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Modelling of Forests Structure and Biomass Distribution

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A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Forest Inventory, Modeling and Remote Sensing".

Deadline for manuscript submissions: closed (1 September 2021) | Viewed by 28527

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Prof. Dr. Rafał Podlaski

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Division of Environmental Biology, Institute of Biology, Jan Kochanowski University, ul. Świętokrzyska 15, 25-406 Kielce, Poland
Interests: finite mixture models; forest dynamics; disturbances; forest structural heterogeneity; structural types; tree rings

Special Issue Information

Dear Colleagues,

Forest structure, defined as the diversity of structural elements in the forest, provides a scientific basis for determining the evaluation of forest resources and scheduling for future silviculture treatment. Usually, a diameter at breast height (DBH) distribution model is used to provide information on the frequency distribution of DBH, a height–diameter model is employed to estimate the average height per diameter class, and then biomass distribution can be computed. Currently available large datasets give the opportunity to complement traditional approaches in forest structure modelling with multidimensional models. The best way to model forest structure and biomass distribution is to take the complex 3D space into account. This Special Issue will provide a cross-disciplinary platform for foresters, ecologists, modellers, and statisticians. forest patch and stand scale studies, and landscape models, are welcome.

Dr. Rafał Podlaski
Guest Editor

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Keywords

Tree size diversity
Biomass distribution
Complex forest structure
Forest modelling
Forest inventories
Large data modelling
Forest dynamics

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Research

14 pages, 3086 KiB

Open AccessArticle

Simulating Biomass Production and Water Use of Poplars in a Plantation Using a STELLA-Based Model

by Ying Ouyang, Satyanarayan Dev, Johnny M. Grace III, Devendra M. Amatya and Theodor D. Leininger

Forests 2022, 13(4), 547; https://doi.org/10.3390/f13040547 - 31 Mar 2022

Cited by 1 | Viewed by 2197

Abstract

Poplar trees (Populus spp.) are some of the fastest growing hardwoods used for biomass production. There are, however, conflicting observations about water use of poplars associated with the impact on local water resources. A STELLA (Structural Thinking and Experiential Learning Laboratory with Animation) model was modified to investigate the aboveground biomass production and water use in a mature (6 to 8 yrs. old) poplar plantation for a 3-year simulation period. The model predicted the typical annual pattern of soil evaporation, root water uptake, and leaf water transpiration in the poplar plantation increasing from winter to summer followed by respective decreases from summer to winter. Root water uptake and leaf water transpiration were proportional to the soil water content. More water was needed to produce the same amount of biomass during summer than during other seasons. Less water was consumed to produce the same amount of biomass as the age of the poplar trees increased. The net increase in biomass over the 3-year period was 0.69 × 10⁴ kg/ha, which was equivalent to a 65% increase in biomass. The average rate of daily water use to daily biomass production was 1.05 × 10⁹ cm³ water/kg biomass/ha. A good linear correlation between cumulative biomass production (CBP) and cumulative water use (CWU) was identified: Y_CBP = 0.001 ∗ X_CWU, R² = 0.99, p < 0.001. This simple correlation provides a very good reference to estimate poplar water use efficiency (i.e., ratio of water use to biomass production) in growing regions where water resources are a limiting factor. Full article

(This article belongs to the Special Issue Modelling of Forests Structure and Biomass Distribution)

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16 pages, 4273 KiB

Open AccessArticle

A Newly Built Model of an Additive Stem Taper System with Total Disaggregation Model Structure for Dahurian Larch in Northeast China

by Yanli Xu, Lichun Jiang and Muhammad Khurram Shahzad

Forests 2021, 12(10), 1302; https://doi.org/10.3390/f12101302 - 24 Sep 2021

Cited by 2 | Viewed by 1594

Abstract

Stem taper function is an important concept in forest growth and yield modeling, and forest management. However, the additivity of the function and the inherent correlations between stem components (diameter outside bark—dob, diameter inside bark—dib, and double-bark thickness—dbt) are seldom considered. In this paper, a total disaggregation model (TDM) structure was developed based on the well-known Kozak (2004) model to ensure the additivity of the stem components. The reconstructed model was fitted with the data of 1281 felled Dahurian larch trees from three regions of Daxing’anling Mountains in Northeast China. The results from TDM were compared with other additive model structures including adjustment in proportion (AP), non-additive taper models (NAM), and three logical structures of NSUR (AMO, SMI, SMB). The results showed that the difference was significant among the three regions. The performance of TDM was slightly better than those of other model structures. Therefore, TDM was considered as another optimal additive system to estimate stem, bark thickness, and volume predicting for Dahurian larch in Northeast China besides NSUR, a method widely used in calculating additive volume or biomass throughout the world. We believe this work is cutting-edge, and that this methodology can be applied to other tree species. Full article

