Validating tree species composition in forest resource inventory for Nipissing Forest, Ontario, Canada

Abstract

Species composition estimated from forest resource inventory (FRI) was validated using field data collected in 136 stands in Nipissing Forest (Ontario, Canada). FRI-and field-based species composition matched in 54% and 56% of cases using stand count and area coverage, respectively. Possible causes of discrepancy between FRI-and field-based species composition are discussed. Low level of agreement between FRI and field data indicated a need for more extensive studies on FRI validation prior to its use for forest management planning.Key words: forest resource inventory, FRI, forest unit, photo-interpretation, timber cruise RÉSUMÉ La composition en espèces estimée à partir de l'inventaire des ressources forestières (IRF) a été validée au moyen des données de terrain recueillies dans 136 peuplements de la forêt de Nipissing (Ontario, Canada). L'IRF et la composition en espèces sur le terrain ont concordé pour 54% et 56% des cas en utilisant respectivement un décompte des peuplements et le recouvrement en superficie. Les causes probables de différence entre l'IRF et la composition en espèces sur le terrain font l'objet de discussion. Le faible taux de concordance entre l'IRF et les données du terrain indiquent la nécessité d'avoir des études plus exhaustives de la validité de l'IRF avant son utilisation à des fins d'aménagement forestier. IntroductionThe main source of information for forest management planning in Ontario is the Forest Resource Inventory (FRI). In general, a forest resource inventory may be defined as a survey of an area to provide information on the present extent, composition, structure and location of the forest (Gillis and Leckie 1993). In Ontario, the FRI is conducted on a cycle of approximately 20 years. The primary data sources for FRI production are aerial photographs taken at 1:20 000 for northern Ontario and 1:10 000 for southern Ontario. These photographs are used to delineate forest stands and assess other stand attributes through interpretation of photos calibrated with timber cruise plots established subjectively in For personal use only.

Changes to preindustrial forest tree composition in central and northeastern Ontario, Canada

“…One limitation of using FRI data are that changes in composition of understory and (or) smallcrowned species (e.g., eastern white cedar (Thuja occidentalis L.) and balsam fir) may arise not from an actual change but from differences between the ground-based OLS and the aerial photographs used to create the current FRI. A second limitation is that, in Ontario, photointerpreted FRI before 2007 was not validated through ground sampling. Potvin et al (1999) and Pinto et al (2007) show that errors in describing tree species composition through photointerpretation do happen and result in errors in describing the current composition of a forest. To reduce errors that may occur with tree growth, reproduction, and mortality, the most current inventory data available were used in our analyses, i.e., >70% of our study area was updated between 2001 and 2006.…”

Multi-Temporal Polarimetric RADARSAT-2 for Land Cover Monitoring in Northeastern Ontario, Canada

“…The forest land cover is a mix of deciduous and coniferous species, with fully developed canopies at the time of the first acquisition (20 June), therefore little change in size and structure occurred over the time of the study. Forests in the area are typically mixedwoods dominated by such hardwoods as red maple (Acer rubrum), sugar maple (Acer saccharum), and red oak (Quercus rubra), as well as softwoods like eastern white pine (Pinus strobus) and balsam fir (Abies balsamea) [17,18]. Sturgeon Falls, a town with a population of approximately six thousand, was used as the urban target as it comprises a combination of roads and buildings with natural vegetation dispersed throughout [19].…”

A comparison of forest resource inventory, provincial land cover maps and field surveys for wildlife habitat analysis in the Great Lakes – St. Lawrence forest

“…These field data are often referred to and treated as "ground truth", in effect without error; examples include Dussault et al (2001), Cunningham (2006), and Thompson et al (2007). However, there is a strong argument and, in fact, a shift in terminology in the literature (e.g., Pinto et al 2007, Booth et al 2008, to a recognition that field-based estimates of stand characteristics such as species composition, age, stocking density, and height, also contain errors. Thus, correspondence between data derived from these two sources, while useful for assessing validity, and offering insight into the likely nature and magnitude of error, is not accuracy analysis per se.…”