In the BCCVL the Ensemble Analysis experiment is used to reduce the uncertainty of using the single-model, or single-emissions-scenario approach to investigating species distributions.

Screen Shot 2016-07-25 at 10.04.54 AM

This experiment is most commonly used in two different ways:

1) Synthesising the results of two or more related but different analytical models

Users can run a Species Distribution Model experiment with a number of different algorithms. When this experiment has completed users can then take the results as input into an Ensemble Analysis experiment. The Ensemble will overlay the probability values of each algorithm and synthesise the results into a single score. An ensemble experiment will provide a number of different probability maps:

  • Summary maximum
  • Summary mean
  • Summary minimum
  • Summary variance
  • 5th percentile
  • 10th percentile
  • 50th percentile
  • 90th percentile
  • 95th percentile

2) Synthesising the results of two or more related but different climate models/scenarios

Users can run a Species Distribution Model experiment with different emission scenarios, or different global circulation models. When this experiment has completed users can then take the results as input into an Ensemble Analysis experiment. This approach to climate impact modelling can reduce the uncertainty of ‘picking’ one GCM or emission scenario over another.

 

Share This