Aim: The interactions between herbivorous insects and woody plants have attracted wide attention due to their critical roles in ecosystems. So far, an increasing number of studies have investigated the distribution patterns of leaf herbivory intensity across the forest and the underlying factors influencing it. Consequently, numerous hypotheses have been proposed in the context. However, these hypotheses may not be universally applicable across different forest communities. In particular, systematic validation in mid-subtropical evergreen broad-leaved forests remains limited. Moreover, current research has predominantly focused on a limited number of species, and the extent to which these findings can be generalized to the entire forest community requires further investigation and verification. 

Methods: In this study, we investigated 400 individuals from 149 broad-leaved tree species in a 25-ha subtropical forest dynamics plot at Baishanzu (Baishanzu plot), Zhejiang Province. First, interspecific differences in leaf herbivory intensity (herbivory rate and frequency) were compared among tree species. And then, based on the plot data, a generalized linear mixed model was used to systematically investigate the effects of sampled tree species categories (classified by tree life form and abundance), leaf size, neighboring tree diversity and composition, and soil nutrients on herbivory rate (the proportion of leaf area consumed by herbivory), with the aim of identifying the dominant factors driving herbivory rate in the Baishanzu plot. 

Results: (1) 99.40% of herbivory in the plot was caused by chewing insects. The average herbivory rate was 7.18%, and the average herbivory frequency was 65.38%. There were significant differences in herbivory rate and frequency among different tree species. Moreover, the herbivory rate of evergreen species was significantly higher than that of deciduous species, common species were significantly higher than rare species, and tree species were significantly higher than shrub species; (2) The results of the model indicated that tree categories significantly influenced herbivory rate, and there was a significant positive correlation between herbivory rate and the phylogenetic diversity of neighboring trees. Furthermore, the results of the variance decomposition showed that tree life form (tree vs. shrub) exhibited the highest relative contribution, accounting for 62.33% of the explained variation. 

Conclusion: The findings of this study corroborated the plant-apparency hypothesis regarding insect herbivory, indicating that evergreen, common, and tree species experienced greater levels of herbivory due to their higher apparency within the community. Additionally, this study also revealed the existence of an associational susceptibility effect in the Baishanzu plot, suggesting that mixtures of phylogenetically distant trees resulted in more severe insect herbivory.

Aims: β diversity reflects the differences in species composition among communities, serving as a key indicator linking local and regional biodiversity while characterizing spatial distribution patterns of species. In this study, using data from a large forest observation network in the Xiaoxing’an Mountains, we disentangled the patterns, components, and influencing factors of forest β diversity, aiming to provide a scientific basis for biodiversity conservation in this region. 

Methods: Using the Podani partitioning method, we decomposed β diversity to assess the relative contributions of species replacement and richness difference. We further quantified the local contribution to β diversity (LCBD) and the species contribution to β diversity (SCBD) to identify ecologically unique sites and key species. In addition, regression and variance partitioning analyses were applied to evaluate the relative effects of environmental, spatial and human disturbance factors on community composition, thereby uncovering the ecological mechanisms underlying forest community assembly and biodiversity patterns. 

Results: (1) Species turnover was the dominant process driving community dissimilarity across the study area. Therefore, conservation strategies in the Xiaoxing'an area should prioritize regions with high species turnover rates. (2) The SCBD values ranged from 0.002% to 21.92%, with Betula platyphylla contributing the most and Populus suaveolens the least. Species with higher SCBD values largely overlapped with the dominant tree species in the region. To maintain forest ecosystem stability, targeted management plans should be implemented for the regeneration and harvesting of keystone species such as Betula platyphylla, Quercus mongolica, and Betula dahurica. (3) LCBD values ranged from 0.54% to 2.68%. Plots with higher species richness exhibited higher LCBD values, with southeastern sites generally having greater LCBD values than those in the northwest. Site-level conservation should be prioritized in areas with high LCBD values to preserve the diversity and stability of the Xiaoxing'an forest ecosystem. (4) Climatic factors were identified as the primary drivers of LCBD variation. The interaction between climate, spatial, topographic and human disturbance variables influence water availability and habitat heterogeneity, thereby indirectly shaping species spatial distribution patterns. 

Conclusion: Our findings reveal the spatial patterns and ecological drivers of forest β diversity in the Xiaoxing’an Mountains, highlight key regions and species essential for maintaining β diversity, and provide scientific evidence for forest ecosystem management and biodiversity conservation in this region.

