Ailao Mountains Research Articles

Leaf trait networks shift toward high modularity during the succession of a subtropical forest, in southwest China

During the process of forest succession, coexisting plant species fulfill diverse functions by modifying the interrelationships among functional traits. Examining the interrelationships of functional traits across multiple dimensions would enable a comprehensive understanding of the plants’ adaptive strategies during forest succession. Plant trait networks (PTNs) comprehensively capture and visualize these intricate relationships among functional traits. Nonetheless, the changes in PTNs during forest secondary succession remain unclear. In this study, we measured 24 functional traits related to leaf resource acquisition, photosynthesis, hydraulics, and physical defense across tree species at three successional stages: young forest (YF), intermediate forest (IF), and old-growth forest (OF) in the Ailao Mountains, Southwest China. We established leaf trait networks (LTNs) to investigate the interrelationships among functional traits during forest succession. Our results revealed a decrease in the Edge Density decreased and an increase in the Modularity as succession advanced. In the YF stage, leaf nitrogen, photosynthetic rate, and force to punch were the hub traits; whereas, canopy exposure and leaf dry mass were highly connected traits in the IF and OF stages, respectively. The connectivity of highly connected traits was related to the plant’s life-history strategies and environmental adaptations at different successional stages. In terms of the importance of the four trait dimensions, resource acquisition and photosynthetic traits consistently demonstrated strong connectivity within LTNs throughout the succession. We concluded that co-occurring tree species adapted to the changing environmental conditions by adjusting trait modules through alternative strategies during secondary succession. Specifically, resource acquisition and trait coordination were more advantageous in the YF stage, while higher modularity offered greater opportunities for niche differentiation in the OF stage. This study provides new insights into exploring the mechanisms of forest succession through the analysis of trait correlation networks.

Drought effects on litter fraction and recovery in a subtropical forest

Litter input is a critical link between the circulation and flows of energy and matter in forest ecosystems. Drought events impact litter inputs, affecting forest ecosystems’ nutrient and energy cycles. To investigate the response of litter production to extreme drought, explore their recovery mechanism, and the difference between whole year, concurrent drought, non-drought period, rainy season, and dry season. We studied an extreme drought event in a subtropical evergreen broadleaved forest in the Ailao Mountain in 2009–2010. We used 10 years (2005–2014) of monthly litter production and climate data, including monthly average precipitation (MAP), soil water content (SWC), and monthly average temperature (MAT). The observation period was separated into pre-drought (2005–2008), during-drought (2009–2010), and post-drought (2011–2014) periods. We found that annual total litter production decreased by 12 % during the drought (p < 0. 05), similar to that in the drought period. Leaf litter production increased by 1 % during drought time, and other fraction decreased obviously. The contribution of water environmental factors to litter production was more evident after drought events. MAT, MAP, and SWC jointly affect litter input under extreme drought conditions, and the dominant factor is related to litter fraction and drought periods. Water environmental factors (MAP & SWC) contributed to litter input after drought events, while MAT mainly affected litter input during the non-drought and rainy seasons. Due to the growth and nutritional strategies of each fraction, the recovery time is branch < leaf < flower & fruit < moss < bark. The results further reveal litter production response to drought events and the importance of water factors in recovery.

Landscape and conservation genetics of western black crested gibbons (Nomascus concolor) in China.

Despite decades of field study, very little is known about the molecular ecology of gibbons, particularly as it relates to their ability to disperse across degraded and fragmentary landscapes. The critically endangered western black crested gibbon (Nomascus concolor) has been reduced to a small, fragmented population with about 1300 individuals. In the largest population genetic study of free-ranging gibbons to date, we sampled 47 of these gibbons from 13 sites in China and generated 15 polymorphic autosomal microsatellite markers. We identify three population clusters of N. concolor in Yunnan centered in 1) the Wuliang and Ailao Mountains, 2) the Yongde Daxueshan Mountains, and 3) an isolated remnant near the border with Vietnam. Within the Wuliang Mountains, we identified four subclusters, three of which are bounded by high-altitude rhododendron forest, and one that is isolated from the main population by ~2 km of degraded forest and pasture. Least-cost path analysis and isolation by resistance modeling demonstrates that the population genetic distances among gibbons in Wuliangshan National Nature Reserve are significantly correlated with geographic paths that avoid use of high-altitude rhododendron forest in favor of evergreen broadleaf forest. Although these gibbons have likely undergone reductions in heterozygosity from recent consanguineous mating, we suggest that their active avoidance of inbreeding on the population level maintains higher than expected levels of genetic diversity. This research provides new insights into how gibbons interact with heterogeneous environments and expands our understanding of their molecular ecology and conservation genetics.