(This article belongs to the Special Issue Modelling of Forests Structure and Biomass Distribution)

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21 pages, 10653 KiB

Open AccessArticle

Structural Characteristics of the Main Resinous Stands from Southern Carpathians, Romania

by Gabriel Murariu, Lucian Dinca, Nicu Tudose, Vlad Crisan, Lucian Georgescu, Dan Munteanu, Mihai Daniel Dragu, Bogdan Rosu and George Dănuţ Mocanu

Forests 2021, 12(8), 1029; https://doi.org/10.3390/f12081029 - 3 Aug 2021

Cited by 17 | Viewed by 2453

Abstract

The purpose of this study, which contains historical data recorded over a period of 40 years, was to identify the main factors that influence and control the level of wood mass production. The main reason was to optimize the management of forest areas and was driven by the necessity to identify factors that can influence most of the volume produced by coniferous forests located in southeast Europe. The data was collected between1980 and 2005 at the National Institute for Research and Development in Forestry, for forests located in the Southern Carpathians, Romania. The studied data refer to the parameters that model forest structure for spruce, fir, pine, and larch. These are the main resinous species found in the Southern Carpathians. The total area covered by these forests is 143,431 ha. At the forest species level, the analysis consists of 16,162 records (corresponding to the elements of the trees), covering an area of 45,008 ha for fir, 4711 ha for larch, 81,995 ha for spruce, and 11,717 ha for pine. The aim of this research has been to investigate and to assess the impact and magnitude of abiotic factors such as altitude and field aspect on forest structures from the main resinous stands located in the Southern Carpathians. Taking into account the size of the database as well as the duration for collecting data, a complete statistical and systematic approach was considered optimum. This resulted from our wish to emphasize and evaluate the influence of each analysed factor on the wood mass production level. The relationship between abiotic factors and forest structure has been analysed by using a systematic statistical approach in order to provide a useful theoretical reference for the improvement of forest management practices in the context of multiple climatic, environmental, and socio-economic challenges. These common characteristics have been found by applying ANOVA and multivariate statistical methods such as PCA and FA methods. A series of parameters were considered in this investigation, namely altitude (ALT), forest site type (TS), forest type (TP), consistency (CONS) etc. In order to obtain a complete image, we have also applied multivariate analysis methods that emphasize the effect size for each database parameter. At such a level of recorded data, the statistical approach ensures a factor level of p <0.001 while the accuracy in evaluating effect size is increased. As such, they influence the spreading and structure of the studied resinous stands to a higher degree, regardless of species. Full article

(This article belongs to the Special Issue Modelling of Forests Structure and Biomass Distribution)

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21 pages, 6243 KiB

Open AccessArticle

Low Cost Automatic Reconstruction of Tree Structure by AdQSM with Terrestrial Close-Range Photogrammetry

by Yanqi Dong, Guangpeng Fan, Zhiwu Zhou, Jincheng Liu, Yongguo Wang and Feixiang Chen

