Michael Walter Doebeli
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Dissertations completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest dissertations.
Understanding the mechanisms that generate and maintain diversity in ecological communities is perhaps the central question of ecological theory. Early theoretical contributions by Robert MacArthur formalized multi-species coexistence by considering how frequency dependent competition can naturally partition a continuous trait space into distinct niches. More recently, the adaptive dynamics framework has extended these ecological dynamics based on frequency dependent interactions to evolutionary timescales, creating a model capable of describing adaptive speciation and the emergence of diversity through natural selection. In this thesis I expand on these theories to help provide a greater understanding of the mechanisms that drive species coexistence and the maintenance of variation in ecological communities. In Chapter 2, I compare the diversity on ecological versus evolutionary timescales by comparing the diversity of randomly assembled communities to that of the ESS (evolutionary stable state, and the theoretical endpoint of evolution). I show that when randomly assembled, ecological communities can be saturated (having a diversity greater than the evolutionary stable state), yet saturation becomes prohibitively hard in higher dimensions. In Chapter 3, I show how Red Queen evolutionary dynamics can trap communities in low diversity metastable states. In Chapter 4, I combine perhaps the two most iconic theories of evolutionary diversity, the rugged fitness landscape and negative frequency-dependence, into one model. In doing so I show how on very rugged landscapes evolutionary dynamics mimic the local optimization and stochastic peak-shift dynamics predicted by rugged fitness landscape theory. However, the diversity each system can support is determined by the relative strength of frequency dependence and the shape of the global landscape, not the ruggedness. In Chapter 5, I consider the evolution of phenotypic heterogeneity, i.e., when genetically identical individuals have different phenotypes. I show that there is a race between diversification leading to a population of specialists and the evolution of heterogeneity, which leads to a division of labor.
Natural selection favors behaviors that increase an organism’s survival and reproduction. However, many organisms exhibit traits that benefit others at a cost to themselves, an apparent contradiction that Darwin called his “special difficulty”. The evolution of cooperation is an important biological question because it underlies group life and the construction of new levels of organization. For example, cells cooperate to make multicellular organisms and social insects as well as humans cooperate to establish large-scale societies. In this thesis, I attempt to increase our understanding of the evolution of cooperation and group life by developing four mathematical models. In Chapter 2, I study a question that dates back to Darwin: whether multilevel selection can be responsible for intergroup conflicts in human societies. Costly conflicts are collective action problems, and it is not clear what mechanisms could explain their prevalence. My model suggests one possible mechanism: the transmission of cultural traits between groups. Chapter 3 focuses on the interplay between the evolution of cooperation and environmental change. This model considers how cooperative interactions (public goods games), which evolve in response to changes in group size caused by environmental change, can either promote evolutionary rescue or, in some cases, lead to evolutionary suicide. In Chapter 4, I investigate the process of evolutionary branching (the diversification of a population into multiple strains), which can result from the evolution of cooperation between individuals. I show that, when multiple phenotypes experience evolutionary branching, the evolving phenotype distribution of the population can affect the direction of diversification. In the long-term, this may have important consequences for the evolution of division of labor. Finally, in Chapter 5, I consider how collectives of cooperating cells—including multicellular organisms and complex multi-species biofilms—reproduce to create new groups. I develop a multilevel selection model to investigate the consequences of various modes of reproduction, such as the production of single-cell gametes or vegetative fragmentation. Considered together, these four models expand our understanding of cooperation and group life.
