Camera trapping expands the view into global biodiversity and its change

Area of Science:

• Ecology
• Conservation Biology
• Biodiversity Informatics

Background:

• Growing biodiversity loss necessitates comprehensive, large-scale species occurrence and diversity data.
• Camera traps (CTs) coupled with computer vision offer high-resolution biodiversity surveying capabilities.

Purpose of the Study:

• To evaluate the effectiveness of CTs in addressing biodiversity knowledge gaps.
• To compare CT data from the Wildlife Insights platform with existing Global Biodiversity Information Facility (GBIF) records.

Main Methods:

• Comparative analysis of terrestrial mammal and bird occurrence data from CTs and GBIF.
• Assessment of data quantity (sampling days) and quality (novel species and range documentation).

Main Results:

• CTs sampled more days (mean 133 vs. 57) and identified additional species compared to existing data.
• CT data provided novel range documentation for 93% of mammals and 48% of birds studied.
• Significant data coverage increases were observed in historically underrepresented Southern Hemisphere countries.

Conclusions:

• CT data collection and mobilization are crucial for a detailed understanding of biodiversity.
• Data sharing, with appropriate attribution and privacy, is vital for maximizing the impact of CT initiatives.
• CTs represent a powerful tool for closing biodiversity knowledge gaps and informing conservation efforts.