Search Results (14)

Pyrogenic carbon (PyC) is generated from the incomplete combustion of biomass and fossil fuels. Pyrogenic carbon is highly stable and is often referred to as a missing carbon sink. It plays a crucial role in global carbon cycling and climate change research. We analyzed the storage of PyC and uncharred biological organic carbon (BOC) within woody debris (WD) and the charcoal layer, as well as the properties of PyC, across four forest types in the cold temperate coniferous forest of the Greater Khingan Mountains. Pyrogenic carbon in WD appears as charred, blackened material, while PyC in the charcoal layer was extracted through chemical oxidation using HF/HCl treatment. Our methodology included particle size separation through dry sieving, followed by the analysis of four size fractions (>2 mm, 2–1 mm, 1–0.5 mm and <0.5 mm) for elemental composition, and the chemical composition was analyzed using DRIFT. With respect to WD, PyC storage ranged from 0.040 to 0.179 Mg·ha⁻¹, whereas BOC storage ranged from 3.1 to 16.8 Mg·ha⁻¹. In the charcoal layer, PyC storage ranged from 7.9 to 44.3 Mg·ha⁻¹, and BOC storage ranged from 3.8 to 11.6 Mg·ha⁻¹. Pyrogenic carbon storage in the charcoal layer dominated (>99%) on the above-ground in each forest type. The DRIFT analysis confirmed that the coarse fraction (>2 mm) contain more polymeric aromatic structures, and most likely indicated the presence of benzene carboxylic compounds (1710 cm⁻¹), which may originate from the charred plant material. Our research aims to enhance the understanding of the retention effects of recalcitrant carbon in WD and charcoal layer of cold temperate coniferous forest, thereby providing new insights into the impact of fire disturbances on carbon cycling within forest ecosystems. Full article

Biomass combustion produces between 50 and 270 Tg of pyrogenic carbon (PyC) annually. PyC is extremely highly stable, making it a significant component of the global carbon sink. We established four plots at different slope positions within a cold temperate coniferous forest that experienced a severe fire in 2010. We mechanically divided the soil into three depths. The PyC content and density of the collected soil samples and four particle sizes were analyzed. Thirteen years after the fire, the PyC content in the soil on the upper slope was low (13.5–14.2 g·kg⁻¹). In terms of PyC density, the valley and the upper slopes presented lower values. The PyC content in the 0~10 cm layer (14.0–16.7 g·kg⁻¹) is only slightly more than 20% higher than that in the two deeper layers, whereas its density is 1.5~2 times more than that in the other layers. Our findings indicate that PyC is predominantly concentrated in coarse sand and silt particles. The spatial pattern of PyC is significantly influenced by the differentiation in topography, soil layer depth, and particle size. These distribution patterns strongly show that PyC plays a key role in forest ecosystem cycles affected by fire. PyC distribution in particle sizes particularly shows connections with specific soil components. There is a synergistic effect between the topographic redistribution (slope position differences), vertical stratification (soil depth), and particle size sorting of PyC. This determines the retention effect of stable carbon in fire-disturbed forest ecosystem soils, thereby influencing the soil carbon cycle. Full article

Leaf functional traits (LFTs) have become a popular topic in ecological research in recent years. Here, we measured eight LFTs, namely leaf area (LA), specific leaf area (SLA), leaf thickness (LT), leaf dry matter content (LDMC), leaf carbon content (LCC), leaf nitrogen content (LNC), leaf phosphorus content (LPC), and leaf potassium content (LKC), in six typical vegetation communities (sclerophyllous evergreen broad-leaved forests, temperate evergreen coniferous forests, cold-temperate evergreen coniferous forests, alpine deciduous broad-leaved shrubs, alpine meadows, and alpine scree sparse vegetation) in the Chayu River Basin, southeastern Qinghai-Tibet Plateau. Our aim was to explore their relationships with evolutionary history and environmental factors by combining the RLQ and the fourth-corner method, and the method of testing phylogenetic signal. The results showed that (i) there were significant differences in the eight LFTs among the six vegetation communities; (ii) the K values of the eight LFTs were less than 1; and (iii) except for LCC, all other LFTs were more sensitive to environmental changes. Among these traits, LA was the most affected by the environmental factors, followed by LNC. It showed that the LFTs in the study were minimally influenced by phylogenetic development but significantly by environmental changes. This study further verified the ecological adaptability of plants to changes in environmental factors and provides a scientific basis for predicting the distribution and diffusion direction of plants under global change conditions. Full article

