Aims: Population dynamics analysis is a crucial basis for formulating conservation strategies of endangered species. The Chinese giant salamander (Andrias davidianus) is an endemic amphibian in China, and the status of its wild populations remains unclear. Through population dynamics analysis, this study aims to provide a basis for the conservation strategies of the Chinese giant salamander.

Methods: This study took the Chinese giant salamander (Andrias davidianus) as the focal taxon in Zhangjiajie Chinese Giant Salamader National Nature Reserve, Hunan Province, China, based on the field survey data obtained from 2006 to 2021 and was complemented by comprehensive stock enhancement and release statistics spanning from 2000 to 2024. Utilizing population growth models, the study examined the population dynamics, carrying capacity, and the efficacy of stock enhancement measures for the Chinese giant salamander population.

Results: The results showed that: (1) The average annual population growth rate was 0.1722 ± 0.0324, with a carrying capacity (K) value of 51,190 individuals. The current population was in an exponential growth phase. (2) There was a highly significant difference in population growth curves between stock enhancement and non-stock enhancement scenarios. In the non-stock enhancement scenario, the instantaneous growth rates in the exponential and Logistic growth functions decreased by 16.27% and 32.11%, respectively. (3) Stock enhancement has demonstrably reinvigorated wild populations of Chinese giant salamander, under the current release regime, population size is projected to reach the environmental carrying capacity in 40 years.

Conclusion: Empirical validation confirms the feasibility of leveraging population growth models to project demographic trajectories, rendering them powerful tools for devising medium to long-term conservation strategies for endangered species; Stock enhancement has a significant effect on the recovery of the wild population of the Chinese giant salamander. Based on the current stock enhancement volume, the population size is projected to reach the peak of the carrying capacity in 40 years. Considering the current population growth rate, population growth trajectory, and environmental carrying capacity, continuous stock enhancement measures should be implemented, and individuals for stock enhancement should be selected based on river systems and genetic lineages, with offspring from local broodstock as the source of stock enhancement individuals. This approach can prevent genetic mixing in wild populations and ensure stable population growth. Additionally, protection and restoration efforts should be focused on breeding sites. This study offers valuable guidance for the analysis of population dynamics, the assessment of conservation effectiveness, and the development of conservation strategies for the Chinese giant salamander and other endangered species.

Aims: Invasive alien plants (IAPs) pose serious threats to ecosystems, biodiversity, and human well-being. Hainan Island, as one of China’s most biodiverse regions, confronts mounting risks of invasion by alien plant species. This study targeted 33 invasive species identified in the newly released Key Management List of Invasive Alien Species (issued jointly by six ministries and commissions, including the Ministry of Agriculture and Rural Affairs), aiming to evaluate their potential suitable habitats and invasion risks on Hainan Island.

Method: We first aggregated occurrence records and environmental variables from multiple databases for the 33 listed invasive plant species. Using the maximum entropy (MaxEnt) model in conjunction with geographic information system (GIS) techniques, we modeled each species’ potential spatial distribution under current climatic conditions. Subsequently, we overlaid species-specific distribution maps to identify invasion hot spots and assessed the relative importance of environmental factors contributing to habitat suitability.

Results: Among the 33 investigated species, 25 were predicted to possess suitable habitats on Hainan Island, which varied in geographical extent. Notably, four species—Sorghum halepense, Chromolaena odorata, Amaranthus spinosus, and Lantana camara—exhibited high-risk distributions covering more than 50% of the island’s total land area. Invasion hot spots were concentrated primarily in low-elevation plains in the northeastern region and several coastal zones. Key environmental drivers included human activity intensity, temperature seasonality, mean diurnal temperature range, and precipitation of warmest quarter. These findings reflected the urgent need for comprehensive prevention and control measures, particularly in vulnerable areas.

Conclusion: Our results underscore the importance of prioritizing high-risk species and high-risk regions for targeted monitoring and integrated management on Hainan Island. Effective strategies should include not only conventional control approaches but also incorporate socio-environmental factors and biotic interaction mechanisms in subsequent research. By enhancing early warning systems and applying science-based interventions, stakeholders can better curb the spread of invasive alien plants and safeguard the island’s rich biodiversity.

