Aims: Biological resources are closely related to national economic and social development, and has key strategic value in food security, ecological security and energy security of a country. As a basic component of the ecosystem on earth, microorganisms are of great strategic significance to human’s life and the sustainable development of society. However, due to the lack of a sound system for the preservation, development and protection of strategic resources, many biological resources have been lost overseas through smuggling, entrainment and natural losses.

Method: Referring to other evaluation systems on biological resources, the assessment method to evaluate the strategic value of microbial resources was established in this study.

Results: Rare and endangered species, high economic value species, biosecurity species and strategic frontier species were chosen as the four aspects for strategic microbial resources, and a scoring system using the method of weighted assignment is established according to these aspects. The scoring system contains 7 different primary criteria with different weights, i.e., the weight of 25% for national conservation strategy, the weight of 15% for conservation status, population biology and economic value, and the weight of 10% for biosecurity, other value and strategic frontier. Based on the criteria, the strategic categories of 773 microbial species were assessed according to the criteria, of which 502 species were assessed as strategic microorganisms, including 440 species of fungi, 7 of oomycetes, 1 of microspore, 53 of bacteria and 1 of archaea. Besides, an online assessing platform (https://www. casbrc.org/assessment) was established with the function of scoring system for strategic microorganism and query for assessed species.

Conclusion: The strategic assessment method and the list of strategic microbial resources were firstly established in our country, which will provide important references for the collection, preservation, management and application of strategic microbial resources in China.

Background: Understanding how environmental filtering, biotic interactions, and neutral processes jointly shape species distributions and community structure is a central question in modern community ecology. However, traditional diversity indices, ordination analyses, and single-species distribution models (SDMs) cannot simultaneously integrate species associations, environmental gradients, functional traits, and phylogenetic relationships, thereby limiting their ability to disentangle community assembly mechanisms.

Framework: Joint species distribution models (JSDMs), particularly the hierarchical modelling of species communities (HMSC) framework, offer a unified and flexible Bayesian tool for community-level mechanistic inference. This study provides a systematic review of the statistical structure, mathematical foundations, and inferential mechanisms of HMSC, and establishes a complete analytical workflow encompassing data organization, model specification, Markov Chain Monte Carlo (MCMC) estimation, model evaluation, ecological interpretation, and predictive applications. A step-by-step tutorial, Joint Species Distribution Modelling with HMSC, accompanies the review and illustrates the practical implementation of HMSC through bryophyte community data and fully reproducible R code.

Theory: In the theoretical component, we clarify how HMSC integrates environmental gradients, species traits, phylogenetic relationships, and spatial structure within a unified hierarchical Bayesian framework to distinguish statistical signals of environmental filtering, biotic filtering, and dispersal limitation. Methodologically, we dissect the mathematical structure of latent variable models, elucidate the boundaries of ecological interpretation for residual correlations, and provide a conceptual basis for differentiating species co-occurrence signals from environmental effects and unobserved factors. We further compare HMSC with other mainstream JSDMs implementations and traditional community analytical methods, highlighting their relative advantages and ecological applicability.

Applications: On the applied side, we synthesize the rapidly expanding use of JSDMs across forest, wetland, grassland, marine, urban, and microbial ecosystems, demonstrating their value in conservation planning, invasive species risk assessment, co-occurrence network analysis, and scenario-based forecasting. With the advancement of GPU-accelerated computation, migration learning, and high-dimensional modelling frameworks, HMSC greatly improves ecological niche estimation and distribution prediction for rare species and enables community modelling for tens of thousands of taxa. Overall, JSDMs and HMSC in particular represent a methodological shift from single-species prediction toward integrative, multi-species and multi-dimensional ecological modelling. They provide an efficient, scalable, and uncertainty-aware platform that strengthens ecological theory testing, enhances understanding of community assembly mechanisms, and supports biodiversity conservation and management decisions.

Background & Aims: Species distribution models (SDMs), often synonymous with ecological niche models (ENMs), have solidified their position as indispensable tools in modern macroecology, biogeography, species invasion and conservation. Their utility in predicting a species’ potential geographic range, evaluating the impacts of climate change, and guiding targeted conservation efforts has led to a remarkable surge in their popularity and application over the last three decades. However, this rapid expansion has also exposed a significant and persistent conceptual gap: a growing disconnect between the practical application of modeling techniques and the foundational ecological theory that should guide them. A primary source of this issue is the widespread confusion surrounding the concept of the “ecological niche”. This ambiguity has led to conceptual errors, inappropriate method use, and potentially flawed ecological inferences. This paper addresses this critical gap by systematically reviewing the core niche concepts, linking them to specific modeling paradigms, diagnosing prevalent issues in current research, and offering recommendations to promote a more theoretically grounded and robust application of SDMs.

Review Results: The term “ecological niche” is not a single, unified concept. It encompasses three distinct yet complementary ideas. The Grinnellian niche defines a species’ existence based on the abiotic environmental conditions and habitat requirements that allow it to persist. As a “scenopoetic” or habitat-based framework, it is most closely aligned with standard SDMs, which statistically correlate species occurrence records with broad-scale climatic and environmental variables. The Eltonian niche, conversely, focuses on a species’ functional role within a community, emphasizing biotic interactions such as resource consumption, predation, and competition. This concept is central to community ecology and is better represented by methods like joint species distribution models (JSDMs) that account for residual correlations between species, or through explicit network analysis. The Hutchinsonian niche provides the most formal definition, conceptualizing the niche as an “n-dimensional hypervolume” encompassing all environmental and resource variables. Different modeling approaches correspond to these niche concepts. Standard correlative SDMs (e.g., MaxEnt, random forest) are primarily used to model the Grinnellian niche, generating a map of environmental suitability based on abiotic variables. To explore the Eltonian niche, JSDMs simultaneously model multiple species to infer interspecific interactions. The Hutchinsonian framework, particularly the concept of the hypervolume, is directly operationalized by analytical methods that quantify niche breadth, overlap, and centrality in multidimensional space. Mechanistic models, which use principles of physiology to predict survival and reproduction, offer a valuable complementary approach to approximate the fundamental niche. Despite these advances, the application of SDMs is fraught with common pitfalls. The most critical error is the fundamental vs. realized niche fallacy, where researchers mistakenly interpret the output of a standard SDM, which is trained on a species’ actual distribution, as a representation of its full fundamental niche. In reality, these models typically capture only a portion of the realized niche, constrained by unmeasured biotic factors and dispersal limitations. Additionally, many studies violate the core assumptions of SDMs, such as the assumption that species are in equilibrium with their environment or that sampling is unbiased. Ignoring biotic interactions and failing to account for non-equilibrium dynamics (e.g., recent invasions) further limits the accuracy and reliability of these models.

Conclusions: To advance SDM, this paper advocates for a multi-pronged approach grounded in ecological theory. First, researchers must strive for greater conceptual clarity, explicitly stating which niche concept their study addresses and interpreting results within that defined framework. Second, there is a clear need for enhanced methodological rigor and integration, encouraging the development of hybrid models that combine the strengths of different modeling paradigms, such as incorporating biotic interactions or dispersal dynamics into standard SDMs. Furthermore, adherence to best practices in data collection, model selection, and rigorous validation is paramount. The future of the field lies in transcending simple correlative methods and embracing a more integrative science that synthesizes Grinnellian, Eltonian, and Hutchinsonian perspectives. By leveraging new data streams and grounding our work in a deep understanding of ecological theory, we can ask more complex questions and provide more robust guidance for biodiversity management in an era of rapid environmental change.

