Mixed Coniferous Broad-leaved Forest Research Articles

Effects of grazing disturbances on soil seed bank diversity in two vegetation types

Soil seed bank (SSB) play an essential role in the restoration and regeneration of plant communities. Grazing is a common disturbance factor that exerts an important effect on the diversity and composition of the SSB community in forests. Here, we evaluated the structure and composition of SSB along a grazing disturbance gradient of two types of vegetation (broad-leaved forests and mixed coniferous broad-leaved forests) in southwest China. A comparison of the similarity of SSBs with the above-ground vegetation strata (tree, shrub and herb layers) was also analyzed. The experiment revealed the germination of 25 species that belonged to 14 families and 24 genera. The density of SSBs did not show significant differences along the grazing disturbance. The alpha diversity of SSBs was the highest at moderate grazing intensity in broad-leaved forests, and not significantly different along disturbance intensities in mixed coniferous broad-leaved forests. No significant changes were observed in the species composition of SSB along the grazing gradients. Nonmetric multidimensional scaling analyses revealed low similarities between SSBs and above-ground vegetation, with the lowest similarity occurring under medium grazing disturbance intensity. Overall, our research offers significant insight into the response of SSBs to grazing in different vegetation types. It serves as a guide for designing grazing management strategies tailored to natural forests.

The Relationship between Trait-Based Functional Niche Hypervolume and Community Phylogenetic Structures of Typical Forests across Different Climatic Zones in China

Functional traits are pivotal for understanding the functional niche within plant communities. Yet, the relationship between the functional niches of typical forest plant communities across different climatic zones, as defined by functional traits, and their association with community and phylogenetic structures remains elusive. In this study, we examined 215 woody species, incorporating 11 functional traits spanning leaf economy, mechanical support, and reproductive phenology, gathered from forests in four climatic zones from tropical, subtropical, warm-temperate to cold-temperate zones in China and supplemented by the literature. We quantified the functional niche hypervolume (FNH), reflecting the multidimensional functional niche variability. We then probed into the correlation between the FNH and community and phylogenetic structures of forests. Our findings reveal that species richness significantly influences the geographic variance of functional niche space in forest vegetation across different climatic zones. Specifically, a community’s species richness correlates positively with the functional niche breadth occupied by the community species. The FNH of woody plants across diverse forest types shows significant associations with both the mean phylogenetic distance (MPD) and the mean nearest phylogenetic taxon distance (MNTD) of the communities. There is a progressive increase in tropical rainforest (TF), subtropical evergreen deciduous broad-leaved mixed forest (SF), and warm-temperate coniferous broad-leaved mixed forest (WF), followed by a decline in the cold-temperate coniferous forest (CF). This pattern suggests potential environmental filtering in CF, which may constrain the spatial extent of plant functional niches. Our research underscores the substantial variability in the FNH across China’s typical forest vegetation, highlighting the complex interplay between functional traits, community richness, and phylogenetic distance.

Analysis of vertical differentiation of vegetation in Taishan World Heritage site based on cloud model

While the forests on Mount Taishan are predominantly man-made, there is a notable vertical variation in vegetation. This study employs the method of cloud model, quantifying uncertainty (fuzziness and randomness) of things. Utilizing digital elevation model (DEM) and vegetation distribution data, we constructed elevation cloud models for Mount Taishan’s deciduous broad-leaved, temperate coniferous, and mixed coniferous-broadleaved forests. Using three numerical features of the cloud model—Expectation (EX), Entropy (EN), and Hyper-entropy (HE)—we quantitatively analyzed the macro regularity and local heterogeneity of Mount Taishan’s forests vertical distribution from the perspective of uncertainty theory. The results indicate: (1) The EX of the core zone elevation of deciduous broad-leaved forest is 716.65 m, temperate coniferous forest is 1053.51 m, and mixed coniferous-broadleaved forest is 1384.09 m. The variation range of the core zone distribution height is smaller in the mixed coniferous-broadleaved forest (EN: 53.74 m) compared to deciduous broad-leaved forest (EN: 99.63 m) and temperate coniferous forest (EN: 121.70 m). (2) The fuzziness and randomness of the distribution height of the lower extension zones of deciduous broad-leaved forest and temperate coniferous forest (EN: 75.15 m, 184.56 m; HE: 24.09 m, 63.54 m) are greater than those of the upper extension zones (EN: 44.75 m, 42.49 m; HE: 14.48 m, 13.23 m). (3) The distribution fuzziness and randomness within temperate coniferous forests exceed those of deciduous broad-leaved forests. Within the core zones, the uncertainty regarding the vertical distribution of vegetation across different aspects remains consistent, which retains the characteristic of man-made forests. However, in transition areas, there is significant disparity, reflecting the adaptive relationship between vegetation and its environment to some extent. In the upper and lower extension zones of deciduous broad-leaved forests, the EX values for the vertical distribution height of mixed coniferous and broad-leaved forests differ significantly from those of deciduous broad-leaved forests (the difference is 22.82–39.15 m), yet closely resemble those of temperate coniferous forests (the difference is 4.79–7.94 m). This suggests a trend wherein deciduous broad-leaved tree species exhibit a proclivity to encroach upon coniferous forest habitats. The elevation cloud model of vertical vegetation zones provides a novel perspective and method for the detailed analysis of Mount Taishan’s vegetation vertical differentiation.

