A quantitative approach to defining soil nutrient regimes within ecosystem classifications for Northwestern Ontario

• Published in: Canadian journal of forest research Vol. 53; no. 8; pp. 620 - 641
• Main Authors: Fleming, R.L, Uhlig, P.W, Morris, D.M, Kwiaton, M, Baldwin, K.A, Hazlett, P.W, Webster, K.I, Chapman, K.A
• Format: Journal Article
• Language: English
• Published: Ottawa NRC Research Press 01.08.2023; Canadian Science Publishing NRC Research Press
• Subjects: Analysis; Cation exchange; Cation exchanging; Chemical properties; Classification; Cluster analysis; Clustering; Horizon; Land classification; Nutrients; pH effects; Soil chemistry; Soil nutrients; Soil properties; Soil quality; Soil texture; Soils; Texture; Vector quantization; Ontario
• ISSN: 0045-5067; 1208-6037
• DOI: 10.1139/cjfr-2022-0296

Soil nutrient regimes (SNRs) are often incorporated in ecosystem classifications. Evaluation of actual nutrient levels associated with these SNRs and the development of complementary soil chemistry regimes (SCRs) could broaden their utility. Using data from 618 forest stands in northwestern Ontario, we developed five-category SCRs using K-means clustering and examined relationships among individual nutrients, SCRs, and the SNRs of the Canadian National Vegetation Classification Associations and the Ontario Ecological Land Classification Ecosites. F, A, and B horizon samples were analyzed for organic C (OrgC), total N (TotN), C:N ratio (C:N), cation exchange capacity (CEC), exchangeable bases, base saturation (BaSat), and pH. CEC, pH, and BaSat showed good correspondence across horizons, and together with C:N accounted for much of the variation in chemical properties. There was broad agreement between Association and Ecosite SNRs and B horizon (BHorz) and All horizon (AllHorz) SCRs. C:N decreased while pH and cation metrics increased with increasing SNR and SCR richness. User's accuracies (SNRs vs. SCRs) for the classifications ranged from 31%-39% but increased to 80%-86% for SNR values within [+ or -]1 SCR class. Classification trees identified pH class, soil texture, and overstory composition as the principal field-measured factors related to BHorz SCRs.