Aims: Unequal sampling is a common issue in field-based community ecology. Choosing α-diversity metrics that remain robust when sample sizes vary among plots is critical for reliable biodiversity assessment. This study evaluated the performance of nine diversity indices, including five “observed” indices calculated directly from the data: (1) species richness, (2) Shannon index, (3) Simpson index, (4) Hurlbert’s rarefied richness, and (5) Fisher’s α; and four “richness-estimator” indices: (1) Chao1 index, (2) abundance-based coverage estimator (ACE), (3) the extrapolated value of iNEXT (interpolation/extrapolation), and (4) total expected species (TES).

Methods: Using simulation, the performance of each index was evaluated under a gradient of minimum-sample thresholds, and for each case the accuracy and precision of between-sites variance (linear regression R²) was recorded. The simulation built up 20 sites in which “true” species richness (S) was linearly correlated with an environmental gradient (x) with a theoretical coefficient of determination R² = 0.80. Four unequal-sampling scenarios were then generated by imposing different minimum sample sizes per site. For each scenario, linear models were fitted between every diversity index and x, recording the corresponding R².

Results: The results indicate that sample size (the number of individuals recorded at a sampling site, as well as the equivalent sampling completeness) is the primary factor determining index performance. As sample size increased, model R² of all diversity metrics significantly improved. Under extremely low sampling (minimum < 20 individuals; sampling coverage < 20 %), rarefied richness had a higher R² than other indices. When the minimum sample size reached 100 individuals, the estimator indices group outperformed the observed indices. This study further clarified the minimum sample size and the corresponding sampling completeness required for each index to recover the predetermined R².

Conclusion: Overall, rarefied richness is recommended for highly unequal, sample size-poor scenarios. In practice, rarefaction threshold should be set at a relatively high level (e.g., > 40 individuals) to enhance the overall comparability among sampling sites, even if it results in the exclusion of extremely under sampled sites. Once sampling completeness is adequate, richness estimators are preferable, as they can generate extrapolated richness that are close to the true gradient.

Background & Aims: The ancient tree biocultural micro-conservation site (ATBMS) represents an innovative conservation pathway designed to synergistically protect the biological and cultural elements of ancient trees. This paper systematically elucidates its conceptual connotation and characteristics. It clarifies its unique position and value within the global protected area system. Through a comprehensive review of the development history of natural protected areas, a comparative analysis of related models such as other effective area-based conservation measures (OECMs), plant micro-reserves, and small-scale natural conservation areas, and case studies.

Review Results: This research delineates the composite features of ATBMS, which centers on individual or small clusters of ancient trees while integrating their micro-habitats and cultural spaces. The core innovation of ATBMS lies in achieving fine-scale, synergistic conservation across both ecological and cultural dimensions. It addresses the gaps in OECMs regarding “cultural and fine-scale protection”, overcomes the “ecological-cultural divide” inherent in traditional small-scale protected areas, and complements small-scale natural conservation areas. Based on this, the study proposes differentiated conservation strategies tailored to various types of ancient trees (e.g., individual/clustered, natural/cultivated, urban/rural).

Conclusion: ATBMS can provide critical habitats for local biodiversity while preserving traditional knowledge and cultural memory. It serves as an effective complement to OECMs and offers an innovative paradigm of “precise and micro-scale guardianship” for global biocultural diversity conservation. Future efforts should focus on developing robust assessment indicator systems, promoting interdisciplinary research, and improving community co-management mechanisms to establish a scientifically sound ATBMS conservation framework.

Background & Aims: Meta-analysis is a crucial statistical tool for deriving generalized conclusions through the weighted analysis of data from case studies, with broad applications in ecology. However, for a long time, researchers have significant misconceptions regarding the fundamental principles and methodological framework of meta-analysis, which has contributed to its misuse, even erroneous application.

Review Results: According to the standard steps of conducting a meta-analysis, this article summarizes the basic feature of meta-analysis and highlights critical considerations for its application, encompassing aspects such as: defining key concepts, literature search and screening, construction of effect sizes, selection of models, incorporation of special data structures, inclusion of explanatory variables, assessment of result reliability, and relevant software tools.

Conclusion: The clarifications of related concepts and key points will aid in constructing more precise and appropriate meta-analysis models, thereby enhancing the reliability of results. Furthermore, continued advancements in meta-analysis methodology is poised to offer more robust and reliable technical approaches for addressing numerous fundamental scientific questions in ecology.

Background & Aims: Both the Kunming-Montreal Global Biodiversity Framework (KMGBF) and China National Biodiversity Conservation Strategy and Action Plan (2023‒2030) (China’s NBSAP) have highlighted the engagement of non-state actors in biodiversity conservation. Philanthropic funding provided to non-state actors for biodiversity conservation purposes can significantly fill the public funding gap. The Fifteenth Meeting of the Conference of the Parties (COP15) to the Convention on Biological Diversity provided a unique opportunity for Chinese non-state actors to conserve China’s biodiversity. In 2021, during the first phase of COP15 in Kunming, a coalition of 10 Chinese non-state actors pledged to mobilize RMB 2.55 billion (USD 359 million) for biodiversity conservation by 2030.

Method: The study provides a systematic analysis by tracking the spending, outputs and outcomes of the pledge made in COP15 over the past five years, offering a systematic analysis of how biodiversity philanthropic funding in China has been mobilized and what results have been attained.

Results: During 2020‒2024, 11 major biodiversity-related philanthropic foundations invested a total of RMB 3.43 billion (USD 481 million) on biodiversity conservation activities. Among them, the seven foundations that made funding pledge at COP15 have spent RMB 1.55 billion (USD 217 million), equivalent to 60.7% of the total pledged amount. This funding has enabled non-state actors to deliver tangible results in the conservation of threatened species, habitat and area-based conservation, and biodiversity mainstreaming in China. The study also identified limitations of China’s conservation philanthropic funding: a disproportionate share of funding has flowed to afforestation-based “ecological restoration”, while comparatively less has been allocated to aligning with national programs or transforming private sector’s business models.

Conclusion: The study recommends that Chinese philanthropic funding should deepen collaboration with government-led biodiversity conservation initiatives to achieve the targets and goals of the NBSAP, and that transforming private sectors’ business models toward nature positivity should also be prioritized.

Aim: This paper focuses on the advancements in taxonomic studies of spiders in 2024 worldwide, with detailed statistical analyses of new taxa, type localities, arachnologists conducting such research, and journals publishing these works.

Results: A total of 1,048 new taxa were described in 2024, including 54 new genera and 994 new species. They belong to 68 families, with type localities spanning across 83 countries or regions. The new taxa were documented by 394 arachnologists in 329 papers, published separately in 65 different journals. Out of these 329 papers, 57 (17.3%) comprised revisions of selected higher taxa (at family and genus levels), regional studies, and monographs. The proportion of papers incorporating DNA analyses made up 14.9% (totaling 49 papers). Among the 994 new species, 643 new species were published based on both male and female specimens, accounting for 64.7% of the total, and 351 new species only published based on male or female specimens, accounting for 35.3%. China is the country with the highest number of new species discovered, a total of 309, accounting for 31.1% of the global tally. With as many as 92 arachnologists naming new spider taxa, China becomes the country with the highest number of publishing spider taxonomists, accounting for 23.4% of the world’s total. Among them, the most prolific arachnologist is Shuqiang Li, who described a total of 144 new taxa, comprising 13.7% of the worldwide total for 2024. Altogether, Li and the other 91 Chinese colleagues described a total of 344 new taxa, comprising 18 new genera and 326 new species from China, Vietnam, and the other six countries or regions. These new taxa described by Chinese arachnologists made up 32.8% of the 2024 global aggregate, higher than the Chinese output during the 2016-2020 period (28.1% on average), but lower than in 2021 (33.8%), 2022 (37.0%) and 2023 (41.2%).

Aims: The increasing adoption of machine learning in ecological research has enabled the modeling of complex, nonlinear ecological patterns. However, the “black-box” nature of many machine learning models limits their interpretability, hindering the extraction of ecological insights. This review aims to introduce the core concepts, methods, and practical tools of interpretable machine learning (IML), and to demonstrate how these techniques can enhance ecological understanding from predictive models.