Earthworms are essential components in temperate forest ecosystems, yet the patterns of change in earthworm-associated microbial communities across different temperate forests remain unclear. This study employed high-throughput sequencing technology to compare bacterial community composition and structure in three earthworm-associated microhabitats (skin, gut, and habitat soil) across three typical temperate forests in China, and investigated the influence of environmental factors on these differential patterns. The results indicate that: (1) From warm temperate forests to cold temperate forests, the soil pH of the habitat decreased significantly. In contrast, the physicochemical properties of earthworm skin mucus exhibited different trends compared to those of the habitat soil. (2) Alpha diversity analysis revealed a declining trend in Shannon indices across all three microhabitats. (3) Beta diversity analysis revealed that the transition from warm temperate deciduous broad-leaved forest to cold temperate coniferous forest exerted the most significant impact on the gut bacterial communities of earthworms, while its influence on the skin bacterial communities was comparatively less pronounced. (4) Actinobacteria and Proteobacteria were the predominant phyla in earthworm skin, gut, and habitat soil, but the trends in bacterial community composition differed among the three microhabitats. (5) Mantel tests revealed significant correlations between bacterial community structures and climatic factors, physicochemical properties of earthworm habitat soil, and physicochemical properties of earthworm skin mucus. The findings of this study offer novel perspectives on the interplay between earthworms, microorganisms, and the environment within forest ecosystems. Full article

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. Full article

The moisture content of fine dead surface fuel in forests is a crucial metric for assessing its combustibility and plays a pivotal role in the early warning, occurrence, and spread of forest fires. Accurate prediction of the moisture content of fine dead fuel on the forest surface is a critical challenge in forest fire management. Previous research on fine surface fuel moisture content has been mainly focused on coniferous forests in cold temperate zones, but there has been less attention given to understanding the fuel moisture dynamics in subtropical forests, which limits the development of regional forest fire warning models. Here, we consider the coupled influence of multiple meteorological, terrain, forest stand, and other characteristic factors on the fine dead fuel moisture content within the subtropical evergreen broadleaved forest region of southern China. The ability of five machine learning algorithms to predict the moisture content of fine dead fuel on the forest surface is assessed, and the key factors affecting the model accuracy are identified. Results show that when a single meteorological factor is used as a forecasting model, its forecasting accuracy is less than that of the combined model with multiple characteristic factors. However, the prediction accuracy of the model is improved after the addition of forest stand factors and terrain factors. The model prediction ability is the best for the combination of all feature factors including meteorology, forest stand, and terrain. The overall prediction accuracy of the model is ordered as follows: random forest > extreme gradient boosting > support vector machine > stepwise linear regression > k-nearest neighbor. Canopy density in forest stand factors, slope position and altitude in terrain factors, and average relative air humidity and light intensity in the previous 15 days are the key meteorological factors affecting the prediction accuracy of fuel moisture content. Our results provide scientific guidance and support for understanding the variability of forest surface fuel moisture content and improved regional forest fire warnings. Full article

