Classifying forestland from model-generated tree species habitat suitability in the Western Ecoregion of Nova Scotia, Canada
Abstract:Forestland classification is central to the sustainable management of forests. In this paper, we explore the possibility of classifying forestland from species–habitat–suitability indices and a hybrid classification of modeled data. Raster-based calculations of species–habitat–suitability were derived as a function of landscape-level descriptions of incident photosynthetically active radiation (PAR), soil water content (SWC), and growing degree-days (GDD) for southwestern Nova Scotia, Canada. PAR and SWC were both generated with the LanDSET model and GDD from thermal data captured with the space-borne MODIS sensor. We compared the distribution of predicted forestland types with the natural range of target species as found in the provincial permanent sample plots (PSPs). Reasonable agreement (≥50% accuracy) existed between some forestland types (e.g., red maple – white birch – red oak and balsam fir – red maple) and PSP-based assessments of species presence–absence. Agreement was noticeably lower for other forestland types, such as sugar maple – beech – yellow birch (<50% accuracy). This discrepancy is attributed to forest-forming factors not directly addressed by the model, e.g., forest succession, stand interventions, and disturbance. Their addition in the model could change the dynamics of tree-species preference in southwest Nova Scotia and is worth examining. True model inaccuracies accounted for about 0.3%–15.0% of the total reported error.
Document Type: Research Article
Affiliations: 1: Faculty of Forestry and Environmental Management, University of New Brunswick, 28 Dineen Drive, P.O. Box 4400, Fredericton, NB E3B 5A3, Canada. 2: Natural Resources Canada, Canadian Forest Service – Canadian Wood Fibre, Atlantic Forestry Centre, P.O. Box 4000, 1350 Regent Street South, Fredericton, NB E3B 5P7, Canada.
Publication date: March 8, 2013
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