Benjamin J. Ridenhour

THE EVOLUTIONARY RESPONSE OF PREDATORS TO DANGEROUS PREY: HOTSPOTS AND COLDSPOTS IN THE GEOGRAPHIC MOSAIC OF COEVOLUTION BETWEEN GARTER SNAKES AND NEWTS

Abstract The “geographic mosaic” approach to understanding coevolution is predicated on the existence of variable selection across the landscape of an interaction between species. A range of ecological factors, from differences in resource availability to differences in community composition, can generate such a mosaic of selection among populations, and thereby differences in the strength of coevolution. The result is a mixture of hotspots, where reciprocal selection is strong, and coldspots, where reciprocal selection is weak or absent, throughout the ranges of species. Population subdivision further provides the opportunity for nonadaptive forces, including gene flow, drift, and metapopulation dynamics, to influence the coevolutionary interaction between species. Some predicted results of this geographic mosaic of coevolution include maladapted or mismatched phenotypes, maintenance of high levels of polymorphism, and prevention of stable equilibrium trait combinations. To evaluate the potential for the geographic mosaic to influence predator-prey coevolution, we investigated the geographic pattern of genetically determined TTX resistance in the garter snake Thamnophis sirtalis over much of the range of its ecological interaction with toxic newts of genus Taricha. We assayed TTX resistance in over 2900 garter snakes representing 333 families from 40 populations throughout western North America. Our results provide dramatic evidence that geographic structure is an important component in coevolutionary interactions between predators and prey. Resistance levels vary substantially (over three orders of magnitude) among populations and over short distances. The spatial array of variation is consistent with two areas of intense evolutionary response by predators (“hotspots”) surrounded by clines of decreasing resistance. Some general predictions of the geographic mosaic process are supported, including clinal variation in phenotypes, polymorphism in some populations, and divergent outcomes of the interaction between predator and prey. Conversely, our data provide little support for one of the major predictions, mismatched values of interacting traits. Two lines of evidence suggest selection is paramount in determining population variation in resistance. First, phylogenetic information indicates that two hotspots of TTX resistance have evolved independently. Second, in the one region that TTX levels in prey have been quantified, resistance and toxicity levels match almost perfectly over a wide phenotypic and geographic range. However, these results do not preclude the role the nonadaptive forces in generating the overall geographic mosaic of TTX resistance. Much work remains to fill in the geographic pattern of variation among prey populations and, just as importantly, to explore the variation in the ecology of the interaction that occurs within populations.

The influence of altitude and topography on genetic structure in the long‐toed salamander (Ambystoma macrodactulym)

A primary goal of molecular ecology is to understand the influence of abiotic factors on the spatial distribution of genetic variation. Features including altitudinal clines, topography and landscape characteristics affect the proportion of suitable habitat, influence dispersal patterns, and ultimately structure genetic differentiation among populations. We studied the effects of altitude and topography on genetic variation of long‐toed salamanders (Ambystoma macrodactylum), a geographically widespread amphibian species throughout northwestern North America. We focused on 10 low altitude sites (< 1200 m) and 11 high‐altitude sites in northwestern Montana and determined multilocus genotypes for 549 individuals using seven microsatellite loci. We tested four hypotheses: (1) gene flow is limited between high‐ and low‐altitude sites; and, (2) gene flow is limited among high‐altitude sites due to harsh habitat and extreme topographical relief between sites; (3) low‐altitude sites exhibit higher among‐site gene flow due to frequent flooding events and low altitudinal relief; and (4) there is a negative correlation between altitude and genetic variation. Overall FST values were moderate (0.08611; P < 0.001). Pairwise FST estimates between high and low populations and a population graphing method supported the hypothesis that low‐altitude and high‐altitude sites, taken together, are genetically differentiated from each other. Also as predicted, gene flow is more prominent among low‐altitude sites than high‐altitude sites; low‐altitude sites had a significantly lower FST (0.03995; P < 0.001) than high altitude sites (FST = 0.10271; P < 0.001). Use of Bayesian analysis of population structure (BAPS) resulted in delineation of 10 genetic groups, two among low‐altitude populations and eight among high‐altitude populations. In addition, within high altitude populations, basin‐level genetic structuring was apparent. A nonequilibrium algorithm for detecting current migration rates supported these population distinctions. Finally, we also found a significant negative correlation between genetic diversity and altitude. These results are consistent with the hypothesis that topography and altitudinal gradients shape the spatial distribution of genetic variation in a species with a broad geographical range and diverse life history. Our study sheds light on which key factors limit dispersal and ultimately species’ distributions.

