The potential for human-driven rapid evolution is clearly evident in domestication selection during captive breeding for production, such as for agriculture, agroforestry, hatcheries, and aquaculture. This artificial selection can lead to maladaptive traits that substantially affect survivorship and reproductive success in natural environments. In many cases cultured populations occur in the same or adjacent habitat as wild conspecifics, such that escape from captive populations can affect the fitness of wild populations. To evaluate of the relative efficacy of alternative management approaches to minimizing such unintended fitness consequences, I will present coupled demographic-quantitative genetic models applied to wild fish populations that receive inputs from hatcheries or aquaculture. For hatcheries, model analysis indicates that a "segregated hatchery" approach of breeding a different population to reduce interactions with the wild population can provide a viable alternative to an "integrated hatchery" approach of breeding a similar population to reduce fitness effects only if a strong natural selection event occurs between hatchery release and reproduction. This relative efficacy, conditional on the ordering of life cycle events, holds for the aquaculture case of comparing the relative fitness consequences of an extremely maladapted (i.e., nonlocal-origin, highly domesticated) stock to a weakly diverged cultured stock. Aquaculture model results also indicate that imperfect sterilization can still substantially reduce unintended fitness consequences, and that reducing escapees through low-level leakage is more effective at minimizing unintended fitness consequences than reducing an analogous number of escapees from large, rare pulses. These models apply insights from the theory of gene flow and local adaptation to the management of artificial propagation and extend that theory to include new dynamics such as assortative mating and variable exchange in time.
In recent years, it has become increasingly clear that studying the joint influence of genotypes, populations, communities and ecosystems may yield different dynamics than if any were studied alone. While researchers are generally excited by this prospect, as is often true of fields in their adolescence, researchers are currently struggling to understand precisely what is meant by these types of interactions and how can they be studied. In this presentation, I will attempt to provide some clarity on this issue by showing how the study of eco-evolutionary interactions represent a resurgence of intra- and interspecific density and frequency-dependence, but with an additional dimension. The resurgence comes from the fact that, although it has long been appreciated that these types of effects may be important in determining many aspects of evolutionary biology and ecology, including the definition of fitness and the stability of biological communities. The added dimension is that research on these interactions has generally taken place under the assumption of weak selection. The prospect that selection can be strong enough to significantly alter the genetic composition of a population on short timescales means to evolutionary biologists that models assuming weak selection may be only a special case and to ecologists that evolutionary dynamics cannot be ignored. I will show a heuristic model as an example of this definition and ask if these types of eco-evolutionary interactions are important in explaining life history evolution in Trinidadian guppies.
In this talk I explore how the shapes of predator-prey cycles change when the predator, the prey, or both species are evolving. Using theoretical eco-evolutionary models and fast-slow systems theory, I categorize the kinds of cycles that can arise when one or more species are evolving.
Classical ecological theory predicts that in the absence of evolution, prey peaks precede predator peaks and cycles have counter-clockwise orientation in the phase plane. Recent theoretical work shows that evolution in one species can drive antiphase cycles (where the species oscillate exactly out of phase) or cryptic cycles (where one species oscillates while the other remains constant). Here I present work on how coevolution can effectively reverse the cycle orientation of predator-prey systems, yielding clockwise cycles in the phase plane. I use this body of theory to categorize the signatures of (co)evolution in predator-prey oscillations. I then revisit published time series from phage-cholera, mink-muskrat, and gyrfalcon-rock ptarmigan systems and show that those systems exhibit clockwise cycles
The evolution of resistance to drugs used for combating infectious diseases has become one of the most serious public health problems in modern medicine. In this talk I will present some theoretical results that explore this problem from several different perspectives, with the goal of better mitigating the emergence and spread of resistance. I will show how simple mathematical models of the drug supply system, of the population-level epidemiology, and of the within-host dynamics of pathogen replication, can contribute to this goal. I will conclude by illustrating how these theoretical results suggest a new approach for preventing the evolution of resistance, and I will present some preliminary data from an experiment that tests these ideas.
