Blockchain Papers

Sibelle Torres Vilaça, Alexandre Aleixo, Juliana A. Vianna

The biodiversity crisis is accelerating, with recent IUCN Red List confirming multiple recent species extinctions (IUCN, 2025). Of the 17 megadiverse countries, which account for ~70% of Earth's biodiversity, 15 are part of the Global South. Most of the habitat and biodiversity loss is concentrated in nine of the megadiverse countries. Generating knowledge for all life on Earth is fundamental for bending the curve of biodiversity loss, and genomics has recently emerged as an important component in conservation biology. Mapping and understanding genome-wide variation can help estimate important biological variables essential for species conservation, understanding adaptation to climate change, and predicting populations' long-term resilience (Vilaça et al., 2024).Genome sequencing has ramped up in the last decade as the costs drop and technology advances (Wetterstrand et al, 2025). The Earth BioGenome Project (EBP) is capitalizing on this in its aim to sequencing the genomes of all known eukaryotic species. The lead article by Blaxter et al., (2025) paves the way for Phase II of the EBP, which aims to sequence reference genomes for 150,000 species throughout the tree of life. With an estimated cost of US$ 1.1 billion (US$4.42 billion for all 3 phases) Phase II will bring important developments in technology for data production and processing, while establishing sequencing centers worldwide. Although these accomplishments are set to change the way we do biodiversity genomics research globally, we believe that major challenges need to be overcome for the project to accomplish its goals and truly reach equitable partnerships and effective engagement with the Global South. Bringing our significant experience as researchers involved in EBP-affiliated initiatives based in South America, we address potential blockers for Phase II in the Global South in sequencing infrastructure and technology, funding sources, enabling equitable global participation, and engaging government and policy makers.Sequencing life on Earth requires global participation, especially in biodiversity-rich regions. A solution proposed by Blaxter et al., (2025) involves the creation of decentralized laboratories (gBox) established at 25 regional nodes. This model is based on the approach used in outbreak response for pathogen detection like COVID-19. While laboratories for rapid response to disease outbreaks require a Biosecurity Level 3/4, the general infrastructure (Affara et al., 2021) is typically simpler in terms of equipment than the laboratories required for sequencing reference genomes. In our experience, maintaining sequencers in countries where few or no other similar equipment is available is challenging due to the lack of specialized and timely maintenance. The reliance on imported reagents from the Global North can further undermine efforts because of common cold-chain failures that often lead to reagents not arriving at their destination with the required integrity for optimal use (Vilaça et al., 2024). The current limitations in technology, maintenance, importing reagents, and keeping sample integrity are important obstacles that need to be overcome for the gBox model to work in countries without a tradition in genomic sequencing.Securing adequate funding remains a key issue. During the SARS-CoV-2 pandemic, rapid funding availability by governments and the private sector allowed investments of USD$9.2 billion in vaccine development (Tortorice et al., 2024) generating trillions in social, health, economic revenue. The same model is needed for biodiversity. With an estimated global cost of €14 trillion in ecosystem services associated with biodiversity loss until 2050 (ten Brink et al., 2009), this loss will bring severe impacts on health, economy and social well-being. Unfortunately, this sense of urgency is not yet instilled in funding priorities and financial investments. In our experience, this is a general pattern of biodiversity-related science funding, as both the Chilean and Brazilian governments have invested in large facilities for astronomy and physics (Catanzaro et al., 2014;Angelo, 2017). Environmental expenditures by governments decrease in times of recession with some countries failing to include biodiversity agendas in their post-COVID economy recovery packages (McElwee et al., 2020). Because reference genomic libraries are key for supporting the monitoring of endangered species and developing local bioeconomy initiatives, wider investments focused on biodiversity knowledge are necessary for its conservation and recovery. The creation of a global public-private co-funding mechanism similar to the recently established Tropical Forests Forever Facility (TFFF) -aimed at compensating financially countries that commit to preserving their tropical forests (https://www.wri.org/insights/financing-nature-conservation-tropical-forest-forever-facility) -could be explored as an alternative to support sequencing efforts in megadiverse countries. Under such a co-funding mechanism, Global South countries would find mechanisms for matching at least some percentage of the external funding that is brought into the country for biodiversity genomics in several alternative ways.We view this as an important step to root perennial biodiversity initiatives in their Global South countries' own territories. These mechanisms could include institutional commitments (e.g., integration into national biodiversity and bioeconomy agendas) and recurrent budget lines supporting the development of local biological collections, biobanks, and molecular biology laboratories, in addition to genomics expertise.Achieving the goals of Phase II of the EBP will require more than advances in sequencing technologies and expanded reference databases; it will require structural changes that enable equitable global participation and governance. Researchers based in megadiverse countries cannot be relegated to sample providers (Vilaça et al., 2024), but need to be embedded in decision-making, generate data locally, and contribute as skilled personnel.Therefore, it is important that EBP-Phase