COS 140-9 - Mechanism matters: The cause of fluctuations in boom-bust populations governs optimal habitat restoration strategy

Thursday, August 10, 2017: 10:50 AM
B113, Oregon Convention Center
Gina K. Himes Boor, Ecology, Montana State University, Bozeman, MT; Biology, Duke University, Durham, NC, Cheryl B. Schultz, School of Biological Sciences, Washington State University, Vancouver, WA, Elizabeth E. Crone, Biology, Tufts University, Medford, MA and William F. Morris, Department of Biology, Duke University, Durham, NC

Many populations exhibit boom-bust dynamics in which their numbers fluctuate dramatically over time. Past research has focused on identifying whether the cause of fluctuations is primarily exogenous, e.g., environmental stochasticity coupled with weak density dependence, or endogenous, e.g., over-compensatory density dependence. Far fewer studies have addressed whether the actual mechanism responsible for boom-bust dynamics matters with respect to species management. Here we ask whether the best strategy for managing fluctuations differs under exogenously versus endogenously driven boom-bust dynamics. We used spatially explicit individual based models to assess how simulated populations of Taylor’s checkerspot butterflies would respond habitat restoration strategies that varied in the level of resource patchiness – from a single large patch to multiple patches spaced at different distances.


We found that exogenously driven populations fared best under a single large patch of restored habitat, whereas endogenously driven populations benefited from patchily distributed resources. Our models showed that population fluctuations governed by endogenous dynamics could be dampened by intentionally fragmenting restored habitat, whereas fluctuations driven by exogenous dynamics could not be managed by manipulating the spatial arrangement of restored patches. The mechanism by which endogenously driven populations became more stable and exhibited lower extinction risk in patchily distributed resources was via slower population growth that precluding both the “boom” phases and – more importantly – the “bust” phases. Our findings underscore the need to understand basic demographic drivers in managed populations.