Guide to using DNA-based monitoring with citizen science

1 Traditional biodiversity monitoring by professionals can be time-consuming and resource-intensive, and many habitats and species remain understudied and data deficient. Citizen Science (CS) and DNAbased monitoring are helping to fill these gaps by expanding the scale and impact of biodiversity monitoring. CS, or community science, involves members of the public in scientific research. It offers opportunities to build skills, improve wellbeing, and foster stronger connections with nature. DNA-based monitoring can detect species that are difficult to survey and help track how species distribution and ecosystem health and function change over time. This guide introduces CS and DNA-based monitoring, demonstrates how the two approaches can work together (CS x DNA), and provides practical advice on project design, volunteer involvement, training, and communication. The CS x DNA project, Genepools (Rees et al., 2023), is used to illustrate project design from start to finish, and we also explore future opportunities and challenges for this emerging approach. This document aims to facilitate crossover between these monitoring approaches and provides high-level advice for those wishing to use DNAbased methods in projects with volunteer involvement. We hope it will inspire collaborations between CS and DNA practitioners to drive better outcomes for people and nature. UKEOF UK DNA Working GroupUKEOF UK DNA Working Group Guide to using DNA-based monitoring with citizen science © Lauren Cook 3 3 Who has created this guide? Written by scientists at UK Centre for Ecology & Hydrology and Natural England, on behalf of Natural England and the UK Environmental Observation Framework DNA Working Group. Natural England is here to secure a healthy natural environment for people to enjoy, where wildlife is protected and England’s traditional landscapes are safeguarded for future generations. The UK Centre for Ecology & Hydrology (UKCEH) is a leading independent research institute dedicated to understanding and transforming how we interact with the natural world. With over 600 researchers, it tackles the urgent environmental challenges of our time, such as climate change, pollution, and biodiversity loss. The UK Environmental Observation Framework (UKEOF) is a partnership of the major public funders of environmental science and was launched in 2008 to address issues of fragmentation, data access and a lack of strategic direction in environmental monitoring. The UKEOF’s UK DNA Working Group facilitates dialogue and collaboration by providing a forum for the wide community of government agencies, academics and other stakeholders to discuss priorities and emerging developments in the use of DNA for environmental monitoring. This guide can be freely distributed in its original form for non-commercial purposes. Please feel free to forward it to anyone you think will be interested. All content is copyright of UK Centre for Ecology & Hydrology, Natural England and UKEOF, and no images or sections of text can be extracted and used elsewhere without first obtaining permission. 4 Contents Who has created this guide? 3 Summary 6 Document navigation 8 1. Introduction to Citizen Science (CS) and DNA 9 1.1. What is biodiversity monitoring? ...............................................................................................9 1.2. CS monitoring ...........................................................................................................................11 1.2.1. What is CS? ....................................................................................................................11 1.2.2. Practical value of CS monitoring ...................................................................................11 1.2.3. Social and educational benefits of CS ..........................................................................12 1.2.4. Considerations and limitations of CS and biomonitoring ............................................13 1.3. DNA-based monitoring ............................................................................................................14 1.3.1. What is DNA-based monitoring?...................................................................................14 1.3.2. How does DNA-based monitoring work? .....................................................................15 1.3.3. Considerations and limitations for DNA-based monitoring .........................................16 1.4. Combining CS and DNA for biodiversity monitoring ...............................................................19 2. CS x DNA projects 20 2.1. How volunteers can get involved ............................................................................................20 2.2. CS x DNA examples ..................................................................................................................21 2.3. Considerations for CS x DNA projects .....................................................................................23 2.3.1. Type and amount of data needed .................................................................................23 2.3.2. Cost ................................................................................................................................23 2.3.3. Level of expertise required ............................................................................................24 2.3.4. Training and coordination ..............................................................................................24 2.3.5. Accessibility ...................................................................................................................24 2.3.6. Communicating results .................................................................................................24 2.3.7. Partner and stakeholder management .........................................................................25 3. Considering volunteers 26 3.1. What motivates volunteers to take part in a CS x DNA project? ...........................................26 3.2. How are you factoring in the benefits to volunteers? ............................................................27 3.3. Training for volunteers ..............................................................................................................28 3.4. Communicating DNA science to diverse audiences .............................................................29 3.4.1. Accessible language ......................................................................................................29 5 3.4.2. Be personal ...................................................................................................................29 3.4.3. Level of detail .................................................................................................................29 3.4.4. Managing expectations through increasing understanding ........................................29 3.4.5. Displaying DNA results ..................................................................................................30 3.4.6. What’s the story? ..........................................................................................................31 3.4.7. How frequently will you communicate? ......................................................................32 4. CS x DNA project design 33 4.1. Defining research questions and aims ...................................................................................34 4.2. Engaging a volunteer group .................................................................................................... 34 4.2.1. Privacy, ethics and permissions ....................................................................................35 4.2.2. Health and Safety...........................................................................................................35 4.2.3. Communications strategy .............................................................................................35 4.3. Sampling design .......................................................................................................................36 4.3.1. How many samples to take from where and when? ..................................................36 4.3.2. Sampling apparatus and methods suitable for citizen scientists ................................37 4.3.3. Preservation and transport of samples ........................................................................39 4.3.4. Metadata and other survey data ..................................................................................41 4.4. Molecular methods and data analysis ....................................................................................41 4.4.1. DNA extraction method .................................................................................................41 4.4.2. Single species vs. metabarcoding and primer choice .................................................42 4.4.3. Sequencing method ......................................................................................................42 4.4.4. Bioinformatics ................................................................................................................42 4.4.5. Data analysis ..................................................................................................................43 4.5. Creating and distributing outputs ............................................................................................43 4.5.1. Reporting .......................................................................................................................43 4.5.2. Impact ............................................................................................................................44 4.5.3. DNA data interoperability ..............................................................................................44 4.5.4. Data sharing and access ............................................................................................... 