Author(s)

Shane Furze¹, Mark Castonguay¹, Jae Ogilvie¹, Mina Nasr¹, Pierre Cormier¹, Rolland Gagnon², Greg Adams², Paul A. Arp¹

¹Forest Watershed Research Center, UNB Faculty of Forestry and Environmental Management, Fredericton, Canada.
²J.D. Irving Ltd., Sussex, Canada.

This article focuses on modelling and mapping the productivity of black (Picea mariana) and white spruce (Picea glauca) plantations across the Black Brook forest management area in northwestern New Brunswick, Canada, encompassing about 200,000 ha. This effort involved establishing 3500 50 m2 survey plots, each informing about: plantation age (15 to 43 years), planted species type, stem count, tree height, basal area, and wood volume. All of this was supplemented with location-specific productivity predictors, i.e., xy location and specifications pertaining to soil type, soil drainage (established through digital elevation modelling by way of the depth-to-water index DTW), and years since thinning (pre-commercial and commercial), and. The DTW index, as it emulates the elevation rise away from open water features such as streams, rivers and lakes, allowed the re-mapping of existing soil borders by topographic position and drainage association. Non-linear regression analysis revealed that plantation height, basal area and volume all increased with plantation age, as to be expected. Pre-commercial thinning in plantations <30 years old had a positive while the more recent commercial thinning still had the negative effect on standing wood volume and mean annual volume increment (MAI). White spruce MAI generally exceeded black spruce (MAI) by a factor of 1.25. Poor and excessive soil drainage reduced MAI. Best growth performances occurred on plantations established on well-drained calcareous soils. The best-fitted results so obtained allowed for generating black and white spruce MAI maps across the forest management area by ridge-to-valley soil and DTW location at 10 m resolution. These maps were subsequently used for site-by-site silvicultural evaluation and ranking purposes.

Forest Plantation Productivity Mapping, Black Spruce, White Spruce, Soil Type & Drainage, Digital Terrain Modelling

Furze, S. , Castonguay, M. , Ogilvie, J. , Nasr, M. , Cormier, P. , Gagnon, R. , Adams, G. and Arp, P. (2017) Assessing Soil-Related Black Spruce and White Spruce Plantation Productivity. Open Journal of Forestry, 7, 209-227. doi: 10.4236/ojf.2017.72013.