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.
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.
We consider optimal control applied to the system of partial differential equations, difference equations and differential equations, respectively. The motivating examples are the competition of native-invasive species (cottonwood and salt cedar), the optimal harvesting of fisheries (Cod) and the harvesting of non-timber forest product. We derive the necessary conditions and the characterizations for the optimal control. Numerical examples are given for each application.
Host-parasite interactions have provided compelling evidence for the occurrence of evolution on ecological timescales, and have also shown that rapid evolution can have profound consequences for ecological dynamics. In my talk, I will focus on the causes and consequences of rapid evolution of Daphnia hosts in response to epidemics of a virulent fungal parasite. We have found that populations evolve rapidly in response to disease outbreaks, and that the type of evolution that occurs is influenced by the ecological context in which the host-parasite interaction is embedded. Moreover, we have shown that rapid evolution of host resistance can fundamentally alter ecological dynamics, driving the termination of parasite epidemics. I will also discuss new work that looks at tradeoffs between resistance and fecundity: while tradeoffs can strongly impact rapid evolution, they are rarely studied in natural populations. We have found that there is variation in costs of resistance in wild host populations, which may be related to previous selection on those populations.
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.
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.
Whether a small cell, a small genome, or a minimal set of chemical reactions with self-replicating properties, simplicity is beguiling. As Robert Austin said, quoting Leonardo da Vinci, "simplicity is the ultimate sophistication." Two diverging views of simplicity emerged in accounts of insect symbionts and cosmopolitan bacteria with small genomes. Ochman and Moran attributed the small genomes of insect symbionts to genetic drift caused by small effective population sizes (Ne). In contrast, streamlining theory attributes small cells and genomes to selection for the efficient use of nutrient resources in populations where Ne is large and nutrients limit growth. Streamlining theory was based on ideas advanced by Lynch and Connery, who showed that, in general, genome size is inversely related to effective population size (Ne), and argued that this was due to the proliferation of DNA that has self-propagating characteristics in populations with a small Ne. The discovery of small and abundant cosmopolitan marine bacteria with small genomes led directly to streamlining theory. The small genomes of bacterioplankton were interpreted as originating from the converse aspect of Lynch and Connery's argument - cases of extreme selection reducing unessential structures and producing minimized cells. Thus, the minimal characteristics of streamlined marine bacteria were attributed to large population sizes and selection favoring the efficient use of limiting resources, such as phosphorous and nitrogen, which are scarce in marine environments. Regardless of the cause of genome reduction, lost coding potential eventually dictates loss of function. The effect of reductive evolution on cellular autonomy was explored in detail in marine chemoheterotrophs of the SAR11 clade (Pelagibacterales), and also in the OM43 clade of marine methylotrophs. In these organisms, many unusual metabolic features have been traced to genome reduction. For example, SAR11 are deficient in assimilatory sulfate reduction genes, and genes for glycine biosynthesis, making them dependent on environmental sources of reduced sulfur and glycine. These observations were directly tied to difficulty culturing, leading to speculation that many other organisms abundant in nature might be difficult to culture because of complex nutritional requirements tied to streamlining selection. Recent evidence suggests that this hypothesis might be partly correct, and might apply broadly to other microbial ecosystems. Similar ideas about consequences of genome reduction were expressed in the Black Queen Hypothesis, which advanced arguments about co-evolutionary dynamics ensuing from genome streamlining. In the case of SAR11, detailed examples from metabolism suggest that evolution has taken paths that minimize genome size, but in many cases also minimize fitness compromises associated with co-evolutionary dynamics. These details matter, in that ocean warming is leading to the expansion of low-nutrient (oligotrophic) conditions, and low diversity communities dominated by streamlined microorganisms. It remains uncertain how these shifts will impact species connectedness and ecosystem stability.
