Biodiversity Research Research Articles

Communicating biodiversity research on YouTube: An experimental comparison of scientists and third-party presenters.

Online videos are a popular medium for science communication. These videos can be presented from many perspectives, including scientists sharing their own work or a third-party presenting research findings. A mixed between- and within-subjects experiment (n = 620) was conducted in the United States to assess the impact of narrative perspective on the communication objectives of increasing knowledge, changing perceptions, and influencing behavior related to bee diversity. Results indicate that watching a video presented by a scientist was associated with higher levels of perceived competence and a higher likelihood to mention a person or persons when recalling the video. However, we did not find significant effects of narrative perspective on knowledge gain and behavioral intentions to help support bee diversity.

The formation, maintenance, and loss of island biodiversity.

Due to the unique geographical features of large numbers, isolated by water and diverse formation histories, islands have become natural laboratories for ecological and evolutionary research. Islands have a high proportion of endemic species and disharmony in representing the species compared with that in the continent, which provides a good opportunity to explore the formation of island biodiversity. In this review, we focuse on island ecosystems and describes the progress of research in island biogeography in recent years from three aspects: formation, maintenance, and loss of island biodiversity. First, we take several representative island systems in the world as examples to introduce the formation mechanism of island biodiversity from species dispersal and immigration, population establishment and selection, species evolution and adaptive radiation. Based on the Equilibrium Theory of Island Biogeography, we then review the species-area relationship and species-isolation relationship and focus on the research progress in community assembly, including Diamond's rule, nestedness pattern, the framework of community structure of island biota, and species interactions on islands. We also discuss the high extinction risks of island species threatened from natural and human disturbances, especially from the impact of habitat loss and change, climate change, alien species invasion and the synergistic effect of these factors on the loss of island biodiversity. Finally, based on the status of island biodiversity, we summarized the current conservation practices for island biodiversity and possible research frontiers in island biogeographic studies.

AI-Powered Sustainable Environmental Practices using Laser-Induced Breakdown Spectroscopy (LIBS)

Technological advancements in artificial intelligence (AI) have the potential to lead the way in promoting sustainable environmental practices as well as support environmental sciences and biodiversity field studies and research. The research will focus on designing an innovative system architecture that integrates laser-induced breakdown spectroscopy (LIBS) with a robust machine learning (ML) framework, significantly advancing sustainable environmental practices, especially since LIBS offers rapid and precise multi-elemental analysis, while AI enhances data processing and predictive capabilities. As technological innovations advance, the integration of the suggested LIBS system and advanced AI will be pivotal in addressing environmental challenges and promoting sustainability. This paper presents LIBS analytical data used to qualitatively assess soil constituents as a case study.

Local and landscape factors differently influence health and pollination services in two important pollinator groups.

Agricultural management significantly affects insects, especially pollinators, which are crucial for crop pollination and biodiversity. In agricultural landscapes, various factors spanning different spatial scales are known to affect pollinator health, which, in turn, can influence pollination services. However, the importance of these factors in driving the health and performance of different pollinator groups remains unclear. Using a long-term biodiversity research platform, the German Biodiversity Exploratories, we investigated links between local and landscape-level land-use, health and pollination services in common pollinators, the bumblebee Bombus lapidarius and the syrphid fly Episyrphus balteatus, by measuring various traits as proxies for pollinator health and pollination services. Because of their different life histories, we expected the territorial bumblebees to be more vulnerable to land-use intensification at both spatial levels, compared with the migratory syrphid flies. Both land-use and environmental factors (climate) across spatial scales affected pollinator health, mostly via changes in body size: High land-use intensity reduced bumblebee body size, whereas higher ambient air temperature decreased syrphid fly body size. Increasing proportions of intensively managed areas at the landscape level decreased viral infections in both species. Additionally, landscape-level land-use and climate changed the bumblebees cuticular chemical profile, which is essential for communication in these social insects. Increasing land-use intensity at the local level and higher proportions of intensive land-use at the landscape level both had an indirect negative effect on pollination services in bumblebees via local flower cover and body size. Pollination services in both species were linked to body size. Thus, land-use factors affect pollinator health differently: bumblebees are more vulnerable to local and landscape-level land-use intensification, while syrphid flies are more resilient potentially due to their higher mobility. As pollinator health affects pollination services, our results indicate that land-use intensification poses a high risk to crops pollinated by species with small home ranges.

