Workshop 2: Rapid Evolution and Sustainability
I will present three examples of eco-evolutionary dynamics. The studies vary in the degree to which they utilize mathematical models, the degree of empiricism, and the degree to which models and empirical findings are linked. Study 1 is concerned with a relatively artificial laboratory predator-prey system. This is the first system, for which a complete feedback cycle between ecological and evolutionary dynamics could be demonstrated. Study 2 reports evolution of resistance in a guppy-monogenean parasite-host system in a field experiment in tropical streams. Surprisingly, relaxed selection (absence of parasites) leads to increased resistance in this complex field situation. Study 3 analyzes a mathematical model of evolutionary rescue in a community context. The idea that species may be able to avoid extirpation due to rapid environmental change through equally rapid adaptation has only been tested for single-population systems. I will show that evolutionary rescue can also occur in complex communities and that it has a distinctive dynamic signature.
Niche theory tells us that in order for multiple species to coexist sustainably, they must evolve traits such that they diverge to use distinct niches. The neutral theory of biodiversity suggests that although similar species cannot coexist indefinitely, they can co-occur for hundreds to thousands of generations. Given that rapid evolution on ecological time scales can affect interactions between species and the outcome of competition, should we expect competitors to converge or diverge in their resource use? We simulated eco-evolutionary competitive dynamics and found that both convergence and divergence are both viable evolutionary strategies. Evolutionary and competitive outcomes depend on: (1) the rate of evolution relative to the rate of competitive exclusion, (2) the initial similarity of any two species of interest, and (3) whether evolution occurs in a community context, where indirect effects play a role in trait evolution. We are now attempting to test predictions from this model in controlled laboratory experiments with competing species of protozoa. Rapid evolution in a community context is increasingly being incorporated into both theoretical and empirical studies and is critical for understanding eco-evolutionary dynamics in complex communities
The past few years have witnessed a growing awareness that fishing might induce evolutionary changes in exploited stocks. With fishing mortalities sometimes exceeding natural mortalities by as much as 400%, adaptive responses to the altered selective environment caused by fishing seem inevitable. Case studies suggest that fisheries-induced evolution can occur within just a few generations, and that evolutionary recovery from the incurred changes may be slow. Many traits are likely to be affected, including maturation schedules, growth rates, reproductive investment, behavior, and morphology. As a result, fisheries-induced evolution may change a stock's yield, stability, and recovery potential. A new generation of fisheries scientists and managers will need scientific tools to cope with the opportunities and threats of fisheries-induced evolution.
When a species is introduced into a novel habitat, it faces a set of selection pressures that may differ considerably from those in its native range. Simultaneously, the arrival of a new species is likely to perturb the resident community and to change the selection pressures acting on resident species. These novel, and potentially strong, selection pressures set the stage for rapid evolution (and coevolution) of the introduced and the resident species. Does rapid evolution following a species introduction increase the chances of successful establishment by the non-native species, or does rapid evolution increase the resident community?s resistance to invasion? I address this question with population genetic models that link the ecological and evolutionary dynamics, allowing for eco-evolutionary feedbacks. As I describe the model results, I will highlight lessons for conservation and priorities for future research.
Marine algae are critically important to the health and well-being of the World Ocean. Not only do they form the base of the marine food web, they are also central players in the biogeochemical cycles of the ocean and the atmosphere. These organisms are amazingly diverse, occurring in 4 kingdom-level phylogenetic groupings and having body sizes spanning 7 orders of magnitude. Nevertheless, models suggest that the distribution of algal functional groups in the modern ocean is a straightforward function of light, nutrient availability, and temperature, all of which are likely to change significantly due to anthropogenic forcing in the coming decades. Attempts to predict how these changes might affect algal communities and the ecosystems they support are hampered by a lack of understanding of the pace of evolutionary adaptation in these populations. In this talk I will discuss the outstanding questions - how fast do mutations arise, how much do they effect algal fitness, and how will the dynamic ocean environment affect their dissemination in the population - and how these questions are being addressed by our lab and others using a combination of experimental evolution techniques and global ocean modeling.