Dos and don'ts of testing the geographic mosaic theory of coevolution

The geographic mosaic theory of coevolution is stimulating much new research on interspecific interactions. We provide a guide to the fundamental components of the theory, its processes and main predictions. Our primary objectives are to clarify misconceptions regarding the geographic mosaic theory of coevolution and to describe how empiricists can test the theory rigorously. In particular, we explain why confirming the three main predicted empirical patterns (spatial variation in traits mediating interactions among species, trait mismatching among interacting species and few species-level coevolved traits) does not provide unequivocal support for the theory. We suggest that strong empirical tests of the geographic mosaic theory of coevolution should focus on its underlying processes: coevolutionary hot and cold spots, selection mosaics and trait remixing. We describe these processes and discuss potential ways each can be tested.

When Is Correlation Coevolution

Studying the correlation between traits of interacting species has long been a popular approach for identifying putative cases of coevolution. More recently, such approaches have been used as a means to evaluate support for the geographic mosaic theory of coevolution. Here we examine the utility of these approaches, using mathematical and computational models to predict the correlation that evolves between traits of interacting species for a broad range of interaction types. Our results reveal that coevolution is neither a necessary nor a sufficient condition for the evolution of spatially correlated traits between two species. Specifically, our results show that coevolutionary selection fails to consistently generate statistically significant correlations and, conversely, that non‐coevolutionary processes can readily cause statistically significant correlations to evolve. In addition, our results demonstrate that studies of trait correlations per se cannot be used as evidence either for or against a geographic mosaic process. Taken together, our results suggest that understanding the coevolutionary process in natural populations will require detailed mechanistic studies conducted in multiple populations or the use of more sophisticated statistical approaches that better use information contained in existing data sets.

Reciprocal Selection at the Phenotypic Interface of Coevolution

Abstract Coevolutionary interactions depend upon a phenotypic interface of traits in each species that mediate the outcome of interactions among individuals. These phenotypic interfaces usually involve performance traits, such as locomotion or resistance to toxins, that comprise an integrated suite of physiological, morphological and behavioral traits. The reciprocal selection from species interactions may act directly on performance, but it is ultimately the evolution of these underlying components that shape the patterns of coevolutionary adaptation in performance. Bridging the macroevolutionary patterns of coevolution to the ecological processes that build them therefore requires a way to dissect the phenotypic interface of coevolution and determine how specific components of performance in one species exert selection on complimentary components of performance in a second species. We present an approach for analyzing the strength of selection in a coevolutionary interaction where individuals interact at random, and for identifying which component traits of the phenotypic interface are critical to mediating coevolution. The approach is illustrated with data from a predator-prey arms race between garter snakes and newts that operates through the interface of tetrodotoxin (TTX) and resistance to it.

Nesting fidelity and molecular evidence for natal homing in the freshwater turtle, Graptemys kohnii

Numerous studies of sea turtle nesting ecology have revealed that females exhibit natal homing, whereby they imprint on the nesting area from which they hatch and subsequently return there to nest as adults. Because freshwater turtles comprise the majority of reptiles known to display environmental sex determination (ESD), the study of natal homing in this group may shed light on recent evolutionary models of sex allocation that are predicated on natal homing in reptiles with ESD. We examined natal homing in Graptemys kohnii, a freshwater turtle with ESD, using mitochondrial sequencing, microsatellite genotyping and mark and recapture of 290 nesting females. Females showed high fidelity to nesting areas, even after being transplanted several kilometres away. A Mantel test revealed significant genetic isolation by distance with respect to nesting locations (r=0.147; p<0.05), suggesting that related females nest in close proximity to one another. The patterns of fidelity and genotype distributions are consistent with homing at a scale that may affect population sex ratios.

Antagonistic coevolution mediated by phenotypic differences between quantitative traits.

Abstract Many well-studied coevolutionary interactions between predators and prey or hosts and parasites are mediated by quantitative traits. In some interactions, such as those between cuckoos and their hosts, interactions are mediated by the degree of phenotype matching among species, and a significant body of theory has been developed to predict the coevolutionary dynamics and outcomes of such interactions. In a large number of other cases, however, interactions are mediated by the extent to which the phenotype of one species exceeds that of the other. For these cases—which are arguably more numerous—few theoretical predictions exist for coevolutionary dynamics and outcomes. Here we develop and analyze mathematical models of interspecific interactions mediated by the extent to which the quantitative trait of one species exceeds that of the other. Our results identify important differences from previously studied models based on trait matching. First, our results show that cyclical dynamics are possible only if the strength of coevolutionary selection exceeds a threshold and stabilizing selection acts on the interacting traits. Second, our results demonstrate that significant levels of genetic polymorphism can be maintained only when cyclical dynamics occur. This result leads to the unexpected prediction that maintenance of genetic polymorphism is enhanced by strong selection. Finally, our results demonstrate that there is no a priori reason to expect the traits of interacting species should match in any literal sense, even in the absence of gene flow among populations.