Background & Aims: With the integrated development of earth sciences and life sciences, geogenomics—an interdisciplinary field integrating geology, geomorphology, paleoclimatology, genomics, phylogenetics, population genetics, and biogeography—links surface landscape changes to biological evolution. This field has become an effective way for testing geological hypotheses and reconstructing Earth’s history, as well as exploring its co-evolution with life. Geogenomics also shows significant potential in global ecological conservation.

Methods: In this review, we utilized the Web of Science core collection, and analyze the evolution of themes and hotspots in geogenomics through bibliometric analysis. Meanwhile, we systematically introduce the fundamental concepts and key scientific questions of geogenomics, as well as its relationship to related research fields.

Review Results: As an emerging interdisciplinary field, geogenomics deeply integrates geological, climatic, and genomic data to inverts the spatio-temporal patterns and interactions between geological structure movements and the history and distribution changes of biological groups. This field holds significant promise for advancing geological and biological evolution. We focus on five key aspects: testing geological hypotheses; elucidating regional or intercontinental scale geological processes; inferring regional biodiversity evolution history; addressing uncertainties in geological reconstruction and scale effects, as well as the geographical distribution patterns and dispersal origins of pathogens.

Perspectives: At present, research in this field is still limited in China, but it has been carried out on several important scientific questions, such as the uplift history was highly variable of the Qinghai-Tibetan Plateau and the evolution of the Yangtze River and Yellow River systems. In the future, it is imperative to enhance the application of multidisciplinary approaches, develop more effective tools, and advocate for the establishment of a global geogenomics research database.

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.

Aim: Tropical tree communities are characterized for their species diversity, with large genera playing a key role in promoting community diversity. However, the mechanisms underlying the coexistence of closely related species within these genera remain a central question in tropical ecology. Traditional approaches, often based on functional traits, have provided insights into niche differentiation but fall short of fully explaining the complex coexistence patterns.

Methods: This study focused on representative Ficusspecies in tropical community. By combining transcriptomics and metabolomics with phylogenetic analysis and functional traits measurements, it explored how differences in phylogenetic relationships, physical defense traits, defense-related genes, and metabolite diversity influence interspecific interactions among Ficus species, thereby promoting and maintaining their coexistence in local communities.

Results: In locally coexisting Ficus species, (1) No significant phylogenetic signals were detected in defensive traits except for C/N ratio; (2) Physical defense traits, defense-related genes, and metabolite diversity exhibited significantly lower values than random structure (P< 0.01), indicating divergent patterns, whereas phylogenetic relationships did not significantly differ from random structure (P= 0.194); (3) The diversity pattern of defensive traits reflected habitat heterogeneity.

Conclusion: This study shows that locally coexisting Ficus species promote defensive niche differentiation through the divergent pattern of defensive traits. The diversity of defense-related genes and metabolites provided new evidence for this, which is expected to provide new insights and ideas in this field.

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 & Aim: Cetaceans are key indicator species of marine ecosystems, and effective monitoring of their population dynamics is essential for biodiversity conservation. Traditional ship-based visual survey methods are constrained by multiple factors such as sea conditions, weather visibility and labor costs, making it difficult to achieve spatial and temporal continuity of ecological monitoring. Passive acoustic monitoring (PAM) breaks through the traditional monitoring bottleneck by deploying hydrophones to receive cetacean acoustic signals and environmental noise in real-time, achieving all-weather, non-invasive and three-dimensional monitoring of cetaceans. We conducted a systematic review of cetacean acoustic monitoring literature published between 2004 and June 2024, categorizing findings into five thematic areas. Our analysis identified recent research achievements and persistent challenges, and proposes strategic recommendations for advancing acoustic monitoring applications in China.

Review Results: Our meta-analysis identified 1,089 relevant papers, revealing limited publication output between 2004 and 2010 followed by exponential growth post-2016. The analyzed literature coalesces into five research domains: (1) equipment development and technical methods (19.9%), (2) acoustic signals and communication patterns (18.7%), (3) population and spatial ecology (38.0%), (4) ecological behavioral patterns of cetaceans (15.1%), and (5) conservation and management applications (8.3%). Technological convergence such as deep learning has revolutionized high-throughput acoustic data processing. Contemporary research extends beyond acoustic signal types to population dynamics, soundscape ecology and behavioral patterns, establishing acoustic monitoring as a critical tool in cetacean conservation and management.

