The Climatch algorithms – A complement to the Climatch user manual

Authors: Zhenhua Hao and Philip Tennant

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Summary

Climatch is a software tool used to assess the climate suitability of a particular environment for a given species. It is widely used in environmental research, particularly for assessing the establishment risk of invasive species. This report complements the existing Climatch user manual by offering an in-depth explanation of the Euclidean and Closest Standard Score algorithms. It provides a detailed, step-by-step comparison of the two methods using a small artificial dataset to demonstrate their application. This report also includes some guidance for users on selecting between the two algorithms and discusses additional considerations when using climate matching software.

Key findings

• The report explains how Climatch’s two algorithms work and differ. Euclidean averages standardised differences across all climate variables, while Closest Standard Score focuses on the worst single climate variable using a ‘max-then-min’ approach and decile bins.
• The two methods may produce similar but different scores for a given area and may identify different best matches because Euclidean averages dissimilarities across all variables, while Closest Standard Score selects the source site based on the most dissimilar variable.
• Choosing between the algorithms also requires consideration of several practical factors, including the quality and representativeness of input data, the number and ecological relevance of selected climate variables, the consistency of outputs across regions or time periods, and comparability with historical Climatch assessments.