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Environmental factors influence phenotypes directly, as well as indirectly via trait correlations and interactions with other environmental variables. Using nine populations of the African cyprinid Barbus neumayeri, we employed path analysis to examine direct, indirect and total effects of two environmental variables, water flow (WF) and dissolved oxygen (DO), on several morphological traits. WF and DO directly influenced relative gill size, body shape and caudal fin shape in manners consistent with a priori predictions. Indirect effects also played an important role in the system: (1) strong, oppositely signed direct and indirect effects of WF on body shape resulted in a nonsignificant total effect; (2) DO had no direct effect on body shape, but a strong total effect via indirect effects on gill size; (3) WF indirectly influenced gill size via effects on DO. Only through examination of multiple environmental parameters and multiple traits can we hope to understand complex relationships between environment and phenotype.
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In natural systems, organisms face a multitude of ecological challenges and often respond with phenotypic shifts. Because organisms experience multiple selective and/or inducing agents, observed phenotypes generally reflect the influence of multiple environmental variables, in addition to other evolutionary factors (e.g. gene flow, genetic drift, genetic/developmental constraints) (e.g. Felsenstein, 1976; Lowell, 1987; Slatkin, 1987; Robinson & Wilson, 1994; Schluter, 2000; DeWitt & Langerhans, 2003; Ackermann & Cheverud, 2004). Environmental influences on traits can arise via genetically based responses to selection – including both environment-contingent phenotype production (i.e. phenotypic plasticity) and environment-independent phenotype production – as well as potentially nonadaptive effects of environment on phenotype (e.g. Levins, 1968; Schluter, 2000; Pigliucci, 2001; Pigliucci & Murren, 2003; West-Eberhard, 2003; DeWitt & Scheiner, 2004). Regardless of the adaptive nature or the form of genetic basis of phenotypic variation, environmental effects on phenotypes can be complex because of the interplay of direct and indirect effects on traits. That is, environmental factors can directly influence phenotypic values, and also indirectly influence phenotypes through trait correlations and interactions with other environmental factors (e.g. Gould & Lewontin, 1979; Lande & Arnold, 1983; Koehl, 1996; DeWitt & Langerhans, 2003; Pigliucci & Preston, 2004; Marks et al., 2005). For example, one environmental factor might directly increase the value of a particular trait, but indirectly decrease the value of that trait via effects on other environmental factors or correlated traits. This scenario might produce a situation where no relationship is observed between phenotype and environment (if examined in isolation of other phenotypes and environmental factors), when the true relationship is quite strong, albeit complex.
Ecologists and evolutionary biologists seek to understand relationships between environment and phenotype; but we are challenged by the complex networks of direct and indirect effects on traits. One useful approach to address this complexity is to apply a methodology that assesses both direct and indirect effects of multiple environmental factors on multiple phenotypes (DeWitt & Langerhans, 2003; Schaack & Chapman, 2003; Caumul & Polly, 2005; Hoverman et al., 2005). This assessment will be stronger if made in relation to an existing a priori understanding of how environmental factors and phenotypes are predicted to affect one another. Such an analysis should reveal how environment and phenotype are associated, even if this relationship is complex.
We examined effects of two abiotic environmental factors, dissolved oxygen (DO) concentration and water flow (WF), on several morphological traits of a cyprinid fish. We selected DO because it is a strong predictor of morphological variation in fishes, as well as other aquatic organisms, such as amphibians (Bond, 1960; Burggren & Mwalukoma, 1983) and arthropods (Jacobsen, 2000; Roast & Jones, 2003). In earlier studies, we have demonstrated population differentiation and/or phenotypic plasticity in respiratory traits for a suite of fish species that occur across DO gradients (e.g. Chapman & Liem, 1995; Chapman et al., 1999, 2000, 2002; Timmerman & Chapman, 2004). WF is generally believed to be a critically important factor in the evolution of morphology (including evolution of morphological plasticity) in fishes (e.g. Hubbs, 1941; McLaughlin & Grant, 1994; Hendry et al., 2000; Pakkasmaa & Piironen, 2000; Brinsmead & Fox, 2002; Imre et al., 2002; Langerhans et al., 2003; McGuigan et al., 2003; Collyer et al., 2005; Hendry et al., 2006; Sidlauskas et al., 2006), as well as other aquatic taxa (e.g. Denny, 1988, 1994; Johnson & Koehl, 1994; Gaylord et al., 2001; Carrington, 2002). Thus, these two abiotic variables may serve as major selective or inducing agents in many aquatic organisms.
Both environmental gradients (DO and WF) are predicted to influence morphological traits in particular manners. Using a comparative analysis of nine populations of the African cyprinid Barbus neumayeri, we tested a priori hypotheses regarding direct effects of each factor on particular phenotypes and direct effects of phenotypes on other phenotypes (Table 1). We developed a set of hypothesized direct effects (see details below), and used these predictions to build a path model. The path model was employed to understand the direct, indirect and total effects of environmental factors on organismal traits. We did not offer predictions regarding indirect or total effects, but rather these effects are designed to be revealed by a path analysis.