Perspectives: This review synthesizes contemporary advancements in cetacean bioacoustics and outlines strategic pathways for China’s nascent research initiatives. We propose five evidence-driven priorities to advance both scientific understanding and conservation applications: (1) advance technological innovation by developing next-generation autonomous recording systems and intelligent analytical tools tailored to cetacean vocalizations; (2) implement holistic monitoring systems that synergize multi-dimensional acoustic data with environmental and behavioral datasets through sensor network integration; (3) establish unified national archives featuring standardized protocols for data sharing and collaboration, incorporating blockchain technology for traceability; (4) strengthen interdisciplinary capacity through specialized training programs integrating marine acoustics, ecology, and computational modeling; (5) expand participatory science frameworks via targeted science communication campaigns and citizen science platforms for coastal communities. These strategic priorities aim to bridge existing research gaps and advance evidence-based cetacean conservation.

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.

Aims: Climatic change and anthropogenic activities have become the principal threats to global biodiversity. Genetic diversity, a fundamental component of biodiversity, is integral to species’ adaptation to environmental changes. Amphibians and mammals have distinct differences in evolutionary history, physiological functions, and ecological behaviors. Notably, their contrasting thermoregulatory capacities and mobility render amphibians may be more susceptible to climate change and human activities than mammals. However, it remains uncertain whether these differences result in divergent patterns of genetic diversity. Haplotype diversity and nucleotide diversity are the critical metrics in assessing genetic diversity, yet their respective responses to climatic and anthropogenic influences need to be further investigated.

Methods: This study concentrated on amphibians and mammals, employing the cytochrome c oxidase subunit I (COI) gene fragment to investigate the impacts of climatic factors and human activities on haplotype diversity and nucleotide diversity of these two vertebrate groups.

Results: We found a substantial difference in overall nucleotide diversity (D = 0.230, P < 0.01) and haplotype diversity (D = 0.211, P < 0.05) between amphibians and mammals. Distinct patterns were recorded on that how climatic and anthropogenic factors influenced nucleotide and haplotype diversity between the two groups. For amphibians, haplotype diversity was positively correlated with precipitation seasonality range (β = 0.467, P < 0.05), while it was negatively correlated with the annual temperature range (β = −0.223, P < 0.05). Furthermore, the human influence index (HII) showed a positive correlation with amphibian nucleotide diversity (β = 0.035, P < 0.05). Conversely, in mammals, HII was negatively correlated with haplotype diversity (β = ‒0.018, P < 0.05), whereas the annual temperature exhibited a positive correlation with nucleotide diversity (β = 0.002, P < 0.05).

Conclusion: Our results underscore the complexity of genetic diversity responses to climatic and anthropogenic influences. We advocate for the integration of multiple metrics to investigate the distribution patterns of genetic diversity and their driving factors. Future research should further explore the mechanisms through which human activities and climatic factors impact genetic diversity across various animal groups, aiming to develop more targeted biodiversity conservation strategies.

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.

Aims: Understanding the activity patterns, range, and suitable habitat distribution of Equus hemionus is essential for assessing its survival strategies in response to environmental changes.

Methods: In this study, we used camera trapping to survey water resource utilization patterns of Equus hemionus during summer season (June to August) from 2021 to 2023 in Kalamaili National Park candidate area. Meanwhile, we studied the kernel activity range of six rescue released Equus hemionus fitted with GPS satellite collars, tracking them from 2022 to 2024 in Kalamaili National Park candidate area. Finally, we combined camera trapping and GPS satellite data, and used the BIOMOD2 model to assess the suitable habitat distribution of species during the summer season, and evaluated the conservation gap within national park candidate area.

Results: The results showed that: (1) we obtained 5,996 independent detections of Equus hemionus at water resource during summer season. Among them, 2,825 independent-detections were recorded during the daytime, 2,212 in the nighttime, 459 in the morning and 500 at nightfall. (2) Equus hemionus exhibited random usage of water sites at nighttime (w_i= 1.32), daytime (w_i= 0.94), morning (w_i= 0.98) and nightfall (w_i= 1.07) in different time periods; the activity index at nighttime was slightly higher than in other three periods, with a peak activity period occurring between 23:00 and 04:00, while activity levels were relatively lower during the morning and nightfall periods; (3) the 50% kernel activity range was 4.98-162.18 km², with a mean of 76.34 ± 69.36 km²; the 95% kernel activity range was 27.67-2,117.72 km² with a mean of 892.95 ± 908.91 km²; (4) based on BIOMOD2 models, the suitable habitat area for Equus hemionus in Kalamaili National Park candidate area during summer was 1.94 × 10⁴ km², with 76.97% of the suitable habitat within national park candidate area boundaries.

