Main Tree Species Research Articles

A healthier water use strategy in primitive forests contributes to stronger water conservation capabilities compared with secondary forests

Water conservation is an important ecological function of forest ecosystems, plant water use strategy is a key factor in regulating forest ecosystem water balance. However, there are still insufficient studies on the water conservation capacity and water use strategies of different forest types, especially in climate-sensitive areas. In this study, we determined the stable isotope values (δD, δ18O and d-excess) of plant water, soil water and precipitation from two typical stand types (primary forest and secondary forest) on Changbai Mountain to reveal plant water use and evaluated the water conservation capacity. The results indicated that rainwater infiltrated into the soil combined with piston flow and preferential flow in the primary forest, and preferential flow was the only form of flow in the secondary forest. The main tree species in the primary forest formed a relatively stable water use niche. Among them, the water use pattern of Quercus mongolica Fisch. ex Ledeb (Qm.) was transformed between shallow and deep soil layers with strong ecological plasticity. The dominant species in secondary forest derived water from similar soil layers with intense interspecific competition. By comparing the water use patterns, the secondary forest conformed to the hypothesis of “two water worlds”, while the primary forest conformed to the hypothesis of one reservoir. The primary forest ecosystem had stronger water conservation capacity than secondary forest ecosystem due to the regulable water use strategies of plants and the stable water conservation capacity of the soil. These results will provide theoretical support and a reference for plan future forest management strategies in the climate-sensitive areas.

Cost-effectiveness of Natura 2000 forest contracts for biodiversity conservation

Natura 2000 contracts in the European Union aim to maintain or restore natural habitats to a favorable conservation status. This article aims to analyze the cost-effectiveness of Natura 2000 forest contracts at the individual level of intervention areas in France. The level of long-term biodiversity was assessed using ex ante and ex post levels of conservation status, evaluated on a 100-point scale. Data collection was conducted on the contract areas using a combination of plotless and line intersection sampling methods. Cost-effectiveness was analyzed by modeling a cost function of conservation measures that is estimated simultaneously with the ex ante and ex post biodiversity equations. We performed an empirical illustration based on a small number of observations, and, therefore, the results deserve to be confirmed using larger databases. The conservation measures implemented in the contracts studied had a significant effect on maintaining and restoring biodiversity. Nevertheless, we found pronounced diseconomies of scale and low cost-effectiveness. This suggests the possibility of less ecologically ambitious contracts with lower average costs. Our results also recommend new targeting and prioritizing rules to implement more cost-effective conservation measures (e.g., veteran trees) in a less costly context (e.g., targeting main tree species in larger intervention areas). These recommendations could make Natura 2000 contracts significantly more cost-effective.

Spatial distribution pattern of dominant tree species in different disturbance plots in the Changbai Mountain

The effects of disturbance on spatial patterns and species interactions provide critical information on community structure and species coexistence. Two standard plots of 1-ha were set, one of them was a sample plot with retrograde succession after disturbance, and the other one was undisturbed. Spatial indices and Spatial patterns statistics were used to analyze the spatial pattern and inter-specific correlation of main tree species in two plots. Our results showed that the diameter distributions of different species have reverse J-shape, unimodal and bimodal distribution in the disturbed plot, while bell-shaped curves were observed in the undisturbed plot. The distributions of tree species were mainly showed clustered patterns in almost all scales through univariate pair correlation function. Some similar results of the classification of Wiegand scheme of species association consistent with the consequences of the bivariate pair correlation. The mark variograms showed positive autocorrelation at a coarse scale. The current study may aid in efforts of forest management planning and ecosystem services. Meanwhile, different research methods of spatial distribution also help to improve the accuracy of spatial distribution and the interspecific association of tree species.

