Artificial Coniferous Forest Research Articles

Biomass Estimation and Saturation Value Determination Based on Multi-Source Remote Sensing Data

Forest biomass estimation is undoubtedly one of the most pressing research subjects at present. Combining multi-source remote sensing information can give full play to the advantages of different remote sensing technologies, providing more comprehensive and rich information for aboveground biomass (AGB) estimation research. Based on Landsat 8, Sentinel-2A, and ALOS2 PALSAR data, this paper takes the artificial coniferous forests in the Saihanba Forest of Hebei Province as the object of study, fully explores and establishes remote sensing factors and information related to forest structure, gives full play to the advantages of spectral signals in detecting the horizontal structure and multi-dimensional synthetic aperture radar (SAR) data in detecting the vertical structure, and combines environmental factors to carry out multivariate synergistic methods of estimating the AGB. This paper uses three variable selection methods (Pearson correlation coefficient, random forest significance, and the least absolute shrinkage and selection operator (LASSO)) to establish the variable sets, combining them with three typical non-parametric models to estimate AGB, namely, random forest (RF), support vector regression (SVR), and artificial neural network (ANN), to analyze the effect of forest structure on biomass estimation, explore the suitable AGB of artificial coniferous forests estimation of machine learning models, and develop the method of quantifying saturation value of the combined variables. The results show that the horizontal structure is more capable of explaining the AGB compared to the vertical structure information, and that combining the multi-structure information can improve the model results and the saturation value to a great extent. In this study, different sets of variables can produce relatively superior results in different models. The variable set selected using LASSO gives the best results in the SVR model, with an R2 values of 0.9998 and 0.8792 for the training and the test set, respectively, and the highest saturation value obtained is 185.73 t/ha, which is beyond the range of the measured data. The problem of saturation in biomass estimation in boreal medium- and high-density forests was overcome to a certain extent, and the AGB of the Saihanba area was better estimated.

Accuracy assessment of GEDI terrain elevation, canopy height, and aboveground biomass density estimates in Japanese artificial forests

Global forests face severe challenges owing to climate change, making dynamic and accurate monitoring of forest conditions critically important. Forests in Japan, covering approximately 70% of the country's land area, play a vital role yet often overlooked in global forestry. Japanese forests are unique, with approximately 50% comprising artificial forests, predominantly coniferous forests. Despite the Japanese government's extensive use of airborne Light Detecting and Ranging (LiDAR) to assess forest conditions, these data need more availability and frequency. The Global Ecosystem Dynamics Investigation (GEDI), the first Spaceborne LiDAR data explicitly designed for vegetation monitoring, is expected to provide significant value for high-frequency and high-accuracy forest monitoring. To assess the accuracy of GEDI data in Japanese artificial coniferous forests, the reference data were gathered from 53,967,770 artificial coniferous trees via airborne LiDAR data in Aichi Prefecture, Japan. This data was then compared to the corresponding GEDI-derived terrain elevations, canopy heights (GEDI RH98), and aboveground biomass density (AGBD) estimates to assess the accuracy of GEDI data. This research also explored how different factors influence the accuracy of GEDI terrain elevation estimates, including the type of beam, time of acquisition (day or night), beam sensitivity, and terrain slope. Additionally, the effects of various forest structural parameters, such as the height-to-diameter ratio, crown length ratio, and the number of trees on the accuracy of the GEDI canopy height and AGBD, were investigated. The results showed that GEDI terrain elevation demonstrated high accuracy across various slope conditions, with rRMSE ranging from 2.28% to 3.25% and RMSE ranging from 11.68 m to 16.54 m. After geolocation adjustment, the comparison of canopy height estimates derived from GEDI to airborne LiDAR-derived canopy height also showed high accuracy, exhibiting a rRMSE of 22.04%. In contrast, the GEDI AGBD product showed moderate accuracy, with a rRMSE of 52.79%. The findings also indicated that the accuracy of GEDI RH98 was influenced by terrain slope and crown length ratio, whereas the accuracy of GEDI AGBD was mainly impacted by the number of trees and crown length ratio. This study provided the first baseline accuracy assessment of GEDI terrain elevation, RH98, and AGBD estimates in Japanese artificial forests. Furthermore, this study provided valuable insights into the accuracy of GEDI metrics by examining potential factors.