A faunal inventory of methane seeps on the Pacific margin of Costa Rica.

The methane seeps on the Pacific margin of Costa Rica support extensive animal diversity and offer insights into deep-sea biogeography. During five expeditions between 2009 and 2019, we conducted intensive faunal sampling via 63 submersible dives to 11 localities at depths of 300-3600 m. Based on these expeditions and published literature, we compiled voucher specimens, images, and 274 newly published DNA sequences to present a taxonomic inventory of macrofaunal and megafaunal diversity with a focus on invertebrates. In total 488 morphospecies were identified, representing the highest number of distinct morphospecies published from a single seep or vent region to date. Of these, 131 are described species, at least 58 are undescribed species, and the remainder include some degree of taxonomic uncertainty, likely representing additional undescribed species. Of the described species, 38 are known only from the Costa Rica seeps and their vicinity. Fifteen range extensions are also reported for species known from Mexico, the Galápagos seamounts, Chile, and the western Pacific; as well as 16 new depth records and three new seep records for species known to occur at vents or organic falls. No single evolutionary narrative explains the patterns of biodiversity at these seeps, as even morphologically indistinguishable species can show different biogeographic affinities, biogeographic ranges, or depth ranges. The value of careful molecular taxonomy and comprehensive specimen-based regional inventories is emphasized for biodiversity research and monitoring.

The biodiversity of ice-free Antarctica database.

Antarctica is one of Earth's most untouched, inhospitable, and poorly known regions. Although knowledge of its biodiversity has increased over recent decades, a diverse, wide-ranging, and spatially explicit compilation of the biodiversity that inhabits Antarctica's permanently ice-free areas is unavailable. This absence hinders both Antarctic biodiversity research and the integration of Antarctica in global biodiversity-related studies. Fundamental and applied research on biodiversity patterns, ecological structure and function, and options for conservation are reliant on spatially resolved, taxonomically consistent observations. Such information is especially important for modern, data-driven biodiversity science, in both Antarctica and globally, and forms the backbone of biodiversity informatics, reflected, for example, in the Darwin Core Standard used by the Global Biodiversity Information Facility. Biodiversity data are also essential to fulfill the conservation requirements for Antarctica, as set out in the Protocol on Environmental Protection to the Antarctic Treaty and inform the design of systematic surveys to address biodiversity and ecological knowledge gaps, for both specific taxa and ecosystems. Such surveys are key requirements for understanding and mitigating the impacts of environmental change on the region's biodiversity. Here, we address these requirements through the public release of The Biodiversity of Ice-free Antarctica Database. In 2008, we extracted a subset of biodiversity records only from terrestrial ice-free areas from the Scientific Committee on Antarctic Research (SCAR) Antarctic Biodiversity Database. We have subsequently added thousands of records from a range of sources: checking, and where necessary (and possible), correcting the spatial location, clarifying, cross-referencing, and harmonizing taxonomy with globally recognized sources, and documenting the original source of records. The Biodiversity of Ice-free Antarctica Database spans the early 1800s to 2019 (with most records collected after 1950) and represents the most comprehensive consolidation of Antarctic ice-free biodiversity occurrence data yet compiled into a single database. The Biodiversity of Ice-free Antarctica Database contains 35,654 records of 1890 species in over 800 genera across six kingdoms and spans all Antarctic Conservation Biogeographic Regions. These data are released under a CC BY Attribution License (http://creativecommons.org/licenses/by/4.0/).

Going down the rabbit hole: insight into the future of Paramecium (Ciliophora, Protista) biodiversity surveys

Paramecium, a research subject in many areas of life sciences, appeared to be a ciliate genus with a well known biodiversity structure. However, the understanding of its biological diversity has been evolving rapidly in recent years, driven by the discovery of new taxa and an expanded knowledge of the distribution of known species. Most future insights into Paramecium biodiversity are expected to come from molecular data, particularly through eDNA sampling. As one of the most recognisable microeukaryotes, commonly found in freshwater ecosystems, and with over a century of biodiversity research – including extensive reference data from GenBank records and living culture collections – Paramecium holds significant potential to become a model ciliate for studies in biodiversity and biogeography. This review addresses the challenges of species identification within the Paramecium genus, the current state of knowledge on its biodiversity and other factors that may shape future research. Despite some existing bottlenecks, new approaches to data acquisition and analysis will enable researchers to integrate diverse lines of evidence, allowing for exceptional explorations of Paramecium species and populations.