КОМПЛЕКСНА ОЦІНКА СКВЕРУ ІМ. І. ЧЕРНЯХОВСЬКОГО М. УМАНЬ ЧЕРКАСЬКОЇ ОБЛАСТІ ТА ПРОПОЗИЦІЇ ЩОДО ЙОГО ВІДНОВЛЕННЯ

The article presents an analysis of the dendrological composition, spatial and phytocenotic structure of the plantations of I. Chernyakhovsky park in Uman, Cherkasy region. During plantation inventory in the park were found 18 taxa of trees, 2 species of shrubs and 3 species of perennial flowering plants. The dendrological structure of the park is mainly represented by the genera Aceraceae (17,1 %), Tiliaceae (17,6 %), Rosaceae (4,8 %), Hippocastanaceae (1,7 %), the share of other genera is insignificant. The main tree species in the groups are Aesculus hippocastanum L. The accompanying species are Styphnolobium japonicum L., Robinia pseudoacacia L., Tilia cordata L. and others. The composition of the park is dominated by simple groups. Green plantations make up 76.2% and occupy a significant part of the park's territory, 36.4% belong to artificial coverings. The project of reconstruction of the territory envisages increase of species composition and improvement of decorative qualities of the park plantations. For this purpose we suggest using the most ornamental plants (Picea pungens f. "Glauca", Larix decidua f. "Pendul", Picea omorika L., Picea abies f. "Ohlendorffii", Catalpa bignonioides L., Platanus occidentalis L., Prunus serrulata f. "Kiku shidare", Stachys lanata, Juniperus communis f. "Repanda", Buxus microphylla f. "Folker", Rhododendron impeditum L., etc.).

Mapping Dominant Tree Species of German Forests

The knowledge of tree species distribution at a national scale provides benefits for forest management practices and decision making for site-adapted tree species selection. An accurate assignment of tree species in relation to their location allows conclusions about potential resilience or vulnerability to biotic and abiotic factors. Identifying areas at risk helps the long-term strategy of forest conversion towards a natural, diverse, and climate-resilient forest. In the framework of the national forest inventory (NFI) in Germany, data on forest tree species are collected in sample plots, but there is a lack of a full coverage map of the tree species distribution. The NFI data were used to train and test a machine-learning approach that classifies a dense Sentinel-2 time series with the result of a dominant tree species map of German forests with seven main tree species classes. The test of the model’s accuracy for the forest type classification showed a weighted average F1-score for deciduous tree species (Beech, Oak, Larch, and Other Broadleaf) between 0.77 and 0.91 and for non-deciduous tree species (Spruce, Pine, and Douglas fir) between 0.85 and 0.94. Two additional plausibility checks with independent forest stand inventories and statistics from the NFI show conclusive agreement. The results are provided to the public via a web-based interactive map, in order to initiate a broad discussion about the potential and limitations of satellite-supported forest management.

Stem volume by height classes of immature, mature and overmature stands of the main forest-forming species of Ukraine

Generally, it is impossible to measure diameters and heights of all trees in a forest stand. Therefore, models of relationships between heights (h) and diameters (d) of trees are commonly used in practice for stem volume estimation. This study aimed at developing models of tree height-diameter (h-d) relationships as well as corresponding models of the tree stem volume for immature, mature and overmature stands of the main forest-forming species of Ukraine. This paper is a aggregation of long-term studies of the stem volume, which are based on the results of measuring about 10 thousand sample trees. Modelling of the tree height-diameter relationships was performed using relative height values. The methodology used in this study allowed generalising the measurements of sample trees collected in stands of various forest site types, productivity levels, and age categories. The average height of trees with a diameter of 24 cm was taken as the reference during modelling relative heights, while the diameter of 40 cm was chosen as the reference for overmature Scots pine stands. As a result, the parameters of a unified mathematical model of relative heights for immature, mature, and overmature stands of the main forest-forming tree species of Ukraine were established. Based on these models, height-diameter relationships in forest stands of different height classes were predicted. The authors demonstrated that the developed mathematical models substantially simplify the methodology of field work during timber surveys. The paper also presents models of the tree stem volume. These models predict the stem volume outside the bark based on diameters and heights of trees or using the developed models of h-d relationships. In this study, a unified system of mathematical models of stem volume by height classes were created for immature, mature, and overmature stands of the main forest-forming species of Ukraine. The results of the study are introduced to the National Forest Inventory of Ukraine for growing stock volume calculation at sample plot level using measurements of individual trees. The developed models can be used both by operation forestry (estimation of the timber volume during harvesting), and forest management (forecasting the future structure of forests and estimating the growing stock volume), as well as in the forest ecology

