Modeling Climatic Effects on Stand Height/Site Index of Plantation-Grown Jack Pine and Black Spruce Trees

Occurrence of Density-Dependent Height Repression within Jack Pine and Black Spruce Populations

“…The site-specific and assumed density-independent relationship between the stand height and age is central to the phytocentric approach used to estimate the productivity of even-aged monospecific boreal stand-types (e.g., site index as defined as the mean dominant height or top height at a specified index or base age [23,24,28]). Stand height is traditionally defined as the mean height of the dominant trees within a stand (e.g., mean height of the tallest trees within the upper quintile of the height distribution and traditionally denoted mean dominant height) or as the mean height of the trees with the largest diameters in a stand (e.g., mean height of the trees within the upper quintile of the diameter distribution which is traditionally denoted top height).…”

Simulating the Potential Effects of a Changing Climate on Black Spruce and Jack Pine Plantation Productivity by Site Quality and Locale through Model Adaptation

“…Hence, similar to other models that attempt to project the effects of the future climate, the biophysical models are being used outside of the range of their underlying calibration data sets. Reviewing the values given in Table 1 of Sharma and others [16], indicates that the precipitation and temperature values for their sample sites ranged from a minimum of 403 mm to a maximum of 502 mm, and from 12.0 to 13.4 • C, respectively. Contrasting these values with those given in Table 1 (490 to 577 mm for precipitation and 12.5 to 17.0 • C for temperature), suggest that there is a significant risk of projection error given the power exponent's functional dependence on these variables (Equations (1) and (2)).…”

“…Additionally, more elaborate biophysical models which directly account for GHG concentrations have also been developed and incorporated into stand-level decision-support systems (e.g., SILVA [7]). With respect to the modified SSDMMs presented in this study, Sharma and others [16] evaluated the significance of including additional climate variables into the biophysical height-age model specifications and concluded that adding variables such as soil-moisture related variables, would not significantly improve the explanatory performance of their models (e.g., final model forms explained over 98% of the variation in the dependent variables). …”

“…Specifically, these new models were developed by Sharma and others [16] for black spruce and jack pine plantations for use in Ontario, Canada: Equations (1) and (2) H (i) is the mean dominant height (m) at the ith age (mean stand age at breast-height; A bh(i) ), S I is site index (mean dominant height at a breast-height age of 25 years), P g(jkl) is the mean total precipitation (mm) during the growing season, and T g(jkl) is the mean temperature ( • C) during the growing season, specific to jth geographic location, kth climate change scenario, and lth commitment period. Secondly, the climate parameters (P g(jkl) , T g(jkl) ) were derived from the Canadian Coupled Global Climate Model (CGCM, V. 3.1; Environment Canada [17]) in association with a regional spatial climatic model [18] for two of the three emissions scenarios (B1 and A2 [10]) across the 2011-2040, 2041-2070, and 2071-2100 commitment periods, for sites at Kirkland Lake, Ontario (Ecoregion 3E-Lake Abitibi [19]), Thunder Bay, Ontario (Ecoregion 3W-Lake Nipigon Ecoregion [19]), and Dryden, Ontario (Ecoregion 4S-Lake Wabigoon [19]).…”

“…Although that analysis suggested that jack pine would experience consequential declines in stand development rates resulting in decreases in rotational mean sizes, biomass yields, recoverable end-product volumes, and economic worth under both the B1 and A2 emission scenarios for the higher site qualities, the results were not uniform across all site qualities examined. However, with the advent of the development of the new biophysical site-specific height-age models by Sharma and others [16] applicable to more than a single species, combined with the computational enhancements which corrected for the discrete and dramatic changes in height estimates predicted to occur beginning of the latter two commitment periods, it was possible to: (1) refresh the jack pine simulations by including additional geographic locations (north-western Ontario), deploy operationally relevant rotation lengths, and account for the critically important third commitment period during which growing conditions are expected to rapidly deteriorate, particularly under the A2 emission scenario; and (2) assess the consequences of a changing climate on another commercially important species in terms of Ontario's future wood supply, i.e., black spruce. As a result, this study provides a more inclusive assessment of simulated climate change effects on the productivity of these species, than that of the previous attempt.…”