MODELING SPECIES DISTRIBUTIONS: APPLICATIONS AND METHODS FOR MARINE BIOGEOGRAPHY AND CONSERVATION

• Main Author: Owens, Hannah L.
• Other Authors: Peterson, Andrew Townsend, Wiley, Edward O, Mort, Mark, Smith, William Leo, Egbert, Stephen
• Format: Doctoral or Postdoctoral Thesis
• Language: English
• Published: University of Kansas 2015
• Subjects: Biology; Ecology; Systematic biology; biogeography; character reconstruction; ecological niche modeling; Gadinae; Latimeria; Arctic; Pacific; Climate change
• Online Access: http://hdl.handle.net/1808/19185; http://dissertations.umi.com/ku:13884

I employed multidisciplinary approaches for understanding distributions of marine fishes in the present, past, and future, and for considering more broadly the historical role of primary research in policy decisions. In chapter 1, I generated ecological niche models (ENMs) for Latimeria chalumnae using two different modeling algorithms; these models anticipated occurrences of L. chalumnae's sister species, L. menadoensis, but sample sizes were not large enough to assess the statistical significance of these species' niche similarity. Furthermore, the range of coelacanths may extend beyond their presently known distributions; future exploration may reveal additional populations of these elusive fishes. In chapter 2, I developed a holistic biogeographic history of codfishes in the subfamily Gadinae. I found both ecological niche and geographic distributions of gadine fishes to be largely conservative, but two clades, tomcods and crown cods, included both Pacific and Atlantic species. Divergence in both clades was estimated to have begun in the Pliocene; environmental tolerance reconstructions support temperate origins of both clades, and cyclical Arctic ice formation may have driven divergence. In chapter 3, I addressed the role of general circulation model (GCM) bias as a significant source of uncertainty in estimates of species' potential distributional responses to climate change. ENMs of 15 gadine species calibrated using an observation-based dataset and a dataset derived from the CCSM4 GCM showed areas of disagreement concordant with known GCM biases. Consciousness of bias in GCM data will allow researchers and policy makers to identify areas of particular concern for biodiversity more realistically. Finally, in chapter 4, I explored the evolution of the relationship between policy makers and researchers through the lens of the U.S. Fisheries Service. Building cooperative capacity between these two groups led to a more systematic understanding of the oceans, and thus to success in reducing numbers of ...