ORCID Profile
0000-0002-0014-3293
Current Organisation
Nipissing University
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: Oxford University Press (OUP)
Date: 19-01-2012
Publisher: Canadian Institute of Forestry
Date: 02-2012
DOI: 10.5558/TFC2012-010
Abstract: Forest Ecosystem Classification (FEC) systems were originally developed and used in the Province of Ontario at regional levels with the objective of classifying forest ecosystems to support silvicultural decision-making in an operational setting. A new provincial Ecological Land Classification (ELC) system has been developed, which integrates the regional systems into a single consistent framework. To make continued use of data and knowledge gained from long-term forest monitoring plots classified under the old FEC system, such as Permanent Growth Plots (PGPs), Permanent S le Plots (PSPs) and Temporary S le Plots (TSPs), an ecosite conversion from the existing FEC data to the new ELC system was deemed necessary. We developed a conversion matrix to convert FEC ecosite classifications from the northeast and north-west to the provincial ELC system for the boreal forest region of Ontario. The conversion system is intended to apply at the scale of in idual plots, with a special focus on PGP, PSP and TSP networks, and has been limited to forested ecosystems, as FEC systems were originally developed for the forest land base only. The conversion is primarily driven by canopy cover composition derived from plot-based in idual tree data, with additional information required on substrate characteristics (e.g., substrate type, depth of mineral material, effective soil texture and moisture regime). It is possible to derive some of the soil variables from the broadly defined soil-type (S-type) categories of the original FEC systems however, this approach requires making some assumptions that could reduce the accuracy of conversion. We anticipate that this conversion matrix will bridge the gap until active plot networks are re-typed in the field into the ELC system, provide a link to historical TSPs, and would be of general interest to a variety of new ELC users.
Publisher: MDPI AG
Date: 08-12-2016
DOI: 10.3390/F7120311
Publisher: Canadian Science Publishing
Date: 05-2014
Abstract: Enhanced forest resources inventory systems delineate and define polygons based on fundamental ecological units such as ecosites, which are standard combinations of vegetation and substrate types. Our study objective was to model wood quality characteristics of in idual black spruce (Picea mariana (Mill.) B.S.P.) trees across a representative boreal forest landscape in northeastern Ontario, Canada, based on relationships to ecosite and other stand-level variables. A total of 127 large (12 mm) increment core s les were extracted at breast height from dominant or co-dominant black spruce trees in forest stands representing a gradient from dry sandy to wet mineral and organic ecosites. S le cores were prepared, processed, and analyzed using standard SilviScan protocols. Hierarchical classification models were then fitted using Random Forests to predict density and latewood percentage for black spruce stems at a reference age of 50 years. These models each explained over 32% of variance, with estimated root mean squared errors of 40.4 kg·m −3 and 5.6% for density and latewood percentage, respectively. Among tree-, site-, and stand-level covariates, ecosite group was the most important predictive variable. Knowledge of ecosite – wood quality relationships could support efficient planning for black spruce management by including an indication of potential use as a modeled variable in a forest inventory system.
Publisher: Canadian Institute of Forestry
Date: 02-2011
DOI: 10.5558/TFC87023-1
Abstract: Forest site classification is a prerequisite to successful integrated forest resources planning and management. Traditionally,site classification has emphasized a phytocentric approach, with tools such as the site index having a rich and longhistory in forest site evaluation. The concept of site index was primarily devised to assess site productivity of an even-aged,single-species stand. Site index has been the primary method of forest site evaluation in support of management for traditionalforest products. However, this method of site classification has been criticized as the needs, perspectives andsocial values of the public regarding forest management have changed the emphasis from timber production to multiplevalueforestry practices. There are alternative approaches to forest site classification that have the potential to meet thegrowing demands placed on forest information for inventory and modeling purposes. Ecological Land Classification(ELC), is a phytogeocentric approach that stratifies the landscape into ecologically meaningful units (ecosites) based onsubstrate characteristics, moisture regime and canopy composition. This approach offers a more holistic view of site productivityevaluation however, until recently it has been difficult to acquire data to support widespread mapping ofecosites. Remote sensing technology along with predictive modeling and interpretive mapping techniques make the applicationof an ecosite-based approach at the forest landscape level possible. As forest management moves towards the considerationof a broader set of resources (e.g., woody biomass), there is an opportunity to develop new tools for linking forestproductivity to the sustainable production of forest bioproducts with forest ecosites as a solid foundation forsegmenting the landscape. Key words: forest site classification, site index, site productivity, Ecological Land Classification (ELC), ecosites, forest biomass,bioproducts
Publisher: MDPI AG
Date: 24-09-2015
DOI: 10.3390/F6103369
Publisher: Elsevier BV
Date: 2014
No related grants have been discovered for Jeffery Dech.