Viviane M. de Oliveira

Effect of Landscape Structure on Species Diversity.

The effects of habitat fragmentation and their implications for biodiversity is a central issue in conservation biology which still lacks an overall comprehension. There is not yet a clear consensus on how to quantify fragmentation even though it is quite common to couple the effects of habitat loss with habitat fragmentation on biodiversity. Here we address the spatial patterns of species distribution in fragmented landscapes, assuming a neutral community model. To build up the fragmented landscapes, we employ the fractional Brownian motion approach, which in turn permits us to tune the amount of habitat loss and degree of clumping of the landscape independently. The coupling between the neutral community model, here simulated by means of the coalescent method, and fractal neutral landscape models enables us to address how the species–area relationship changes as the spatial patterns of a landscape is varied. The species–area relationship is one of the most fundamental laws in ecology, considered as a central tool in conservation biology, and is used to predict species loss following habitat disturbances. Our simulation results indicate that the level of clumping has a major role in shaping the species–area relationship. For instance, more compact landscapes are more sensitive to the effects of habitat loss and speciation rate. Besides, the level of clumping determines the existence and extension of the power-law regime which is expected to hold at intermediate scales. The distributions of species abundance are strongly influenced by the degree of fragmentation. We also show that the first and second commonest species have approximately self-similar spatial distributions across scales, with the fractal dimensions of the support of the first and second commonest species being very robust to changes in the spatial patterns of the landscape.

ENVIRONMENTAL HETEROGENEITY ENHANCES CLONAL INTERFERENCE

Abstract Clonal interference (CI) is a phenomenon that may be important in several asexual microbes. It occurs when population sizes are large and mutation rates to new beneficial alleles are of significant magnitude. Here we explore the role of gene flow and spatial heterogeneity in selection strength in the adaptation of asexuals. We consider a subdivided population of individuals that are adapting, through new beneficial mutations, and that migrate between different patches. The fitness effect of each mutation depends on the patch and all mutations considered are assumed to be unconditionally beneficial. We find that spatial variation in selection pressure affects the rate of adaptive evolution and its qualitative effects depend on the level of gene flow. In particular, we find that both low migration and high levels of heterogeneity lead to enhanced CI. In contrast, for high levels of migration the rate of fixation of adaptive mutations is higher when environmental heterogeneity is present. In addition, we observe that the level of fitness variation is higher and simultaneous fixation of multiple mutations tends to occur in the regime of low migration rates and high heterogeneity.

The effect of spatially correlated environments on genetic diversity–area relationships

Understanding the spatial patterns of genetic diversity and what causes them is an important outstanding question in ecology. Here we investigate the roles of spatial heterogeneity and system area in generating genome diversity, and study its dependence with sampled area. We study an individual-based model that incorporates natural selection on the habitat type and compare the effects of asexual and sexual reproductions. A key ingredient of the model is the possibility to tune the level of spatial heterogeneity among the habitats. Our results corroborate either the bi-phasic or tri-phasic scenarios, one phase corresponding to a power law regime, for the diversity-area relationship in both sexual and asexual populations, being the shape of the curve influenced by mutation rates and spatial correlation. These observations are verified for distinct sets of parameter values.

Adaptive walks on correlated fitness landscapes with heterogeneous connectivities

We propose a model for studying the statistical properties of adaptive walks on correlated fitness landscapes which are established in genotype spaces of complex structure. The fitness distribution on the genotype space follows either the bivariate Gaussian distribution or the bivariate exponential distribution. In both cases the degree of correlation of the fitness landscape can be tuned by using a single parameter. To perform the adaptive walks two distinct rules are applied: the random adaptation walk (RAW) and the gradient adaptation walk (GAW). While for the RAW the mean walk length, , is a monotonic increasing function of the connectivity of the genotype space, for the GAW is a one-humped function. The RAW produces longer adaptive walks compared to the GAW, though its performance is slightly poorer and thereby the local maxima reached by the GAW algorithm are usually closer to the global optimum of the fitness landscape.

Model inspired by population genetics to study fragmentation of brittle plates

We use a model whose rules were inspired by population genetics and language competition, the random capability growth model, to describe the statistical details observed in experiments of fragmentation of brittle plate-like objects, and in particular the existence of (i) composite scaling laws, (ii) small critical exponents τ associated with the power-law fragment-size distribution, and (iii) the typical pattern of cracks. The proposed computer simulations do not require numerical solutions of Newtons equations of motion, nor several additional assumptions normally used in discrete element models. The model is also able to predict some physical aspects which could be tested in new experiments of fragmentation of brittle systems.

A resource-based game theoretical approach for the paradox of the plankton

The maintenance of species diversity is a central focus in ecology. It is not rare to observe more species than the number of limiting resources, especially in plankton communities. However, such high species diversity is hard to achieve in theory under the competitive exclusion principles, known as the plankton paradox. Previous studies often focus on the coexistence of predefined species and ignore the fact that species can evolve. We model multi-resource competitions using evolutionary games, where the number of species fluctuates under extinction and the appearance of new species. The interspecific and intraspecific competitions are captured by a dynamical payoff matrix, which has a size of the number of species. The competition strength (payoff entries) is obtained from comparing the capability of species in consuming resources, which can change over time. This allows for the robust coexistence of a large number of species, providing a possible solution to the plankton paradox.