44 4.5.5. Evaluation processes .....................................................................................................44 5. The future of CS x DNA 46 References 48 Summary Summary meaningful contribution to conservation spending time outside health and wellbeing enjoyment interest in state of the art science personal or career development discovering local nature sharing knowledge satisfaction low barrier to entry (ease of sampling) CONNECTION TO NATURE SCIENTIFIC INTEREST SENSE OF PURPOSE 6 Guide to using DNA-based Monitoring with Citizen Science What is a Citizen Science x DNA Project? In a DNA-based monitoring project with Citizen Science (CS), scientists and volunteers come together to study the natural world using DNA analysis. These projects leverage the collective power of volunteers to accelerate scientific discoveries, and advance our understanding of ecosystems and species. Considering a CS x DNA Project? Whether a CS x DNA project will be suitable for your research question depends on the following factors: • the spatial and temporal scale of the project; • the scope of the project’s funding; • the type and amount of data needed to obtain results; • the level of expertise required to collect the data • any training and coordination efforts needed; • the stakeholder groups involved in the project. Also consider the limitations of CS x DNA including volunteer bias, accuracy of CS datasets, health and safety, and the range of skills required in running the project. How can volunteers get involved? • co-designing the project; • sampling; • lab work; • data analysis; • actions informed by the research outcomes, e.g. tips for looking after their local patch for biodiversity. Examples of CS x DNA projects GenePools: Revealing the hidden biodiversity in UK ponds. Sampling the Munros: Volunteers hiking up mountains and taking samples down to understand the health of mountain ecosystems through fungal communities. Environmental DNA Expeditions: Global marine monitoring of vertebrates by UNESCO with recreational sailors and school children. Why CS x DNA? Large-Scale Data Collection: These projects can amass a vast amount of genomic data from a diverse range of sources and at large spatial and temporal scales, which can be valuable for research. Engaging the Public: These projects engage the public in science and can foster a sense of scientific curiosity and community involvement. Cost-Effective and Accelerated Research: By utilising volunteers, these projects can reduce the cost of data collection and analysis, allowing researchers to undertake larger-scale studies and accelerate the pace of scientific discovery. Engaging with volunteers What motivates volunteers? Incorporate participant motivations through feedback and evaluation. 1 2 3 Defining research questions and aims Engaging a volunteer group Sampling design Molecular methods and data analysis Creating and distributing outputs 7 Tips for CS x DNA engagement Writing: When working with volunteers of varying expertise, simplify complex subjects to a level understandable by a 9-year-old, as it enhances information absorption - even by the most skilled experts. Introducing DNA: Provide context for DNA results, explaining what is typically found in environmental samples and how factors like UV exposure, pH, and temperature affect DNA persistence. Managing expectations by ensuring participants understand the process and limitations of DNA analysis, including the role of primer choice in species detection. Tell a story: Enhance stakeholder engagement by crafting contextually relevant narratives that ground findings into a coherent project ‘story’ – what is the beginning, middle and end? Tailoring outputs: Enhance the accessibility and engagement of projects by incorporating participantoriented outputs, including visual summaries, interactive web portals and tailored final reports. Lasting impact: Consider project longevity beyond the funding timeline by creating lasting resources like videos and web portals. Data flow considerations Project Management: Defining project objectives, specifying target species and geographic scope, and outlining how citizen scientists will contribute to data collection using DNA technologies. Privacy and Ethics: Ensuring that data collection and sharing adhere to ethical guidelines and regulations, including obtaining informed consent from citizen scientists and handling personal data in compliance with GDPR. Data Handling and Analysis: Consider the flow for DNA and participant data - including establishing a data management system, implementing data quality control measures, and considering data sharing, storage, access, and long-term sustainability. CS x DNA project design Main elements of CS x DNA project design Future horizons Standardised biodiversity data platforms / DNA dashboards are being set up to increase synergy between different projects and biodiversity metrics. Emerging global CS practitioner networks will start to address challenges in the field, assimilate lessons learned and foster collaboration and communication. Portable DNA sequencers and mobile apps see volunteers able to carry out the whole DNA workflow in future. Open Science - The transition towards ‘open science’ creates the opportunity to mainstream citizen science through the emphasis of public engagement, open access, FAIR data and open education. Conservation genetics x CS projects through sampling organism derivatives and DNA with the development of sequencing technologies. Engaging with volunteers (continued) 3 4 5 1 What is Citizen Science (CS) x DNA? 2 Using CS and DNA 3 Considering Citizen Scientists 4 CS x DNA project design 5 The Future of CS x DNA 6 References 8 Document navigation There are many excellent but separate resources on citizen science project design, DNA sample collection and analysis, and interpretation of resulting data. This document aims to facilitate crossover between these monitoring approaches and provides high-level advice for those wishing to use DNA-based technology in projects with volunteer involvement. 9 1. Introduction to Citizen Science (CS) and DNA 1.1. What is biodiversity monitoring? Biodiversity is all the different kinds of life that make up the natural world, including animals, plants, fungi, and bacteria. Taxonomy is a branch of science that attempts to group biodiversity into hierarchical categories (taxa) based on shared characteristics and evolutionary relationships. A single taxon represents a division of life, for example, the common frog (Rana temporaria) is a species in the genus Rana (pond frogs), which belongs to the family Ranidae containing other species of true frogs such as pool frog (Pelophylax lessonae) and marsh frog (Pelophylax ridibundus). This family is one of many in the order Anura (frogs and toads) along with true toads (Bufonidae). Anurans belong to the class Amphibia, which includes all amphibians found on earth, including frogs, toads, salamanders and caecilians. This class is part of the phylum Chordata, a group of animals that share key features at some point in their development, including vertebrates which all have a vertebral column and a cranium or skull. The kingdom Animalia contains all animals that have or consist of many cells, eat organic material and can move for at least part of their life cycle. This kingdom is part of the domain Eukaryota, which includes all animals, plants, fungi, seaweeds, and other single-celled organisms. Figure 1 overleaf illustrates the taxonomic classification of the common frog. 16 For identification of single species (e.g. rare or invasive species), quantitative PCR (qPCR) or digital PCR (dPCR) are typically used as these technologies offer high sensitivity and accuracy for quantifying low concentrations of DNA. Depending on the length of the target DNA sequence, Sanger sequencing may be employed to verify species identity by determining the DNA sequence and comparing to reference sequences (Thalinger et al., 2021). For identification of multiple species, PCR followed by High-Throughput Sequencing is used, known as metabarcoding (De Brauwer et al., 2022). Each DNA sequence produced is known as a sequencing read. The sequencing reads must be bioinformatically processed to group DNA sequences according to samples (demultiplexing), combine forward and reverse sequence reads (merging), filter by quality, cluster into Operational Taxonomic Units (OTUs) or Amplicon Sequence Variants (ASVs) to remove redundancy, and assign taxonomy by comparing sequences to a reference database (Hakimzadeh et al., 2023). The taxonomically assigned data are then analysed to address the monitoring or research question (Beng and Corlett, 2020). 