Spatio-temporal model for the genetic resistance to ash-dieback

Abstract

Ash-dieback is an invasive fungal disease of ash trees characterised by leaf loss and crown dieback in infected trees. First detected in Poland in the early 1990s, it rapidly progressed throughout Europe causing large numbers of deaths and threatening today the survival of the species. We modelled the evolution of the disease from 2010 to 2014 within a field experiment located in northern France, with 777 trees from 23 progenies originating from three french provenances. The objective was to assess the genetic (co)variation associated with two different symptoms: _Crown Dieback_ (CD) and _Collar Lesion_ (CL), since this has direct implications for breeding and for the management of the disease. Due to a high proportion of non-symptomatic observations of CL we used a mixture Binomial-Gamma for modelling the probability of infection and its conditional severity separately at the data level. For CD and both components of CL, a latent gaussian field accounted for some specific relevant covariates, the temporal global trend, the genetic effects and a spatio-temporal structure that represented the regionalized relative exposure to pathogen agent