Aims: Establishing biodiversity baselines is essential for advancing a national park–centered protected area system in China. This study aims to document bird and mammal diversity in the Xizang Mangkang Yunnan Snub-nosed Monkey National Nature Reserve and to examine the seasonal spatial occupancy patterns of selected representative species based on long-term camera-trap monitoring. 

Methods: From December 2021 to July 2025, a total of 122 infrared camera traps were deployed across the reserve and adjacent areas for continuous wildlife monitoring. Species richness and relative abundance were summarized for all detected birds and mammals. Based on data completeness and representativeness, five representative species, i.e., Vulpes vulpes, Capricornis milneedwardsii, Rhinopithecus bieti, Crossoptilon crossoptilon, and Ithaginis cruentus, were selected for single-season occupancy modeling to evaluate seasonal differences in spatial occupancy and altitudinal habitat use. 

Results: The survey recorded 26 mammal species (12 families, 4 orders) and 51 bird species (18 families, 8 orders). Six species were listed as National Class I Protected Wild Animals—Panthera pardus, Moschus berezovskii, Moschus chrysogaster, Rhinopithecus bieti, Tetrastes sewerzowi, and Tetraophasis szechenyii—and 20 species as National Class II Protected Wild Animals. Among mammals, the tufted deer (Elaphodus cephalophus), woolly hare (Lepus oiostolus), Chinese serow (Capricornis milneedwardsii), rhesus macaque (Macaca mulatta), and red fox (Vulpes vulpes) exhibited higher relative abundance. Among birds, Ithaginis cruentus, Crossoptilon crossoptilon, and Tetraophasis szechenyii were dominant. Occupancy probabilities differed significantly among species and seasons. Vulpes vulpes showed the highest mean annual occupancy (ψ = 0.64), followed by Capricornis milneedwardsii (ψ = 0.44), Rhinopithecus bieti (ψ = 0.43), and Crossoptilon crossoptilon (ψ = 0.43), whereas Ithaginis cruentus exhibited relatively lower occupancy (ψ = 0.41). 

Conclusions: Overall, seasonal spatial use patterns differed substantially among species, indicating strong species-specific responses. These variations were associated with multiple environmental factors, including vegetation conditions, topographic features, and water availability. This study provides a comprehensive assessment of bird and mammal diversity in the reserve and clarifies the seasonal spatial occupancy patterns of selected representative large- and medium-sized mammals and ground-dwelling birds, offering a robust scientific basis for biodiversity conservation planning and adaptive management within the reserve.

Aim: Different dimensions of biodiversity often exhibit distinct patterns and shaping mechanisms. Studying bird diversity patterns from multiple dimensions is important for a comprehensive understanding of the mechanisms that maintain and regulate communities. Sichuan Province, characterized by its complex natural environments and exceptionally high avian diversity, ranks second nationwide in terms of wild bird species richness. However, the spatial distribution patterns of bird diversity across different dimensions and their key driving factors in the region remain unclear. 

Methods: Based on survey data from 288 survey sites collected through stratified sampling in Sichuan Province from 2023 to 2024, this study calculated the taxonomic, functional, and phylogenetic diversity of breeding bird communities. We used generalized linear models to analyze the relative effects of climate, habitat, and human activities on each dimension of community diversity. 

Results: The results showed that taxonomic diversity was primarily positively influenced by habitat and climate factors, showing significant positive correlations with the proportions of forest, water body, and cropland within the plots, while exhibiting a significant negative correlation with annual precipitation. Functional diversity was jointly affected by climate and habitat factors, being positively associated with precipitation variability, Shannon index of the land-use types, and cropland proportion, and negatively associated with mean annual temperature. Phylogenetic diversity was influenced by climate, habitat, and human activities, showing a significant positive correlation with mean annual temperature, and negative correlations with forest proportion and the human footprint index. 

Conclusion: This study reveals that the taxonomic, functional, and phylogenetic diversity of breeding bird communities are driven by distinct ecological factors, with the same factor exhibiting both consistent and contrasting effects across different dimensions. Integrating taxonomic, functional, and phylogenetic perspectives provides a more comprehensive understanding of community structure and its maintenance mechanisms to provide scientific basis for regional bird diversity conservation.

