Global Patterns of Genetic Diversity - Mangrove Forests

PP-highlights_final.mp4


The aim of this Professional Practice (PP) was to compile existing genetic data of mangrove forests to detect patterns of intraspecific diversity variation across species and to identify relevant hotspots for future conservation.


Mangroves

Mangroves are a group of around 80 higher plant species, typically found in the inter-tidal zones of tropical and subtropical coastlines(1). Despite offering a huge variety of ecosystem services and goods, mangrove forests are one of the most threatened ecosystems in the world(2)(3).

Meta-Analysis

"A meta-analysis is a statistical analysis that combines the results of multiple scientific studies. "(4)(5)


Pros:

  • low cost

  • requires minimal facilities (computer)


Cons:

  • pooling of data causes bias, which requires correction

  • rigorous & time-consuming




How to do your own Meta-Analysis?






1.






Literature Screening

  1. Use a search engine to retrieve all papers related to your topic of research

  • use keywords designed to optimize your output

e.g. (genetic diversity + mangrove) OR (genetic differentiation + mangrove)

  • using search engines that only contain peer reviewed papers insures the credibility of your meta-analysis

e.g. Web of Science

  1. Export the search result into an excel file

  • Tab limited UTF-8 format

  1. Skim the titles and the abstracts of each paper and label those that potentially have relevant data for your meta-analysis





2.






Data Extraction and Database Compilation

  1. Read papers that where previously labeled relevant

  2. Extract the data on genetic diversity

        • GPS coordinates must be presented in the same format, convert coordinates into the decimal degree format if necessary

  3. Extract data on markers

  4. Extract the Differentiation matrix (DM) as a separate excel file

  • be aware that the populations/locations in the DM must be listed in the same order as in the diversity database

  • take a look at the supplementary data if available














3.




















Data Handling


Part 1: Maps per Study

  1. Run an R-script on each study separately to get a feeling of the data that you have collected

        • Several maps are produced per study:

          • Genetic diversity maps per species and per index

          • Genetic differentiation maps per species







Part 2: Summary Maps

  1. Run an R-script to create summary maps containing the data of several studies

    • combining data of several studies requires a certain level of comparability

e.g. by limiting the number of studies to those whose sampling sites cover at least two marine ecoregions


Outcomes


Skills Learned


  • general knowledge on mangroves

  • ability to skim papers for relevant information

  • skill to conduct the data compilation of a meta-analysis

  • competence in using the R-studio interface

  • confident use of several online tools (Zoom, Dropbox, etc.)

  • video editing and animating using several programs (windows video editor, blender, opentoonz)

Future Aspirations


  • to familiarize my self further with the program R

  • the chance to work with my supervisors in other research projects (Jorge Assis, Eliza Fragkopoulou, Ester Serrao).

  • a PhD position in which I would be able to collaborate with several IMBRSea/EMBRC parter institutes.




Acknowledgements

I would like to thank Ester A. Serrao for presenting me with an interesting research topic despite the short notice which was provided to her. I would like to thank Eliza Fragkopoulou and Jorge Assis for guiding me through each step of the meta-analysis.

Furthermore, I want to thank the IMBRSea coordination office for their swift response to the increased regulations imposed during the COVID-19 pandemic, without their efforts the continuation of the master program would have been impossible.


Supplementary Videos

Institute_Description.mp4

CCMAR: Interview with a PhD student

Eliza Fragkopoulou is studying how climate change is going to affect the gene pools of marine forest species by developing models for different climatic change scenarios.

Travel_Covid_19_20001-4982.mp4

Traveling during times of a global Pandemic

16th-17th of May, 2020 Banyuls-sur-Mer, France -> Faro, Portugal













Created by E.H. Taraneh Westergerling for the IMBRSea Online Symposium 2020

contact: taraneh.westergerling@imbrsea.eu