Capture of fire smoke particles by leaves of Cunninghamia lanceolata and Schima superba, and importance of leaf characteristics

Emission of particulate matter (PM) during forest fires is a major source of air pollution and hence purification of atmospheric pollution has gained increasing importance. Trees can absorb polluting gases and fine particles by their leaves from the atmosphere and act as a sustainable air purification filter. However, the capture efficiency varies among tree species; thus exploring the ability of forest trees to capture smoke PM released during forest fires provides a basis for assessing net emissions from forest fires and the impact of smoke on forest ecosystems. In this study, the main afforestation tree species, Cunninghamia lanceolata (Lamb.) Hook, and a fire-resistant tree species, Schima superba Gardn.et Champ, in southern China were exposed to different smoke concentrations by simulating forest fire. The amount of PM per unit leaf area, absorption of nutrient element, leaf surface characteristics and antioxidant enzyme activities were determined. The main findings were: (1) The total quantity of PM captured by unit leaf area (μg·cm−2) of C. lanceolata was 28.25 ± 1.12, 30.52 ± 3.43 and 33.14 ± 3.00 in low, intermediate and high smoke concentrations, respectively. The corresponding values for S. superba was 5.96 ± 0.56, 10.09 ± 1.13 and 12.27 ± 0.39, respectively. (2) Both species had weak absorption capacity for inorganic ions in the PM. (3) The purification of smoke PM by leaves was mainly related to leaf surface roughness, where it was higher for C. lanceolata than S. superba leaves. (4) Smoke treatment positively affected the contents of chlorophyll and soluble protein as well as increased antioxidant enzyme activities. In conclusion, the findings highlight the importance of leaf structural characteristics in capturing smoke particles and C. lanceolata is better suited for purification of atmospheric smoke particles following forest fire than S. superba.

The current state of Ulmus pumila L. in shelterbelts dry steppe zone of the Republic of Khakassia

One of the most effective and cheapest ways to reduce environmental stress on arable land is forest shelterbelts. Elm (Ulmus pumila L.) is the main tree species used in field-protective afforestation in the dry steppe zone of the Republic of Khakassia. The studies were carried out in field-protective forest belts of different planting methods, consisting of Ulmus pumila, growing in the Koibal steppe of the Beisky district of the Republic of Khakassia. Here, using modern techniques, temporary trial plots were laid. The aim of the study was to study the current state of life of elm shelterbelts in the dry steppe zone of the Republic of Khakassia. The features of growth, preservation, natural regeneration and sanitary condition of elm forests on trial plots are analyzed depending on the planting methods and the design of forest plantations growing on underdeveloped chestnut sandy loamy soil. It has been established that the best condition of elm trees (1.7-2.2 points) 31 years after planting is noted in forest belts with a checkerboard arrangement of trees, and the worst (2.8-3.2 points) is in forest belts with row plant placement, which is necessary take into account when creating a new generation of shelterbelts.

Forest vegetation structure of the Bogd Khan Mountain: A strictly protected area in Mongolia

Bogd Khan Mountain is a strictly protected area located in the Khentei mountain range. It lies in the transitional zone of the Siberian coniferous taiga and the Asian steppe and has a unique ecosystem. The present study was conducted with the objective of identifying the plant community type, forest structure, and the changes in forest stands of the Bogd Khan Mountain. Sampling was done at 155 plots randomly along the gradients of the entire forest. Differences in species composition, biological spectrum, species diversity, and importance value were analyzed in each community. This study revealed the occurrence of six plant community types comparing of Larix sibirica, Picea obovata , Pinus sibirica , Betula pendula subsp. mandshurica , Pinus sylvestris and Populus tremula . These communities were different in species richness, diversity, and their distribution correlated to the altitudinal gradient (score 0.71735; p value 0.001). An upsurge in Picea obovata, and Betula pendula subsp. mandshurica community was found, indicating changes in the ecosystem such as permafrost melting, caused by anthropogenic influences. We suggest preserving the main dominant tree species in the native communities and reduction of the anthropogenic impacts urgently for the effective management of the biodiversity of the Bogd Khan Mountain.