FLApy: A Python package for evaluating the 3D light availability heterogeneity within forest communities

Abstract Light availability (LAv) dictates a variety of biological and ecological processes across a range of spatiotemporal scales. Quantifying the spatial pattern of LAv in three‐dimensional (3D) space can promote the understanding of microclimates that are critical to fine‐scale species distribution. However, there is still a lack of tools that are robust to evaluate spatiotemporal heterogeneity of LAv in forests. Here, we propose the Forest Light Analyzer python package (FLApy), an open‐source computational tool designed for the analysis of intra‐forest LAv variation across multiple spatial scales. FLApy is freely invoked by Python, facilitating the processing of LiDAR point cloud data into a 3D data container constructed by voxels, as well as traversal calculations related to the LAv regime by high performance synthetic hemispherical algorithm. Furthermore, FLApy incorporates 37 indicators, enabling users to expediently export and visualize LAv patterns and the evaluation of heterogeneity of LAv at two scales (voxel scale and 3D‐cluster scale) for a range of fine‐scale ecological study purposes. To validate the efficacy of the FLApy, we employed a simulated point cloud dataset that simulates forests (varying in canopy closure). Furthermore, to evaluate real world forest, we executed the standard workflow of FLApy utilizing drone‐derived data from three subtropical evergreen broad‐leaved forest dynamics plots within the Ailao Mountain Reserve. Our findings underscore that a series of indices derived from FLApy provide a robust characterization of light availability heterogeneity within diverse forest settings. Additionally, when juxtaposed with conventional monitoring techniques, the metrics offered by FLApy demonstrated better generality in our field assessments. FLApy offers ecologists a solution for rapid quantification of understory light 3D‐regimes across multiple scales, addressing the disparity between traditional manual approaches and the precision required for contemporary ecological studies. Moreover, FLApy provides robust support for the establishment and expansion of heterogeneity indices based on 3D micro‐environments, enhancing our understanding of the largely uncharted 3D structural patterns. Anticipated outcomes suggest that FLApy will enhance our knowledge concerning the intra‐forest climatic conditions into a 3D context, proving pivotal in the delineation of microhabitats and the development of detailed 3D‐scale species distribution models.

Effects of warming on the seedling adaptation and growth of Machilus gamblei in a subtropical forest

Accurate predictions of community stability feedback to climate warming depend on an advanced understanding of responses of the key species. The transition from seed germination to seedling establishment is the most vulnerable stage of plants, which determines the maintenance of plant diversity and community resistance to climate change. To elucidate how the establishment and physiological characteristics of Machilus gamblei seedlings will respond to future global warming, artificial warming experiments (infrared warming, +0.75 ℃, +1.5 ℃, +3 ℃, +4 ℃) were conducted at the Ailao Mountain National Nature Reserve in Yunnan Province, China. The responses of seedling establishment and their physiological adaptation to different warming conditions were studied, and the contents of nutrients, chlorophyll, and nonstructural carbohydrate (NSC) in the leaves were measured. The results showed that: (1) increasing the temperature by 0.75 ℃ did not affect the survival rate or physiological characteristics of the seedlings, but increasing the temperature by 4 ℃ reduced the survival rate of the seedlings; (2) As the temperature increased from 1.5 ℃ to 3 ℃, the chlorophyll production in the seedling leaves improved, thus particularly promoting the accumulation of NSC by increasing the starch content. In summary, our work suggests that the temperature increase in 1.5 ℃ and 3 ℃ might be conducive to the establishment and growth of Machilus gamblei seedlings in the two-year experimental period, but increasing the temperature by 4 ℃ would threaten their survival and development.

