scholarly journals An approximate height growth and site index model for Quercus sideroxyla Bonpl. in mixed-species stands of Durango, Mexico

Author(s):  
Gerónimo Quiñonez-Barraza ◽  
◽  
Dehai Zhao ◽  
Héctor M. de los Santos-Posadas ◽  
José J. Corral-Rivas ◽  
...  
2017 ◽  
Vol 47 (11) ◽  
pp. 1441-1449 ◽  
Author(s):  
Mehmet Seki ◽  
Oytun Emre Sakici

Some dynamic site index models based on the generalized algebraic difference approach (GADA) were fitted for Crimean pine (Pinus nigra J.F. Arnold subsp. pallasiana (Lamb.) Holmboe) stands in Taşköprü, Turkey. Data were obtained from 132 dominant trees representing the wide range of site quality in the region. Nonlinear regression analysis and a second-order continuous-time autoregressive error structure were applied. After autoregressive modeling, the fitted models were evaluated both statistically and graphically. The best results were obtained with the dynamic site index model derived from the Bertalanffy–Richards base equation, accounting for about the 99% of the total variance in height–age relationships in dominant trees, with an Akaike information criterion (AIC) value of 119.55 and root mean square error (RMSE) of 0.5446. The selected base-age invariant dynamic site index curves provided the polymorphism with multiple asymptotes and other realistic height growth patterns.


2010 ◽  
Vol 40 (6) ◽  
pp. 1175-1183 ◽  
Author(s):  
Zhengjun Hu ◽  
Oscar García

Height growth was modelled for spruce-dominated, even-aged stands in the Sub-Boreal Spruce biogeoclimatic zone of British Columbia, Canada, using both stem analysis (SA) and permanent sample plot (PSP) data. The model is based on a stochastic differential equation (SDE) formulation of the Bertalanffy–Richards growth equation. The SDE approach accounts for serial correlation and heterogeneous variance and makes hypothesis testing possible. Statistically significant differences in height–age trends between SA and PSP data were found that may be attributed to bias caused by dominance changes in SA trees. Error structure in SA and PSPs was also significantly different. Combining both data sources in a way that respects these different error structures reduced bias and increased precision. Four parametrizations were tested; the best was a polymorphic version. The final model fit the data well with no appreciable bias over the full range of ages and site qualities. The currently used spruce site-index model was found to underestimate growth and overestimate site index in young stands. The new model can be recommended for height prediction and site-quality assessment in interior spruce.


2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Sghaier Tahar ◽  
Palahi Marc ◽  
Garchi Salah ◽  
Bonet José Antonio ◽  
Ammari Youssef ◽  
...  

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.


1996 ◽  
Vol 72 (6) ◽  
pp. 647-650 ◽  
Author(s):  
Yonghe Wang ◽  
Bijan Payandeh

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


1993 ◽  
Vol 23 (12) ◽  
pp. 2487-2489 ◽  
Author(s):  
Yonghe Wang ◽  
Bijan Payandeh

A numerical solution was derived for previously published site index equations for trembling aspen (Populustremuloides Michx.). Data from aspen stands in north central Ontario were used to verify the validity and accuracy of the numerical method. With the numerical solution, only the height-growth equation is employed to estimate (i) height from site index and age and (ii) site index from height and age. The numerical method simplified site index estimation and improved its accuracy for aspen stands in north central Ontario.


2018 ◽  
Vol 42 (3) ◽  
Author(s):  
Ugur Akbas ◽  
Muammer SENYURT

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.


2019 ◽  
Vol 53 (4) ◽  
pp. 13-18
Author(s):  
Joon Hyung Park ◽  
◽  
Kwang Soo Lee ◽  
Yeong Mo Sonk ◽  
Su Young Jung ◽  
...  

2002 ◽  
Vol 32 (11) ◽  
pp. 1916-1928 ◽  
Author(s):  
Kalle Eerikäinen ◽  
Danaza Mabvurira ◽  
Ladislaus Nshubemuki ◽  
Jussi Saramäki

The aim of the study was to develop a site index model for Pinus kesiya Royle ex Gordon plantations in southeastern Africa based on the relationship between the dominant height and stand age. Conversely, analysis of dominant height and age data showed that the growth patterns of plantations were different. In addition, the asymptotes and forms of standwise dominant height curves varied within plantations. In developing a common site index model, instead of using the more common approach of estimating separate dominant height–age models for different plantations or sites, a mean curve approach based on a linear random parameter model with fixed and random parameters was applied. The random parameter model of this study was calibrated by predicting random parameters for the plantation and stand effects, in accordance with the standard linear prediction theory. The analyses showed that the calibration of the dominant height model was an efficient method to obtain reliable dominant height predictions of a stand, particularly when several dominant height–age observations from different stands of a plantation and at least one measured dominant height and stand age of a target stand are available. This is the case in many forest inventories based on temporary samples, i.e., cross-sectional data. The new site index model is a useful tool for use in different mensurational applications, and its properties can efficiently be utilized for example in forest inventories of P. kesiya plantations in southeastern Africa.


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