Maximal ecological diversity exceeds evolutionary diversity in model ecosystems.

Understanding community saturation is fundamental to ecological theory. While investigations of the diversity of evolutionary stable states (ESSs) are widespread, the diversity of communities that have yet to reach an evolutionary endpoint is poorly understood. We use Lotka-Volterra dynamics and trait-based competition to compare the diversity of randomly assembled communities to the diversity of the ESS. We show that, with a large enough founding diversity (whether assembled at once or through sequential invasions), the number of long-time surviving species exceeds that of the ESS. However, the excessive founding diversity required to assemble a saturated community increases rapidly with the dimension of phenotype space. Additionally, traits present in communities resulting from random assembly are more clustered in phenotype space compared to random, although still markedly less ordered than the ESS. By combining theories of random assembly and ESSs we bring a new viewpoint to both the saturation and random assembly literature.

Adaptive diversification and niche packing on rugged fitness landscapes.

Explaining the emergence of diversity and the coexistence of competing types has long been one of the main goals of ecological theory. Rugged fitness landscapes have often been used to explain diversity through the presence of local peaks, or adaptive zones, in the fitness landscape acting as available niches for different species. Alternatively, niche-packing and theories based on limiting similarity describe frequency-dependent selection leading to the organic differentiation of a continuous phenotype space into multiple coexisting types. By combining rugged carrying capacity landscapes with frequency-dependent selection, here we investigate the effects of ruggedness on adaptive diversification and stably maintained diversity. We show that while increased ruggedness often leads to a decreased opportunity for adaptive diversification, it is the shape of the global carrying capacity function, not the local ruggedness, that determines the diversity of the ESS and the total diversity a system can stably maintain.

Evolution to alternative levels of stable diversity leaves areas of niche space unexplored.

One of the oldest and most persistent questions in ecology and evolution is whether natural communities tend to evolve toward saturation and maximal diversity. Robert MacArthur's classical theory of niche packing and the theory of adaptive radiations both imply that populations will diversify and fully partition any available niche space. However, the saturation of natural populations is still very much an open area of debate and investigation. Additionally, recent evolutionary theory suggests the existence of alternative evolutionary stable states (ESSs), which implies that some stable communities may not be fully saturated. Using models with classical Lotka-Volterra ecological dynamics and three formulations of evolutionary dynamics (a model using adaptive dynamics, an individual-based model, and a partial differential equation model), we show that following an adaptive radiation, communities can often get stuck in low diversity states when limited by mutations of small phenotypic effect. These low diversity metastable states can also be maintained by limited resources and finite population sizes. When small mutations and finite populations are considered together, it is clear that despite the presence of higher-diversity stable states, natural populations are likely not fully saturating their environment and leaving potential niche space unfilled. Additionally, within-species variation can further reduce community diversity from levels predicted by models that assume species-level homogeneity.

Effects of forced taxonomic transitions on metabolic composition and function in microbial microcosms.

Surveys of microbial systems indicate that in many situations taxonomy and function may constitute largely independent ('decoupled') axes of variation. However, this decoupling is rarely explicitly tested experimentally, partly because it is hard to directly induce taxonomic variation without affecting functional composition. Here we experimentally evaluate this paradigm using microcosms resembling lake sediments and subjected to two different levels of salinity (0 and 19) and otherwise similar environmental conditions. We used DNA sequencing for taxonomic and functional profiling of bacteria and archaea and physicochemical measurements to monitor metabolic function, over 13 months. We found that the taxonomic composition of the saline systems gradually but strongly diverged from the fresh systems. In contrast, the metabolic composition (in terms of proportions of various genes) remained nearly identical across treatments and over time. Oxygen consumption rates and methane concentrations were substantially lower in the saline treatment, however, their similarity either increased (for oxygen) or did not change significantly (for methane) between the first and last sampling time, indicating that the lower metabolic activity in the saline treatments was directly and immediately caused by salinity rather than the gradual taxonomic divergence. Our experiment demonstrates that strong taxonomic shifts need not directly affect metabolic rates.

Rethinking the evolution of specialization: A model for the evolution of phenotypic heterogeneity.

