Spatial dynamics of chestnut blight disease at the plot level using the Ripley’s K function
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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.