Forests 2021, 12(8), 1020; https://doi.org/10.3390/f12081020 - 31 Jul 2021

Cited by 16 | Viewed by 3281

Abstract

The quantitative structure model (QSM) contains the branch geometry and attributes of the tree. AdQSM is a new, accurate, and detailed tree QSM. In this paper, an automatic modeling method based on AdQSM is developed, and a low-cost technical scheme of tree structure modeling is provided, so that AdQSM can be freely used by more people. First, we used two digital cameras to collect two-dimensional (2D) photos of trees and generated three-dimensional (3D) point clouds of plot and segmented individual tree from the plot point clouds. Then a new QSM-AdQSM was used to construct tree model from point clouds of 44 trees. Finally, to verify the effectiveness of our method, the diameter at breast height (DBH), tree height, and trunk volume were derived from the reconstructed tree model. These parameters extracted from AdQSM were compared with the reference values from forest inventory. For the DBH, the relative bias (rBias), root mean square error (RMSE), and coefficient of variation of root mean square error (rRMSE) were 4.26%, 1.93 cm, and 6.60%. For the tree height, the rBias, RMSE, and rRMSE were—10.86%, 1.67 m, and 12.34%. The determination coefficient (R²) of DBH and tree height estimated by AdQSM and the reference value were 0.94 and 0.86. We used the trunk volume calculated by the allometric equation as a reference value to test the accuracy of AdQSM. The trunk volume was estimated based on AdQSM, and its bias was 0.07066 m³, rBias was 18.73%, RMSE was 0.12369 m³, rRMSE was 32.78%. To better evaluate the accuracy of QSM’s reconstruction of the trunk volume, we compared AdQSM and TreeQSM in the same dataset. The bias of the trunk volume estimated based on TreeQSM was −0.05071 m³, and the rBias was −13.44%, RMSE was 0.13267 m³, rRMSE was 35.16%. At 95% confidence interval level, the concordance correlation coefficient (CCC = 0.77) of the agreement between the estimated tree trunk volume of AdQSM and the reference value was greater than that of TreeQSM (CCC = 0.60). The significance of this research is as follows: (1) The automatic modeling method based on AdQSM is developed, which expands the application scope of AdQSM; (2) provide low-cost photogrammetric point cloud as the input data of AdQSM; (3) explore the potential of AdQSM to reconstruct forest terrestrial photogrammetric point clouds. Full article

(This article belongs to the Special Issue Modelling of Forests Structure and Biomass Distribution)

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12 pages, 2846 KiB

Open AccessArticle

Decline in Aboveground Biomass Due to Fragmentation in Subtropical Forests of China

by Chunyu Shen, Nannan Shi, Shenglei Fu, Wanhui Ye, Lei Ma and Dongsheng Guan

Forests 2021, 12(5), 617; https://doi.org/10.3390/f12050617 - 13 May 2021

Cited by 9 | Viewed by 2662

Abstract

Fragmentation has long been considered the primary cause for ecosystem degradation and biodiversity loss worldwide. Forest fragmentation affects ecosystem functioning and biodiversity in multiple ways. Here, we ask how forest fragmentation influences aboveground biomass storage (AGB) in sub-tropical forests in China. We established 207 20 m × 20 m plots within 69 forest fragments of varying size. Forest fragmentation process simulation was carried out via repeated quadrat sampling using different sized quadrats in two non-fragmented stands. AGB was estimated and compared across forest fragments and quadrats with different sizes within two non-fragmented stands. Our results indicate that AGB is significantly lower in forest fragments than in quadrats within two non-fragmented forests. In addition, species richness and abundance were lower in fragmented stands, respectively. In fragmented forests, the average diameter at breast height (DBH) increased with decreasing patch size, while declined for non-fragmented plots. Species richness, abundance, and mean DBH have strongly positive effects on AGB. This was the case both in forest fragments and quadrats within two non-fragmented forests. Forest fragmentation leads to lower richness, lower abundance, and higher mean DBH in forest fragments than in the two non-fragmented forests. Our results suggest that forest fragmentation increases edge habitats, which drastically decreases forests aboveground biomass storage. These results show that land degradation not only reduces the area of forests, but also reduces the aboveground biomass carbon density of forests. Full article

(This article belongs to the Special Issue Modelling of Forests Structure and Biomass Distribution)

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19 pages, 3460 KiB

Open AccessArticle

A Tree Ring Measurement Method Based on Error Correction in Digital Image of Stem Analysis Disk

by Wenjie Zhang, Tianzhong Zhao, Xiaohui Su, Baoguo Wu, Zhiqiang Min and Yingze Tian

