Modeling perspectives of forest growth and yield: Framework of multivariate diffusion process

2019 ◽  
Author(s):  
P. Rupšys
Keyword(s):  
Diffusion Process ◽  
Forest Growth ◽  
Growth And Yield ◽  
Forest Growth And Yield

Ontario's forest growth and yield modelling program: Advances resulting from the Forestry Research Partnership

2008 ◽  
Vol 84 (5) ◽  
pp. 694-703 ◽  
Author(s):  
Mahadev Sharma ◽  
John Parton ◽  
Murray Woods ◽  
Peter Newton ◽  
Margaret Penner ◽  
...  
Keyword(s):  
Tree Species ◽  
Stand Density ◽  
Forest Growth ◽  
Growth And Yield ◽  
Research Partnership ◽  
Wood Supply ◽  
Permanent Sample Plots ◽  
Forestry Research ◽  
Research Activities ◽  
Forest Growth And Yield

The province of Ontario holds approximately 70.2 million hectares of forests: about 17% of Canada’s and 2% of the world’s forests. Approximately 21 million hectares are managed as commercial forests, with an annual harvest in the early part of the decade approaching 200 000 ha. Yield tables developed by Walter Plonski in the 1950s provide the basis for most wood supply calculations and growth projections in Ontario. However, due to changes in legislation, policy, and the planning process, they no longer fully meet the needs of resource managers. Furthermore, Plonski`s tables are not appropriate for the range of silvicultural options now practised in Ontario. In October 1999, the Canadian Ecology Centre- Forestry Research Partnership (CEC-FRP) was formed and initiated a series of projects that collectively aimed at characterizing, quantifying and ultimately increasing the economically available wood supply. Comprehensive, defensible, and reliable forecasts of forest growth and yield were identified as key knowledge gaps. The CEC-FRP, with support from the broader science community and forest industry, initiated several new research activities to address these needs, the results of which are outlined briefly in this paper. We describe new stand level models (e.g., benchmark yield curves, FVS Ontario, stand density management diagrams) that were developed using data collected from permanent sample plots and permanent growth plots established and remeasured during the past 5 decades. Similarly, we discuss new height–diameter equations developed for 8 major commercial tree species that specifically account for stand density. As well, we introduce a CEC-FRP-supported project aimed at developing new taper equations for plantation grown jack pine and black spruce trees established at varying densities. Furthermore, we provide an overview of various projects undertaken to explore measures of site productivity. Available growth intercept and site index equations are being evaluated and new equations are being developed for major commercial tree species as needed. We illustrate how these efforts are advancing Ontario’s growth and yield program and supporting the CEC-FRP in achieving its objective of increasing the supply of fibre by 10% in 10 years while maintaining forest sustainability. Key words: permanent sample plots (PSPs), permanent growth plots (PGPs), normal yield tables, sustainable forest management, NEBIE plot network, forest inventory, Forest Vegetation Simulator

Development and Use of Bounding Functions in a Forest Growth Model

1993 ◽  
Vol 8 (1) ◽  
pp. 24-27
Author(s):  
K. Leroy Dolph ◽  
Gary E. Dixon
Keyword(s):  
Computer Simulation ◽  
Simulation Models ◽  
Height Growth ◽  
Forest Growth ◽  
Growth And Yield ◽  
Forest Growth Model ◽  
Individual Trees ◽  
Computer Simulation Models ◽  
Forest Growth And Yield

Abstract Erroneous predictions of forest growth and yield may result when computer simulation models use extrapolated data in repeated or long-term projections or if the models are used outside the range of data on which they were built. Bounding functions that limit the predicted diameter and height growth of individual trees to maximum observed values were developed to constrain these erroneous predictions in a forest growth and yield simulator. Similar techniques could be useful for dealing with extrapolated data in other types of simulation models. West. J. Appl. For. 8(1):24-27.

scholarly journals Using JABOWA-3 for forest growth and yield predictions under diverse forest conditions of Nova Scotia, Canada