1.3.3. Considerations and limitations for DNA-based monitoring The cost of processing a DNA sample can in some cases be less expensive than using traditional methods that involve physically observing or capturing species, and may save many hours, days or weeks of work by ecologists in collecting the samples and by taxonomists in identifying tricky organisms under the microscope (Beng and Corlett, 2020). It is especially cost-effective at larger scales as sampling consumables are often ordered in bulk and laboratory processing becomes progressively more cost-efficient as the number of samples increases (Bálint et al., 2018). However, there is a trade-off between sample size and the resources required for sample collection, processing and analysis. Greater sampling effort is needed for high spatial and / or temporal resolution, or the detection of low-density species (Erickson et al., 2019), and this will incur higher equipment, laboratory and personnel costs (Lyet et al., 2021). New projects may also face high set-up costs (e.g. purchase of equipment, development of analytical tests), or some sample types or analytical tests may require higher technical replication in the laboratory, both of which can influence cost-efficiency of DNA-based monitoring (Smart et al., 2016). Therefore, costs of sample collection (including equipment and personnel) must be balanced against those of laboratory processing and data analysis. DNA-based methods can produce false positives, i.e. false detection of a species that is not present in the field (Beng and Corlett, 2020). Contaminants can be introduced by field surveyors or laboratory technicians if decontamination procedures, single-use equipment and / or unidirectional workflows are not in place. In the field, historical or ancient DNA can also be resuspended when sediment is disturbed. Environmental contamination can occur if DNA is introduced to a sampling site by the general public, domestic animals or other wildlife who have visited other sites. Similarly, DNA may be inadvertently transported on the body of another organism, or poo from predators will contain the DNA from other species they have eaten. For example, a bird might eat a fish from the sea, then deposit droppings containing DNA of that fish when flying over a lake (Furlan et al., 2020; Burian et al., 2021). Best practice to minimise contamination in DNA projects is well-described in the literature (Bruce et al., 2021; Goldberg et al., 2016). Controls at each stage of the workflow, especially at the earliest steps, are key to identify which contaminants are being introduced at each stage and for quality assurance (Hutchins et al., 2021). 17 False positives can be introduced by erroneous PCR amplification or sequencing resulting in false sequences (Furlan et al., 2020); these should be removed during bioinformatic processing but the efficiency of this will depend on the reference database used (Beng and Corlett, 2020) and the abundance of false sequences (Furlan et al., 2020). There may also be misidentifications where sequences are assigned to an incorrect species or higher taxonomic rank (also a source of non-detections) (Furlan et al., 2020). This could be due to lack of reference sequences, genetic similarity between species (e.g. domestic species and wild ancestors), or an incorrect record in the DNA reference library if a species had originally been misidentified based on appearance or sequence inaccuracy (Beng and Corlett, 2020; Furlan et al., 2020). This can happen when species are ‘cryptic’, i.e. they are almost impossible to distinguish by how they look but they are genetically distinct. For example, with the advent of DNA technologies, investigation has revealed that many earthworm ‘species’ are, in fact, groups of genetically distinct cryptic species (Marchán et al., 2018). In the case of genetically similar species, common examples are detecting wolf (Canis lupus) instead of dog (Canis lupus familiaris), Scottish wildcat (Felis silvestris) instead of cat (Felis catus), or green-winged teal (Anas carolinensis), a rare migrant, instead of mallard (Anas platyrhynchos) or common teal (Anas crecca) (Harper et al., 2019b). DNA methods can also produce false negatives, i.e. failure to detect a species despite its presence in the field (Beng and Corlett, 2020). Species may not be detected when present if: the DNA is not captured in samples due to insufficient sampling effort and / or inappropriate timing of sampling; low DNA concentrations; fast DNA breakdown; and / or environmental conditions (Burian et al., 2021). Sampling only represents a portion of what lives in that environment. It is possible to miss some species living there by chance, i.e. if you know you have a frog in your pond and frog DNA does not come up in the results, that may just be because frog DNA was not collected in that particular sample (Brys et al., 2020). Additionally, false negatives can occur if the sample is not preserved and stored appropriately, leading to breakdown of collected DNA. Samples typically have to be stabilised by freezing or addition of chemical solutions for storage at warmer temperatures. Samples should always be kept in the dark away from sunlight to avoid damage by ultraviolet radiation (Bruce et al., 2021). To analyse the collected DNA, it must be separated from the rest of the sample and purified. This process is known as DNA extraction and must be tailored to the type of sample and taxa of interest. Inefficient DNA extraction can lead to poor recovery of DNA or co-extraction of PCR inhibitors (i.e. substances that interfere with PCR amplification) and subsequently false negatives (Burian et al., 2021). Similarly, suboptimal PCR conditions, reagents and replication can produce false negatives. During PCR, primer bias can occur, where primers bind more efficiently to DNA of some species than others (Beng and Corlett, 2020). The analytical test or assay may also have low sensitivity (Burian et al., 2021) Alternatively, there may be species masking, where DNA of larger and / or more abundant species is preferentially amplified over DNA of smaller and / or less abundant species (Kelly et al., 2014). Other technical factors that can increase the risk of false negatives are insufficient sequencing depth, suboptimal bioinformatic processing, and reference database coverage, i.e. the availability of reference sequences for taxa expected to be present in an area (Furlan et al., 2020). Additionally, species detected in past DNA projects that are still present may not be detected in new projects, or species detected by one laboratory may not be detected by another laboratory if different methods are used (Rodriguez et al., 2025). 18 There are key considerations at each stage of the workflow to minimise false positives and false negatives. When collecting DNA samples, the number of sampling locations, number of samples at each location, distribution of locations and samples, and sample quantity must be appropriate to the size and type of system being studied. DNA may be patchily distributed in still waterbodies due to lack of water movement (Harper et al., 2019a). DNA of different species will be spatially segregated in deeper lakes that experience thermal stratification in summer, but more evenly mixed in winter once layers dissipate (Lawson Handley et al., 2019). In flowing water, DNA could have a more homogenous distribution due to mixing of the water column, or a patchy distribution due to transport and dilution (Curtis et al., 2020). In large, fast-flowing rivers, DNA may be transported tens to thousands of kilometres from its source (Pont et al., 2018). Similarly, tidal currents can transport DNA long distances (Andruszkiewicz et al., 2019). As an example, at least 10 water samples (each 2 L) at equidistant intervals around the perimeter of a temperate lake in winter are required to detect the majority of fish species present. Greater sampling effort, including sampling at depth, is required in summer to ensure species detection, especially for rare species (Sellers et al., 2024). Timing is crucial to ensure sampling is conducted when species are more active and likely to release more DNA, such as during breeding, spawning, rearing young, dispersal etc. (de Souza et al., 2016). Timing can make the