2010–2014年哀牢山亚热带常绿阔叶林土壤呼吸数据集

Subtropical forests, as the largest forest type in China, play an important role in regulating global climate change and maintaining atmospheric carbon balance. The carbon emitted by soil through respiration is the main contributor of atmospheric CO2 levels, so even slight changes in soil carbon pool can significantly affect the concentration of atmospheric CO2. Therefore, at present, the magnitude and dynamic change characteristics of soil carbon storage in subtropical forests are attached great importance to. Ailao Mountain in Yunan Province stands as a crucial region for the distribution of subtropical forests in China. This study used a multichannel automated chamber system to estimate soil respiration in a subtropical evergreen broad-leaved forest ecosystem of Ailao Mountain. Ailao Mountain Station for Subtropical Forest Ecosystem Studies is a national field station and a basic observation station of the Chinese Ecosystem Research Network. We gathered soil respiration data from the subtropical evergreen broad-leaved forest in Ailao Mountain from 2011 to 2014, including soil temperature 5cm (TS), soil moisture content 10cm (SWC) and soil respiration data (RS), organized at daily, monthly and annual scales. This dataset is of great significance in revealing the effects of climate change on soil ecological processes in subtropical evergreen broad-leaved forests. It can facilitate precise evaluation of soil organic carbon emissions and forest ecosystem management, and provide both empirical and theoretical basis for further research on the effects of global changes (e.g. climate warming) on soil respiration components, especially with a focus on soil organic carbon emissions.

Fossil woods of Cryptocarya (Lauraceae) from the middle Miocene of Southwest China

The structure of lauraceous fossil woods from the middle Miocene deposits of the Dajie Formation of Ninger County, Yunnan Province, China has been studied. The occurrence of wide (> 7 seriate) rays in combination with the presence of scalariform perforation plates, the oil/mucilage cells in rays, axial parenchyma and among fibers as well as some other traits allow us to attribute the fossil woods to the extant genus Cryptocarya. We describe the woods as a new species C. latiradiata R. Zhang, T. Su & A. A. Oskolski sp. nov. (Lauraceae). This is an important improvement in the fossil record of Cryptocarya showing that this genus was widely ranged across southern China in the middle Miocene. The occurrence of the fossil woods of such termophyllous genus as Cryptocarya in the Dajie Formation suggests that this middle Miocene climate in southern Yunnan was frostless. This result is consistent with other evidence for the warm environment caused by complex topographic structures in this region since the middle Miocene linked to the successive uplift of the Tibetan Plateau and the Ailao Mountains. Particularly, it suggests that the Ailao Mountains in the middle Miocene were high enough to weaken the influence of the Asian Winter Monsoon on the territory of Yunnan.

Growth-climate relationships of four tree species in the subtropical evergreen broad-leaved forests in Southwest China

Subtropical forests are an important carbon sink, yet our understanding on tree growth response to inter-annual climate variability remains limited. This study investigated the growth-climate relationships of four evergreen broad-leaved tree species (Stewartia pteropetiolata W. C. Cheng, Schima noronhae Reinw. ex Bl. Bijdr, Machilus gamblei King ex J. D. Hooker, and Machilus yunnanensis Lec) in the subtropical evergreen broad-leaved forests (EBFs) in the Ailao Mountains of Yunnan province, southwest China. We constructed tree ring-width residual chronologies for each species and correlated them with daily and monthly climate data. Ring-width chronologies of S. pteropetiolata and S. noronhae were positively correlated with precipitation, relative humidity, and self-calibrated Palmer drought index (scPDSI) during autumn of the previous year and spring-to-early summer of the current year, indicating that these two Theaceae species were sensitive to moisture availability. Tree radial growth of two Machilus species was primarily limited by excessive precipitation and dense cloud cover during the rainy season in this middle montane cloud forest. Moving correlations between climate variables and radial growth of all species were temporally unstable, with a weakening response to climate variability in recent decades. We highlight the dendroclimatic potential of evergreen broad-leaved tree species in moist subtropical forests. The findings offer a pertinent perspective, emphasizing the necessity of separately considering distinct ecological indicators for trees in order to obtain a comprehensive understanding of climate-growth responses within highly diverse subtropical forests.