Phenotypic heterogeneity refers to genetically identical individuals that express different phenotypes, even when in the same environment. Traditionally, "bet-hedging" in fluctuating environments is offered as the explanation for the evolution of phenotypic heterogeneity. However, there are an increasing number of examples of microbial populations that display phenotypic heterogeneity in stable environments. Here we present an evolutionary model of phenotypic heterogeneity of microbial metabolism and a resultant theory for the evolution of phenotypic versus genetic specialization. We use two-dimensional adaptive dynamics to track the evolution of the population phenotype distribution of the expression of two metabolic processes with a concave trade-off. Rather than assume a Gaussian phenotype distribution, we use a Beta distribution that is capable of describing genotypes that manifest as individuals with two distinct phenotypes. Doing so, we find that environmental variation is not a necessary condition for the evolution of phenotypic heterogeneity, which can evolve as a form of specialization in a stable environment. There are two competing pressures driving the evolution of specialization: directional selection toward the evolution of phenotypic heterogeneity and disruptive selection toward genetically determined specialists. Because of the lack of a singular point in the two-dimensional adaptive dynamics and the fact that directional selection is a first order process, while disruptive selection is of second order, the evolution of phenotypic heterogeneity dominates and often precludes speciation. We find that branching, and therefore genetic specialization, occurs mainly under two conditions: the presence of a cost to maintaining a high phenotypic variance or when the effect of mutations is large. A cost to high phenotypic variance dampens the strength of selection toward phenotypic heterogeneity and, when sufficiently large, introduces a singular point into the evolutionary dynamics, effectively guaranteeing eventual branching. Large mutations allow the second order disruptive selection to dominate the first order selection toward phenotypic heterogeneity.

Informed herbivore movement and interplant communication determine the effects of induced resistance in an individual-based model.

1. Plant induced resistance to herbivory affects the spatial distribution of herbivores, as well as their performance. In recent years, theories regarding the benefit to plants of induced resistance have shifted from ideas of optimal resource allocation towards a more eclectic set of theories that consider spatial and temporal plant variability and the spatial distribution of herbivores among plants. However, consensus is lacking on whether induced resistance causes increased herbivore aggregation or increased evenness, as both trends have been experimentally documented. 2. We created a spatial individual-based model that can describe many plant-herbivore systems with induced resistance, in order to analyse how different aspects of induced resistance might affect herbivore distribution, and the total damage to a plant population, during a growing season. 3. We analyse the specific effects on herbivore aggregation of informed herbivore movement (preferential movement to less-damaged plants) and of information transfer between plants about herbivore attacks, in order to identify mechanisms driving both aggregation and evenness. We also investigate how the resulting herbivore distributions affect the total damage to plants and aggregation of damage. 4. Even, random and aggregated herbivore distributions can all occur in our model with induced resistance. Highest levels of aggregation occurred in the models with informed herbivore movement, and the most even distributions occurred when the average number of herbivores per plant was low. With constitutive resistance, only random distributions occur. Damage to plants was spatially correlated, unless plants recover very quickly from damage; herbivore spatial autocorrelation was always weak. 5. Our model and results provide a simple explanation for the apparent conflict between experimental results, indicating that both increased aggregation and increased evenness of herbivores can result from induced resistance. We demonstrate that information transfer from plants to herbivores, and from plants to neighbouring plants, can both be major factors in determining non-random herbivore distributions.

Modeling the Effect of Herd Immunity and Contagiousness in Mitigating a Smallpox Outbreak.

The smallpox antiviral tecovirimat has recently been purchased by the U.S. Strategic National Stockpile. Given significant uncertainty regarding both the contagiousness of smallpox in a contemporary outbreak and the efficiency of a mass vaccination campaign, vaccine prophylaxis alone may be unable to control a smallpox outbreak following a bioterror attack. Here, we present the results of a compartmental epidemiological model that identifies conditions under which tecovirimat is required to curtail the epidemic by exploring how the interaction between contagiousness and prophylaxis coverage of the affected population affects the ability of the public health response to control a large-scale smallpox outbreak. Each parameter value in the model is based on published empirical data. We describe contagiousness parametrically using a novel method of distributing an assumed R-value over the disease course based on the relative rates of daily viral shedding from human and animal studies of cognate orthopoxvirus infections. Our results suggest that vaccination prophylaxis is sufficient to control the outbreak when caused either by a minimally contagious virus or when a very high percentage of the population receives prophylaxis. As vaccination coverage of the affected population decreases below 70%, vaccine prophylaxis alone is progressively less capable of controlling outbreaks, even those caused by a less contagious virus (R0 less than 4). In these scenarios, tecovirimat treatment is required to control the outbreak (total number of cases under an order of magnitude more than the number of initial infections). The first study to determine the relative importance of smallpox prophylaxis and treatment under a range of highly uncertain epidemiological parameters, this work provides public health decision-makers with an evidence-based guide for responding to a large-scale smallpox outbreak.