Aim: Traditional bird diversity surveys have largely relied on manual observations; however, in recent years, voiceprint monitoring technology has been gradually applied, providing a new approach for studying avian diversity. Avian diversity is a key indicator for assessing the quality of wetland ecosystems. This study aims to compare AI-based voiceprint monitoring with manual transect surveys, offering a case reference for the application of bird voiceprint monitoring devices in wetland parks nationwide. 

Methods: In January (winter), April (spring), August (summer), and October (autumn) of 2024, this study conducted comprehensive and systematic bird diversity surveys at five sites within Xixi National Wetland Park in Hangzhou, Zhejiang, where manual transect surveys and voiceprint monitoring devices overlapped. The voiceprint monitoring uses a confidence threshold of 77.5% for output data. Based on Simpson dominance index (C), Shannon-Wiener diversity index (H′), Pielou evenness index (J), and Margalef richness index (M), the applicability and limitations of two methods were evaluated. 

Results: (1) Across the four seasons, voiceprint monitoring detected 105 species, while manual transect surveys recorded 89 species; voiceprint monitoring showed better performance in species richness (S). (2) In terms of residency status, voiceprint monitoring showed higher detection efficiency for migratory and passage birds, whereas manual transect surveys performed better for resident birds; moreover, voiceprint monitoring contributed new regional records. (3) The seasonal variations of the indices obtained by the two methods were not entirely consistent. (4) By region, the highest H′, J, and M values under voiceprint monitoring were observed at Lüdi/Shuixiachanglang area, whereas under manual transect surveys, the highest values were recorded at Lianhuatan area. 

Conclusion: Overall, voiceprint monitoring is suitable for long-term and wide time-scale dynamic monitoring, with broad application prospects, and can serve as a complement to manual transect surveys. An evaluation system incorporating recognition confidence and quality control thresholds is recommended to enhance the accuracy and comparability of the method.

Aims: The three-dimensional structure of vegetation is crucial for the formation and spatial distribution of soundscapes in green spaces. Biophony, a key component of soundscapes, indirectly reflects regional biodiversity and ecosystem health. However, the complex relationship between vegetation structure and biophony in urban parks is not well understood. 

Methods: During the summer of 2024, we simultaneously collected high-resolution acoustic recordings and backpack LiDAR data from 52 sites in central Beijing parks. Six acoustic indices and 42 vegetation structural variables were calculated from these datasets. We used principal component analysis (PCA) and the XGBoost-SHAP model to identify and assess the importance of key vegetation variables influencing biophony. A generalized additive model (GAM) was then used to quantify the nonlinear relationships between these variables and biophony characteristics. 

Results: Our key findings are: (1) The power spectral density (PSD) of different biophony frequency bands showed distinct diurnal patterns. PSD at 2–4 kHz and 4–6 kHz exhibited similar circadian rhythms, while the 6–10 kHz band showed a staggered vocalization pattern. (2) Mean diameter at breast height (DBH), canopy relief ratio (CRR), and rumple index (RI) were key drivers of biophony across all frequency bands. Understory structure and canopy cover (CC) were dominant factors in regulating overall soundscape indices (ACI, ADI, and BIO). (3) Forest stands with a euphotic volume over 50% and medium-sized trees were more favorable for bird vocal activity. Increased CRR and canopy surface morphology significantly enhanced biophony, particularly insect sounds. (4) Excessive understory density and a large proportion of oligophotic volume were detrimental to the coexistence and propagation of multiple sound sources, which can reduce soundscape diversity. 

Conclusions: This study systematically reveals how three-dimensional vegetation structure influences biophony, identifies key structural factors for biophony patterns, and provides a scientific basis for soundscape optimization and biodiversity conservation in urban green spaces.

Aims: Microtopography is a key driver regulating species distribution patterns and community structure at the local scale. However, existing studies have largely focused on plants and microorganisms, while soil fauna remain comparatively understudied. Collembola, as soil indicator organisms highly sensitive to environmental changes, can effectively reflect microenvironmental heterogeneity through variations in their community composition and diversity. 

Methods: This study was conducted in the western Tianshan Mountains of Xinjiang. Three representative microtopographic habitats—shady slopes, sunny slopes, and ravines—were selected for investigation. In each habitat, soil Collembola communities and associated environmental variables were systematically surveyed to evaluate the effects of microtopography on community structure and diversity, and to identify the key environmental drivers shaping these patterns. 

