title: Two-dimensional wavelet analysis of spruce budworm host basal area in the Border Lakes landscape.
abstract: Increases in the extent and severity of spruce budworm (Choristoneura fumiferana Clem.) outbreaks over the last century are thought to be the result of changes in forest structure due to forest management. A corollary of this hypothesis is that manipulations of forest structure and composition can be used to reduce future forest vulnerability. However, to what extent historical forest management has influenced current spatial patterns of spruce budworm host species is unknown. To identify landscape-scale spatial legacies of forest management in patterns of spruce budworm host species (i.e., Abies balsamea and Picea spp.), we analyzed remotely sensed forest data from the Border Lakes landscape of northern Minnesota and northwestern Ontario. Our study area contains three regions with different management histories: (1) fine-scale logging patterns in Minnesota, (2) coarse-scale logging patterns in Ontario, and (3) very limited logging history in the Boundary Waters Canoe Area and adjacent Quetico Provincial Park. We analyzed forest basal-area data using wavelets and null models to identify: (1) at which scales forest basal area is structured, (2) where those scales of pattern are significantly present, and (3) whether regions of local significance correspond to regional boundaries that separate the study area. Results indicate that spatial patterns in host basal area are created by nonstationary processes and that these processes are further constrained by lakes and wetlands. Wavelet analysis combined with significance testing revealed a bimodal distribution of scale-specific wavelet variance and separate zones of host species basal area that partially correspond with regional boundaries, particularly between Minnesota and the Wilderness region. This research represents one of the first comparisons of forest spatial structure in this region across an international border and presents a novel method of two-dimensional wavelet analysis that can be used to identify significant scale-specific structure in spatial data.
authors.affiliation: Faculty of Forestry, University of Toronto, Toronto, Ontario M5S3B3, Canada. pjames@ualberta.ca
authors.forename: Patrick M A
authors.initials: PM
authors.lastname: James
authors.forename: Brian R
authors.initials: BR
authors.lastname: Sturtevant
authors.forename: Phil
authors.initials: P
authors.lastname: Townsend
authors.forename: Pete
authors.initials: P
authors.lastname: Wolter
authors.forename: Marie-Josée
authors.initials: MJ
authors.lastname: Fortin
mesh_terms: D000818:Animals; D017753:Ecosystem; D004784:Environmental Monitoring; D008910:Minnesota; D008954:Models, Biological; D009036:Moths / Q000502:physiology*; D009864:Ontario; D011156:Population Density; D013997:Time Factors; D014197:Trees