Моделювання поширення видів засобами MaxEnt: огляд і перспективи

Niche modelling of species has become increasingly important in the context of accelerating climate change and anthropogenic impacts on the biosphere. One such tool for predicting the potential distribution of species is the maximum entropy method (MaxEnt). This method is particularly valuable when working with biodiversity data collected from herbaria and museum collections, as such data typically only contain information about where a species has been recorded, rather than where it is absent. It is precisely this feature of MaxEnt that makes it an indispensable tool for biodiversity research based on historical data. This allows for the reconstruction of historical species ranges, the detection of changes in their distribution, and the forecasting of future trends, namely the prediction of potential ranges, the assessment of the impact of climate change and anthropogenic pressure, and the development of effective biodiversity conservation strategies. This article provides a brief overview of the MaxEnt software’s operating principle, its capabilities, and limitations. In particular, it analyses the impact of data quality on modelling results and considers various approaches to assessing the importance of ecological factors for species distribution. One of the key issues discussed in the article is the problem of sampling bias. Sampling bias arises because data on the presence of species are often collected non-randomly and depend on the accessibility of the locality, the interests of researchers, and other factors. This can lead to distortions in modelling results. Various methods can be used to correct these biases, such as the bias grid method and the background points method. Another important aspect is the choice of the territory for the background sample. It should be taken into account that when using projections where cells have different areas, MaxEnt may give incorrect results. The article also emphasises the need for cautious interpretation of modelling results. Assessing niche models solely based on AUC (area under ROC curve) can be misleading, therefore, for a more reliable assessment of variable importance, it is worth supplementing it with permutation importance and the jackknife method. Examples of modelling for various groups, including mammals of the Ukrainian fauna, were considered.

On the presence of Hipparchia parisatis (Kollar, 1849) in the Republic of Georgia (Lepidoptera, Nymphalidae, Satyrinae)

The first records of the highly distinctive Nymphalid species Hipparchia parisatis (Kollar, 1849) from the Republic of Georgia (Vashlovani Nature Reserve, hereafter VNR) are reported. The taxonomy and distribution of the species in the South Caucasus region are discussed, and the importance of the Vashlovani Protected Areas (hereafter VPA) as a hotspot for butterfly diversity in Georgia is emphasized. The report also highlights the importance of active collaboration, at the interface of web-based data recording platforms, between professional biologists and citizen science initiatives for the effective advancement of biodiversity research and conservation.

DNA Barcodes and Morphology Reveal Two New Species of the Genus Prochas Walkley, 1959 (Ichneumonidae, Campopleginae), from China.

DNA barcoding is an effective modern tool in taxonomy, evolutionary biology, and biodiversity research. Many new species have been discovered and described with DNA barcodes as part of their diagnostic features. We combined morphological examination and molecular species delimitation of the mitochondrial cytochrome c oxidase 1 (COI) gene using the automatic barcode gap discovery (ABGD) to investigate species boundaries. The genus Prochas Walkley (Hymenoptera, Ichneumonidae, Campopleginae) was first reported from China and is new for the Oriental and Eastern Palearctic regions. Using an integrative taxonomy method, two new species P. rugipunctata sp. nov. and P. striata sp. nov. are hereby described and illustrated. A key to the world species and a distribution map are provided.

Guidelines for species descriptions of free-living aquatic nematodes: characters, measurements and their presentation in taxonomic publications.

Free-living aquatic nematodes are abundant, diverse and of general environmental importance. However, knowledge of species distributions of both marine and freshwater nematodes is sparse. Species distribution data are crucial for evaluating environmental impacts from human activities and to conduct integrated nematode community assessments. Basic knowledge on taxonomy and species descriptions is lacking for many regions due to decreasing taxonomic expertise, yet it is essential for biodiversity research and for building molecular sequence libraries for the application of methods such as environmental DNA. In order to encourage and facilitate taxonomic and descriptive work on this understudied group, we present here a framework for nematode species description. We begin by providing a brief overview of nematology history, then provide suggestions of microscopic methods that should be used and provide a list of characters essential for morphometric species descriptions. Finally, we briefly discuss common molecular sequencing approaches that are commonly used in nematode taxonomic literature.