Conclusion: Our study has preliminarily obtained the water resource utilization patterns, activity range and suitable habitat distribution of Equus hemionus in Kalamaili National Park candidate area. These findings enrich our understanding of behavioral ecology, and provide a scientific basis for developing conservation measures to protect the endangered species and their habitats in national park candidate area.

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%).

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: This study aims to systematically compile the species diversity of terrestrial mammals in Hainan Province, clarify the taxonomic status of certain species, and provide scientific references for the conservation and management of biodiversity in Hainan Province.

Methods: We systematically collected literature data on the classification and distribution of terrestrial mammals in Hainan Province over the past few decades. The study integrated field survey data, infrared camera monitoring data, and refers to the most recent references, including the Catalogue of Mammals in China (2024) and Diversity of China’s Mammals Inventory, Distribution and Conservation.

Results: The main results are as follows: (1) A total of 97 species of terrestrial mammals in Hainan Province, belonging to 9 orders, 26 families, and 61 genera. Chiroptera dominates, followed by Rodentia. (2) Among the 97 species, 6 are first-class nationally protected wild mammals, and 11 are second-class national protection. Additionally, 7 species are endemic to Hainan Province. According to the IUCN Red List (2021), 2 species are Critically Endangered (CR), 3 are Endangered (EN), 5 are Vulnerable (VU), and 6 are Near Threatened (NT). (3) From the perspective of faunal regions, 85 species belong to the Oriental realm, 9 species belong to the Palearctic realm, and 3 species are widely distributed. The Oriental realm accounts for 87.63% of the terrestrial mammal species in Hainan, showing absolute dominance. (4) A comparison with the 2009 revision of the mammal catalog of Hainan Island reveals 22 newly added species, including Chiromyscus langbians, Chiropodomys gliroides, Rattus andamanensis, R. exulans, Crocidura rapax, Eonycteris spelaea, Lyroderma lyra, Hipposideros pomona, H. pratti, Rhinolophus shortridgei, Miniopterus fuliginosus, Kerivoula furva, Harpiocephalus harpia, Murina aurata, M. eleryi, M. harrisoni, Myotis chinensis, M. davidii, M. horsfieldii, M. siligorensis, Pipistrellus pipistrellus, and P. tenuis. In contrast, 75 species listed in the previous catalog have been remained.

Conclusion: Through the compilation and updating of the terrestrial mammal species diversity in Hainan Province, our study provides foundational support for regional wildlife conservation and management efforts.

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.

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.

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 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.

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: The white-cheeked macaque (Macaca leucogenys), a primate species of the genus Macaca, is classified as a Class II National Protected Animal in China. It is a newly discovered mammal species, first identified and named by Chinese scholars in the Medog area in 2015. Due to its limited distribution range and small population size, research on the habitat suitability of Macaca leucogenys remains scarce.

Methods: To understand the distribution patterns of Macaca leucogenys, this study integrated infrared camera surveys and sample line data, with multiple environmental variables, including canopy height, human influence index (HII), normalized difference vegetation index (NDVI), elevation, aspect, slope, and 19 bioclimatic factors. We applied the MaxEnt model to systematically analyze the species’ current habitat distribution and key influencing factors within the Yarlung Zangbo Grand Canyon National Nature Reserve, Xizang. Additionally, we predicted habitat change trends based on the habitat conditions of the region under different future climate scenarios.

Results: (1) The MaxEnt models, fitted with the selected factors, achieved an AUC (area under the curve) value of 0.924, indicating a high level of prediction accuracy; (2) the key environmental variables affecting the current distribution of Macaca leucogenys were precipitation of wettest month (bio 13), human influence index (HII), temperature annual range (bio 7) and precipitation seasonality (bio 15); (3) under current climate conditions, the most suitable habitats for Macaca leucogenys are primarily concentrated in the experimental area of the Yarlung Zangbo Grand Canyon National Nature Reserve, with some high-suitability areas extending into Damu core area; (4) under future climate scenarios (SSP1-2.6 and SSP3-7.0) for the 2050s, the suitable habitat area for Macaca leucogenys is projected to increase compared to the current climate conditions.