Results: A total of 1,548 Collembola individuals were collected, belonging to six families, twelve genera, and 19 species. Significant differences in soil temperature, total phosphorus content, and canopy cover were observed among microtopographic types. Collembola community composition also differed significantly among habitats. Although differences in diversity indices were not statistically significant, clear spatial trends were observed: diversity was highest on shady slopes, intermediate on sunny slopes, and lowest in ravines. At the genus level, distinct distribution patterns were detected: Willowsia, Entomobrya, and Homidia occurred exclusively on shady slopes, whereas Xenylla was restricted to sunny slopes. Redundancy analysis (RDA) indicated that soil temperature and ammonium nitrogen (NH₄⁺-N) were the primary factors influencing community composition. Collembola abundance was significantly negatively correlated with soil moisture, and hydrothermal conditions were closely coupled with soil nutrient availability. 

Conclusion: The study revealed that microtopography shapes heterogeneous microenvironmental conditions through the coupled effects of vegetation structure, microclimate, and soil properties, thereby driving spatial differentiation of soil Collembola communities.

Aims：To investigate the elevational patterns and driving factors of soil microbial diversity and community composition in Abies fargesii var. faxoniana forests in Shennongjia National Park, and to analyze the relationships between soil microbial communities and plant communities along the elevational gradient. 

Methods：This study was conducted in A. fargesii forests in Shennongjia National Park. Soil samples were collected along an elevational gradient. High-throughput sequencing was used to analyze the diversity and community composition of soil bacterial and fungal communities. In addition, inter-kingdom ecological networks (IDENs) were constructed to examine the characteristics of soil microbial communities and their relationships with plant communities across different elevations. 

Results：With increasing elevation, total nitrogen, soil organic carbon, and mean annual precipitation (MAP) significantly increased, whereas total phosphorus (TP), available potassium (TK), and plant alpha diversity significantly decreased (P < 0.05). Bacterial Shannon index and richness significantly declined with elevation (P < 0.05), while fungal diversity indices showed no significant change. Among dominant bacterial phyla, the relative abundance of Acidobacteriota, particularly subgroups Gp2, Gp1, and Gp3, increased significantly with elevation (P < 0.05). Dominant fungal phyla showed no significant elevational trends, but Russula increased and Inocybe decreased at the genus level (P < 0.05). Partial Mantel tests indicated that mean annual temperature (MAT) and MAP were the main drivers of microbial community variation, and canonical correspondence analysis (CCA) further showed that MAP and plant diversity significantly shaped bacterial and fungal community structures. Network modularity, connectance, and nestedness increased significantly along the elevational gradient (P < 0.05). Rhododendron przewalskii and Acer mono were the main plant components of module hubs in the plant–microbe IDEN, whereas A. fargesii occupied a central position as a network hub in the plant–fungus IDEN. 

Conclusion：Soil microbial communities in A. fargesii forests exhibit clear elevational patterns. With increasing elevation, bacterial diversity decreases significantly, whereas fungal diversity remains relatively stable. MAT, MAP, and plant diversity are important drivers shaping microbial community structure. In addition, the connectance and modularity of plant–microbe inter-kingdom ecological networks increase significantly with elevation. Plants act as network hub species and, together with key microbial taxa involved in decomposition and nutrient cycling, jointly maintain the structural and functional stability of plant–microbe interaction networks.

Aims: Soil bacterial communities serve as pivotal links sustaining plant–soil interaction processes. They play essential roles in regulating soil biogeochemical cycles, facilitating plant community succession, and driving the restoration of soil ecological functions. Currently, the compositional shifts, diversity patterns, functional succession, and underlying influence factors of soil bacterial communities during vegetation restoration in degraded high-altitude forest ecosystems remain poorly understood. 

Methods: We investigated degraded post-fire forest sites of Yulong Snow Mountain in Northwest Yunnan, China, restored with the native shrub Paeonia delavayi for 1-year (1Y), 3-year (3Y), and 6-year (6Y), as well as bare ground formed by post-fire forest undergoing natural succession. Soil physicochemical properties were characterized, and Illumina MiSeq high-throughput sequencing was employed to analyze the composition, diversity, and relationship of functional succession in soil bacterial communities in restoration years. 

