Skip to main content

Long-term archival of environmental samples empowers biodiversity monitoring and ecological research

Abstract

Human-induced biodiversity loss and changes in community composition are major challenges of the present time, urgently calling for comprehensive biomonitoring approaches to understand system dynamics and to inform policy-making. In this regard, molecular methods are increasingly applied. They provide tools for fast and high-resolution biodiversity assessments and can also focus on population dynamics or functional diversity. If samples are stored under appropriate conditions, this will enable the analysis of DNA, but also RNA and proteins from tissue or from non-biological substrates such as soil, water, or sediments, so-called environmental DNA (eDNA) or eRNA. Until now, most biodiversity studies using molecular methods rely on recent sampling events, although the benefit of analyzing long-time series is obvious. In this context Environmental Specimen Banks (ESBs) can play a crucial role, supplying diverse and well-documented samples collected in periodically repeated sampling events, and following standardized protocols. Mainly assembled for integrative monitoring of chemical compounds, ESB collections are largely accessible to third parties and can in principle be used for molecular analysis. While ESBs hold great potential for the standardized long-time storage of environmental samples, the cooperation with Biodiversity Biobanks as scientific collections guarantees the long-time storage of nucleotide (DNA, RNA) extracts together with links to analytical results and metadata. The present contribution aims to raise the awareness of the biodiversity research community regarding the high-quality samples accessible through ESBs, encourages ESBs to collect and store samples in DNA-friendly ways, and points out the high potential of combining DNA-based approaches with monitoring chemicals and other environmental stressors.

Introduction

Chemical pollution is one of the main drivers behind biodiversity decline [38]. Still, many questions remain about the specific modes of action of chemicals on organisms and populations and the mechanisms triggering biodiversity loss. Consequently, both environmental policy and research have identified an increasing need for investigations into the links between chemical pollution and the loss of biodiversity [25, 27, 48, 83, 84]. In this respect, Environmental Specimen Banks (ESBs) fulfil an important role in ecosystem monitoring by ensuring sample collection and long-term storage based on standardized protocols and extensive documentation [14]. Stored ESB samples are to date mainly used for analyses of chemical pollutants but are generally accessible for scientific purposes. Thus, they provide the opportunity to link chemical parameters with biodiversity pattern analysis, also allowing for a perspective backwards in time. In this context, DNA-based methods such as environmental DNA (eDNA) metabarcoding or metagenomics show a high potential for retrospective biodiversity assessments and correlation with prevailing contaminants or other environmental stressors, e.g., climate change, nutrients and anthropogenic land use [4, 10, 22, 49, 75, 93]. Concomitantly, the increased application of DNA-based approaches induces the need for storage of extracted DNA samples linked with associated metadata. In this context, Biodiversity Biobanks-in close collaboration with ESBs-can guarantee the appropriate deposition of DNA samples and associated data, such as extraction methods, DNA storage parameters, links to performed studies and to international nucleotide databases.

Environmental specimen banks (ESBs)

Currently more than 20 ESBs exist around the world, mainly distributed throughout Europe, Asia and North America. To foster global harmonization of ESB activities within the growing community, the International Environmental Specimen Bank Group (IESB) was initiated. The consortium promotes the development of techniques and strategies of ESBs as well as the cooperation and standardization among repositories [47, 79]. For a detailed overview of ESBs and stored sample types see Chaplow et al. [14]. ESBs are part of the precautionary principle in environmental policy as they continuously document the state of the environment and subsequently store the samples. Present and future generations can thus use the archived samples at any time to retrospectively analyse and better understand emerging environmental problems and trends. In addition, the samples allow for the investigation of stressors that could not be measured or were not known to be problematic at the time the samples were collected. Monitoring purposes are often associated with regional or national screening programs and are mostly related to persistent and toxic chemical contaminants (e.g., chlorinated, brominated and fluorinated organic contaminants, heavy metals) and their effects on terrestrial, freshwater and marine environments also including natural background and conurbation areas [5, 43]. Beside the main focus on chemical monitoring, samples are used for manifold other approaches such as, e.g., ecological status assessments or population structure analyses [19, 33, 63]. ESB collections include samples from around the globe, some of them being collected annually for more than 40 years, thereby allowing for a comprehensive analysis of pollution residues and changes through time, functioning as a basis for political decisions and appropriate restrictions in chemical compounds management. Next to real-time monitoring, specimen storage and documentation enables retrospective sample analysis for chemicals of emerging concern or with newly developed analytical tools [14]. ESBs periodically collect a variety of specified samples at selected sampling sites, ranging from human tissues to plant and animal samples from different ecosystem types, including top predators. In addition, abiotic samples as soil, sediment, suspended particulate matter, waste water, sewage sludge or atmospheric samples (airborne particulate matter) are collected and archived in ESBs [14].

To ensure sample integrity, collection is conducted according to standardized protocols. These cover sampling, transportation, processing and storage of material. Depending on ESB, sample storage is implemented in cold (−20 °C) or ultra-cold freezers (−80 °C) or in liquid nitrogen vapor tanks (around −190 °C) to ensure the integrity of the samples' biological and chemical composition over a long time period. Together with chemical and biological analyses, protocols and metadata are accessible through reports or peer-reviewed publications and the release in publicly available databases [8, 47, 69]. The research strategy of environmental specimen banks over the last 40 years reflects the progress in environmental chemistry. Common substances analysed in the twentieth century were metals, organochlorine pesticides, dioxins, polychlorinated biphenyls, and polycyclic aromatic hydrocarbons [51, 72]. During this century, ESB samples were also analysed for elemental isotope signatures [19, 90], per- and polyfluorinated alkylated substances [26, 28], plasticizers [61, 92], pharmaceuticals [11], biocides [45], modern pesticides, flame retardants [31], and other chemicals of emerging concern. However, the scientific potential of ESB collections is not yet exhausted, especially when considering how newly developed techniques as high-resolution mass spectrometry or high-throughput sequencing open up novel analytical tools and possibilities in real-time and retrospective chemical analysis, including targeted and Non-Target Screening (NTS), effects based methods, and biodiversity assessments [36].