Methods: We first clarify key distinctions among white-box model and black-box model, global interpretability and local interpretability, and intrinsic interpretability versus post-hoc interpretability models. Using a simulated dataset representing plant diversity and environmental variables (e.g., elevation, temperature, soil moisture), we apply both white-box models (e.g., linear regression, decision trees) and black-box models (e.g., random forest) to illustrate major interpretability techniques, including regression coefficients, permutation importance, partial dependence plots (PDP), accumulated local effects (ALE), Shapley additive explanations (SHAP), and local interpretable model-agnostic explanations (LIME).

Results: White-box models offer direct and transparent interpretability through their model structure, while black-box models require additional tools to derive explanations. Our case study shows that both model types can yield consistent insights about variable importance and ecological relationships. Furthermore, methods such as ALE and SHAP effectively address common limitations in conventional approaches like PDP by accounting for feature interactions and dependencies.

Conclusion: IML provides a valuable toolkit for improving model transparency and interpretability in ecological research. It serves as a crucial complement to traditional statistical modeling, enabling researchers to extract meaningful ecological interpretations from complex models. As ecological data and modeling complexity continue to grow, the integration of IML techniques will become increasingly important for hypothesis generation and ecological decision-making.

Aim: To collate and report on new vertebrate taxa in China published in 2024.

Method: This paper summarizes the basic information about new vertebrate taxa in China from the academic literature published in 2024.

Results: In 2024, 133 new vertebrate taxa were recognized in China, including 97 new species, 24 new record species, and 7 subspecies elevated to species rank, in addition, 1 new subspecies was described, and 4 species were reinstated as valid. These taxa belong to 16 orders, 47 families, and 87 genera. Among them, there are 40 new species of fish; 30 species of amphibian, including 25 new species and 5 new record species; 43 species of reptile, including 28 new species and 10 new record species in China, in addition, plus 1 new subspecies and 4 reinstated valid species; 10 species of bird, including 6 subspecies elevated to species rank and 4 new record species; 10 species of mammal, including 4 new species, 5 new record species, and 1 subspecies elevated to species rank. Ectothermic vertebrates account 85% of new discoveries; most representative orders were Cypriniformes (28/40) for fish, Anura (26/30) for amphibians, Squamata (39/43) for reptiles, Passeriformes (8/10) for birds, and Eulipotyphla (5/10) for mammals. These 133 new vertebrate taxa were recorded across 34 provincial-level regions. Most species (115) were found in only one region, while Yunnan, Guangxi, Xizang, Guangdong, and Fujian were the top five regions, with 46, 25, 18, 18, and 13 species recorded, respectively. A total of 111 of these discovered taxa have been supported by molecular systematics. Most findings (126 taxa) were published in 28 academic journals, with 15 of which were published in 4 English journals and 9 of which were published in 3 Chinese journals in China.

Conclusion: This article provides essential baseline data for the classification and conservation of vertebrates in China. In addition, it highlights that ectothermic vertebrates are a major focus of current diversity research, and underscores the importance of an integrated taxonomic approach for future studies.

Aims: Environmental DNA (eDNA) technology has been increasingly applied in biodiversity research. However, its rapid development has also sparked methodological debates. A key issue involves the selection of bioinformatic pipelines, particularly for extremely biodiverse taxa such as invertebrates. Bioinformatic pipelines significantly affect eDNA-based biodiversity profiles, yet a systematic comparative evaluation of relevant pipelines is currently lacking. Therefore, this study aims to compare and evaluate bioinformatic pipelines commonly used for analyzing eDNA-derived invertebrate sequencing data.

Method: Invertebrate metabarcoding sequencing was carried out on freshwater eDNA samples, and the performance of various bioinformatic pipelines in processing invertebrate sequences was comparatively assessed. Four commonly used clustering or denoising methods (UPARSE, Swarm, UNOISE, and DADA2) and three taxonomic assignment methods (BOLDigger, BLASTN, and Naïve Bayesian Classifier) were selected, together constituting 12 bioinformatic pipelines.

Results: Of the 12 evaluated pipelines, the combination of DADA2 denoising and BOLDigger taxonomic assignment yielded the largest number of invertebrate molecular operational taxonomic units (MOTUs), along with the highest levels of taxonomic coverage and resolution. Among the four clustering or denoising methods, UNOISE and DADA2 denoising yielded more invertebrate MOTUs than UPARSE and Swarm clustering. Among the three taxonomic assignment methods, BOLDigger and BLASTN yielded higher taxonomic coverage and resolution than Naïve Bayesian Classifier.

Conclusion: These findings have significant implications for eDNA-based research of freshwater invertebrate biodiversity. Furthermore, our results suggest that bioinformatic pipelines should be adjusted according to different study taxa and barcode regions to obtain accurate and reliable biodiversity data.

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 are 2,304 species of Poaceae in China, belonging to 283 genera, 37 tribes, and 10 subfamilies. Among these, native species account 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 ranks as the second largest family of seed plants in China, following Asteraceae. The alien flora consists of 326 species from 109 genera, 20 tribes, and 8 subfamilies; cultivated plants constitute the majority (69%). Among the native species, the subfamilies Pooideae (746 species, 74 genera) and Bambusoideae (712 species, 46 genera) are the two most species-rich. At the genus level, Bambusa (99 species) and Elymus (96 species) are the two largest genera in terms of species number. The centers of generic and species diversity for native Poaceae are located in Southwestern and Southern China, which harbor 92% of genera and 76% of species nationwide. Regarding conservation status, there are 29 national key protected wild species (from 21 genera), 16 provincial protected species (from 15 genera), and 54 threatened species (from 31 genera). The top 15 herbaria collectively house 73% of all Poaceae specimens in China, and most of these herbaria are affiliated with institutes of the Chinese Academy of Sciences. Furthermore, specimen collections are concentrated in large genera and widely distributed species, while collections of oligotypic genera and narrow-range endemic species remain 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.

Located in central China, Henan Province is a crucial transitional zone where the warm temperate and subtropical climates converge, and also serves as a key belt transitioning from the humid climate of the east to the semi-arid climate of the northwest. Due to its unique geographical location and climatic conditions, the region boasts a complex and diverse flora with varied components. Flora of Henan (1980-1997) had a prolonged publication timeline due to limitations in available literature at the time, coupled with advancements in the discipline that led to revisions or mergers of some plant names. With continuous discoveries of new species, Henan Province still lacks an accurate and comprehensive list of plant species. To address this, this study comprehensively utilizes multiple sources including Flora of Henan, Flora of China, relevant journal articles, master’s and doctoral dissertations, along with field-collected plant specimens and website references, to compile a vascular plant catalog and county-level distribution data for Henan Province. As of March 2025, Henan has recorded 184 families and 1,065 genera of wild vascular plants, totaling 3,916 taxonomic units (including taxa under species). Among these, there are 26 families and 71 genera of 259 species of lycophytes and ferns; 25 species of gymnosperms from 5 families and 12 genera; while angiosperms constitute the most abundant group with 3,632 species across 153 families and 982 genera. Compared to the merged version in Flora of Henan, the number of species increased by 655, with 618 new species added across 116 families and 314 genera. Furthermore, statistics indicate that Henan hosts 94 nationally protected wild plant species distributed across 39 families and 65 genera. The results can provide a solid theoretical and data basis for plant resource background survey, field dynamic monitoring, germplasm resources preservation and biodiversity conservation in Henan.

Aims: Zhejiang Province features complex water systems and extensive sea area that support high fish diversity. However, comprehensive studies on fish diversity in this region remain insufficient. To update and refine the fish species checklist of Zhejiang Province, we summarize taxonomic revisions for each taxon, species geographical distribution patterns, and their conservation status.

