Detecting spatial connections within a dendrochronological network on Vancouver Island, British Columbia

In dendrochronology, temporal patterns in radial growth are considered an expression of historical climate processes that cannot be measured. Dendrochronological networks, developed to characterize the geographical and temporal patterns of tree rings, have additional spatial information that can add to our understanding of historical climate conditions. This paper summarizes the use of spatial autocorrelation statistical tools for quantifying spatial trends in dendrochronological networks. Using this approach it is possible to characterize the spatial nature of the process influencing radial growth trends within a tree-ring network. Using a local or mapable measure of spatial autocorrelation it is possible to locate clusters of similar and extreme radial growth trends in any given year and to characterize the persistence of spatial patterns of growth through time. Applied to a dendrochronological network of yellow-cedar (Chamaecyparis nootkatensis (D. Don) Spach), our results suggest that spatial patterns in extreme growth are most often associated with growth limiting climate processes.