Animal movement is typically studied at the population level, such that only the overall population size, average number of dispersers, mean dispersal distance, and average fecundity is assessed (Naranjo et al. 2009). While these population measures are readily determined with trapping or visual/auditory survey methods (Thomson et al. 2004; El-Sayed et al. 2006), this approach masks important variation among individuals that influences population dynamics (Nathan et al. 2012). The individuals that disperse, colonize a new habitat patch, and reproduce early in population expansion are a small and nonrandom portion of the source population, but have a disproportionately large impact on the growth and genetic composition of destination populations. 

Individuals vary in their sensitivity to local environmental conditions (e.g. density), causing some to disperse and others to stay (Meylan et al. 2009, Arendt 2015). While individual variation in dispersal tendency is well known, what is less clear is how individuality in dispersal affects the array of other traits relevant to population growth and environmental impact in local populations (Spiegel et al. 2017 and refs therein, Plard et al. 2019 and refs therein). Differing trends in sensitivity to local conditions among groups of dispersers, can produce clusters of similar phenotypes in local habitat patches, known as spatial sorting. Spatial sorting leads to assortative mating of similar phenotypes, such that dispersers at the range edge produce even better dispersers in the next generation, leading to spatial selection for dispersal behavior.

 

Spatial selection alone (excluding any effect of natural selection such as release from competition at the periphery of dispersal), can produce evolution of a population (Shine et al. 2011). However, it is extremely unlikely that spatial selection alone is acting on a population. Especially when we transfer the concept of spatial sorting from the expanding edge of an invasive species range to a more spatially complex environment, such as a metapopulation (multiple subpopulations connected via dispersal). At first glance, spatial sorting within a metapopulation appears to be only a transient state, if occurring at all, and may not have impacts on long-term metapopulation dynamics, because if multiple individuals are dispersing every generation, then there should continue to be genetic admixing of the population over time. However, if other life-history traits are genetically or phenotypically correlated with dispersal, then spatial sorting may still be a transient state within the metapopulation, but the sorting of other life-history traits can affect eco-evolutionary feedbacks within the metapopulation.

 

My research program aims to connect the hierarchical processes of individual variation in sensitivity to the environment with dispersal and spatial sorting to understand the ecological and evolutionary feedbacks that affect landscape population dynamics. Currently, I'm using the cowpea bean beetle (Callosobruchus maculatus), a pest that damages stored legume seeds, to:

 

1) Assess the extent to which larval feeding vibrations indicate competitor density and function as a cue for dispersal through recordings and playback experiments (click here for more information), and 

 

2) Determine traits that are genetically correlated with dispersal by comparing populations artificially selected for high and low dispersal propensity (click here for more information)

Cowpea Bean Beetle​

The bean beetle (Callosobruchus maculatus) is a classic species for studying metapopulation dynamics.  The beetle lives its entire life on legumes, such as black-eyed peas (Vigna unguiculata) and mung beans (Vigna radiata). Bean beetles are easy to maintain in the lab for multiple generations.  Adults live 1-2 weeks and do not require any food to survive.  Females lay eggs on beans, where the larvae will develop entirely inside the bean until they emerge as adults.

Funding Sources

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