Methods: Based on existing literature, survey records and updated taxonomic and systematic findings, we revised the fish species checklist and distribution information of Zhejiang Province since the publication of Species checklist of freshwater fishes in Zhejiang Province and Marine Fishes of Zhejiang Province. The average similarity index (S) and cluster analysis were employed to examine the relationships among native inland fish communities across eight major water systems.

Results: The classification and distribution of 118 fish species in the original checklist were revised, and 237 species were added in our study. As of 31 December 2024, 1,148 fish species (including 13 alien species) were recorded in Zhejiang, belonging to 659 genera, 257 families, 46 orders, and 3 classes. The dominant orders are Perciformes (395 species), Cypriniformes (130 species), Scorpaeniformes (72 species), Pleuronectiformes (71 species), and Tetraodontiformes (53 species), collectively accounting for 62.80% of Zhejiang’s total fish species. There are 201 native inland fish species in Zhejiang, with the highest species richness observed in the Qiantang River (including Cao’e River) (155 species) and the Oujiang River (136 species); additionally, 934 native marine fish species are distributed in the region. The average similarity index of native inland fish communities among eight water systems exceeds 0.650. Cluster analysis of fish fauna shows that at a similarity distance of 0.5, the Tiaoxi River and the Grand Canal form one cluster; the Yongjiang River, Jiaojiang River (Lingjiang River), Oujiang River, Feiyun River, and Aojiang River form another; while the Qiantang River (including Cao’e River) forms a distinct cluster. Among Zhejiang’s fishes, 121 native species are under state protection or considered threatened. Of these, 14 species are listed in the List of State Key Protected Wild Animals, 32 species are included in the CITES Appendices, 104 species are assessed as Vulnerable (VU) or above on the IUCN Red List of Threatened Species, and 16 species are similarly classified on China’s Red List of Biodiversity.

Conclusion: Zhejiang harbors abundant fish resources. Based on their current status, we suggest strengthening species research, habitat protection, and scientific publicity. This updated checklist will facilitate research and law enforcement, and provide foundational data for fish conservation and sustainable utilization.

Background & Aims: Global biodiversity is declining at an unprecedented rate. As a widespread and diverse taxonomic group, birds are crucial indicators, and understanding drivers and consequences of their population dynamics is vital for biodiversity conservation. Passive acoustic monitoring (PAM), a non-invasive technique with high spatiotemporal resolution, offers a revolutionary tool for large-scale, long-term avian diversity surveys. Despite the rapid development of PAM globally, its application in China is currently hampered by scattered projects, heterogeneous equipment, and inconsistent methodologies. This has resulted in a “data island” dilemma, significantly hindering data integration and comparability and limiting the utility of these data for biodiversity policy and conservation. This study aims to provide a scientific blueprint and implementation guide for establishing a standardized, networked, and intelligent avian acoustic monitoring system in China.
Method & Results: We systematically reviewed the corresponding urgent needs of PAM in light of the global loss of avian biodiversity. We then compared and analyzed the technical development, network construction, and data-sharing experiences of avian PAM both internationally and domestically, identifying the core challenges China faces due to the lack of unified standards. Drawing on successful international PAM practices, we propose a comprehensive framework of standards suitable for China. This framework covers the entire workflow, from monitoring design and core technical parameters to metadata standards and data processing and analysis.
Perspectives: Finally, we present a series of actionable recommendations and a strategic roadmap for future implementation. These proposals address multiple facets, including top-level design, national network construction, technological innovation, data sharing mechanisms, and essential policy support, charting a clear course for the future of avian acoustic monitoring in the nation.

Background & Aims: Biodiversity conservation is essential for ecological security and sustainable human development. Nevertheless, the intricate interactions within ecosystems and the impact of external influences like human actions and climate change create substantial hurdles for conservation efforts. The advent of artificial intelligence (AI) and large language models (LLMs) offers new opportunities in this field. This study aims to review how these technologies are being used.

Methods: We discussed recent progress in using AI and LLMs for biodiversity conservation research and practice. Our focus was on AI and LLMs in knowledge synthesis and discovery, ecosystem modeling, assessment and monitoring, decision-making, and fieldwork.

Results & Conclusion: There is great potential for AI and LLMs in biodiversity conservation research and practices. Despite the promise, challenges such as data quality, model response times, ecosystem heterogeneity, ethical considerations, and data security remain. Future research should focus on developing specialized AI models and building high-quality, multimodal biodiversity datasets to effectively address these challenges.

Aims: Since 2020, the average annual number of changes in plant names in China has accounted for about 1.5%. Although this proportion is small, the cumulative changes over time cannot be ignored. To timely integrate these plant nomenclatural changes into the Catalogue of Life China, it is necessary to compile information on new taxa, new records, and nomenclatural changes related to Chinese plants annually, facilitating reference for scholars.

Methods: We collected data on newly discovered taxa and nomenclatural changes for Chinese higher plants by reviewing 117 journals and related monographs. This compilation involved 409 articles from 61 journals and 5 monographs, focusing on the new taxa and nomenclatural changes of higher plants in 2024.

Results: In 2024, China reported a total of 6 new families, 5 new genera, 284 new species (including hybrid), 24 new infraspecies, 34 new higher taxa (including 1 suborder, 2 new subfamilies, 15 new supertribes, 8 new tribes, 8 subtribes), 5 new sections, 1 new series in higher plants. Additionally, 531 new combinations and status (5 at supraspecific level, 507 at species level and 19 at infraspecific level) and 92 replacement names were published. At the national level, 6 newly recorded genera, 56 newly recorded species, and 3 newly recorded infraspecies were documented. Furthermore, 166 names were synonymized with 109 species, 9 names were resurrected. 4 species that had not been observed for many years were rediscovered, and 3 species distribution was excluded. Among the newly published species, there were 4 bryophytes, 21 pteridophytes (including 2 hybrids), 3 new gymnosperms, and 256 angiosperms (including 1 hybrid) and 24 infraspecies. Detailed intergrative evidences were provided for 136 new species when described, accounting for 44% of all new species. Additionally, the conservation status of 97 new species were evaluated according to Guidelines for Using the IUCN Red List Categories and Criteria when published, representing 31% of all new species. Four southwestern provinces, i.e., Yunnan, Guangxi, Xizang, and Sichuan, boast the highest number of species new to science, accounting for two-thirds of the total new species reported nationwide. Medog County is the richest in the number of new species and national new records among county-level administrative units, with 13 new species and 6 new records published.

Conclusion: In 2024, China witnessed a net increase of 316 new taxa of higher plants, accounting for 0.67% of the total Chinese plant species. Additionally, 796 names of higher plants underwent changes, accounting for 1.69% of the total. These changes represented 2.36% of all Chinese plant names modified in 2024, encompassing both species additions and nomenclature treatments. Multiple indicators suggest that the number of newly published plant taxa and nomenclatural changes in China have fluctuated but still remain at a comparatively high level.

Aims: The Qinghai-Xizang Plateau is the largest and highest plateau in the world, expanding across China, Nepal, India, Pakistan, Bhutan, Tajikistan, Afghanistan, and Myanmar, with majority of its area in China. Its complex terrain and diverse climate conditions have nurtured a rich and unique biota, making it one of the global hotspots for biodiversity research and conservation. This study focuses on the herpetofauna diversity from the Chinese part of the Qinghai-Xizang Plateau, aiming to compile an annotated checklist of amphibians and reptiles of the region and analyze their distribution patterns for future taxonomic and conservation works.