The Changes in Soil Microbial Communities and Assembly Processes along Vegetation Succession in a Subtropical Forest

Soil microbes are the primary drivers of the material cycling of the forest ecosystem, and understanding how microbial structure and composition change across succession assists in clarifying the mechanisms behind succession dynamics. However, the response of soil microbial communities and assembly processes to succession is poorly understood in subtropical forests. Thus, through the “space instead of time” and high throughput sequencing method, the dynamics of the soil bacterial and fungal communities and assembly process along the succession were studied, where five succession stages, including Abandoned lands (AL), Deciduous broad-leaved forests (DB), Coniferous forests (CF), Coniferous broad-leaved mixed forests (CB), and Evergreen broad-leaved forests (EB), were selected in a subtropical forest on the western slope of Wuyi Mountain, southern China. The results demonstrated that succession significantly decreased soil bacterial α-diversity but had little effect on fungal α-diversity. The composition of soil bacterial and fungal communities shifted along with the succession stages. LEfSe analysis showed the transition from initial succession microbial communities dominated by Firmicutes, Bacteroidota, Ascomycota, and Chytridiomycota to terminal succession communities dominated by Actinobacteriota and Basidiomycota. Distance-based redundancy analysis (db-RDA) revealed that soil total organic carbon (TOC) was the main factor explaining variability in the structure of soil bacterial communities, and multiple soil environmental factors such as the TOC, soil total nitrogen (TN), C:N ratio, and pH co-regulated the structure of fungi. The null models illustrated that deterministic processes were dominant in the soil bacterial communities, while the stochastic processes contributed significantly to the soil fungal communities during succession. Collectively, our results suggest that different patterns are displayed by the soil bacterial and fungal communities during the succession. These findings enhance our comprehension of the processes that drive the formation and maintenance of soil microbial diversity throughout forest succession.

Species and Structural Diversity of Coniferous-Broadleaved Mixed Forests of the Pshekha River, North-Western Caucasus

The article presents the species and structural diversity of coniferous-broadleaved forests of the Pshekha river – the largest tributary of the Kuban river. All in all, 7 main types of forest were identified and described: fir-beech fern-forb forest, fir-hornbeam blackberry-forb forest, aspen-hornbeam honeysuckle-small-herb forest, hornbeam-black alder nitrophilic-tall-herb forest, hornbeam-oak rhododendron-blackberry forest, hornbeam-beech blackberry-forb forest and hornbeam honeysuckle-blackberry forest. The composition of the forest flora of the Pshekha river includes 270 species, including 221 species of vascular plants and 49 species of mosses. Floristic diversity of coniferous-broadleaved forests of the Pshekha river is inversely related to the crown density of the stand and the proportion of oriental beech (Fagus orientalis). The highest species saturation was noted in the hornbeam-black alder nitrophilic-high-grass forest type, the lowest – in the fir-beech fern-forb type. Ecological and coenotic structure of coniferous-broadleaved forest types of the Pshekha river depends on the height above sea level, which determines the indicators of the average annual precipitation and average annual temperature – with a decrease in altitude above sea level. m. the proportion of boreal species in the composition of the flora decreases, while the proportion of nemoral and meadow-edge species increases. In the coniferous-broadleaved forests of the river. Pshekha, 11 species of earthworms were identified, belonging to four morpho-ecological groups: epigeic, epi-endogeic and endogeic, as well as anecic. In forests with a high quality of litter (hornbeam-dominated), the greatest contribution to the biomass is made by epigeic (up to 41%) and endogeic (up to 45%) groups of earthworms. In forests with low quality litter (fir- and beech-dominated), the share of endogeic earthworms is high (up to 66%). Anecic worms are mostly confined to forests on moist soils. In all types of forests, Crimean-Caucasian endemics make a large contribution to biomass and abundance: polymorphic species D. schmidti, anecic D. mariupolienis, as well as Mediterranean species: litter D. attemsi (often inhabiting oak and hornbeam deadwood) and proper soil A. jassyensis. Cosmopolitan species (D. r. tenuis, D. octaedra) are numerous among the epigeic worms and often inhabit deadwood of coniferous tree species.

