Assessing the impacts of species composition, top height and density on individual tree height prediction of quaking aspen in boreal mixedwoods

Huang, Shongming; Wiens, Douglas P.; Yang, Yuqing; Meng, Shawn X.; VanderSchaaf, Curtis L.

doi:10.1016/j.foreco.2009.06.017

Cited by 32 publications

(33 citation statements)

References 27 publications

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“…Here, we show that for mixed stands, the explicit evaluation of mixing proportion based on species-specific growing space requirements could be advantageous for modeling the more complex effects of the vertical structure of mixed species stands compared to pure stands. Different species almost certainly differ in their influence on competition for light in a forest canopy given their variation in potential crown dimensions, branching structure, leaf area density, and light capture [17,55,56]. Although other tree and stand variables such as stand age or spatially explicit competition indices may also help fine-tune h-d relationships [39], these were not considered because they require a substantial increase in the cost of forest inventory, which restricts the practical application of the developed predictive functions.…”

Section: Influence On Species-mixing In Tree Allometrymentioning

confidence: 99%

Species Mixing Effects on Height–Diameter and Basal Area Increment Models for Scots Pine and Maritime Pine

Riofrío

Rı́o

Maguire

et al. 2019

Forests

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Models that incorporate known species-mixing effects on tree growth are essential tools to properly design silvicultural guidelines for mixed-species stands. Here, we developed generalized height–diameter (h-d) and basal area growth models for mixed stands of two main forest species in Spain: Scots pine (Pinus sylvestris L.) and Maritime pine (Pinus pinaster Ait.). Mixed-effects models were fitted from plot measurement and tree rings data from 726 Scots pine and 693 Maritime pine trees from mixed and pure stands in the Northern Iberian Range in Spain, with the primary objective of representing interactions between the species where they are interspersed in mixtures of varying proportions. An independent dataset was used to test the performance of the h-d models against models previously fitted for monospecific stands of both species. Basal area increment models were evaluated using a 10-fold block cross-validation procedure. We found that species mixing had contrasting effects on the species in both models. In h-d models, the species-mixing proportion determined the effect of species interactions. Basal area growth models showed that interspecific competition was influential only for Maritime pine; however, these effects differed depending on the mode of competition. For Scots pine, tree growth was not restricted by interspecies competition. The combination of mixed-effect models and the inclusion of parameters expressing species-mixing enhanced estimates of tree height and basal area growth compared with the available models previously developed for pure stands. Although the species-mixing effects were successfully represented in the fitted models, additional model components for accurately simulating the stand dynamics of mixtures with Scots pine and Maritime pine and other species mixtures require similar model refinements. Upon the completion of analyses required for these model refinements, the degree of improvement in simulating growth in species mixtures, including the effects of different management options, can be evaluated.

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Section: Influence On Species-mixing In Tree Allometrymentioning

confidence: 99%

Species Mixing Effects on Height–Diameter and Basal Area Increment Models for Scots Pine and Maritime Pine

Riofrío

Rı́o

Maguire

et al. 2019

Forests

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“…Forests 2020, 11, 183 2 of 15In the study of forest ecology and forest management, the height-diameter (H-D) relationship is one of the most important elements in estimating the stand volume and biomass, and is used as a reliable indicator of forest growth and sustainable forest management [4][5][6]. The precise estimation of the H-D relationship is essential for giving a clear description of the stand conditions and its changes over time, and can further be employed in the estimation of stand growth and yield projection [7,8]. For example, Parresol [9] described the relationship between the height and diameter of a stem as important components in yield estimation, stand description and damage appraisal.…”

mentioning

confidence: 99%

Predicting Tree Height-Diameter Relationship from Relative Competition Levels Using Quantile Regression Models for Chinese Fir (Cunninghamia lanceolata) in Fujian Province, China

Zhang

Chen

Zhou

et al. 2020

Forests

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The importance of the height-diameter (H-D) relationship in forest productivity is well known. The general nonlinear regression model, based on the mean regression technical, is not able to give a complete description of the H-D relationship. This study aims to evaluate the H-D relationship among relative competition levels and develop a quantile regression (QR) model to fully describe the H-D relationship. The dominance index was applied to determine the relative competition levels of trees for the Chinese fir. Based on the basic Weibull growth model, the mean regression for five relative competition levels and 11 QR models was constructed with 10-fold cross-validation. We have demonstrated that the H-D relationship for the Chinese fir strongly correlated with relative competition states, but the five curves from mean regression models did not show a notable difference between the trends of H-D relationship under different competition levels. Similar regression results were found in QR models of the specific quantiles; the average tree height of five competition levels varied between 5.78% and 17.65% (i.e., about 0.06 and 0.18 quantiles). In addition, some special curves of the H-D relationship such as the QR models of the 0.01 and 0.99 quantile showed the H-D relationship under certain conditions. These findings indicate that the QR models not only evaluated the rates of change of the H-D relationships in various competition levels, but also described their characteristics with more information, like the upper and lower boundary of the conditional distribution of responses. Although the flexible QR curves followed the distribution of the data and showed more information about the H-D relationships, the H-D curves may not intersect with each other, even when the trees reached their maximum height. Hence, the QR model requires further practice in assessing the growth trajectory of the tree’s diameter or tree height to gain better results.

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“…As for stand density, various measures were examined and it was found that using the number of black spruce trees per hectare produced better fits of the model; therefore this variable was included as a predictor in the model. Regarding the site quality (SQ), top height was used as an indicator of SQ in this study, considering that both the site index and dominant/codominant height, two common measures of SQ, have some disadvantages comparing to the top height for measuring SQ (Huang et al 2009c). Top height can serve as a good surrogate for SQ when age is in the equation, as shown in some other studies (e.g., Sharma and Parton 2007).…”

Section: Mixed-effects Modelmentioning

confidence: 99%

Accounting for serial correlation and its impact on forecasting ability of a fixed- and mixed-effects basal area model: a case study

et al. 2011

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Successfully accounting for serial correlations has always been a vital part of growth and yield modeling when using repeated measurement data. In this case study, 16 alternative functions addressing the serial correlations of errors from a basal area model of black spruce (Picea mariana (Mill.) B.S.P.) were examined and compared. Results from this study showed that functions incorporated into the fixed and mixed models to account for the serial correlations improved model fit. The serial correlation of the residuals from the fixed model with directly modeled error structure was significantly lower than that from the fixed model without a modeled error structure. For the mixed model, modeling error structure resulted in only a moderate reduction in serial correlation of residuals. The comparison of the fixed and mixed models with and without directly modeling the error structure showed that for fixed model, a substantial improvement in forecasting ability was achieved when the error structure was directly modeled to account for serial correlation, and when the forecasts were adjusted based on the estimated correlation. But for the mixed model, further modeling of the error structure to account for more serial correlation resulted in worsened or comparative forecasting ability of the fitted model.

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Assessing the impacts of species composition, top height and density on individual tree height prediction of quaking aspen in boreal mixedwoods

Cited by 32 publications

References 27 publications

Species Mixing Effects on Height–Diameter and Basal Area Increment Models for Scots Pine and Maritime Pine

Species Mixing Effects on Height–Diameter and Basal Area Increment Models for Scots Pine and Maritime Pine

Predicting Tree Height-Diameter Relationship from Relative Competition Levels Using Quantile Regression Models for Chinese Fir (Cunninghamia lanceolata) in Fujian Province, China

Accounting for serial correlation and its impact on forecasting ability of a fixed- and mixed-effects basal area model: a case study

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