Methods: Following Zhang et al (2021a), we clarified the scope of the Qinghai-Xizang Plateau within China, covering 220 county-level administrative units in six provinces and autonomous regions. Based on this preset geographic area, we extracted data on herpetofauna diversity and their distribution from comprehensive literature review and supplemented their distribution data with our new field records. With the checklist, we further incorporated additional information including their endemic status, conservation status, and national protection status. Finally, we analyzed the county-level spatial distribution patterns of amphibians and reptiles separately, focusing on the total species richness, endemic species, threatened species (Critically Endangered (CR), Endangered (EN), and Vulnerable (VU)), assessment-pending species (Data Deficient (DD) and Not Evaluated (NE)), and newly discovered species.

Results: As of December 31, 2024, the amphibian fauna of the Qinghai-Xizang Plateau comprised of 151 species in 39 genera, 12 families, and 2 orders (Caudata: 10 species in 3 genera and 3 families; Anura: 141 species in 36 genera and 9 families), representing 22.0% of China’s total amphibian species. On the other hand, the reptile fauna of the Qinghai-Xizang Plateau includes 206 species in 62 genera, 19 families, and 2 orders (Testudines: 1 species in 1 genus and 1 family; Squamata: 96 species in 24 genera and 6 families for Lacertilia, 109 species in 37 genera and 12 families for Serpentes), representing 30.3% of China’s total reptile species. Among them, 64 species of amphibian and 72 species of reptile species are endemic to the region. Notably, over a quarter of the herpetofauna species of the Qinghai-Xizang Plateau were either described or newly recorded within the past decade (2015-2024). According to China’s Red List of Biodiversity, 22.5% and 11.7% of the amphibians and reptiles from the region, respectively, are classified as threatened, while 42.4% and 43.7% of them respectively lack effective conservation assessments. Analysis of county-level distribution patterns reveals a clear spatial heterogeneity in herpetofauna composition across the region. Three distinct biodiversity hotspots emerge, including southeastern Xizang, northwestern Yunnan, and western Sichuan, and Medog County stands out with the highest species richness, endemism and number of new species/new records discovered among all county-level administrative regions.

Conclusion: Characterized by both a rich species diversity and a high level of endemism, the Qinghai-Xizang Plateau possesses exceptional conservation value. Southeastern Xizang, western Sichuan, and northwestern Yunnan were identified as priority regions for continuous field surveys and taxonomic studies in the future. The lack of both conservation assessments and basic natural history data that support conservation assessments would prevent effective conservation of the herpetofauna from Qinghai-Xizang Plateau, and such data gaps should be filled urgently. Future conservation strategies must address escalating threats including habitat loss, overexploitation, and climate-driven environmental changes.

Background: Initiated in 1971, the Man and the Biosphere (MAB) Programme seeks to establish a scientific basis for strengthening the relationship between humans and the environment, recognizing humanity as an integral part of nature. Its core vehicle, the World Network of Biosphere Reserves, has expanded to 785 reserves across 142 countries. Following the momentum of four world congresses held in Minsk, Seville, Madrid, and Lima, the Hangzhou Action Plan emerged.

Methods & Results: This paper systematically elaborates on the evolution of the MAB Programme and provides an interpretation of its latest UNESCO MAB Hangzhou Strategic Action Plan. The Plan is structured around three parts: background, action targets, and monitoring and evaluation. Its main body contains 34 action targets focusing on three key areas: supporting global environmental protection and sustainable development agendas, strengthening the construction and development of the World Network of Biosphere Reserves, and advancing toward a sustainable future for humanity. Action Targets 1-13 translate global commitments—including the United Nations Sustainable Development Goals and the Kunming-Montreal Global Biodiversity Framework—into local action by safeguarding ecosystem integrity, expanding ecological restoration, and ensuring species and genetic diversity. Action Targets 14-26 reinforce the institutional, financial, and social foundations of the network through resource mobilization, inclusive governance, knowledge sharing, and international cooperation. Finally, Action Targets 27-34 focus on strengthening scientific research, adaptive governance, and global collaboration, ensuring that biosphere reserves serve as engines of innovation and education worldwide. Compared with the Madrid Action Plan and the Lima Action Plan, the Hangzhou Action Plan demonstrates stronger integration with global frameworks, places greater emphasis on equity, rights, and operational feasibility, and highlights financing and partnerships as core pillars. Despite challenges such as balancing conservation and development, addressing climate change, and coping with uneven resources, the Plan points the way toward a sustainable future of harmony between people and nature through enhanced partnerships, mainstreaming climate adaptation strategies, and promoting digital transformation.

Aims: The purpose of this study is to systematically examine soil viral community composition and assess their carbon metabolic functional potential across urban wetland ecosystems.

Methods: We took five habitat types of sample plots, including trees, shrubs and grasslands, shrub grasslands, reed marshes, shoals and ponds, distributed widely in Hangzhou Xixi National Wetland Park, Zhejiang Province (Xixi Wetland) as the research objects. This study investigated soil viral diversity patterns and carbon metabolic gene composition across these five habitat types using virus metagenomic sequencing coupled with bioinformatics analysis.

Results: There were significant differences in viral richness and diversity among the five habitat types (P < 0.05), with hierarchical rankings as follows: shrub grasslands > trees, shrubs and grasslands > reed marshes > shoals > ponds; The structural equation modeling analysis showed that this spatial pattern was predominantly mainly driven by soil physicochemical properties, with the order of effect size was pH > soil moisture > SOC (soil organic carbon) ≈ TN (total nitrogen) > soil temperature. The contribution of comprehensive effect size of viral host and viral diversity was in the order of TN > SOC > soil temperature, and the direct effect of viral host on viral diversity was the strongest (effect size = 0.87); A total of 158 unique carbohydrate transport and metabolism (G) genes were identified, including 13 distinct carbohydrates active enzyme (CAZyme) families. Among these glycosyltransferases accounted for the highest proportion (65.8%), indicating that soil viruses may play an important role in wetland carbon cycling through glycosylation-mediated processes.

Conclusion: The diversity of soil viruses in Xixi Wetland exhibits significant spatial heterogeneity. This distribution pattern is closely linked to variations in soil physicochemical properties (especially the key factors such as SOC, TN and soil moisture). The CAZyme genes identified in five habitat types contribute to wetland carbon cycling processes through regulating the metabolic pathways of host microorganisms.

Seed plants, as a fundamental component of ecosystems and a critical genetic resource reservoir, play key ecological functions and contain rich genetic diversity. They possess significant ecological, genetic, economic, and cultural value, making them indispensable for human survival and development. However, Hunan Province currently lacks a systematically organized inventory of wild seed plant resources. This study aims to integrate multi-source data to develop a comprehensive, classified dataset that includes a checklist and the geographical distribution of wild seed plants in the region. The dataset is intended to provide robust data support for plant diversity research, conservation initiatives, and sustainable resource utilization in Hunan Province. The dataset was constructed through an extensive review of academic literature, digitized herbarium records, and authoritative plant diversity databases. Species identification and taxonomic arrangement followed the latest systems and research advances. Up to August 31, 2025, the finalized dataset documents 194 families, 1,272 genera, 5,476 taxa (4,910 species, 92 subspecies, 468 varieties, and 6 forms) of wild seed plants in Hunan Province. Each entry in the dataset includes detailed taxonomic information (family, genus, species, and infraspecific taxa), leaf phenology (for woody plants), life form, growth form, county-level distribution in Hunan Province, elevational range, endemism, endangered status (according to IUCN or national criteria), and conservation level. Specimen vouchers or photographic records are provided as supporting evidence where available. The dataset covers all 122 county-level administrative regions across the 14 prefecture-level cities and autonomous prefectures of Hunan Province. This dataset constitutes the most complete checklist and geographical distribution dataset of wild seed plants in Hunan Province at present. It provides essential baseline data for conserving plant genetic diversity, establishing germplasm resource banks, and supporting genetic breeding research. It also offers a scientific basis for practical applications such as nature reserve planning, ecological corridor design, and the identification of priority conservation areas. The dataset is expected to make a substantial contribution to regional biodiversity conservation strategies and biosecurity management.