II -in addition to direct efforts to reference genome sequencing proper -also include the training of local researchers in genome sequencing, assembly, curation, and annotation to overcome the capacitation gap in genomics found nowadays in Global South countries.First, the involvement of Global South scientists within the EBP must extend to decision-making and leadership roles that reflect the contribution of the communities within megadiverse countries. Other critical roles include setting local priorities in terms of species to be sequenced and linking locally generated genomes with national research, development, and innovation agendas, as done in the Genomics of Brazilian Biodiversity (GBB) consortium (Vilaça et al., 2024;Povill et al., 2025). Recently, Latin American countries started organizing an EBP node (Red de Genomas Neotropicales -BioGenomas) with country representatives sharing experiences, realities and local models for sequencing projects with reduced financing support. Brazil and Chile began coordinating meetings with scientists from Argentina, Colombia, and Mexico. Since then, Argentina has set the first framework for a national biodiversity genomics consortium. In our model, organizing under nationwide initiatives, followed by a larger network is the first step to ensure that regional and local realities are represented and considered. Other approaches can also be used as models, like the African BioGenome Project, which started as a continent-wide initiative.Second, the feasibility of decentralized sequencing infrastructure-such as the proposed gBox-must be carefully evaluated within the context of countries facing recurrent challenges in importing reagents, maintaining equipment, and ensuring reliable cold-chain delivery. These barriers remain major bottlenecks that cannot be overlooked when deploying high-throughput sequencing technology globally. The establishment of the proposed US$0.5 billion Foundational Impact Fund (FIF) in Phase II is therefore essential. By focusing support on capacity development and long-term infrastructure in the Global South, the FIF could catalyze sustainable growth in biodiversity genomics rather than short-term or project-bound grants. Decentralized funding models, unconstrained from politically-bound research agendas are crucial for the EBP hubs to dictate research direction considering local aspects. In this way, we can focus on local solutions to solve global problems.In many Global South countries, the acquisition of reagents is hindered by persistent failures in maintaining the required cold chain during importation, customs delays, and the lack of reliable distributor networks. These issues lead to frequent reagent degradation and increased costs that slow down or halt genomic workflows. There is a pressing need for supply chains that support room temperature reagents to preserve, high-quality samples.Legal uncertainties, the absence of standardized national frameworks, and administrative bottlenecks further constrain access and sharing of biological samples. Creating and supporting existing local biodiversity biobanks, possibly associated with natural history collections, is also important for access to high-quality well-documented samples for genome sequencing. Addressing these challenges requires coordinated technological advances, policy development and long-term engagement with keystone local institutions.Third, a critical step toward enabling equitable participation in EBP's Phase II is transforming how political leaders and policymakers engage with biodiversity science. They must recognize that the biodiversity crisis is as urgent as climate change or future pandemics, and that delaying action will have profound consequences. The ongoing discussions in international policy like the Convention for Biological Diversity highlight a timely opportunity: biodiversity genomics must be integrated into global and national environmental agendas as a strategic tool for conservation, climate adaptation, and sustainable development.Genomic resources are not only essential for monitoring and protecting biodiversity, they also underpin emerging bioeconomy value chains, biotechnological innovation, and preparedness for future biological emergencies.Importantly, national public policies for genetic-resource protection-including implementation of the Nagoya Protocol and emerging approaches to Digital Sequence Information (DSI) benefit sharing-are key to enabling local sequencing and ensuring that local researchers remain central. Countries need legislation that not only regulates the use of genetic resources but also actively encourages and funds local sequencing, capacity development, and equitable scientific leadership. This will enable Global South researchers and governments to play active roles in international agreements, boosting their confidence in becoming equitable partners in biodiversity genomics initiatives, rather than adopting a defensive attitude to avoid any undue use of the countries' genomic resources.As biodiversity loss accelerates, investments in biodiversity genomics should not depend solely on academic enthusiasm; they must be recognized as essential national and global priorities, with clear economic, health, and societal implications. To realize this vision, policymakers should no longer be considered as "stakeholders". They must become active partners in the co-creation of genomic initiatives (see Vilaça et al. 2024). Co-designing strategies with governments ensures that genomic data are incorporated into national priorities, that legal frameworks evolve in tandem with scientific advances, and that investments in infrastructure and capacity remain stable across political cycles. This shift is especially critical for megadiverse countries, where genomic knowledge can directly inform sustainable resource management, climate resilience, and health surveillance systems. By integrating scientific, political, and community perspectives, the EBP Phase II can become not only a global sequencing effort but a transformative movement toward a more inclusive, resilient, and strategically valuable model of biodiversity science.Author contribution