Comammox Nitrospira dominates the nitrification in artificial coniferous forest soils of the Qilian Mountains

Complete ammonia oxidizers (Comammox, CMX) are a newly discovered and important component of the nitrogen cycle. While CMX Nitrospira has been detected in various ecosystems, few studies so far have focused on the relative contribution and co-occurrence network of ammonia oxidizing archaea (AOA), bacteria (AOB), and CMX Nitrospira in artificial forest ecosystems (tree plantations). We evaluated the dynamics of composition, co-occurrence patterns and contribution of soil microbial nitrifiers to nitrification in soil of various tree species with different ages in the Qilian Mountains employing the space for time substitution approach, quantitative PCR and high-throughput sequencing technology. Generally, plantation development significantly reduced soil potential nitrification rates. Inhibition experiments and modular analysis showed that AOA played leading roles in nitrification of abandoned farmland and 17-year-old Hippophae rhamnoides, whereas CMX Nitrospira dominated in 36-year-old Picea crassifolia, 36-year-old Picea crassifolia and Larix gmelinii mixed plantation, and 50-year-old Picea crassifolia. The dominant AOA and CMX Nitrospira lineages in all samples were Group I.1b and Clade B, respectively. The assembly of nitrifier community was governed by stochastic processes, in which dispersal limitation made a significant contribution. The nitrifiers coexist in a mutualistic manner, albeit with possible functional redundancy, while the modular analysis revealed the aggregation pattern of the four modules in different artificial forests' soil. The Mantel test showed that modular formation is mainly affected by NH4+ and SOM. These results broaden our current understanding of the relation between CMX Nitrospira and canonical ammonia oxidizers in terrestrial ecosystems, and provide empirical evidence for not only niche differentiation, but also the relative contribution and co-occurrence patterns of nitrifying communities in an artificial forest ecosystem.

Seasonal Dynamics and Influencing Factors of Litterfall Production and Carbon Input in Typical Forest Community Types in Lushan Mountain, China

Litterfall is an important part of the process of nutrient circulation and energy flow in forest ecosystems. Mountain forests are strongly eroded by running water in that the surface soil is thinner, and the terrain is complex and diverse. They are more sensitive to climate change, which will affect the ecological processes and carbon sink functions of forest ecosystems. Taking Lushan Mountain as an example, we studied the dynamic characteristics of litterfall components, seasonal changes in carbon input and the influencing factors of typical forest communities in the subtropics. The results showed that the total annual average litterfall components of evergreen broad-leaved forest (EBF) > artificial coniferous forest (ACF) > deciduous broad-leaved forest (DBF) > renew young forest (RYF), and that leaf litterfall is the first productivity in the litterfall components, and the peak of litterfall is mainly concentrated in spring and autumn, showing a single- or double-peaked change pattern. There was a linear relationship between the components of litterfall in the four forest communities and the stand factor, but the correlation degree R2 was small. Overall, the results showed that the total amount of litterfall in the four forest communities was affected by canopy density and stand density. Light, temperature and water at different altitudes had different effects on the amount of litterfall, with excessive temperatures at lower altitudes likely to limit forest growth and development under adequate light and water, and the opposite was true at higher altitudes. The results of Pearson correlation analysis showed that EBF and DBF were negatively correlated with rainfall, that ACF and RYF were negatively correlated with temperature and rainfall, and that wind speed was positively correlated. The average annual carbon input size of the four forest communities was EBF > ACF > RYF > DBF, which may be related to environmental conditions and vegetation types, and the seasonal differences were arranged in order of spring > autumn > summer > winter. It can be seen that, considering performance under future climate change, EBF is more conducive to nutrient input and has good soil fertility maintenance ability.

Result of a year-long animal survey in a state-owned forest farm in Beijing, China.

Background Artificial forest can have great potential in serving as habitat to wildlife, depending on different management methods. As the state-owned forest farms now play a new role in ecological conservation in China, the biological richness of this kind of land-use type is understudied. Once owned by a mining company, a largest state-owned forest farm, Jingxi Forest Farm, has been reformed to be a state-owned forest farm with the purpose of conservation since 2017. Although this 116.4 km2 forest farm holds a near-healthy montaine ecosystem very representative in North China, a large proportion of artificial coniferous forest in the forest farm has been proven to hold less biodiversity than natural vegetation. This situation, however, provides a great opportunity for ecological restoration and biodiversity conservation. Therefore, from November 2019 to December 2020, we conducted a set of biodiversity surveys, whose results will serve as a baseline for further restoration and conservation. New information Here, we report the result of a multi-taxa fauna diversity survey conducted in Jingxi Forest Farm mainly in year 2020 with explicit spatial information. It is the first survey of its kind conducted in this area, revealing a total of 19 species of mammals, 86 birds, four reptiles, two amphibians and one fish species, as well as 101 species of insects. Four species of mammals are identified as data-poor species as they have less than 100 occurrence records with coordination in the GBIF database. One species of insect, representing one new provincial record genus of Beijing, is reported.