Environmental genomics

Developments in environmental genomics in particular High-Throughput Sequencing (HTS) techniques revolutionized species identification and biodiversity assessment throughout the tree of life. Using short DNA fragments up to whole genomic or transcriptomic information, possible applications of the method focus on assessing species richness and interactions, population genetic structure, functional trait expression and diversity of complex communities [17]. 'DNA barcoding' describes the DNA isolation and amplification of a short gene fragment from a single individual and the subsequent comparison to a reference database. It is used for simple and fast specimen identification in problematic life stages (e.g., larvae, seeds), incomplete specimens (tissue pieces), or to separate 'lookalikes' [34, 82]. Based on the same principle and using the same reference databases, DNA metabarcoding uncovers the biodiversity of sample mixtures, comprising high numbers of individuals with different taxonomies [52, 91]. The method uses DNA mass extraction from bulk samples or their preservation fluids, followed by the application of HTS techniques and bioinformatic pipelines to assess biodiversity up to genospecies level [2, 77, 94]. DNA metabarcoding can also be applied on environmental, non-biological samples (e.g., soil, water, air) targeting intra- as much as extracellular DNA molecules (mitochondria, intact cells, free DNA) released from organisms into the environment. So-called environmental DNA (eDNA) metabarcoding is tempting through its non-invasiveness with a huge potential for large-scale biodiversity assessment [20, 78]. Due to the relative stability of DNA, the molecule persists in the environment even after cell death and can be detected by metabarcoding for a given period of time (depending on substrate). In contrast to DNA, RNA is very unstable and degrades in the environment minutes to hours after cell death. Environmental RNA-based markers, therefore, target metabolically active organisms and might be the more suitable tool to indicate living biotic assemblages or even gene expression patterns [18, 65]. In comparison to the above-mentioned approaches that are based on PCR amplification of a standardized short gene fragment, metagenomic techniques are PCR free, targeting the whole genomic material of an environmental sample [17]. Due to the absence of the PCR step, metagenomics approaches are hence assumed to provide more accurate abundance predictions but induces much greater costs and a higher complexity in laboratory and bioinformatic protocols [46]. Whole-genome information can also be extracted from single individuals providing a tremendous increase in molecular information compared to marker-based approaches with applications in phylogenetic or functional analysis [66]. Bypassing marker amplification through PCR, also transcribed RNA (mRNA, rRNA) can be used as a template for sample analysis [53, 57]. While transcriptomic approaches target transcribed RNA from single individuals, metatranscriptomics provide information of simultaneously expressed genes in mixed communities under given environmental conditions. However, with the instability of RNA molecules sampling and processing is accompanied with challenging collection and storage efforts.

Opening up environmental specimen banks for molecular analysis, and the role of biodiversity biobanks

First biodiversity studies already utilize ESB samples, as for example [21], where scientists retrospectively applied eDNA metabarcoding on freshwater suspended particulate matter (SPM) collections from the German ESB to monitor fish communities through time. This analysis includes cryo-archived SPM samples from six riverine systems in Germany representing different conditions and fish communities. Another study used specimens of the zebra mussel (Dreissena polymorpha) collected over the last 25 years and stored at the same ESB [86]. The study investigates mussel diet through eDNA metabarcoding and the utility of mussels as eDNA filters of planktonic organisms. Recently, the German ESB together with University Duisburg-Essen started the project ‘TrendDNA’, which includes the comprehensive analysis of ESB samples through molecular approaches (www.trenddna.de) also aiming to formulate guidelines for sample quality assurance and control (QA/QC) for the application of molecular approaches. However, the potential of ESB collections is still very far from being fully used. Barcoding, metabarcoding as well as metagenomic approaches can be applied to banked specimens, sample mixtures or non-biological samples to investigate biodiversity, population dynamics or diet composition over long-term periods, assessing the influence of natural and human-made environmental changes through time [2, 12, 18, 50, 60].

To ensure the integrity of DNA and ideally even RNA molecules, environmental samples need to be stored under defined constant and controlled conditions which should ideally be standardized [32, 39, 74, 88]. Centralized repositories warrant consistent storage quality and cater to the needs of individual research institutes or individual researchers, who often have only limited, short-term storage capacities, and are not specialized on the task. Subsequent to analysis, remaining DNA extracts should be professionally archived to save resources and to warrant reproducibility of research results. Each extract, depending on isolation method, is unique. In addition, over the course of the years, often additional markers (up to meta-/genomes) are added to data sets that started out based on the analysis of a single gene. Long-term storage of DNA isolates can happen directly at ESBs. However, dedicated Biodiversity Biobanks (BBBs, see [3] and [24] focus specifically on archiving and handling DNA and RNA. As research collections, BBBs are directly in touch with biodiversity research groups and the user communities. In addition to the isolated biomolecules, they hold fixed tissues-sometimes even viable tissues (live cells)-that are linked to the respective species. Not uncommonly, BBBs are housed at natural history collections, which enables them to archive entire organisms as reference specimens and to make their holdings publicly visible (while implementing digital rights in accordance with depositor wishes). Currently more than 100 BBBs and associated initiatives have joined forces to form the Global Genome Biodiversity Network [24]. GGBN.org offers a unified platform to internationally find and access samples suitable to molecular biodiversity research. BBBs see themselves as information brokers regarding the analytical data associated with their samples. For instance, they enrich their samples by linking them with publications and with the databases of the International Nucleotide Sequence Database Collaboration (e.g., ENA or NCBI GenBank, with the Barcode of Life Data systems (BOLD [67]), or others).

One exemplary instance of the described cooperation between an ESB and a BBB exists in Germany, where the German Environmental Specimen Bank collaborates closely for long-term storage of extracted DNA with the Leibniz Institute for the Analysis of Biodiversity Change (LIB) at Museum Koenig, Bonn. The LIB Biobank extends the offer to the ESB community and to metabarcoding projects to deposit environmental DNA or RNA extracts in its currently expanded cryofacility (contact through last author), making them available for future reference and potential sequencing of additional molecular markers.

Challenges

Storage conditions

Inadequate temperature or pH, exposure to degrading compounds or to light all compromise DNA and RNA quality. These and other factors have to be considered during storage [1, 70], upon which depends the success of molecular biodiversity assessment. Ideally, DNA isolation from substrate should be conducted as soon as possible after collection to maximize DNA quality and quantity. However, due to the nature of workflows or limited resources, this is not always an option. For not yet isolated DNA samples, conservation will vary according to its medium: DNA attached to soil particles, for instance, will persist considerably longer than free DNA [70, 80]. The time interval from field collecting until storage depends on sample type, aim of analysis and technical possibilities during sampling [58, 64, 68, 71]. Optimal conditions include the immediate freezing (the colder the better) of samples and the maintenance of cold chains. Storage can also be initiated by drying the (ideally cooled) material. Nevertheless, DNA extraction for conventional metabarcoding purposes (sequencing of individual genes) is still possible from samples exposed to ambient temperature up to several weeks, if feasible fixation is applied [6, 23, 37]. Long-term storage of tissue samples or small organisms should be conducted in fixative (e.g., 96% non-denatured ethanol) with no light exposure and cold or ultra-cold condition counteracting DNA degradation [52, 87]. Storage of isolated or amplified DNA is recommended buffered (for long-term archival most often in Tris EDTA or Tris low EDTA) or-depending on planned application-sometimes in water at −80 °C [42] down to −190 °C in liquid nitrogen storage tanks [7, 29], alternatively dried and sealed [16]. While −20 °C is not an optimal storage temperature, extracts immediately stored at −20 °C will likely lend themselves to DNA analysis for up to decades, if multiple freeze–thaw cycles are avoided and when a high initial DNA concentration is given (NB: DNA will gradually decay during this period at −20 °C). More careful processing is necessary if samples are to be used for RNA analysis. Due to the high instability of this biomolecule, cold chains should be maintained right from the moment of sampling (dry ice, liquid nitrogen-based vapor shippers, etc.) and kept at least at −80 °C at any time if molecules are not transferred to a specific preservation medium [56, 59, 73]. Additional concepts for RNA handling and storage have been developed as, e.g., RNA desiccation in RNAstable [9] and the subsequent storage at room temperature for up to 1 year [35, 54, 73]. However, while the RNA analysis of banked samples in combination with chemical measurements could provide interesting insights about ecotoxicogenomics and gene expression under the influence of anthropogenic stressors [76, 85], the processing of RNA from long-term stored substrate is largely unexplored and its application to banked samples needs to be further tested.

