surviving to maturity. Likewise, processes that influence which individuals are selectively lost from the population *Corresponding author. Accepted for publication November can have a major influence on the subsequent distribution of phenotypic (Vigliola & Meekan 2002; Giménez 2004; Pechenik et al. 2006) and genotypic traits (Planes & Romans 2004; Jones & Barber 2005). Successive developmental stages are connected across the life history of individuals, metamorphosis is generally not a new beginning (reviewed in Pechenik 2006), and the physiological experiences and resultant phenotypes from one stage can carry-over to affect fitness of subsequent developmental stages (Madsen & Shine 2000; Phillips 2002, 2004; Marshall et al. 2003; Hoey & McCormick 2004; Marshall & Keough 2004; Scott et al. 2007). Developmental histories have been shown to influence subsequent growth and performance of fishes (e.g. McCormick & Hoey 2004), amphibians (e.g. Altwegg & Reyer 2003), terrestrial invertebrates (e.g. Jannot 2009) and aquatic invertebrates (e.g. Wacker & von Elert 2002). This variation in growth and performance can facilitate natural

2 2 A. C. SMITH AND J. S. SHIMA selection (i.e. selective mortality) on phenotypes and/or physiological traits that were established earlier in the developmental history (e.g. Sogard 1997; Searcy & Sponaugle 2001; Marshall et al. 2003; Hoey & McCormick 2004; Gagliano et al. 2007; Vigliola et al. 2007; Hamilton et al. 2008). Recent studies of marine fishes have shown that the advantages associated with a high larval growth rate lead to enhanced survival during the period of high mortality following transition to the adult habitat (i.e. settlement; Searcy & Sponaugle 2001; Bergenius et al. 2002; Shima & Findlay 2002; Wilson & Meekan 2002). Although it is becoming clear that selective processes acting on larval traits are widespread among marine fishes, relatively few studies have explored how the direction and intensity of selection may vary through time and space (but see McCormick & Hoey 2004; Holmes & McCormick 2006; McCormick & Meekan 2007; Samhouri et al. 2009). The implications of growth-related carry-over effects for survival are not straightforward, and these will likely depend upon (i) the underlying patterns of initial phenotypic or physiological variation; (ii) the strength of carry-over effects (i.e. the extent to which intrinsic variation in growth is propagated across life stages and the relative advantage that is maintained in subsequent stages); and (iii) the ecological context within which these effects ultimately play out. For example, the intensity of size-selective mortality acting on recently settled reef fish is known to vary depending on predator abundance (McCormick & Hoey 2004; Holmes & McCormick 2006), adult conspecific abundance (Samhouri et al. 2009) and/or the presence of competitors (McCormick & Meekan 2007). Extrinsic factors (e.g. environmental variation, habitat quality, local community structure experienced by the present life history stage) provide an additional set of proximate mechanisms that can strongly affect variation in growth and survival of individuals (Tupper & Boutilier 1997; Relyea & Hoverman 2003). Little is known about the potential for extrinsic variability to interact with (and potentially mediate) the strength and importance of intrinsic variation present at settlement on subsequent growth and survival. Here, we evaluate variation in potential interactions between intrinsic (individual) and extrinsic (environmental) variation on patterns of growth and survival of a temperate reef fish. We sampled cohorts of recently settled reef fish from different sites and microhabitats, and we reconstructed growth histories of individuals during their larval (pre-settlement) stage and the juvenile (post-settlement) stage. We evaluated patterns of variation in the strength of carry-over effects on growth, and we quantified variation in the intensity of selective mortality across cohorts, sites and microhabitats. doi: /j x METHODS Study system and sampling regime We quantified life history traits and demographic performance of the common triplefin, Forsterygion lapillum near Wellington, New Zealand. Forsterygion lapillum is a small reef fish (maximum standard length = 6.7 cm; Fricke 1994) of the family Tripterygiidae, and is one of the most abundant species in shallow rocky reef habitats of New Zealand (Clements 2003; Feary & Clements 2006; Wellenreuther & Clements 2008). Adults spawn benthic eggs that hatch after approximately 20 days, and hatchlings have a pelagic larval duration of approximately 50 days (Shima & Swearer 2009a). In the Wellington region, larval F. lapillum settle to the fronds of several different species of macroalgae between December and April (McDermott & Shima 2006), where they remain for approximately 40 days before shifting to open cobble habitats to establish breeding territories (A. Smith, unpubl. data, 2008). Larval phenotypes (e.g. growth, pelagic larval duration) are variable among individuals, and these traits appear to be shaped by larval developmental environments (Shima & Swearer 2009a). Specifically, larvae with environmental signatures consistent with development in a semi-enclosed embayment (Wellington harbour) grow faster