Individual-based multiple-unit dissimilarity: novel indices and null model for assessing temporal variability in...

Area of Science:

• Ecology
• Biodiversity research
• Community ecology

Background:

• Beta-diversity traditionally measures spatial variation in community composition.
• Temporal beta-diversity extends this concept to changes over time.
• Existing individual-based indices are limited to pairwise comparisons.

Purpose of the Study:

• To extend individual-based beta-diversity indices to multiple temporal units.
• To introduce novel permutation criteria for detecting individual persistence patterns.
• To provide tools for analyzing temporal biodiversity dynamics using individual-level data.

Main Methods:

• Extension of pairwise individual-based beta-diversity indices to multiple-unit cases.
• Development of a novel random permutation criterion for assessing individual persistence.
• Application of the new indices to a long-term forest dynamics plot dataset.

Main Results:

• The study successfully extended individual-based beta-diversity metrics to multiple temporal contexts.
• Novel indices and permutation criteria were developed and demonstrated.
• The methods were applied to a real-world dataset, showing their practical utility.

Conclusions:

• The proposed multiple-unit individual-based beta-diversity indices offer a powerful new approach for ecological research.
• These methods address a critical gap in analyzing temporal biodiversity dynamics, especially with individual-tracked data.
• The findings are expected to advance understanding of temporal changes in biodiversity across various ecosystems.