Future Reductions in Suitable Habitat for Key Tree Species Result in Declining Boreal Forest Aboveground Biomass Carbon in China

China’s forest ecosystem plays a crucial role in carbon sequestration, serving as a cornerstone in China’s journey toward achieving carbon neutrality by 2060. Yet, previous research primarily emphasized climate change’s influence on forest carbon sequestration, neglecting tree species’ suitable area changes. This study combinates the Lund–Potsdam–Jena model (LPJ) and the maximum entropy model (MaxENT) to reveal the coupling impacts of climate and tree species’ suitable area changes on forest aboveground biomass carbon (ABC) in China. Key findings include the following: (1) China’s forests are distributed unevenly, with the northeastern (temperate coniferous broad-leaved mixed forest, TCBMF), southwestern, and southeastern regions (subtropical evergreen broad-leaved forest, SEBF) as primary hubs. Notably, forest ABC rates in TCBMF exhibited a worrisome decline, whereas those in SEBF showed an increasing trend from 1993 to 2012 based on satellite observation and LPJ simulation. (2) Under different future scenarios, the forest ABC in TCBMF is projected to decline steadily from 2015 to 2060, with the SSP5-8.5 scenario recording the greatest decline (−4.6 Mg/ha/10a). Conversely, the forest ABC in SEBF is expected to increase under all scenarios (2015–2060), peaking at 1.3 Mg/ha/10a in SSP5-8.5. (3) Changes in forest ABC are highly attributed to climate and changes in tree species’ highly suitable area. By 2060, the suitable area for Larix gmelinii in TCBMF will significantly reduce to a peak of 65.71 × 104 km2 under SSP5-8.5, while Schima superba Gardner & Champ and Camphora officinarum in SEBF will expand to peaks of 94.07 × 104 km2 and 104.22 × 104 km2, respectively. The geographic detector’s results indicated that the climate and tree species’ suitable area changes showed bi-variate and nonlinear enhanced effects on forest ABC change. These findings would offer effective strategies for achieving carbon neutrality.

Assessment and Mechanism Analysis of Forest Protection against Rockfall in a Large Rock Avalanche Area

Trees in forests can obstruct falling rocks and serve as a natural barrier to reduce the velocity of falling rocks. Recently, there has been growing interest in utilizing forests to safeguard against potential rockfall. Nevertheless, there is a dearth of research regarding the impact of rock size and forest structure on forest preservation against rockfall. This study takes the Jiweishan rock avalanche that occurred in China in June 2009 as an example to discuss the protection mechanism of forests against rockfall in rock avalanche disasters. Three sizes of rockfalls from the Jiweishan rock avalanche were simulated and analyzed with and without forests using Rockyfor3D software. The findings indicate that forests can mitigate the energy impact of falling rocks. Especially in the debris flow area of rock avalanches, the protective effect of trees on small-sized falling rocks is most obvious, reducing the runout distance and damage range of the debris flow. Moreover, the protective effect of forest structures on rockfall risk was explored. It was found that broad-leaved forests had the best protection against falling rocks, followed by coniferous broad-leaved mixed forests, and coniferous forests had the worst protective effect. Furthermore, increasing forest planting density and tree diameter at breast height (DBH) can result in better protection against rockfall. Thus, rational planning of forest species and planting density in areas of rockfall can effectively reduce the threat of rockfall risk. The research ideas in this study can provide a basis for evaluating the mitigation of rockfall hazards by forests and provide a reference for constructing and planning protective forests in rockfall and rock avalanche hazard areas.

A dataset of soil water and heat dynamics from Pinus massoniana plantations under close-to-nature management in South Subtropics (2016–2021)

This study was conducted at the Tropical Forestry Experimental Center of the Chinese Academy of Forestry in Youyiguan Pingxiang Chongzuo Forest Ecosystem Observation and Research Station of Guangxi. Based on the automatic meteorological observation station, we monitored and analyzed the soil hydrothermal dynamics in Pinus massoniana plantations under close-to-nature management. The sample plots layout, index monitoring, and data quality control were carried out in accordance with relevant specifications. This dataset contains the data of soil temperature, soil volume water content, soil heat flux, as well as air temperature and air humidity in Pinus massoniana plantations of close-to-nature management in South Subtropics from 2016 to 2021. After standard data processing, including outlier elimination and data interpolation, we statistically derived the daily data of soil water and heat dynamics of Pinus massoniana, and explained the construction of the dataset. The establishment and sharing of this dataset are valuable for facilitating a comprehensive understanding of the characteristics of soil water and heat in Pinus massoniana plantations under close-to-nature management in South Subtropics. Furthermore, the dataset can serve as an important resource for in-depth research on the response of mixed coniferous broad-leaved forest to global climate change. It can provide essential to support the sustainable management and conservation of forest resources in South Subtropics.