and settle sooner than larvae that putatively develop along the Wellington south coast, irrespective of natal origin (Shima & Swearer 2009a). Moreover, the relationship between larval phenotypes and recruitment strength varies between these regions: for sites within the harbour, recruitment is positively correlated with larval growth, although for sites on the south coast, the relationship is negative (Shima & Swearer 2009b). We sampled recently settled F. lapillum in January and February 2008 at a site within Wellington harbour (Kau Bay, S, E) and a site on the adjacent Wellington south coast (Island Bay, S, E). These sites were chosen because they are known to be replenished by larvae with different phenotypes (Shima & Swearer 2009b), and because they differ in local environmental conditions. Sites differed in wave exposure, temperature and the distribution and relative abundance of predator species (A. Smith & J. Shima, unpubl. data, 2008). Kau Bay, located within the comparatively sheltered Wellington harbour had recorded sea temperatures of 16.8 C ( 1.0 SD) during the study period. The second study site, Island Bay, located on the open coast adjacent to Kau Bay, is partially protected from periodic large southerly swells by a small offshore island (Taputeranga Island) and had recorded sea temperatures of 15.0 C ( 1.4 SD) during the study period. Macroalgal canopy (the settlement habitat for F. lapillum) is patchily distributed within both sites, and is predominately comprised of two species of fucalean brown algae, Carpophyllum maschalocarpum and Cystophora torulosa (A. Smith, pers. obs., 2008) in the shallow (<7 m deep) subtidal zone. At each site we identified a representative area of reef approximately 10 m long (parallel to the shore), 5 m wide, and at a depth of approximately 5 m; from within these areas we collected recently settled F. lapillum (individuals <40 mm Standard Length (SL)) with hand nets (and aided by the use of Self contained underwater breathing apparatus (SCUBA)). Because we were interested 2011 The Authors

3 LARVAL HISTORY AND POPULATION DYNAMICS 3 in the potential effect of microhabitat on life history traits and demographic performance of F. lapillum, we further stratified our sampling within two distinct types of settlement habitat: (i) monocultures of Carpophyllum, or (ii) mixed algal stands (generally comprised of Carpophyllum and Cystophora). It is known that F. lapillum associate with both kinds of algae (McDermott & Shima 2006). During each sampling event, we collected fish from four separate 1-m 2 quadrats, placed haphazardly within each of these two microhabitats for a total of 16 quadrats. Quadrats delineated the holdfasts and an overstory of stipes and fronds (i.e. the canopy), and these components of the microhabitat were all exhaustively sampled. We collected fish on three dates, paired (as closely in time as weather and sea conditions would permit) between locations (harbour: 16 Jan, 15 Feb, 29 Feb; south coast: 21 Jan, 13 Feb, 22 Feb). Quantifying age and growth histories before and after settlement To quantify age and growth histories of individuals, we extracted and analysed sagittal otoliths ( ear stones ) of recently settled F. lapillum. Otoliths of many fishes (including F. lapillum) form in daily growth increments that can be used to infer stage-specific age and growth patterns of individuals (Hare & Cowen 1997; Campana & Thorrold 2001; Shima & Findlay 2002; Sponaugle et al. 2006). Otoliths were prepared following the methods of Shima and Swearer (2009a). We used an image analysis system consisting of a compound microscope, a digital camera and computerbased image analysis software (Image Pro Plus v5.0) to measure sequences of daily otolith increment widths from different stages of the life history of each sampled fish. We estimated late larval growth rate as the average increment width (mm day 1 ) across the final 7 days of larval growth prior to the distinct settlement mark that was visible on each otolith (Kohn 2007). We estimated post-settlement age from the number of daily growth increments following the settlement mark, and this facilitated a back-calculation of settlement date from the known date of collection. We estimated average juvenile growth rate as the average increment width (mm day 1 ) across the entire juvenile period (i.e. from settlement to capture; mean postsettlement age of sampled fish = days, SD = 10.68), and we identified two discrete settlement cohorts in our sample (see Results). Of the 142 fish sampled and analysed, 43 of these fish were identified as day 0 (i.e. had settled within the last 24 h). Variation in carry-over effects on growth Demographic performance in the post-settlement stage of many marine organisms is not decoupled from prior life history. However, the strength of carry-over effects may vary through time (e.g. among cohorts that experience different environmental conditions during their larval development), and/or these may be mediated by local environmental conditions (e.g. habitat quality; Searcy et al. 2007) in the post-settlement stage. All juvenile fish sampled and analysed from each site were divided into cohorts (based on estimated settlement date). At both sites, the number of fish in each group was roughly equal