DYNAMICS OF THE SHORT TERM AND LONG TERM AVIAN DISTRIBUTIONS IN NORTH AMERICA - THE ROLES OF VEGETATION HEIGHT HETEROGENEITY AND CLIMATIC FACTORS

Understanding how biodiversity spatially distribute over both the short term and long term, and what factors are affecting the distribution, are critical for modeling the spatial pattern of biodiversity as well as for promoting effective conservation planning and practices. This dissertation aims to examine factors that influence short-term and long-term avian distribution from the geographical sciences perspective. The research develops landscape level habitat metrics to characterize forest height heterogeneity and examines their efficacies in modelling avian richness at the continental scale. Two types of novel vegetation-height-structured habitat metrics are created based on second order texture algorithms and the concepts of patch-based habitat metrics. I correlate the height-structured metrics with the richness of different forest guilds, and also examine their efficacies in multivariate richness models. The results suggest that height heterogeneity, beyond canopy height alone, supplements habitat characterization and richness models of two forest bird guilds. The metrics and models derived in this study demonstrate practical examples of utilizing three-dimensional vegetation data for improved characterization of spatial patterns in species richness. The second and the third projects focus on analyzing centroids of avian distributions, and testing hypotheses regarding the direction and speed of these shifts. I first showcase the usefulness of centroids analysis for characterizing the distribution changes of a few case study species. Applying the centroid method on 57 permanent resident bird species, I show that multi-directional distribution shifts occurred in large number of studied species. I also demonstrate, plain birds are not shifting their distribution faster than mountain birds, contrary to the prediction based on climate change velocity hypothesis. By modelling the abundance change rate at regional level, I show that extreme climate events and precipitation measures associate closely with some of the long-term distribution shifts. This dissertation improves our understanding on bird habitat characterization for species richness modelling, and expands our knowledge on how avian populations shifted their ranges in North America responding to changing environments in the past four decades. The results provide an important scientific foundation for more accurate predictive species distribution modeling in future.

SOCIAL AND ECOLOGICAL FACTORS INFLUENCING COLLECTIVE BEHAVIOR IN GIANT DANIO

A fundamental problem in biology is understanding how and why things group together. Collective behavior is observed on all organismic levels - from cells and slime molds, to swarms of insects, flocks of birds, and schooling fish, and in mammals, including humans. The long-term goal of this research is to understand the functions and mechanisms underlying collective behavior in groups. This dissertation focuses on shoaling (aggregating) fish. Shoaling behaviors in fish confer foraging and anti-predator benefits through social cues from other individuals in the group. However, it is not fully understood what information individuals receive from one another or how this information is propagated throughout a group. It is also not fully understood how the environmental conditions and perturbations affect group behaviors. The specific research objective of this dissertation is to gain a better understanding of how certain social and environmental factors affect group behaviors in fish. I focus on two ecologically relevant decision-making behaviors: (i) rheotaxis, or orientation with respect to a flow, and (ii) startle response, a rapid response to a perceived threat. By integrating behavioral and engineering paradigms, I detail specifics of behavior in giant danio Devario aequipinnatus (McClelland 1893), and numerically analyze mathematical models that may be extended to group behavior for fish in general, and potentially other groups of animals as well. These models that predict behavior data, as well as generate additional, testable hypotheses. One of the primary goals of neuroethology is to study an organism's behavior in the context of evolution and ecology. Here, I focus on studying ecologically relevant behaviors in giant danio in order to better understand collective behavior in fish. The experiments in this dissertation provide contributions to fish ecology, collective behavior, and biologically-inspired robotics.