This study was a product of my Delta Science Postdoctoral Fellowship to investigate the mechanisms for effective biological control of the invasive water hyacinth in the Sacramento-San Joaquin River Delta (hereafter “Delta”).
In a nutshell: Two weevils (insects) are currently used all over the world for the biological control of the invasive water hyacinth, including the Sacramento-San Joaquin River Delta, California. They have had variable success, with notable reduction of biomass and cover of this invasive aquatic weed in warmer climates compared to more temperate climates such as the Delta. Although temperature plays a large role in their success, I also investigated the role of genetic variation in the success of these weevils and whether there is lower genetic diversity and heterozygosity in the Delta compared to the native origin of these weevils (South America). To do this, I used polymorphic microsatellite markers (repeating regions of DNA in the genetic blueprints of a species) to detect differences between individuals and between populations. Additionally, as myself and others noticed weevils from the field that appeared to be hybrids of these two species, I examined whether these hybrid-like weevils are genetic hybrids (meaning that they have genetic patterns representative of the genetic blueprints from both species).
In my opinion, the most important findings from this study were:
- We found hybrids! This is huge! These two weevils are introduced all over the world for the control of invasive water hyacinth. So now that we know hybridization occurs, it is critical since to understand how hybridization affects their success. For instance, sometimes hybrids can outperform non-hybrids (hybrid-vigor) whereas other times hybridization can decrease performance, as well as population growth (hybrid-breakdown). I am very excited however that Dr. Julie Coetzee’s laboratory in South Africa is now starting to look into the effects of hybridization between these two weevil species.. so stay tuned (I know I will!) .
- We found that low genetic variation from demographic bottlenecks (small populations of the weevils being introduced over and over again through the biological control programs), can sometimes be buffered by genetic admixture from multiple introductions. This was one of several findings from this study that was made possible through the unique combination of documented historical records from biological control programs and population genetic analyses, such as those we made with the program, FLOCK.
- Through combining this genetic study with a temperature performance study, we found that low genetic variation does not always hinder population adaptation or performance. This finding has been observed in other study systems, such as with the invasive Argentine ant, which has lower genetic variation in the introduced region, but is more successful than in the native range due to reduced intraspecific aggression among separate ant nests in the introduced populations.
I also think that the lessons I learned from the process of writing this manuscript were very important, and I detail these below.
Lesson 1: Know when to ask for help
This study culminated out of work that I did at UC Davis, advised by Dr. Ted Grosholz, and in collaboration with researchers, Dr. Paul Pratt and Dr. Kent McCue (USDA/ARS), Dr. Ruth Hufbauer (Colorado State University) and Dr. Pierre Duchesne (Université Laval, Quebec, Canada). The latter two coauthors of whom I actually contacted out of the blue during the analysis and writing portion of the study, since I felt like I needed more guidance from experts in the population genetics and data analysis field. I think knowing when to ask for help is really critical in science (no matter what your academic standing is), and it almost always improves the study to get additional opinions and critique. Think of it as a preliminary peer review before the ultimate peer review!
I also asked several folks that are experts in population genetics for advice on the collection, processing and analysis of the data before and during the start of this project, including: Dr. Jeremy Andersen (UC Berkeley), and Dr. Rick Grosberg and Brenda Cameron (UC Davis) and Dr. Neil Tsutsui (UC Berkeley).
Lesson 2: Be Flexible, and Adapt to let the Data tell the Story
The title of this manuscript felt very suitable to me as ecological data are not always clear-cut, and sometimes it can take some time to wade through the weeds of data and figure out how to tell the accompanying story. This is especially true for when resulting data don’t match up with your original expectations and initial story you thought you would tell. The key to this issue, is don’t try to force your old story on the data… get a second opinion if needed, and be open-minded by letting the data ‘speak’ for itself.
Lesson 3: Work Hard, Be Patient and Persistent
I think with anything that you do, sometimes a final product comes easy… and other times it seems like a long drawn out process. This project fell in the latter category, as it was my first time learning about and implementing a population genetics study, and I was working on the analysis and write-up of this study all while starting a new postdoc in an entirely new study system. I think an important aspect to finishing this project was really persistence. I spent week nights and weekends working diligently on the data analysis and writing and re-writing the paper. I also had to be patient with myself as I had to give myself time to learn the new types of analyses (which means new R packages and code!) and time to read all of the important papers in the study field.
If by chance you are also just starting a population genetic study, and feel a bit lost, please see my three-part tutorial blog posts which hopefully will provide some assistance:
- How-to use microsatellites for population genetics, Part I: Study Design, DNA extraction, Microsatellite Marker Design/Outsourcing
- Population Genetics Part II: Tips and Tricks, Multiplex PCR and Workflow of Microsatellites- the cheap way
- Population Genetics, Part III: Data Wrangling and Analyses
Lesson 4: Implement Self-Deadlines and Advertise them to your CoAuthors
Sometimes its hard to finish something if you don’t have a deadline. So make yourself a deadline, and tell everyone about this deadline, so that you are held accountable for this timeline. I actually had some coauthors that needed me to submit this article to the journal by October 1st in order to meet some of their workplace requirements for publications. Needless to say, I pulled an all-nighter and got it in to the journal by 5am that day.. true story….
Nothing like a little pressure to light up that writing-fire…
Lesson 5: Don’t cut corners
This goes with Lesson 3, on being patient. Towards the end of writing up a big study, you might find yourself just wanting it to be over. You would do anything to not have to think about that project or the data anymore. However, crossing that finish line is actually one of the most crucial components and can make or break your ability to get into a decent journal. Having co-authors often really helps solve this problem, as they will call you out on any cut corners (if they are doing their job), and will suggest critical improvements to the paper that maybe you were thinking about.. but were just initially too lazy to do. Also on this note.. Read the proof-version (final version before being published) of the paper word for word! You don’t want any typos in your finished product.. especially true in your Title, Abstract and Figure Legends!
Lesson 6: Celebrate at Each Stage of Completion
Be sure to acknowledge your accomplishments after you submit the manuscript the first time, after the revisions and acceptance, and after the manuscript goes In Press. After all- you worked hard to get to each of those stages, and celebration will help motivate you for the next time you have to do it all over again!