A New Bivalve Species Glauconome huangheensis of the Genus Glauconome J. E. Gray, 1828 (Bivalvia, Venerida, Cyrenoidea, Glauconomidae), from Shandong, China.

The family Glauconomidae has few species, limited molecular data description, and insufficient research attention. The biodiversity of Glauconomidae within China deserves further exploration. In recent years, the taxonomic status of Glauconomidae has undergone changes, and some studies have found a close relationship between Glauconomidae and the family Cyrenidae based on molecular data, suggesting that Glauconomidae should be classified under the superfamily Cyrenoidea. However, both domestic and international research has mainly focused on only four species of Glauconomidae, indicating an urgent need for more species data support. Recently, 46 specimens of Glauconomidae were collected in the Yellow River Estuary in Dongying City of Shandong Province in China. Through a comparative analysis of shell morphology and molecular phylogenetic analysis of COI and 16S rRNA, two species of Glauconomidae was discovered. One is Glauconome angulata Reeve, 1844, and the other is a new species of Glauconomidae found in the Yellow River, named Glauconome huangheensis sp. nov. The G. huangheensis sp. nov. exhibits distinct differences in shell shape and shell color compared to other species of Glauconomidae, resembling G. angulata. There are also significant differences in shell color, shell sculpture, ligament size, and shell thickness. Furthermore, the molecular phylogenetic analysis based on COI and 16S rRNA genes supports the validity of G. huangheensis sp. nov. as a species. It indicates a close phylogenetic relationship with G. angulata, making them sister species. This study provides a redescription of the morphological characteristics of G. angulata and G. huangheensis sp. nov., laying the foundation for the morphological classification, biodiversity research, and conservation of Glauconomidae species.

Can fieldwork driven by predictive species distribution models yield new rare or relevant geographic records? A case study with Neotropical snakes

AbstractUnderstanding species distribution patterns has been a major quest in biodiversity research. Due to their secretive habits and rarity, snakes have been historically underrepresented in assessments of geographic distribution range. In this work, we employ a pipeline for predictive model‐based species sampling, using Neotropical snakes as a model organism. We employ species distribution models based on verified point records for five candidate snake species of probable occurrence to Rio Grande do Sul state, Brazil: Apostolepis dimidiata (Jan 1862), Erythrolamprus aesculapii (Linnaeus 1758), Helicops leopardinus (Schlegel 1837), Lygophis meridionalis (Schenkel 1901), and Micrurus corallinus (Merrem 1820). Based on the resulting models, we conducted fieldwork on areas with higher overlap of suitable ranges and probability of new records. Our study yields a new state record of A. dimidiata to Rio Grande do Sul and highlights the usefulness of species distribution models in eliciting priority areas for faunal assessments.

Curating protected area-level species lists in an era of diverse and dynamic data sources

Dynamic yet accurate species lists for protected areas are essential for conservation and biodiversity research. Even when such lists exist, changing taxonomy, ongoing species migrations and invasions, and new discoveries of historically overlooked species mean static lists can become rapidly outdated. Biodiversity databases such as the Global Biodiversity Information Facility, and citizen science platforms such as iNaturalist, offer rapidly accessible, georeferenced data, but their accuracy is rarely tested. Here we compare species lists generated for two of the world's oldest, more famous protected areas – Yosemite National Park in California, United States and Royal National Park in New South Wales, Australia – using both automated data extraction techniques and extensive manual curation steps. We show that automated list creation without manual curation offers inflated measures of species diversity. Lists generated from herbarium vouchers required more curation than lists generated from iNaturalist, with both incorrect coordinates attached to vouchers and long-outdated names inflating voucher-based species lists. In comparison, iNaturalist data had relatively few errors, in part due to continual curation by a large community, including many botanical experts, and the frequent and automatic implementation of taxonomic updates. As such, iNaturalist will become an increasingly accurate supplementary source for automated biodiversity lists over time, but currently offers poor coverage of graminoid species and introduced species relative to showier, native taxa, and relies on continued expert contributions to identifications. At this point, researchers must manually curate lists extracted from herbarium vouchers or static park lists, and integrate these data with records from iNaturalist, to produce the most robust and taxonomically up-to-date species lists for protected areas.

