COS 127-8
Modeling interactions between environmental and demographic factors in a rare endemic plant

Friday, August 9, 2013: 10:30 AM
L100H, Minneapolis Convention Center
Matthew Ryan Tye, Department of Biology, University of Central Florida, Orlando, FL
Pedro Quintana-Ascencio, Dept. of Biology, University of Central Florida, Orlando, FL
Eric S. Menges, Plant Ecology Program, Archbold Biological Station, Venus, FL
Carl W. Weekley, Archbold Biological Station, Venus, FL
Roberto Salguero-Gomez, Centre for Biodiversity and Conservation Science, The University of Queensland, Brisbane, Australia

In order to optimize management strategies for the conservation of threatened species, it is critical to understand the interplay between the demography of a species and its environment. However, this is often difficult for species with complex demography. Liatris ohlingerae is a rare endemic herb native to the Lake Wales Ridge of Central Florida. This perennial species has a complex life cycle characterized by three possible life history stages with disparate morphologies in each year: non-reproductive, reproductive and dormant. Previous analyses have shown that size within each of these stages significantly affects survival, growth and fecundity. Because of these factors, we constructed a multistage integral projection model incorporating these stages as well as continuous size data. This demographic framework allowed us to test how environmental covariates such as climate, habitat, population, herbivory, and time since fire influence the lifecycle of the species.


Our current modeling efforts indicated a strong negative effect of herbivory on the fecundity of reproductive individuals.  We also found that habitat and population influenced survival of both reproductive and non-reproductive individuals.  Our data indicated that individuals transitioning between reproductive to non-reproductive stages are likely to maintain a similar relative size, while individuals staying in the same stage across multiple years tended to increase in size. These results provide detailed demographic information that can be used by land managers and other decision makers to further inform conservation decisions. Our general modeling framework also facilitates the possibility of adapting this model to other species with multiple, demographically distinct life history stages.