Contamination

DNA/RNA-based approaches are extremely susceptible to contamination with non-target molecules caused by free-circulating aerosols or cross-contamination between samples [74]. Since many applications aim to detect extremely low concentrated molecules from substrates, even the slightest contamination can skew analysis and depict erroneous results for species composition. Sampling of substrates to be screened via molecular analysis should, therefore, include intensive cleaning and sterilization of equipment between samples and quality assurance and quality control measures (QA/QC) covering the sampling process but also storage and reanalysis need to be implemented and integrated in standard operating procedures (SOPs). Sodium hypochlorite bleach is extensively used as a decontaminating solution in laboratory processes. The application of at least 2% sodium hypochlorite solution (exposure time 10 min) is recommended to remove extraneous DNA [30, 41, 89]. However, commercial bleach is a hazardous substance potentially corroding material and affecting fine-tuned chemical analysis. Where this has to be avoided, the decontamination of material through UV radiation or better the usage of single-use equipment should be considered to minimize as much as possible the transfer of DNA/RNA traces among samples [13, 30]. With respect to QC, negative controls/field blanks should routinely be integrated in field sampling and laboratory processes to recognize potential contaminations in downstream analyses [30, 74].

Data accessibility

To increase visibility and accessibility of ESB samples (as for BBB samples through GGBN), information on these should be publicly available including relevant metadata such as storage protocols used, generated results and ideally even studies performed so far with the samples and based on FAIR (findability, accessibility, interoperability, reusability) data principles [44]. Data provision has already been initiated (https://www.umweltbundesamt.de/en/topics/chemicals/international-environmental-specimen-bank-group). A comprehensive, updated overview needs to be compiled giving detailed information on ESB samples and indicating their availability to the scientific community. This could potentially include a combined web interface that aggregates results generated from ESB samples around the globe. Such a tool would enable cross-linking and exploring available data and identifying and addressing global environmental concerns [19, 47, 62].

New sample types

Several biodiversity monitoring approaches rely on analyses of trapped arthropods to assess biodiversity change. Typical methods include Malaise traps for flying insects or pitfall traps for 'crawlers'. Since the advent of metabarcoding, the number of projects and studies employing arthropod traps has been rapidly increasing [ 37, 49, 52, 77], and with them the number of available community samples. Sometimes, caught arthropods are homogenized (ground up) prior to analysis, but often, they are preserved for additional biodiversity studies and only the killing and preservation fluid (ethanol, propylene glycol, etc.) is used for DNA extraction. While homogenized samples are relatively easy to store in ESBs or Biodiversity Biobanks due to small size, warranting cold storage for large numbers of entire jars of arthropods in ethanol is considerably more challenging. The existing frozen repositories typically do not and to date usually cannot focus on such samples. This leads to the situation that biologically very valuable trap samples are amassing rapidly without the perspective of long-term storage. Considerable funding goes into the underlying biomonitoring surveys and we urgently encourage the research community and policy makers to devise strategies and to work towards new infrastructures able to hold large numbers of non-homogenized trapped arthropod specimens.

Outlook and recommendations

With standard procedures from sampling to storage, Environmental Specimen Banks play an important role among the biomonitoring infrastructures. The combination of collections condensing the results of up to 40 years of field sampling with the rapidly developing molecular techniques for biodiversity assessment and for chemical pollutant analysis, holds the key for a new level of environmental research. It must now be examined in detail to what extent these standards are already sufficient to be able to use the samples as extensively as possible for genetic analysis and, if necessary, to harmonize optimized protocols for this purpose. Recently, first metabarcoding studies and projects were launched that already include ESB samples into molecular approaches. Tapping into this resource opens up high-quality, well-documented sample collections that allow easily adding a retrospective component to biomonitoring projects. For a fruitful synergy, biomonitoring research should be aware of ESBs as convenient sample sources and archives, while the ESB community should embrace biodiversity analyses as a new and highly relevant use of its collections. Thus, ESBs should cater increasingly also to the needs of the biomonitoring community, ideally in partnership with Biodiversity Biobanks. With further transparency of ESBs and the standardized publication of data, ESBs can become the basis for a wide array of interconnected scientific studies that allow scientists, natural resource managers and policy-makers an informed look back in time from an integrated biological and chemical perspective.

Availability of data and materials

Not applicable.

Abbreviations

BBB:

Biodiversity Biobank

BOLD:

Barcode of Life data system

DNA:

Desoxyribonucleic acid

eDNA:

Environmental desoxyribonucleic acid

ENA:

European Nucleotide Archive

ESB:

Environmental Specimen Bank

GGBN:

Global Genome Biodiversity Network

HTS:

High-throughput sequencing

IESB:

International Environmental Specimen Bank Group

LIB:

Leibniz Institute for the Analysis of Biodiversity Change

mRNA:

Messenger ribonucleic acid

rRNA:

Ribosomal ribonucleic acid

SPM:

Suspended particulate matter

References

  1. Anchordoquy TJ, Molina MC (2007) Preservation of DNA Cell. Preserv Technol 5:180–188. https://doi.org/10.1089/cpt.2007.0511

    CAS  Article  Google Scholar 

  2. Arribas P, Andújar C, Salces-Castellano A, Emerson BC, Vogler AP (2021) The limited spatial scale of dispersal in soil arthropods revealed with whole-community haplotype-level metabarcoding. Mol Ecol 30:48–61. https://doi.org/10.1111/mec.15591

    Article  Google Scholar 

  3. Astrin JJ, Zhou X, Misof B (2013) The importance of biobanking in molecular taxonomy, with proposed definitions for vouchers in a molecular context. ZooKeys. https://doi.org/10.3897/zookeys.365.5875

    Article  Google Scholar 

  4. Bálint M, Pfenninger M, Grossart H-P, Taberlet P, Vellend M, Leibold MA, Englund G, Bowler D (2018) Environmental DNA time series in ecology. Trends Ecol Evol 33:945–957. https://doi.org/10.1016/j.tree.2018.09.003

