Tree neighbourhood conditions vary greatly through time for individual trees and throughout a forest at any given time. Therefore, many trees experience very different neighbourhood conditions to the stand mean. Although changes in stand density or species composition are often recommended to mitigate the effects of global change on forest functioning, these recommendations are often based on stand means and lack guidance on acceptable variability around the means or acceptable ranges in neighbourhood conditions. This study examined how the spatial and temporal variability in tree neighbourhood conditions varies between species and with stand structural characteristics. A trees neighbourhood, defined by all trees within a 10-m radius, was quantified in terms of basal area G_N, relative height rh_N (tree height divided by mean height of all trees in neighbourhood), species proportion Prop_N and species richness R_N. Weibull functions were used to describe the frequency distributions of G_N, rh_N, Prop_N and R_N within the stands. Equations were developed to describe the Weibull shape, scale and location parameters as functions of the species, stand basal area, mean tree diameter and management (even-aged vs single-tree selection forests). All of these variables significantly influenced the frequency distributions of neighbourhood characteristics. These equations can be used to show the proportion of trees experiencing significantly higher or lower values of a given characteristic than the stand mean or other threshold values relevant for management objectives. Single-tree selection forests had much greater ranges in neighbourhoods. There were also large temporal changes in tree neighbourhoods, especially in single-tree selection forests. Large trees had not experienced better neighbourhood conditions than smaller trees of approximately the same age, when considered over the long-term. Given that foresters typically consider tree neighbourhoods when marking trees for thinning, and that trees respond to tree neighbourhood conditions rather than to mean stand conditions, stand-level recommendations may be easier to transfer into practice and to interpret, when accompanied by neighbourhood-level information that indicates the distribution of neighbourhoods that actually exist within a stand.