A Novel Forest Dynamic Growth Visualization Method by Incorporating Spatial Structural Parameters Based on Convolutional Neural Network DOI Creative Commons
Linlong Wang, Huaiqing Zhang,

Kexin Lei

et al.

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Journal Year: 2023, Volume and Issue: 17, P. 3471 - 3488

Published: Dec. 13, 2023

Current visual methods of forest dynamic growth mostly focus on the plot or stand level, which cannot express morphological and structural characteristics individual trees, as well their statistical linkages, causes each tree in growing at same rate. Additionally, these models still have some space for improvement terms prediction accuracy multi-relational data mining. In our study, uneven-aged Chinese fir ( Cunninghamia lanceolata ) plantations were chosen study subject proposed a novel method visualization modeling by incorporating spatial structure parameters using convolutional neural network technique (FDGVM-CNN-SSP) to explore effect develop model introducing (CNN) model. The results show that, (1) Spatial C U certain contribution growth, can explained 21.5%, 15.2%, 9.3% variance DBH, H, CW models, respectively. (2) CNN outperformed machine learning algorithms SVR, MARS, Cubist, RF, XGBoost performance. (3) Based FDGVM-CNN-SSP, we simulated level from 2018-2022 found that DBH H' fitting performance measured predicted was highly consistent with R 2 RMSE 86.8%, 2.06cm 79.2%, 1.11m but CW's R2 72.2%, 0.65m caused crowding (C) inconsistency.

Language: Английский

Effects of age, neighborhood competition and drought on the productivity of Larix principis-rupprechtii (Mayr) forests DOI
Ran Wang,

Yang Zhang,

Xinyu Zhang

et al.

European Journal of Forest Research, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 5, 2025

Language: Английский

Citations

1
Optimizing variables selection of random forest to predict radial growth of Larix gmelinii var. principis-rupprechtii in temperate regions DOI
Liang Yu,

Jinglei Liao,

Xu Chen

et al.

Forest Ecology and Management, Journal Year: 2024, Volume and Issue: 569, P. 122159 - 122159

Published: July 29, 2024

Language: Английский

Citations

3
Soil Microbial Community, Soil Quality, and Productivity along a Chronosequence of Larix principis-rupprechtii Forests DOI Creative Commons
Jing Zhang, Qiang Liu, Dongzhi Wang

et al.

Plants, Journal Year: 2023, Volume and Issue: 12(16), P. 2913 - 2913

Published: Aug. 10, 2023

Elucidating the correlation between soil microbial communities and forest productivity is focus of research in field ecology. Nonetheless, relationship stand age, quality, microorganisms, their combined influence on still unclear. In this study, five development stages (14, 25, 31, 39, >80 years) larch (Larix principis-rupprechtii) forests were investigated Inner Mongolia Shanxi provinces China. We evaluated quality using Integrated Soil Quality Index (SQI) analyzed changes bacterial fungal high-throughput sequencing. Regression models also established to examine impacts diversity, SQI productivity. The findings revealed an ascending trend organic matter (SOM), total nitrogen (TN), phosphorus (TP), available potassium (AK), 14, 39-year-old stands. abundance oligotrophic bacteria Acidobacteria exhibited a gradual decline with increasing whereas copiotroph Proteobacteria displayed progressive increase. Stands older than 80 years higher both saprophytic fungus Ascomycota mycorrhizal Basidiomycota. Forest age had significant impact particularly terms impacting α β diversity. community structure was influenced by AK, SOM, TN, TP, pH. Conversely, regulated crucial factors including TK, Fungal diversity demonstrated positive basal area increment (BAI) larch. Furthermore, accounted for 23.6% variation BAI. summary, implied robust association composition, chemical properties throughout chronosequence forests. These collectively played role influencing forest.

Language: Английский

Citations

7
Stand spatial structure and productivity based on random structural unit in Larix principis‐rupprechtii forests DOI Creative Commons
Jing Zhang, Chong Liu,

Zhaoxuan Ge

et al.

Ecosphere, Journal Year: 2024, Volume and Issue: 15(4)

Published: April 1, 2024

Abstract Stand spatial structure plays a key role in forest management, and particular the random structural unit, comprising tree its neighbors, largely determines stability productivity. However, how of unit affects productivity remains unclear. The study focused on four larch types from Hebei Shanxi provinces, China: 35‐year‐old ( Larix principis‐rupprechtii ) plantations (35LP), 39‐year‐old mixed larch–birch Betula platyphylla forests (39LB), 58‐year‐old natural (58LN), 73‐year‐old larch–birch–spruce Picea asperata (73LBS). index (FSSI) was employed to comprehensively evaluate stand structure. Additionally, uniform angle used discern whether units were uniform, random, or clumped. A regression model elucidate effects species mingling, diameter dominance, crowding trees. Results showed that FSSI varied among types, ranking as 35LP < 58LN 39LB 73LBS. values distribution frequency percentages basal area increment (BAI) for trees above 0.5% 40% most respectively. dominance significant negative correlation with BAI trees, whereas mingling 73LBS displayed positive Thus, increasing size well units, can facilitate formation rational structure, thereby enhancing forests.

Language: Английский

Citations

2
Growth data of outlying plantations allows benchmarking the tolerance to climate extremes and drought stress in the European larch DOI Creative Commons
J. Julio Camarero, Antonio Gazol, Cristina Valeriano

et al.