difference between detection and non-detection of some species such as crayfish. Crayfish breed in the spring/summer so lots of DNA will be shed as a result of increased activity compared to winter (Troth et al., 2021). Environmental factors (e.g. temperature, pH, salinity) can also influence the rates at which DNA is released by organisms and breaks down in the environment, so it is important to take measurements of variables likely to influence DNA in different systems to aid modelling and interpretation of data (Harrison et al., 2019). Laboratory protocols must be optimised to maximise DNA recovery and amplification, and minimise primer bias. Primer design and validation is key to target specific species or taxonomic groups and minimise non-target amplification (Collins et al., 2019; Langlois et al., 2020). Sequencing depth will depend on the expected diversity of samples and the purpose of the study, e.g. greater sequencing depth will be required to detect rare species in highly diverse samples (Shirazi et al., 2021). Bioinformatics parameters must be given careful consideration to ensure these are tailored to the target DNA sequence and taxonomic group (Bayer et al., 2025). Ultimately, a species cannot be identified by DNA analysis if it does not have a reference sequence so it is important to evaluate reference database coverage before undertaking a DNA study to understand what can and cannot be detected, and generate new reference sequences for priority species if none are available. There are potentially thousands of species which do not yet have reference sequences (Weigand et al., 2019). Work is ongoing around the world to fill in these gaps, such as the Darwin Tree of Life Project. Metadata is key to understand the methods used to generate DNA data and ensure transparent reporting. It ensures reliable interpretation of results and enables a confidence judgement to be made for the data. Metadata standards / requirements are well-established in the literature for both single species (Thalinger et al., 2021) and metabarcoding (Klymus et al., 2024; Takahashi et al., 2025) projects. 19 1.4. Combining CS and DNA for biodiversity monitoring A monitoring project combining CS and DNA (or “CS x DNA”) can take many forms, the most common of which is involving volunteers in collecting DNA samples, which are analysed to monitor some aspect of biodiversity, such as surveying an area for endangered and elusive species (Biggs et al., 2015). Combining DNA technologies with CS can bring many benefits, such as helping to address data gaps by improving under-sampled areas or taxa in a way that is cost-efficient, relatively quick and highly scalable. DNA analysis becomes more cost-efficient when many samples are processed at once, lending itself to the collective power of citizen scientists (Meyer et al., 2021). Involving volunteers means that science can glean local knowledge through participant input, and empower advocacy and action in the wider community (Pocock et al., 2018). CS x DNA can also engage volunteers who might find it difficult to participate in more time-intensive or physically demanding CS schemes. The combination of the two techniques therefore provides a potentially powerful tool for large scale monitoring across the UK and globally. Citizen science is increasingly recognised for its valuable and often vital contributions in environmental monitoring, particularly in biodiversity assessments, and has tremendous potential to expand DNA survey efforts, thereby enhancing the reach and impact of both approaches (Hansen and Bonney, 2022; Pocock et al., 2018). Scaling up DNA analysis with CS could significantly contribute to Sustainable Development Goal indicators (Fraisl et al., 2020) and help to bridge taxonomic and geographic gaps in biodiversity data (Chandler et al., 2017; Johnston et al., 2023; Pocock et al., 2018). Successfully achieving this integration, however, requires substantial collaboration across molecular ecology, bioinformatics, data management, science communication and public engagement. This guide aims to assist interested parties in effectively utilising DNA technologies alongside CS to monitor and understand the state of biodiversity and ecosystem health, and aims to highlight practical considerations for those deciding whether to use a combined CS x DNA approach. 20 2. CS x DNA projects 2.1. How volunteers can get involved There are several stages in a CS x DNA project where volunteers can be involved. These include: • Sampling: This is the most common stage where volunteers can add immense value to DNA surveys, as a cost-effective way for a project to collect a large number of samples across a large spatial scale (e.g. Agersnap et al., 2022), and to access locations otherwise unavailable to professional field surveyors such as private gardens (e.g. Rees et al., 2023). Sampling DNA from the environment (eDNA) is relatively straightforward and allows volunteers to spend time in nature. The particular considerations of sampling will vary depending on the habitat and taxa of interest, and there are many sampling options suitable for CS (see examples in Section 4); • At the design stage: It is possible to involve volunteers in co-designing or participating in the initial design of the project. This will ensure participant needs can be addressed in the project aims, as well as the needs of the scientists and other stakeholders (e.g. Clarke et al., 2023). Factoring participant motivations into the design of the project could mean collecting additional metadata to address questions they are interested in, adding a test to analyse a particular taxon of interest, combining other techniques alongside DNA, or simply feeding back results in a way which will have the most impact; • Continual feedback opportunities: Volunteers can share their thoughts throughout the project via formal or informal feedback, leading to the continual improvement of the project and shared learnings for future CS x DNA projects (e.g. Broadhurst et al., 2025); • Informed action: Advice can be given to participants in light of the project results, increasing their understanding of the ecology and providing tips for managing their local environment, e.g. gardens or public green spaces; • Engaging in data analysis: Citizen scientists may be motivated to contribute to data analysis or be involved in community-driven data interpretation efforts. To facilitate this, DNA sequence results and bioinformatics pipelines (code) can be shared on an open access platform as offered by Wilderlab, New Zealand. This offers participants (or anyone interested) the opportunity to work with the data for their own questions. However, this would require a relatively high level of expertise and would not be widely inclusive; • Lab processing: It may be feasible to involve volunteers in the process of DNA extraction and PCR, which would require additional training, connection with a partner with lab facilities, and / or engagement with a skilled volunteer group, e.g. Tøttrup (2020), Urban Nature Project, DNA Sequencing by The British Lichen Society, and Knudsen et al. (2023). With the advent of portable DNA extraction, CRISPR-Cas and portable sequencing technologies, this option will become more viable in future. Note: Acknowledging the efforts of citizen scientists ensures they receive appropriate recognition for their contributions to the project. 21 2.2. CS x DNA examples CS and DNA have been combined for biomonitoring since 2015 (Biggs et al., 2015). In such projects, volunteers have shown strong motivation and commitment, with large numbers of volunteers and a high return rate of samples (Agersnap et al., 2022, Broadhurst et al., 2025). Successful projects combining the two methods span from monitoring a single endangered species (e.g. ‘Can environmental DNA help find the kōkako?’) and human disease vectors (Schneider et al., 2016), to monitoring entire communities of organisms to establish large-scale biodiversity baselines (Lin et al., 2021; Meyer et al., 2021). In some cases, volunteer engagement has enabled sampling strategies which would be otherwise logistically impossible for scientists, such as the simultaneous collection of samples from 100 sites, giving a view of fish diversity largely unaffected by temporal variation (Agersnap et al., 2022), or providing biodiversity data from private garden ponds which would otherwise be inaccessible (Rees et al., 2023). Further examples are outlined in Table 1. Table 1. Examples of monitoring projects employing a CS x DNA approach. Description Reference/Link Monitoring great crested newt (Triturus cristatus) in ponds - this was the first time volunteers were involved with an eDNA project in the UK Biggs et al. (2015) Monitoring populations of invasive mosquito vectors in Europe by sampling ponds and waterways (quantitative PCR and metabarcoding) Schneider et al. (2016) CaleDNA Project - monitoring entire communities of organisms for large-scale biodiversity baselines Lin et al. (2021), Meyer et