Developing machine learning models with multiple environmental data to predict stand biomass in natural coniferous-broad leaved mixed forests in Jilin Province of China

Forest biomass is influenced by multiple environmental factors. Multi-source data on site-specific soil, climate, and stand factors are essential for stand biomass prediction. While previous studies concerning planted forest biomass at stand level highlighted the importance of environmental factors, few have been conducted on the effects of climate and soil on stand biomass estimation, especially for natural mixed forest with complicated stand structure. Machine learning (ML) algorithms provide new tools for examining the effects, but the applications are still limited. Therefore, the objectives of this paper were to develop ML models for stand biomass estimation with stand and multiple environmental predictors, and quantify the relative importance of environmental variables. Tree above- and below-ground biomass at stand level was set as output variable with the random forest (RF) and boosted regression tree (BRT) regression methods. The data were from 286 sample plots from the National Forest Inventory (NFI) in Jilin Province, northeast China. The results showed that models with the inclusion of stand, soil, and climate variables explained > 89% of forest biomass variations. BA (stand basal area) and H (stand average height) were the most important stand variables, DD18 (degree-days above 18 °C) was the most important climate variable, and bdod (bulk density) and pH were the most important soil variables. Relative importance of climate and soil factors was 0.5% to 5.1% and 1.2% to 4.1%, respectively, which were weak but important predictors of stand biomass. In the RF model, climate variables were more important than soil variables, but the opposite in the BRT models. We concluded that above forest stand, climate and soil factors were significant input variables for regional forest biomass mapping using ML.

Effects of decreased precipitation and thinning on soil respiration in a temperate forest: A one-year field experiment in Central China

Silvicultural practices are essential for alleviating the impacts of drought on the health and structure of forest ecosystems. However, it is yet uncertain how precipitation reduction and forest management together affect soil carbon (C) cycling. Therefore, we carried out a one-year field manipulative experiment to examine the influences of decreased precipitation and thinning on soil respiration (Rs) and its heterotrophic component (Rh) in a coniferous-broadleaved mixed forest in a warm temperate-subtropical climate transition zone in Central China. We found that thinning significantly suppressed Rs by 13.9%, but decreased precipitation by 25% did not affect it, and decreased precipitation by 50% significantly decreased it by 18.6%. Thinning significantly reduced Rh by 12.2%, and decreased precipitation by 25% and 50% significantly decreased Rh by 15.9% and 23.5%, respectively. The decreasing Rh was primarily to blame for the reduction in Rs. Reduced soil moisture and microbial biomass C were the key regulators of declines in Rh and Rs caused by decreased precipitation or thinning. There was no evidence of an interactive impact between decreased precipitation and thinning on Rs or Rh. Our findings indicate that decreased precipitation and thinning may alleviate soil C release in the short term and enhance their potential benefits for soil C accumulation under future climate change scenarios.

Effects of Topography on Radial Growth of Tree Species with Different Mycorrhizal Types

In the dynamic monitoring fixed sample plot of 25 ha of coniferous broad-leaved mixed forest in the temperate zone of Northeast China, we used the data from two surveys (2013 and 2018) and microtopography data of the sample plot, and the mycorrhizal type data of tree species to explore whether the different microtopography types and single terrain factors will affect the radial growth of tree species with different mycorrhizal types on a regional scale. We studied the adaptability of tree species with different mycorrhizal types in the north end of Changbai Mountain and the south slope of Laoyeling mountain, and which provided basis for further revealing the response mechanism of tree species with different mycorrhizal types to the microtopography in this area. We found that: the tree species with different mycorrhizal types have higher radial growth rates on gentle slopes than on steep slopes. Tree species on sunny slopes have higher growth rates and survival rates than tree species of the same mycorrhizal type on shady slopes. The quantity and radial growth of AM (Arbuscular mycorrhiza) type, EcM (Ectomycorrhiza) type, and ErM (Ericoid mycorrhiza) type tree species were significantly positively correlated with different microtopography types. The quantity and radial growth of AM type tree species and EcM type tree species were significantly positively correlated with slope. The quantity of AM type tree species, EcM type tree species and the radial growth of EcM type tree species were significantly negatively correlated with slope aspect. The quantity and radial growth of ErM type tree species and radial growth of EcM type tree species the were significantly positively correlated with slope position. We believe that the reasons for these conclusions may be caused by the differences in soil temperature, humidity, and water distribution caused by different slopes.