Rob J. Lewis, Jonas Lembrechts, P. D. Walker, Chunli Li · 5 authors

Background and Rationale Despite decades of progress in ecological monitoring, primary biodiversity and environmental data remain unevenly mobilised and poorly interoperable (Hampton et al. 2015, Poisot et al. 2019). Datasets, often gathered with public funds, frequently remain inaccessible or insufficiently described, limiting their reuse in global syntheses (Culina et al. 2018). Ecologists’ concerns about trust, transparency, and control of shared data persist, particularly where data production is resource-intensive or socially embedded. These concerns echo the foundational properties of distributed ledgers, where ownership and governance are distributed across peer networks rather than centralized repositories (Lewis et al. 2023). Forests exemplify both the potential and the challenge of such decentralised infrastructures. As globally significant carbon and biodiversity reservoirs, forests are also deeply fragmented across ownership and jurisdictional boundaries. In Europe alone, over half of forested land is privately owned, yet these actors often lack mechanisms to derive tangible value from stewardship. At the same time, digital twins (macroecological models) that integrate in situ and remotely sensed data, are becoming central to forest policy and monitoring frameworks (e.g., Food and Agriculture Organization of the United Nations (FAO), Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), Global Biodiversity Framework (GBF)). ForestWeb3 (FW3) hypothesizes that a decentralised, Findable Accessible, Interoperable, Reusable (FAIR; Wilkinson et al. 2016, Nosek et al. 2022)-aligned data network can unlock the latent value of underused biodiversity data while building trust and incentives for participation.. Objectives Mobilisation and harmonisation of forest biodiversity and environmental data (Objective 1): to spearhead a shift from data curation to data stewardship through a decentralised data infrastructure built on open-source blockchain frameworks. Incentivisation and uptake (Objective 2): to design transnational pathways through which private forest owners and local communities can be economically rewarded for verifiable ecological data via nature-backed digital assets and ReFi mechanisms. Together, these objectives align technical innovation (Objective 1) with behavioural and economic motivation (Objective 2), establishing the groundwork for distributed biodiversity observatories capable of sustaining long-term ecological data flows. Methodological Approach WP 1 develops a blockchain-based data ledger with smart contracts that autonomously manage data registration, access control, and reuse. Metadata and identifiers are immutably recorded on-chain, while primary datasets remain decentralised on contributor-managed nodes. This architecture enables contributors to retain data sovereignty while ensuring transparency and traceability in reuse transactions. WP 2 extends the infrastructure to real-time environmental sensing through the integration of modular Internet ofThings (IoiT)-based microclimate sensors. These devices stream environmental data at high temporal resolution directly into the distributed ledger, forming a Decentralized Physical Infrastructure Network (DePIN) for ecological data. WP 3 links these data streams to the creation of digital twins of forest ecosystems, combining in situ biodiversity observations with satellite and climate datasets to model ecosystem integrity. These models underpin the valuation of nature-backed digital assets, a form of tokenised evidence for ecological performance, providing the data foundation for voluntary biodiversity and carbon markets. Finally, WP4 investigates forest owners’ perceptions, motivations, and barriers to adopting regenerative finance (ReFi)-based conservation mechanisms. Through interviews and a pan-European survey, it explores how varying sociocultural and institutional contexts shape engagement with emerging biodiversity credit schemes, drawing parallels to established Payment for Ecosystem Services frameworks (Kaiser et al. 2021). Significance and Legacy FW3 exemplifies the convergence of data decentralisation, digital sensing, and regenerative economics, a triad capable of transforming how ecological knowledge is produced, verified, and valued. By embedding data provenance and attribution within the infrastructure itself, we addresses long-standing issues of trust and recognition in ecological data sharing. Its incentive mechanisms offer pathways to decouple conservation finance from traditional public funding, potentially scaling stewardship and democratizing data mobilisation across millions of hectares of privately owned forest land. The project’s legacy lies in demonstrating that data infrastructures can be both scientific and economic commons, capable of sustaining biodiversity monitoring through distributed participation. Beyond its immediate technical deliverables, ForestWeb3 contributes to a broader vision of dynamic, self-sustaining ecological data ecosystems that power both global biodiversity frameworks and locally grounded conservation action.