Results: (1) With increasing restoration years, soil organic carbon (SOC), total nitrogen (TN), available nitrogen (AN), total phosphorus (TP), and soil moisture content (SMC) decreased significantly initially and then increased gradually. Conversely, total potassium (TK) and pH showed an initial increase followed by a decrease. Available phosphorus (AP) and available potassium (AK) in 6-year restoration sites were significantly higher than those in bare ground. (2) Shannon-Wiener, Simpson, and Pielou indices of soil bacterial communities were significantly lower in 3-year and 6-year restoration than in 1-year restoration and bare ground, though Chao1 index showed no significant differences across restoration years. β-diversity showed significant alterations across restoration years. The relative abundances of Pseudomonadota, Acidobacteriota, and Verrucomicrobiota declined markedly with restoration years, whereas Actinomycetota and Gemmatimonadota increased significantly. Chloroflexota peaked in 1-year restoration. The relative abundances of Bradyrhizobium and Mycobacterium (involved in nitrogen cycling) and Gemmatimonas (involved in phosphorus cycling) increased significantly with the restoration years, whereas the relative abundances of Reyranella and Bacillus (biocontrol-associated genera) showed a decreasing trend. (3) RDA analysis indicated that AN, AK, TK, TN, SOC, SMC, and pH significantly shaped bacterial community composition. Structural equation modeling demonstrated that: soil bacterial community diversity exhibited a significant negative correlation with restoration years, while SOC indirectly influenced the community composition by regulating total nutrient content and pH. Conversely, restoration years positively enhanced soil bacterial community composition through its indirect effects on available nutrient. 

Conclusion: A critical shift in the rhizosphere soil of Paeonia delavayi—encompassing physicochemical characteristics, bacterial diversity, abundance of dominant species, and the composition of functional groups—occurred at the 3-year mark of restoration in the degraded post-fire forest. Soil available nutrients continuously improved with restoration years, and the bacterial community composition was significantly enhanced in the later stages of vegetation restoration.

Aims: The conservation of wild animals in the Saihanwula region of Inner Mongolia is of great significance for maintaining regional biodiversity. Behavioral analysis helps enhance the scientific basis and intelligent management of biodiversity conservation, with pose estimation serving as the prerequisite and core support for behavioral analysis. 

Methods: Aiming at the problem that the accuracy of pose estimation is decreased due to illumination changes, high-speed movement of animals and complex environmental occlusion factors in wildlife monitoring, in this paper, we propose a novel wildlife pose estimation method combining attention mechanism and dynamic confidence suppression (selective coordinate-enhanced decoupling-HRNet, SCD-HRNet). Firstly, combined with the squeeze-and-excitation (SE) module, the channel-level context features were extracted by global average pooling to enhance the discrimination ability of the network for species morphological features and effectively solve the problem of feature distortion caused by illumination changes. Secondly, in order to deal with the positioning deviation caused by the high-speed movement of animals, the coordinate attention (CA) mechanism is introduced to decompose the two-dimensional coordinates into the horizontal and vertical components for sinusoidal position coding, and the bidirectional attention mechanism is used to establish the cross-direction long-range dependence relationship to improve the joint positioning accuracy under motion blur. Finally, the dynamic confidence suppression (DCS) module is proposed to establish an adaptive threshold function based on the model inference accuracy to realize the robust detection of the key points in occlusion. 

Results: This paper carries out comparative experiments to verify the performance of the model. The experimental results show that the mean average precision of the SCD-HRNet method reaches 82.61% and 69.79% on the collected and labeled wild animal dataset in Saihanwula area and the AP-10K public animal dataset, respectively, which are better than the existing methods. 

Conclusion: The proposed SCD-HRNet method significantly improves the pose estimation accuracy of wildlife images in complex ecological scenes, and provides reliable technical support for wildlife behavior analysis in ecological monitoring.

Aims: The rapid development of China's distant-water fisheries has exerted significant negative impacts on the marine ecological environment and the survival of marine mammals. Acoustic recognition of marine mammals can facilitate monitoring of their population dynamics and habitat changes, playing a crucial role in ecological monitoring, conservation, and research. To address the challenges of background noise interference and low accuracy in feature extraction and classification of marine mammal vocalizations, this paper proposes a classification method based on an improved spectral subtraction technique combined with Stacking ensemble learning. 