Multi-Criteria Decision-Making Scenario Insights into Spatial Responses and Promotion Under Ecosystem Services

The Blue Economic Zone of the Shandong Peninsula is located in the transitional zone between land and sea, with a complex ecological environment. The determination of hot and cold spots in various ecosystem services is crucial for the coordinated development of ecosystem services and the optimization of the spatial pattern of the ecological environment. This study, based on natural and socio-economic data, utilizes various ecological models to simulate water yield (provisioning service), carbon sequestration (regulating service), biodiversity (supporting service), and aesthetic and scientific research values (cultural service). Using a multi-criteria decision-making approach, it identifies hot and cold spots of ecosystem services in different development–conservation scenarios. Combining the protection efficiency of different areas, it proposes a spatial pattern promotion scheme. The research indicates significant spatial differences in ecosystem services without clear trade-offs and synergies. Changes in the weights of ecosystem services in 11 scenarios result in significant differences in hot and cold spots. Compared to the neutral scenario (S6), the distribution of hot and cold spots in protection scenarios (S1–S5) is relatively scattered, while in development scenarios (S7–S11), hot spots show an increasing trend of concentration in the southeast, with cold spots scattered in the west and northwest. Four spatial pattern promotion schemes are proposed based on protection efficiency and policy preferences. Promotion areas should focus on ecological restoration and improvement to raise local ecosystem service levels. Protection areas should emphasize maintaining their existing high-level ecosystem services to achieve a synergistic enhancement of various ecosystem services.

Enhancing Plant Species Retrieval in Flora Through Language Model Integration

Traditionally, textual data storage and retrieval systems were designed primarily for human reading, mainly relying on paper records. However, as information technology has advanced, computerized searches have become common. However, Boolean logic-based data retrieval systems often struggle to handle data's diversity and richness effectively. These systems rely on strict matching rules, which can lead to either too few or too many results. For example, when searching for plant species descriptions, a query like "circle" AND "ellipse" may exclude relevant records that describe these traits using slightly different terms (e.g., "round" or "oval"). Conversely, broader queries like "oblong" may return an overwhelming number of irrelevant results. This rigidity limits the system's ability to adapt to the nuanced and varied ways users describe data. With the advent of advanced semantic models such as SBERT (Sentence-Bidirectional Encoder Representations from Transformers) (Reimers and Gurevych 2019), we can now delve deeper into the semantic relationships within textual data. Unlike general-purpose large language models, SBERT is specifically designed for efficient semantic similarity computation. In plant taxonomy, records in Flora, such as Flora of Taiwan or Flora of China, play a crucial role in understanding plant diversity in specific regions. These records provide critical information on plant growth environments, morphological characteristics, and economic values. Our research aims to enhance the efficiency of retrieving plant data using language models. Specifically, we transform textual descriptions from Flora and user queries into vector representations (Fig. 2) and calculate their cosine similarity to determine the relevance between user inputs and species records. Cosine similarity, a metric commonly used in text mining and information retrieval, quantifies the similarity between two vectors by measuring the cosine of the angle between them. The similarity score ranges from -1 (completely dissimilar) to 1 (identical), where higher scores indicate greater similarity. By applying this method, we can provide users with ranked scores of plant species related to their queries (Fig. 1). This approach not only streamlines data retrieval but also introduces new perspectives for botanical research and data management, fostering a more efficient exploration of plant diversity. Our results demonstrate the potential of language models to facilitate biodiversity research and data management, especially in retrieving plant taxonomy information. Our approach provides a novel tool for future biodiversity data analysis and retrieval, thereby contributing to the progress of biodiversity conservation.

A Portable Photocollector for the Field Collection of Insects in Biodiversity Assessment.

Arthropod biodiversity research usually requires large sample collections. The efficient handling of these samples has always been a critical bottleneck. Sweep netting along transects is an effective and commonly used approach to sample diverse insects. However, sweep netting requires the time-consuming task of sorting insects from the large amounts of debris and foliage that end up in the sweep net along with the insects. To address this, we introduce a robust, portable, and inexpensive photocollector device with an LED light source to extract insects from sweep net samples in a standardized way. Timed field trials tested the photocollector's efficiency in extracting live insect samples from debris, focusing on Hymenoptera and Diptera. We found that 73% (±13%) of undamaged specimens moved toward the collection bottle within the first hour and 79% (±13%) after four hours. Of the insects failing to move after four hours, most (81%) were damaged and likely unable to move. Accounting only for undamaged specimens, 83% (±11%) moved after 1 h and 90% (±11%) moved after 4 h. We found significant differences in when families of Hymenoptera and Diptera moved. We suggest that the photocollector can be a useful tool in standardized biodiversity assessments.

