A site-index model remodified

1994 ◽  
Vol 24 (1) ◽  
pp. 197-198 ◽  
Author(s):  
Bijan Payandeh ◽  
Yonghe Wang
Keyword(s):  
White Spruce ◽  
Site Index ◽  
Parameter Estimates ◽  
Data Sets ◽  
Index Model ◽  
Site Index Model ◽  
A Site

A previously reported site index model with unconstrained parameter estimates may not be amenable to extrapolation. A modification is presented that is more robust and has no apparent shortcomings. Results of fitting both models to white spruce (Piceaglauca (Moench) Voss) and aspen (Populustremuloides Michx.) data sets are presented and discussed.

Developing a site index model for P. Pinaster stands in NW Spain by combining bi-temporal ALS data and environmental data

2021 ◽  
Vol 481 ◽  
pp. 118690
Author(s):  
Juan Guerra-Hernández ◽  
Stefano Arellano-Pérez ◽  
Eduardo González-Ferreiro ◽  
Adrián Pascual ◽  
Vicente Sandoval Altelarrea ◽  
...  
Keyword(s):  
Site Index ◽  
Environmental Data ◽  
Nw Spain ◽  
Index Model ◽  
Site Index Model ◽  
A Site

Developing a site index model considering soil characteristics for Pinus thunbergii stands grown on the west coast of Korea

2013 ◽  
Vol 56 (2) ◽  
pp. 173-180 ◽  
Author(s):  
Hyun Kim ◽  
Seong-Hun Jeong ◽  
Dong-Gyu Kam ◽  
Hyun-Jun Kim ◽  
Soo-Min Choi ◽  
...  
Keyword(s):  
West Coast ◽  
Site Index ◽  
Soil Characteristics ◽  
Pinus Thunbergii ◽  
The West ◽  
Index Model ◽  
Site Index Model ◽  
A Site ◽  
West Coast Of Korea

scholarly journals Modeling Dominant Height Growth in PlantedPinus pineaStands in Northwest of Tunisia

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Sghaier Tahar ◽  
Palahi Marc ◽  
Garchi Salah ◽  
Bonet José Antonio ◽  
Ammari Youssef ◽  
...  
Keyword(s):  
Site Index ◽  
Height Growth ◽  
Pinus Pinea ◽  
Parameter Estimates ◽  
Site Classification ◽  
North West ◽  
Index Model ◽  
Variable Approach ◽  
Algebraic Difference ◽  
Site Index Model

Six generalized algebraic difference equations (GADAs) derived from the base models of log-logistic, Bertalanffy-Richards, and Lundqvist-Korf were used to develop site index model forPinus pineaplantations in north-west of Tunisia. To assure the base-age invariance of the model parameter estimates, a dummy variable approach was used. Data from stem analysis, corrected with Carmean's method, were used for modelling. To take into account the inherent autocorrelation of the longitudinal data, a second-order continuous-time autoregressive error structure was used, which allows the models to be applied to irregularly spaced, unbalanced data. Both a qualitative analysis based on the biological realism of the models and numerical and graphical analyses based on the accuracy of the models as well were used to evaluate the performance of candidate models. The relative error in site index predictions was used to select 30 years as the best reference age. Based on the analysis, a generalized algebraic difference equation (GADA) derived from the base model of Lundqvist-Korf realized the best compromise between biological and statistical constraints, producing the most adequate site index curves. It is a polymorphic model with site-dependent asymptotes. This model is therefore recommended for height growth prediction and site classification ofPinus pineaplantations in north-west of Tunisia.

scholarly journals Adaptation to climate change: Genetic variation is both a short- and a long-term solution

2005 ◽  
Vol 81 (5) ◽  
pp. 704-709 ◽  
Author(s):  
Jean Beaulieu ◽  
André Rainville
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
White Spruce ◽  
Site Index ◽  
Seed Source ◽  
Transfer Model ◽  
Index Model ◽  
Seed Sources ◽  
Site Index Model ◽  
Plantation Yield

We propose a methodology combining a biophysical site index model and a seed source transfer model based on both temperature and precipitation to estimate white spruce plantation yield under present and future global warming conditions. The biophysical site index model predicts dominant height at 25 years, which is further used to estimate plantation yield using yield tables. The transfer model shows that, on average, seed sources are best adapted to the temperature conditions where they presently grow, and give maximum yield under these conditions. However, this model also shows that transfer of seed sources to drier sites could improve plantation yield. To predict site index values under climate change conditions, values obtained from the biophysical site index model are corrected by a factor estimated using the seed source transfer model. Our simulation results predict that global warming should favour a slight increase in white spruce plantation yield in southern Québec. However, one cannot expect to obtain similar yields from a seed source rapidly exposed to warmer conditions compared with a seed source that is presently growing under climatic conditions to which it has become adapted. It would take several generations (adaptation lag) for a seed source to adapt to warmer conditions. We believe that the method we propose will be helpful in identifying the most productive seed source to be used at any given location in the province, and in revising seed source transfer rules. Key words: climate change, white spruce, provenance test, transfer model, site index, adaptation, plantation, GIS