塞罕坝地区人工针叶林径向生长对水热条件的响应

PDF HTML阅读 XML下载 导出引用 引用提醒 塞罕坝地区人工针叶林径向生长对水热条件的响应 DOI: 10.5846/stxb202107071814 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金(41771051,41630750) Response of radial growth of artificial coniferous forest to hydrothermal conditions in Saihanba Area Author: Affiliation: Fund Project: the National Natural Science Foundation of China (41771051和41630750) 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:树木生长对水热条件响应的研究在揭示气候变化的生态影响中发挥着重要作用。为探讨水热因子对亚洲最大的人工针叶林生长的影响及不同树种生长-水热因子关系特征,选取塞罕坝地区龄级较高的人工针叶林群落的优势树种华北落叶松(Larix principis-rupprechtii)和樟子松(Pinus sylvestrisvar.mongolica),采集树木年轮样芯,并通过年轮宽度数据建立标准年表。通过分析两树种的标准年表数据与气温、地温、降水量、饱和水汽压差等水热因子的相关关系,揭示不同树种对水热因子响应的异同。研究结果显示:华北落叶松的生长受到6、7、9月的干旱胁迫和8月过多降水的限制,同时受到冬季较高的平均地温和降水的促进;樟子松的生长则受到夏季的高温干旱胁迫和8月过多降水的抑制,但8月较高的平均地温以及春季较高的平均最低地温对樟子松的生长存在明显促进作用。塞罕坝地区华北落叶松受干旱胁迫强于樟子松,而樟子松受较低地温的胁迫强于华北落叶松。考虑到区域增温的趋势,推断樟子松应是更适合在塞罕坝等半干旱地区继续进行大面积人工造林和经营管理的树种。 Abstract:The research on the responses of tree growth to the hydrothermal factors in the marginal areas, such as the agro-pastoral ecotone, has played a vital role in revealing the ecological impacts of climate change. To probe into the influences of hydrothermal condition on the artificial coniferous forest growth, and the characteristic features of tree growth to its hydrothermal factors within different coniferous tree species, we chose the Saihanba Area, where the largest artificial coniferous forests in the Asian region were growing, as the sampling area. We sampled the tree ring data in high age-class artificial forests from two dominant afforestation species, the Larix principis-rupprechtii (larch) and the Pinus sylvestris var. mongolica (pine), and built up two standard tree-ring width chronologies for those two species based on lab analyses. Through examining the correlations between the chronologies of the two species and the local climatic factors including air temperature, surface temperature, precipitation, vapor pressure deficit, and so on, we have further revealed the similarities and differences of those two species in responding to the driving hydrothermal factors. The results are shown as follows. The growth of the larch was limited by the drought stress in June, July and September, and by the excessive rainfall in August, but promoted by the warm surface temperature and relatively more precipitation in winter. Similarly, the growth of the pine was confined by the drought stress resulted from the higher temperature in whole summer, as well as by the over-wet rainfall in August, but promoted apparently by the warm surface temperature in August, as well as by the relatively higher level in the lowest mean surface temperature in spring. The above results suggested that in Saihanba Area, the larch confronted more severe drought stress than that the pine did, but at the same time the larch underwent stronger stress in lower surface temperature than that pine did. Concerning the ever-increasing trend of temperature in the whole region in the coming future, we are inclined to predict that the Pinus sylvestris var. mongolica might be a better and more suitable tree species than that of Larix principis-rupprechtii for further afforestation and reforestation management in those large semi-arid regions such as Saihanba and the similar areas. 参考文献 相似文献 引证文献

Effect of Climate Change on CO2 Flux in Temperate Grassland, Subtropical Artificial Coniferous Forest and Tropical Rain Forest Ecosystems.