Aims: Spice plants are one of the most significant commodities in global trade since the Age of Exploration and they still hold important economic and medicinal value nowadays. Ethnobotanical research on spice plants meets the needs of modern society and aligns with modern societal demands and the development trends of the “Big Health” industry. Ethnobotany studies play a crucial role in promoting the utilization of plant resources and the economic development of ethnic regions by offering unprecedented clues for screening medicines related to human safety and pharmacological activity. China, Myanmar, and Laos tropical regions are one of the global biodiversity hotspots with abundant spice plants and cultural diversity. This study aims to catalogue the traditional knowledge of spice plants consumed by the ethnic groups in these regions, thereby providing a scientific basis for their conservation and sustainable utilization.
Methods: Based on ethnobotanical principles and multidisciplinary approaches, integrating botany, anthropology, pharmacology, linguistics, ecology, and economics, field surveys were conducted in China, Myanmar and Laos tropical regions. Semi-structured interviews (“5W+H”), village and market investigations, were done among eight ethnic groups, including Dai, Hani, Yao, Lao, Khmu, Burmese, Chin, and Kachin people. Literature on spice plants published in English or Chinese from 1985 to 2024 were reviewed. The spice plants diversity, traditional knowledge, resources origin and conservation status were systematically collected. Use value (UV) and Jaccard index (JI) were analyzed.
Results: A total of 414 spice plant species (including varieties) belonging to 63 families and 206 genera were documented. Among 300 medicinal, 123 edibles, 95 flavoring and 74 dual-purpose (medicinal-edible) species, 54.83% were herbs, with leaves (46.62%) and roots (20.77%) as the main used parts. Spice plants with a UV greater than 0.2 are predominantly multifunctional medicinal-food species. Of all recorded species, 178 could only be collected from wild, 185 were cultivated; however, only about 12% of them have fully completed the transition from wild harvesting to cultivation and market sale. The Jaccard index of spice plants utilization across the three countries is relatively low (JI, 0.20-0.25), indicating the rich cultural diversity and distinct ethnobotanical traditions shaped by long-term adaptation to different ecological and cultural contexts in these regions. There were 52 (12.56%) species under protection or threaten, and 15 nationally protected or rare and endangered spice plants were identified for priority investigation, conservation and utilization.
Conclusions: This study provides the world’s first comprehensive and systematic ethnobotanical catalogue of spice plants utilized by local ethnic communities in the tropical regions of China, Myanmar, and Laos. It not only provides an initial intellectual prototype for the sustainable development and cross-border utilization of spice plant resources in the food, pharmaceutical, and cosmetic industries, but also offers fundamental data and scientific case for promoting transboundary cultural and biodiversity conservation and contributes to the green development of the Belt and Road.

Wildlife diversity monitoring is a crucial approach for biodiversity conservation and an essential task within nature reserves. The Ma’anshan Provincial Nature Reserve in Ganluo County, Sichuan Province, is located in a mountainous canyon area transitioning from the western edge of the Sichuan Basin to the Qinghai-Xizang Plateau. It serves as an important distribution area for the southernmost marginal population of the giant panda (Ailuropoda melanoleuca). This study compiled a total of 1,136.08 GB of infrared camera monitoring data collected from 2021 to 2024 in the region. After screening and species identification, a comprehensive dataset of bird and mammal observations from infrared cameras was provided. The dataset covers 59 effective camera sites, accumulating 17,586 camera days and capturing 38,482 video records. Among these, there were 12,325 mammal records, with 5,911 independent valid detections, covering 24 mammal species across 4 orders and 14 families. Additionally, 5,427 bird records were documented, with 1,578 independent valid detections, involving 51 bird species across 5 orders and 21 families. This dataset provides a checklist of the bird and mammal species and spatiotemporal distribution information, offering fundamental data for understanding the current state of biodiversity in the reserve and supporting subsequent conservation management as well as further research.

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.

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 higher 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 higher 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 higher plants have been recorded in the province, belonging to 386 families and 2,396 genera. Among these, there are 10,967 species of wild higher plants in 373 families and 2,185 genera, 547 endemic higher plant species in Guizhou, 782 karst-obligate plant species, 719 commonly introduced and cultivated plant species in 115 families and 402 genera, and 202 invasive higher plant species. The dataset also records 256 national key protected wild higher plant species and 55 provincial key protected wild higher plant species in Guizhou. In terms of spatial distribution, Qiannan Buyi and Miao Autonomous Prefecture (6,792 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 higher plant diversity in Guizhou and for their conservation and utilization. They also offer a data support for the compilation of specialized works such as the Flora of Guizhou (second edition) and the Dendrology of Guizhou.

Background: Amid the accelerating global biodiversity crisis driven by human activities, precise monitoring and assessment of species distributions and population dynamics have become urgent priorities for conservation. Traditional survey methods often suffer from imperfect detection, leading to biased estimates of occupancy and hindering effective management decisions. The advent of big data offers opportunities for integrating diverse sources, yet challenges in handling heterogeneity and observational biases persist. Hierarchical occupancy models, by explicitly separating ecological processes (true occupancy) from observation processes (detection probability), provide a robust statistical framework to obtain unbiased inferences and have emerged as a powerful tool in biodiversity monitoring.

Main Content: This paper reviews the theoretical foundations of hierarchical occupancy models, including the classic single-season framework and key extensions such as multi-season (dynamic) models for quantifying colonization, extinction, and temporal trends, as well as multispecies (community) models that harness interspecific correlations to enhance inferential precision. We highlight their core advantages: correcting for false negatives through explicit detection probability estimation, flexibly integrating heterogeneous multi-source data, and generating interpretable, auditable ecological indicators for biodiversity assessment. However, practical applications face several challenges, including data quality and heterogeneity issues, violations of key assumptions (e.g., independence of observations, population closure within seasons, absence of false positives), potential constraints on the biological interpretability of parameters, high computational demands for complex models and large datasets, and difficulties in communicating results to non-specialists and policymakers. Corresponding mitigation strategies are discussed, such as standardized data preprocessing, rigorous assumption validation, interdisciplinary collaboration, algorithmic optimization, and enhanced science-policy translation.

Conclusion: Hierarchical occupancy models significantly advance the scientific rigor and reliability of biodiversity monitoring and evaluation by addressing imperfect detection and enabling integrative analyses. Moving forward, continued methodological innovations, fusion with emerging data types and technologies, deeper cross-disciplinary integration, and efforts toward standardization and broader application will further strengthen their role in supporting evidence-based conservation in the face of ongoing global change.

Aims: Understanding how urbanization alters the taxonomic and functional diversity of aquatic communities is essential for assessing urban river environments and conserving biodiversity. Macroinvertebrates play a crucial role in maintaining the functions and integrity of river ecosystems, yet the ecological variables and mechanisms through which urbanization influences their functional diversity remain poorly understood.

Methods: In 2019, macroinvertebrate samples were collected during both the wet and dry seasons from 62 sites distributed across five major watersheds in Shenzhen, covering a gradient of urbanization intensity. Taxonomic and functional diversity was quantified using species richness and the RaoQ index, respectively. The Mann-Whitney U test was used to compare these two diversity indices between urban and suburban rivers. Furthermore, multivariate stepwise regression analysis was performed to identify key environmental variables shaping macroinvertebrate taxonomic and functional diversity. Finally, variation partitioning was applied to assess the relative contributions of local physical environmental conditions, water chemistry variables, and land-use variables.