Cristian Barros‐Diaz, Abel Gallo‐Pérez, Manuel Chiquito, Pamela León · 7 authors

The Cordillera Chongón Colonche, part of the Tumbes-Chocó-Magdalena biodiversity hotspot, is known for its abundance of endemic species. Our research was conducted in six protected areas, including mature and secondary forests. We utilized a grid of camera traps spaced at an average distance of 1.2 km, totaling 8819 camera-days. The data yielded 5413 independent events which recorded 29 species of mammals, including 23 native and six introduced species. Based on the documented diversity, conservation status of native mammals, and anthropogenic pressures, we propose the Cordillera Chongón Colonche as a priority area for mammal conservation in western Ecuador. This study provides updated information on mammal presence in the area and represents the first systematized camera-trap study along the mountain range. Furthermore, we strongly recommend the development of a comprehensive management plan for the mountain range. This plan would enhance existing conservation strategies in certain communal forests while also facilitating the reconnection of the mountain range with the Chocó Region. To achieve this, we advocate for the implementation of participatory projects involving local communities, decentralized autonomous provincial and cantonal governments, and non-profit organizations actively working in the area. This collaborative approach would create synergies, fostering more effective and sustainable conservation efforts.

Rob J. Lewis, Kjell‐Erik Marstein, John‐Arvid Grytnes

Research centred on understanding scientists’ attitudes towards open data in ecology and evolution point to an increased acceptance of and willingness to engage in open data practices 1 , 2 , but also identifies common threads of concern which present barriers to data sharing . Mindsets concerning data as proprietary are common 3 , especially where data production is resource intensive 4 . Fears of competing research in concert with loss of exclusivity to hard earned data are pervasive 1 , 5 , 6 , 7 . This is for good reason given that current reward structures in academia focus overwhelmingly on journal prestige and high publication counts 8 , and not accredited publication of open datasets. And, then there exists reluctance of researchers to cede control to centralised repositories, citing concern over the lack of trust and transparency over the way complex data are used and interpreted 6 , 9 , 10 .

