Spatial dynamics of chestnut blight disease at the plot level using the Ripley’s K function Conference Paper uri icon

abstract

  • We used the Ripley’s K function, a second order analysis method, to describe the spatial dynamics of tree infection caused by chestnut blight (Cryphonectria parasitica (Murrill) Barr) in sweet chestnut orchards. Our research question was whether the location of infected trees affected the spatial pattern of spread of the disease in orchards. We also wanted to know whether existing patterns could be associated with management practices. Surveys of infections and mortality caused by chestnut blight were conducted at the tree level in 4 plots in 2003, 2004, 2005, and 2009 in the Curopos parish, Vinhais, Portugal. We applied the Ripley’s K function to locations of diseased (infected and dead) trees to look for spatial pattern. We compared locations from successive dates using the bivariate form of the K function to look for spatial association of diseased trees in consecutive years. We found both random and aggregated patterns of infected trees in the beginning of the study period and significant association of infected trees between successive dates, particularly at short distances. The results indicate that fast, short distance spread of chestnut blight occurs within orchards which can possibly be explained by both natural propagation of the disease and management practices.
  • We used the Ripley’s K function to describe the spatial dynamics of chestnut blight (Cryphonectria parasitica (Murrill) Barr) in sweet chestnut orchards to look at pattern in the pathogen distribution over time and the effect of the location of infected trees on the pattern of disease spread. We used data on infected and dead trees in 2003, 2004, 2005, and 2009 in 4 orchards located in Curopos parish, Portugal. We found both random and aggregated patterns of infected trees in the beginning of the study period and significant association of infected trees between successive dates, particularly at short distances. Two of the 4 studied orchards showed significant clustering of infected and dead trees in any of the dates observed but random spatial pattern in the remaining two which can possibly be explained by both natural propagation of the disease and management practices.

publication date

  • January 1, 2010