Bayesian Methods to Analyze Historical Collections in Time and Space: A Case Study Using Cabo Verde Endemic Flora

Area of Science:

• Biodiversity research
• Island biogeography
• Botanical exploration history

Background:

• Biological collections, such as herbarium specimens, are crucial for understanding biodiversity and historical scientific knowledge.
• Oceanic islands, with high endemic and threatened species, require detailed study of discovery processes.
• The Macaronesian archipelagos have been explored since the late 17th century, but an integrated study of their flora's collection history is lacking.

Purpose of the Study:

• To investigate the historical process of collecting, discovery, and description of the endemic angiosperm flora in Cabo Verde.
• To analyze the accumulation of species discovery over time and space across the archipelago's islands.
• To identify factors influencing the development of botanical knowledge in the region.

Main Methods:

• Review of the historical collection records for the Cabo Verde flora.
• Application of a Bayesian approach to model species discovery accumulation.
• Spatial and temporal analysis of species discovery across nine islands.

Main Results:

• Species discovery was influenced by both natural island characteristics (area, age, altitude, terrain ruggedness) and historical factors (harbor locations).
• The study identified key drivers shaping the process of species description in the archipelago.
• Accumulation of knowledge varied significantly across the islands.

Conclusions:

• Understanding the history of scientific discovery is vital for interpreting biodiversity patterns, especially on islands.
• Both intrinsic geographical features and extrinsic historical influences play significant roles in botanical exploration.
• This study provides a framework for analyzing discovery processes in other island ecosystems.