气候变化情景下天宝岩国家级自然保护区森林景观演替长期动态模拟

PDF HTML阅读 XML下载 导出引用 引用提醒 气候变化情景下天宝岩国家级自然保护区森林景观演替长期动态模拟 DOI: 10.5846/stxb202202170376 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目(31370624);福建农林大学林学高峰学科建设项目(72202200205);福建江夏学院科研人才培育项目(JXS2020008) Long-term dynamic simulation of forest landscape succession in Tianbaoyan National Nature Reserve under climate change scenarios Author: Affiliation: Fund Project: 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:气候变化将会对森林树种结构、空间结构以及林龄结构等产生重大影响,准确预测森林景观演替对未来气候变化的响应,不仅能够为科学管理森林生态系统提供理论依据,而且对制定生物多样性保护与珍稀物种保护策略也具有重要意义。本文运用LANDIS Pro 7.0与LINKAGES模型,模拟天宝岩国家级自然保护区8个树种在2种不同气候变化情景(RCP4.5和RCP8.5)下未来300年的森林植被演替动态,分析森林景观格局变化特征及其对气候变化的响应。结果表明:毛竹、马尾松、猴头杜鹃、长苞铁杉以及杉木的潜在面积分布与景观格局指数对气候变化的响应较为显著。在气候变化情景下,各树种的景观分维度均介于1.03-1.08,保护区内各景观斑块相对简单规则。毛竹、猴头杜鹃和杉木聚集度下降趋势明显而斑块密度显著上升,长苞铁杉随演替进行面积逐渐减少而聚集度相对较高且斑块密度剧增,马尾松斑块密度缓慢增加而聚集度先降后升,随气候变化这些树种的景观完整度都遭到了不同程度的破坏,且在RCP8.5气候情景下景观破碎化更严重。而气候变化对阔叶林与柳杉的影响则较小,且阔叶林在演替期间斑块密度下降而聚集度稳中有增,潜在面积分布呈现出良好的发展势头。随气候变化,天宝岩自然保护区森林景观的演替最终将朝着"常绿阔叶林为主、针阔叶混交林为辅"的群落组成演变,保护区森林景观格局对气候变化的响应较为敏感。 Abstract:Climate change will have a significant impact on forest tree species structure, spatial structure and forest age structure. Accurately predicting the response of forest landscape succession to future climate change not only provides a theoretical basis for scientific management of forest ecosystems, but also plays an important role in formulating strategies for biodiversity conservation and rare species conservation. In this study, LANDIS Pro 7.0 and LINKAGES models were used to simulate forest landscape succession dynamics of eight tree species in Tianbaoyan National Nature Reserve under two different climate change scenarios (RCP4.5 and RCP8.5) over the next 300 years, so as to analyze the forest vegetation landscape pattern change characteristics and its response to climate change. The results showed that the potential area distribution and landscape pattern index of Phyllostachys hetericycla, Pinus massoniana, Rhododendron simiarum, Tsuga longibracteata, and Cunninghamia lanceolata had significant responses to climate change. Under the climate change scenario, the fractal dimension index of each species ranged from 1.03 to 1.08, indicating that each landscape patch in the reserve was relatively simple and regular. For Phyllostachys hetericycla, Rhododendron simiarum and Cunninghamia lanceolate, the contagion index decreased while the patch density increased significantly. For Tsuga longibracteata, the contagion index was relatively high and patch density increased with the gradual decrease of area during succession. For Pinus massoniana, patch density increased slowly while contagion index first decreased and then increased. These results indicated that landscape integrity of these species was damaged to varying degrees with climate change, and landscape fragmentation was more serious under RCP8.5 climate scenario. However, climate change had no significant effect on broad-leaved forest and Cryptomeria fortunei. And for broad-leaved forest, the patch density decreased during succession while the patch aggregation increased steadily, and the potential area distribution showed a good momentum of development. Therefore, with the change of climate, the forest landscape succession in Tianbaoyan Nature Reserve will eventually evolve towards the community composition of evergreen broad-leaved forest, supplemented by mixed coniferous broad-leaved forest. And the forest landscape pattern of the nature reserve is more sensitive to climate change. 参考文献 相似文献 引证文献

Correlations between forest soil quality and aboveground vegetation characteristics in Hunan Province, China.

