The Species Distribution Model Experiment (SDM) lets you investigate the potential distribution of a species under current climatic and environmental conditions.

 

Keep in mind it is very easy to create an estimate of species distribution with these tools. It can be easy to produce a good model for your specific question, but it can also be easy to produce a poor model with these tools. For more information read more about Species Distribution Modelling here. 


The Biosecurity Commons currently provides 19 different algorithms across 4 different categories of SDMs to run your species distribution model. 

 

Note: You will need to run a Species Distribution Model before you can run a Climate Change or Ensemble Experiment.




 

Before running an SDM

 

The data you want to use in your experiments must be available within the Biosecurity Commons platform before you start the experiment. You can either import data from external services or upload your own in the “Datasets” section of Biosecurity Commons. Environmental data available on Biosecurity Commons can be selected after you start your experiment, but if you are uploading your own that will need to be done before you start your experiment.


Run SDM


On the top of the page click on “Workflows” and then “Species Distribution Modelling”. Under “Primary experiments” choose “Species Distribution Modelling”.


Step 1: Description tab

  • Enter the title for your experiment in the first box e.g. Baudin’s Black Cockatoo. 

  • (optional) You can also add a description of your experiment in the box below if you want to convey more information. Some researchers use this box to record their research questions or hypotheses for later referral.

  • Click “Next” on the bottom of the page.


Step 2: Occurrences tab

  • Select your pre-loaded species occurrence dataset by clicking on “+ Select an occurrence dataset”. 

  • Note: If you click this and you have no loaded species occurrence datasets you will need to visit the dataset page and import or upload the required data.

  • In the pop-up box select the dataset you wish to use in your SDM. 

  • (optional) You can visualise your occurrence data by clicking the green eye icon next to your loaded data.

  • Click “Next” on the bottom of the page.


Step 3: Absences tab

You have two options for adding absence data: 

  • Uploaded true absence data: If you have your own absence data you can select this for your experiment as follows:

  • Select “Yes” under the question whether you have true absence data.
  • Click on “+ Select an absence dataset”. 
  • In the pop-up box select the pre-loaded absence dataset you wish to use in your SDM. 
  • (optional) You can visualise your absence data by clicking the green eye icon. 
  • Click “Next” on the bottom of the page.

  • Pseudo-absence data: Biosecurity Commons can randomly generate pseudo-absence or background (if using Maxent as algorithm) points for your experiment.

  • Select “No” under the question whether you have true absence data.
  • You can change the pseudo-absence generation settings (absence-presence ratio and strategy) or the background generation settings (number of background points). By default, the generation will be random throughout the geographic extent of the area selected in the constraints tab, with a 1:1 ratio of absence:presence data. All algorithms in the experiment will use these settings, unless you change it for specific algorithms on the Algorithms tab.
  • Click “Next” on the bottom of the page.


Step 4: Climate & Environmental Data tab

  • Click “+ Select datasets”.

  • In the pop-up box you can enter search terms to filter for required datasets or filter by collection, resolution and/or domain.

  • Once you have found the dataset/s you are looking for select them and click “Close”.

  • When back on the Climate & Environmental Data tab you can select/deselect data layers in the white box.

  • (optional) You can visualise each of the data layers by clicking the green eye icon.

  • Once you have selected all your environmental and climate layers click “Next” on the bottom of the page.

Note: If you choose data layers that do not have the same resolution you can choose whether they should be scaled to the finest or coarsest resolution.


Step 5: Study Area Extent tab

In this section you can select the area in which to train your model. This means that only the occurrence records from the constrained area are used, and pseudo-absence or background points are only generated in this area. It is good practice to remove parts of the geographic or environmental space where you are certain your species will not be found.

  

The default constraint is the convex hull (= minimum polygon) around all occurrence records. This convex hull is shown as a blue outline on the map. The different constraint options are:

  • Use Convex Hull

  • You can add a buffer around the convex hull by nominating a distance in km. The buffer will be added on the map once you click outside the white box. 

  • Select pre-defined extent 

    • Select a region type from the drop-down menu. 
    • You can also add a buffer around the pre-defined region constraints. 

  • Use bounding box of predictor data 

    • This is the geographic extent of where all selected climate/environmental datasets overlap. 

  • Draw extent on map 

    • Click on “Start drawing”, then click on the map to draw a shape on the map to which the model will be constrained. 

  • Upload Shapefile  

    • Not available yet. 
  • Note: The model will be trained on the selected area, and the results will include a predicted distribution map for the constrained area, as well as a projection to the geographic extent of your environmental/climate layers.
  • Once you selected the constrained area click “Next” on the bottom of the page


Step 6: Algorithms tab

  • Select the algorithm/s you would like to use to calibrate your model. You can choose one or many (or even all!) to run your experiment. Don't know which one to select? You can read about each algorithm here.

  • (optional) Configuration:

  • If you want to change the pseudo-absence/background selection settings for a particular algorithm, you can do that here. If you change nothing, the settings from the Absence tab will be used for all selected algorithms. 
  • Other configuration options are available for most algorithms. These options can be changed by changing the value or making a different selection from the drop down menu. The configuration options are currently set to the standard default values of the R packages. More information about each configuration option can be found on the support page for that particular algorithm.

  • Click “Next” on the bottom of the page.

 

Step 7: Run tab

  • Ensure you are happy with your experiment design.

  • If none of the tabs have a triangle with an exclamation mark, your experiment is ready to go.

  • Click “Start Experiment”.

  • If any of your tabs have a triangle with an exclamation mark, revisit them and ensure you have filled in each component correctly.

 

A log file will now be sent to our virtual machines where your experiment will be run. 

 

You can view the progress of your job under “My job”. Once your job is finished you can view the results by either clicking “View all results” inside your job or click on the “My results” tab under Workspace. 

 

For now, sit back and relax, grab a coffee, or do some other work without being hampered by a slower computer that is running heavy models in the background.