PARENT SESSION
Oral Session # 31: Reserve Design and Planning.
Presiding: J Franklin
Tuesday, August 5. 1:30 PM to 5:00 PM, SITCC Meeting Room 105.
Predicting recovery patterns in short and long-lived organisms.
Lewison, Rebecca *,1, Heppell, Selina2, 1 Nicholas School of the Environment and Earth Science, Beaufort, NC, US2 Department of Fisheries and Wildlife, Corvallis, OR, US
ABSTRACT- Life history theory has been used to evaluate the effect of different demographic profiles on population growth rates. These comparisons have served to place organisms into broad categories — long vs. short lived, high vs. low fecundity (effort), delayed or early reproduction. Life history theory also makes predictions about a population's ability to recover from a collapse, such as one mediated by severe environmental or anthropogenic factors. How useful are life history characterizations to projecting the recovery process? Can we predict post-disturbance population trends for species of conservation concern? Large, historical pulse disturbances that have occurred in the past 30 years provide a natural experiment to test these predictions. To test the utility of demographic profiles to predict recoveries, we construct a standard population model for each species based on all available demographic data. Using time series data (pre and post disturbance), we then compare model-predicted and observed recovery trends for a range of short and long lived species. For cases where the demographic model projects a recovery, but none was observed, we explore the likelihood alternate hypotheses, such as inaccurate demographic estimates, Allee effects, or compensatory mortality from another source. Our comparisons suggest the utility of demographic profiles to predict recovery may be species specific, as there were no clear trends in the success of the model to capture the post-disturbance trajectories.
Key words: recovery, demographic modeling, Population , disturbance