Vascular epiphyte diversity and the correlation analysis with host tree characteristics: A case in a mid-mountain moist evergreen broad-leaved forest, Ailao Mountains

Vascular epiphyte diversity and the correlation analysis with host tree characteristics: A case in a mid-mountain moist evergreen broad-leaved forest, Ailao Mountains

Methods for processing and analyzing passive acoustic monitoring data: An example of song recognition in western black-crested gibbons

The extraction of species-specific calls from passive acoustic recordings is a common preliminary step in ecological analysis. But for many species, especially those occupying noisy, acoustically variable habitats, the call extraction process remains largely manual, a time-consuming, and increasingly unsustainable process. Deep neural networks have been shown to provide excellent performance in a range of acoustic classification applications. We take as an example the recognition of four songs of one of the rarest mammals in the world, the western black-crested gibbon (Nomascus concolors).The process of recognition in this paper which includes distributed BIC ambient sound segmentation based on the OpenPAI platform; DNN-based western black-crested gibbon song enhancement processing; data pre-processing, labeling samples; proposed DNN + ResNet34 + CBAM + GRU + Attention recognition model; comparing other classical neural network models.Our best model converts acoustic recordings into spectrogram images on the mel frequency scale and uses these images to train convolutional neural networks.Our proposed model proved to be very accurate in predicting the segmented western black-crested gibbon songs with an accuracy of 99.8%, and almost a few western black-crested gibbon songs were incorrectly identified when all segmented data were recognized. In the four consecutive years of the acoustic monitoring system deployed in the Ailao Mountain National Nature Reserve, the western black-crested gibbon was most active near the monitoring site from March to August each year, and least active in January and February. Based on call sound intensity analysis, we monitored a total of two different western black-crested gibbon groups (G1 and G2) during the monitoring cycle. We demonstrate that passive acoustic monitoring combined with CNN classifiers is an effective tool for the remote detection of one of the rarest and most threatened species in the world.

Liana regeneration in the treefall gaps, at the gap edges and in the forest interior of a subtropical montane moist evergreen broad-leaved forest in the Ailao Mountains, Southwestern China

Liana regeneration in the treefall gaps, at the gap edges and in the forest interior of a subtropical montane moist evergreen broad-leaved forest in the Ailao Mountains, Southwestern China

Alp-valley and elevation effects on the reference evapotranspiration and the dominant climate controls in Red River Basin, China: Insights from geographical differentiation

Complicated topography can drastically affect the geographical distribution of evaporation, runoff production, water cycle, and water security guarantee. However, whether the elevation and Alp-valley have differentiated effects on basin evaporation and handle the change with constant variables is still being determined. This manuscript calculates reference evapotranspiration (ET0) of the Red River Basin with a typical Alp-valley and elevation gradient from 1960 to 2021. Then at the scales of the whole basin, both sides of the main Alp (western of Ailao mountain (WAL) and eastern of Ailao mountain (EAL)), the mainstream valley (Yuanjiang valley (YJV)), the spatial–temporal distribution pattern of ET0 and its sensitivity of climate variables are depicted from the insights of barrier-corridor and elevation effects. The results indicate that ET0 grows at a rate of 27.77 mm per decade throughout the Red River Basin, China (RRBC), gradually declines from northwest to southeast, and increases with increasing elevation. The barrier effect of the Ailao Mountains within the RRBC alters the elevation distribution pattern of ET0 on both sides of the mountain. In contrast, the corridor effect along the YJV causes the ET0 increases with the depth of the valley. Accordingly, the aridity index increases with rising elevation resulting in drier climatic conditions in the north of the RRBC, and suffers a significant influence from Alp-valley topography resulting in wet WAL, dry EAL and drier YJV. The topography plays an impact on ET0 through the climatic control variables. Solar radiation (Rs) has the highest impact on ET0, followed in descending order by relative humidity (RH), air temperature (T) and wind speed (U). With the elevation increases, Rs and T reduce the effect on ET0, whereas RH increases its effect. Also, the barrier effect changed the dominant factors: Rs and RH control the ET0 on WAL and EAL, respectively, while the corridor effect enhances the role of T and U. Moreover, the schematic diagram of the ET0’s change with elevation gradient and Alp-valley, and its climate controls is deduced. This research can help us comprehend the spatial differentiation of ET0 in complicated topographical areas, as well as uncover its dynamic mechanisms under elevation and Alp-valley effects.

