The EcoCommons currently offers seven different experiment types. These are divided in four primary and three secondary experiments, which means that the outcomes of a primary experiment can be used as input for a secondary experiment. 


Primary experiments

Primary experiments model your species under current conditions. The outputs of these models are then used as input into secondary experiments.

Species Distribution Model (SDM)

The Species Distribution Model experiment lets you investigate the potential distribution of a species under current climatic and environmental conditions. The BCCVL currently provides 17 algorithms across 4 different categories to run your species distribution model. 


Multi Species Distribution Model (MSDM)

The Multispecies Distribution Model experiment can be used to investigate the potential distribution of multiple species under current climatic and environmental conditions. You have to upload your own multi-species csv file for this experiment, and then select 1 algorithm (out of a choice of 17). It is important to note that the MSDM experiment does not run multiple species in the same model, but rather runs a separate SDMs for each species. This experiment is mostly used to run a big batch of species (think hundreds of SDMs) in one hit, and to then select this experiment as input to a Biodiverse analysis experiment to find hotspots of biodiversity for your group/community of species.


Migratory Modelling (MM)

In the Migratory Modelling experiment you can divide your species occurrence dataset in subsets, and use a different suite of climate and environmental variables for each subset. This is particularly useful if you are modelling a species that occurs in different geographic areas in different time periods such as migratory species and want to model these subpopulations (e.g. breeding and feeding populations/areas) separately.


Species Trait Model (STM)

In the Species Trait Modelling experiment you can analyse the effect of environmental variables on 1 or more species traits, and also test how traits differ among multiple species.


Secondary experiments

Secondary experiments allow you to build on your existing models. Before running a secondary experiment you must first run at least one primary experiment to be used as input. 

Climate Change Experiment

The Climate Change experiment lets you investigate the distribution of a species under potential future climatic conditions. It takes the outcomes of an SDM or MSDM and projects these into the future. You can select from a range of emission scenarios and climate models.


Ensemble Analysis

The Ensemble Analysis experiment can be used to reduce the uncertainty of using the single-model, or single-emissions-scenario approach to investigating species distributions. You can, for example, synthesise the results of two or more related but different analytical models, such as multiple algorithms in an SDM, or combine the results of two or more related but different climate models/scenarios from a Climate Change experiment.


Biodiverse Experiment

Biodiverse is a system to compute indices of biodiversity. This experiment type is based on Associate Professor Shawn Laffan’s (UNSW) Biodiverse software, which is a free tool for the spatial analysis of diversity using indices based on taxonomic, phylogenetic and matrix-based relationships. In the BCCVL, Biodiverse uses the outcomes of multiple SDMs, an MSDM, or a Climate Change experiment and stacks these to calculate gridded estimates/hotspots of species richness, rarity and endemism.