Wednesday, March 12, 2014

Evolution in small spaces: microgeographic adaptation and the spatial scale of evolution

Local adaptation has been the focus of intense study for many decades. Given how widely it has been observed across diverse taxa and ecological settings, one may not be too far out on a limb in saying that it is the default evolutionary scenario when suitable conditions exist. But we rarely reflect on what is “local” about this adaptation. In fact, the “local” moniker can be rather misleading. Local adaptation occurs when a population evolves traits that result in higher fitness of native individuals in the home environment relative to individuals from foreign populations, regardless of spatial scale. In a review article in this month’s issue of Trends in Ecology & Evolution, Mark Urban, Dan Bolnick, Dave Skelly, and I lay out the arguments for why we need to think about space more explicitly in studies of local adaptation, particularly at fine spatial scales.   

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.

Clausen, Keck and Hiesey’s 300 km transect and morphology of Potentilla glandulosa populations used in their common garden experiment. Individuals were transplanted to three locations (Stanford, Mather and Timberline) where the experiments were done, demonstrating a genetic basis for local adaptation at a large spatial scale.
Compare that example with local adaptation happening at much finer spatial scales. Evolutionary divergence at very small scales has largely been discounted as unlikely, due primarily to expectations of high gene flow that is expected to disrupt any incipient divergence. Yet more and more examples of fine-scale local adaptation are being documented and reported every year. The threespine stickleback (Gasterosteus aculeatus) provides important examples of this fine-scale adaptation. Data from Andrew Hendry’s lab suggest that stickleback body morphology diverges dramatically between fish separated by tens of meters between lake and adjoining stream habitats (e.g., Hendry & Taylor 2004; Moore & Hendry 2005). At even finer scales, Dan Bolnick’s group has found divergence in stickleback size, coloration, trophic position and diet across only a 1–2 meter cline of water depth in these highly mobile fish (e.g., Snowberg & Bolnick 2012).

Left: A typical inlet stream entering a lake habitat on Vancouver Island in British Columbia. Phenotypic divergence has been documented at this small spatial scale between stickleback inhabiting the inlet (and outlet) streams and the pond basin. Right: Within a lake, stickleback males can evolve divergent coloration, size and trophic position along a water depth gradient of only 1–2 meters. Photos by Dan Bolnick and Chad Brock.
One of the aims of our TREE review article is to highlight the empirical support for and theory behind evolutionary divergence at small spatial scales. However, “small spatial scales” is entirely relative to the study species being investigated and their dispersal attributes. For this reason, we advance three main concepts in our review:

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.
3. We evaluate seven mechanisms that can either initiate or amplify adaptive divergence at fine spatial scales. Microgeographic adaptation is of particular interest because it occurs despite the high potential for mixing between nearby populations, making it unlikely that neutral processes can generate appreciable variation at this scale. This divergence requires some process that increases the strength of natural selection or reduces maladaptive gene flow relative to dispersal ability. The full list can be found in the paper; however, non-random gene flow (e.g. habitat choice and phenotypic sorting), spatially autocorrelated selection regimes, and selective barriers against migrants are three mechanisms that may commonly contribute to microgeographic adaptation.

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.

The paper:

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.

http://www.cell.com/trends/ecology-evolution/abstract/S0169-5347(14)00015-9    

3 comments:

  1. Thanks for this interesting post!

    While reading the paper and in particular the list of mechanisms promoting microgeographic adaptation, I was wondering what differentiates a microgeographic scale from what is known as "sympatry"... Could you please comment on this?

    Otherwise, I thought it was a very good point to stress the fact that distance must be scaled with respect to dispersal abilities!

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  2. This is a really good question, given that the topic of spatial scale seems to be dominated by the 'sympatry' vs. 'allopatry' speciation debates.

    In our mind, the distinction between microgeographic and sympatry is fairly simple. 'Sympatry' is not tied to a quantitative scale, just a sometimes vague understanding that the ranges of species or ecotypes overlaps to some, unspecified, degree. 'Microgeographic', as we define it, is a quantitative threshold scaled to the dispersal ability of a species.

    More importantly, this microgeographic threshold (i.e., one Wright dispersal neighborhood) is the specific distance within which the role of neutral processes, such as drift, should play a minimal role in creating any divergence observed between populations. This is because of the high levels of gene flow expected at these scale.

    It seems that 'sympatry' is often (but not always) used to describe things living in the same space. In our evaluation of microgeographic adaptation, we are often referring to populations that are separate but located close to each other, relative to dispersal. Of course, in systems where populations (or demes or groups) of distinct ecotypes are less discrete and more interwoven on a landscape, classic sympatry may also be observed. If common garden and transplant experiments reveal adaptive divergence in such a system, this would represent sympatric divergence at the smallest end of the microgeographic scale, assuming non-zero dispersal. Colleagues have suggested that heterogeneous soil conditions can lead to these pattern in grasses and flowering herbaceous plants.

    Perhaps there are many more examples of systems that fit both the sympatric and microgeographic criteria. Or maybe they are exceedingly rare. We're hoping that the spatially scaled 'wright' measure of divergence will help us shed light on these interesting evolutionary patterns!

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  3. Hi Jonathon,
    I really enjoyed reading the article and this post. Scale and "local" adaptation are both topics that I'm fascinated by and I really like the idea of a quantifiable threshold with which to define "microgeographic". I work in alpine systems, and I suspect that microgeographic adaptation is relatively common in these environments. I'd like to try estimating the "wright" for some of the species I've worked with up there! Thanks for the thought-provoking piece.

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