As a key component of terrestrial ecosystems, soil interacts directly with aboveground vegetation. Evaluating soil quality is therefore of great significance to comprehensively explore the interaction mechanism of this association. The purpose of this study was to fully understand the characteristics of aboveground vegetation, soil quality, and their potential coupling relationship among different forest types in Hunan Province, and to provide a theoretical basis for further exploring the mechanisms underlying soil-vegetation interactions in central China. We have set up sample plots of five kinds of forests (namely broad-leaved forest, coniferous forest, coniferous broad-leaved mixed forest, bamboo forest, and shrub forest) in Hunan Province. To explore the differences of vegetation characteristics and soil physical and chemical properties among the five stand types, variance analysis, principal component analysis, and regression analysis were used. Finally, we explored the coupling relationship between soil quality and aboveground vegetation characteristics of each forest. We found that there were significant differences in soil quality among the forest types, ranked as follows: shrub forest > bamboo forest > broad-leaved forest > mixed coniferous and broad-leaved forest > coniferous forest. In general, there was a negative correlation between vegetation richness and soil quality in the broad-leaved forest and the shrub forest, but they showed a positive correlation in the coniferous forest, the mixed coniferous and broad-leaved forest, and the bamboo forest. As a necessary habitat condition for aboveground vegetation, soil directly determines the survival and prosperity of plant species. These results indicated that for vegetation-soil dynamics in a strong competitive environment, as one aspect wanes the other waxes. However, in a weak competitive environment, the adverse relationship between vegetation and soil is less pronounced and their aspects can promote.

The impact of abiotic and biotic factors on growth, mortality and net tree C stock in mountain forest ecosystems in southwest China

Mountain forest ecosystems play an important role in global carbon sequestration and may respond differently to variations in climate. The timely and accurate assessment of the factors (abiotic and biotic) that affect forest types will improve our understanding of the ecological mechanisms underlying forest carbon stock and dynamics. Here, we used linear mixed effect models to assess the impact of abiotic and biotic factors on the rate of net tree C accumulation, growth, and mortality, over nearly four decades in 1248 permanent forest plots, in different forest types along an elevational gradient on the eastern Qinghai-Tibet Plateau in China. We found that the annual rise in net tree C stock ranged from 0.13 to 0.23 Mg C ha−1 yr−1, as forest growth increased from 1979 to 2017. The highest rates of growth and mortality were in coniferous broad-leaved mixed forest (CBMF), followed by deciduous broad-leaved forests (BDF), evergreen, deciduous broad-leaved mixed forest (EDBMF), and coniferous forest (CF). Mortality increased in EDBMF and CF during the study period. The most important biotic factors were tree richness and tree density, especially in BDF and CBMF. The most important abiotic factors driving these biological responses were a significant rise in monthly mean temperature (MMT) and a decline in precipitation in the growing season. The decrease in precipitation was negatively correlated with net tree C in CBMF and CF. The increase of MMT was positively correlated with growth and mortality of each forest type, and generally more important than richness and density, and overall had a positive effect on net tree C in CBMF and CF. Overall, we suggest that tree carbon stocks will continue to increase in CBMF and CF in the coming decades due to the warming.

Climax forest has a higher soil bacterial diversity but lower soil nutrient contents than degraded forests in temperate northern China.

Bacteria are a crucial component of forest soil biodiversity and play an important role in numerous ecosystem processes. Here, we studied the patterns of soil bacterial community diversity and structure in a climax forest (Larix gmelinii; LG) compared with those in degraded forest ecosystems of four forest vegetation types (BD, Betula dahurica; BP, Betula platyphylla; QM, Quercus mongolica; and LGQM, a mixed coniferous-broadleaved forest composed of Larix gmelinii and Quercus mongolica) in the Heilongjiang Zhongyangzhan Black-billed Capercaillie Nature Reserve in northern China, using Illumina MiSeq sequencing of 16 S rRNA genes. Soil physicochemical properties (pH, soil organic carbon=SOC, total nitrogen=TN, carbon/nitrogen=C/N, total phosphorous=TP, available nitrogen=AN, available phosphorous=AP) differed significantly (p < .05) among the five forests. SOC, C/N, TP, AN, and AP were highest in QM, whereas SOC was lowest in LGQM. Soil pH was lowest in BD and highest in LGQM. α diversity was highest in LG and lowest in QM. The soil bacterial community composition in the climax forest was significantly different from that in the four degraded forests (p < .05). The dominant bacterial phyla were Acidobacteria, Proteobacteria, Verrucomicrobia, Bacteroidetes, Actinobacteria, Gemmatimonadetes, Firmicutes, Chloroflexi, and Rokubacteria. The highest relative abundances of these phyla were: 30.7% for Acidobacteria in LGQM, 42.6% for Proteobacteria in LG, 17.6% for Verrucomicrobia in BD, 5.5% for Firmicutes in BP, and 6.9% for Actinobacteria in QM. The dominant bacterial genera across the five forest vegetation types were Bryobacter and some poorly characterized taxa (e.g., Candidatus_Udaeobacter and Candidatus_Solibacter). Redundancy analysis indicated that SOC, C/N, TP, AN, and AP were the main soil physicochemical properties that shaped the bacterial communities. Our study revealed distinct bacterial diversity and composition in the climax forest compared with values in degraded forests, suggesting that the biotic and abiotic factors associated with climax ecosystems play an important role in shaping soil bacterial community structure and thus biogeochemical functions. The results of this study contribute to a deeper understanding and better predictions of the network among belowground systems and of the functions and services of degraded forests compared with climax ecosystems.

