Data from: Examining disease prevalence for species of conservation concern using non-invasive spatial capture-recapture techniques
Muneza, Arthur B. et al. (2017), Data from: Examining disease prevalence for species of conservation concern using non-invasive spatial capture-recapture techniques, Dryad, Dataset, https://doi.org/10.5061/dryad.2s910
1. Non-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 camelopardalisare increasingly becoming recognized as a species of conservation concern with decreasing population trajectories across their range in Africa. 2. Diseases may be an important component impacting giraffe population declines, and the emerging ‘Giraffe Skin Disease’ (GSD), characterized by the appearance of wrinkled skin and alopecic lesions on the limbs, neck, and chest of infected giraffe, may hinder movement causing increased susceptibility to predation. 3. We examined the prevalence of GSD in Tanzania's Ruaha National Park over a 4-month period in 2015, using photographic capture–recapture surveys via road-based transects. We divided the study area into five circuitous survey units, each approximately 100 km in length ($\bar x$ = 99.22 km, SD = 3.72), and surveyed for giraffes for four months. From these surveys, we developed a database of spatially-explicit giraffe photographs. 4. We processed these photos for individual identification and fitted spatial capture–recapture models to predict the spatial configuration of giraffe abundance and GSD prevalence within the study area. 5. Our results indicated that >86% of the giraffe population showed signs of GSD and that the disease was more prevalent in the northern and north-eastern portion of Ruaha National Park. 6. Synthesis and applications. Our research shows that data from non-invasive surveys can be used in spatial capture–recapture (SCR) models to estimate the proportion of a population affected by a visible disease. Researchers and conservationists can use SCR models to better examine the variation in parameters associated with these populations such as sex and age class, movement, and encounter rate, which may be linked to the prevalence of the disease, while incorporating broad spatial and temporal dimensions of the population in such areas. We discuss the implications of this research for conservation of threatened species with an emphasis on disease ecology and vulnerability to predations, and more broadly, for wildlife conservation.
Ruaha National Park