Height-Diameter Relationships for Different Genetic Planting Stock of Loblolly Pine at Age 6

Egbäck, Samuel; Bullock, Bronson P.; Isik, Fikret; McKeand, Steven E.

doi:10.5849/forsci.14-015

Cited by 9 publications

(7 citation statements)

References 21 publications

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“…However, inclusion of H in the model would be of no value if D and H were perfectly correlated. Although D and H are always correlated to some degree, their relationship varies greatly (Feldpausch et al, 2010), being influenced by genotype, competition and environmental conditions (Egbäck et al, 2015;Hulshof et al, 2015;Dutcă et al, 2018b). As a result, including H in allometric models has been shown to improve biomass prediction accuracy (Chave et al, 2005(Chave et al, , 2014Feldpausch et al, 2012;Fayolle et al, 2013;Rutishauser et al, 2013;Dutcă et al, 2018a).…”

Section: Introductionmentioning

confidence: 99%

A practical measure for determining if diameter (D) and height (H) should be combined into D2H in allometric biomass models

Dutcă

McRoberts

Næsset

et al. 2019

Forestry: An International Journal of Forest Research

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Tree diameter at breast height (D) and tree height (H) are often used as predictors of individual tree biomass. Because D and H are correlated, the combined variable D2H is frequently used in regression models instead of two separate independent variables, to avoid collinearity related issues. The justification for D2H is that aboveground biomass is proportional to the volume of a cylinder of diameter, D, and height, H. However, the D2H predictor constrains the model to produce parameter estimates for D and H that have a fixed ratio, in this case, 2.0. In this paper we investigate the degree to which the D2H predictor reduces prediction accuracy relative to D and H separately and propose a practical measure, Q-ratio, to guide the decision as to whether D and H should or should not be combined into D2H. Using five training biomass datasets and two fitting approaches, weighted nonlinear regression and linear regression following logarithmic transformations, we showed that the D2H predictor becomes less efficient in predicting aboveground biomass as the Q-ratio deviates from 2.0. Because of the model constraint, the D2H-based model performed less well than the separate variable model by as much as 12 per cent with regard to mean absolute percentage residual and as much as 18 per cent with regard to sum of squares of log accuracy ratios. For the analysed datasets, we observed a wide variation in Q-ratios, ranging from 2.5 to 5.1, and a large decrease in efficiency for the combined variable model. Therefore, we recommend using the Q-ratio as a measure to guide the decision as to whether D and H may be combined further into D2H without the adverse effects of loss in biomass prediction accuracy.

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Section: Introductionmentioning

confidence: 99%

A practical measure for determining if diameter (D) and height (H) should be combined into D2H in allometric biomass models

Dutcă

McRoberts

Næsset

et al. 2019

Forestry: An International Journal of Forest Research

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“…Among the abovementioned factors, the role of the prestorm tree distribution in generating damage patterns has remained relatively underrepresented and unresolved in the literature (Gardiner et al 1997). In a physiological sense, and if all other factors are held constant (e.g., species identity, topographic position, soil condition, wind speed and direction, and time since last storm), a wide inter-tree spacing is generally believed to reduce the intensity of competition, thereby allowing individual trees to maintain active (diameter) growth (Pinkard and Neilsen 2003;Egbäck et al 2015). This will likely decrease their susceptibility to direct windstorm damage (Cremer et al 1982;Peltola and Kellomäki 1993;Oliver 1997;Valinger and Fridman 1997;Wonn and O'Hara 2001).…”

Section: Insights From Detailed Spatial Analysismentioning

confidence: 99%

Biotic and spatial factors potentially explain the susceptibility of forests to direct hurricane damage

2019

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Background: Ecologists continue to investigate the factors that potentially affect the pattern and magnitude of tree damage during catastrophic windstorms in forests. However, there still is a paucity of research on which trees are more vulnerable to direct damage by winds rather than being knocked down by the fall of another tree. We evaluated this question in a mixed hardwood-softwood forest within the Big Thicket National Preserve (BTNP) of southeast Texas, USA, which was substantially impacted by Hurricane Rita in September 2005. Results: We showed that multiple factors, including tree height, shade-tolerance, height-to-diameter ratio, and neighborhood density (i.e., pre-Rita stem distribution) significantly explained the susceptibility of trees to direct storm damage. We also found that no single factor had pervasive importance over the others and, instead, that all factors were tightly intertwined in a complex way, such that they often complemented each other, and that they contributed simultaneously to the overall susceptibility to and patterns of windstorm damage in the BTNP. Conclusions: Directly damaged trees greatly influence the forest by causing secondary damage to other trees. We propose that directly and indirectly damaged (or susceptible) trees should be considered separately when assessing or predicting the impact of windstorms on a forest ecosystem; to better predict the pathways of community structure reorganization and guide forest management and conservation practices. Forest managers are recommended to adopt a holistic view that considers and combines various components of the forest ecosystem when establishing strategies for mitigating the impact of catastrophic winds.

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“…Height-diameter (H-D) ratio is also used to improve prediction accuracy of allometric models [21,23,24]. As each forest site has particular environmental conditions, and because it is widely understood that H-D ratio is in part affected by environmental conditions [27][28][29], it follows that the inclusion of height (together with diameter) in allometric models may explain the site effect. However, wood density and height has been shown to make relatively little contribution to improving prediction of biomass at particular forest stands [30].…”

Section: Introductionmentioning

confidence: 99%

Site-effects on biomass allometric models for early growth plantations of Norway spruce (Picea abies (L.) Karst.)

Dutcă

Mather

Blujdea

et al. 2018

Biomass and Bioenergy

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Height-Diameter Relationships for Different Genetic Planting Stock of Loblolly Pine at Age 6

Cited by 9 publications

References 21 publications

A practical measure for determining if diameter (D) and height (H) should be combined into D2H in allometric biomass models

A practical measure for determining if diameter (D) and height (H) should be combined into D2H in allometric biomass models

Biotic and spatial factors potentially explain the susceptibility of forests to direct hurricane damage

Site-effects on biomass allometric models for early growth plantations of Norway spruce (Picea abies (L.) Karst.)

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