The discovery of an overseen pygmy backswimmer in Europe (Heteroptera, Nepomorpha, Pleidae)

The Pleidae, or pygmy backswimmers, is a family of aquatic bugs (Hemiptera, Heteroptera, Nepomorpha) containing four genera. Here, we describe Plea cryptica sp. nov. and redescribe its sister species, Plea minutissima Leach, 1817. Whereas the morphological distinction of these closely related species is only possible for males, molecular data clearly separate them. As part of our taxonomic study, we provide comprehensive molecular data including more than 200 DNA barcodes from all over Europe, complete nuclear ribosomal DNA, full mitochondrial genome data, and 3D scans for both species. Furthermore, the same molecular markers are also presented for Neoplea striola (Fieber, 1844). We used Maximum Likelihood (ML) analyses to reconstruct the phylogeny of the Pleidae and Notonectoidea based on available mitogenomic data. Our study represents a successful implementation of the proposed concept of taxonomics, using data from high-throughput sequencing technologies for integrative taxonomic studies, and allowing high confidence for both biodiversity and ecological research.

Instagram data for validating Nothofagus pumilio distribution mapping in the Southern Andes: A novel ground truthing approach

The availability of valid, non-biased species occurrence data has always been a major challenge for biodiversity research and modelling studies. Data from open-source databases or remote sensing are promising approaches to increase the availability of species occurrence data. However, these data may contain spatial, temporal, and taxonomic biases or require ground truthing. In recent years, social media has received attention for its contribution to species occurrence data sampling and ground truthing approaches. The wide reach of social media platforms allows for rapid and large-scale analyses. Here we introduce a novel Instagram ground truthing approach to validate the occurrence mapping of Nothofagus pumilio across its entire distribution range. The treeline species of the southern Andes has been extensively studied in small-scale studies, but large-scale modelling approaches are largely missing due to limited accessibility to treeline sites resulting in a lack of occurrence data. The content posted on the social media platform Instagram consists of images and videos in which the species N. pumilio and its location can be identified. By searching for suitable posts using hashtags and location tags, we created 1238 Instagram ground truthing points. We compared the performance of our dataset with open-source data from the Global Biodiversity Information Facility (GBIF) through visual, quantitative, and bias analyses, acknowledging that both social media-based and Citizen Science data are subject to sampling and spatial biases due to collection in human-accessible areas. The Instagram ground truthing points were subsequently used to validate remote sensing occurrence data, generated using Sentinel-2 level 2A data and Supervised Classification. The combined approach – Instagram ground truthing and remote sensing – allows for the collection of occurrence data over the entire latitudinal range of N. pumilio, covering approximately 2000 km. The use of social media content provides potentially important contributions to species occurrence data sampling and ground truthing In our study we introduce a novel ground truthing approach for species occurrence data sampling based on Instagram data Instagram ground truthing points, combined with Supervised Classification generate species occurrence data of Nothofagus pumilio over its entire distribution range in the southern Andes The performance of the Instagram ground truthing points is evaluated by comparison with existing data from the GBIF database. Our Instagram ground truthing approach demonstrates a new way of sampling species occurrence data and can be applied to other suitable species and study areas.

Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2025.

The National Genomics Data Center (NGDC), which is a part of the China National Center for Bioinformation (CNCB), offers a comprehensive suite of database resources to support the global scientific community. Amidst the unprecedented accumulation of multi-omics data, CNCB-NGDC is committed to continually evolving and updating its core database resources through big data archiving, integrative analysis and value-added curation. Over the past year, CNCB-NGDC has expanded its collaborations with international databases and established new subcenters focusing on biodiversity, traditional Chinese medicine and tumor genetics. Substantial efforts have been made toward encompassing a broad spectrum of multi-omics data, developing innovative resources and enhancing existing resources. Notably, new resources have been developed for single-cell omics (scTWAS Atlas), genome and variation (VDGE), health and disease (CVD Atlas, CPMKG, Immunosenescence Inventory, HemAtlas, Cyclicpepedia, IDeAS), biodiversity and biosynthesis (RefMetaPlant, MASH-Ocean) and research tools (CCLHunter). All resources and services are publicly accessible at https://ngdc.cncb.ac.cn.