A Dynamic System of Growth and Yield Equations for Pinus patula

Santiago-García, Wenceslao; Pérez-López, Eloísa; Quiñonez-Barraza, Gerónimo; Rodríguez-Ortiz, Gerardo; Santiago-García, Elías; Ruíz-Aquino, Faustino; Tamarit-Urias, Juan Carlos

doi:10.3390/f8120465

Cited by 20 publications

(12 citation statements)

References 7 publications

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“…This fact was verified in the present study. The choice of this model is in agreement with that obtained by Cecília et al (2014), Santana et al (2017), Freitas and Andrade (2017) and Santiago-García et al (2017)…”

Section: Adjustment and Selection Of Mathematical Models For Estimatisupporting

confidence: 90%

Use of aerial image in the estimation of volume and biomass of Eucalyptus sp. forest stand

et al. 2020

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Assessing forest stands is crucial for managing and planning the use of these resources. Forest inventory is the instrument that provides information about the stand situation, which can be costly and time consuming. In order to facilitate and reduce the time spent obtaining these data, the main objective of this work was to evaluate the accuracy of volume and biomass estimates per unit area with data from remote sensing. Forty sample units were allocated and georeferenced, in which all trees with diameter at breast height (DBH) ≥ 5 cm were inventoried. Sequentially, the cubage was performed in order to obtain individual biomass, volume, and adjustment of the individual models. With data from georeferenced images of the study area, the vegetation indices MSAVI (Modified Soil-Adjusted Vegetation Index) and NDVI (Normalized Difference Vegetation Index) were obtained. The volume and biomass estimation using remote sensing variables were carried out through the adjustment of sigmoidal models by regression analysis, which used a combination of the average values of the vegetation indices and the basal area of the plot/hectares as an independent variable. The fit statistics and the accuracy of the tested models presented consistent results to estimate forest production. The results showwd that indices derived from remote sensing techniques associated with forest variables information could accurately estimate the volume and biomass of Eucalyptus spp. plantations.

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Section: Adjustment and Selection Of Mathematical Models For Estimatisupporting

confidence: 90%

Use of aerial image in the estimation of volume and biomass of Eucalyptus sp. forest stand

et al. 2020

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“…The predominant vegetation type in the study area corresponds to pine-oak forest (STF. 2015;Santiago-Garc ıa et al 2017)…”

Section: Study Area and Species Selectionmentioning

confidence: 99%

“…The allometric relationship between total height and the diameter at breast height (TH/D) of trees is important for the forester since it provides information to predict the total tree volume or the merchantable volume accurately, by means of tree volume tables or percentage volume (Soares and Tom e 2002;Trincado and Leal 2006). In growth and yield projection systems, models that allow estimating the TH-D ratio over the projection period are required (Sharma and Parton 2007;Santiago-Garc ıa et al 2017) for the programing of silvicultural treatments and the quantitative estimation of volume production according to industrial uses (Castedo-Dorado et al 2005). Also, for the biomass estimation in even-aged stands, and is usual to include the dominant height and age to estimate the stand productivity using the site index (Lappi 1997;Ju arez-de Gal ındez et al 2007).…”

Section: Introductionmentioning

confidence: 99%

Generalized height-diameter models for five pine species at Southern Mexico

Santiago-García

Jacinto-Salinas

Rodríguez-Ortiz

et al. 2020

Forest Science and Technology

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Generalized height-diameter at breast height (D) models are essential for the estimation of the timber stocks of a forest stand, as well as in the generation of base information to develop forest growth models, and as basic inputs in the development of forest management plans. Generalized models were developed to estimate total height (TH) based on the D and stand variables, of five Pinus species in forests under forest management of Ixtl an de Ju arez, Oaxaca, Mexico. The data used come from a timber forest inventory, where n ¼ 1041 sampling plots of 1000 m 2 each were established based on a stratified-systematic sampling design. The species selected according to their relative abundance were: Pinus patula, Pinus oaxacana, Pinus ayacahuite, Pinus teocote and Pinus leiophylla. Five nonlinear equations were fitted using regression techniques to predict the TH of the trees under several silviculture regimes and forest management conditions. The statistical criteria of goodness of fit used were: adjusted coefficient of determination (R 2 adj ), root mean square error (RMSE) and absolute average bias in the prediction ( E). Likewise, the graphic analysis of the predictive capacity of the equations was considered. The D and the stand variables (quadratic mean diameter, dominant diameter and dominant height) for these species explained between 75 and 83% of the variability of the TH data. The predicting variables to apply the developed generalized models to estimate tree's total height require less sampling effort and are derived from conventional forest inventory data, which allows to reduce costs and time in field work.

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“…This is because the conditions of the stands, such as age, SI and Nha, are very diverse in each space. Santiago-García et al [54] developed a stand-level model by using 66 plots of data from a permanent plot within the period of 2015 and 2016 and identified the forest productivity status in Juárez, Oaxaca, and in Mexico, based on the changes in DBH. Ji et al [9] used surveyed data from 405 plots within the period of 2014 and 2015 to develop a stand forest growth model that did not consider climatic factors and the SI and identified forest carbon stocks in the city of Lishui in China.…”

Section: Integrated Dbh Estimation Model With Stand and Climate Variamentioning

confidence: 99%

Development of an Integrated DBH Estimation Model Based on Stand and Climatic Conditions

Piao

Kim

Choi

et al. 2018

Forests

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Using Korean National Forest Inventory (NFI) data, our study developed a model to estimate stand mean diameter at breast height (DBH) reflecting the influence of site and climate factors on forest growth for the major tree species in South Korea. A DBH estimation model was developed using stand-level variables (stand age, site index and number of trees per hectare) as independent factors. The spatial autocorrelation of residuals of the model was identified using semi-variogram analysis for each tree species. Further, a residual model, in which residuals were estimated by climatic factors (mean temperature, sum temperature in the growing season and precipitation), was developed assuming that the spatial autocorrelation of residuals reflects the differences in regional climatic conditions. Linear regression analysis showed that residuals of all tree species were significantly correlated with temperature and precipitation. The DBH and residual models were integrated to estimate the current DBH under different climatic factors (temperature and precipitation) and stand-level variables. This model had high reliability (R 2 = 0.74-0.79), and no obvious dependencies or patterns in residuals were noted. Our results indicated that temperature increases caused by climate change would negatively affect the DBH estimate of coniferous trees, but not of oak species.

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A Dynamic System of Growth and Yield Equations for Pinus patula

Cited by 20 publications

References 7 publications

Use of aerial image in the estimation of volume and biomass of Eucalyptus sp. forest stand

Use of aerial image in the estimation of volume and biomass of Eucalyptus sp. forest stand

Generalized height-diameter models for five pine species at Southern Mexico

Development of an Integrated DBH Estimation Model Based on Stand and Climatic Conditions

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