A site‐index model for pure and mixed stands ofBetula pendulaandBetula pubescensin Sweden

1997 ◽  
Vol 12 (2) ◽  
pp. 149-156 ◽  
Author(s):  
Harry Eriksson ◽  
Ulf Johansson ◽  
Andres Kiviste
Keyword(s):  
Site Index ◽  
Mixed Stands ◽  
Index Model ◽  
Site Index Model ◽  
A Site

scholarly journals Evaluating a dimensionally compatible height growth modelling approach

1996 ◽  
Vol 72 (6) ◽  
pp. 647-650 ◽  
Author(s):  
Yonghe Wang ◽  
Bijan Payandeh
Keyword(s):  
Regression Models ◽  
Analysis Data ◽  
Site Index ◽  
Height Growth ◽  
Data Sets ◽  
Nonlinear Regression Models ◽  
Index Model ◽  
Site Index Model ◽  
Better Than ◽  
Modelling Approach

McDill and Amateis (1992) developed a dimensionally compatible height growth model which may be applied as either a base-age specific or a base-age invariant site index model. Its relative performance was compared with four published site index models on three stem analysis data sets from Ontario and the Northwest Territories of Canada. Results indicated that the modified McDill and Amateis (1992) model performed as well as, if not better than, the other models. Key words: base-age specific and base-age invariant site index models, nonlinear regression models, sum of squared errors

scholarly journals A Site Index Model for Lodgepole Pine in British Columbia

2014 ◽  
Vol 60 (5) ◽  
pp. 982-987 ◽  
Author(s):  
Adrian Batho ◽  
Oscar García
Keyword(s):  
British Columbia ◽  
Lodgepole Pine ◽  
Site Index ◽  
Index Model ◽  
Site Index Model ◽  
A Site

A site index model for lodgepole pine (Pinus contorta Dougl. var. latifolia) in northern Sweden

2016 ◽  
Vol 31 (6) ◽  
pp. 583-591 ◽  
Author(s):  
Mateusz Liziniewicz ◽  
Urban Nilsson ◽  
Eric Agestam ◽  
Per Magnus Ekö ◽  
Björn Elfving
Keyword(s):  
Pinus Contorta ◽  
Lodgepole Pine ◽  
Site Index ◽  
Northern Sweden ◽  
Index Model ◽  
Site Index Model ◽  
A Site

scholarly journals SITE QUALITY ESTIMATIONS BASED ON THE GENERALIZED ALGEBRAIC DIFFERENCE APPROACH: A CASE STUDY IN ÇANKIRI FORESTS

2018 ◽  
Vol 42 (3) ◽  
Author(s):  
Ugur Akbas ◽  
Muammer SENYURT
Keyword(s):  
Site Index ◽  
Site Quality ◽  
Model Parameters ◽  
Successful Model ◽  
Index Model ◽  
Prediction Technique ◽  
Algebraic Difference ◽  
Pine Stands ◽  
Site Index Model ◽  
Generalized Algebraic Difference Approach

ABSTRACT In this study, it is aimed that the dynamic site index models were developed for Crimean Pine stands in Sarikaya-Cankiri forests located in middle northern Turkey. The data for this study are 153 sample trees obtained from the Crimean Pine stands. In modeling relationships between height and age of dominant or co-dominant trees, some dynamic site index equations such as Chapman-Richards (M1, M2, M3), Lundqvist (M4 and M6), Hossfeld (M5), Weibull (M7) and Schumacher (M8) based on the Generalized Algebraic Difference Approach (GADA) were used. The estimations for these eight-dynamic site index model parameters with well as various statistical values were obtained using the nonlinear regression technique. Among these equations, the Chapman-Richards’s equation, M3, was determined to be the most successful model, with accounted for 89.03 % of the total variance in height-age relationships with MSE: 1.7633, RMSE: 1.3279, SSE: 1165.6, Bias: -0.0380. After determination of the best predictive model, ARMA (1, 1) autoregressive prediction technique was used to account autocorrelation problems for time-series height measurements. When ARMA autoregressive prediction technique was applied to the Chapman-Richards function for solving autocorrelation problem, these success statistics were improved as SSE: 868.7, MSE: 1.3183, RMSE: 1.1482, Bias: -0.06369, R2: 0.918. Also, Durbin-Watson statistics displayed that autocorrelation problem was solved by the use of ARMA autoregressive prediction technique; DW test value=1.99, DW<P=0.5622, DW>P=0.4378. The dynamic site index model that was developed has provided results compatible with the growth characteristics expected in the modeling of height-age relations, such as polymorphism, multiple asymptote, and base-age invariance.

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