|Title||Understanding the role of variability in fish population and community response to changing environmental conditions|
|Year of Publication||2017|
|Authors||Vidal, Tiffany E.|
|University||University of Georgia|
|Keywords||climate change, fish, Great Lakes, Perturbation, population dynamics, Statistical modeling, Variance partitioning|
Understanding how populations, and the ecosystems of which they are a part, respond to fluctuations in the environment is paramount for conservation, sustainable management of natural resources, and perpetuation of ecosystem function. In this dissertation, I evaluated the role of source components of variability as statistical indicators of large-scale ecologi- cal shifts, assessed the impact of age truncation on frequency signals in catches of a prey population over time, and investigated how a fish community has responded to a suite of environmental drivers. An analysis of variability in standardized fish catch data showed that spatial and temporal components of variability can be responsive major perturbation, offering finer-scale information about ecological reorganization than a mean response or to- tal variability alone. This analytical framework is flexible and could be broadly applicable to questions about population responses to a changing climate, physiographic differences, or monitoring program efficacy, for example. In the next chapter, I evaluated demographic changes to test the hypothesis that predation can induce similar effects as fishing. Age trun- cation of an important prey fish was associated with increased variability in recruitment and biomass, and greater correlation between these population metrics and temperature indices. These results suggest that the relative abundance of a fish population could be tracking the
environment more closely due to the loss of a buffering capacity otherwise associated with a broader reproducing age structure. Lastly, I went beyond single-species assessment by evaluating data for a fish community in relation to environmental fluctuations. Using gradi- ent forest methods, I was able to quantify the influence of different environmental signals on community indicators and identify thresholds along gradients of those environmental signals. Collectively, this research highlights tools and approaches to disentangle variability in stan- dardized fish catch data. The findings illustrate the complexity of patterns and correlative relationships that may exist between populations and their environment, which may change over time, and which are likely consequential for effectively managing dynamic ecological systems.