The interactions between CO2 flux, an important component of ecosystem carbon flux, and climate change vary significantly among different ecosystems. In this research, the inter-annual variation characteristics of ecosystem respiration (RE), gross ecosystem exchange (GEE), and net ecosystem exchange (NEE) were explored in the temperate grassland (TG) of Xilinhot (2004–2010), the subtropical artificial coniferous forest (SACF) of Qianyanzhou (2003–2010), and the tropical rain forest (TRF) of Xishuangbanna (2003–2010). The main factors of climate change affecting ecosystem CO2 flux were identified by redundancy analysis, and exponential models and temperature indicators were constructed to consider the relationship between climate change and CO2 flux. Every year from 2003 to 2010, RE and GEE first increased and then decreased, and NEE showed no significant change pattern. TG was a carbon source, whereas SACF and TRF were carbon sinks. The influence of air temperature on RE and GEE was greater than that of soil temperature, but the influence of soil moisture on RE and GEE was greater than that of air moisture. Compared with moisture and photosynthetically active radiation, temperature had the greatest impact on CO2 flux and the exponential model had the best fitting effect. In TG and SACF, the average temperature was the most influential factor, and in TRF, the accumulated temperature was the most influential factor. These results provide theoretical support for mitigating and managing climate change and provide references for achieving carbon neutrality.

An observation dataset of carbon and water fluxes of artificial coniferous forests in Qianyanzhou (2003–2010)

An observation dataset of carbon and water fluxes of artificial coniferous forests in Qianyanzhou (2003–2010)

Difference assessment on ecological functions of artificial coniferous forests in water conservation area of Northwestern Hebei

Difference assessment on ecological functions of artificial coniferous forests in water conservation area of Northwestern Hebei

Simulation study on the effects of climate change on aboveground biomass of plantation in southern China: Taking Moshao forest farm in Huitong Ecological Station as an example

Global climate warming has significant effect on territorial ecosystem, especially on forest ecosystem. The increase in temperature and radiative forcing will significantly alter the structure and function of forest ecosystem. The southern plantation is an important part of forests in China, its response to climate change is getting more and more intense. In order to explore the responses of southern plantation to climate change under future climate scenarios and to reduce the losses that might be caused by climate change, we used climatic estimated data under three new emission scenarios, representative concentration pathways (RCPs) scenarios (RCP2.6 scenario, RCP4.5 scenario, and RCP8.5 scenario). We used the spatially dynamic forest landscape model LANDIS-2, coupled with a forest ecosystem process model PnET-2, to simulate the impact of climate change on aboveground net primary production (ANPP), species' establishment probability (SEP) and aboveground biomass of Moshao forest farm in Huitong Ecological Station, which located in Hunan Province during the period of 2014-2094. The results showed that there were obvious differences in SEP and ANPP among different forest types under changing climate. The degrees of response of SEP to climate change for different forest types were shown as: under RCP2.6 and RCP4.5, artificial coniferous forest>natural broadleaved forest>artificial broadleaved forest. Under RCP8.5, natural broadleaved forest>artificial broadleaved forest>artificial coniferous forest. The degrees of response of ANPP to climate change for different forest types were shown as: under RCP2.6, artificial broadleaved forest> natural broadleaved forest>artificial coniferous forest. Under RCP4.5 and RCP8.5, natural broadleaved forest>artificial broadleaved forest>artificial coniferous forest. The aboveground biomass of the artificial coniferous forest would decline at about 2050, but the natural broadleaved forest and artificial broadleaved forest showed a rising trend in general. During the period of 2014-2094, the total aboveground biomass under RCP2.6, RCP4.5 and RCP8.5 scenarios increased by 68.2%, 79.3% and 72.6%, respectively. The total aboveground biomass under various climatic scenarios sort as: RCP4.5>RCP8.5>RCP2.6. We thought that an appropriate temperature might be beneficial to the biomass accumulation in this study area. However, overextended temperature might hinder the sustainable development of forest production and ecological function.

Effects of Stand Origin and Near-Natural Restoration on the Stock and Structural Composition of Fallen Trees in Mid-Subtropical Forests