Forests 2021, 12(4), 464; https://doi.org/10.3390/f12040464 - 10 Apr 2021

Cited by 4 | Viewed by 4010

Abstract

Stem analysis is an essential aspect in forestry investigation and forest management, as it is a primary method to study the growth law of trees. Stem analysis requires measuring the width and number of tree rings to ensure the accurate measurement, expand applicable tree species, and reduce operation cost. This study explores the use of Open Source Computer Vision Library (Open CV) to measure the ring radius of analytic wood disk digital images, and establish a regression equation of ring radius based on image geometric distortion correction. Here, a digital camera was used to photograph the stem disks’ tree rings to obtain digital images. The images were preprocessed with Open CV to measure the disk’s annual ring radius. The error correction model based on the least-square polynomial fitting method was established for digital image geometric distortion correction. Finally, a regression equation for tree ring radius based on the error correction model was established. Through the above steps, click the intersection point between the radius line and each ring to get the pixel distance from the ring to the pith, then the size of ring radius can be calculated by the regression equation of ring radius. The study’s method was used to measure the digital image of the Chinese fir stem disk and compare it with the actual value. The results showed that the maximum error of this method was 0.15 cm, the average error was 0.04 cm, and the average detection accuracy reached 99.34%, which met the requirements for measuring the tree ring radius by stem disk analysis. This method is simple, accurate, and suitable for coniferous and broad-leaved species, which allows researchers to analyze tree ring radius measurement, and is of great significance for analyzing the tree growth process. Full article

(This article belongs to the Special Issue Modelling of Forests Structure and Biomass Distribution)

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23 pages, 3469 KiB

Open AccessArticle

Changes in Community Composition of Tropical Evergreen Forests during Succession in Ta Dung National Park, Central Highlands of Vietnam

by Nguyen Hong Hai, Nguyen Thanh Tan, Tran Quang Bao, Any Mary Petritan, Trinh Hien Mai, Cao Thi Thu Hien, Pham The Anh, Vu Tien Hung and Ion Catalin Petritan

Forests 2020, 11(12), 1358; https://doi.org/10.3390/f11121358 - 18 Dec 2020

Cited by 5 | Viewed by 2952

Abstract

Degradation of tropical forests is a major driver of the global extinction crisis. A key question is understanding the role of evolution history during forest succession in the context of forest restoration for maintaining ecosystem function and stability. This study was conducted in a fragmented forest landscape in the central highlands of Vietnam. We sampled living trees with diameters at breast height of ≥6.0 cm in nineteen 0.25 ha plots to evaluate forest community structure changes over two early successional stages (<10 years and 10–20 years old) after abandonment and old-growth. We used both statistically metric and nonmetric analyses to examine correlations of community composition during successional stages and along elevational gradients. We found that (i) significant differences existed in the structural compositions between early successional forests and old-growth forests, but did not exist within early successional forests; (ii) the phylogenetic structure shifted from overdispersion to clustering with increasing successional ages; and (iii) above-ground biomass (AGB), representing ecosystem functioning, significantly increased from early-to-late successional stages, but did not correlate with phylogenetic diversity or elevation. Our results revealed that the forest community structure was strongly affected by degradation, particularly AGB and phylogenetic structure. These findings have clear implications for sustaining biodiversity persistence and ecosystem functioning in human-modified landscapes in the study region. Full article

(This article belongs to the Special Issue Modelling of Forests Structure and Biomass Distribution)

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16 pages, 1234 KiB

Open AccessArticle

Performance of Kernel Estimator and Johnson S_B Function for Modeling Diameter Distribution of Black Alder (Alnus glutinosa (L.) Gaertn.) Stands

by Piotr Pogoda, Wojciech Ochał and Stanisław Orzeł

Forests 2020, 11(6), 634; https://doi.org/10.3390/f11060634 - 3 Jun 2020

Cited by 10 | Viewed by 2050

Abstract

We compare the usefulness of nonparametric and parametric methods of diameter distribution modeling. The nonparametric method was represented by the new tool—kernel estimator of cumulative distribution function with bandwidths of 1 cm (KE1), 2 cm (KE2), and bandwidth obtained automatically (KEA). Johnson S_B (JSB) function was used for the parametric method. The data set consisted of 7867 measurements made at breast height in 360 sample plots established in 36 managed black alder (Alnus glutinosa (L.) Gaertn.) stands located in southeastern Poland. The model performance was assessed using leave-one-plot-out cross-validation and goodness-of-fit measures: mean error, root mean squared error, Kolmogorov–Smirnov, and Anderson–Darling statistics. The model based on KE1 revealed a good fit to diameters forming training sets. A poor fit was observed for KEA. Frequency of diameters forming test sets were properly fitted by KEA and poorly by KE1. KEA develops more general models that can be used for the approximation of independent data sets. Models based on KE1 adequately fit local irregularities in diameter frequency, which may be considered as an advantageous in some situations and as a drawback in other conditions due to the risk of model overfitting. The application of the JSB function to training sets resulted in the worst fit among the developed models. The performance of the parametric method used to test sets varied depending on the criterion used. Similar to KEA, the JSB function gives more general models that emphasize the rough shape of the approximated distribution. Site type and stand age do not affect the fit of nonparametric models. The JSB function show slightly better fit in older stands. The differences between the average values of Kolmogorov–Smirnov (KS), Anderson–Darling (AD), and root mean squared error (RMSE) statistics calculated for models developed with test sets were statistically nonsignificant, which indicates the similar usefulness of the investigated methods for modeling diameter distribution. Full article