Crown allometry and growing space requirements of four rare domestic tree species compared to oak and beech: implications for adaptive forest management

Rare domestic tree species are increasingly being viewed as promising alternatives and additions to current main tree species in forests facing climate change. For a feasible management of these rare species, it is, however, necessary to know their growth patterns and space requirements. This information has been lacking in management and science up to now. Our study investigated the basic crown allometries of four rare domestic tree species (European hornbeam, European white elm, field maple and wild service tree) and compared them to the more established and assessable European beech and oak (sessile oak and pedunculate oak). For our analysis, we used data from eight temporary research plots located on seven sites across south-eastern Germany, augmented by data from long-term plots. Using quantile regression, we investigated the fundamental relationships between crown projection area and diameter, and height and diameter. Subsequently, we used a mixed-effect model to detect the dependence of crown allometry on different stand variables. We derived maximum stem numbers per hectare for each species at different stand heights, thus providing much-needed practical guidelines for forest managers. In the early stages of stand development, we found that European white elm and field maple can be managed with higher stem numbers than European beech, similar to those of oak. European hornbeam and wild service tree require lower stem numbers, similar to European beech. However, during first or second thinnings, we hypothesise that the rare domestic tree species must be released from competitors, as shade tolerance and competitiveness decrease with age. Furthermore, we argue that thinnings must be performed at a higher frequency in stands with admixed European beech because of the species’ high shade tolerance. When properly managed, rare species can reach target diameters similar to oak and beech.

Analysis of Tree Species Suitability for Plantation Forests in Beijing (China) Using an Optimal Random Forest Algorithm

For afforestation, it is necessary to consider habitat conditions and their impact on specific tree species, in order to enable the selection of appropriate species to improve forest productivity and stand stability. Based on the 2014 Beijing forest management inventory data, we evaluated site quality using theoretical growth equations and quantile regression; we analyzed the effects of climate, topography, and soil variables on the growth of six main tree species using random forest models optimized by a genetic algorithm; and we mapped the potential habitat of six main tree species in Beijing. The results showed that climatic factors were the most important factors affecting tree growth. The prediction models had good accuracy, with an AUC of 0.75–0.85. Among the six main tree species studied, Pinus tabulaeformis Carr. was suitable for all of Beijing’s forest land. Platycladus orientalis (Linn.) Franco, Robinia pseudoacacia Linn. and Salix matsudana Koidz. were suitable for the mountainous areas, while Sophora japonica Linn. and Populus tomentosa Carr. were suitable for planting in the plains area of southeast Beijing. The optimized random forest model applied in this study gives insight into the distribution suitability of the main tree species in Beijing, and could serve as a reference for afforestation design.

Effect of pH on the sorption of dissolved organic carbon derived from six tree species in forest soils

Dissolved organic carbon (DOC) is an important component of the total carbon (C) pool in temperate forest soils. The ability of forest soils to sorb DOC is an essential feature in the context of ecosystem changes (such as climate change) and the resulting changes in the C cycle. The aim of this study was to investigate the ability of forest soils with different pH levels to sorb DOC from litter of different forest tree species. To accomplish this, we conducted two laboratory experiments in which the soil differed in the depth from which they were sampled (topsoil vs. subsoil) and the initial DOC content. We modified the soil pH to obtain a range covering most soils in temperate forests (approximately 3.5–8). Soil samples were leached with extracts of similar DOC content obtained from the litter of six main forest-forming tree species in temperate zone. Increased DOC sorption was observed at approximate soil pH levels of 3.5 and 7.5, with the highest sorption capacity occurring at low pH. The DOC sorption capacity was decreasing with consecutive leaching with litter extract. The capacity of DOC sorption also depended on the litter species. In addition, the initial concentration of C in soil had no significant relationship with sorption capacity. Litter species were related to the sorption of released DOC, which was probably linked to the Al content in the litter. The increased DOC sorption at low pH was likely because of dissolved organic matter protonation (saturation of functional groups with H+ ions resulting in proton bridging and van der Waals forces), while Ca2+ ions causing cation bridging, flocculation or non-columbic interactions were likely responsible for the increased sorption at high pH. Our research shed light on the significant effects of soil pH on the stabilization of DOC, as well as the important role and positive influence of Al on DOC sorption by forest soils. Our findings provide new, significant insight by presenting that litter-derived DOC sorption is dependent both on soil pH and litter chemical composition.

