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Sampling biological data - the response variables

Predictive mapping is based on estimated relations between biological variables and environmental gradients. Only if these relationsships are accurately measured and representative to the area can models predict reliably. Therefore, it matters very much how the data on biological variables are collected.

Once it is clear that predictive mapping needs to be applied (i.e. the whole area of interest can not be mapped directly), several aspects need to be considered before sampling:

  • the distribution of sampling effort (and units)
  • the scale of models (resolution and extent)
  • the number of samples
  • taxonomic resolution

Use the column to the right for more general information on what to consider when sampling biological data for predictive mapping.

Explore the menu on the left for more specific information on sampling biological data for modelling vegetation, invertebrates and fish!

Distribution of sampling efforts

Point sampling has many advantages when modelling biodiversity.


Spatial and temporal scales

Determining the extent and resolution is fundamental for sampling and modelling!


Sample size

More independent data will always produce better models. But how much data is needed and how does sample size affect model performance?


Taxonomic resolution

Sampling methods must be suitable for the desired level of taxonomic resolution of the biodiversity you wish to model.


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