|
Using the
space-time permutation scan statistic to map anomalous diameter
distributions drawn from landscape-scale forest inventories (with D. MacFarlane,
Michigan State University).
Landscape-scale tree stem size-class distributions
contain information that is potentially useful for evaluating the structural
sustainability of forests, describing the impacts of past disturbance and predicting
future forest structure. One
obstacle to interpreting diameter distributions at large scales is that
typical boundaries used to define populations, such as ecoregions
or counties, may not correspond to areas with different diameter
distributions. We modified the space-time permutation scan statistic
(STPSS), a disease outbreak detection technique, to identify and map areas
in Pennsylvania, USA, where diameter distributions
based on Forest Inventory and Analysis
(FIA) plots differed from the diameter distributions of the state as a
whole. Regression models confirmed
that the STPSS identified areas where the diameter distributions of all
species, oaks, and red maple differed from their corresponding statewide
populations. Through a nested
application of the STPSS at successively smaller spatial scales, we mapped
core zones within each area where the difference was greatest.
|