Interview with the authors: historical barriers to gene flow in a fragmenting landscape

In a recent issue of Molecular Ecology, Drs. Maigret, Cox, and Weisrock published their work focused on copperhead snake response to habitat fragmentation. Interestingly, these researchers detected population structure putatively resulting from a historically important highway, even though most traffic has been shuttled to an alternative route for the last 50 years. Understanding the complexities of movement patterns in response to barriers is of increasing importance as our landscape becomes more and more fragmented. For more information, please see the full article and the interview with Dr. Maigret below. 

What led to your interest in this topic / what was the motivation for this study? The immense and rapid shift from forest to barren land and grassland which accompanies surface mining in central Appalachia is striking, especially when viewed from the air. Upwards of 20% of the land surface of some counties has been mined since 1980 through a process often termed “mountaintop removal”. The lack of research on the implications of this fragmentation was curious to me: why had such a major driver of forest loss garnered so little attention? Moreover, if we use next-generation sequencing, could we detect any effects of this land-use change on wildlife populations? It seemed like a nice natural experiment waiting to be investigated.

What difficulties did you run into along the way? Fieldwork was challenging: on top of the issues one deals with when trying to capture large numbers of secretive venomous snakes, nearly all the land in our study area is privately held, and thus gaining access to properties to collect tissue samples was time consuming. In terms of generating our data, obtaining enough DNA from our tissues (mainly scale clips) proved to be a challenge, though DNA quality was fortunately not an issue. Finally, given the diverse array of methods and subsampling protocols we used, optimizing our software pipeline took a little extra time. Thankfully, our university’s computing resources – including our associated staff and faculty – were more than adequate for the task at hand.

What is the biggest or most surprising innovation highlighted in this study? We found no evidence for an effect of mining or the current array of high-traffic roads on genetic differentiation; both of these features were hypothesized to be barriers to movement. But the most surprising part was what we did detect: a break in population similarity spatially coinciding with the path of a road which was a major highway for most of the 20th century. Previous research has suggested that highways can cleave populations of herpetofauna, and modeling work has suggested that these effects could persist for many years. We seem to have found evidence for a combination of these hypotheses, and subsampling suggested that we could have come to a similar conclusion with fewer markers and more missing data.

Moving forward, what are the next steps in this area of research? It will be interesting to see what unfolds as more genomic data is integrated into landscape genetics studies, and especially in landscapes with putative barriers of different ages or permeabilities. Re-analysis of existing data sets using (possibly) more sensitive methods, like the spatially-informed methods we used, might reveal barriers where none were detected using other approaches. As for surface coal mining, more study of the consequences of forest fragmentation – ideally, using species which might be more sensitive – could be very informative.

What would your message be for students about to start developing or using novel techniques in Molecular Ecology? Try to keep abreast of the new programs coming out. It seems like every month new approaches are being developed, and while the deluge of methods can be overwhelming at times, employing an assortment of different approaches can help enlighten one’s interpretation of genomic patterns.

What have you learned about methods and resources development over the course of this project? I’ve learned about the importance of integrating methods within an ecological framework. While a new method for analyzing genomic data is usually developed to fill a particular analytical gap, translating that goal into an ecological framework can make the method much more accessible to a broader range of researchers. And in general, doing one’s best to stay on top of the new methods coming online is important, if a little overwhelming at times.

Describe the significance of this research for the general scientific community in one sentence. Our results seem to suggest that the genomic legacy of human settlements and infrastructure can persist in wildlife populations beyond the lifespan of the infrastructure itself.

Describe the significance of this research for your scientific community in one sentence. With genomic data and statistical approaches that integrate spatial information, it might be possible to detect relatively weak genetic structuring in wild populations, and it may not require large amounts of the highest-quality data.

Maigret TA, Cox JJ, Weisrock DW. 2020. A spatial genomic approach identifies time lags and historical barriers to gene flow in a rapidly fragmenting Appalachian landscape. Molecular Ecology. https://doi.org/10.1111/mec.15362.

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