Shenghui Cheng, Yue Zhang, Xiaofei Li, Lin Yang · 6 authors

Truth must be told, but not much—a hybrid society of real and virtual is coming. Metaverse,1Cheng S.H. Metaverse: Concepts, Technologies and Ecology. China Machine Press, 2022Google Scholar rise recently, is attracting significant attention from academia to industry. A metaverse is a network of three-dimensional (3D) virtual worlds focused on social connection. Bearing the outbreak of the coronavirus 2019 pandemic, people are physically isolated, which triggered the growth of the metaverse. Different from existing work, this commentary targets the roadmap of the metaverse from an artificial intelligence (AI) perspective. First, we blueprint a roadmap for this digital cyberspace transformation, including immersion creation, hardware support, text interpretation, audio processing, connection construction, economy operation, and security protection. Second, at each phase of the roadmap, we address the status as well as the advanced technologies to provide in-depth views accordingly. The whole pipeline is illustrated from an AI2Xu Y.J. Liu X. Cao X. et al.Artificial intelligence: a powerful paradigm for scientific research.Innovation. 2021; 2: 100179Scopus (114) Google Scholar perspective, as shown in Figure 1, and we believe that AI is playing an increasingly important role in core techniques toward this technological singularity. Immersion creation refers to the technique that provides human beings with immersive feelings by constructing a 3D virtual world. Inspired by computer vision, graphics, and visualization techniques, immersion creation includes generating virtual scenes in the metaverse and displaying them to end users. AI has revolutionized these techniques recently. For instance, the scene generation process has been significantly speeded up to nearly real time. However, the scenes generated by these computer-vision-based methodologies are limited by the pre-defined elements used in AI algorithms, which would preclude the immersive feeling of human interaction with a digital human in the metaverse since these elements are different from the real ones, but we desire both parties to share the same scene and thus the same feeling of the environment. This brings challenges in sensing, sampling, and scene generation in the metaverse. One solution is to capture real scenes and use those images or videos to generate new ones and update the scenes in the metaverse with a short period of time, possibly in real time eventually. To this end, computational imaging has provided a promising solution to capture scenes efficiently in a low-cost, low-bandwidth manner;3Altmann Y. McLaughlin S. Padgett M.J. Goyal V.K. Hero A.O. Faccio D. Quantum-inspired computational imaging.Science. 2018; 361: 6403https://doi.org/10.1126/science.aat2298Crossref Scopus (119) Google Scholar along with AI, computational imaging may develop rapidly in metaverse-related applications in the future to provide a higher sense of immersion. Hardware denotes the end-user devices, such as the brain-computer interface, robotics, and virtual reality or augmented reality headsets as well as glass-free 3D devices, which determine the quality of the user’s immersive experience. These devices have been revolutionized many times in history;4Lee L.K. Braud T. Zhou P.Y. et al.All one needs to know about metaverse: a complete survey on technological singularity, virtual ecosystem, and research agenda.arXiv. 2021; (Preprint at)https://doi.org/10.48550/arXiv.2110.05352Crossref Google Scholar taking the AR headset as an example, it was designed from macro- to micro-optics and now is heading toward nano-optics, and the size has been reduced dramatically. However, one main challenge is the design of large-scale diffractive devices used in glasses, and AI is now helping with and speeding up the design in a number of ways, from accelerating the iterations to proposing new solutions. The AI accelerator, such as neural-inspired AI chips, designed to accelerate AI and its applications, is growing tremendously now and will evolve to task-specific chips to be used in the metaverse. We believe this is a trend in optical or other devices’ design and is not limited to the metaverse. Text interpretation regards to text generation and text for communication purpose. The metaverse brings convenience for recording activities in business and social life, which potentially facilitates the role of natural language processing,5Zhang Y. Teng Z.Y. Natural Language Processing: A Machine Learning Perspective. Cambridge University Press, 2021Crossref Google Scholar a research domain widely supported by AI. Most natural language processing applications in the metaverse focus on personal assistance and business meeting analysis: from the personal side, new dialogue systems could benefit book-keeping of social activities, enabling a personal assistant to give clear instructions, and from a business perspective, it keeps track of meeting minutes, where AI algorithms generate summaries and answer questions concerning specific details. However, in a hybrid society, how to communicate with people of different backgrounds even living in different eras could be an interesting AI-powered application. Audio processing aims for the rendering of auditory immersion. Voice is considered one important interface for humans to enter the metaverse, and it is also the main interaction model between entities (avatars, digital humans, or even non-human objects) in the metaverse. Voice processing consists of two major tasks: automatic speech recognition and text to speech (or speech synthesis), which transforms voice signals to text, or vice versa. Together with the language-understanding techniques, automatic speech recognition and text to speech enable entities in the metaverse to understand the message and intention of others and to speak as if they were in the real world. In addition, audio signals could be rendered as binaural signals, from which humans can sense the location of the sound source and