Methods: (1) Variational Mode Decomposition (VMD) is utilized to decompose noisy audio signals into multiple frequency bands. Noise-dominant modes are identified using the Pearson correlation coefficient and are subsequently suppressed through targeted spectral subtraction. (2) For feature extraction, a fusion strategy is employed that combines time-domain and frequency-domain statistical features with deep representations extracted from Mel spectrograms via a convolutional neural network (CNN). To enhance class separability and reduce dimensionality, Linear Discriminant Analysis (LDA) is applied, producing a compact and discriminative feature set. (3) In the classification phase, a Stacking ensemble model is built by integrating five base learners—SVM, KNN, XGBoost, MLP, and GNB—whose predictions are aggregated using LightGBM as the meta-learner. 

Results: Experimental results demonstrate that the proposed method significantly enhances classification performance in low-frequency marine mammal sound recognition. The improved spectral subtraction effectively reduces background noise while preserving critical acoustic features. The fusion of Mel-spectrogram deep features with statistical features, followed by LDA dimensionality reduction, produces highly discriminative feature vectors. The Stacking ensemble model, integrating five diverse base learners with LightGBM as the meta-learner, achieves a classification accuracy of 94.78%, surpassing the best-performing individual model by 5.12% and the worst-performing by 9.89%. Additionally, the model exhibits robust performance across imbalanced classes, maintaining high precision and recall even for underrepresented species. 

Conclusion: This study presents an effective framework for low-frequency marine mammal acoustic classification under complex oceanic noise conditions. By integrating VMD-based spectral subtraction for noise suppression, multi-domain feature extraction, and a Stacking ensemble model, the proposed method achieves superior classification accuracy and generalization ability. The results validate that combining domain knowledge in signal processing with ensemble learning strategies can significantly improve the robustness and precision of marine bioacoustic monitoring systems. This approach holds promise for real-time ecological surveillance and conservation applications in noisy marine environments.

Aims: In recent years, molecular phylogenetic studies have prompted some changes in the names and taxonomic status of genera and species of Poaceae in China. Concurrently, the digitization of specimen information has provided vast amounts of species distribution data. Therefore, it is necessary to consolidate these changes to update the checklist of Poaceae in China and to investigate the diversity composition and distribution patterns of Chinese Poaceae from multiple perspectives. 

Methods: Based on data collected from references such as Flora of China and the Catalogue of Life China: 2025 Annual Checklist, as well as online databases including the Tropicos, and combined with species distribution records obtained from the Chinese Virtual Herbarium (CVH), the Global Biodiversity Information Facility (GBIF), and field investigations, we update the checklist of Poaceae in China and provide a statistical analysis of its composition and distribution. 

Results: The statistical results indicate that there were 2,304 species of Poaceae in China, belonging to 283 genera, 37 tribes, and 10 subfamilies. Among these, native species accounted for 1,978, which belonging to 232 genera, 34 tribes, and 10 subfamilies (including 12 endemic genera and 1,028 endemic species). With this native species richness, Poaceae ranked as the second largest family of seed plants in China, following Asteraceae. The alien flora consisted of 326 species from 109 genera, 20 tribes, and 8 subfamilies; cultivated plants constituted the majority (69%). Among the native species, the subfamilies Pooideae (746 species, 74 genera) and Bambusoideae (712 species, 46 genera) were the two most species-rich. At the genus level, Bambusa (99 species) and Elymus (96 species) were the two largest genera in terms of species number. The centers of generic and species diversity for native Poaceae were located in Southwestern and Southern China, which harbor 92% of genera and 76% of species nationwide. Regarding conservation status, there were 29 national key protected wild species (from 21 genera), 54 threatened species (from 31 genera), and 16 provincial protected species (from 15 genera). The top 15 herbaria collectively house 73% of all Poaceae specimens in China, and most of these herbaria were affiliated with institutes of the Chinese Academy of Sciences. Furthermore, specimen collections were concentrated in large genera and widely distributed species, while collections of oligotypic genera and narrow-range endemic species remained relatively insufficient. 

Conclusion: This study updates the checklist of Poaceae species in China, analyzes the characteristics of their diversity, and summarizes the status of specimen preservation and collection. It can serve as a scientific basis for taxonomic and phylogenetic research, biodiversity conservation, and sustainable utilization of Poaceae resources.

