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Disease dynamics during wildlife translocations: disruptions to the host population and potential consequences for transmission in desert tortoise contact networks
Author(s) -
Aiello C. M.,
Nussear K. E.,
Walde A. D.,
Esque T. C.,
Emblidge P. G.,
Sah P.,
Bansal S.,
Hudson P. J.
Publication year - 2014
Publication title -
animal conservation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.111
H-Index - 85
eISSN - 1469-1795
pISSN - 1367-9430
DOI - 10.1111/acv.12147
Subject(s) - tortoise , outbreak , wildlife , population , chromosomal translocation , transmission (telecommunications) , biological dispersal , biology , ecology , disease , environmental health , computer science , genetics , medicine , virology , pathology , telecommunications , gene
Wildlife managers consider animal translocation a means of increasing the viability of a local population. However, augmentation may disrupt existing resident disease dynamics and initiate an outbreak that would effectively offset any advantages the translocation may have achieved. This paper examines fundamental concepts of disease ecology and identifies the conditions that will increase the likelihood of a disease outbreak following translocation. We highlight the importance of susceptibility to infection, population size and population connectivity – a characteristic likely affected by translocation but not often considered in risk assessments – in estimating outbreak risk due to translocation. We then explore these features in a species of conservation concern often translocated in the presence of infectious disease, the M ojave Desert tortoise, and use data from experimental tortoise translocations to detect changes in population connectivity that may influence pathogen transmission. Preliminary analyses comparing contact networks inferred from spatial data at control and translocation plots and infection simulation results through these networks suggest increased outbreak risk following translocation due to dispersal‐driven changes in contact frequency and network structure. We outline future research goals to test these concepts and aid managers in designing effective risk assessment and intervention strategies that will improve translocation success.

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