Trees, Journal Year: 2024, Volume and Issue: unknown
Published: Sept. 29, 2024
Language: Английский
Tropical Ecology, Journal Year: 2025, Volume and Issue: unknown
Published: May 2, 2025
Language: Английский
Citations
0
Forest Ecology and Management, Journal Year: 2023, Volume and Issue: 532, P. 120843 - 120843
Published: Feb. 6, 2023
Information on tree height is useful for volume estimation and site productivity assessment as such, remains one of the most important variables often measured in forest inventories. Measuring a sufficient number sample trees requires considerable sampling effort cost. In this study, we developed functions optimizing measurement Swedish long-term experiments (LTFEs). Two large datasets from LTFE databases: fitting data (from thinning, fertilisation mixed species experiments) validation (tree spacing collected over several decades were used. The comprise 133,788 68,440 observations, respectively, each covering range growth environmental conditions across Sweden. A multilevel nonlinear mixed-effects modelling approach was used to build generalised Scots pine, Norway spruce, birch (Silver Downy united), other conifers broadleaves, considering variations heights stand characteristics at plot-level revision-level. response calibration first carried out with all data, second, using six obtained different selection strategies (diameter extremes, largest diameters, smallest diameters). explained dataset (pseudo R2: 0.938 – 0.970; RMSE: 0.957 1.363 m) without any residual trends. showed that accounted 95 98 % variation dataset, RMSE ranging between 0.770 1.040 m, confirming functions' high accuracy. We recommend four based diameter extremes ideal threshold calibration. These suggested technique would reduce inventory cost measurements subsequent inventories LTFEs.
Language: Английский
Citations
6
Frontiers in Plant Science, Journal Year: 2023, Volume and Issue: 14
Published: July 27, 2023
Stand biomass models can be used as basic decision-making tools in forest management planning. The Moso bamboo (Phyllostachys pubescens) forest, a major system tropical and subtropical regions, represents substantial carbon sink, slowing down the rise of greenhouse gas concentrations earth's atmosphere. Bamboo stand are important for assessment contribution to terrestrial ecosystem. We constructed model using destructively sampled data from 45 sample plots that were located across Yixing state-owned farm Jiangsu Province, China. Among several variables predictors models, mean diameter at breast height (MDBH), (MH), canopy density (CD) contributed significantly model. To increase model's accuracy, we introduced effects block random effect into through mixed-effects modeling. described large part variation (R2 = 0.6987), higher than ordinary least squares regression 0.5748). Our results show an increased with increasing MH CD, confirming our biological logic. proposed may have implications; example, it combined other estimate biomass, sequestration, different growth stages.
Language: Английский
Citations
6
Frontiers in Plant Science, Journal Year: 2023, Volume and Issue: 14
Published: March 30, 2023
Height to crown base (HCB) is an important predictor variable for forest growth and yield models of great significance bamboo stem utilization. However, existing HCB built so far on the hierarchically structured data are arbor forests, not applied forests. Based fitting acquired from 38 temporary sample plots Phyllostachys edulis forests in Yixing, Jiangsu Province, we selected best model (logistic model) among six basic extended it by integrating variables, which involved evaluating impact 13 variables HCB. Block- plot-level random effects were introduced account nested structures through mixed-effects modeling. The results showed that height, diameter at breast total basal area all individuals with a larger than subject bamboo, canopy density contributed significantly more variation other did. Introducing two-level resulted significant improvement accuracy model. Different sampling strategies evaluated response calibration (model localization), optimal strategy was identified. prediction substantially improved, increase number samples calibration. our findings, recommend use four randomly per provide compromise between measurement cost, efficiency, accuracy.
Language: Английский
Citations
5
Trees, Journal Year: 2024, Volume and Issue: 38(4), P. 849 - 862
Published: June 18, 2024
Language: Английский
Citations
1
Frontiers in Plant Science, Journal Year: 2023, Volume and Issue: 14
Published: Feb. 16, 2023
Bamboo crown width (CW) is a reliable index for evaluating growth, yield, health and vitality of bamboo, light capture ability carbon fixation efficiency bamboo forests. Based on statistical results produced from fitting the eight basic growth functions using data 1374 Phyllostachys pubescens in Yixing, Jiangsu Province, China, this study identified most suitable function (logistic function) to construct two-level mixed effects (NLME) CW model with forest block sample plot-level included as random model. Four methods selecting bamboos per plot (largest medium-sized smallest randomly selected bamboos) sizes (1–8 plot) were evaluated calibrate our NLME Using diameter at breast height (DBH), base (HCB), arithmetic mean (MDBH), (H) predictor variables, best fit statistics (Max R 2 , min RMSE, TRE). This was further improved by introducing two levels. The showed positive correlation HCB DBH negative H. poles used estimate provided satisfactory compromise regarding measurement cost, efficiency, prediction accuracy. presented may guide effective management estimation
Language: Английский
Citations
2
Trees, Journal Year: 2024, Volume and Issue: unknown
Published: Sept. 29, 2024
Language: Английский
Citations
0