Results: Taxonomic and functional diversity were consistently higher in suburban rivers (with lower levels of urbanization) than in urban rivers (with higher levels of urbanization) during both the wet and dry seasons. This disparity was more pronounced during the wet season, suggesting that urbanization exerts stronger impacts on macroinvertebrate diversity during periods of higher water flow. In contrast, functional redundancy was higher in urban rivers than in their suburban counterparts. Stepwise regression and variation partitioning analyses revealed that land-use variables, local physical environmental variables, and water chemistry variables collectively accounted for 37%-57% of the variation in taxonomic and functional diversity. However, the relative influence of these ecological variables varied depending on the biodiversity dimension and the season. Among them, local physical environmental (explaining 4%-23% of the variation) and water chemistry variables (0-9%) emerged as the primary variables, followed by land-use variables (0-4%). Specifically, water chemistry variables—such as permanganate index and conductivity—had the greatest influence on taxonomic and functional diversity during the dry season, whereas local physical environmental variables—such as substrate composition and water depth—played a more significant role in shaping functional diversity during the wet season.

Conclusions: Urbanization significantly reduces the taxonomic and functional diversity of river macroinvertebrates, primarily through changes in local environmental conditions. The lower taxonomic and functional diversity, coupled with higher functional redundancy observed in urban rivers, suggests more homogeneous macroinvertebrate community compositions in these systems. The findings of this study enhance our understanding of the processes and mechanisms underlying the decline of aquatic ecosystem functioning caused by urbanization, and provide a scientific basis for biodiversity conservation and land-use planning in the rivers of the Greater Bay Area of Guangdong-Hong Kong-Macao.

Background & Aims: Biodiversity data serve as a fundamental basis for advancing biodiversity science and achieving effective conservation outcomes. The Global Biodiversity Information Facility (GBIF), as the most influential biodiversity information platform, has established a global collaborative network and integrated over 3 billion species occurrence records from across the globe. These resources provide essential support for scientific research, policy-making, and management decisions. This study aims to systematically examine the key initiatives and corresponding achievements of the GBIF. Drawing on an analysis of China’s current practices and challenges in biodiversity data development, the study seeks to provide well-founded recommendations and insights to inform the advancement of relevant national platforms.

Progresses: This paper systematically reviews the development history, organizational structure, key initiatives, and major achievements of GBIF, and analyzes its valuable experiences in promoting innovation in scientific research and policy-making, enhancing coordination mechanisms, developing a global network, and strengthening infrastructure. Over 12,000 peer-reviewed publications have cited GBIF data, and the platform has been widely recognized by international organizations such as the Convention on Biological Diversity (CBD), the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), and the Group on Earth Observations Biodiversity Observation Network (GEO BON). The development of China’s biodiversity data platforms commenced at a relatively early stage and have yielded substantial outcomes. However, challenges remain in their development, limiting the full application potential of China’s biodiversity data in scientific research and policy-making.

Prospects: Based on the development potential of biodiversity data infrastructure in China, the paper proposes recommendations such as establishing a top-level coordination mechanism, enhancing research infrastructure, improving national-level platforms for data-driven innovation, and deepening support for scientific and policy decision-making, aiming to provide practical insights for the planning and development of related platforms in China.

Background & Aims: The compilation of authoritative biodiversity catalogs is of great significance for biodiversity research, resource protection, as well as social and economic development. In the era of rapid development and progress on scientific research, a large number of new species and new distribution records are reported every year. It is very important to summarize the discoveries of new taxa and update the species checklist in time.

Method: The taxonomic data of newly published fungal names were retrieved and analyzed from the Fungal Names nomenclatural repository.

Results: In 2024, 2,106 scholars have published 5,500 new fungal names all over the world, including 3 new subphylum, 17 new classes, super classes and subclasses, 9 new orders and suborders, 37 new families, subfamilies and tribe, 280 new genera and subgenera, 3,716 new species and intraspecific taxa, 1,094 new combinations, 37 replacement names and 307 other new names. These new names belonged to 3 kingdoms, 16 phyla, 49 classes, 183 orders, 494 families and 1,429 genera, among which agaricomycetes and wood-inhabiting fungi have received more attentions. The newly published 3,681 fungal species were discovered from 107 countries and regions in the world. East and south Asia were the hottest spots of new species discovery, while China retained the top country for yearly new species discoveries, accounting for 48.85% of the world’s total. Besides, Chinese scholars led the world in research outputs on fungal taxonomy this year. There are 635 Chinese scholars participated in the publications of 2,686 new fungal names, contributing nearly half of the world’s total.

Conclusion: After a slight decline in 2023, the number of globally published new fungal names has rebounded to 5,500 last year, which is the highest number in history. Since 2021, the number of new names published by Chinese scholars, and the contribution ratio to the world have broken the historically record for consecutive three years.

Background & Aims World Biosphere Reserves are designated demonstration areas to promote a balanced relationship between humans and the biosphere, exploring pathways for harmonious coexistence between human societies and natural ecosystems. China currently has 34 World Biosphere Reserves. However, there remains a lack of comprehensive and systematic research at the national level regarding how these reserves can effectively drive the coordinated development of human society and ecological conservation. Additionally, it is unclear whether the logistic support functions of protected areas contribute meaningfully to fostering sustainable human-nature relationships within these reserves.

Methods: This study integrated comprehensive spatial data from all 34 World Biosphere Reserves in China and their associated protected areas. By combining human footprint indicators, ecological remote sensing datasets to calculate ecosystem quality index, as well as trend detection methods including Theil-Sen Median slope estimation and Mann-Kendall analysis, we evaluated the relationship between human social development and natural ecological protection at a 1 km × 1 km pixel resolution within these reserves.

Results: Linear regression results indicated that ecosystem quality across China’s 34 World Biosphere Reserves increased from 2010 to 2020, although the trend was not statistically significant (P > 0.05). In contrast, human footprint exhibited a statistically significant upward trend during the same period (P < 0.05). Within these reserves, 10% of the pixel units demonstrated significant changes in human-nature relationships, with coordination interactions accounting for the largest proportion (72.2%), particularly evident in seven reserves including Jinggangshan and Bogda, etc. Furthermore, a lower coverage ratio of protected areas within a World Biosphere Reserve, a larger total area of the World Biosphere Reserve, and a longer duration since its designation as a World Biosphere Reserve are all associated with enhanced coordination between human development and ecological conservation.

Conclusion: With the upcoming Fifth World Congress of Biosphere Reserves to be held in Hangzhou, China in September 2025, this study offers robust scientific support for understanding the role of China’s World Biosphere Reserves in advancing harmonious development between human society and nature. Furthermore, it provides valuable insights and references for future global research and sustainable management of World Biosphere Reserves.

Background & Aim: Species represent fundamental entities in biological research. In recent years, the integrative species concept has gained increasing popularity. It emphasizes that the delimitation of closely related species should be based on multiple lines of evidence. Juniperus coxii, initially described as a variety of J. recurva, was subsequently elevated to species rank. Nevertheless, population-level evidence supporting this taxonomic classification remains scarce.

Methods: To clarify the boundaries between two taxa within the J. recurva complex from the eastern Hengduan-Himalayan region, chloroplast DNA sequences were obtained from 197 individuals across 26 populations for lineage delimitation. While the molecular data delineated the phylogenetic framework, statistical morphological analyses and niche differentiation assessments were further conducted on representative populations. Additionally, ecological niche modeling was performed by integrating environmental climatic factors from both our sampling sites and previously published occurrence records.

Results: Chloroplast haplotype network analysis has divided the J. recurva complex into two lineages: eastern and western. Geographically, these lineages have been roughly separated by Cona City. No significant statistical discontinuity has been observed in their morphology, although morphological variation has been found among individuals. The ecological niches of the eastern and western lineages have shown significant differentiation, with some overlap remaining.

Conclusion: The above evidence supports classifying populations west of Cona City as J. recurva, while eastern populations represent J. coxii. However, as this study relies exclusively on chloroplast DNA data, further research employing nuclear genome-derived molecular markers is warranted.