    Article  Google Scholar 

  5. Balmer JE, Morris AD, Hung H, Jantunen L, Vorkamp K, Rigét F, Evans M, Houde M, Muir DCG (2019) Levels and trends of current-use pesticides (CUPs) in the arctic: An updated review, 2010–2018. Emerg Contam 5:70–88. https://doi.org/10.1016/j.emcon.2019.02.002

    Article  Google Scholar 

  6. Barsoum N, Bruce C, Forster J, Ji Y-Q, Yu DW (2019) The devil is in the detail: Metabarcoding of arthropods provides a sensitive measure of biodiversity response to forest stand composition compared with surrogate measures of biodiversity. Ecol Indic 101:313–323. https://doi.org/10.1016/j.ecolind.2019.01.023

    CAS  Article  Google Scholar 

  7. Baust JG (2008) Strategies for the storage of DNA. Cell Preserv Technol 6:251

    Article  Google Scholar 

  8. Becker PR, Wise SA (2006) The U.S. National Biomonitoring Specimen Bank and the Marine Environmental Specimen Bank. J Environ Monit 8:795–799

    CAS  Article  Google Scholar 

  9. Biomatrica, 2009. RNAstable Handbook.

  10. Bohmann K, Evans A, Gilbert MTP, Carvalho GR, Creer S, Knapp M, Yu DW, de Bruyn M (2014) Environmental DNA for wildlife biology and biodiversity monitoring. Trends Ecol Evol 29:358–367. https://doi.org/10.1016/j.tree.2014.04.003

    Article  Google Scholar 

  11. Boulard L, Parrhysius P, Jacobs B, Dierkes G, Wick A, Buchmeier G, Koschorreck J, Ternes TA (2020) Development of an analytical method to quantify pharmaceuticals in fish tissues by liquid chromatography-tandem mass spectrometry detection and application to environmental samples. J Chromatogr A 1633:461612. https://doi.org/10.1016/j.chroma.2020.461612

    CAS  Article  Google Scholar 

  12. Bush A, Sollmann R, Wilting A, Bohmann K, Cole B, Balzter H, Martius C, Zlinszky A, Calvignac-Spencer S, Cobbold CA, Dawson TP, Emerson BC, Ferrier S, Gilbert MTP, Herold M, Jones L, Leendertz FH, Matthews L, Millington JDA, Olson JR, Ovaskainen O, Raffaelli D, Reeve R, Rödel M-O, Rodgers TW, Snape S, Visseren-Hamakers I, Vogler AP, White PCL, Wooster MJ, Yu DW (2017) Connecting Earth observation to high-throughput biodiversity data. Nat Ecol Evol 1:0176. https://doi.org/10.1038/s41559-017-0176

    Article  Google Scholar 

  13. Champlot S, Berthelot C, Pruvost M, Bennett EA, Grange T, Geigl E-M (2010) An Efficient multistrategy DNA decontamination procedure of PCR reagents for hypersensitive PCR applications. PLoS ONE 5:e13042. https://doi.org/10.1371/journal.pone.0013042

    CAS  Article  Google Scholar 

  14. Chaplow, J.S., Bond, A.L., Koschorreck, J., Rüdel, H., Shore, R.F., 2021. The role of environmental specimen banks in monitoring environmental contamination, In: Monitoring Environmental Contaminants. Elsevier B.V.

  15. Chariton AA, Ho KT, Proestou D, Bik H, Simpson SL, Portis LM, Cantwell MG, Baguley JG, Burgess RM, Pelletier MM, Perron M, Gunsch C, Matthews RA (2014) A molecular-based approach for examining responses of eukaryotes in microcosms to contaminant-spiked estuarine sediments. Environ Toxicol Chem 33:359–369. https://doi.org/10.1002/etc.2450

    CAS  Article  Google Scholar 

  16. Colotte M, Coudy D, Tuffet S, Bonnet J (2011) Adverse effect of air exposure on the stability of DNA stored at room temperature. Biopreservation Biobanking 9:47–50. https://doi.org/10.1089/bio.2010.0028

    Article  Google Scholar 

  17. Cordier T, Alonso-Sáez L, Apothéloz-Perret-Gentil L, Aylagas E, Bohan DA, Bouchez A, Chariton A, Creer S, Frühe L, Keck F, Keeley N, Laroche O, Leese F, Pochon X, Stoeck T, Pawlowski J, Lanzén A (2021) Ecosystems monitoring powered by environmental genomics: a review of current strategies with an implementation roadmap. Mol Ecol 30:2937–2958. https://doi.org/10.1111/mec.15472

    Article  Google Scholar 

  18. Cristescu ME (2019) Can Environmental RNA Revolutionize Biodiversity Science? Trends Ecol. Evol 34:694–697. https://doi.org/10.1016/j.tree.2019.05.003

    Article  Google Scholar 

  19. Day RD, Becker PR, Donard OFX, Pugh RS, Wise SA (2014) Environmental specimen banks as a resource for mercury and mercury isotope research in marine ecosystems. Environ Sci Process Impacts 16:10–27. https://doi.org/10.1039/C3EM00261F

    CAS  Article  Google Scholar 

  20. Deiner K, Fronhofer EA, Mächler E, Walser J-C, Altermatt F (2016) Environmental DNA reveals that rivers are conveyer belts of biodiversity information. Nat Commun 7:12544. https://doi.org/10.1038/ncomms12544

    CAS  Article  Google Scholar 

  21. Díaz C, Wege F-F, Tang CQ, Crampton-Platt A, Rüdel H, Eilebrecht E, Koschorreck J (2020) Aquatic suspended particulate matter as source of eDNA for fish metabarcoding. Sci Rep 10:14352. https://doi.org/10.1038/s41598-020-71238-w

    CAS  Article  Google Scholar 

  22. Djurhuus A, Closek CJ, Kelly RP, Pitz KJ, Michisaki RP, Starks HA, Walz KR, Andruszkiewicz EA, Olesin E, Hubbard K, Montes E, Otis D, Muller-Karger FE, Chavez FP, Boehm AB, Breitbart M (2020) Environmental DNA reveals seasonal shifts and potential interactions in a marine community. Nat Commun 11:254. https://doi.org/10.1038/s41467-019-14105-1

    CAS  Article  Google Scholar 

  23. Dopheide A, Xie D, Buckley TR, Drummond AJ, Newcomb RD (2019) Impacts of DNA extraction and PCR on DNA metabarcoding estimates of soil biodiversity. Methods Ecol Evol 10:120–133. https://doi.org/10.1111/2041-210X.13086

