Assessing the significance of endemic disease in conservation—koalas, chlamydia, and koala retrovirus as a case study

Abstract

It can be difficult to establish the conservation significance of endemic infectious diseases-those that are well established in a population-in contrast with infectious diseases that are still invading. This difficulty can have important implications for designing policy to address species declines. The infectious diseases of koalas provide an ideal case study to examine issues involved in identifying the role of endemic disease in conservation biology. Koala populations are in decline, amidst claims for many years that infectious diseases, particularly those with chlamydial etiology, play a key role in this loss. However, weak associations between prevalence of infection, clinical signs of disease, and population decline mean that it remains unclear whether infectious disease is a primary driver of koala population decline. There are multiple causes of koala decline including drought, habitat destruction, and disease. Welldesigned experiments, linked to appropriate models, are necessary to determine the true role of infectious disease in the current koala population declines and whether a focus on disease is likely to be a feasible, let alone the most cost-effective, means of preventing further declines.

Developing noninvasive methodologies to assess koala population health through detecting Chlamydia from scats

“…Mapping strains, in addition to analyzing data on disease im- the long-standing conundrum that certain populations of koalas seem to cope with Chlamydia better than others (McCallum et al, 2017). Investigating this using scat detection methods, however, might be limited to urogenital tract infections, given that our data suggest that ocular Chlamydia infections cannot consistently be detected in scats using molecular methods.…”

“…One benefit of qPCR and DArTseq methods compared to the detection dog method, however, is that they enable mapping of the co‐occurrence of Chlamydia genotypes in wild populations. Mapping strains, in addition to analyzing data on disease impact (for example, by calculating the proportion of animals with overt signs of Chlamydia across the landscape) and other existing stressors (anthropogenic and environmental) might help elucidate the long‐standing conundrum that certain populations of koalas seem to cope with Chlamydia better than others (McCallum et al, ). Investigating this using scat detection methods, however, might be limited to urogenital tract infections, given that our data suggest that ocular Chlamydia infections cannot consistently be detected in scats using molecular methods.…”

“…Indeed, high Chlamydia loads in urogenital swabs have been found in koalas with no clinically detectable disease (Wan et al, ). It also has to be noted that if a pathogen and a host have co‐evolved for a long time, the pathogen can be found at high prevalence yet disease be the exception, not the rule (Munson et al, ); this possibility has been recently emphasized for the koala– Chlamydia dyad (McCallum et al, ).…”

“…However, many factors can upset this balance such as environmental or physiological stressors, nutrition or concomitant infections or, in the case of new host/parasite associations, the equilibrium might not yet have been reached (Merianos, ). In the Chlamydia /koala case, the cause(s) for variability in pathogenicity between individual koalas and between populations remain(s) speculative (McCallum, Kerlin, Ellis, & Carrick, ; Quigley, Carver, Hanger, Vidgen, & Timms, ). Increasing diagnostic accuracy and efficiency are major steps that can improve our understanding of relationships between ecological factors and disease prevalence, as well as disease severity (Miller, Talley, Lips, & Campbell Grant, ).…”

“…In the Chlamydia/koala case, the cause(s) for variability in pathogenicity between individual koalas and between populations remain(s) speculative (McCallum, Kerlin, Ellis, & Carrick, 2017;Quigley, Carver, Hanger, Vidgen, & Timms, 2018). Increasing diagnostic accuracy and efficiency are major steps that can improve our understanding of relationships between ecological factors and disease prevalence, as well as disease severity (Miller, Talley, Lips, & Campbell Grant, 2012).…”