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 replacement was the dominant process driving community dissimilarity across the study area. (2) The SCBD values ranged from 0.002% to 21.918%, 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. (3) LCBD values ranged from 0.537% to 2.677%. Plots with higher species richness exhibited higher LCBD values, with southeastern sites generally having greater LCBD values than those in the northwestern. (4) Climatic factors were identified as the primary drivers of LCBD variation. The interaction between climate, spatial, topographic, and human disturbance variables influenced 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.

Odonata, one of the most ancient lineages of aquatic insects, is highly sensitive to environmental change and serves as a crucial link between aquatic and terrestrial ecosystems. As such, Odonata plays an important role in biodiversity research and ecological monitoring and is widely recognized as a key indicator group for assessing ecosystem health and guiding conservation efforts. Guangdong Province is one of China’s biodiversity hotspots for Odonata. However, systematic surveys of the region’s Odonata diversity remain limited, largely because comprehensive species distribution data are lacking, which hinders effective conservation planning. To address this gap, we compiled a comprehensive checklist and geographic distribution dataset of Odonata for Guangdong Province, based on long-term field surveys, literature review, and multi-source database integration. The dataset covers records from 1980 to 2024 and documents 261 species (including subspecies) across 115 genera and 19 families, including 180 (including subspecies) Anisoptera and 81 (including subspecies) Zygoptera species. At the family level, Libellulidae (24.14%), Gomphidae (19.54%), Aeshnidae (13.03%), Coenagrionidae (8.81%), and Macromiidae (5.75%) are the most species-rich family. The dataset integrates IUCN Red List status information for 149 Odonata species. With its high spatial resolution, this dataset enables identification of insect diversity hotspots and provides a foundation for long-term monitoring and conservation assessment. The accompanying species checklist constitutes a key resource for characterizing the biogeographic structure of insect assemblages in South China and for providing baseline information to guide the establishment of Nanling National Park.

Aims: Establishing biodiversity baselines is essential for supporting the development of China’s protected area system with national parks as the mainstay. This study aims to document bird and mammal diversity in the Mangkang Yunnan Snub-nosed Monkey National Nature Reserve, Xizang and to examine the seasonal spatial occupancy patterns of selected representative species based on long-term camera trapping.
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. We summarized species richness and relative abundance for all detected birds and mammals. Based on data completeness and representativeness, we selected five representative species—Vulpes vulpes, Capricornis milneedwardsii, Rhinopithecus bieti, Crossoptilon crossoptilon, and Ithaginis cruentus—for single-season occupancy modeling to evaluate seasonal differences in spatial occupancy habitat use.
Results: The survey recorded 26 species of mammals (12 families, 4 orders) and 51 bird species (18 families, 8 orders). Six species were listed as Class I nationally protected species in China—Panthera pardus, Moschus berezovskii, M. chrysogaster, Rhinopithecus bieti, Tetrastes sewerzowi, and Tetraophasis szechenyii—and 20 species were listed as Class II nationally protected species. Among mammals, Elaphodus cephalophus, Lepus oiostolus, Capricornis milneedwardsii, Macaca mulatta, and Vulpes vulpes showed the highest 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: Seasonal spatial use patterns differed substantially among species, indicating strong species-specific responses. These variations were associated with various 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, providing a solid scientific basis for biodiversity conservation planning and adaptive management within the reserve.

The modern history of Chinese botany takes 1950 as a crucial turning point, marking the reorganization of previous research institutions under the newly established Chinese Academy of Sciences and the advent of a new era in botanical science. This article chronicles the developments before 1950, beginning with the establishment of the first biology department at a national university by Chi Ping and Hsen-Hsu Hu in 1921. Subsequently, several research institutes were founded, primarily dedicated to the collection and taxonomic study of Chinese flora. These efforts laid the foundation for the compilation of the Flora of China. This historical overview illustrates how Chinese botany, under the leadership of prominent figures, evolved from its inception to a period of flourishing development, and then declined under the impact of war.

Background: Biodiversity conservation remains one of the most urgent priorities on the global environmental agenda. Effectively halting and reversing the ongoing loss of biodiversity constitutes a fundamental challenge for contemporary ecological governance. In order to fulfill the objectives of global sustainable development, it is essential to establish a robust and responsive global biodiversity early warning system capable of real-time monitoring and dynamic assessment of biodiversity trends. The Kunming-Montreal Global Biodiversity Framework (KMGBF), adopted at the fifteenth meeting of the Conference of the Parties to the Convention on Biological Diversity (COP15), outlines a strategic roadmap for the future of global biodiversity governance.

Aims: Based on the objectives articulated by the KMGBF, this study investigates the current status, principal challenges, emerging opportunities, and strategic pathways for advancing the development of a global biodiversity early warning system. Through enhanced international policy coordination and collaborative efforts, the envisioned system aspires to promote the scientific and intelligent governance of global biodiversity. It is expected to provide a rigorous scientific foundation for the formulation and execution of biodiversity conservation policies across nations, thereby making a substantive contribution to global biodiversity protection and the broader pursuit of sustainable development.

Challenges & Prospects: This study begins by underscoring the pivotal role of the KMGBF in guiding the development of a global biodiversity early warning system. Despite notable advancements in recent years, significant challenges persist, including incomplete data coverage, reliance on outdated technologies, and insufficient international cooperation. Building on the vision articulated in the KMGBF, this paper systematically outlines the foundational architecture and key components of a global biodiversity early warning system, and proposes a suite of global indicators to facilitate its implementation. Furthermore, this paper advocates the integration of multi-source data, including satellite remote sensing and ground-based camera observations, along with advanced technologies such as cloud computing and artificial intelligence. This integrated approach aims to establish a scalable and resilient global biodiversity early warning system that can support multidimensional, multilevel, and multiscale biodiversity assessments.

Aims: Spatial distribution of species represents a core issue in population biology and macroecology. Commonly used metrics for quantifying species aggregation include the negative binomial distribution parameter k for quadrat data and neighborhood density indices (such as Ω proposed by Condit et al. (2000) and k_ff proposed by Wiegand et al. (2025)) for point pattern data. However, how the choice of index and its estimation uncertainty jointly affect the inference of the aggregation-abundance relationship remains unclear.

Methods: We use a spatially explicit neutral model to simulate community data, then computed the aforementioned aggregation indices along with their standard errors. Finally, we analyzed how the index selection and its estimation error influence the power-law relationship between aggregation and species abundance.

Results: (1) The three aggregation indices are strongly correlated under high aggregation intensity. Under weak aggregation, however, k remains effective in discriminating interspecific differences in aggregation, whereas the two point pattern indices lack such discriminative power. (2) Estimation errors of different indices are weakly positively correlated. The standard error of k for rare and weakly aggregated species estimated by maximum likelihood is large, consistent with simulation results. In contrast, standard errors of point pattern indices based on resampling methods are generally smaller. (3) The aggregation-abundance relationship varies depending on the chosen index and whether weighted regression is applied. For 1/k, weighted regression consistently recovers the theoretical exponent of -1 predicted by neutral theory, whereas unweighted regression yields shallower slopes, especially in communities with weak aggregation. The exponents for the two point pattern indices vary with the mean aggregation intensity of the community.

Conclusions: Ignoring the uncertainty in aggregation estimates can significantly bias inferences of the aggregation-abundance relationship, potentially leading to the incorrect rejection of the neutral null hypothesis (i.e., an increased risk of Type I error). The relationships derived from the two point pattern indices reflect mean community aggregation but are not suitable for directly testing neutral assembly mechanisms. We recommend using the maximum likelihood estimate of the negative binomial parameter k and its standard error to measure species aggregation from quadrat data and incorporating uncertainty into subsequent analyses. For other aggregation indices, there is a need to develop predictions of their relation with species abundance from theories such as the simple neutral case.

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. Here herbivory rate was proportion of leaf area consumed by herbivory and herbivory frequency was proportion of leaf by herbivory. 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, 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.