Forest ecosystems in the mid-latitudes of the Northern Hemisphere are significantly affected by frequent extreme weather events. How different forest ecosystems respond to these changes is a major challenge. This study aims to assess differences in the response of daily net ecosystem exchange (NEE) of CO₂ and latent heat flux (LE) between different boreal and temperate ecosystems and the atmosphere to extreme weather events (e.g., anomalous temperature and precipitation). In order to achieve the main objective of our study, we used available reanalysis data and existing information on turbulent atmospheric fluxes and meteorological parameters from the global and regional FLUXNET databases. The analysis of NEE and LE responses to high/low temperature and precipitation revealed a large diversity of flux responses in temperate and boreal forests, mainly related to forest type, geographic location, regional climate conditions, and plant species composition. During the warm and cold seasons, the extremely high temperatures usually lead to increased CO₂ release in all forest types, with the largest response in coniferous forests. The decreasing air temperatures that occur during the warm season mostly lead to higher CO₂ uptake, indicating more favorable conditions for photosynthesis at relatively low summer temperatures. The extremely low temperatures in the cold season are not accompanied by significant NEE anomalies. The response of LE to temperature variations does not change significantly throughout the year, with higher temperatures leading to LE increases and lower temperatures leading to LE reductions. The immediate response to heavy precipitation is an increase in CO₂ release and a decrease in evaporation. The cumulative effect of heavy precipitations is opposite to the immediate effect in the warm season and results in increased CO₂ uptake due to intensified photosynthesis in living plants under sufficient soil moisture conditions. Full article

The change in habitat pattern is one of the key factors affecting the survival of the moose population. The study of the habitat landscape pattern is the key to protecting the Chinese cold-temperate forest moose population and monitoring the global distribution of moose. Through the ecological risk assessment of the moose habitat landscape pattern in a cold-temperate forest, we hope to assess the strength of habitat resistance under stress factors. This study provides a theoretical basis for the protection of the moose population in the cold-temperate forest in China and the establishment of the cold-temperate forest national park. In the study, the MaxEnt model, landscape index calculation and ecological risk assessment model construction were used to analyze the field survey and infrared camera monitoring data from April 2014 to January 2023. The habitat suitability layer of the moose population in the Nanwenghe National Nature Reserve of the Great Khingan Mountains was calculated, and the range of the moose habitat was divided based on the logical threshold of the model. The landscape pattern index of the moose habitat was calculated by Fragstats software and a landscape ecological risk assessment model was established to analyze the landscape pattern and ecological risk dynamic changes of the moose habitat in 2015 and 2020. The results showed that under the premise of global warming, the habitat landscape contagion index decreased by 4.53 and the split index increased by 4.86 from 2015 to 2020. In terms of ecological risk: the area of low ecological risk areas increased by 0.88%; the area of medium ecological risk areas decreased by 1.11%; and the area of high ecological risk areas increased by 0.23%. The fragmentation risk of the landscape pattern of the moose habitat tends to increase, the preferred patch type is dispersed, the degree of aggregation is low, and the risk of patch type transformation increases. The middle and high ecological risk areas are mainly concentrated in the river area and its nearby forests, showing a fine and scattered distribution. Under the interference of global warming and human activities, the fragmentation trend of the moose habitat in the study area is increasing, and the habitat quality is declining, which is likely to cause moose population migration. For this reason, the author believes that the whole cold temperate forest is likely to face the risk of increasing the transformation trend of dominant patch types in the cold-temperate coniferous forest region mainly caused by global warming, resulting in an increase in the risk of habitat fragmentation. While the distribution range of moose is reduced, it has a significant impact on the diversity and ecological integrity of the whole cold-temperate forest ecosystem. This study provides theoretical references for further research on the impact of climate warming on global species distribution and related studies. It is also helpful for humans to strengthen their protection awareness of forest and river areas and formulate reasonable protection and sustainable development planning of cold-temperate forests. Finally, it provides theoretical references for effective monitoring and protection of cold-temperate forests and moose population dynamics. Full article