POLYGENIC TRAITS AND PARASITE LOCAL ADAPTATION

Abstract The extent to which parasites are locally adapted to their hosts has important implications for human health and agriculture. A recently developed conceptual framework—the geographic mosaic theory of coevolution—predicts that local maladaptation should be common and largely determined by the interplay between gene flow and spatially variable reciprocal selection. Previous investigation of this theory has predominately focused on genetic systems of infection and resistance characterized by few genes of major effect and particular forms of epistasis. Here we extend existing theory by analyzing mathematical models of host–parasite interactions in which host resistance to parasites is mediated by quantitative traits with an additive polygenic basis. In contrast to previous theoretical studies predicated upon major gene mechanisms, we find that parasite local maladaptation is quite uncommon and restricted to one specific functional form of host resistance. Furthermore, our results show that local maladaptation should be rare or absent in studies that measure local adaptation using reciprocal transplant designs conducted in natural environments. Our results thus narrow the scope over which the predictions of the geographic mosaic theory are likely to hold and provide novel and readily testable predictions about when and where local maladaptation is expected.

Identification of Selective Sources: Partitioning Selection Based on Interactions

Interspecific interactions are an inescapable reality in nature. The evolution of a species is largely determined by the environment, abiotic or biotic, in which selection occurs. Quantifying the magnitude of selection is crucial to understanding which aspects of the environment are important to the evolution of a species. Such knowledge is particularly important to fields such as conservation biology, which attempts to maintain a suitable environment for the prosperity of a species, or coevolution, where dynamics are determined by the strength of reciprocal selection between species. I present a general method by which selection due to interspecific interactions may be quantified. This technique is based on past quantitative genetic models of selection and can be used with other methodologies that build on these standard models. The approach may be expanded to account for n‐species interactions (e.g., a plant with two pollinators). Simulation studies conducted using this method indicate that the magnitude of selection between two species is strongly correlated with the presence of nonrandom interactions.

Effectiveness of Inactivated Influenza Vaccines in Preventing Influenza-Associated Deaths and Hospitalizations among Ontario Residents Aged ≥65 Years: Estimates with Generalized Linear Models Accounting for Healthy Vaccinee Effects

Background Estimates of the effectiveness of influenza vaccines in older adults may be biased because of difficulties identifying and adjusting for confounders of the vaccine-outcome association. We estimated vaccine effectiveness for prevention of serious influenza complications among older persons by using methods to account for underlying differences in risk for these complications. Methods We conducted a retrospective cohort study among Ontario residents aged ≥65 years from September 1993 through September 2008. We linked weekly vaccination, hospitalization, and death records for 1.4 million community-dwelling persons aged ≥65 years. Vaccine effectiveness was estimated by comparing ratios of outcome rates during weeks of high versus low influenza activity (defined by viral surveillance data) among vaccinated and unvaccinated subjects by using log-linear regression models that accounted for temperature and time trends with natural spline functions. Effectiveness was estimated for three influenza-associated outcomes: all-cause deaths, deaths occurring within 30 days of pneumonia/influenza hospitalizations, and pneumonia/influenza hospitalizations. Results During weeks when 5% of respiratory specimens tested positive for influenza A, vaccine effectiveness among persons aged ≥65 years was 22% (95% confidence interval [CI], −6%–42%) for all influenza-associated deaths, 25% (95% CI, 13%–37%) for deaths occurring within 30 days after an influenza-associated pneumonia/influenza hospitalization, and 19% (95% CI, 4%–31%) for influenza-associated pneumonia/influenza hospitalizations. Because small proportions of deaths, deaths after pneumonia/influenza hospitalizations, and pneumonia/influenza hospitalizations were associated with influenza virus circulation, we estimated that vaccination prevented 1.6%, 4.8%, and 4.1% of these outcomes, respectively. Conclusions By using confounding-reducing techniques with 15 years of provincial-level data including vaccination and health outcomes, we estimated that influenza vaccination prevented ∼4% of influenza-associated hospitalizations and deaths occurring after hospitalizations among older adults in Ontario.