Spatial asymmetries in connectivity influence colonization−extinction dynamics


Movement has broad implications for many areas of biology, including evolution, community and population ecology. Movement is crucial in metapopulation ecology because it facilitates colonization and reduces the likelihood of local extinction via rescue effects. Most metapopulation modeling approaches describe connectivity using pair-wise Euclidean distances resulting in the simplifying assumption of a symmetric connectivity pattern. Yet, assuming symmetric connectivity when populations show net asymmetric movement patterns may result in biased estimates of colonization and extinction, and may alter interpretations of the dynamics and conclusions regarding the viability of metapopulations. Here, we use a 10-year time series on a wind-dispersed orchid Lepanthes rupestris that anchors its roots in patches of moss growing on trees or boulders along streams, to test for the role of connectivity asymmetries in explaining the colonization−extinction dynamics of this orchid in a network of 975 patches. We expected that wind direction could highly alter dispersal direction in this orchid. To account for this potential asymmetry, we modified the connectivity measure traditionally used in metapopulation models to allow for asymmetric effective distances between patches and subsequently estimated colonization and extinction probabilities using a dynamic occupancy modeling approach. Asymmetric movement was prevalent in the L. rupestris metapopulation and incorporating potential dispersal asymmetries resulted in higher colonization estimates in larger patches and more accurate models. Accounting for dispersal asymmetries may reveal connectivity effects where they were previously assumed to be negligible and may provide more reliable conclusions regarding the role of connectivity in patch dynamics.

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Miguel Acevedo
Miguel Acevedo
Assistant Professor of Quantitative Wildlife Population Ecology

My research interests include global change, lizard malaria, and quantitative applications for conservation planning.