al. (2021) Mapping coastal fish biodiversity on a national scale – sampling nearly simultaneously at 100 sites in Denmark Agersnap et al. (2022) Fish community monitoring along vast sub-Saharan coastlines Burian et al. (2022) Monitoring terrestrial mammals in Essex, England, with eDNA metabarcoding of river water Lavin (2022), Broadhurst et al. (2025) Creation of an eDNA toolkit for CS monitoring of urban wetland biodiversity in Nanjing, China, with a group of junior students and scientists Zhang et al. (2023) Fungus monitoring on mountaintops in the Scottish highlands SEFARI Environmental DNA Expeditions – global CS project measuring marine biodiversity (mainly fish) and impacts of climate change across UNESCO World Heritage marine sites with many school children involved in sampling campaigns Environmental DNA Expeditions in UNESCO World Heritage Marine Sites Continued overleaf 22 Description Reference/Link Using water eDNA samples with CS to find the South Island kokako (Callaeas cinereus), presumed extinct The South Island kōkako Charitable Trust The Great Australian Platypus Search – school children help scientists by collecting eDNA samples from their local waterways to map the distribution of platypuses, fish and other aquatic vertebrates across Victoria, Australia EnviroDNA Case Study: The Great Australian Platypus Search Detection of amphibian eDNA in Denmark - sample collection and quantitative PCR analysis carried out by high school students, producing 4 (of 2,250) unexpected test results that needed professional scrutiny and detecting 9 of 14 amphibian species Knudsen et al. (2023) eDNA samples collected by volunteers as part of Spot the Monk to be analysed for the endangered Mediterranean monk seal (Monachus monachus) to better understand distribution Valsecchi et al. (2023) Using water eDNA samples with CS to describe the distribution and abundance of groundwater amphipods Couton et al. (2023a) Six groups of volunteers recruited to collect samples for examination of coastal fish biodiversity with eDNA metabarcoding Miya et al. (2023) Citizen scientists designed and executed an eDNA-based survey of a small chalk stream catchment to explore questions of concern around vertebrate species Clarke et al. (2023) GenePools – monitoring the diversity in garden ponds across 3 UK cities in first year, then 6 UK cities in second year, with multi-marker metabarcoding targeting vertebrates, invertebrates, plants, bacteria and eukaryotes Rees et al. (2023) Unlocking the Severn – a CS x DNA approach was used to monitor the shad (Alosa spp.) migration and other fish species with metabarcoding Griffiths et al. (2024) 800 lakes sampled worldwide by citizen scientists and scientific researchers on International Day for Biological Diversity 2024 to monitor terrestrial and freshwater biodiversity LeDNA DNA and life – high school students engaged in both fieldwork and advanced laboratory analyses by collecting and analyzing eDNA samples from marine environments across Denmark Leerhøi et al. (2024) Table 1 continued 23 2.3. Considerations for CS x DNA projects Deciding whether CS x DNA is the right approach depends on several factors, each with specific considerations, pertaining to the research questions and scope of the project. Consider first if involving volunteers will help to achieve the desired results, while at the same time benefiting participants by addressing their needs or fostering new skills and expertise. Second, consider if DNA survey is the most effective method to provide results addressing the question being asked. 2.3.1. Type and amount of data needed Consider the choice of molecular methods (e.g. DNA extraction methods, primers, bioinformatics pipelines), and sample type (e.g. water, soil, air, swabs etc.). Outline the metadata you will need to support the DNA output (more in Section 4). Consider the number of sampling locations and number of samples at each location that might be needed. Sampling may need to happen at a particular time of year to maximise detection success. Consider if samples can be taken individually or in teams, and how data will be recorded – a smartphone app or data sheets may be needed. The time and effort required needs to be realistic for volunteer participation. Consider how comparable the dataset might be to similar projects at local or national scales to maximise data use and validate results from citizen scientists, i.e. it will be beneficial if there is data from the same area / species which can be used to confirm / refute results from CS x DNA projects. The level of accuracy required from the data should be considered. Studies have shown the quality of DNA data from volunteer-collected samples was comparable to those taken by professional researchers, and more species known to occur in the study area were detected by volunteers than by researchers (Broadhurst et al., 2025; Lavin, 2022). However, it is more challenging to train and coordinate volunteers to process samples in the laboratory with precision compared to collecting field samples. More time and established protocols will be needed for laboratory training, and additional precautions and controls will be required to minimise contamination and ensure quality. Detection thresholds for the resulting data will also require consideration. While involving volunteers in laboratory processing offers educational and training benefits and can motivate volunteers to engage with the research process on a deeper level, some volunteers may find laboratory processing to be too advanced and complicated (Leerhøi et al., 2024). 2.3.2. Cost The more DNA samples you need to process, and any additional analysis on those samples will add cost. Projects that require expensive or highly technical equipment or demand a great deal of time commitment, such as collecting detailed measurements every day, may be unsuitable for CS. Factor in time for laboratory analysis (you can usually expect this to take weeks for single species or months for metabarcoding). Consider including additional time as there is a high risk of analysis delays. There should be some budget set aside for providing curated and engaging feedback to the volunteers (e.g. in the form of an interactive web app, portal or report) and responding to their 24 queries. Consider the time required for engagement as well as providing necessary training and disseminating results. 2.3.3. Level of expertise required For most DNA sample types, sampling requires no expertise from the volunteers prior to basic training. This is important to stress to volunteers to promote diverse participation. However, there may be physical limitations that need to be considered, e.g. safe access for disabled vs. non-disabled individuals. Advice on sampling can be provided by research scientists and commercial companies. Although volunteers can be trained in laboratory processing, molecular and bioinformatic analysis will typically be provided by an external contractor or project partner. It is also common to partner with communications experts to engage, motivate and look after volunteers. 2.3.4. Training and coordination CS requires training in collecting samples as well as coordination in organising sampling trips for volunteers and sending and receiving DNA sampling kits via post. Resource development (such as web apps, instruction booklets) and training for volunteers in person, via video call, or in the form of a recorded video will be necessary. These resources may be provided by a DNA sampling kit contractor but may need to be tailored for CS. Always check whether the sampling passes organisational Health and Safety requirements. Safety conscious approaches should be employed. If the project requires participants to take samples, the potential risks should be clearly communicated along with information on how to avoid or minimise these risks. Biosecurity must be considered and landowner permissions for sampling must be obtained which could limit location accessibility and CS involvement. 2.3.5. Accessibility Some sites that may be useful to survey (e.g. ports and marinas, remote areas) may not be accessible to ‘typical’ citizen scientists. The degree of portability and safety required will be different for a group with lay knowledge to a skilled volunteer group (e.g. recreational divers / fishers). Sampling from bridges over rivers may be easier than sampling bankside, or sampling surface water will likely be more accessible than pelagic / benthic sampling. To make it logistically possible to involve volunteers, a balance could be struck between reducing the size of the sample, which could become unwieldy for a volunteer, but increasing the number of samples to achieve an adequate representation, or considering another sampling method such as using passive samplers (Bessey et al., 2021; Maiello et al., 2022; Neave et al., 2023). The costbenefits of involving citizen scientists would weigh into the decision. 