Marine Biogeography and
Evolution
TP05. Species distribution modeling
TP04. Presence records and plot
You will use CRAN-R to obtain hierarchical area cladograms from their data. Even if students do not have the fundamentals of R, we strongly advise them to use it, as it is a widely used tool, with many different applications, and this exercise will allow you an easy introduction to its use.
With a script one tends to run the script by clicking our script away. In this case to fully understand the results you need to consult the package manuals
R-script for area clustering analysis:
TP 02. Exploratory data session: area cladograms and non-hierarchical areas relationships - I
Students will be given an excel file (see below) and their task is to work out the summary information about genus, species and endemic numbers of each region. iIt seems a trivial task ... but it turns out to be harder than at first glance.
Finally students will try to convey this information through graphs.
Atlantic reef fish biogeography and evolution, references:
Floeter SR, Rocha LA, Robertson DR, et al. (2007) Atlantic reef fish biogeography and evolution. Journal of Biogeography, 35 (1),22-47. PDF
Joyeux et al. (2001) Biogeography of tropical reef fishes: the South Atlantic puzzle. Journal of Biogeography, 28 (7): 831-841.
data matrix: lusitania_828_14.xlsx
TP 01. Exploratory data session: summary of biodiversity and graph building
The first course project will span 1 to 3 weeks, and each student will work on a presence/absence database of over 800 continental shelf fish species from 13 different regions including the Lusitania Province, Bay of Biscay, Atlantic Iberia, western Mediterranean Sea, eastern Mediterranean Sea, Atlantic Morocco, West Sahara, archipelagoes of the Azores, Madeira and the Canary Islands, the tropical eastern Atlantic, Cape Verde and São Tomé and Principe).
The goal is to understand how geographic regions of the Northeastern Atlantic Ocean relate to each other. Students will curate use similarity indexes to investigate biogeographical relationships among those areas. A main part of the work will be to summarise species richness and level of endemism and get data ready to produce tables and graphs. Students will work individually to conduct analyses.
A reference list is available on the website as support for this work, but students are encouraged to go beyond this list and find other relevant information for themselves.
A must for biologists: Brief introductions to R
TP 01
Part 2. Species distribution modelling
TP 03. Exploratory data session: area cladograms and non-hierarchical areas relationships - II
You will use CRAN-R to obtain non-hierarchical multi-dimensional scaling - MDS plots from their data. Even if students do not have the fundamentals of R, we strongly advise them to use it, as it is a widely used tool, with many different applications, and this exercise will allow you an easy introduction to its use.
With a script one tends to run the script by clicking our script away. In this case to fully understand the results you need to consult the package manuals.
With plots from TP3 and TP4, class will discuss aided by Freitas et al. (2019) paper, the validity of Macaronesia inegratin Cape Verde archipelago.
R-script for Multi-dimensional scaling analysis
Center for Marine Sciences, Faro, University of Algarve, Portugal
NEW PAPER TO READ
Part 1. Biogeography: biodiversity assessment and area relationships
Before the TP you must have:
1) installed RStudio in your own computer or verify the installation of RStudio in the computers of class
2) a general understanding of what R and RStudio are
3) completed the RStudio primer “The Basics”
The goal of this week is to achieve the modelled distribution of the species you have chosen.
Road map for today:
1. Load layers here.
2. Use the script: maxent_2025.R to build the SDM.
3. Read dependences very carefully !! You are required to install and/or modify certain settings on the computer.
4. Species distribution modeling is a quite sophisticated biogeographic approach. Nonetheless, today's class introduces a SDM 101, simplified way to build a model of distribution.
Data from "bad graphic" to be used in a good graph
How to retrieve records from GBIF manually and curation.
Road map for today:
1. Register in GBIF and explore the site (http://www.gbif.org) to get acquainted with GBIF.
2. Use the script occurrences_2025.R to retrieve data from the species you have chosen from GBIF records and plot a distribution map. There is part of the script, dedicated to curate the data retrieved, which is quite complex. Hopefully all will run as intended.
3. Save the resulting csv file.