Table 1. Defined a priori direct effects, predictions and references supporting predictions.
|Direct effect||Predicted nature of effect||Reference|
|Water flow→dissolved oxygen||Higher WF→higher DO||1–3|
|Water flow→body shape||Higher WF→more fusiform body shape||4–11|
|Water flow→caudal fin form||Higher WF→larger, higher aspect ratio caudal fin||4–11|
|Dissolved oxygen→gill size||Lower DO→larger gills||12–19|
|Dissolved oxygen→body shape||Unknown|| |
|Gill size→body shape||Larger gills→larger head region||15,17,20–21|
|Body shape ←?→ caudal fin form||Unknown|| |
We proposed specific predictions regarding the nature of direct effects for five of seven hypothesized direct effects (Table 1). These predictions were made based on physical, physiological, biomechanical and architectonical knowledge of the system (see references in Table 1). For instance, physical interaction of atmospheric oxygen with turbulent surface waters causes rapid dissolution of oxygen into water (where oxygen concentration is much lower than air), and thus generally leads to a positive association between WF and DO. Each prediction concerning direct effects of environment on phenotype reflects an adaptive hypothesis (via either plasticity and/or fixed responses). For example, larger gills can extract oxygen more efficiently (but may be costly to produce), and thus selection should favour larger gills in hypoxic waters and relatively small gills in well-oxygenated waters. Further, to reduce the energetic expenditure necessary to maintain position in high-flowing water, fish morphologies should minimize drag and maximize thrust for steady swimming; this is accomplished with a large anterior body depth and narrow caudal peduncle (i.e. fusiform shape), and a large, high aspect ratio caudal fin (morphologies that compromise other aspects of swimming that employ the same propulsors, such as fast starts). In addition, we hypothesized that DO might directly affect overall body shape in an unknown manner, that larger gills would result in fish with larger head regions, and that body shape might influence caudal fin form in an unknown manner. This latter prediction describes the hypothesis that caudal fin form may partially derive from changes in body morphology (e.g. caudal peduncle depth could necessarily increase caudal fin height). However, alternative hypotheses exist regarding the relationship between body shape and caudal fin form, and thus we evaluate alternative hypotheses using a model selection approach.
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We retained the first PC for each set of morphometric variables (Table 3). Body shape variation described by the first PC is visualized in Fig. 4. AIC unambiguously selected the path model where body shape directly influences caudal fin form (ΔAIC = 4.6 for second best model). Using Akaike weights, the selected model was approximately 10 times more likely to be the best model for the observed data than the next best alternative model (Akaike weights of 0.81 vs. 0.08). There was no indication that the selected path model was inadequately structured (Bollen–Stine bootstrap P = 0.4383) and multicollinearity was reasonably low for those components of the analysis simultaneously considering multiple related factors (all variance inflation factors < 5.02). Results of the path analysis largely matched a priori predictions (Fig. 5), and most direct, indirect and total effects in the path analysis were significant (Table 4). We summarize the major findings of the path analysis below.
Table 3. Pearson correlation coefficients between size-adjusted morphological variables and principal components.
|Variable||Principal component 1|
|Relative gill size||56.90% of variance|
| log TGFN||0.36|
| log TGFL||0.94|
| log THA||0.96|
| log THP||0.94|
| log AHL||0.10|
|Caudal fin form||63.50% of variance|
| log CFL||0.80|
| log CFAR||0.80|
|Body shape||41.70% of variance|
Figure 4. Visualization of the first principal component for body shape. Populations varied significantly in morphology (mancova, P < 0.0001; Procrustes distances ranged from 0.01 to 0.03). (A) Vectors describing the direction and relative magnitude of change in the location of each landmark (landmarks follow Fig. 2; arrows point toward positive PC1 values). (B) Thin-plate spline visualization illustrating the nature of body shape variation described by the first principal component for body shape (magnified 3× to more clearly illustrate variation; grid transformations are relative to the mean landmark configuration). The head region is shaded to emphasize differences in relative head size.
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Figure 5. Path analysis results. Numerical values indicate path coefficients, and line thickness reflects the strength of the path. Solid lines represent positive effects, and dashed lines represent negative effects.