Microbial metabolic activity drives biogeochemical cycling in virtually every ecosystem. Yet, microbial ecology and its role in ecosystem biochemistry remain poorly understood, partly because the enormous diversity found in microbial communities hinders their modeling. Despite this diversity, the bulk of global biogeochemical fluxes is driven by a few metabolic pathways encoded by a small set of genes, which through time have spread across microbial clades that can replace each other within metabolic niches. Hence, the question arises whether the dynamics of these pathways can be modeled regardless of the hosting organisms, for example based on environmental conditions. Such a pathway-centric paradigm would greatly simplify the modeling of microbial processes at ecosystem scales.Here I investigate the applicability of a pathway-centric paradigm for microbial ecology. By examining microbial communities in replicate "miniature" aquatic environments, I show that similar ecosystems can exhibit similar metabolic functional community structure, despite highly variable taxonomic composition within individual functional groups. Further, using data from a recent ocean survey I show that environmental conditions strongly explain the distribution of microbial metabolic functional groups across the world's oceans, but only poorly explain the taxonomic composition within individual functional groups. Using statistical tools and mathematical models I conclude that biotic interactions, such as competition and predation, likely underlie much of the taxonomic variation within functional groups observed in the aforementioned studies. The above findings strongly support a pathway-centric paradigm, in which the distribution and activity of microbial metabolic pathways is strongly determined by energetic and stoichiometric constraints, whereas additional mechanisms shape the taxonomic composition within metabolic guilds. These findings motivated me to explore concrete pathway-centric mathematical models for specific ecosystems. Notably, I constructed a biogeochemical model for Saanich Inlet, a seasonally anoxic fjord with biogeochemistry analogous to oxygen minimum zones. The model describes the dynamics of individual microbial metabolic pathways involved in carbon, nitrogen and sulfur cycling, and largely explains geochemical depth profiles as well as DNA, mRNA and protein sequence data. This work yields insight into ocean biogeochemistry and demonstrates the potential of pathway-centric models for microbial ecology.
Assortative mating by fitness has the potential population-level benefit of reducing migration load during times of environmental stasis, while allowing introgression of immigrant genetic variation in the event of environmental change. Assortative mating by fitness was examined with respect to within-population spread of a recombination modifier under selective sweep and mutation-selection balance scenarios. Only the latter scenario boosted modifier frequency, given a strength of assortative mating unlikely to be present in most species.In a second attempt to identify a new general advantage for sexual reproduction, the focus was on how inter-individual reproduction might reduce noise in inheritance and increase the power of selection. Individuals can experience good and bad "luck" at various stages of their life history, in any habitat, and it was found that combining gametes from two separate experiences of this ecological noise could indeed reduce noise in inheritance.The puzzle of small mammal population density cycles was approached from an evolutionary, rather than a population regulation perspective. An appropriate pattern of reproductive effort would seem key to survival through repeated population crashes to low numbers. Small mammals reproduce below their apparent potential through the decline and into the low phase of a cycle, and determining whether this reproductive pattern is adaptive is an important question. A standard cycling analytical model, the Rosenzweig-MacArthur, was carefully examined for the basis of this life history work, and found wanting even after considering several modifications. So an individual-based simulation was done. For simplicity and generality a novel mechanism was used: the "cumulative recent activity" of a population predicts several mortality causes, and has the property of delayed density dependence required to drive cycles. If animals cue from this quantity, then some controversy-causing experimental results might be explained.Branching theory and the simulation model showed that reproductive slowdown evolves under high mortality rates and, given a premium on short term persistence such as might exist at low numbers or densities, at low mortality rates. This explains the reproductive pattern observed in cycling mammals. The known reproductive suppression by stress physiology now appears to be adaptive, rather than inadvertent.
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Master's Student Supervision
Theses completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest theses.
There is growing evidence that disruptive selection generated by intraspecific resource competition may be a common mechanism for generating biological diversity. Adaptive dynamics models provide a framework describing how frequency dependent selection drives such diversification, but these models don’t consider the complexities that arise as a result of gene interactions. Here, we explore the relative effects of ecological and genetic constraints on diversification using an experimental system of Escherichia coli in which diversification is driven by frequency dependence based on resource use. Diversified populations consist of ecotypes that consume glucose and ac- etate at different rates, and a mutation in the arcA gene has been identified that has a large effect on this phenotype. By isolating clones of each eco- type from a previously diversified population, we find that the effect of the arcA mutation on rediversification depends on both the ecotype and the genetic background. While some of these observations are consistent with predictions made by adaptive dynamics models, others cannot be explained without also accounting for epistasis and genetic constraints, highlighting the importance of considering both ecological and genetic factors when pre- dicting diversification. Adaptation in this system also provides an example of an interaction between ecological and evolutionary processes, adding to a growing number of studies that exhibit a clear feedback between these two processes.
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