Conclusion: This study provides theoretical and foundational data for understanding the current and future distribution of Macaca leucogenys, which is important for designing effective conservation strategies for this endangered species.

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.

Aims: Understanding the link between genetic diversity and species distribution is crucial for biodiversity conservation. Genetic diversity facilitates species’ adaptation to climate change, whereas area size results from the combined effects of climate change and species’ adaptive capacity. Under this context, climatic factors can be considered a pivotal link between genetic diversity and area size, exerting a regulatory influence on their relationship.

Methods: To assess the above hypothesis, the current study examined the cytochrome c oxidase subunit I (COI) gene fragment in avian species, exploring the influence of 8 climatic factors (annual temperature, annual temperature range, annual precipitation, annual precipitation range, precipitation seasonality, precipitation seasonality range, temperature seasonality, temperature seasonality range) on the relationships between haplotype diversity and area size, as well as nucleotide diversity and area size. Haplotype diversity and nucleotide diversity were utilized as principal indicators of genetic diversity in this analysis.

Results: Results show that the overall nucleotide diversity of birds was 0.008 ± 0.001(mean ± SE), and the haplotype diversity was 0.699 ± 0.011. Additionally, the results revealed that climatic factor differentially affect the relationship between genetic diversity and area size. Notably, climatic factor predominantly influence the relationship between haplotype diversity and area size indirectly by altering the area size (df = 6, χ²= 10.77, AIC = 2,231.8, BIC = 2,270.5). In contrast, for nucleotide diversity, the climatic factor exert a dual impact, affecting both the area size and nucleotide diversity, thereby mediating the relationship between nucleotide diversity and area size in a more complex manner (df = 0, χ² = 0, AIC = 2,155.0, BIC = 2,219.6).

Conclusion: Our results recommend that multiple genetic diversity indices should be considered when examining the effects of climate change on genetic diversity. Additionally, more targeted biodiversity conservation strategies should be developed to effectively address the challenges posed by future climate change.

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 & Aim: A high-quality checklist is essential for plant taxonomy, ecology, geography, and resource utilization studies. However, the checklist for Jilin Province has remained largely unrevised since the 1980s, which has seriously impeded related research. This paper attempts to obtain a credible province-wide checklist and county-level plant distribution data.

Methods: The TNRS (Taxonomic Name Resolution) was used to correct the spelling of scientific names. And the scientific name adopted the viewpoints in the Catalogue of Life China (2024). The checklist mainly refered to documents, i.e. Catalogue of Life China (2024), Key of Distribution Atlas of Northeast China Plant, 2nd edn, Flora of Jilin Province (Vols. 1-2), Atlas of Medicinal Plant Resource in the Northeast China, Distribution Atlas of Northeast China Plant, Flora Plantarum Herbacearum Chinae Boreali-Orientalis, Illustrated Flora of Northeast China, some articles and specimen data (from National Specimen Information Infrastructure (NSII), Global Biodiversity Information Facility (GBIF), NEFI, IFP) to locate the species distribution in county-level divisions.

Results: The checklist included 2,467 species (including 67 subspecies and 200 varieties) of tracheophyte in Jilin Province, belonging to 142 families and 728 genera, with voucher specimens available for 1,940 species. Among them, there are 21 lycophytes (2 families, 6 genera), 98 ferns (16 families, 40 genera; including 2 subspecies and 5 varieties), 21 gymnosperms (4 families, 9 genera; including 6 varieties), and 2,327 angiosperms (120 families, 673 genera; including 65 subspecies and 189 varieties). The most species-rich families are Asteraceae (75 genera, 260 species, including 7 subspecies and 9 varieties), Poaceae (65 genera, 182 species, including 12 subspecies and 11 varieties), Cyperaceae (14 genera, 148 species, including 1 subspecies and 11 varieties), Rosaceae (31 genera, 127 species, including 24 varieties), and Ranunculaceae (18 genera, 125 species, including 1 subspecies and 24 varieties). Other records are supported by reliable data. This checklist showed remarkable differences in species distribution among counties in Jilin Province. About 7 percent of 60 counties have more than 1,000 species, and the county-level distribution data were seriously imbalance.