Estimating Tree Defects with Point Clouds Developed from Active and Passive Sensors

Traditional inventories require large investments of resources and a trained workforce to measure tree sizes and characteristics that affect wood quality and value, such as the presence of defects and damages. Handheld light detection and ranging (LiDAR) and photogrammetric point clouds developed using Structure from Motion (SfM) algorithms achieved promising results in tree detection and dimensional measurements. However, few studies have utilized handheld LiDAR or SfM to assess tree defects or damages. We used a Samsung Galaxy S7 smartphone camera to photograph trees and create digital models using SfM, and a handheld GeoSLAM Zeb Horizon to create LiDAR point cloud models of some of the main tree species from the Pacific Northwest. We compared measurements of damage count and damage length obtained from handheld LiDAR, SfM photogrammetry, and traditional field methods using linear mixed-effects models. The field method recorded nearly twice as many damages per tree as the handheld LiDAR and SfM methods, but there was no evidence that damage length measurements varied between the three survey methods. Lower damage counts derived from LiDAR and SfM were likely driven by the limited point cloud reconstructions of the upper stems, as usable tree heights were achieved, on average, at 13.6 m for LiDAR and 9.3 m for SfM, even though mean field-measured tree heights was 31.2 m. Our results suggest that handheld LiDAR and SfM approaches show potential for detection and measurement of tree damages, at least on the lower stem.

Uncertainty of biomass stocks in Spanish forests: a comprehensive comparison of allometric equations

Biomass and carbon content are essential indicators for monitoring forest ecosystems and their role in climate action, but their estimation is not straightforward. A typical approach to solve these limitations has been the estimation of tree or stand biomass based on forest inventory data, using either allometric equations or biomass expansion factors. Many allometric equations exist, but very few studies have assessed how the calculation methods used may impact outcomes and how this impact depends on genera, functional group, climate or forest structural attributes. In this study we evaluate the differences in biomass estimates yielded by the most widely used biomass equations in Spain. We first quantify the discrepancies at tree level and among the main forest tree species. We observed that the divergences in carbon estimations between different equations increased with tree size, especially in the case of hardwoods and for diameters beyond the range used to calibrate the equations. At the plot level, we found considerable differences between the biomass values predicted using different methods (above 25% in one out of three plots), which constitutes a warning against the uncritical choice of equations to determine biomass or carbon values. The spatial representation of the differences revealed geographical patterns related to the dominance of fast-growing species such as Eucalyptus or Pinus pinaster, with a minor effect of forest structure, and almost no effect of climate. Finally, we observed that differences were mostly due to the data source rather than the modelling approach or equation used. Based on our results, BEF equations seem a valid and unbiased option to provide nation-level estimations of carbon balance, although local equations should preferably be used if they are available for the target area.

Response of Ginkgo biloba growth and physiological traits to ozone stress

Ginkgo biloba , the main greening tree species in Beijing, was used to study the effects of elevated ozone (O 3 ) concentrations on physiology and ecology using an open-top air chamber (OTC). We set three O 3 concentration gradients (NF: normal atmospheric O 3 concentration; NF40: normal atmospheric O 3 concentration plus 40 nmol/mol; NF80: normal atmospheric O 3 concentration plus 80 nmol/mol). Based on the theoretical basis of the coupling of O 3 and transpiration through stomata, the O 3 uptake from the leaf surface of G. biloba was studied under artificial control. The results showed that with the O 3 concentration increased, the leaves of G. biloba were damaged, stomatal density, stomatal aperture, stomatal size, net photosynthetic rate, transpiration rate, stomatal conductance, and chlorophyll content decreased, while intercellular CO 2 concentrations and relative conductivity increased. The monthly and daily variations in the liquid flow density of G. biloba decreased with the increase in O 3 concentration. Similarly, water consumption and the ozone uptake rate ( F O3) of G. biloba decreased with the increase in O 3 concentration: Water consumption by the entire tree under the NF40 and NF80 ozone concentrations decreased compared to NF, the rates of decline were 68.77% and 78.38%, respectively. The rates of F O3 decrease were 15.48% and 31.04%, respectively.