Temporal Changes in Litterfall and Nutrient Cycling from 2005-2015 in an Evergreen Broad-Leaved Forest in the Ailao Mountains, China.

The study of litter can provide an important reference for understanding patterns of forest nutrient cycling and sustainable management. Here, we measured litterfall (leaves, branches, etc.) from a wet, evergreen, broad-leaved forest in Ailao Mountains of southwestern China on a monthly basis for 11 years (2005-2015). We measured the total biomass of litter fall as well as its components, and estimated the amount of C, N, P, K, S, Ca, and Mg in the amount of litterfall. We found that: The total litter of evergreen, broadleaved forest in Ailao Mountains from 2005 to 2015 was 7.70-9.46 t/ha, and the output of litterfall differed between years. This provides a safeguard for the soil fertility and biodiversity of the area. The total amount of litterfall and its components showed obvious seasonal variation, with most showing a bimodal pattern (peak from March to May and October to November). The majority of litterfall came from leaves, and the total amount as well as its components were correlated with meteorological factors (wind speed, temperate and precipitation) as well as extreme weather events. We found that among years, the nutrient concentration was sorted as C > Ca > N > K > Mg > S > P. The nutrient concentration in the fallen litter and the amount of nutrients returned showed a decreasing trend, but the decreasing rate was slowed through time. Nutrient cycling was influenced by meteorological factors, such as temperature, precipitation, and wind speed, but the nutrient utilization efficiency is high, the circulation capacity is strong, and the turnover time is short. Our results showed that although there was nutrient loss in this evergreen, broad-leaved forest, the presence of forest litterfall can effectively curb potential ecological problems in the area.

Variation characteristics of microorganisms at different soil depths of typical forests in southwest China.

Microbial biomass and community structure play a significant role in soil carbon cycling. There is a large amount of organic carbon in the subsoil, but most studies on soil microbial community have focused on the surface soil. The changes and influencing mechanisms of microbial community in subsoil are unclear. We analyzed soil microbial biomass and community structure at different soil depths (0-20, 20-40, 40-60, 60-80, and 80-100 cm) in three typical forests in southwest China, Xishuangbanna tropical rain forest, Ailao Mountain subtropical broad-leaved forest, and Lijiang temperate coniferous forest, by using phospholipid fatty acid technology, to explore their variation characteristics and influencing factors in different forests and soil depths. The results showed that contents of soil organic carbon and total nitrogen decreased gradually, microbial biomass declined significantly. The ratio of Gram-positive bacteria to Gram-negative bacteria (G+:G-) reduced gradually, while the ratio of fungi to bacteria (F:B) increased with the increasing soil depth. Microbial community turned from G--dominated which adapted to eutrophic environment into G+-dominated which adapted to oligotrophic environment. The three forest types differed little in soil microbial biomass, but different significantly in microbial community structure. Ailao Mountain subtropical broad-leaved forest and Lijiang temperate coniferous forest had much higher F:B at 0-20 cm than Xishuangbanna tropical rain forest, while significantly higher G+:G- at 0-100 cm in Xishuangbanna tropical rain forest was observed. Results of the redundancy analysis showed that the contents of soil organic carbon and total nitrogen were the main factors determining microbial biomass, with combined explanation of 78.3%. Results of the stepwise regression analysis showed that C:N was the most important driving factor on F:B and G+:G-. The change in microbial community structure and the decrease in biomass along soil profile might strongly affect the dynamics of soil organic carbon in southwest China forests.

