Spotting the difference: towards fully-automated population monitoring of African penguins Spheniscus demersus

Endangered Species Research

Innes C. Cuthill¹  Richard B. Sherley¹  Tilo Burghardt¹  Peter J. Barham¹  Neill Campbell¹ 

关键词: Biometrics;    Individual recognition;    Population monitoring;    Conservation biology;    Computational biology;   

DOI  :  10.3354/esr00267

学科分类：动物科学

来源: Inter-Research

【 摘 要 】

ABSTRACT: Placing external monitoring devices onto seabirds can have deleterious effects on welfare and performance, and even the most benign marking and identification methods return sparse population data at a huge time and effort cost. Consequently, there is growing interest in methods that minimise disturbance but still allow robust population monitoring. We have developed a computer vision system that automatically creates a unique biometric identifier for individual adult African penguins Spheniscus demersus using natural markings in the chest plumage and matches this against a population database. We tested this non-invasive system in the field at Robben Island, South Africa. False individual identifications of detected penguins occurred in less than 1 in 10000 comparisons (n = 73600, genuine acceptance rate = 96.7%) to known individuals. The monitoring capacity in the field was estimated to be above 13% of the birds that passed a camera (n = 1453). A significant increase in this lower bound was recorded under favourable conditions. We conclude that the system is suitable for population monitoring of this species: the demonstrated sensitivity is comparable to computer-aided animal biometric monitoring systems in the literature. A full deployment of the system would identify more penguins than is possible with a complete exploitation of the current levels of flipper banding at Robben Island. Our study illustrates the potential of fully-automated, non-invasive, complete population monitoring of wild animals.

【 授权许可】

Unknown