We first reviewed the LG literature and found 5 ways in which LG research can be applied:
1) Identification of evolutionarily significant units for conservation
2) Managing pathogen and invasive spread
3) Natural heritage systems planning
4) Assessing population status
5) Restoration of populations
We then wanted to know whether LG was being applied more often than other research fields. We gathered random titles that relate to 25 different research fields in ecology and evolutionary biology from Web of Science. We then used R to web scrap government websites to find whether these titles were mentioned within government documentation. Our definition of an "applied" article is whether an article is ever mentioned within government documentation.
We first found that LG was applied comparatively less to the other research fields we investigated. We additionally found that research fields in evolutionary biology were systematically less applied than research fields in ecology. We wanted to know whether this was more of a temporal issue, but as we factored time out of the equation we found the same thing. One explanation for this finding could be a lack of understanding of genetics by practitioners or ecologist are better at communicating their findings.
Below is some of the R code we used to web scrap and count the number of applications of each article. The script runs through 10 LG articles that we defined as being "applied" (See below for article references). The structure of the code is as follows: Take a title, make a google search query, build the URL, connect to the URL, count the number of hits. Be careful not to overload google with searches. This code is design to sleep after every query so that google doesn't get upset and block your IP. If google does block you, my code releases and renews your IP. I am not sure if this really works, but you can easily remove this functionality. Have fun!
Blanchong, J.A., Samuel, M.D., Scribner, K.T., Weckworth, B.V., Langenberg, J.A. and Filcek, K.B., 2008. Landscape genetics and the spatial distribution of chronic wasting disease. Biology Letters, 4(1), pp.130-133.
Deyoung, R.W., Zamorano, A., Mesenbrink, B.T., Campbell, T.A., Leland, B.R., Moore, G.M., Honeycutt, R.L. and Root, J.J., 2009. Landscape‐Genetic Analysis of Population Structure in the Texas Gray Fox Oral Rabies Vaccination Zone. The Journal of Wildlife Management, 73(8), pp.1292-1299.
Epps, C.W., Wehausen, J.D., Bleich, V.C., Torres, S.G. and Brashares, J.S., 2007. Optimizing dispersal and corridor models using landscape genetics. Journal of applied ecology, 44(4), pp.714-724.
Hagerty, B.E. and Tracy, C.R., 2010. Defining population structure for the Mojave desert tortoise. Conservation genetics, 11(5), pp.1795-1807.
Hunter, M.E., Mignucci-Giannoni, A.A., Tucker, K.P., King, T.L., Bonde, R.K., Gray, B.A. and McGuire, P.M., 2012. Puerto Rico and Florida manatees represent genetically distinct groups. Conservation Genetics,13(6), pp.1623-1635.
McRae, B.H. and Beier, P., 2007. Circuit theory predicts gene flow in plant and animal populations. Proceedings of the National Academy of Sciences,104(50), pp.19885-19890.
Muñoz‐Fuentes, V., Darimont, C.T., Wayne, R.K., Paquet, P.C. and Leonard, J.A., 2009. Ecological factors drive differentiation in wolves from British Columbia. Journal of Biogeography, 36(8), pp.1516-1531.
Row, J.R., Wilson, P.J., Gomez, C., Koen, E.L., Bowman, J., Thornton, D. and Murray, D.L., 2014. The subtle role of climate change on population genetic structure in Canada lynx. Global change biology, 20(7), pp.2076-2086.
Schwartz, M.K., Copeland, J.P., Anderson, N.J., Squires, J.R., Inman, R.M., McKelvey, K.S., Pilgrim, K.L., Waits, L.P. and Cushman, S.A., 2009. Wolverine gene flow across a narrow climatic niche. Ecology, 90(11), pp.3222-3232.
Stevens, V.M., Verkenne, C., Vandewoestijne, S., Wesselingh, R.A. and Baguette, M., 2006. Gene flow and functional connectivity in the natterjack toad. Molecular Ecology, 15(9), pp.2333-2344.