Season, decay stage, habitat, temperature and carrion beetles allow estimating the post‐mortem interval of wild boar carcasses

Author:

Müller Jörg12ORCID,Rietz Janine23ORCID,von Hoermann Christian12ORCID,Conraths Franz J.4,Benbow M. Eric5ORCID,Mitesser Oliver1ORCID,Schlüter Jens2,Lackner Tomáš2ORCID,Reckel Frank6,Heurich Marco23ORCID

Affiliation:

1. Field Station Fabrikschleichach, Department of Animal Ecology and Tropical Biology Biocenter University of Würzburg Rauhenebrach Germany

2. Bavarian Forest National Park Grafenau Germany

3. Chair of Wildlife Ecology and Management Albert Ludwigs University Freiburg Freiburg Germany

4. Friedrich‐Loeffler‐Institut Federal Research Institute for Animal Health, Institute of Epidemiology Greifswald‐Insel Riems Germany

5. Department of Entomology; Department of Osteopathic Medical Specialties; Ecology, Evolution and Behavior Program; AgBioResearch Michigan State University East Lansing Michigan USA

6. Bavarian State Criminal Police Office Munich Germany

Abstract

Abstract The decay process of animal carcasses is a highly complex succession driven by abiotic and biotic variables and their interactions. As an underexplored ecological recycling process, understanding carrion decomposition associated with pandemics such as African swine fever is important for predicting the rate and post‐mortem interval (PMI) variation of wild animal carcasses to improve disease management. To model PMIs of wild boar, we deployed 73 wild boar carcasses in four different forest habitat types throughout a year and monitored the decomposition process, carrion beetles and blow fly larval populations. The 601 single observations were split randomly into 501 training data and 100 validation data. A linear additive mixed model for log‐transformed PMI values using the training data identified the decay stage, day of year, ambient temperature during sampling, habitat and prevalence of Oiceoptoma thoracicum (Silphidae) as predictive variables for time since death, but neither the initial body mass nor if a fresh or previous frozen carcass was used. Using the validation data, this model showed a high predictive power for log‐transformed PMI values (R2 = 0.80). This study aimed at improving the methodology of estimating the PMI of wild boar carcasses based on important abiotic and biotic environmental factors that can be easily assessed in the field. Using only a small set of predictors, including a conspicuous beetle species, allowed prediction of the mean, minimum and maximum PMI of wild boar carcasses. The strong effects of a few surrogates on PMI in our model suggest that this model can easily be transferred to wider regions of Central Europe by retraining the model with data from a broader environmental space and can thus be instrumental in assessing timing of disease introduction in areas newly affected by emerging diseases such as African swine fever.

Publisher

Wiley

Subject

Management, Monitoring, Policy and Law,Nature and Landscape Conservation,Ecology,Global and Planetary Change

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