| Literature DB >> 26357533 |
James B Johnson1, Daniel Saenz2, Cory K Adams2, Toby J Hibbitts3.
Abstract
Divergent natural selection drives a considerable amount of the phenotypic and genetic variation observed in natural populations. For example, variation in the predator community can generate conflicting selection on behavioral, life-history, morphological, and performance traits. Differences in predator regime can subsequently increase phenotypic and genetic variations in the population and result in the evolution of reproductive barriers (ecological speciation) or phenotypic plasticity. We evaluated morphology and swimming performance in field collected Bronze Frog larvae (Lithobates clamitans) in ponds dominated by predatory fish and those dominated by invertebrate predators. Based on previous experimental findings, we hypothesized that tadpoles from fish-dominated ponds would have small bodies, long tails, and large tail muscles and that these features would facilitate fast-start speed. We also expected to see increased tail fin depth (i.e., the tail-lure morphology) in tadpoles from invertebrate-dominated ponds. Our results support our expectations with respect to morphology in affecting swimming performance of tadpoles in fish-dominated ponds. Furthermore, it is likely that divergent natural selection is playing a role in the diversification on morphology and locomotor performance in this system.Entities:
Keywords: Anuran larvae; fast-start performance; morphology; phenotypic integration; predation; tadpole
Year: 2015 PMID: 26357533 PMCID: PMC4559044 DOI: 10.1002/ece3.1538
Source DB: PubMed Journal: Ecol Evol ISSN: 2045-7758 Impact factor: 2.912
Figure 1Illustration of the lateral (A) and dorsal (B) digitizing scheme used in this study. For the dorsal digitizing scheme, C = body centroid; MBA = main body axis; TL = tail length; and ITL = inferred tail length. Traditional landmarks are shown as solid points and semi-landmark as open points.
Figure 3Surface plot showing lateral CV1 and dorsal CV1 in relation to fast-start speed; red denotes faster and blue slower.
ANOVA results showing differences in fast-start performance by predator regime and pond nested within predator regime (F approximation based on Wilk’s Lambda)
| Effect | F | Num DF | Den DF |
|
|---|---|---|---|---|
| Pond (Predator regime) | 26.014 | 8 | 240 | <0.0001 |
| Predator regime | 35.568 | 1 | 240 | <0.0001 |
Figure 2The means and standard errors for fast-start speed for ponds with fish predators (F1–F5) and ponds with invertebrate predators (I1–I5). Global means are shown to the left of each panel in columns F (fish) and I (invertebrate).
Results for lateral (A) and dorsal (B) MANCOVA models where morphology was dependent on pond nested within predator regime (F approximation based on Wilk’s Lambda), predator regime and log centroid size
| Effect | F | Num DF | Den DF |
|
|---|---|---|---|---|
| (A) Lateral | ||||
| Pond (Predator regime) | 4.714 | 176 | 1661.4 | <0.0001 |
| Predator regime | 13.934 | 22 | 218 | <0.0001 |
| Log centroid size | 9.891 | 22 | 218 | <0.0001 |
| (B) Dorsal | ||||
| Pond (Predator regime) | 8.633 | 80 | 1467.3 | <0.0001 |
| Predator regime | 24.967 | 10 | 230 | <0.0001 |
| Log centroid size | 25.012 | 10 | 230 | <0.0001 |
Figure 4The relationship between Gosner stage and log centroid size for tadpoles from ponds with fish and invertebrate predators.
ANCOVA results where log centroid size was dependent on pond nested within predator regime (F approximation based on Wilk’s Lambda), predator regime, Gosner stage, and the interaction of predator regime and Gosner stage
| Effect | F | Num DF | Den DF |
|
|---|---|---|---|---|
| Pond (Predator regime) | 20.27 | 8 | 226 | <0.0001 |
| Predator regime | 124.90 | 1 | 226 | <0.0001 |
| Gosner stage | 425.27 | 1 | 226 | <0.0001 |
| Predator regime * Gosner stage | 4.90 | 1 | 226 | 0.028 |