    Article  Google Scholar 

  24. Droege G, Barker K, Astrin JJ, Bartels P, Butler C, Cantrill D, Coddington J, Forest F, Gemeinholzer B, Hobern D, Mackenzie-Dodds J, Tuama Ó, É., Petersen, G., Sanjur, O., Schindel, D., Seberg, O., (2014) The global genome biodiversity network (GGBN) data portal. Nucleic Acids Res 42:D607–D612. https://doi.org/10.1093/nar/gkt928

    CAS  Article  Google Scholar 

  25. Fairbrother A, Muir D, Solomon KR, Ankley GT, Rudd MA, Boxall ABA, Apell JN, Armbrust KL, Blalock BJ, Bowman SR, Campbell LM, Cobb GP, Connors KA, Dreier DA, Evans MS, Henry CJ, Hoke RA, Houde M, Klaine SJ, Klaper RD, Kullik SA, Lanno RP, Meyer C, Ottinger MA, Oziolor E, Petersen EJ, Poynton HC, Rice PJ, Rodriguez-Fuentes G, Samel A, Shaw JR, Steevens JA, Verslycke TA, Vidal-Dorsch DE, Weir SM, Wilson P, Brooks BW (2019) Toward sustainable environmental quality: priority research questions for North America. Environ Toxicol Chem 38:1606–1624. https://doi.org/10.1002/etc.4502

    CAS  Article  Google Scholar 

  26. Faxneld S, Berger U, Helander B, Danielsson S, Miller A, Nyberg E, Persson J-O, Bignert A (2016) Temporal trends and geographical differences of perfluoroalkyl acids in Baltic sea herring and white-tailed sea eagle eggs in Sweden. Environ Sci Technol 50:13070–13079. https://doi.org/10.1021/acs.est.6b03230

    CAS  Article  Google Scholar 

  27. Furley TH, Brodeur J, Silva de Assis HC, Carriquiriborde P, Chagas KR, Corrales J, Denadai M, Fuchs J, Mascarenhas R, Miglioranza KS, Miguez Caramés DM, Navas JM, Nugegoda D, Planes E, Rodriguez-Jorquera IA, Orozco-Medina M, Boxall AB, Rudd MA, Brooks BW (2018) Toward sustainable environmental quality: Identifying priority research questions for Latin America. Integr Environ Assess Manag 14:344–357. https://doi.org/10.1002/ieam.2023

    CAS  Article  Google Scholar 

  28. Gewurtz SB, De Silva AO, Backus SM, McGoldrick DJ, Keir MJ, Small J, Melymuk L, Muir DCG (2012) Perfluoroalkyl contaminants in lake Ontario lake trout: detailed examination of current status and long-term trends. Environ Sci Technol 46:5842–5850. https://doi.org/10.1021/es3006095

    CAS  Article  Google Scholar 

  29. Gleason JE, Elbrecht V, Braukmann TWA, Hanner RH, Cottenie K (2020) Assessment of stream macroinvertebrate communities with eDNA is not congruent with tissue-based metabarcoding. Mol Ecol. https://doi.org/10.1111/mec.15597

    Article  Google Scholar 

  30. Goldberg CS, Turner CR, Deiner K, Klymus KE, Thomsen PF, Murphy MA, Spear SF, McKee A, Oyler-McCance SJ, Cornman RS, Laramie MB, Mahon AR, Lance RF, Pilliod DS, Strickler KM, Waits LP, Fremier AK, Takahara T, Herder JE, Taberlet P (2016) Critical considerations for the application of environmental DNA methods to detect aquatic species. Methods Ecol Evol 7:1299–1307. https://doi.org/10.1111/2041-210X.12595

    Article  Google Scholar 

  31. Greaves AK, Letcher RJ, Chen D, McGoldrick DJ, Gauthier LT, Backus SM (2016) Retrospective analysis of organophosphate flame retardants in herring gull eggs and relation to the aquatic food web in the Laurentian Great Lakes of North America. Environ Res 150:255–263. https://doi.org/10.1016/j.envres.2016.06.006

    CAS  Article  Google Scholar 

  32. Guardiola M, Wangensteen OS, Taberlet P, Coissac E, Uriz MJ, Turon X (2016) Spatio-temporal monitoring of deep-sea communities using metabarcoding of sediment DNA and RNA. PeerJ 4:e2807. https://doi.org/10.7717/peerj.2807

    Article  Google Scholar 

  33. Hanson N, Larsson Å, Parkkonen J, Faxneld S, Nyberg E, Bignert A, Henning HE, Bryhn A, Olsson J, Karlson AML, Förlin L (2020) Ecological changes as a plausible explanation for differences in uptake of contaminants between European perch and eelpout in a coastal area of the Baltic Sea. Environ Toxicol Pharmacol 80:103455. https://doi.org/10.1016/j.etap.2020.103455

    CAS  Article  Google Scholar 

  34. Hebert PDN, Cywinska A, Ball SL, deWaard JR (2003) Biological identifications through DNA barcodes. Proc R Soc Lond B Biol Sci 270:313–321. https://doi.org/10.1098/rspb.2002.2218

    CAS  Article  Google Scholar 

  35. Hernandez GE, Mondala TS, Head SR (2009) Assessing a novel room-temperature RNA storage medium for compatibility in microarray gene expression analysis. Biotechniques 47:667–670. https://doi.org/10.2144/000113209

    CAS  Article  Google Scholar 

  36. Hollender J, van Bavel B, Dulio V, Farmen E, Furtmann K, Koschorreck J, Kunkel U, Krauss M, Munthe J, Schlabach M, Slobodnik J, Stroomberg G, Ternes T, Thomaidis NS, Togola A, Tornero V (2019) High resolution mass spectrometry-based non-target screening can support regulatory environmental monitoring and chemicals management. Environ Sci Eur 31:42. https://doi.org/10.1186/s12302-019-0225-x

    CAS  Article  Google Scholar 

  37. Howlett SE, Castillo HS, Gioeni LJ, Robertson JM, Donfack J (2014) Evaluation of DNAstable™ for DNA storage at ambient temperature. Forensic Sci Int Genet 8:170–178. https://doi.org/10.1016/j.fsigen.2013.09.003

    CAS  Article  Google Scholar 

  38. IPBES, 2019. Summary for policymakers of the global assessment report on biodiversity and ecosystem services.

  39. Jarman SN, Berry O, Bunce M (2018) The value of environmental DNA biobanking for long-term biomonitoring. Nat Ecol Evol 2:1192–1193. https://doi.org/10.1038/s41559-018-0614-3

    Article  Google Scholar 

  40. Ji Y, Ashton L, Pedley SM, Edwards DP, Tang Y, Nakamura A, Kitching R, Dolman PM, Woodcock P, Edwards FA, Larsen TH, Hsu WW, Benedick S, Hamer KC, Wilcove DS, Bruce C, Wang X, Levi T, Lott M, Emerson BC, Yu DW (2013) Reliable, verifiable and efficient monitoring of biodiversity via metabarcoding. Ecol Lett 16:1245–1257. https://doi.org/10.1111/ele.12162