2.3.6. Communicating results Good communication must be maintained throughout a project, especially if it will take a long time for results. Consider managing expectations of DNA results and highlighting the quality assurance processes involved. DNA projects can have unexpected results, such as species which are present but have not been observed by volunteers or recorded by other monitoring schemes. Alternatively, these could be species which are false positives due to contamination or false negatives due to methods used (see section 1.3). The metadata required to understand and assess level of 25 confidence in DNA data must be communicated to all stakeholders (including volunteers) to avoid false conclusions being drawn, and avoid confusion or lack of trust in the data. CS x DNA datasets must be carefully scrutinised by researchers to catch any unexpected or erroneous results from contamination or mismatches in the DNA reference library used (Knudsen et al., 2023). There are no standard procedures for scrutinising DNA results, and thus it must be subject to expert opinion / analysis. If a dubious result is found (e.g. finding tuna DNA in a garden pond), there is a choice whether to delete that datapoint, or keep it in but explain where it might have come from. It is of the utmost importance to clearly communicate how the data can be interpreted (see section 3.5) to volunteers and other stakeholders. Sometimes the most valuable data may be the most difficult to interpret for participants. Finding the balance between project needs and volunteer needs (i.e. really considering the project aims, what you are willing to sacrifice, and allocating sufficient resources to volunteer engagement) can be critical to a successful CS x DNA project. For example, scientific names may not be that informative to volunteers, but can be key to describe microbial diversity as these taxa often lack common names. 2.3.7. Partner and stakeholder management Consider that a CS x DNA approach requires a wide range of skills which may require substantial investment or partnerships with other teams and institutes. For example, support may be needed for planning and executing communication strategies, community building, participant management, and public engagement. This can be mitigated by partnering with another institution. Roles for all project partners should be outlined within the initial project specification / partnership agreements. It is important to ensure the output DNA data (species distribution or community inventories) and metadata are fit for purpose for the original aims of the project, and consider the requirements of the different stakeholders (e.g. participants, policymakers, funders, scientific and practitioner communities) involved. Different stakeholders may be interested in different types of data and presentation. 32 3.4.7. How frequently will you communicate? Phased or continual communication will update the volunteers to any changes in the timeline, e.g. if there is a lag in the DNA analysis and feedback of the results. Transparency in the process will increase satisfaction and reduce frustration for volunteers. Phases may include communication at the following points: • Immediately after submission (thank you and basic details of their response); • During the data collection period (details of goings-on such as how the processing happens, updates of stages, timelines, i.e. “where is your sample now?”); • Once the data collection season ends and all the results are in (e.g. total number of samples, number of co-researchers/participants, distribution of collected samples) and timeline for final results; • Once the lab analysis has been completed and the species information is available. Funded projects must take into consideration the funding timescales, deliverables and milestones. Although communications should be built into the project timeline, there may be limited time for follow-through with volunteers. It is important therefore to consider the project’s longevity should funding cease, e.g. whether it is beneficial to have lasting resources like videos. Figure 5. CS x DNA project design. Illustration by Lauren Cook. • Privacy, ethics and permissions • Health and safety • Communications strategy • How many samples to take, from where, and when • Sampling apparatus and methods suitable for citizen scientists • Preservation and transport of samples • Metadata and other survey data • DNA extraction method • Single species vs metabarcoding and primer choice • Sequencing method • Bioinformatics • Data analysis • Reporting • Impact • DNA data interoperability • Data sharing and access • Evaluation process Defining reseach questions and aims Engaging a volunteer group Sampling design Molecular methods and data analysis Creating and distributing outputs Main elements of CS x DNA project design 33 4. CS x DNA project design The main elements of CS x DNA project design (Figure 5) are: • Defining research questions and aims; • Engaging a volunteer group; • Sampling design; • Molecular methods and data analysis; • Creating and distributing outputs. Project design is illustrated above with specifics from the first year of the GenePools project (Rees et al., 2023) detailed in the boxes. Note that some of these elements are likely to happen in parallel, for example, the molecular methods will need to be established before data collection occurs, and these are likely to influence the design of the sampling strategy. The communications 34 strategy will also need to be at least partly established before engaging volunteers. For some projects, the design process will be more iterative or adaptive. Indeed, the methods and volunteer engagement for GenePools have changed in the second and third years. Genepools was funded by Defra’s Natural Capital and Ecosystem Assessment programme. For further general advice on implementing citizen science for studying biodiversity and the environment in the UK, see Tweddle et al. (2012). 4.1. Defining research questions and aims Work out what the question is that you need answering. The information gained through DNA analysis needs to serve a useful purpose towards this question, i.e. which taxa might be the most useful indicators of ecosystem health and is DNA a good way to survey these species? Think about the suitability for citizen scientists. There may be a volunteer group with specific expertise which could carry out sampling. Note: Co-design of the project means engaging the volunteers at the beginning of the process. GenePools The aim was to understand the ecology of urban garden ponds through eDNA samples. DNA present in water samples from organisms including bacteria, eukaryotes, plants, invertebrates, and vertebrates was sequenced. It was important to involve volunteers that could send samples from ponds in private gardens that are inaccessible to professional surveyors and so represent a gap in scientific knowledge. Recommendations on how to improve ponds for biodiversity in urban areas were made, based on the DNA findings and the other data on the ponds. 4.2. Engaging a volunteer group The volunteer group engaged may depend on project factors such as the geographic location of sampling, any specific demographic group that should be targeted, and any prior expertise or skills required. The project may be suited to an already engaged network of volunteers, or it may be necessary to engage a new network as part of the project. There are methods to increase the diversity of participants in CS by reaching out to members of the community which would be historically underrepresented in nature and the outdoors. Schools, education centres, community groups and initiatives such as the National Education Nature Park may be another avenue for engaging diverse communities. 35 GenePools A collaboration was set up between Natural England, Cefas, Natural History Museum (NHM) and Joint Nature Conservation Committee. The volunteers were engaged through the NHM, where there is an existing network. Natural England and the NHM worked to widen participation of GenePools by targeting underrepresented religious groups through contacting places of worship throughout the cities being studied. The NHM also hosted a workshop with students from Imperial College London, who highlighted some intersectional groups to engage with. 4.2.1. Privacy, ethics and permissions Permissions: Ensuring the appropriate permissions are in place is still required, e.g. access to the land, Site of Special Scientific Interest (SSSI) consent etc. If sampling on private land, land access / data storage / sharing permissions will need to be agreed before the project commences. The project manager must be satisfied with the consents and licenses for any activity that takes place. Privacy / Ethics: The use of personal data under UK General Data Protection Regulation (GDPR) must be agreed by participants. GenePools The Natural Capital and Ecosystem Assessment (NCEA) programme privacy notice was used for the project. It contains information on the collection of personal data, what personal data is collected, how it is used etc. Participants were also asked to confirm they had permission from the pond owner before sampling the pond. 4.2.2. Health and Safety The potential risks to the participants should be clearly communicated to them along with information on how to avoid these risks. A risk assessment should be written, and appropriate steps taken to mitigate any risks, as well as discussed with the appropriate Health and Safety advisors within the lead organisation. GenePools Health and Safety guidance was outlined to volunteers prior to sampling via a risk assessment. 