How Does Sample Labeling and Distribution Affect the Accuracy and Efficiency of a Deep Learning Model for Individual Tree-Crown Detection and Delineation

Monitoring and assessing vegetation using deep learning approaches has shown promise in forestry applications. Sample labeling to represent forest complexity is the main limitation for deep learning approaches for remote sensing vegetation classification applications, and few studies have focused on the impact of sample labeling methods on model performance and model training efficiency. This study is the first-of-its-kind that uses Mask region-based convolutional neural networks (Mask R-CNN) to evaluate the influence of sample labeling methods (including sample size and sample distribution) on individual tree-crown detection and delineation. A flight was conducted over a plantation with Fokienia hodginsii as the main tree species using a Phantom4-Multispectral (P4M) to obtain UAV imagery, and a total of 2061 manually and accurately delineated tree crowns were used for training and validating (1689) and testing (372). First, the model performance of three pre-trained backbones (ResNet-34, ResNet-50, and ResNet-101) was evaluated. Second, random deleting and clumped deleting methods were used to repeatedly delete 10% from the original sample set to reduce the training and validation set, to simulate two different sample distributions (the random sample set and the clumped sample set). Both RGB image and Multi-band images derived from UAV flights were used to evaluate model performance. Each model’s average per-epoch training time was calculated to evaluate the model training efficiency. The results showed that ResNet-50 yielded a more robust network than ResNet-34 and ResNet-101 when the same parameters were used for Mask R-CNN. The sample size determined the influence of sample labeling methods on the model performance. Random sample labeling had lower requirements for sample size compared to clumped sample labeling, and unlabeled trees in random sample labeling had no impact on model training. Additionally, the model with clumped samples provides a shorter average per-epoch training time than the model with random samples. This study demonstrates that random sample labeling can greatly reduce the requirement of sample size, and it is not necessary to accurately label each sample in the image during the sample labeling process.

Estimation and Economic Valuation of Above-Ground Carbon in Forest Area with the Special Purpose of Gunung Bromo, Karanganyar, Central Java, Indonesia

Climate change and the increasing greenhouse effect are serious problems of global concern today. The existence of forests plays an essential role in carbon sequestration and storage to reduce greenhouse gas (GHG) concentration in the atmosphere. Forest Area with the Special Purpose (KHDTK) of Gunung Bromo has an area of 126,291 ha that is designated as an educational forest. The area has been managed by Universitas Sebelas Maret since 2019 and consists of three main tree species, namely Pinus merkusii, Swietenia mahagoni, and Dalbergia latifolia. This study aims to estimate the potential uptake and economic valuation of carbon stocks in the KHDTK of Gunung Bromo. Stratified Systematic Sampling with Random Start was used as an inventory method in this study. The estimation of above-ground carbon uptake used general allometric equations (non-destructive method). Furthermore, the carbon economy valuation referred to the range of calculating the average carbon price for each program specification. The results showed that the estimated carbon of tree stands in KHDTK of Gunung Bromo reached 75.81 tonnes C/ha with a carbon economic valuation of USD 758.1/ha or equivalent to IDR 10,856,863.80/ha. Exploring the potential for biodiversity (flora and fauna) and environmental services such as carbon sink will support the ecotourism program in KHDTK of Gunung Bromo. Keywords: biomass, carbon estimation, economic valuation, KHDTK of Gunung Bromo

Methane Contributions of Different Components of Kandelia candel–Soil System under Nitrogen Supplementation