    Article  Google Scholar 

  41. Kemp BM, Smith DG (2005) Use of bleach to eliminate contaminating DNA from the surface of bones and teeth. Forensic Sci Int 154:53–61. https://doi.org/10.1016/j.forsciint.2004.11.017

    CAS  Article  Google Scholar 

  42. Knebelsberger T, Stöger I (2012) DNA extraction, preservation, and amplification. In: Kress WJ, Erickson DL (eds) DNA barcodes: methods and protocols. Humana Press, Totowa, NJ, pp 311–338. https://doi.org/10.1007/978-1-61779-591-6_14

    Chapter  Google Scholar 

  43. Knudtzon NC, Thorstensen H, Ruus A, Helberg M, Bæk K, Enge EK, Borgå K (2021) Maternal transfer and occurrence of siloxanes, chlorinated paraffins, metals, PFAS and legacy POPs in herring gulls (Larus argentatus) of different urban influence. Environ Int 152:106478. https://doi.org/10.1016/j.envint.2021.106478

    CAS  Article  Google Scholar 

  44. Koizumi A, Harada KH, Inoue K, Hitomi T, Yang H-R, Moon C-S, Wang P, Hung NN, Watanabe T, Shimbo S, Ikeda M (2009) Past, present, and future of environmental specimen banks. Environ Health Prev Med 14:307–318. https://doi.org/10.1007/s12199-009-0101-1

    Article  Google Scholar 

  45. Kotthoff M, Rüdel H, Jürling H, Severin K, Hennecke S, Friesen A, Koschorreck J (2019) First evidence of anticoagulant rodenticides in fish and suspended particulate matter: spatial and temporal distribution in German freshwater aquatic systems. Environ Sci Pollut Res 26:7315–7325. https://doi.org/10.1007/s11356-018-1385-8

    CAS  Article  Google Scholar 

  46. Krehenwinkel H, Wolf M, Lim JY, Rominger AJ, Simison WB, Gillespie RG (2017) Estimating and mitigating amplification bias in qualitative and quantitative arthropod metabarcoding. Sci Rep 7:17668. https://doi.org/10.1038/s41598-017-17333-x

    CAS  Article  Google Scholar 

  47. Küster A, Becker PR, Kucklick JR, Pugh RS, Koschorreck J (2015) The international environmental specimen banks—let’s get visible. Environ Sci Pollut Res 22:1559–1561. https://doi.org/10.1007/s11356-013-2482-3

    Article  Google Scholar 

  48. Leung KMY, Yeung KWY, You J, Choi K, Zhang X, Smith R, Zhou G-J, Yung MMN, Arias-Barreiro C, An Y-J, Burket SR, Dwyer R, Goodkin N, Hii YS, Hoang T, Humphrey C, Iwai CB, Jeong S-W, Juhel G, Karami A, Kyriazi-Huber K, Lee K-C, Lin B-L, Lu B, Martin P, Nillos MG, Oginawati K, Rathnayake IVN, Risjani Y, Shoeb M, Tan CH, Tsuchiya MC, Ankley GT, Boxall ABA, Rudd MA, Brooks BW (2020) Toward sustainable environmental quality: priority research questions for Asia. Environ Toxicol Chem 39:1485–1505. https://doi.org/10.1002/etc.4788

    CAS  Article  Google Scholar 

  49. Li F, Peng Y, Fang W, Altermatt F, Xie Y, Yang J, Zhang X (2018) Application of environmental DNA metabarcoding for predicting anthropogenic pollution in rivers. Environ Sci Technol 52:11708–11719. https://doi.org/10.1021/acs.est.8b03869

    CAS  Article  Google Scholar 

  50. Liénart C, Garbaras A, Qvarfordt S, Sysoev AÖ, Höglander H, Walve J, Schagerström E, Eklöf J, Karlson AM (2021) Long-term changes in trophic ecology of blue mussels in a rapidly changing ecosystem. Limnol Oceanogr 66:694–710. https://doi.org/10.1002/lno.11633

    Article  Google Scholar 

  51. Lind Y, Bignert A, Odsjö T (2006) Decreasing lead levels in Swedish biota revealed by 36 years (1969–2004) of environmental monitoring. J Environ Monit 8:824–834. https://doi.org/10.1039/B517867C

    CAS  Article  Google Scholar 

  52. Liu M, Clarke LJ, Baker SC, Jordan GJ, Burridge CP (2020) A practical guide to DNA metabarcoding for entomological ecologists. Ecol Entomol 45:373–385. https://doi.org/10.1111/een.12831

    Article  Google Scholar 

  53. Lopez MLD, Lin Y, Sato M, Hsieh C, Shiah F-K, Machida RJ (2021) Using metatranscriptomics to estimate the diversity and composition of zooplankton communities. Mol Ecol Resour. https://doi.org/10.1111/1755-0998.13506

    Article  Google Scholar 

  54. Lou JJ, Mirsadraei L, Sanchez DE, Wilson RW, Shabihkhani M, Lucey GM, Wei B, Singer EJ, Mareninov S, Yong WH (2014) A review of room temperature storage of biospecimen tissue and nucleic acids for anatomic pathology laboratories and biorepositories. Biorepositories Biobanks 47:267–273. https://doi.org/10.1016/j.clinbiochem.2013.12.011

    CAS  Article  Google Scholar 

  55. Lynggaard C, Yu DW, Oliveira G, Caldeira CF, Ramos SJ, Ellegaard MR, Gilbert MTP, Gastauer M, Bohmann K (2020) DNA-based arthropod diversity assessment in amazonian iron mine lands show ecological succession towards undisturbed reference sites. Front Ecol Evol 8:426. https://doi.org/10.3389/fevo.2020.590976

    Article  Google Scholar 

  56. Ma S, Huang Y, van Huystee RB (2004) Improved plant RNA stability in storage. Anal Biochem 326:122–124. https://doi.org/10.1016/j.ab.2003.10.026

    CAS  Article  Google Scholar 

  57. Machida RJ, Kurihara H, Nakajima R, Sakamaki T, Lin Y-Y, Furusawa K (2021) Comparative analysis of zooplankton diversities and compositions estimated from complement DNA and genomic DNA amplicons, metatranscriptomics, and morphological identifications. ICES J Mar Sci. https://doi.org/10.1093/icesjms/fsab084

    Article  Google Scholar 

  58. Majaneva M, Diserud OH, Eagle SHC, Hajibabaei M, Ekrem T (2018) Choice of DNA extraction method affects DNA metabarcoding of unsorted invertebrate bulk samples. Metabarcoding Metagenomics 2:e26664. https://doi.org/10.3897/mbmg.2.26664

