Examining disease prevalence for species of conservation concern using non-invasive spatial capture–recapture techniques
on‐invasive techniques have long been used to estimate wildlife population abundance and density. However, recent technological breakthroughs have facilitated non‐invasive estimation of the proportion of animal populations with certain diseases. Giraffes Giraffa camelopardalis are increasingly becoming recognized as a species of conservation concern with decreasing population trajectories across their range in Africa. Diseases may be an […]
Computer-aided photographic pelage pattern analysis of Giraffa camelopardalis (Artiodactyla: Giraffidae)
The giraffe (Giraffa camelopardalis) is one of the most recognisable animal species on earth. Yet hunting and habitat loss and fragmentation have led to severe, but until recently largely unnoticed, declines of giraffe populations all over Africa. The IUCN recognised one single species with nine subspecies and changed the status from ‘Least Concern’ to ‘Vulnerable’ […]
Revisiting giraffe photo-identification using deep learning and network analysis
An increasing number of research programs rely on photographic capture-recapture (vs. direct marking) of individuals to study distribution and demography within animal populations. Photo-identification of individuals living in the wild is sometimes feasible using idiosyncratic coat or skin patterns, like for giraffes. When performed manually, the task is tedious and becomes almost impossible as populations […]
A computer-assisted system for photographic mark–recapture analysis
Photographic mark–recapture is a cost-effective, non-invasive way to study populations. However, to efficiently apply photographic mark–recapture to large populations, computer software is needed for image manipulation and pattern matching. We created an open-source application for the storage, pattern extraction and pattern matching of digital images for the purposes of mark–recapture analysis. The resulting software package […]