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Bridging Knowledge and Data Gaps in Odonata Rarity: A South Korean Case Study Using Multispecies Occupancy Models and

Sungsoo Yoon1,2, Wanmo Kang3

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Summary
This summary is machine-generated.

Data-driven models and ecological knowledge reveal species rarity. Findings highlight discrepancies, emphasizing the need for standardized surveys and data sharing for accurate conservation assessments of Odonata in South Korea.

Keywords:
OdonataRabinowitz rarity frameworkknowledge–data discrepancyoccupancy modelingspecies rarity

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Area of Science:

  • Ecology
  • Conservation Biology
  • Biodiversity Assessment

Background:

  • Accurate species rarity and conservation status assessment requires integrating data-driven models with ecological knowledge.
  • Odonata (dragonflies and damselflies) are important indicators of freshwater ecosystem health.
  • Existing assessments may be influenced by survey biases and data accessibility limitations.

Purpose of the Study:

  • To apply multispecies occupancy (MSO) and latent factor multispecies occupancy (LFMSO) models to estimate Odonata occurrence in South Korea.
  • To conduct data-based rarity assessments using the Rabinowitz framework and compare them with traditional ecological knowledge.
  • To identify discrepancies and understand factors influencing rarity assessments for conservation planning.

Main Methods:

  • Application of multispecies occupancy (MSO) and latent factor multispecies occupancy (LFMSO) models for 133 Odonata species.
  • Implementation of the Rabinowitz rarity framework using model outputs for data-driven rarity assessments.
  • Comparison of data-driven assessments with geographic ranges, habitat preferences, regional Red List statuses, and citizen science data.

Main Results:

  • General alignment between data-driven rarity classifications and regional Red List statuses (Near Threatened, Vulnerable).
  • Identified significant discrepancies, particularly for lentic Odonata species perceived as common.
  • Spatial biases in surveys and limited data access for protected species were identified as potential impediments to accurate assessments.

Conclusions:

  • Data-driven rarity assessments offer valuable insights but require validation against ecological knowledge.
  • Standardized survey protocols and improved data-sharing policies are crucial for reliable biodiversity assessments.
  • Enhanced accuracy in rarity assessments is essential for effective conservation planning and management of freshwater ecosystems.