Natural selection can act at multiple biological levels, often in opposing directions. This is particularly the case for pathogen evolution, which occurs both within the host it infects and via transmission between hosts, and for the evolution of cooperative behavior, where individually advantageous strategies are disadvantageous at the group level. In mathematical terms, these are multiscale systems characterized by stochasticity at each scale. I show how a simple and natural formulation of this can be viewed as a ball-and-urn process. This equivalent process has very nice mathematical properties, namely it converges weakly to the solution of an analytically tractable integro-partial differential equation. I then use properties of this limiting object to infer general properties of multilevel selection.
Pest species can affect the sustainability of some natural resources. Optimal control theory can be used to choose management strategies in models in involving a resource population and a pest population. Illustrative examples on managing gypsy moth populations will be given; issues of spatial spread will be included.
Despite the fact that the speaker is NOT an expert in the area of antibiotic resistance, he takes this opportunity to draw the attention of the audience to the subject. The reason is that antibiotic resistance poses such a big threat for our society. The hope is that the formulation and analysis of mathematical models may play in the future a bigger role in reducing this many-faceted problem, than it has so far. For concreteness, a few specific examples of models and their use are presented.
Historical DNA reveals dynamic patterns of recent microevolution in overfished populations of Atlantic codNina Therkildsen
Understanding whether natural populations are adapted to their local environments and how quickly they may evolve in face of altered conditions is important for predicting responses to global change and other anthropogenic impacts. Previously, it was expected that local adaptation would be absent or rare in marine fish such as Atlantic cod that presumably exhibits high levels of gene flow. Yet, recent evidence has suggested widespread adaptive divergence in this species, even over small geographic scales. In light of parallel reports of drastic fisheries-induced adaptive changes over decadal time scales, it remains uncertain, however, how important temporal variation in selection pressures within single populations are â€“ relative to spatial variation â€“ for shaping patterns of genetic diversity and adaptation. We here address this issue by analyzing historical DNA samples that provide unique opportunities to study microevolution directly at the genomic level in retrospective real time. Using recently developed high-throughput genotyping methods, we screened the temporal and spatial variation in â€º 1000 gene-associated single nucleotide polymorphisms (SNPs) across four populations of Atlantic cod over a period of up to 80 years. We identified 28 loci that showed highly elevated levels of differentiation ('outliers'), likely an effect of selection, in either time, space or both. Surprisingly, largely non-overlapping sets of loci were temporal outliers in the different populations and outliers from an early period showed almost complete stability during later periods. The contrasting micro-evolutionary trajectories among populations resulted in sequential shifts among spatial outliers, with no locus maintaining elevated differentiation throughout the study period. Simulations coupled with observations of significant temporally stable spatial structure at neutral loci suggest that population replacement or shifting migration patterns alone cannot explain the observed allele frequency variation, indicating that highly dynamic temporally and spatially varying selection has likely been important for shaping the observed patterns. These findings have important implications for our understanding of local adaptation and evolutionary potential in high gene flow organisms and underscore the need to carefully consider biocomplexity in fisheries management.
Adaptive dynamics theory has been devised to account for feedbacks between ecological and evolutionary processes. Doing so opens new dimensions to and raises new challenges about evolutionary rescue. Adaptive dynamics theory predicts that successive trait substitutions driven by eco-evolutionary feedbacks can gradually erode population size or growth rate, thus potentially raising the extinction risk. Even a single trait substitution can suffice to degrade population viability drastically at once and cause 'evolutionary suicide'. In a changing environment, a population may track a viable evolutionary attractor that leads to evolutionary suicide, a phenomenon called 'evolutionary trapping'. Evolutionary trapping and suicide are commonly observed in adaptive dynamics models in which the smooth variation of traits causes catastrophic changes in ecological state. In the face of trapping and suicide, evolutionary rescue requires that the population overcome evolutionary threats generated by the adaptive process itself. Evolutionary repellors play an important role in determining how variation in environmental conditions correlate with the occurrence of evolutionary trapping and suicide, and what evolutionary pathways rescue may follow. In contrast with standard predictions of evolutionary rescue theory, low genetic variation may attenuate the threat of evolutionary suicide, and small population sizes may facilitate escape from evolutionary traps.