Canadian Woodlands Forum (CWF) Presentation - Oct 2019
Species Map Images and Accuracy Statistics
You will need to superimpose non-productive land features and semi-productive bogs on these maps. The species models are not applicable in areas without trees and in marginal forest-land.
Ecological relative abundance (affinity) of tree species in New Brunswick on any given topographical position, based on provincial ground surveys and photo-interpretation of immature-old stands in that area.
The CWF presentation link above provides more details on methods; or, contact Dr. Chris Hennigar at FORUS Research for the latest information on this work.
These maps may allow you to:
For understanding where species have naturally regenerated in NB and where they tend to compete well, these maps are useful. They are not useful for mapping current species distributions; for that, see the NB provincial forest inventory shapefile on GeoNB.
For any given location point, these maps explained about 20-50% of species variability in unmanaged immature-old forest established before 1980; see Accuracy Statistics pdf link above. If accuracy was to be accessed more broadly with species relative abundance averaged over all stands sitting on similar topographical positions within each eco-district, we would expect accuracy to be quite a bit higher. This has not been assessed, but is probably a better indicator of the ecological relative abundance of a species on a particular eco-site we have observed.
Species with strong ecological site preferences (e.g., sugar maple, black spruce) seemed to be mapped at higher accuracy compared to generalists (e.g., red maple, white birch), rare species (e.g., tamarack), or common but relatively dispersed species that are present in small amounts on many sites (e.g., white pine).
As availability of LIDAR derived DEMs, better digital soil maps, and remote sensing information improves over the next few years, we hope to revisit this work. Currently, species were mapped locally to elevation, depth-to-water, and slope layers derived from SRTM data.
We would also like to try to prorate all of these species mapped % values to add up to 100% and then map ecological affinity of species composition types in a single raster layer. Users are encouraged to try this themselves; we would love to see your results. Keep in mind that there are some small tree and rare hardwood and softwood species maps missing (e.g., oak, ash, red pine, non-commercial hardwood), and we hope to someday get to those.