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Table 4. Direct, indirect and total effects for the path analysis.
|Dissolved oxygen||Relative gill size (PC1)||Body shape (PC1)||Caudal fin form (PC1)|
|Relative Gill Size (PC1)||–||–||–||–||–||–||1.69||–||1.69||–||1.61||1.61|
|Body Shape (PC1)||–||–||–||–||–||–||–||–||–||0.95||–||0.95|
|r2|| || ||0.54|| || ||0.69|| || ||0.73|| || ||0.86|
We found that higher WF resulted in an increased DO and was directly associated with deep-bodied fish having relatively deep heads and large, high aspect ratio caudal fins. Interestingly, indirect effects of WF on body shape, via indirect effects on relative gill size, opposed direct effects, resulting in a nonsignificant total effect of WF on body shape for the populations studied. DO was negatively associated with relative gill size. Although DO had no direct relationship with body shape, it indirectly influenced body shape via effects on gill size, resulting in a strong total effect. Other findings included a direct effect of relative gill size on body shape (larger gills resulted in fish with relatively deeper bodies and particularly large heads) and a direct effect of body shape on caudal fin form (fish with relatively deeper bodies and particularly large heads also had large, high aspect ratio caudal fins). Because body shape directly influenced caudal fin form, there were also significant total effects of DO and relative gill size on caudal fin form via their effects on body shape.
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Environmental impacts on phenotypes can be complex. Our path analysis uncovered a complex set of direct and indirect effects of WF and DO on morphological characters in B. neumayeri. We found an array of significant direct, indirect and total effects of environment on phenotype, as well as effects of phenotypes on other phenotypes.
Results of the path analysis largely matched a priori predictions for all five direct effects for which we proposed specific hypotheses: (1) higher WF resulted in higher DO; (2) higher WF resulted in fish with a relatively more fusiform body shape (e.g. greater anterior depth); (3) higher WF was directly associated with larger, higher aspect ratio caudal fins; (4) populations experiencing lower DO exhibited relatively larger gills; and (5) populations with relatively large gills had relatively large heads. Such correspondence between observations and predictions suggests that our a priori understanding of the system's direct effects is well founded, and that phenotypic shifts likely reflect adaptive responses through either phenotypic plasticity and/or divergent genetically based traits. We also found that body shape was associated with caudal fin form. This association could reflect phenotypic integration of functionally related traits (e.g. body morphology might influence caudal fin form architectonically, or through effects on developmental pathways) (Olson & Miller, 1958; Pigliucci, 2003; Pigliucci & Preston, 2004). Further, we found no evidence for a direct effect of DO on body shape, although we suspected that such an effect might exist because of effects of oxygen on growth, development and gene expression (e.g. Stewart, 1967; Cech, 1984; Rombough, 1988; Secor & Gunderson, 1998; Gracey et al., 2001; Kajimura et al., 2006).
The use of path analysis provided important insights into the indirect and total effects observed among factors in the system. For example, had we simply examined the bivariate relationship between WF and body shape (i.e. ignored variation in DO and relative gill size), we would have detected a nonsignificant association in the opposite direction, leading to the false conclusion that WF was not strongly associated with body shape. This suggests that prior studies reporting a nonsignificant association, or an association in the opposite direction of that observed here, between WF and body shape in fishes might have actually obtained a spurious result because of indirect effects of WF on body shape. That is, WF can influence DO, and thus gill size, which can cause indirect effects on body shape that mask the direct effects. This is a genuine possibility in some cases; however, in the present study we specifically chose populations exhibiting marked variation in both WF and DO; many previous studies likely did not examine populations exhibiting such variation in DO – although, DO is rarely measured and reported in such studies. We suggest that future studies examining the relationship between WF and body shape take DO into consideration in light of the results observed in this study.
Another interesting finding was that caudal fin form reflected the influence of multiple environmental factors and multiple phenotypes, despite having only two direct effects connecting it to the rest of the system. WF, DO, relative gill size and body shape all had significant total effects on caudal fin form, illustrating how some phenotypes can be influenced by more factors (environmental and phenotypic) than others. Effects of DO and gill size on caudal fin form resulted via indirect effects mediated through body shape. If this apparent phenotypic integration between body shape and tail form is a general phenomenon in fishes, it suggests that caudal fins can be influenced by a large number of factors as body shape is known to be influenced by numerous selective/inducing agents and other phenotypic attributes (e.g. Wimberger, 1992; Schluter, 1993; Robinson & Wilson, 1994; Walker, 1997; Robinson et al., 2000; Ruber & Adams, 2001; Langerhans et al., 2003; Ghalambor et al., 2004; Langerhans & DeWitt, 2004; Sidlauskas et al., 2006). Such findings are only possible through an examination of multiple environmental factors and multiple phenotypes, coupled with path analysis to distinguish direct and indirect connections among factors in the system.
Integrative studies examining multiple phenotypes and multiple selective/inducing agents are required to gain a more complete understanding of how phenotype and environment are associated. We employed such an approach in this study, and revealed how two abiotic environmental variables directly and indirectly influence three types of morphological parameters in B. neumayeri. Through the examination of multiple environmental factors and multiple traits, we should acquire a better understanding of phenotype–environment relationships, even if complex.