For example, the classic common garden experiment by Clausen, Keck and Hiesey in the 1930s was a beautiful demonstration of local adaptation in Potentilla glandulosa, a small flowering herb that shows clear divergence in several traits along a ~300 km transect (and 3.6 km elevation gradient). This is an example of local adaptation at a large spatial scale and, more importantly, with the low gene flow expected between the populations investigated. In this sense, adaptive divergence in Potentilla will not surprise most evolutionary ecologists – populations experience very different environments and share little gene flow, allowing them to adapt to their local natural selection regimes without intrusion of maladaptive gene flow.
1. We propose a metric called the “wright” that measures phenotypic divergence across space while standardizing this divergence based on the dispersal of the organism. The “wright” is scaled to the dispersal neighborhood of a species or population, representing all of the individuals located within a radius extending two standard deviations from the mean of the dispersal distribution (i.e., dispersal kernel). Scaling the metric based on dispersal allows comparisons of the degree of adaptive divergence among species with very different dispersal abilities. For example, significant phenotypic divergence between two populations of songbirds situated 100 meters apart will be far more unexpected than divergence between snail populations over the same Euclidean distance. However, by scaling the divergence observed by the number of dispersal neighborhoods separating those 100 meters, we can compare the differentiation between birds and snails in a meaningful way. We coined the term “wright” for this metric because of Sewall Wright’s development of the dispersal neighborhood (also called the “gene flow neighborhood”, “Wright’s neighborhood” or “panmictic unit”), and the fact that it is a direct analog to the previously defined “haldane”, a measure of divergence through time.
2. We establish a threshold for distinguishing evolution at fine spatial scales, and formalize the definition of microgeographic adaptation. The microgeographic term has long been used, albeit inconsistently, to describe local adaptation at small spatial scales. This includes divergence across 25 meters in snails to 40 kilometers in brown trout. In order to be applied consistently across studies and species, we define microgeographic adaptation as adaptive divergence occurring within one dispersal neighborhood, an area where dispersal is expected to be frequent enough to prevent genetic drift. In this way, microgeographic adaptation is defined as a special case of local adaptation occurring at spatial scales where populations should experience high gene flow based on the expected levels of dispersal.
Top: A hypothetical landscape with three forest patches of the ‘light’ and ‘dark’ variety supporting populations of a moth species with two distinct color morphs. Each morph has higher fitness on the trees more closely matching their color and providing better camouflage. Bottom: The dispersal distribution (i.e., kernel) for this moth overlaid on the focal ‘light’ forest patch. The red circle delineates the dispersal neighborhood proposed by Wright, with a radius of two standard deviations from the mean of the kernel. Microgeographic adaptation occurs when two populations separated by less than one neighborhood radius adaptively diverge (e.g., the moth morphs diverge between the two forest patches under the kernel). Divergence between sites outside of this neighborhood would be considered local adaptation, but not microgeographic (e.g., between the light forest and the dark forest patch to the left). Adapted from Richardson et al. 2014.
We also highlight notable examples of microgeographic adaptation, consider broader implications of fine-scale adaptation for ecology and evolutionary biology, and conclude with a discussion of the immense opportunities that exist to more explicitly integrate spatial scale into evolutionary ecology. This includes specific recommendations for evaluating evolutionary processes at fine spatial scales.
The most salient messages we hope result from this article are that (1) we need to start considering space explicitly by incorporating spatial considerations into any study design, (2) understanding the role of dispersal and gene flow is critical to understanding the scale of evolution, and researchers should make a more concerted effort to characterize and quantify the dispersal distributions of our study species, (3) researchers should integrate observations of natural selection, standard experimental methods (e.g, common garden and transplant experiments) and innovative approaches (e.g., introduction and tracking of maladapted genotypes) with an eye towards understanding the minimum scale of evolutionary divergence and the mechanisms driving this divergence, and (4) a standard measure of evolution across space is needed to compare divergence across multiple species. Our hope is that the “wright” will catalyze the collection of data needed to evaluate the generality of microgeographic adapation in nature. Abundant opportunities also exist for creative manipulations of natural selection, dispersal and the genetic makeup of populations in the wild in order to understand how evolution operates at small scales.
After our review was in press, we had a chance to present these ideas as part of a symposium at the January meeting of the American Society of Naturalists at Asilomar in California. The response then and since the article was published has been exceedingly positive. The one objection that has come up several times is from researchers asserting that we have known about and appreciated fine-scale adaptation for a long time. With some probing, however, what they are generally referring to is divergence occurring at spatial scales that are “surprising” to the investigator in that system. Perhaps that’s a necessary starting point, but with this article and the standardized “wright” metric we are trying to move away from subjective assessments of what scales are surprising, to quantitative evaluations of the spatial scale of evolution.
Richardson JL, Urban MC, Bolnick DI, Skelly DK. 2014. Microgeographic adaptation and the spatial scale of evolution. Trends in Ecology & Evolution 29 (3): 165-176.