Dr. Ian Wang is an assistant professor in the Department of Environment Science, Policy, and Management at UC Berkeley and has spent the bulk of his career asking questions and developing techniques that further the general field of landscape genetics. Dr. Wang was a visiting seminar speaker here at Ohio State a couple of weeks ago, and he graciously volunteered to answer some questions based on our conversations during his visit:
The Molecular Ecologist recently published a brief review of the landscape genetics field. What do you think is next?
Genomic datasets have just brought us into the realm of adaptive landscape genetics, and there are certainly many interesting avenues now open in that area. In the next few years, I think we’ll also see more comparative landscape genetics studies – some of which will tell us about how different species respond to the same underlying landscape and some of which will demonstrate how spatial genetic patterns in single species vary across different landscapes and through time.
One of the main themes in many reviews about landscape genetics is the need for more biological knowledge of study organisms. You’ve worked in some very well-studied groups (Caribbean anoles) and some lesser understood groups. Do you support an emphasis on more natural history awareness?
I think that more natural history awareness is certainly a good thing. Natural history can provide a good foundation for landscape genetics and can help us properly interpret results and make sure we’re accounting for all of the important factors. It can also be especially important for putting the results of landscape genetic studies into a broader context.
At the same time, there are also some great examples from landscape genetics that taught us something about an organism that we didn’t know from its natural history – for instance, in species with cryptic life histories. So, landscape genetics can also be valuable when we don’t have a good natural history understanding of a species or to correct our misunderstanding of one.
What are some of the difficulties in asking questions that have contemporary and historical components using neutral genetic variation?
The difficulties are numerous: historical effects can be long-lasting and hard to disentangle from contemporary effects; historical landscapes must be measured or reconstructed accurately; demographic histories and metapopulation processes both come into play; and landscapes and processes can fluctuate through time as well. There are some lab groups developing methods explicitly aimed at dealing with these problems, and I look forward to seeing what they work out.
For examining historical effects, Amanda Zellmer and Lacey Knowles’ paper on “Disentangling the effects of historic vs. contemporary landscape structure on population genetic divergence,” Qixin He and Knowles’ “Integrative testing of how environments from the past to the present shape genetic structure across landscapes,” Rodney Dyer et al.’s ” Landscape modelling of gene flow: improved power using conditional genetic distance derived from the topology of population networks,” and Rachael Dudaniec et al’s “Current and historical drivers of landscape genetic structure differ in core and peripheral salamander populations” are all good reads.
There are a glut of new statistical methods for analyzing genetic, geographic, and sometimes phenotypic data (GDM, SEM, BEDASSLE, etc). Do you see more of an emphasis of phenotype on future isolation-by-environment studies?
Probably – there’s always been an interest in adaptive phenotypic variation and connecting genotype to phenotype to environment, and IBE and landscape genetics provide a good framework for those efforts. I think this is also an area where landscape genetics will need to connect with other approaches (including traditional experimental approaches) for looking at the mechanisms driving phenotypic and genetic divergence across environments.
If a student is interested in your field, what are a few of your most-recommended reads?
There are so many good papers in landscape genetics these days; I usually end up giving them a really long reading list. I think Andrew Storfer’s “Putting the ‘landscape’ in landscape genetics” review is a great overview of the field, as are Helene Wagner and Marie-Josee Fortin’s ” A conceptual framework for the spatial analysis of landscape genetic data,” Victoria Sork and Lisette Waits’ “Contributions of landscape genetics – approaches, insights, and future potential,” and Sean Schoville et al.’s “Adaptive genetic variation on the landscape.” Erin Landguth’s work on simulation methods for landscape genetics and the approaches developed by Gideon Bradburd, like Bedassle and SpaceMix, are definitely worth reading for anyone interested in working landscape genetics.
I also think Andrew Hendry et al.’s “Evolutionary inferences from the analysis of exchangeability,” Patrik Nosil et al.’s “Divergent selection and heterogeneous genomic divergence,” Rose Andrew et al.’s, “Adaptation with gene flow across the landscape in a dune sunflower,” and Jeremy Yoder et al.’s “Genomic signature of adaptation to climate in Medicago truncatula” all have some really important ideas for landscape genetics as well.
I also try to regularly highlight some of the top new landscape genetics studies for F1000.
As a new hire at Berkeley, do you have any advice for Post docs and graduate students who are out looking for a position in academia?
I don’t know if there’s any secret formula. I think you just have to do good work and do a lot of it. If you can develop a valuable skill set and be creative in your problem solving approaches, those will probably help too.
Andrew RL, Ostevik KL, Ebert DP, Rieseberg LH (2012) Adaptation with gene flow across the landscape in a dune sunflower. Molecular Ecology, 21, 2078–2091.
Bradburd GS, Ralph P, Coop G (2013) Disentangling the effects of geographic and ecological isolation on genetic differentiation. Evolution, 67, 3258–3273.
Dudaniec RY, Spear SF, Richardson JS, Storfer A (2012) Current and historical drivers of landscape genetic structure differ in core and peripheral salamander populations. PLOS One, 7, e36769.
Dyer RJ, Nason JD, Garrick RC (2010) Landscape modelling of gene flow: improved power using conditional genetic distance derived from the topology of population networks. Molecular Ecology, 19, 3746–3759.
He Q, Edwards DL, Knowles LL (2013) Integrative testing of how environments from the past to the present shape genetic structure across landscapes. Evolution, 67, 3386–3402.
Hendry AP, Kaeuffer R, Crispo E, Peichel CL, Bolnick DI (2013) Evolutionary inferences from the analysis of exchangeability. Evolution, 67, 3429–3441.
Nosil P, Funk DJ, Ortiz-Barrientos D (2009) Divergent selection and heterogeneous genomic divergence. Molecular Ecology, 18, 375–402.
Schoville SD, Bonin A, François O et al. (2011) Adaptive Genetic Variation on the Landscape: Methods and Cases. Annual Review of Ecology, Evolution, and Systematics, 43, 120830113150004.
Sork VL, Waits L (2010) Contributions of landscape genetics – Approaches, insights, and future potential. Molecular Ecology, 19, 3489–3495.
Storfer A, Murphy MA, Evans JS et al. (2007) Putting the “landscape” in landscape genetics. Heredity, 98, 128–42.
Wagner HH, Fortin M-J (2013) A conceptual framework for the spatial analysis of landscape genetic data. Conservation Genetics, 14, 253–261.
Wang IJ, Bradburd GS (2014) Isolation by Environment. Molecular Ecology, 23, 5649–5662.
Yoder JB, Stanton-Geddes J, Zhou P et al. (2014) Genomic signature of adaptation to climate in Medicago truncatula. Genetics, 196, 1263–1275.
Zellmer AJ, Knowles LL (2009) Disentangling the effects of historic vs. contemporary landscape structure on population genetic divergence. Molecular Ecology, 18, 3593–3602.