4.2.3. Communications strategy A communications strategy depends on the project aim, the target audience(s), motivations of your participants, and your communication budget. Tactics for communication to promote continued participation can include offering a fun experience such as a social event or excursion, and use of social media to allow interaction between scientists and volunteers and volunteers to make connections with each other. 36 Use visuals, audio or text to tell a story, often including personal perspectives, as well as historical and educational contexts to the project. Storytelling can create a sense of belonging for the volunteers, especially if they are able to give their personal stories, and create interest and curiosity. Stories can be shared through the normal communication channels, e.g. blog, newsletter or social media etc. Including aspects of game playing (‘gamification’) into the CS project can promote continued participation for volunteers who may feel motivated by taking on a challenge, tracking their improvements or winning a competition. This may include using points, badges and trophies, and awarding prizes for competition of a ‘mission’ or ‘race against the clock’ etc. Employing project ‘ambassadors’, such as a volunteer who has been involved since the beginning of the project, knows a lot about the research topic or with some prior experience in CS, can promote continued participation. They have a strong motivation to participate and can help with project logistics / administration / communication. Note: Learn more by reading ‘Tactics and Tools’ from Communication in Citizen Science by Veeckman et al. (2019). GenePools Communications strategies included sharing the project with volunteer networks at the NHM, and on social media by the partner institutes. The NHM hosted a web page with information on the project. Frequent updates via email were sent to participants. The results were shared with participants via a written report and an interactive dashboard. The project was communicated with staff of partner organisations via intranet and newsletter articles. They project results were communicated with the wider scientific community via social media, presentations at conferences, and a Natural England commissioned report. A scientific journal publication is planned. 4.3. Sampling design Consider whether to adopt a published sampling protocol or design a new sampling protocol. A new protocol should be validated against established protocols and / or conventional surveys to ensure quality and reliability of results. 4.3.1. How many samples to take from where and when? The choice of sample matrix (e.g., water, air, soil, bulk samples) will depend on the ecology of the group(s) in question, for instance, where does that organism spend most of its time, and therefore where might DNA accumulate. Depending on the group(s) in question, it may be appropriate to collect bulk samples, e.g. invertebrates through pitfall or malaise traps. GenePools A broad baseline of biodiversity in and around ponds was required, so water samples from the pond were best. 37 The number of samples should reflect the spatial complexity and size of the system being sampled as well as the spatial and temporal resolution you wish to achieve, e.g. are you interested in biodiversity at local, regional or national scale, or in specific habitats, and at a single point in time or seasonally. Note: Read more about factors to consider for aquatic sampling in p. 12 of ‘A practical guide to DNA-based methods for biodiversity assessment’ by Bruce et al. (2021). GenePools The sampling protocol was chosen to align with existing Natural England pond eDNA surveys to enable use of the data beyond this project. One water sample of 1 L is deemed sufficient for a pond balanced with the practicalities of volunteers taking samples themselves. Many small subsamples from around the pond were taken and combined to produce a mixed sample from throughout the pond. 4.3.2. Sampling apparatus and methods suitable for citizen scientists Sampling kits need to be relatively inexpensive if sending out en masse to individuals. Some sampling apparatus may be less suitable for use by citizen scientists than others. The type of volunteer group will affect which apparatus may be suitable, i.e. if you are engaging a volunteer group with a particular skill which may have a higher level of fitness or capability. Gloves should be provided with sampling kits but hand sizes can vary and some people may have allergies to the glove material. If gloves are not worn, there is a risk of human contamination and skin irritation / damage if the sampling kit contains any hazardous chemicals. You may want to consider the target for your survey and whether contamination may be an issue, i.e. whether you are analysing the samples for vertebrate or bacterial DNA where human or microbial contamination would impact results. You should also consider risk associated with any chemicals in sampling kits. Citizen scientists previously involved in DNA projects have expressed concerns about plastic waste when sampling (Broadhurst et al., 2025). This would especially be an issue in countries where capacity for responsible waste disposal and recycling is limited. To minimise environmental impact by eliminating unnecessary plastic waste, provision of unwrapped kits (with unwrapped components such as the filter and syringe) could be considered depending on the target of the project, understanding the contamination risk with the primers chosen, and deciding whether to accept that risk. Some options of sampling methods which may be suitable for citizen scientists include: a. Water In aquatic environments, ladles may be needed to access the water. These can be attached to a pole or to a rope to be lowered into the water from a height. Collection bags / buckets may suffice if a sampling location is sufficiently accessible and safe, and these can be lowered into water. Sterile water bottles can also be used for sampling (Broadhurst et al., 2025; Lavin, 2022). After water has been collected, it is generally filtered in the field with a pump or syringe so only the filter with preservative needs to be sent back to the laboratory. For manual filtering, 38 apparatus which does not require a high level of physical strength will be necessary for a diverse volunteer group as pushing water through a filter by hand can be challenging, especially in more turbid water (Andreou et al., 2023). Pumps (e.g. Smith-Root) can be used where manual filtering of water would limit the accessibility of sampling, or where sample volumes are high (e.g. more than 1 L). However, pumps are expensive to purchase and could potentially be damaged when shipping to or being returned by volunteers, or during operation in the field. Aquatic sampling kits suitable for CS need to be robust against contamination, for example, with filters enclosed inside a solid housing, e.g. Sterivex filters (Merck), Sylphium filters (Sylphium), or Whatman Polydisc filters (Camlab). The preservative solution should be pre-loaded into a syringe. Alternatively, passive samplers (no filtering required) can be used to collect DNA, e.g. gauze inside a 3D printed container can be submerged following which the DNA is directly extracted from the gauze. Passive samplers could be attached to a diver during a normal recreational dive (Neave et al., 2023) or attached to a fishing line from a pier / boat / beach (Maiello et al., 2022). They can also be left in an aquatic area for a certain length of time while DNA accumulates, which is especially useful for capturing microorganisms (Sikorski and Levine, 2020). b. Soil / mud / sediment Soil or sediment can be collected by using a corer. More make-shift collection of soil and sediment can include using a sterilised spoon / spatula or tube to scoop material into a tube as used in the ‘Sampling the Munros’ project. c. Swabs and Scrapes Swabs or scrapes can be used to collect eDNA from surfaces such as rocks, plants, or other substrates where organisms have left genetic traces (Lyngaard et al., 2023). d. Air Similar to water, DNA in air can be captured using passive (e.g. dust traps, sticky surfaces) or active (e.g. fans or pumps drawing air in through a filter or over a microscope slide) sampling approaches for the detection of vertebrates, invertebrates, plants, fungi, bacteria, viruses etc. (Johnson and Barnes, 2024). Note: Some of these sampling approaches are in the early stages of development, but new devices and increasing use are likely to be seen in the next few years, e.g. AirDNA Sampler designed by Harnpicharnchai et al. (2023). e. Natural samplers DNA can be concentrated naturally inside an organism or an organism derivative, e.g., bloodmeal, honey). Note that there are ethical considerations when working with live organisms and it may only be suitable for a volunteer group with some specific training. Some examples include: • Sponges – sponges can be non-lethally sampled and concentrated DNA in their tissues from the surrounding biota can be screened (Mariani et al., 2019); • Haematophagous invertebrates – sometimes referred to as invertebrate-derived DNA (iDNA), blood can be linked to animals that invertebrates have fed on, e.g., terrestrial mammals (Baker et al., 2021); • Honey – honey contains DNA from plants foraged by pollinators, and microbiomes of bees, as collected by volunteer beekeepers, e.g. National Honey Monitoring Scheme. 