    Article  Google Scholar 

  59. Mathay C, Yan W, Chuaqui R, Skubitz APN, Jeon J-P, Fall N, Betsou F, Barnes, (ISBER Biospecimen Science Working Group), Michael (2012) Short-term stability study of RNA at room temperature. Biopreservation Biobanking 10:532–542. https://doi.org/10.1089/bio.2012.0030

    CAS  Article  Google Scholar 

  60. Mendes LW, Braga LPP, Navarrete AA, de Souza DG, Silva GGZ, Tsai SM (2017) Using metagenomics to connect microbial community biodiversity and functions. Curr Issues Mol Biol. https://doi.org/10.21775/cimb.024.103

    Article  Google Scholar 

  61. Nagorka R, Koschorreck J (2020) Trends for plasticizers in German freshwater environments – Evidence for the substitution of DEHP with emerging phthalate and non-phthalate alternatives. Environ Pollut 262:114237. https://doi.org/10.1016/j.envpol.2020.114237

    CAS  Article  Google Scholar 

  62. Odsjö T (2006) The environmental specimen bank, Swedish Museum of Natural History—A base for contaminant monitoring and environmental research. J Environ Monit 8:791–794. https://doi.org/10.1039/B602676C

    Article  Google Scholar 

  63. Paulus M, Klein R, Wagner G, Müller P (1996) Biomonitoring and environmental specimen banking. Environ Sci Pollut Res 3:169–177. https://doi.org/10.1007/BF02985528

    CAS  Article  Google Scholar 

  64. Pilliod DS, Goldberg CS, Arkle RS, Waits LP (2014) Factors influencing detection of eDNA from a stream-dwelling amphibian. Mol Ecol Resour 14:109–116. https://doi.org/10.1111/1755-0998.12159

    CAS  Article  Google Scholar 

  65. Pochon X, Zaiko A, Fletcher LM, Laroche O, Wood SA (2017) Wanted dead or alive? Using metabarcoding of environmental DNA and RNA to distinguish living assemblages for biosecurity applications. PLoS ONE 12:e0187636. https://doi.org/10.1371/journal.pone.0187636

    CAS  Article  Google Scholar 

  66. Quince C, Walker AW, Simpson JT, Loman NJ, Segata N (2017) Shotgun metagenomics, from sampling to analysis. Nat Biotechnol 35:833–844. https://doi.org/10.1038/nbt.3935

    CAS  Article  Google Scholar 

  67. Ratnasingham S, Hebert PDN (2007) The barcode of life data system. Mol Ecol Notes 7:355–364. https://doi.org/10.1111/j.1471-8286.2007.01678.x

    CAS  Article  Google Scholar 

  68. Renshaw MA, Olds BP, Jerde CL, McVeigh MM, Lodge DM (2015) The room temperature preservation of filtered environmental DNA samples and assimilation into a phenol–chloroform–isoamyl alcohol DNA extraction. Mol Ecol Resour 15:168–176. https://doi.org/10.1111/1755-0998.12281

    CAS  Article  Google Scholar 

  69. Rüther, M., Bandholtz, T., 2009. The German environmental specimen bank: discovering data and information on the web.

  70. Sakata MK, Yamamoto S, Gotoh RO, Miya M, Yamanaka H, Minamoto T (2020) Sedimentary eDNA provides different information on timescale and fish species composition compared with aqueous eDNA. Environ DNA 2:505–518. https://doi.org/10.1002/edn3.75

    Article  Google Scholar 

  71. Sales NG, Wangensteen OS, Carvalho DC, Mariani S (2019) Influence of preservation methods, sample medium and sampling time on eDNA recovery in a neotropical river. Environ DNA. https://doi.org/10.1002/edn3.14

    Article  Google Scholar 

  72. Schuur, S.S., Kucklick, J.R., Lynch, J.M., Pugh, R.S., Ragland, J.M., Reiner, J.L., Trevillian, J., 2016. Lessons Learned from Monitoring Organic Contaminants in Three Decades of Marine Samples from the Pacific Basin Archived at the USA’s Marine Environmental Specimen Bank, in: Persistent Organic Chemicals in the Environment: Status and Trends in the Pacific Basin Counties II Temporal Trends.

  73. Seelenfreund E, Robinson WA, Amato CM, Tan A-C, Kim J, Robinson SE (2014) Long term storage of dry versus frozen RNA for next generation molecular studies. PLoS ONE 9:e111827. https://doi.org/10.1371/journal.pone.0111827

    CAS  Article  Google Scholar 

  74. Sepulveda AJ, Hutchins PR, Forstchen M, Mckeefry MN, Swigris AM (2020) The elephant in the lab (and field): contamination in aquatic environmental DNA studies. Front Ecol Evol 8:440. https://doi.org/10.3389/fevo.2020.609973

    Article  Google Scholar 

  75. Seymour M, Edwards FK, Cosby BJ, Bista I, Scarlett PM, Brailsford FL, Glanville HC, de Bruyn M, Carvalho GR, Creer S (2021) Environmental DNA provides higher resolution assessment of riverine biodiversity and ecosystem function via spatio-temporal nestedness and turnover partitioning. Commun Biol 4:512. https://doi.org/10.1038/s42003-021-02031-2

    CAS  Article  Google Scholar 

  76. Snape JR, Maund SJ, Pickford DB, Hutchinson TH (2004) Ecotoxicogenomics: the challenge of integrating genomics into aquatic and terrestrial ecotoxicology. Aquat Toxicol 67(2):143–54. https://doi.org/10.1016/j.aquatox.2003.11.011

    CAS  Article  Google Scholar 

  77. Taberlet P, Bonin A, Zinger L, Coissac E (2018) Environmental DNA: for biodiversity research and monitoring. Oxford Universty Press, Oxford, UK. p. 253. https://doi.org/10.1093/oso/9780198767220.001.0001

    Book  Google Scholar 

  78. Taberlet P, Coissac E, Hajibabei M, Riesenberg LH (2012) Environmental DNA. Mol Ecol 21:1789–1793. https://doi.org/10.1111/j.1365-294X.2012.05542.x

    CAS  Article  Google Scholar 

  79. Tanabe S (2006) Environmental Specimen Bank in Ehime University (es-BANK), Japan for global monitoring. J Environ Monit 8:782–790. https://doi.org/10.1039/B602677J

    CAS  Article  Google Scholar 

  80. Turner CR, Uy KL, Everhart RC (2015) Fish environmental DNA is more concentrated in aquatic sediments than surface water. Spec. Issue Environ. DNA Powerful New Tool Biol Conserv 183:93–102. https://doi.org/10.1016/j.biocon.2014.11.017

