Geography and Genetics of Ecological Speciation in Pea Aphids

During ecological speciation, divergent natural selection drives evolution of ecological specialization and genetic differentiation of populations on alternate environments. Populations diverging onto the same alternate environments may be geographically widespread, so that divergence may occur at an array of locations simultaneously. Spatial variation in the process of divergence may produce a pattern of differences in divergence among locations called the Geographic Mosaic of Divergence. Diverging populations may vary in their degree of genetic differentiation and ecological specialization among locations. My dissertation examines the pattern and evolutionary processes of divergence in pea aphids (Acyrthosiphon pisum) on alfalfa (Medicago sativa) and clover (Trifolium pretense). In Chapter One, I examined differences among North American aphid populations in genetic differentiation at nuclear, sequence-based markers and in ecological specialization, measured as aphid fecundity on each host plant. In the East, aphids showed high host-plant associated ecological specialization and high genetic differentiation. In the West, aphids from clover were genetically indistinguishable from aphids on alfalfa, and aphids from clover were less specialized. Thus, the pattern of divergence differed among locations, suggesting a Geographic Mosaic of Divergence. In Chapter Two, I examined genomic heterogeneity in divergence in aphids on alfalfa and clover across North America using amplified fragment length polymorphisms (AFLPs). The degree of genetic differentiation varied greatly among markers, suggesting that divergent natural selection drives aphid divergence in all geographic locations. Three of the same genetic markers were identified as evolving under divergent selection in the eastern and western regions, and additional divergent markers were identified in the East. In Chapter Three, I investigated population structure of aphids in North America, France, and Sweden using AFLPs. Aphids on the same host plant were genetically similar across many parts of their range, so the evolution of host plant specialization does not appear to have occurred independently in every location. While aphids on alfalfa and clover were genetically differentiated in most locations, aphids from alfalfa and clover were genetically similar in both western North America and Sweden. High gene flow from alfalfa onto clover may constrain divergence in these locations.

Bioenergetic and ecological consequences of diet variability in Atlantic croaker Micropogonias undulatus

Atlantic croaker Micropogonias undulatus is a commercially and ecologically important bottom-associated fish that occurs in marine and estuarine systems from Cape Cod, MA to Mexico. I documented the temporal and spatial variability in the diet of Atlantic croaker in Chesapeake Bay and found that in the summer fish, particularly bay anchovies Anchoa mitchilli, make up at least 20% of the diet of croaker by weight. The use of a pelagic food source seems unusual for a bottom-associated fish such as croaker, but appears to be a crepuscular feeding habit that has not been previously detected. Thus, I investigated the bioenergetic consequences of secondary piscivory to the distribution of croaker, to the condition of individuals within the population and to the ecosystem. Generalized additive models revealed that the biomass of anchovy explained some of the variability in croaker occurrence and abundance in Chesapeake Bay. However, physical factors, specifically temperature, salinity, and seasonal dynamics were stronger determinants of croaker distribution than potential prey availability. To better understand the bioenergetic consequences of diet variability at the individual level, I tested the hypothesis that croaker feeding on anchovies would be in better condition than those feeding on polychaetes using a variety of condition measures that operate on multiple time scales, including RNA:DNA, Fulton's condition factor (K), relative weight (Wr), energy density, hepatosomatic index (HSI), and gonadosomatic index (GSI). Of these condition measures, several morphometric measures were significantly positively correlated with each other and with the percentage (by weight) of anchovy in croaker diets, suggesting that the type of prey eaten is important in improving the overall condition of individual croaker. To estimate the bioenergetic consequences of diet variability on growth and consumption in croaker, I developed and validated a bioenergetic model for Atlantic croaker in the laboratory. The application of this model suggested that croaker could be an important competitor with weakfish and striped bass for food resources during the spring and summer when population abundances of these three fishes are high in Chesapeake Bay. Even though anchovies made up a relatively small portion of croaker diet and only at certain times of the year, croaker consumed more anchovy at the population level than striped bass in all simulated years and nearly as much anchovy as weakfish. This indicates that weak trophic interactions between species are important in understanding ecosystem processes and should be considered in ecosystem-based management.

Modeling the Effects of Habitat Fragmentation on the Movements of the Mongolian Gazelle in the Eastern Mongolian Steppe

The Mongolian gazelle, Procapra gutturosa, resides in the immense and dynamic ecosystem of the Eastern Mongolian Steppe. The Mongolian Steppe ecosystem dynamics, including vegetation availability, change rapidly and dramatically due to unpredictable precipitation patterns. The Mongolian gazelle has adapted to this unpredictable vegetation availability by making long range nomadic movements. However, predicting these movements is challenging and requires a complex model. An accurate model of gazelle movements is needed, as rampant habitat fragmentation due to human development projects - which inhibit gazelles from obtaining essential resources - increasingly threaten this nomadic species. We created a novel model using an Individual-based Neural Network Genetic Algorithm (ING) to predict how habitat fragmentation affects animal movement, using the Mongolian Steppe as a model ecosystem. We used Global Positioning System (GPS) collar data from real gazelles to “train” our model to emulate characteristic patterns of Mongolian gazelle movement behavior. These patterns are: preferred vegetation resources (NDVI), displacement over certain time lags, and proximity to human areas. With this trained model, we then explored how potential scenarios of habitat fragmentation may affect gazelle movement. This model can be used to predict how fragmentation of the Mongolian Steppe may affect the Mongolian gazelle. In addition, this model is novel in that it can be applied to other ecological scenarios, since we designed it in modules that are easily interchanged.