Kandelia candel is the most widely distributed tree species on the southeast coast of China and is also the main afforestation tree species along the coastal wetland. In recent years, inorganic nitrogen pollution has become increasingly severe, and investigating the effects of nitrogen input on methane emissions in Kandelia candel–soil systems has become significant from a global change perspective. However, the effect of nitrogen input on methane emissions in coastal wetland systems is still uncertain. The field tidal environment is complex and varied, and thus it is difficult to accurately control the amount of nitrogen in the system. Therefore, in order to accurately assess the effects of different concentrations of foreign nitrogen input on methane emission fluxes in a Kandelia candel–soil system, we use indoor tidal simulation experimental devices and design two simulation systems with and without plant planting to explore the difference of methane emission flux in this system under five nitrogen input concentrations: N0 (0 g N·m−2·a−1), N1 (5 g N·m−2·a−1), N2 (10 g N·m−2·a−1), N3 (20 g N·m−2·a−1), and N4 (30 g N·m−2·a−1). The results showed that: (1) The introduction of Kandelia candel promoted methane emissions in coastal wetland ecosystem. Under each nitrogen application concentration, the mean CH4 emission flux in the planting group was 42.98%, 65.59%, 40.87%, 58.93% and 39.23% higher than that in the non-planting group, respectively. (2) Nitrogen input significantly promoted methane emissions in both planted and non-planted environments, and the promoting effect showed as follows: N4 > N3 > N2 > N1 > N0. (3) After the introduction of Kandelia candel, the contribution of Kandelia candel and soil microorganisms to methane emissions was different under different concentrations of nitrogen addition. The contribution rate of Kandelia candel to CH4 emission flux of Kandelia candel–soil system ranged from 10.74% to 60.25%, with an average contribution rate of 37.30%. The changed soil microbes contributed 39.75% to 89.26% to the CH4 emission flux in the Kandelia candel–soil system, with an average contribution rate of 62.60%. Under N3 nitrogen application concentration, the emission flux of plant was the largest, which was significantly higher than that of the soil microbial pathway; at other concentrations, the methane emissions from the soil microbial pathway were greater than that of the plant pathway, and the contribution rate to the plant–soil system reached 60.25%. The results of this study provide an important basis for improving the estimation accuracy of carbon emissions in coastal waters and formulating policies for the restoration and protection of coastal wetlands.

A Study of the Distribution of Forest Density in Inner Mongolia Based on Environmental Factors

With the intensification of global climate change, exploring the impact of environmental factors on tree density can provide technical support for sustainable forest management. In this paper, the random forest parameters nTree and mtry were optimized using a particle swarm optimization algorithm. The density, average temperature, soil thickness, forest water consumption, slope, slope direction, slope position, soil type, and diameter at breast height (DBH) of the dominant tree species in Inner Mongolia were fitted using random forest regression with a satisfactory fitting effect (R2 > 0.60). The results show that the average temperature, soil thickness, and forest water consumption were the main factors restricting tree density, and the influence of each factor changed depending on the stage of tree growth. Based on 2018 forest resource data of the Inner Mongolia Autonomous Region, four diameter class models were used to calculate tree density, and Kriging interpolation was used to form a density distribution grid map of the main tree species according to diameter class toward providing a theoretical basis and data support for afforestation and forest management strategies that are justified according to the available environmental resources.

Specific effects of tree species on soil carbon sequestration in a rice-tree association mesocosm experiment: Evidence from natural 13C abundance

Within agroforestry systems, trees greatly contribute to soil carbon (C) sequestration. We still know little about how this contribution varies according to tree species. Here, we quantified the soil C content derived from three main tree species, Eucalyptus robusta, Coffea arabica and Citrus clementina, used in rainfed rice-based agroforestry in the Highlands of Madagascar. A fully factorial controlled mesocosm experiment was performed, with seedlings of the tree species planted with or without rice in a Ferralsol. The natural 13C abundance in the soil was measured to assess tree- and rice-derived C. One year after planting, Eucalyptus robusta was the species exhibiting the highest tree-derived C values, with 148 g C m−2 on average. In contrast, Citrus clementina transferred only 12 g C m−2 to the soil. No significant contribution of Coffea arabica to the soil C stock was found. The presence of rice affected neither the growth of tree seedlings nor their abilities to provide C to the soil. The difference in soil C sequestration among tree species was significantly correlated with differential root biomass. Tree root biomass was significantly correlated with soil δ13C. This experimental assay highlighted the contrasting contributions of tree species to ecological processes such as soil C sequestration at the early stage of agroforestry establishment. Further studies considering tree density and spatial arrangement should be conducted under field conditions to gain further insights into tree contributions to soil C sequestration in agroforestry systems.