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Temporal area approach for distributional data in biogeography.

Elizabeth M Dowding1, Malte C Ebach1, Evgeny V Mavrodiev2

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This study introduces a structural approach to temporality in palaeobiogeography, dividing areas temporally to better represent changes over time. This method enhances analyses like Parsimony Analysis of Endemicity (PAE) for more robust classifications.

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Area of Science:

  • Palaeobiogeography
  • Geographical Information Systems
  • Computational Biology

Background:

  • Temporal dynamics are crucial for understanding biogeographical patterns.
  • Existing methods may not adequately capture historical area changes.
  • Palaeobiogeographical data often contains temporal artefacts.

Purpose of the Study:

  • To present a structural approach for incorporating temporality into distributional data.
  • To enable the representation of geographical areas across different time intervals.
  • To improve the robustness of palaeobiogeographical area classifications.

Main Methods:

  • Structuring distributional data into a temporal matrix.
  • Splitting pre-established geographical areas into temporal iterations.
  • Applying the temporal matrix to analyses such as Parsimony Analysis of Endemicity (PAE).

Main Results:

  • The temporal matrix allows for the capture of differing relationships between areas through time.
  • Facilitates the use of numerical methods to assess area relationships.
  • Enables exploration of data rather than a hypothesis-driven model.

Conclusions:

  • The Temporal Area Approach (TAAp) provides a novel structural method for palaeobiogeographical data.
  • Reduces temporal artefacts, leading to more reliable area classifications.
  • Enhances the analysis of non-phylogenetic palaeobiogeographical data.