Temporal niche partitioning is an important strategy for sympatric species or populations when utilizing limited resources while minimizing competition. Different resource availability across seasons may also influence the intensity of competition, resulting in a varied temporal niche partitioning pattern between species. These competitive interactions are important drivers for the formation of biodiversity patterns and species coexistence on the eastern Qinghai-Tibet Plateau. To clarify these interspecies relationships among sympatric species, we carried out a camera trap survey from 2017 to 2020. We deployed 60 camera traps in the temperate coniferous forests of the eastern Qinghai-Tibet Plateau. We analyzed the daily activity patterns of birds and mammals to reveal the temporal niches and seasonal relationships among the species-specific activity rhythms. The results are summarized as follows: (1) Eight major species, including mammals and birds, have different temporal peak activity rhythms to reduce intense competition for resources. (2) The activity rhythm of a species varies seasonally, and the competition among species is more intense in the warm season than in the cold season. (3) Among 15 pairs of competitor species, seven pairs had significantly different coefficients, with higher winter values than summer values, perhaps due to the abundance of resources in summer and the scarcity of resources in winter causing intensified competition. Among the predators and prey, the summertime coefficients were higher than those in winter, perhaps due to the need to replenish energy during the summer breeding season. The main purpose of animals in winter is to survive the harsh environment. Our results provide important information on temporal and interspecies relationships and contribute to a better understanding of species-coexistence mechanisms. Full article

Pinewood nematode (Bursaphelenchus xylophilus) is a highly destructive invasive species, causing extensive economic and ecological losses across Eurasia. It has recently invaded mid-temperate zone of northern China, threating large areas of coniferous forests. Herein, we evaluated the physiological and molecular basis of cold tolerance in pinewood nematode isolates from different temperature zones of China. After exposure to −5 °C and −10 °C, the survival rates of five pinewood nematode isolates from different temperature zones were 93.94%–94.77% and 43.26%–45.58% after 8 h, and 93.04%–94.85% and 9.93%–10.56% after 24 h, without significant differences among isolates. In a comparison of an isolate from a mid-temperate zone and an isolate from a subtropical zone under gradient cooling, the survival rates remained steady at nearly 95% when minimum temperature ranged from −5 °C to −15 °C, with no significant difference between isolates. In addition, phylogenetic and population structure analyses based on whole genome resequencing data suggested that isolates from mid-temperate and warm temperate zones are clustered with different isolates from subtropical zone, with no obvious geographic pattern. We did not detect significant variation in cold tolerance ability and selected gene among pinewood nematode isolates from different temperature zones. The recently invaded pinewood nematodes in the mid-temperate zone of northern China may spread by multiple invasion events from southern China, without adaptive revolution. Our research implies that it is important to reinforce quarantine inspection to control the rapid spread of pinewood nematode. Full article

Yunnan has a complicated geological history, a particular geography, and a complex topography, which have influenced the formation of various habitats of high biodiversity: 245 families; 2140 genera; 13,253 species and varieties of seed plants; more than 12 types of vegetation; and 167 plant formations, including tropical rain forests, tropical dry forests, subtropical evergreen broad-leaved forest, cold temperate coniferous forests, and alpine bushes and meadows. An analysis of the geographic elements to the current Yunnan flora shows that the tropical distribution contributed to 51% of all families and to 57.5% of all genera, of which the genera from the tropical Asian distribution make up the highest proportion among all geographical elements. During the late evolution of Yunnan, its flora was strongly affected by the tropical Asian flora. The complicated patterns and diversity in Yunnan flora and vegetation have been shaped mainly by its particular geological histories, which include the differential uplifts in topography, the clock-wise rotation of the Simao-Lanping geoblock, and the extrusion of the Indochina geoblock by the Himalayan uplift. The flora and vegetation of Yunnan were possibly derived from tropical-subtropical Tertiary flora before later diverging. Northwestern Yunnan flora likely evolved due to rapid speciation from families and genera from cosmopolitan and northern temperate distributions during the uplift of the Himalayas and climatic oscillations after the late Tertiary. Southern Yunnan flora likely evolved into tropical Asian flora following the southeastward extrusion of the Indochina block, which brought along tropical Asian elements. Central Yunnan flora inherited most of the elements of the Tertiary flora from East Asia. The formation and strengthening of the southwest monsoon by the uplift of the Himalayas was also a direct factor in the formation of the tropical rain forests found in southern Yunnan. The flora from southern and southeastern Yunnan also diverged, with the former being more closely related to Indo-Malaysian flora and the latter being more closely related to Eastern Asian flora. This floristic divergence is well supported by the geological history of these regions: that is, the tropical flora of southeastern Yunnan derived from the South China geoblock, whereas the flora of southern and southwestern Yunnan mainly derived from the Shan-Thai geoblock. Full article

