With Biosecurity Commons, you can predict the potential future distribution of a species under a variety of possible future climate scenarios. The Climate Change Experiment takes the results of your Species Distribution Modelling experiment, and projects that distribution into the future using predicted climatic changes expected under different emissions scenarios and climate models. There are many future environmental datasets to choose from as they vary by year, according to predicted emissions (i.e. business as usual or reduced emissions) and the global circulation model used. Future predicted climate variables like rainfall and temperature are available from 2015 to 2085. 

  

Note: You will need to run a (Multi) Species Distribution Model before you can run a Climate Change Experiment.  

  

Run a CC on Biosecurity Commons  

On the top of the page click on “Workflows” and then on “Species Distribution Modelling”. Under “Secondary experiments” choose “Climate Change Experiment”. 

 

Step 1: Description tab 

  • Enter the title for your experiment in the first box e.g. Red fox (Vulpes vulpes).  
  • (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: Source Experiment tab 

  • Click "+ Select an experiment" 
  • Select the species distribution model trained on current climate data which you would like to use for making predictions under climate change and click "Close" 
  • Check the box for the algorithm/s with which you would like to use. 
  • Select the threshold you would like to use. 
  • Click “Next” on the bottom of the page.  
     

Step 3: Projection tab 

  • Click “+ Select future climate data". Again, there are thousands of these to choose from and they vary by year, emissions scenario and the global circulation model used. 
  • Unless you know better for your specific experiment it is a good idea to use the same source of climate data for your current and future predictions. For example, if you trained your initial model using WorldClim climate data, it would make sense to use one of the many WorldClim datasets for the future. Same with Chelsa or other climate 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”. 
  • Click "Next" on the bottom of the page. 
     

Step 4: Study Area Extent tab 


In this section you can select the spatial area to which you want to make climate change predictions. By default, the spatial extent of predictions will be the same area as the trained area from your selected SDM. But you can select a different area here if you want to project to a different area. The different constraint options are: 
 

Use Source SDM Experiment Constraint 

  • This is the same constrained area as your SDM experiment. You can add a buffer around this area 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. 
     

Step 5: 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 “View job information” in “My results”. Once your job is finished you can view the results in “My results”.  

  

If you are waiting for a job to be completed, 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.