The proximate causes of asymmetric movement across heterogeneous landscapes

Abstract

Asymmetric movements, in which the probability of moving from patch i to patch j is not necessarily the same as moving in the opposite direction, may be the rule more than the exception in nature where organisms move through spatially heterogeneous environments. Empirical tests of dispersal asymmetries are rare with even fewer tests of the mechanisms driving such patterns. Objectives We tested for the mechanisms of asymmetric movement in the cactus-feeding insect, Chelinidea vittiger, using a combination of observational and experimental approaches. Methods In the observational approach, we analyzed movements from mark-recapture data in a large plot for over 4–5 generations and tested for the role of differences in patch area and wind direction driving broad-scale asymmetric movements. In the field experiment, we translocated individuals to experimental arenas where we tested for the roles of patch area, wind, presence of conspecifics, and matrix height driving directed movements at fine spatio-temporal scales. Results We found that population-level patterns of movements in C. vittiger were generally asymmetric. At broad scales, observational data suggested that these asymmetries were related to variations in patch size, with movements being directed from small to large patches. At fine scales, experiments showed that movement was also directed from small to large patches, but this effect was mediated by the structure of the surrounding matrix. Conclusions Our results illustrate how and why movement asymmetries can occur across landscapes. Accounting for such asymmetries may improve our understanding and prediction of spatially structured population dynamics and landscape connectivity.

Publication
Landscape Ecology
Click the Cite button above to import publication metadata into your reference management software.
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.