Guizhou Province is located in the hinterland of southwestern China and the eastern part of the Yunnan-Guizhou Plateau, with a unique ecological position and rich biodiversity. Its vascular plant species diversity ranks fourth in China. Based on the Flora of Guizhou, related literature, and specialized surveys, this study systematically compiled data on the diversity of vascular plants in Guizhou, covering information such as species names, distribution, and conservation status. Statistics were conducted according to administrative divisions and natural geographic regions, including the four major mountain ranges and eight major river systems of the province. As of April 30, 2025, a total of 11,686 species and infraspecific taxa (including 9,921 species and 1,765 infraspecific taxa) of vascular plants have been recorded in the province, belonging to 386 families and 2,396 genera. Among these, there are 10,967 species of wild vascular plants in 373 families and 2,185 genera, 548 endemic vascular plant species in Guizhou, 781 karst-obligate plant species, 719 commonly introduced and cultivated plant species in 115 families and 402 genera, and 202 invasive vascular plant species. The dataset also records 256 nationally key protected wild vascular plant species and 55 provincially key protected wild vascular plant species in Guizhou. In terms of spatial distribution, Qiannan Buyi and Miao Autonomous Prefecture (6,790 species) and Libo County (3,981 species) have the highest species richness among prefecture-level and county-level units, respectively. The Miaoling Mountains (6,340 species) and the Wujiang River System (8,732 species) are the regions with the highest species diversity among mountain ranges and river systems, respectively. These results provide important data for understanding the characteristics of vascular plant diversity in Guizhou and for their conservation and utilization. They also offer the latest data support for the compilation of specialized works such as the Flora of Guizhou (second edition) and the Dendrology of Guizhou.

Arthropods play crucial ecological roles in forest ecosystems, including pollination, decomposition, and regulation of community structure. They are a key biological group supporting ecosystem stability and productivity. However, compared with plants and vertebrates, the systematic accumulation of arthropod diversity datasets remains limited, and baseline information at regional scales is particularly scarce. Here, we conducted a comprehensive survey in the typical forest ecosystems of the Xinglong Mountains National Nature Reserve during July–August of 2023 and 2024. Across 27 sampling plots, we collected 20,564 arthropod specimens using three complementary methods: beating sheet, Malaise trap, and pitfall trap. Based on DNA sequencing complemented with morphospecies sorting, a total of 1,060 arthropod species were identified, including 882 insect species in 14 orders, 146 families, and 551 genera, 164 species of arachnid species in 3 orders, 21 families, and 68 genera, and 14 species from other arthropod classes in 4 orders, 5 families, and 8 genera. This dataset systematically compiles a checklist of arthropod species, specimen images, and associated DNA barcodes, providing valuable support for rapid species identification, functional trait measurement, detection of cryptic species, biodiversity conservation, and ecological research.

Background & Aim: Enchytraeidae is the second most species abundant family in the Annelida Clitellata. Recognized as micro-ecosystem engineers, soil enchytraeids play crucial regulatory roles in improving soil structure and aggregate stability, enhancing soil porosity, air permeability and water infiltration through their burrowing, ingesting and mixing mineral soil particles. In addition, as key decomposers of soil organic matter, soft-bodied enchytraeids are vital drivers of nutrient cycling and forming intimate interactions with soil microorganisms, plant roots, and other soil fauna, which make them inevitably involved in the complex soil food webs. 

Review Results: In this review, the recent advances of ecological studies of soil enchytraeids were systematically summarized, especially focusing on their trophic ecology and ecological functions. In the field of trophic ecology, the most important advances including: (1) clearly clarifying the diverse food sources of the soil enchytraeids; (2) unveiling the biological mechanisms underlying the absorption and transformation of nutritional materials their guts; and (3) preliminary figuring out their trophic niches. Regarding the ecological functions of soil enchytraeids, the key findings involving: (1) clearly demonstrating the engineering roles of enchytraeids in improving the soil structures; ( 2) preliminary recognizing their important dual roles in soil carbon (i.e. enhancing organic carbon mineralization, controlling labile carbon releasing and sequestration by their effects on soil microbes) and nitrogen dynamics (i.e. increasing soil organic nitrogen mineralization, controlling inorganic nitrogen releasing and transporting); and (3) basically understanding the multiple interactions of enchytraeids with soil microorganisms, other soil fauna, and plant roots. 