Frontiers in Plant Science, Journal Year: 2024, Volume and Issue: 15

Published: May 31, 2024

Introduction Plantations located outside the species distribution area represent natural experiments to assess tree tolerance climate variability. Climate change amplifies warming-related drought stress but also leads more extremes. Methods We studied plantations of European larch (Larix decidua), a conifer native central and eastern Europe, in northern Spain. used climate, tree-ring data from four including wet (Valgañón, site V; Santurde, S), intermediate (Ribavellosa, R) dry (Santa Marina, M) sites. aimed benchmark by analysing relationships between radial growth increment (hereafter growth), (temperature, precipitation, radiation) index. Results Basal (BAI) was lowest driest M (5.2 cm2 yr-1; period 1988–2022), followed R (7.5 yr-1), with youngest oldest trees being planted (35 years) (150 BAI peaked wettest sites (V; 10.4 S, 10.8 yr-1). detected sharp reduction (30% regional mean) 2001 when springto-summer conditions were very dry. In V S sites, positively responded current March June-July radiation, negatively precipitation. site, high April precipitation enhanced growth. warm late prior winter spring improved growth, warm-sunny July dry-sunny August reduced it. Larch spring-summer considering short (1-6 months) long (9-24 time scales (site wet-intermediate (sites respectively. Discussion is vulnerable slow-growing plantations, extreme wet-cloudy events dry-hot fast-growing plantations.

Language: Английский

Citations

1
Development of Polymorphic Index Model for Assessing Subtropical Secondary Natural Oak Forest Site Quality Under Complex Site and Climate Variables DOI Open Access
Lang Huang, Guangyu Zhu, Guoqi Chen

et al.

Forests, Journal Year: 2024, Volume and Issue: 15(11), P. 1867 - 1867

Published: Oct. 24, 2024

Site and climate conditions are the key determinants controlling dominant height growth forest productivity, both independently interactively. Secondary natural oak forests a typical type in China, especially Hunan Province, but little is known about site index of this under complex variables subtropics. Based on survey data trees from 101 plots secondary obtained using spatial interpolation, we used random method, correlation analysis, analysis variance to determine main factors affecting proposed modeling method an based effect site–climate interaction type. Of variables, elevation affected stand most, followed by slope direction position. Winter precipitation summer mean maximum temperature had greatest impact height. To develop created 10 popular base models found low performance (R2 ranged 0.1731 0.2030). The optimal model was Mitscherlich form M3 = 0.1940) parameter significance tests. Since affect curve, were combined into types types, respectively, nonlinear mixed-effects approach simulate different their combinations as effects. Site–climate factor enhanced (M3.4) prediction accuracy 0.1940 0.8220) compared optimum model. After clustering 62 three, five, eight groups hierarchical clustering, with effects improved 0.8265) applicability. developed study could be assess regional evaluate productivity.

Language: Английский

Citations

0
Site Quality Evaluation Model of Chinese Fir Plantations for Machine Learning and Site Factors DOI Open Access

Weifang Gao,

Dong Chen,

Yuhao Gong

et al.

Sustainability, Journal Year: 2023, Volume and Issue: 15(21), P. 15587 - 15587

Published: Nov. 3, 2023

Site quality evaluation is an important foundation for decision-making and planning in forest management provides scientific decision support guidance the sustainable development of forests commercial plantations. index site form models were constructed subsequently compared utilizing fir (Cunninghamia lanceolata) plantations Nanping City, Fujian Province, China. This papers aim was to construct a classification model, conduct further analysis on effects different factors site, achieve assessment Chinese An algebraic difference approach used establish model Province. The suitability two using accuracy partial correlation, optimal chosen classifying stands. On this basis, established random algorithm, importance each factor determined through ranking terms their impact quality. Within study area, R2 results 0.581, values five based reference breast diameters, ranked from high low, 0.894, 0.886, 0.884, 0.880, 0.865. bias correlation coefficient between stand volume 0.71, 0.52. confirmed that better suited evaluating forest-based had with generalization 0.87. greatest altitude, canopy closure, slope gradient, whereas landform smallest form. These can provide natural southern China ensure long-term use resources.

Language: Английский

Citations

1
A Novel Forest Dynamic Growth Visualization Method by Incorporating Spatial Structural Parameters Based on Convolutional Neural Network DOI Creative Commons
Linlong Wang, Huaiqing Zhang,

Kexin Lei

et al.

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Journal Year: 2023, Volume and Issue: 17, P. 3471 - 3488

Published: Dec. 13, 2023

Current visual methods of forest dynamic growth mostly focus on the plot or stand level, which cannot express morphological and structural characteristics individual trees, as well their statistical linkages, causes each tree in growing at same rate. Additionally, these models still have some space for improvement terms prediction accuracy multi-relational data mining. In our study, uneven-aged Chinese fir ( Cunninghamia lanceolata ) plantations were chosen study subject proposed a novel method visualization modeling by incorporating spatial structure parameters using convolutional neural network technique (FDGVM-CNN-SSP) to explore effect develop model introducing (CNN) model. The results show that, (1) Spatial C U certain contribution growth, can explained 21.5%, 15.2%, 9.3% variance DBH, H, CW models, respectively. (2) CNN outperformed machine learning algorithms SVR, MARS, Cubist, RF, XGBoost performance. (3) Based FDGVM-CNN-SSP, we simulated level from 2018-2022 found that DBH H' fitting performance measured predicted was highly consistent with R 2 RMSE 86.8%, 2.06cm 79.2%, 1.11m but CW's R2 72.2%, 0.65m caused crowding (C) inconsistency.

Language: Английский

Citations

0