Fallen trees comprise an important part of forest ecosystems and serve a central role in maintaining the biodiversity and tree regeneration of forests. However, the effects of stand origin and near-natural restoration on the biomass and carbon stock of fallen trees remain unclear. Based on 60 sampling plots of field surveys of mid-subtropical forests in Jiangxi Province, we investigated the stock and structural composition of fallen trees in artificial coniferous forests (Acf), natural coniferous forests (Ncf) (e.g., different stand origins) and natural evergreen broadleaf forests (Nebf) (e.g., near-natural restoration). The following results were obtained: (1) the largest biomass and carbon stocks of fallen trees among three forest types (Nebf, Ncf and Acf) were measured for Nebf; (2) the fallen tree biomass and carbon stock in natural Cunninghamia lanceolata forest (Nclf) were significantly larger than that in artificial Cunninghamia lanceolata forest (Aclf), and the fallen tree biomass and carbon stock in natural Pinus massoniana forest (Npf) were also significantly larger than those in artificial Pinus massoniana forest (Apf); (3) the diameter class allocation in natural forests was more uniform than that in artificial forests; (4) the biomass of fallen trees with mild decay was not significantly different among forest types within stand origin or among the stand origin within forest types; however, the biomass of fallen trees with moderate and heavy decay significantly differed among stand origin (Aclf vs. Nclf, Apf vs. Npf), but was not significant among the forest types (Aclf vs. Apf, Nclf vs. Apf) within a stand origin. Our results suggested that the large biomass and carbon stock of fallen trees in Nebf may serve a significant role in mitigating global warming and carbon cycles in mid-subtropical forests. Therefore, stand origin and near-natural restoration exert significant effects on the carbon stock and structural composition of fallen trees in mid-subtropical forests.

An Evaluation Model for Improving Biodiversity in Artificial Coniferous Forests Invaded by Broadleaf Trees

Increasing attention is being paid to the various functions of forests, especially the conservation of biodiversity. In Japan, 67% of national land is covered by forest, 41% of which is artificial forest (i.e., plantations). Therefore, efforts to conserve forest biodiversity should also target artificial forests. In this study, we investigated the increase in biodiversity resulting from broadleaf tree invasion of artificial coniferous forests. We examined diversity indices and combinations of indices to identify which ones can aid forest managers in evaluating forest diversity. We also studied classification according to the richness of diversity, which corresponded to the growth stages of Chamaecyparisobtusa and Cryptomeria japonica plantation forests. Moreover, we developed a model that will contribute to sustainable forest management and biodiversity over an entire area. The model, based on a specific rotation scenario in a geographic information system, is easy to use and presents spatial and temporal changes at sites visually.

무등산 인공 침엽수림에서 테르펜과 기상인자의 상관성분석

There are many factors to influence the amount of terpene at the forest. However, it is poorly understood whether the amount is altered by meteorological factors. In order to study correlation analysis between terpene amount and meteorological(i.e., temperature, humidity, wind speed, solar radiation) and environmental factors(i.e., oxygen, carbonb dioxide) at the artificial coniferous forest of Chamaecyparis obtusa (site 1) and Cryptomeria japonica (site 2) nearby the <TEX>$1^{st}$</TEX> reservoir at Mt. Moodeung, the research was executed during April to November in 2011. Forest density at site 1 was 1,692 trees/ha, being occupied with 87.2% of Chamaecyparis obtusa, higher than 925 trees/ha at site 2. Carbon dioxide at site 1 was in the range of 385~410 ppm in June, similar to at Anmyundo(395 ppm in 2010). Solar radiation has positive correlation with ambient temperature and inversely negative with relative humidity. Main species of terpene released were <TEX>${\alpha}$</TEX>-pinene, camphene, <TEX>${\beta}$</TEX>-pinene, cymene, <TEX>${\delta}$</TEX>-limonene and camphor at two sites and terpene was more effluent at spring and summer than at fall. The large amount of terpene was emitted in the afternoon than in the morning under the influence of the wind speed and the topographical property. The terpene amount has positive correlation with relative humidity and oxygen, and negative with wind speed and soil temperature. Because correlations of <TEX>${\alpha}$</TEX>-pinene and other terpene materials showed statistically significant within p=0.01. <TEX>${\alpha}$</TEX>-pinene could be suggested as the basic material in explaining the amount of other terpene materials.