the presence of an enclosed space; in other words, to have the sense of auditory immersion. For auditory immersion in the metaverse, many challenges need to be further overcome, such as separating metaverse sound from real-world sound, customized speech synthesis, complex 3D soundscape generation, etc., which highly rely on advanced signal-processing and machine-learning techniques. Sound is ubiquitous in the metaverse, and we believe that AI is playing a leading role in audio management in the metaverse. Connection construction in the metaverse includes network connection and social construction to get connected with others. Network connections require high-speed network to transfer massive amounts of data, accounting for the obstacles in latency, bandwidth, and consistency. AI overcomes the obstacles in various aspects including traffic planning, routing and classification, congestion control, quality of service, and quality of experience management. After being networked, the society emerges but faces challenges like behavior communication or community management. AI is capable of optimizing social group management by matching people with their desired communities so that the whole society will be divided spiritually rather than physically. As the core purpose of the connection, social activity is a requisite of some recognition techniques, such as face recognition for meeting people and gesture recognition for behavior interaction, as well as pose tracking, texture restoration, and blur correction—all of which are common cases where AI excels. Economy operation is for exchanging virtual goods through a blockchain digital system. With the exponential growth of virtual economy, some challenges have arisen, like large-scale asset management and fraudulent-transaction detection. AI empowers the virtual economy by generating and managing digital assets, monitoring transactions among huge databases, and more. New classifiers and mechanisms supported by AI verify the authenticity of transactions via a decentralized blockchain infrastructure to improve security posture. AI-generated non-fungible tokens and AI-assisted asset tagging increase the efficiency of asset generation and management. In the future, AI can build a more reliable technology-based virtual economy system. Security protection corresponding to the security framework and privacy protection becomes extremely challenging when tremendous virtual devices are connected. This connection is not that reliable and gives space to get attacked, e.g., identity theft and spying, which are common problems that security faces. To be protected, the security system has to require frequent authentications when accessing the service related to virtual devices, which results in time-consuming and other problems. New mechanisms are demanding for authentication with alternative modalities, such as biometric authentication driven by muscle movements or eye gazes, as well as seamless authentication. None of these would happen without AI. Moreover, countless activities and interactions are recorded, creating a crisis of personal privacy. AI is capable of privacy protection through algorithms that automatically and dynamically detect user privacy preferences from diverse contexts in the metaverse. An AI-powered security system will emerge in the metaverse. Besides, other techniques like robotics, cloud computing, the Internet of Things, and decision-making are also important components for the metaverse. Likewise, AI also contributes significantly to them—for example, with the help of reinforcement learning, decision-making demonstrates great potential since it enables AI to make decisions through huge amounts of data with various factors and has now become a new trend. AI not only advances the above technologies but is itself evolving rapidly. Current components such as immersion creation and hardware techniques are not really “intelligent” by themselves but are composed “sensing/sampling + AI algorithms” to claim to be intelligent. Looking forward, the next step of AI in the metaverse should move from “make the hardware intelligent by AI algorithms” to “build intelligent hardware by AI algorithms,” where the latter is a hybrid mode and focuses on end-to-end solutions. In this solution, other important techniques in AI such as reinforcement learning, federated learning, and few-shot learning will probably lead to new revolutions. A new era driven by AI is emerging. The digital human produced by AI will increase dramatically, and a digital second life is appearing—a society combined with real and digital humans is launching. It is likely that other species or organisms will be reborn and that a “creator-verse” will turn up. Immortal technology—living forever—will eventually become true. At the current stage, it is more from the inorganic side where everything is generated with digital computers; however, the society will continue, and people will eventually reach the third-verse or even the multi-verse, where the organic world and the inorganic world may merge. AI will speed up this revolution. We would like to thank the support from the Research Center for Industries of the Future (RCIF) at Westlake University, Westlake Fundation (2021B1501-2) and the funding from Lochn Optics. The authors declare no competing interests.

Samuel J. Bolton, JOSEPH R. CORA

Describing a substantial proportion of the world’s species could be made much easier by the 3D digitization of collections, which would facilitate the dissemination of taxonomic information locked up in natural history museums. Three-dimensional imaging captures many characters and allows a lot of versatility in the way that morphological data is displayed and used (Wheeler et al. 2012; Faulwetter et al. 2013). Moreover, the loss and damage of valuable specimens, many of which are very fragile, can be reduced as a result of the use and sharing of 3D model substitutes among researchers. This can also lead to a reduction in the handling and transportation expenses of many specimens.