Prospects: Although having the abovementioned key progresses in recent years, the ecological studies of the soil enchytraeids are largely overlooked in the fundamental and applied fields. To further understating the ecological functions and potential ecosystem services of the soil enchytraeids, and using the soil enchytraeids to serve the practices and sustainable development, the interdisciplinary perspectives are needed in the future studies of enchytraeids regarding their trophic ecology and multifunctionality.

Background & Aim: Soil microbes inhabiting plant rhizospheres, known as the "second genome" of plants, play a pivotal role in shaping interspecific interactions, maintaining biodiversity, ecosystem functions and sustainable agriculture. Owing to the rapid development of molecular techniques such as high-throughput DNA sequencing, plant-rhizosphere microbe interactions have become a hot topic in ecology and have yielded substantial achievements in the past three decades. These achievements profoundly advanced our understandings of alien species invasion and biodiversity maintenance, and provided new avenues to improve agricultural productivity and crop quality. However, current research on plant-rhizosphere microbial interactions, specifically those encompassing multi-species coexistence and spatiotemporal dynamics, remains relatively scarce. 

Progresses: To improve our ability to predict how plant-rhizosphere interactions respond to insect herbivory, we synthesize current understanding on plant-rhizosphere microbe interaction mechanisms, spatiotemporal variation and the underlying environmental drivers, as well as responses of the mechanisms and their ecological effects of both entities and their interactions to insect herbivory, spanning from the individual to the community level. 

Perspectives: We outlined some key limitations in current plant-rhizosphere microbe interaction studies and proposed some future directions, aiming to promote the development of relevant studies.

Background & Aim: As a complementary market tool to address the financing gap in biodiversity conservation and support the ecological value transition, biodiversity credits are emerging as an innovative mechanism that mobilizes corporate capital and participation in conservation and restoration. Biodiversity credit markets are still at an early stage, yet they are increasingly recognized by enterprises as relevant to regulatory expectations, risk management needs, brand value and social responsibility, and long-term investment potential. This paper systematically analyzes the core elements of biodiversity credit markets, including how biodiversity net gain is quantified, how value is priced, why and how enterprises participate, and examines key issues in the development of biodiversity credit markets. 

Results: In this paper, we showed that biodiversity credits usually quantify biodiversity net gain through methodologies that aggregate multiple biodiversity indicators; their pricing is based on the direct and transaction costs of conservation and restoration actions rather than ecosystem asset valuation. Corporate participation is driven by regulatory and disclosure requirements, risk mitigation considerations, brand value and social license, and expectations of long-term returns. Participation pathways include direct credit purchases, co-development of conservation and restoration projects, product-credit bundling, and biodiversity–carbon combined instruments. However, challenges persist: concerns about credit misuse and offsetting, greenwashing risks, methodological uncertainty, monitoring and verification difficulties, insufficient market infrastructure, and gaps in regulatory systems and standardized guidelines for credit use and claims. These challenges collectively limit market confidence and hinder corporates’ effective participation. 

Suggestions & Perspectives: Based on the identified gaps, we propose a set of recommendations for the future development of China’s biodiversity credit market, including learning from the carbon market, linking accounting methods with demands, improving market infrastructure and regulatory rules, and establishing consensus on credit claims. These measures are essential for creating a high-integrity biodiversity credit framework that supports enterprise-driven biodiversity investment and financing and contributes to biodiversity conservation outcomes.

Background: Ex situ conservation is an important approach to conserving rare or endangered plants. The National Botanical Garden System Layout Plan of China proposed that more than 70% of the rare or endangered plants should be under effective ex situ conservation by 2035. However, the criteria that constitute effective ex situ conservation and the methods for its implementation remain poorly defined. This paper addresses these critical issues. 

Results: Survival and normal growth, successful reproduction, self-sustainability, and species authenticity can serve as indicators for evaluating different extents of success of ex situ conservation, which are grouped into ex situ preservation and effective ex situ conservation. This paper suggests self-sustainability, genetic distinctiveness, and genetic integrity as the standards for effective ex situ conservation. Accordingly, four recommendations are proposed for implementing effective ex situ conservation. 

Perspective: The definition, standards, and recommendations presented in this paper will help to clarify the concept of effective ex situ conservation, thereby facilitating the achievement of the goals set forth in The National Botanical Garden System Layout Plan of China.