Conclusion: The provincial checklist is reliable, but the quality of county-level distribution data needs to be significantly improved.

Aims: Understanding the spatio-temporal distribution of wildlife is crucial for the effective conservation of forest ecosystems. Studies on the spatio-temporal distribution patterns of wildlife provides key insights into ecosystem structure and function analysis, contributing to the precise formulation of conservation strategies and management plans. As a national second-class protected species, Tragopan temminckii plays an important role in maintaining forest ecosystem balance.

Methods: To explore the spatio-temporal distribution characteristics of Tragopan temminckii, a total of 83 infrared cameras were deployed at different periods from January 2011 to May 2019 in Wanglang National Nature Reserve (WLNNR). The optimized MaxEnt model, kernel density estimation, and one-sample t-test were applied to analyze the species’ suitability and activity rhythm from both spatial and temporal perspectives.

Results: (1) The potential suitable habitat area of Tragopan temminckii was 6,858 ha, accounting for 22.2% of the total area in WLNNR. (2) Vegetation was the main factor affecting the habitat distribution, while annual precipitation, mean temperature of driest quarter, and aspect were secondary factors. (3) Tragopan temminckii showed a typical diurnal activity pattern (diurnal-nocturnal index β > 13/24), and a unimodal pattern in daily activity rhythm (Φ = 17.777), peaking at around 11:00 AM. (4) There was no significant difference in the monthly daily-discrepancy index (α = 0.069 (t= -1.6847, df= 11, P > 0.05)) or in the diurnal-nocturnal index (β= 0.68 (t= -0.0764, df= 11, P > 0.05)). (5) Cold and warm season activity rhythms exhibited a moderate overlap (∆₄ = 0.78) but differed significantly (P < 0.01). During the cold season, peak activity occurred around 8:00 AM and 18:00 PM, whereas in the warm season, peak activity was delayed by 3 to 4 hours, occurring at around 11:00 AM.

Conclusion: The study identified vegetation as the primary factor influencing the spatio-temporal distribution of Tragopan temminckii, with climatic and topographical variables also playing significant roles. The species exhibited a diurnal activity pattern, with peak activity at noon, and its daily activity rhythm varied significantly with season, reflecting ecological adaptation strategies. By filling the knowledge gap of spatio-temporal ecological niche for Tragopan temminckii in WLNNR, this study provides a scientific foundation for future conservation and management within the reserve.

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.

Background & Aim: The SLOSS debate in the field of biodiversity conservation outlines whether single large protected area (SL) or several small protected areas (SS) are preferred for the conservation of species diversity, given equal total area or limited resources. This issue has been of great interest to ecologists and conservation biologists and has important implications for the design of protected areas and biodiversity conservation. As a result of the development of research methods and the rise of interdisciplinarity, the SLOSS debate has made important multi-stage advances in both analytical methods and theoretical mechanisms. The main objective of this paper is to review the rapidly research progress of the SLOSS debate and provide some targeted suggestions for future directions.

Review results: We first described the origins of the SLOSS debate and then analyzed the SLOSS literature from different aspects, including comparisons of publications between study regions and study times. Secondly, we described the analysis methods of the SLOSS debate and the strengths and limitations of each method. In addition, we reviewed the improved saturation indices proposed by previous researchers as well as the optimized indices developed by us. Thirdly, we explored several theoretical mechanisms that influence the SLOSS pattern, e.g, the theory of extinction-colonization dynamics dominated by extinction, the theory of extinction-colonization dynamics dominated by colonization, and the role of risk resistance. We then described how SLOSS debate can be applied to guide conservation management and protected area design. Lastly, we put forward some targeted suggestions for the future direction of SLOSS debate, including the importance of using flexible analytical methods, interdisciplinary collaborations to test theoretical mechanisms, more functional SLOSS and phylogenetic SLOSS research, and integrating the SLOSS debate with other fields such as restoration ecology.

Conclusion: Our review will be helpful to gain a deeper understanding of the progress of SLOSS debate, which is of great significance for promoting the development of this research field.

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 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 & 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.

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.