39 f. Bulk sampling Invertebrates can be collected in a preservative (e.g. propylene glycol) from various types of traps (e.g. malaise, pitfall) or collected using nets then added to a preservative. Invertebrates are killed on contact with preservative but specimens may be damaged in the process of collection. For DNA analysis, these bulk invertebrate samples are typically homogenised or a leg or piece of tissue taken from each specimen for DNA extraction. The resulting data can be useful for conducting a rapid biodiversity assessment in the area (Rees, 2022) or providing evidence for change in insect composition and abundance over time (Koperski, 2023). The suitability of this method for CS will depend on the volunteer group as the ethicality of sampling invertebrates is subjective. Invertebrates do not have the same ethical procedures in place as vertebrates, which may result in the suffering or killing of many more individuals than necessary (Koperski, 2023). Where possible, efforts should be made to reduce suffering and mortality, through statistical power analysis, reducing bycatch, and making bycatch available for future use (Drinkwater, E. et al., 2019). New approaches, such as collecting aquatic macroinvertebrates and leaving them in a water sample for a set time period before releasing them and filtering the water (Sander et al., 2025) or collecting faeces that insects have come into contact with (Drinkwater, R. et al., 2021) may offer solutions. Where mortality is unavoidable, the reasons and need for this to fulfil project objectives should be carefully communicated to volunteers to avoid backlash and disengagement, e.g. UK Pollinator Monitoring Scheme pan trapping protocol. A BBC Radio 4 interview covered these issues in more detail. GenePools Enclosed Sylphium filters were used to minimise contamination. The filter pore size was changed from 0.22 µm to 0.8 µm as many volunteers complained that the manual filtering was too hard with the smaller pore size. A 100 mL syringe was included in the sampling kit, meaning a full syringe needed to be pushed through 10 times. Ladles were used to access the water and each scoop tipped into the large 2 L capacity sample collection bag, which was sealable to be able to shake and mix the sample. 4.3.3. Preservation and transport of samples To ensure the quality of the DNA in a sample, freezing will be required or a preservative substance will need to be added. It is recommended to ensure a cold chain is in place for samples from field collection to laboratory processing, or purchase an appropriate preservative from the same company that will supply sampling equipment (e.g. filters) and / or process samples to ensure compatibility. The preservative must be in line with Health and Safety for CS, i.e. non-toxic and non-flammable to be used by volunteers. 40 GenePools A preservative solution was injected into the filter housing after sampling from preloaded syringes. Using a preservative such as Longmire’s buffer (Longmire et al., 1997) or Cetyltrimethylammonium bromide is not hazardous if spilled. Filters loaded with preservative in a solid filter housing can be sealed and kept at ambient temperature until being received at the laboratory. Soils and sediments are often kept and transported cool without any preservative added, but can be fixed in a preservative solution and transported as a whole sample at ambient temperature. GenePools After preservative solution was added, samples were stored at ambient temperature until they were received at the laboratory where they were frozen. When transporting eDNA samples from citizen scientists to a laboratory for analysis it is critical to ensure the samples remain viable and uncontaminated during transport. Consider the following guidelines: • Sample labelling: Provide a label to clearly distinguish containers with unique identifiers, time, date, and location (GPS coordinates if possible). Using a pen or pencil appropriate for the containers and the preservative being used is also important; • Packaging: Packaging should ideally be (i) insulated (samples should be kept cool to minimise DNA degradation), (ii) leak-proof, air-tight and in a secondary bag to prevent leaks, and (iii) properly cushioned to prevent physical damage; • Postage: Use a reputable courier with experience in handling biological samples. Choose a shipping option that ensures samples reach the laboratory quickly and under appropriate conditions. Conditions of carriage need to be considered dependent on any preservative used. A sample tracking system to monitor the location of samples during transit will ensure samples can be traced in case of any issues; • Cost: Consideration should also be given to the cost of posting, and ensuring that everyone is able to participate, i.e. ensuring in the contract with suppliers that the sample kits sent to participants must include a stamped return envelope; • Communication: Establish clear communication channels, e.g. contact information for questions or concerns regarding sample transit. Clear deadlines should be included in the instructions indicating when the kits should be sent. GenePools Participants were sent their sampling kits via post with a pre-stamped and pre-labelled envelope included in the sampling kits. 41 4.3.4. Metadata and other survey data Consider what additional data will be needed to describe the data which will provide valuable additional context for data analysis. Metadata also includes personal information from participants, which should be outlined in the privacy statement. Other survey data includes information about where the sample was taken, e.g. any geographical or biochemical information. The use of standardised metadata templates will enhance the impact of the DNA results for wider use beyond the project. These descriptive data are required to enable the data to be understood and to provide confidence in the results. They enable the DNA records to be uploaded onto public repositories to be combined with other biodiversity data and accessible for other researchers to use. Templates are available from the Genomic Observatories Metadatabase (Deck et al., 2017), the Metabarcoding Data Toolkit (GBIF Secretariat, 2024), or the FAIR eDNA project (Takahashi et al., 2025). However, note that excessive metadata requirements can be off-putting to volunteers – the choice of what to collect should be carefully thought through and the rationale explained. GenePools Survey data collection (e.g. the size of the pond, vegetation cover, the age of the pond, the type of lining, the date and time of sample collection, the location of the pond etc.) was sent out to participants to fill in at the time of sampling. Personal information of participants (e.g. locations and email addresses) were also collected and stored by the NHM on behalf of Natural England. Participants also took measurements of pond chemistry (e.g. pH, nitrate levels etc.) with strip tests included in original sample kits. 4.4. Molecular methods and data analysis Consider whether to adopt published molecular methods or design new protocols and / or primer sets for the target taxa. The former may save time and money if suitable for the study system, target taxa, and project aims, but the latter may be more efficient in the long-term if the project is on understudied systems or taxa. As with sampling, new protocols and / or primer sets should be validated against established protocols and / or conventional survey to ensure quality and reliability of results (Bayer et al., 2025; Biggs et al., 2015; Rodriguez et al., 2025; Thalinger et al., 2021; Vasselon et al., 2025). 4.4.1. DNA extraction method The involvement of citizen scientists will not impact the DNA extraction method, although additional training may be required if volunteers are performing DNA extraction. This guide will not cover details of DNA extraction, but these are described in Bruce et al. (2021). GenePools This was agreed with Cefas. 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