(This article belongs to the Special Issue Modelling of Forests Structure and Biomass Distribution)

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18 pages, 4627 KiB

Open AccessArticle

Temporal Changes in Community Structure over a 5-Year Successional Stage in a Subtropical Forest

by Mingfeng Xu, Ting Liu, Peiyun Xie, Hongyu Chen and Zhiyao Su

Forests 2020, 11(4), 438; https://doi.org/10.3390/f11040438 - 13 Apr 2020

Cited by 1 | Viewed by 2771

Abstract

In the context of global warming, the changes of forest structure, diversity, and productivity along with forest succession have always been a topic of interest for many researchers. Studying the changes in community structure, biomass, and diversity of different diameter at breast height (DBH) classes in subtropical mountainous forests during forest succession can provide data in support of future forest succession predictions and forest management. We analyzed the changes of three DBH classes in a 10-ha plot while studying subtropical mountainous forest succession in 2012 and 2017. The results showed that during forest succession, the community abundance and richness significantly decreased while biomass increased slightly. Among the three DBH classes, changes were the greatest in small trees, followed by large trees, and then medium-sized trees. The abundance, biomass, richness, and Shannon–Wiener index of small trees all decreased significantly. In forests with medium-sized trees, biomass decreased significantly and abundance did not change significantly. In large trees, abundance and biomass increased significantly. Changes were observed in environmental driving factors during forest succession. In 2012, driving factors with significant effects included total phosphorus, transmitted direct solar radiation, organic matter, and capillary water capacity. In 2017, two driving factors were total phosphorus and total potassium while the main driving factor was still total phosphorus. The results showed that during forest succession the abundance and diversity of small trees were principal components of community abundance and diversity. A reduction in small-tree abundance and diversity will decrease community abundance and diversity. Large-tree biomass was a principal component of community biomass; accumulation of large-tree biomass will increase community biomass. Schima superba Gardner and Champ. and Castanopsis carlesii (Hemsl.) Hayata are the main dominant species in this area, which can quickly form stable communities. S. superba is also a fire-resistant tree species. Therefore, in natural forest management, planting of S. superba and C. carlesii in the secondary bare land can be considered. In addition, the evergreen broad-leaved forest can be recovered to the forest structure and productivity level before selective cutting, which provides important inspiration for forest management in the region. Full article

(This article belongs to the Special Issue Modelling of Forests Structure and Biomass Distribution)

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16 pages, 5745 KiB

Open AccessArticle

by Karol Bronisz and Lauri Mehtätalo

Forests 2020, 11(4), 381; https://doi.org/10.3390/f11040381 - 27 Mar 2020

Cited by 18 | Viewed by 3171

Abstract

Secondary succession that occurs on abandoned farmlands is an important source of biomass carbon stocks. Both direct and indirect tree biomass estimation methods are applied on forest lands. Using empirical data from 148 uprooted trees, we developed a seemingly unrelated mixed-effects models system for the young silver birch that grows on post agricultural lands in central Poland. Tree height, biomass of stem, branches, foliage, and roots are used as dependent variables; the diameter at breast height is used as the independent variable. During model elaboration we used restricted cubic spline: 5 knots at the quantiles (0.05, 0.275, 0.5, 0.725, and 0.95) of diameter at breast height provided sufficiently flexible curves for all biomass components. In this study, we demonstrate the use of the model system through cross-model calibration of the biomass component model using tree height measured from 0, 2, 3, and 4 available extreme trees feature in the plot in question. A different number of extreme trees were measured for final model system and our results indicated that for all analyzed components, random-effect predictions are characterized by higher accuracy than fixed-effects predictions. Full article

(This article belongs to the Special Issue Modelling of Forests Structure and Biomass Distribution)

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