The southern boreal forests of North America are susceptible to large changes in composition as temperate forests or grasslands may replace them as the climate warms. A number of mechanisms for this have been shown to occur in recent years: (1) Gradual replacement of boreal trees by temperate trees through gap dynamics; (2) Sudden replacement of boreal overstory trees after gradual understory invasion by temperate tree species; (3) Trophic cascades causing delayed invasion by temperate species, followed by moderately sudden change from boreal to temperate forest; (4) Wind and/or hail storms removing large swaths of boreal forest and suddenly releasing temperate understory trees; (4) Compound disturbances: wind and fire combination; (5) Long, warm summers and increased drought stress; (6) Insect infestation due to lack of extreme winter cold; (7) Phenological disturbance, due to early springs, that has the potential to kill enormous swaths of coniferous boreal forest within a few years. Although most models project gradual change from boreal forest to temperate forest or savanna, most of these mechanisms have the capability to transform large swaths (size range tens to millions of square kilometers) of boreal forest to other vegetation types during the 21st century. Therefore, many surprises are likely to occur in the southern boreal forest over the next century, with major impacts on forest productivity, ecosystem services, and wildlife habitat. Full article

In temperate forests, climate seasonality restricts the photosynthetic activity of primary producers to the warm season from spring to autumn, while the cold season with temperatures below the freezing point represents a period of strongly reduced plant activity. Although soil microorganisms are active all-year-round, their expressions show seasonal patterns. This is especially visible on the ectomycorrhizal fungi, the most abundant guild of fungi in coniferous forests. We quantified the production of fungal mycelia using ingrowth sandbags in the organic layer of soil in temperate coniferous forest and analysed the composition of fungal communities in four consecutive seasons. We show that fungal biomass production is as low as 0.029 µg g⁻¹ of sand in December–March, while it reaches 0.122 µg g⁻¹ in June–September. The majority of fungi show distinct patterns of seasonal mycelial production, with most ectomycorrhizal fungi colonising ingrowth bags in the spring or summer, while the autumn and winter colonisation was mostly due to moulds. Our results indicate that fungal taxa differ in their seasonal patterns of mycelial production. Although fungal biomass turnover appears all-year-round, its rates are much faster in the period of plant activity than in the cold season. Full article

Soil respiration (R_s) is seldom analyzed using remotely sensed data because satellite technology has difficulty monitoring various respiratory processes in the soil. We investigated the potential of remote sensing data products to estimate R_s, including land surface temperature (LST) and spectral vegetation indices from the Moderate Resolution Imaging Spectroradiometer (MODIS), using a nine-year (2007–2015) field measurement dataset of R_s and soil temperature (T_s) at five forest sites at the eastern Loess Plateau, China. The results indicate that soil temperature is the primary factor influencing the seasonal variation of R_s at the five sites. The accuracy of the model based on the observed data is not significantly different from the model based on MODIS-derived nighttime LST values. There was a significant difference with the model based on MODIS-derived daytime LST values. Therefore, nighttime LST was the optimum LST for estimation of R_s. The normalized difference vegetation index (NDVI) consistently exhibited a stronger correlation with R_s when compared to the green edge chlorophyll index and enhanced vegetation index. Further analysis showed that adding the NDVI into the model considering only T_s or nighttime LST could significantly improve the simulation accuracy of R_s. The models depending on nighttime LST and NDVI showed comparable accuracy with the models based on the in situ T_s and NDVI. These results suggest that models based entirely on remote sensing data from MODIS have the potential to estimate R_s at the cold temperate coniferous forest sites. The performance of the model in other vegetation types or regions has also been proved. Our conclusions further confirmed that it is feasible for large-scale estimates of R_s by means of MODIS data in temperate coniferous forest ecosystems. Full article