between cohorts (Kau Bay: n = 28 and 29, Island Bay: n = 18 and 24 for cohorts 1 and 2, respectively). We expected a priori that fish sampled from different cohorts and sites would differ in their growth histories, particularly given our prior observations of variation among sites within the harbour versus the open coast (Shima & Swearer 2009b). Furthermore, we hypothesized that microhabitats might play a role in mediating the pattern and strength of carry-over effects (i.e. the degree of coupling between growth in the larval and post-settlement stages). Separately for each cohort and site, we evaluated variation in the relationship between juvenile growth and larval growth across the two sampled microhabitats (Carpophyllum monoculture vs. mixed algal stands) using ancova (PROC GLM, SAS v9.2). Variation in intensity of selective mortality Variation in individual phenotypes (e.g. larval growth histories) can facilitate selective mortality in subsequent life history stages (Searcy & Sponaugle 2001). On different sampling days we subsampled fish that had settled in the same cohort (as determined by back calculating settlement day). This allowed us to observe how the phenotypic distribution in back-calculated larval traits of fish from four individual cohorts changed through time (i.e. between fish of different post-settlement ages that had settled in the same cohort). Phenotypic differences in backcalculated traits between fish of different post-settlement ages from the same cohort are consistent with selective mortality (Sogard 1997). We hypothesized that the strength of selection on individual phenotypes related to late larval growth varies among cohorts, sites and microhabitats. In order to assess the degree to which surviving individuals represented a skewed portion of the original cohort distribution (as an indication of selectivity) we calculated the normal deviate of late larval growth rate for each individual relative to the original cohort at settlement (defined as individuals with a post-settlement age of 0) (Figueira et al. 2008). The normal deviate = (X -m)/s, where X is the late larval growth rate of an individual fish, m is the sample mean (i.e. mean late larval growth rate of all settlers, defined as individuals with a post-settlement age of 0 sampled from a given site and cohort), and s is the sample standard deviation (Zar 1984). We looked at the pattern and magnitude of selectivity operating on late larval growth rate by testing for differences in normal deviates between microhabitats (Carpophyllum monoculture vs. mixed algal stands), separately for each cohort and site. Because individuals varied in post-settlement age (and hence, time for selection to operate), we analysed variation between microhabitats using ancova (PROC GLM, SAS v9.2), with post-settlement age as a covariate. Least-square means from this model were used as our estimate of selective intensity, and we tested the null hypotheses that (i) selective intensity was not different between the two microhabitats and (ii) that selective intensity was 0 for each microhabitat.

4 4 A. C. SMITH AND J. S. SHIMA RESULTS We identified two discrete settlement cohorts in our sample: fish identified as cohort 1 settled between 10 January 2008 and 22 January 2008, and fish identified as cohort 2 settled between 8 February 2008 and 20 February 2008 (Fig. 1A). The distributions of settlement dates for the two cohorts were similar for each site and microhabitat. A high level of variation in larval growth rates was observed among individuals within each cohort and between cohorts (Fig. 1B). Variation in carry-over effects on growth The pattern and strength of carry-over effects varied among sites, cohorts and microhabitats (Fig. 2, Table 1). For cohort 1 settling to the south coast, we observed a significant carry-over effect (late larval growth rate as a covariate; F 1,15 = 18.23, P = ), although the relationship between post-settlement growth and late larval growth differed between microhabitats (interaction term: F 1,15 = 11.06, P = 0.005; main effect of microhabitat: F 1,15 = 7.59, P = 0.016; Fig. 2A). Carry-over effects observed for cohort 1 settling to the south coast were accentuated on mixed algal stands, where individuals with higher growth rates as larvae grew increasingly more as juveniles, relative to individuals that settled to Carpophyllum monocultures (Fig. 2A). For cohort 2 settling to the south coast, we observed a significant carry-over effect (F 1,21 = 13.92, P = ) that did not differ between microhabitats (interaction term: F 1,21 = 0.14, P = 0.71; main effect of microhabitat: F 1,21 = 0.03, P = 0.87; Fig. 2B). Similarly, for cohort 1 settling to the harbour, we observed a significant carry-over effect (F 1,24 = 6.47, P = 0.018) that did not differ between microhabitats (interaction term: F 1,25 = 0.01, P = 0.95; main effect of microhabitat: F 1,25 = 0.02, P = 0.90; Fig. 2C). In contrast, for cohort 2 settling to the harbour we observed no significant carry-over effect (F 1,26 = 0.01, P = 0.96) or variation between microhabitats (interaction term: F 1,26 = 0.20, P = 0.66; main effect of microhabitat: F 1,26 = 0.32, P = 0.58; Fig. 2D). Variation in intensity of selective mortality Selective intensity varied among sites, cohorts and microhabitats (Fig. 3).Values for z-scores were consistently positive, indicating that the predominant trend was for the distribution of late larval growth rates among survivors to be positively skewed relative to settlers. This is consistent with selection that favours individuals that were growing rapidly as larvae (Fig. 3). The intensity of selection on fish from cohort 1 settling to the south coast differed between microhabitats; selective intensity was greater (and significantly different from 0) on Carpophyllum monocultures, and was comparatively weak (and not different from 0) on mixed algal stands (Fig. 3A). Selective intensity on fish from cohort 2 settling to the south coast was statistically indistinguishable between microhabitats, and was moderately strong (and different from 0) for both Fig. 1. Variation of Forsterygion lapillum in (A) daily settler frequency and (B) daily mean late larval growth (mm day -1 1SE) for 16 quadrats sampled across all sites and microhabitats. doi: /j x 2011 The Authors

5 LARVAL HISTORY AND POPULATION DYNAMICS 5 Fig. 2. Comparison of the relationships between late larval growth (mm day -1 ) and post-settlement growth (mm day -1 ) of juvenile fish from two different microhabitats; mixed stands of macroalgae (open circles/dotted lines) and Carpophyllum monocultures (closed circles/black lines), for each of the two identified settlement cohorts (cohort 1 or 2) at each of the two sampling sites (harbour or south coast). These four groups (for each cohort at each site) are labelled A D. See Table 1 for full ancova results. Table 1. ancova results for effects of larval growth and habitat on juvenile growth for fish that settled to: south coast, cohort 1; south coast, cohort 2; harbour, cohort 1; and harbour, cohort 2 Location & cohort Source of variation Sum of squares d.f. F P South coast, cohort 1 Habitat , Larval growth , Habitat * Larval growth , South coast, cohort 2 Habitat , Larval growth , Habitat * Larval growth , Harbour, cohort 1 Habitat , Larval growth , Habitat * Larval growth , Harbour, cohort 2 Habitat , Larval growth , Habitat * Larval growth , Significant P-values are displayed in bold. (Fig. 3B). Selective intensity on fish from cohort 1 settling to the harbour was qualitatively similar to that observed for fish of the same age class settling to the south coast, although the difference between microhabitats was not statistically significant (Fig. 3C). No evidence of selective mortality was observed for fish from cohort 2 settling to the harbour (Fig. 3D). DISCUSSION Physiological coupling across the larval juvenile stage transition for F. lapillum varied in space and time. Larval growth rate was positively correlated with postsettlement growth rate in three of four samples, suggesting that carry-over effects on growth were common, but context-dependent. Although previous studies of reef fishes have demonstrated that variation in developmental history can affect individual growth and survival (Searcy & Sponaugle 2001; Shima & Findlay 2002; McCormick & Hoey 2004; Raventos & Macpherson 2005), at the population level it is less clear how individual variation interacts with extrinsic variability through space and time. Extrinsic factors may potentially affect both the level of phenotypic expression (e.g. Schoeppner & Relyea 2008) and the

6 6 A. C. SMITH AND J. S. SHIMA Fig. 3. Comparison of selective intensity (z-score 1SE) for juvenile fish from different microhabitats; mixed stands of macroalgae (M; open bars) and Carpophyllum monocultures (C; black bars), for each of the two identified settlement cohorts at each of the two sampling sites (A D). For each cohort sampled from each site the probabilities of three null hypotheses being met are given; that selective intensity does not differ between microhabitats (H 0 C = M) and that for each microhabitat selective intensity does not differ from zero (H 0 C = 0 and H 0 M = 0). relationship between phenotype and fitness (e.g. Kingsolver & Gomulkiewicz 2003). We observed variation in the strength of the growth advantage conveyed by carry-over effects, and concomitant variation in selective intensity across cohorts, sites and microhabitats. Late larval growth rate may be correlated with a range of physiological and phenotypic traits that can contribute to variation in post-settlement growth, size and/or performance. For example, the level of intraspecific aggression shown by some fishes shortly after settlement has been linked to larval condition, with high condition fish performing a higher rate of intraspecific chases (Johnson 2008). In addition, expression of traits or behaviour patterns may be modified by extrinsic factors, for example the threat of predation can affect the expression of boldness and activity levels (McPeek et al. 2001; reviewed in Lima 1998), which can lead to a reduced level of amongindividual variation in size (Peacor et al. 2007). These studies suggest that extrinsic factors such as elevated risk of predation may reduce the strength of carry-over effects on performance. Alternatively, interactions such as interference competition may contribute to increased phenotypic variation among individuals if the competitive advantage of individuals with certain traits becomes more prenounced (Ziemba & Collins 1999; Ward