2012 ◽  
Vol 88 (06) ◽  
pp. 708-721 ◽  
Author(s):  
M. Irfan Ashraf ◽  
Charles P.-A. Bourque ◽  
David A. MacLean ◽  
Thom Erdle ◽  
Fan-Rui Meng
Keyword(s):  
Climate Change ◽  
Nova Scotia ◽  
Model Prediction ◽  
Prediction Accuracy ◽  
Basal Area ◽  
Forest Growth ◽  
Growth And Yield ◽  
Individual Tree ◽  
Forest Conditions ◽  
Forest Growth And Yield

Empirical growth and yield models developed from historical data are commonly used in developing long-term strategic forest management plans. Use of these models rests on an assumption that there will be no future change in the tree growing environment. However, major impacts on forest growing conditions are expected to occur with climate change. As a result, there is a pressing need for tools capable of incorporating outcomes of climate change in their predictions of forest growth and yield. Process-based models have this capability and may, therefore, help to satisfy this requirement. In this paper, we evaluate the suitability of an ecological, individual-tree-based model (JABOWA-3) in generating forest growth and yield projections for diverse forest conditions across Nova Scotia, Canada. Model prediction accuracy was analyzed statistically by comparing modelled with observed basal area and merchantable volume changes for 35 permanent sample plots (PSPs) measured over periods of at least 25 years. Generally, modelled basal area and merchantable volume agreed fairly well with observed data, yielding coefficients of determination (r2) of 0.97 and 0.94 and model efficiencies (ME) of 0.96 and 0.93, respectively. A Chi-square test was performed to assess model accuracy with respect to changes in species composition. We found that 83% of species-growth trajectories based on measured basal area were adequately modelled with JABOWA-3 (P > 0.9). Model-prediction accuracy, however, was substantially reduced for those PSPs altered by some level of disturbance. In general, JABOWA-3 is much better at providing forest yield predictions, subject to the availability of suitable climatic and soil information.

scholarly journals Forest Growth and Yield Modeling

2011 ◽  
Author(s):  
Aaron R. Weiskittel ◽  
David W. Hann ◽  
John A. Kershaw ◽  
Jerome K. Vanclay
Keyword(s):  
Forest Growth ◽  
Growth And Yield ◽  
Yield Modeling ◽  
Growth And Yield Modeling ◽  
Forest Growth And Yield

Slash Pine Growth and Yield Responses to Sludge Applications

1986 ◽  
Vol 10 (3) ◽  
pp. 142-145
Author(s):  
H. Riekerk ◽  
M. C. Lutrick
Keyword(s):  
Pinus Elliottii ◽  
Forest Growth ◽  
Slash Pine ◽  
Metal Mobility ◽  
Growth And Yield ◽  
Seedling Mortality ◽  
Tree Establishment ◽  
Sludge Treatment ◽  
Yield Improvement ◽  
Forest Growth And Yield

Abstract Sewage sludge was applied to forestland to test the effect of waste utilization on forest growth and yield improvement. Growth and yield improvement were associated with increased acidity and extractable phosphorus (P) in the surface sail. Heavy metal mobility was minimal. Slash pine (Pinus elliottii Engelm.) volume growth and yield improvement were significant at 0.035 ft3/yr and 8.0 ft3/ac/yr, respectively, for each 10 tons/ac of dry weight sludge. Sludge application after tree establishment improved growth by 0.054 ft3/yr and yield by 28.9 ft3/ac/yr. This was a two- to three-fold increase over sludge treatment before tree establishment. Differences were attributed to increased weed competition, disease, and seedling mortality in the pines planted after sludge treatment. Lower sludge rates frequently applied to established stand would be the best procedure for forest growth and yield improvement with a minimum of site problems. South. J. Appl. For. 10:142-45, Aug. 1986.

scholarly journals Combining Multi-Date Airborne Laser Scanning and Digital Aerial Photogrammetric Data for Forest Growth and Yield Modelling

2018 ◽  
Vol 10 (3) ◽  
pp. 347 ◽  
Author(s):  
Piotr Tompalski ◽  
Nicholas Coops ◽  
Peter Marshall ◽  
Joanne White ◽  
Michael Wulder ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Forest Growth ◽  
Airborne Laser Scanning ◽  
Growth And Yield ◽  
Airborne Laser ◽  
Forest Growth And Yield
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