Isotopic niche variation in Tasmanian devils Sarcophilus harrisii with progression of devil facial tumor disease

Abstract

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Living in human-modified landscapes narrows the dietary niche of a specialised mammalian scavenger

“…Instead, the higher nitrogen values found in heavier devils indicate that they were feeding primarily on medium-sized herbivorous mammals, while the lower values of smaller devils imply a diet of herbivorous birds 54 . This relationship was consistent with previous findings that better body condition was associated with higher nitrogen in DFTD-affected devils 67 and carnivore body size being correlated with prey body size is a common trend observed between species 104 – 107 . Although species that frequently scavenge can get around the constraints of their body size, feeding on carcasses the same size or larger than themselves, greater competition surrounding these carcasses that are easier to find and harder to quickly remove still favours larger individuals 108 .…”

“…They were limited however, by their ability to only use short-term dietary data from scat or stomach contents containing food that had been consumed over approximately one day 65 . Bulk stable isotope analysis of nitrogen and carbon in whiskers has more recently been used for longer-term analysis of devil diets based on differences in age 66 , DFTD status 67 , and body size and intraspecific competition 54 over several weeks or months. While nitrogen isotopic composition is frequently used to provide an indication of trophic position within the food web, as nutrients from food items are assimilated into the body tissue of consumers in a predictable manner 68 – 70 , carbon isotopic composition can differ significantly at the vegetation baseline of the ecosystem depending on the characteristics of plant species and environmental conditions 71 – 74 .…”

Coupling spatial statistics with social network analysis to estimate distinct risk areas of disease circulation to improve risk‐based surveillance

“…Even with the development of the R‐INLA, inlabru, and rSPDE packages (E. Bachl et al., 2019; Bolin & Kirchner, 2020; van Niekerk et al., 2021), more specifically the work done by Bakka et al. (2019) that implemented the option for a non‐stationary barrier model directly via R‐ILNA, the vast majority of non‐stationary models have been limited to ecology (Bell et al., 2021), fisheries (Monnahan et al., 2021), and theoretical studies (Lindgren et al., 2022; Sanz‐Alonso & Yang, 2021). One reason for a lack of studies that include the explicit effect of barriers in animal disease epidemiology may be associated with the challenges of model implementation, which have been resolved by Bakka et al.…”

“…to ecology (Bell et al, 2021), fisheries (Monnahan et al, 2021), and theoretical studies (Lindgren et al, 2022;Sanz-Alonso & Yang, 2021). One reason for a lack of studies that include the explicit effect of barriers in animal disease epidemiology may be associated with the challenges of model implementation, which have been resolved by Bakka et al (2019).…”

The SPDE approach for Gaussian and non-Gaussian fields: 10 years and still running

“…As an initial illustration of the method's practical relevance, we here present an incomplete list of recent applications. In the time-period of May-Sep 2021, we find applications of the SPDE-approach to Gaussian fields in astronomy (Levis et al, 2021), health (Mannseth et al, 2021;Scott, 2021;Moses et al, 2021;Bertozzi-Villa et al, 2021;Moraga et al, 2021;Asri and Benamirouche, 2021), engineering (Zhang et al, 2021), theory (Ghattas and Willcox, 2021;Sanz-Alonso and Yang, 2021a;Lang and Pereira, 2021;Bolin and Wallin, 2021), environmetrics Beloconi et al, 2021;Vandeskog et al, 2021a;Wang and Zuo, 2021;Wright et al, 2021;Gómez-Catasús et al, 2021;Valente and Laurini, 2021b;Bleuel et al, 2021;Florêncio et al, 2021;Valente and Laurini, 2021a;Hough et al, 2021), econometrics (Morales and Laurini, 2021;Maynou et al, 2021), agronomy (Borges da Silva et al, 2021), ecology (Martino et al, 2021;Sicacha-Parada et al, 2021;Williamson et al;Bell et al, 2021;Humphreys et al;Xi et al, 2021;Fecchio et al), urban planning (Li, 2021), imaging (Aquino et al, 2021), modelling of forest fires (Taylor et al; Lindenmayer et al), fisheries (Babyn et al, 2021;van Woesik and Cacciapaglia, 2021;Jarvis et al, 2021;…”