    Article  Google Scholar 

  81. Uhler J, Redlich S, Zhang J, Hothorn T, Tobisch C, Ewald J, Thorn S, Seibold S, Mitesser O, Morinière J, Bozicevic V, Benjamin CS, Englmeier J, Fricke U, Ganuza C, Haensel M, Riebl R, Rojas-Botero S, Rummler T, Uphus L, Schmidt S, Steffan-Dewenter I, Müller J (2021) Relationship of insect biomass and richness with land use along a climate gradient. Nat Commun 12:5946. https://doi.org/10.1038/s41467-021-26181-3

    CAS  Article  Google Scholar 

  82. Valentini A, Pompanon F, Taberlet P (2009) DNA barcoding for ecologists. Trends Ecol Evol 24:110–117. https://doi.org/10.1016/j.tree.2008.09.011

    Article  Google Scholar 

  83. Van den Brink PJ, Boxall ABA, Maltby L, Brooks BW, Rudd MA, Backhaus T, Spurgeon D, Verougstraete V, Ajao C, Ankley GT, Apitz SE, Arnold K, Brodin T, Cañedo-Argüelles M, Chapman J, Corrales J, Coutellec M-A, Fernandes TF, Fick J, Ford AT, Giménez Papiol G, Groh KJ, Hutchinson TH, Kruger H, Kukkonen JVK, Loutseti S, Marshall S, Muir D, Ortiz-Santaliestra ME, Paul KB, Rico A, Rodea-Palomares I, Römbke J, Rydberg T, Segner H, Smit M, van Gestel CAM, Vighi M, Werner I, Zimmer EI, van Wensem J (2018) Toward sustainable environmental quality: Priority research questions for Europe. Environ Toxicol Chem 37:2281–2295. https://doi.org/10.1002/etc.4205

    CAS  Article  Google Scholar 

  84. van Dijk J, Leopold A, Flerlage H, van Wezel A, Seiler T-B, Enrici M-H, Bloor MC (2021) The EU Green Deal’s ambition for a toxic-free environment: filling the gap for science-based policymaking. Integr Environ Assess Manag 17:1105–1113. https://doi.org/10.1002/ieam.4429

    Article  Google Scholar 

  85. Villeneuve DL, Garcia-Reyero N, Escalon BL, Jensen KM, Cavallin JE, Makynen EA, Durhan EJ, Kahl MD, Thomas LM, Perkins EJ, Ankley GT (2012) Ecotoxicogenomics to support ecological risk assessment: a case study with bisphenol A in fish. Environ Sci Technol 46(1):51–9. https://doi.org/10.1021/es201150a

    CAS  Article  Google Scholar 

  86. Weber S, Brink L, Wörner M, Künzel S, Veith M, Teubner D, Klein R, Paulus M, Krehenwinkel H (2021) Molecular diet analysis in zebra and quagga mussels (Dreissena spp.) and an assessment of the utility of aquatic filter feeders as biological eDNA filters. BioRxiv. https://doi.org/10.1101/2021.03.01.432951

    Article  Google Scholar 

  87. Wegl G, Grabner N, Köstelbauer A, Klose V, Ghanbari M (2021) Toward Best Practice in Livestock Microbiota Research: A Comprehensive Comparison of Sample Storage and DNA Extraction Strategies. Front Microbiol 12:322. https://doi.org/10.3389/fmicb.2021.627539

    Article  Google Scholar 

  88. Welti EAR, Joern A, Ellison AM, Lightfoot DC, Record S, Rodenhouse N, Stanley EH, Kaspari M (2021) Studies of insect temporal trends must account for the complex sampling histories inherent to many long-term monitoring efforts. Nat Ecol Evol 5:589–591. https://doi.org/10.1038/s41559-021-01424-0

    Article  Google Scholar 

  89. Wilcox TM, McKelvey KS, Young MK, Jane SF, Lowe WH, Whiteley AR, Schwartz MK (2013) Robust Detection of Rare Species Using Environmental DNA: The Importance of Primer Specificity. PLoS ONE 8:e59520. https://doi.org/10.1371/journal.pone.0059520

    CAS  Article  Google Scholar 

  90. Yamakawa A, Amouroux D, Tessier E, Bérail S, Fettig I, Barre JPG, Koschorreck J, Rüdel H, Donard OFX (2021) Hg isotopic composition of one-year-old spruce shoots: application to long-term Hg atmospheric monitoring in Germany. Chemosphere 279:130631. https://doi.org/10.1016/j.chemosphere.2021.130631

    CAS  Article  Google Scholar 

  91. Yu DW, Ji Y, Emerson BC, Wang X, Ye C, Yang C, Ding Z (2012) Biodiversity soup: metabarcoding of arthropods for rapid biodiversity assessment and biomonitoring. Methods Ecol Evol 3:613–623. https://doi.org/10.1111/j.2041-210X.2012.00198.x

    Article  Google Scholar 

  92. Yuan B, Vorkamp K, Roos AM, Faxneld S, Sonne C, Garbus SE, Lind Y, Eulaers I, Hellström P, Dietz R, Persson S, Bossi R, de Wit CA (2019) Accumulation of short-, medium-, and long-chain chlorinated paraffins in marine and terrestrial animals from Scandinavia. Environ Sci Technol 53:3526–3537. https://doi.org/10.1021/acs.est.8b06518

    CAS  Article  Google Scholar 

  93. Zhang X (2019) Environmental DNA shaping a new era of ecotoxicological research. Environ Sci Technol 53:5605–5612. https://doi.org/10.1021/acs.est.8b06631

    CAS  Article  Google Scholar 

  94. Zizka VMA, Weiss M, Leese F (2020) Can metabarcoding resolve intraspecific genetic diversity changes to environmental stressors? A test case using river macrozoobenthos. MBMG 4:e51925. https://doi.org/10.3897/mbmg.4.51925

    Article  Google Scholar 

Download references

Acknowledgements

We thank Florian Leese from the University of Duisburg-Essen and Thomas Källman from the Swedish Museum of Natural History as well as two anonymous reviewers for helpful discussion and input to the manuscript.

Funding

Open Access funding enabled and organized by Projekt DEAL. VMAZ is member of the DINA (Diversity of Insects in Nature protected Areas) project supported by the German Federal Ministry of Education and Research. No further funding was acquired for the manuscript.

Author information

Authors and Affiliations

Authors

Contributions

Conceptualization: JJA, JK, VMAZ, Manuscript writing and editing: CCK, JJA, JK, VMAZ. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Vera M. A. Zizka, Jan Koschorreck or Jonas J. Astrin.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent of publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Zizka, V.M.A., Koschorreck, J., Khan, C.C. et al. Long-term archival of environmental samples empowers biodiversity monitoring and ecological research. Environ Sci Eur 34, 40 (2022). https://doi.org/10.1186/s12302-022-00618-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12302-022-00618-y

Keywords

  • Environmental specimen banks
  • Biomonitoring
  • eDNA
  • Metabarcoding
  • Biodiversity biobanks