Ant species diversity along the vertical zones of the east slope of Ailao Mountain National Nature Reserve, Yunnan Province

Ant species diversity along the vertical zones of the east slope of Ailao Mountain National Nature Reserve, Yunnan Province

Dynamic Change Characteristics of Litter and Nutrient Return in Subtropical Evergreen Broad-Leaved Forest in Different Extreme Weather Disturbance Years in Ailao Mountain, Yunnan Province

By studying the dynamic change characteristics of litter production, composition, nutrient content, and return amount of different components in different extreme weather interference years of Ailao Mountain evergreen broad-leaved forest, the paper provides theoretical support for the post-disaster nutrient cycle, ecological recovery, and sustainable development of the subtropical mid-mountain humid evergreen broad-leaved forest. Square litter collectors were randomly set up to collect litter. After drying to a constant mass, we calculated the seasonal and annual litter volume and the contents of organic carbon (C), total nitrogen (N), total phosphorus (P), total potassium (k), total sulfur (S), total calcium (Ca), and total magnesium (Mg). Finally, the nutrient return amount is comprehensively calculated according to the litter amount and element content. We tracked dynamic changes in litter quantity, nutrient composition, and nutrient components across different years. The results showed that the amount of litter from 2005 to 2015 was 7704–8818 kg·hm−2, and the order of magnitude was: 2005 (normal year) &gt; 2015 (extreme snow and ice weather interference) &gt; 2010 (extreme drought weather interference); the composition mainly included branches, leaves, fruit (flowers), and other components (bark, moss, lichen, etc.), of which the proportion of leaves was the largest, accounting for 41.70%–61.52%; The monthly changes and total amounts in different years exhibited single or double peak changes, and the monthly litter components in different years showed significant seasonality. In this study, the nutrient content of litter was higher than that of litter branches each year. The total amount of litter and the nutrient concentration of each component are C, Ca, N, K, Mg, S, and P, from large to small. The order of nutrient return in different years was the same as that of litter, and the returns of nutrients in litter leaves were greater than that of litter branches. The ratio of nutrient returns of litter and litter branches from 2005 to 2010 was 2.03, 1.23, and 3.69, respectively. The research shows that the litter decreased correspondingly under the extreme weather disturbance, and the impact of the extreme dry weather disturbance was greater than that of the extreme ice and snow weather disturbance. However, the evergreen broad-leaved forest in the study area recovers well after being disturbed. The annual litter amount and nutrient return amount is similar to that of evergreen broad-leaved forests in the same latitude and normal years in other subtropical regions. The decomposition rate and seasonal dynamics of litter nutrients are not greatly affected by extreme weather.

Responses of aboveground litterfall respiration to unexpected snowfall events in Ailao subtropical forests in Southwest China

Soil respiration, the second largest CO2 flux in terrestrial ecosystems, involves the microbial respiration of litter from aboveground sources, belowground litter and root respiration, from rhizodeposition. In the subtropical forests of the Ailao Mountain, a chamber with automated CO2 efflux was set up with two treatments: a control treatment with litterfall to measure the total soil respiration (RT) and a litter removal treatment to measure aboveground litterfall respiration (RL). This study aimed to examine the responses of RL to unexpected heavy snowfall events and soil temperature (ST), soil moisture (SM), rainfall (RF), total litterfall (TL), litter water content (LWC), nitrate nitrogen (NO3−-N), and ammonium nitrogen (NH4+-N). The period of the study was divided into two: before the heavy snowfall event (BS) and during and after the heavy snowfall event (AS). The rate of RL was slightly decreased in AS (1.18 ± 0.03 μmol CO2 m−2 s−1) compared with that in BS (1.19 ± 0.02 μmol CO2 m−2 s−1). The relationships between RL and ST, SM, RF, and LWC, respectively, were all statistically significant (p < 0.05) in both periods. However, the relationships between RL and TL and NH4+-N, respectively, were not statistically significant for either period. The relationship between RL and NO3−-N was statistically significant for AS but not for BS. The relationship between RL and RF was statistically significant from 2011 to 2018. The temperature dependence of soil respiration was higher in BS than in AS, and the effect of litter removal was 2.55 % and 2.32 % for AS and BS respectively. The results indicate that current global terrestrial models underestimate RL trends for the feedback of global climate change in subtropical forests.