Classification of forest types in Cuigang Forest Farm based on time series data of Landsat 8

To explore the practical role of enhanced vegetation index (EVI) time series data in improving the accuracy of forest type recognition could promote the deep application of optical remote sensing data in forest resources investigation and monitoring. With Cuigang Forest Farm of Xinlin Forestry Bureau in Daxing'anling as the object, we constructed six classification schemes, using random forest algorithm with spectral feature, texture feature and EVI time series feature. The data sources were 20-view Landsat 8 OLI time series data from 2014 to 2018, 56 fixed plots data from 2017-2019, and the 2016 Class II survey data. Our aims were to realize the classification of forest types in Cuigang Forest Farm and to evaluate the accuracy of different classification schemes. The results showed the EVI values of Larix gmelinii forest, Betula platyphylla forest, coniferous-broadleaved mixed forest, coniferous mixed forest and broadleaved mixed forest were significantly different in non-growing seasons (36-111 days and 287-367 days), with the EVI value of mixed conifer forest being significantly higher, and that of mixed broadleaf forest being always lower than the other four forest types. In the early growing season (111-143 days), the EVI value of B. platyphylla forest were higher than L. gmelinii forest, which could effectively distinguish the two forests. Among the six classification schemes, spectral feature, texture feature, and EVI time series feature had the highest classification accuracy, with a Kappa of 0.82 and a classification accuracy of 86.1%. The comparison results showed that the overall accuracy of adding vegetation index time series feature was improved by 14.3% compared with that of spectral feature. The random forest algorithm with combined spectral, texture and EVI time series features could effectively classify forest stand types in Cuigang Forest Farm, with good recognition accuracy and confidence.

Altitudinal Variation Influences Soil Fungal Community Composition and Diversity in Alpine-Gorge Region on the Eastern Qinghai-Tibetan Plateau.

Soil fungi play an integral and essential role in maintaining soil ecosystem functions. The understanding of altitude variations and their drivers of soil fungal community composition and diversity remains relatively unclear. Mountains provide an open, natural platform for studying how the soil fungal community responds to climatic variability at a short altitude distance. Using the Illumina MiSeq high-throughput sequencing technique, we examined soil fungal community composition and diversity among seven vegetation types (dry valley shrub, valley-mountain ecotone broadleaved mixed forest, subalpine broadleaved mixed forest, subalpine coniferous-broadleaved mixed forest, subalpine coniferous forest, alpine shrub meadow, alpine meadow) along a 2582 m altitude gradient in the alpine–gorge region on the eastern Qinghai–Tibetan Plateau. Ascomycota (47.72%), Basidiomycota (36.58%), and Mortierellomycota (12.14%) were the top three soil fungal dominant phyla in all samples. Soil fungal community composition differed significantly among the seven vegetation types along altitude gradients. The α-diversity of soil total fungi and symbiotic fungi had a distinct hollow pattern, while saprophytic fungi and pathogenic fungi showed no obvious pattern along altitude gradients. The β-diversity of soil total fungi, symbiotic fungi, saprophytic fungi, and pathogenic fungi was derived mainly from species turnover processes and exhibited a significant altitude distance-decay pattern. Soil properties explained 31.27−34.91% of variation in soil fungal (total and trophic modes) community composition along altitude gradients, and the effects of soil nutrients on fungal community composition varied by trophic modes. Soil pH was the main factor affecting α-diversity of soil fungi along altitude gradients. The β-diversity and turnover components of soil total fungi and saprophytic fungi were affected by soil properties and geographic distance, while those of symbiotic fungi and pathogenic fungi were affected only by soil properties. This study deepens our knowledge regarding altitude variations and their drivers of soil fungal community composition and diversity, and confirms that the effects of soil properties on soil fungal community composition and diversity vary by trophic modes along altitude gradients in the alpine–gorge region.