et al. 2006). We speculate that the effects of larval history that carry-over to subsequent stages may become more prenounced in highly competitive doi: /j x contexts. In this way, the local competitive environment (i.e. the ecological context) may mediate the strength of carry-over effects on phenotypes, as well as how phenotypes then correlate to performance and fitness. Microhabitat often shapes the local ecological context experienced by juvenile fish, such as predation rate (Tupper & Boutilier 1997) and intraspecific competition (Bonin et al. 2009). We found that under some conditions (e.g. cohort 1 from south coast) microhabitats appeared to mediate the fitness and phenotypic consequences of intrinsic variation among individuals. Fish in cohort 1 that settled on the south coast grew on average faster in mixed macroalgal stands following settlement in comparison to monospecific Carpophyllum stands and the selective intensity based on larval growth rate was also lower. Increased habitat complexity is expected to mitigate the negative effects of competition and predation by providing a greater spectrum of resources (e.g. structural refuge) or decreasing encounter rates due to reduced manoeuvrability and/or the ability to visually detect competitors/prey (Anderson 1984; Main 1987; Persson & Eklov 1995; Lindholm et al. 1999). Conversely, variation in macroalgal composition may drive variability in the abundance and range of predators which can counteract these positive effects (e.g. Shima et al. 2008). In this case, mixed macroalgal stands appeared to result in fish growing faster and being 2011 The Authors

7 LARVAL HISTORY AND POPULATION DYNAMICS 7 subject to lower selective pressure, although it is unknown whether this is due to an increase in habitat heterogeneity or to the presence of certain algal species. In different ecological contexts, carry-over affects and selective intensity appeared to be important but unaffected by microhabitat (e.g. cohort 1 from harbour and cohort 2 from south coast). Spatiotemporal variability in the apparent effects of microhabitat may be attributable to any number of variables that likely varied among sites and through time (e.g. temperature, food availability, predator and/or conspecific density, turbidity, quality of the refuge provided by microhabitat, etc.). At present, we are unable to identify the mechanisms that contribute to the observed variation in carry-over effects and selective intensity. Other workers have hypothesized that carryover effects may be of lesser importance when environmental conditions are favourable (e.g. Marshall et al. 2006; Donelson et al. 2009), as all individuals may have sufficient access to resources, and competition is minimized. Regardless of mechanisms, our observations of variation in both carry-over effects and selective intensity have important implications for the dynamics and phenotypic structure of local populations. We can speculate that spatial variation in the strength of phenotypic links may have implications for the range of a phenotype present, for example the size distribution of individuals within a local population. By modifying the distribution of phenotypic traits, carry-over effects may play a substantial role in mediating the strength and direction of ecological interactions, from antagonism to mutualism (De Roos et al. 2003; Peacor et al. 2007). This has implications for a suite of evolutionary processes, including disruptive selection, niche expansion and adaptive radiation (Bolnick 2001). The ecological and evolutionary implications of phenotypic variation are further amplified for organisms where initial intrinsic variation is associated with dispersal history, as is the case for F. lapillum (Shima & Swearer 2009a). If post-settlement fitness is associated with an individual s natal origin and/or its dispersive pathway, the identity of surviving fish could determine which sources contribute to population persistence (Hamilton et al. 2008). Variation in the strength of carry-over effects may therefore mediate patterns of connectivity among local populations. In such ecological contexts where larval history has a reduced effect on phenotypic expression and fitness (e.g. for F. lapillum, cohort 2 in the harbour), a wider collection of source populations may successfully contribute to replenishment of the local population. In contrast, when strong carry-over effects and intense selection occur (e.g. for F. lapillum on the south coast), individuals that survive to successfully replenish the local population may represent only a small subset of contributing source populations. In short, patterns of metapopulation connectivity may be mediated by the local ecological context (and specifically, how this shapes the strength of carry-over effects and selective mortality). For organisms with complex life cycles, experiences throughout the larval phase or at particular critical periods before metamorphosis can undoubtedly influence fitness at later life stages. Our study highlights context-dependent variation in the strength of carryover effects and selection, and this spatio-temporal variation may have important implications for population dynamics and evolutionary processes. 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