The bacterial and fungal microbiomes of ectomycorrhizal roots from stone oaks and Yunnan pines in the subtropical forests of the Ailao Mountains of Yunnan.

Ectomycorrhizal (ECM) symbioses play an important role in tree biology and forest ecology. However, little is known on the composition of bacterial and fungal communities associated to ECM roots. In the present study, we surveyed the bacterial and fungal microbiome of ECM roots from stone oaks (Lithocarpus spp.) and Yunnan pines (Pinus yunnanensis) in the subtropical forests of the Ailao Mountains (Yunnan, China). The bacterial community was dominated by species pertaining to Rhizobiales and Acidobacteriales, whereas the fungal community was mainly composed of species belonging to the Russulales and Thelephorales. While the bacterial microbiome hosted by ECM roots from stone oaks and Yunnan pines was very similar, the mycobiome of these host trees was strikingly distinct. The microbial networks for bacterial and fungal communities showed a higher complexity in Lithocarpus ECM roots compared to Pinus ECM roots, but their modularity was higher in Pinus ECM roots. Seasonality also significantly influenced the fungal diversity and their co-occurrence network complexity. Our findings thus suggest that the community structure of fungi establishing and colonizing ECM roots can be influenced by the local soil/host tree environment and seasonality. These results expand our knowledge of the ECM root microbiome and its diversity in subtropical forest ecosystems.

Ecological Drivers of the Soil Microbial Diversity and Composition in Primary Old-Growth Forest and Secondary Woodland in a Subtropical Evergreen Broad-Leaved Forest Biome in the Ailao Mountains, China.

Replacement of primary old-growth forests by secondary woodlands in threatened subtropical biomes drives important changes at the level of the overstory, understory and forest floor, but the impact on belowground microbial biodiversity is yet poorly documented. In the present study, we surveyed by metabarcoding sequencing, the diversity and composition of soil bacteria and fungi in the old-growth forest, dominated by stone oaks (Lithocarpus spp.) and in the secondary Yunnan pine woodland of an iconic site for biodiversity research, the Ailaoshan National Nature Reserve (Ailao Mountains, Yunnan province, China). We assessed the effect of forest replacement and other environmental factors, including soil horizons, soil physicochemical characteristics and seasonality (monsoon vs. dry seasons). We showed that tree composition and variation in soil properties were major drivers for both bacterial and fungal communities, with a significant influence from seasonality. Ectomycorrhizal Operational Taxonomic Units (OTUs) dominated the functional fungal guilds. Species richness and diversity of the bacterial and fungal communities were higher in the pine woodland compared to the primary Lithocarpus forest, although prominent OTUs were different. The slightly lower complexity of the microbiome in the primary forest stands likely resulted from environmental filtering under relatively stable conditions over centuries, when compared to the secondary pine woodlands. In the old-growth forest, we found a higher number of species, but that communities were homogeneously distributed, whereas in the pine woodlands, there is a slightly lower number of species present but the communities are heterogeneously distributed. The present surveys of the bacterial and fungal diversity will serve as references in future studies aiming to assess the impact of the climate change on soil microbial diversity in both old-growth forests and secondary woodlands in Ailaoshan.

Impacts of the Western Pacific and Indian Ocean Warm Pools on Wildfires in Yunnan, Southwest China: Spatial Patterns With Interannual and Intraannual Variations

AbstractThe Indo‐Pacific warm pool affects the regional climatic conditions in Southeast Asia mediated by the Western Pacific (WP) and Indian Ocean (IO) monsoons, which are recognized as critical regulators of wildfires in this region. Our study explored the spatiotemporal effects of the warm pools on wildfire records in Yunnan, Southwest China. We showed the interannual records had a negative relationship with the simultaneous WP warm pool area index. The Ailao Mountains in the central Yunnan could be a geographical barrier that blocked the influences of the WP warm pool from the east side. For the intraannual changes, the wildfire number variations had a stronger connection to the IO warm pool dynamics than the WP. Our study provided the novel evidence on the teleconnection between the Indo‐Pacific warm pool dynamics and regional environmental processes in Yunnan, also indicating this area as a part of the transitional zone between the two warm pools.