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Life-history trade-offs can mediate population declines following perturbations, and early reproduction should be favoured when adult survival is impacted more than juvenile survival. In Tasmanian devils (Sarcophilus harrisii), following the emergence of a transmissible cancer that caused steep population declines, females started to breed precocially (i.e. at age 1 instead of 2 years old). Here, using 18 years of mark–recapture data from a site where the disease was present (Freycinet Peninsula, Tasmania, Australia), we tested whether: (i) the probability of 1-yea-old females breeding continued to increase over time; (ii) there was a relationship between body size and breeding success for either 1-year-old or adult females; and (iii) there was inbreeding depression in breeding success for either age category. We show that the probability of 1-year-old females breeding did not increase between 2003 and 2021, and that the proportion of precocially breeding females remains at around 40%. We also show that there was no effect of skeletal body size on the probability of breeding, but heavier females were always more likely to breed. Finally, we found no evidence for inbreeding depression in breeding success. We discuss our results in the context of possible constraints by way of limitations to growth in the offspring of precocially breeding females. 

Coevolution is common and frequently governs host–pathogen interaction outcomes. Phenotypes underlying these interactions often manifest as the combined products of the genomes of interacting species, yet traditional quantitative trait mapping approaches ignore these intergenomic interactions. Devil facial tumor disease (DFTD), an infectious cancer afflicting Tasmanian devils (Sarcophilus harrisii), has decimated devil populations due to universal host susceptibility and a fatality rate approaching 100%. Here, we used a recently developed joint genome-wide association study (i.e., co-GWAS) approach, 15 y of mark-recapture data, and 960 genomes to identify intergenomic signatures of coevolution between devils and DFTD. Using a traditional GWA approach, we found that both devil and DFTD genomes explained a substantial proportion of variance in how quickly susceptible devils became infected, although genomic architectures differed across devils and DFTD; the devil genome had fewer loci of large effect whereas the DFTD genome had a more polygenic architecture. Using a co-GWA approach, devil–DFTD intergenomic interactions explained ~3× more variation in how quickly susceptible devils became infected than either genome alone, and the top genotype-by-genotype interactions were significantly enriched for cancer genes and signatures of selection. A devil regulatory mutation was associated with differential expression of a candidate cancer gene and showed putative allele matching effects with two DFTD coding sequence variants. Our results highlight the need to account for intergenomic interactions when investigating host–pathogen (co)evolution and emphasize the importance of such interactions when considering devil management strategies. 

Abstract Emerging infectious diseases (EIDs) not only cause catastrophic declines in wildlife populations but also generate selective pressures that may result in rapid evolutionary responses. One such EID is devil facial tumour disease (DFTD) in the Tasmanian devil. DFTD is almost always fatal and has reduced the average lifespan of individuals by around 2 years, likely causing strong selection for traits that reduce susceptibility to the disease, but population decline has also left Tasmanian devils vulnerable to inbreeding depression. We analysed 22 years of data from an ongoing study of a population of Tasmanian devils on Freycinet Peninsula, Tasmania, to (1) identify whether DFTD may be causing selection on body size, by estimating phenotypic and genetic correlations between DFTD and size traits, (2) estimate the additive genetic variance of susceptibility to DFTD, and (3) investigate whether size traits or susceptibility to DFTD were under inbreeding depression. We found a positive phenotypic relationship between head width and susceptibility to DFTD, but this was not underpinned by a genetic correlation. Conversely, we found a negative phenotypic relationship between body weight and susceptibility to DFTD, and there was evidence for a negative genetic correlation between susceptibility to DFTD and body weight. There was additive genetic variance in susceptibility to DFTD, head width and body weight, but there was no evidence for inbreeding depression in any of these traits. These results suggest that Tasmanian devils have the potential to respond adaptively to DFTD, although the realised evolutionary response will critically further depend on the evolution of DFTD itself. 

Emerging infectious diseases pose one of the greatest threats to human health and biodiversity. Phylodynamics is often used to infer epidemiological parameters essential for guiding intervention strategies for human viruses such as severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2). Here, we applied phylodynamics to elucidate the epidemiological dynamics of Tasmanian devil facial tumor disease (DFTD), a fatal, transmissible cancer with a genome thousands of times larger than that of any virus. Despite prior predictions of devil extinction, transmission rates have declined precipitously from ~3.5 secondary infections per infected individual to ~1 at present. Thus, DFTD appears to be transitioning from emergence to endemism, lending hope for the continued survival of the endangered Tasmanian devil. More generally, our study demonstrates a new phylodynamic analytical framework that can be applied to virtually any pathogen. 

Abstract Infectious diseases are strong drivers of wildlife population dynamics, however, empirical analyses from the early stages of pathogen emergence are rare. Tasmanian devil facial tumour disease (DFTD), discovered in 1996, provides the opportunity to study an epizootic from its inception. We use a pattern‐oriented diffusion simulation to model the spatial spread of DFTD across the species' range and quantify population effects by jointly modelling multiple streams of data spanning 35 years. We estimate the wild devil population peaked at 53 000 in 1996, less than half of previous estimates. DFTD spread rapidly through high‐density areas, with spread velocity slowing in areas of low host densities. By 2020, DFTD occupied >90% of the species' range, causing 82% declines in local densities and reducing the total population to 16 900. Encouragingly, our model forecasts the population decline should level‐off within the next decade, supporting conservation management focused on facilitating evolution of resistance and tolerance.