10.5061/DRYAD.2S910
Muneza, Arthur B.
Michigan State University
Linden, Daniel W.
Cornell University
Montgomery, Robert A.
Michigan State University
University of Oxford
Dickman, Amy J.
University of Oxford
Roloff, Gary J.
Michigan State University
Macdonald, David W.
University of Oxford
Fennessy, Julian T.
Giraffe Conservation Foundation; PO Box 86099 Eros Windhoek Namibia
Data from: Examining disease prevalence for species of conservation
concern using non-invasive spatial capture-recapture techniques
Dryad
dataset
2017
disease prevalence
Noninvasive surveys
Giraffe Skin Disease
spatial capture-recapture
Population modeling
Giraffa camelopardalis
2017-09-15T00:00:00Z
2017-09-15T00:00:00Z
en
https://doi.org/10.1111/1365-2664.12796
156658 bytes
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CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
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.
GSD_photo_data_JAEData set file with sightings records and individual
giraffe dataAppendix1JAGS code for giraffe spatial capture-recapture model
Tanzania
Ruaha National Park