Sustainable harvest refers to exploiting a resource so that it is not depleted or permanently damaged. Sustainability is traditionally assessed in purely demographic terms. However, there is an increasing realization that genetic composition of the harvested individuals and those left behind typically differ; effects of such selective removals will accumulate over time and result in evolutionary change. Significant changes can often be detected after just few generations of intensive harvest. In this talk I summarize the present knowledge about management implications of this fisheries-induced evolution. I first discuss the potential consequences of fisheries-induced evolution on maximum sustainable yield, reference points, quality of catch, and resilience, establishing the case that fisheries-induced evolution needs to be accounted for in truly sustainable management. I then outline harvest strategies and tactics that may be used to minimize unwanted evolutionary changes.
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.
One of the key issues in the control of immunizing infections is determining the optimal level of vaccination in a population and achieving it. What is optimal for a whole population might not be best for an individual; and what is optimal for one country might not be optimal for their neighbours. This talk describes how the optimum level of vaccination results from interplay between epidemiological dynamics and the economic constraints that shape and influence control strategies on local, national and international levels.
From an epidemiological perspective alone, vaccination policies are guided by the basic reproductive number R0 - the average number of new infections caused by a single case in a wholly susceptible population. In order to locally interrupt transmission, vaccination coverage should be at or above the critical elimination threshold, 1 - 1/R0. However, when local economic constraints in the form of the relative costs of vaccination and infection are added to this picture, the optimal control level can range anywhere from no intervention to elimination; for a non-virulent pathogen, it may be optimal to sustain immunization well below the elimination threshold.
Turning to consider multiple countries connected by migration, the incentives of one country to invest in vaccination are additionally dependent on their neighbours' vaccination coverage and infection status. In the absence of regional or global bodies that can impose a universal vaccination strategy, human mobility could promote free-riding on each others' vaccination efforts, leading to a below-optimal coverage (surprisingly, at a higher overall cost).
The last part of this talk outlines a potential solution to this problem, specifically the use of coalition formation as a regional public health tool. Theory suggests that self-enforcing coalitions can lead to higher, more consistent and more uniform regional vaccination coverage even in the absence of global enforcement, but how do they became a reality?
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.
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.
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.
The rapid evolution of many species of applied significance occurs concomitantly with the expansion of those species' ranges. Important examples include invasive species, emerging pathogens, and species responding to climate change. In all of these cases, evolutionary change may result from evolutionary processes that are unique to the fundamentally spatial context of range expansion. In this talk, I will provide an overview of what those spatial evolutionary processes are, the mathematics required to account for them, and the impacts that they can have on the ecological dynamics of range expansion and on evolutionary outcomes for range-expanding species.
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 – relative to spatial variation – 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 › 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.
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
Biodiversity, in part, is maintained by two forms of coexistence mechanisms: stabilizing mechanisms that confer fitness advantages to species as they become rare, and equalizing mechanisms that minimize the intrinsic fitness difference between species. As stabilizing mechanisms involve feedbacks operating on ecological time scales, evolution hasn't been a key player in the coexistence literature. Empirical studies over the past years, however, have shown that evolution can impact population dynamics on ecological time scales. Inspired by these empirical findings, I will discuss preliminary results on how evolution mediates coexistence in communities structured by exploitative or apparent competition. These mathematical results highlight how coexistence can be driven by a cyclic eco-genetic feedback similar to an extended rock-paper-scissor game, how evolution simultaneously can act as stabilizing and equalizing mechanism, and how rates of evolution impact the effectiveness of these mechanisms.
Phytoplankton are microscopic plant-like organisms that live in the ocean and require sunlight, water, and nutrients for growth. Zooplankton are animals that eat phytoplankton and smaller species of zooplankton and are uniquely adapted to factors like light, temperatures, pollution and food. Grazing is one of the most important factors controlling the correlation between the two plankton communities. Although phytoplankton bloom is related to nutrient concentration and may decrease by grazing, the effect depends on zooplankton composition. We assume that evolutionary change can occur through random mutation of cell sizes of phytoplankton and zooplankton. Here, we analyze a co-evolutionary NPZ model to discover the pattern formation of co-evolution of phytoplankton and zooplankton cell size according to the level of nutrient and the type of evolution.