Disease risks associated with translocations

Disease risks associated with translocations of wildlife were addressed in a seminal publication conducted by Cunningham et al. (1996). In the last 14 years, significant advances in our ability to detect and monitor pathogens have improved our epidemiological understanding of pathogen dynamics in natural ecosystems.

Here I evaluate how this study has contributed to new perspectives on disease risk associated with current wildlife management conservation practices.

The role and significance of infectious disease impacts on wildlife remains relatively uncertain. The threat and impact of disease appears to increase as species move closer to extinction (Heard et al. 2013), justifying the need for protection against unnecessary pathogen incursions. The IUCN wildlife health specialist group (IUCN WHSG 2014) and institutes such as the World Organisation for Animal Health (OIE) (OIE 2014) provide guidance upon such matters relating to disease risks associated with the conservation and translocation of wildlife (Jakob-Hoff et al. 2014; OIE & IUCN 2014). However, many translocations occur without sufficient pre- and post-release disease monitoring (Chapter 6 ; Griffith et al. 1993), making it more difficult to assess the role of infectious disease in programme failure.

Correlations between host and pathogen dynamics are inevitable due to dependency of pathogens on their host for survival (Tompkins et al. 2011). Thus any changes in host conditions resulting from translocation may alter this relationship. Although justified for reasons relating to management of small populations, forced perturbation of population dynamics in endangered populations is likely to increase the risk of pathogenic incursions (Torchin & Mitchell 2004). Additionally, translocation mediated stress (Teixeira et al. 2007) may induce immunosuppression and increase susceptibility to disease in the species of concern (Kock et al. 2007; Viggers et al. 1993). Disease can have significant impacts on populations and if an outbreak were to occur within an endangered species it could take decades to recover, particularly if they have low reproductive output (Rushmore et al. 2013). Pathogen incursions may not necessarily result in mortality, instead impacting hosts in subtle ways causing a reduction in fitness, reproduction and changes in behaviour. Pathogen associated morbidity can be difficult to detect, for example animals infected with Toxoplasma gondii show no overt symptoms of disease but the protozoan can influence the behaviour of its host, increasing risk and likelihood of transmission between mice and cats (Berdoy et al. 2000).

Co-evolutionary interactions between hosts and their pathogens can be determined by spatial characteristics and resulting gene flow (Archie & Ezenwa 2011; Gandon & Nuismer 2009). If infectious organisms are carried across ecological barriers through the translocation process, allopatric speciation of host-adapted organisms is a distinct possibility within the new environment (Chapter 4). Alternatively, host management and the presence of alternative reservoirs may increase opportunities for genetic recombination between infectious organisms (Chapter 4). For example, antibiotic resistance genes were detected in gram negative bacteria isolated from faecal samples of the captive brush-tail rock wallaby (Petrogale penicillata) but were

not present in the bacteria isolated from the wild populations (Power et al. 2013). The class 1 integrons were thought to have been acquired from environmental contamination during captivity (Power et al. 2013). Similarly, the genotype diversity of C. sp. nova 1 carried by takahe populations was associated with host location (Chapter 4). The functional significance of the microbial diversity in my study was not determined, but it does demonstrate that translocation has the potential to cause changes to the host’s microbiota. The unforeseen developments described above would not be mitigated by current practices of targeted pathogen screening prior to translocation. Most disease surveillance of wildlife translocations is extremely limited with targeted organisms being identified only to genus or species level. This ignores the possibility of detecting strain variation, or novel organisms such as the C. sp. nova 1 identified in this study.

If the isolation of wildlife into sub-populations is resulting in biogeographic divergence of micro-organisms (Chapter 4), a natural question arises whether conservation practices should be less conservative and increase mixing of sub-populations with the aim of building immunity and resilience for pathogen incursions. A study of plant-fungal relationships found that highly connected host populations experienced lower incidence of pathogens due to increased levels of disease resistance (Jousimo et al. 2014). Many infectious organisms exhibit variation in pathogenicity and can be unpredictable if transmitted to naive hosts; what is a commensal in one species may be a pathogen in another (Waldenstrom et al. 2010). For instance, Hendra virus is carried asymptomatically by bats of the genus Pteropus in Australia (Halpin et al. 2011). Incidental viral spill-over into horses or humans in areas where bat colonies overlap with urban centres (Plowright et al. 2011) results in disease symptoms and occasionally death in the new host (Daszak et al. 2006; Playford et al. 2010). Translocation decisions and risk assessments should ideally account for potential reservoirs of pathogens within a location and the possibility of bidirectional transmission of generalist infectious organisms able to colonise and transmit between sympatric wildlife. However, the logistical difficulty of accounting for the increasingly complex interactions of the host and microbiome described in my study make accurate risk assessment of translocations problematic, especially with the limited budgets available to most conservation programmes.

Our ability to inform conservation management is hindered by our inability to capture the influence of complex interactions between hosts and environments and their potential confounding effects on pathogen diversity. In situ investigations of wildlife epidemics are insightful, however free living animals are frequently inconspicuous especially if afflicted by illness and the recovery of samples from unhealthy or deceased individuals may be logistically difficult. Although currently underexploited, non-invasive epidemiological investigations of host-commensal relationships in wildlife populations are a good proxy for 125

the study of infectious disease epidemiology and as a result are gradually increasing in popularity, e.g. (Bull et al. 2012; Chapter 3 ; Chapter 4 ; Chapter 5 ; Chiyo et al. 2014). Recent advances in epidemiological tools, methods and interdisciplinary research are starting to improve our understanding of pathogen dynamics and may in time improve the accuracy of our forecasting of disease risk associated with translocations of wildlife.