Comparative analysis of basidiomycetous laccase genes in forest soils reveals differences at the cDNA and DNA levels

This study was undertaken to investigate laccase-containing basidiomycete communities at the cDNA and DNA levels and to assess the influences of vegetation and soil types on the basidiomycete communities in forest soils. Soil samples were collected from the upper soil layers of two typical subtropical forests (a broad-leaved forest developed in Karst limestone soil and an artificial coniferous forest with Pinus massoniana in red soil) in China. The basidiomycete communities were characterized by cloning and sequencing of the laccase genes at both the cDNA and DNA levels. Compositions of lignin monomers were determined by gas chromatography–mass spectrometry. Most of the laccase genes obtained in this study were new, highlighting the research gap of this functional group. The trends of the basidiomycetous laccase gene diversity among the upper soil layers of the two forests were consistent between the cDNA and DNA levels. The Agaricales had high activity because they dominated all the tested soils. However, the total basidiomycete communities reflected at the cDNA and DNA levels were significantly different due to the presence of some quiescent basidiomycetous groups. Almost all of the lignin components were decomposed from the O to the A layers in the two forests, and laccases produced by Agaricales were likely responsible for the decomposition of guaiacyl monomers. Both vegetation and soil types had great influences on the active laccase-containing basidiomycete communities, primarily via the pH, C/N, and the contents of lignin monomers. The cDNA- and DNA-level approaches presented good consistency of diversities but different compositions of laccase-containing basidiomycete communities, thus emphasizing the importance of focusing on laccase genes at the cDNA level in future studies. It is the quality but not the quantity of SOM to determine the diversity and composition of the active laccase-containing basidiomycete communities.

The Flow Processes of Carbon Fixation Value of Typical Ecosystems

Based on data from ChinaFLUX this study analyzed the daily value flow processes of carbon fixation, monthly value distribution, and daily accumulative processes in a year of two kinds of typical forest, two kinds of grasses and a farmland. The results showed that the annual value of carbon fixation of these ecosystems was different, and flow processes and cumulative processes followed different trends over a year. The sequence of the five kinds of ecosystems based on the annual value of carbon fixation from largest to smallest was Yucheng warm temperate agriculture ecosystem (Yucheng), Qianyanzhou subtropical artificial coniferous forest ecosystem (Qianyanzhou), Changbai Mountain temperate mixed coniferous broad-leaved forest ecosystem (Changbaishan), Haibei alpine meadow ecosystem (Haibei)and Dangxiong alpine meadow ecosystem (Dangxiong). Variability in the daily and monthly carbon fixation at Qianyanzhou was the smallest, followed by Changbaishan, Yucheng, Dangxiong and Haibei. The cumulative processes of daily carbon fixation for the five kinds of ecosystems were well fitted to cubic curves.

Characteristics of Hydrological Runoff in an Artificial Coniferous Forest with Delayed Thinning and Its Long-term Changes

Characteristics of Hydrological Runoff in an Artificial Coniferous Forest with Delayed Thinning and Its Long-term Changes

FIFTY YEARS OF FOREST CHANGE IN NANJING SPIRIT VALLEY

We studied 50 years of change in the species composition, abundance, frequency, importance value, population structure and species diversity of secondary subtropical forests in Nanjing Spirit Valley by comparing data collected along the same belt transects in 1951, 1981 and 2002. In general, the amount of stumpage was relatively steady over time, but the spatial heterogeneity increased. The number of under-story seedlings, saplings and shrubs changed significantly, increased from 4 712 in 1951 to 44 130 in 1981, and then decreased to 7 372 in 2002. Both species richness and dominance changed greatly. The number of species decreased from 75 in 1951 to 50 in 1981 and increased to 73 in 2002. The species diversity indices varied but there was no obvious increase or decrease over time. During over 50 years of secondary succession, the dominant species in the masson pine forest, Pinus massoniana, declined over time because of poor regeneration. It was first replaced by intolerant broad-leaved species, such as Pistacia chinensis and Liquidambar formosana, which were then replaced by relatively tolerant species, such as Quercus variabilis. Some evergreen species invaded successfully and were increasing in dominance. Artificial coniferous forests succeeded to coniferous and deciduous mixed forests, then to deciduous forests, and gradually to zonal vegetation —— deciduous and evergreen broad-leaved mixed forests. Communities on good sites were found to have faster successional rates of change.

The Effect of Delayed Thinning on Nonpoint Pollutants from Artificial Coniferous Forests (Ⅰ)

The Effect of Delayed Thinning on Nonpoint Pollutants from Artificial Coniferous Forests (Ⅰ)

The Effect of Delayed Thinning on Nonpoint Pollutants from Artificial Coniferous Forests (Ⅱ)

The Effect of Delayed Thinning on Nonpoint Pollutants from Artificial Coniferous Forests (Ⅱ)

The Effect of Delayed Thinning on Nonpoint Pollutants from Artificial Coniferous Forests (Ⅲ)

The Effect of Delayed Thinning on Nonpoint Pollutants from Artificial Coniferous Forests (Ⅲ)