Characteristics of Soil Mites Communities Structure under Vegetation Vertical Gradient in the Shibing World Natural Heritage Property, China

In montane environments, as elevation increases, the combination of hydrothermal factors changing and vegetation types changing can cause changes to the soil mite community. To reveal the influence of different vertical vegetation types on the structure and diversity of soil mite communities in the Shibing Karst World Natural Heritage Property, in September 2021, specimen collection and identification of soil mites were carried out under the four typical vegetation zones of coniferous broad-leaved mixed forests (CBF), evergreen broad-leaved forests (EBF), deciduous broad-leaved forests (DBF), and river beach scrubs (RBS) in the Heritage Property. This occurred in order to analyze the community structure of soil mites. A total of 10,563 soil mites were captured in this region, belonging to 3 orders, 67 families, 137 genera; Perscheloribates and Scheloribates are the dominant groups in the area. The number of soil mite genera (CBF &gt; EBF &gt; DBF &gt; RBS) and the number of individuals (RBS &gt; DBF &gt; CBF &gt; EBF) differed between vegetation types. The dominant soil mite genera were not entirely consistent, with the highest values for each soil mite community diversity parameter being in the EBF habitat. The number of soil mite genera and individuals differed among vegetation types in different soil layers. It showed an apparent aggregation towards the surface layer, with complex diversity and richness indices changes. The highest community similarity indices were found between CBF and DBF, which were moderately similar. The cluster analysis results further showed that soil mite communities differed in different vegetation zones and among the same vegetation zones. The predatory gamasid mite structure is mainly r-selective. The ecological groups of oribatid mites are all O-type in the number of groups and P-type in the number of individuals. Lasiobelba, Nanhermannia, Tectocepheus, and Mochlozetes, among others, represent the group of nutrient functions that make up the soil mites in the study area. The study shows that the soil mite community of the Shibing Karst World Natural Heritage Property is rich in groups and shows gradient differences with the vegetation spectrum, and based on the unique subtropical canyon karst habitat of the Heritage Property, the community structure of soil mites will be in the process of adaptation and dynamic change, so long-term dynamic monitoring and in-depth study of the soil mites community structure of the Heritage Property are needed.

Soil Water Use Strategies of Dominant Tree Species Based on Stable Isotopes in Subtropical Regions, Central China

Water is a crucial factor affecting plant growth and ecosystem processes. In the subtropical region, global climate change leads to frequent seasonal droughts. How plant water strategies and the adaptability of forest ecosystems change is an urgent issue to be discussed. In this study, four sample plots (P. massoniana for Plot 1, C. lanceolata for Plot 2, Q. acutissima for Plot 3, C. funebris and I. corallina for Plot 4) were selected in the Taizishan Mountain area of Hubei, China, including three forest types (coniferous forest, broad-leaved forest and coniferous broad-leaved mixed forest) and five dominant tree species. The δD and δ18O isotope compositions in plant and soil water were analysed, and the water use strategies of dominant species were predicted by using the MixSIAR model. The water absorption depth and proportion of the five species were significantly different in different seasons. In plot 4, I. corallina and C. funebris derived (58.8 ± 14.0% and 55.7 ± 23.4%, respectively) water from 10–40 cm soil in wet season, but C. funebris shifted to derive water from deep soil in dry season. This result indicates that the mixing of C. funebris and I. corallina can effectively prevent water competition in dry season with water deficit. From wet season to dry season, the depth of water utilisation of the P. massoniana, C. lanceolata, Q. acutissima and C. funebris with deep roots converted from shallow to deep soil, suggesting that the four species had significant dimorphic root systems and strong ecological plasticity.

Adopting renewable energies to meet the carbon reduction target: Is forest carbon sequestration cheaper?

In most countries, the current goal for greenhouse gas emission reduction is to achieve a 50% reduction by 2050 with a carbon neutrality target. Most energy policies have been to adopt at least 20% renewable energies in the country energy portfolio. This study conducted a comparative cost analysis on various carbon emission reduction options: reducing fossil energies (including coal, natural gas, and petroleum), increasing renewable energies (including hydroelectric power, wind power, photovoltaics, and wood fuel), and increasing afforestation (including coniferous forests, broadleaved forests, and mixed coniferous-broadleaved forests). In analyzing the discounted costs per unit of carbon reduction, this study explored the costs of these options at a fixed amount of carbon reduction, which means the lower the costs, the more effective the carbon emission reduction. Taking Taiwan as an example, the results indicated that coal-fired power has the lowest cost (US$24.80 per ton of CO2). The costs of other energy sources (i.e., natural gas, petroleum, hydroelectric power, wind power, solar power, and wood fuel) are US$79.72–182.17 per ton of CO2. The cost of afforestation for reducing carbon emissions is US$34.68–64.82 per ton of CO2, lower than the cost of adopting renewable energies assuming no technological advancement in current renewable energies.