10.5061/DRYAD.JM63XSJB4
Khanyari, Munib
0000-0003-4624-5073
Nature Conservation Foundation
Robinson, Sarah
Interdisciplinary Center for Conservation Science
Morgan, Eric
Queen's University Belfast
Brown, Tony
Queen's University Belfast
Singh, Navinder
Swedish University of Agricultural Sciences
Salemgareyev, Albert
Association for the Conservation of Biodiversity of Kazakhstan
Zuther, Steffen
Association for the Conservation of Biodiversity of Kazakhstan
Kock, Richard
Royal Veterinary College
Milner-Gulland, E
Interdisciplinary Centre for Conservation Sciences
Building an ecologically-founded disease risk prioritization framework for
migratory species based on contact with livestock
Dryad
dataset
2021
disease transmission
saiga
multi-use landscapes
Overlap
socio-ecological system
uncertainity
2021-06-08T00:00:00Z
2021-06-08T00:00:00Z
en
69839 bytes
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CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
1. Shared use of rangelands by livestock and wildlife can lead to disease
transmission. To align agricultural livelihoods with wildlife
conservation, a multi-pronged and interdisciplinary approach for disease
management is needed, particularly in data-limited situations with
migratory hosts. Migratory wildlife and livestock can range over vast
areas, and opportunities for disease control interventions are limited.
Predictive frameworks are needed which can allow for identification of
potential sites and timings of interventions. 2. We developed an iterative
three-step framework to assess cross-species disease transmission risk
between migrating wildlife and livestock in data-limited circumstances and
across social-ecological scales. The framework first assesses risk of
transmission for potentially important diseases for hosts in a multi-use
landscape. Following this, it uses an epidemiological risk function to
represent transmission-relevant contact patterns, using density and
distribution of the host to map locations and periods of disease risk.
Finally, it takes fine-scale data on livestock management and observed
wildlife-livestock interactions to provide locally-relevant insights on
disease risk. 3. We applied the framework to characterize disease
transmission between livestock and saiga antelopes (Saiga tatarica) in
Central Kazakhstan. 4. At step 1, we identified peste-des-petits-ruminants
as posing a high risk of transmission from livestock to saigas,
foot-and-mouth disease as low risk, lumpy skin disease as unknown and
pasteurellosis as uncertain risk. At step 2 we identified regions of high
disease transmission risk at different times of year, indicating where
disease management should be focussed. At step 3, we synthesized field
surveys, government data and literature review to assess the role of
livestock in the 2015 saiga mass mortality event from pasteurellosis,
concluding that it was minimal. 5. Synthesis and Applications. Our
iterative framework has wide applicability in assessing and predicting
disease spill-over at management-relevant temporal and spatial scales in
areas where livestock share space with migratory species. Our case study
demonstrated the value of combining ecological and social information to
inform management of targeted interventions to reduce disease risk, which
can be used to plan disease surveillance and vaccination programmes.