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2. Automatic image-based identification and biomass estimation of invertebrates

3. Empirical Bayes to assess ecological diversity and similarity with overdispersion in multivariate counts

4. Human experts vs. machines in taxa recognition

6. A practical guide to DNA-based methods for biodiversity assessment

10. Policy-driven monitoring and evaluation: Does it support adaptive management of socio-ecological systems?

11. Protecting and restoring Europe's waters: An analysis of the future development needs of the Water Framework Directive

12. Metabarcoding for use in Nordic routine aquatic biomonitoring - a validation study​

20. DNA metabarcoding : Guidelines to monitor phytoplankton diversity and distribution in marine and brackish waters

21. DNA metabarcoding - Guidelines to monitor phytoplankton diversity and distribution in marine and brackish waters

22. Case study optimisation strategies

24. Multiple Order Gradient Feature for Macro-Invertebrate Identification Using Support Vector Machines

25. Why We Need Sustainable Networks Bridging Countries, Disciplines, Cultures and Generations for Aquatic Biomonitoring 2.0: A Perspective Derived From the DNAqua-Net COST Action

28. WG3: New Concepts and Standards for Data management (Content, curation, quality management, technical framework, documentation)

29. A strategy for successful integration of DNA-based methods in aquatic monitoring

32. A strategy for successful integration of DNA-based methods in aquatic monitoring

33. Supplementary material 1 from: Blancher P, Lefrançois E, Rimet F, Vasselon V, Argillier C, Arle J, Beja P, Boets P, Boughaba J, Chauvin C, Deacon M, Duncan W, Ejdung G, Erba S, Ferrari B, Fischer H, Hänfling B, Haldin M, Hering D, Hette-Tronquart N, Hiley A, Järvinen M, Jeannot B, Kahlert M, Kelly M, Kleinteich J, Koyuncuoğlu S, Krenek S, Langhein-Winther S, Leese F, Mann D, Marcel R, Marcheggiani S, Meissner K, Mergen P, Monnier O, Narendja F, Neu D, Onofre Pinto V, Pawlowska A, Pawlowski J, Petersen M, Poikane S, Pont D, Renevier M-S, Sandoy S, Svensson J, Trobajo R, Tünde Zagyva A, Tziortzis I, van der Hoorn B, Vasquez MI, Walsh K, Weigand A, Bouchez A (2022) A strategy for successful integration of DNA-based methods in aquatic monitoring. Metabarcoding and Metagenomics 6: e85652. https://doi.org/10.3897/mbmg.6.85652

36. Roadmap for implementing environmental DNA (eDNA) and other molecular monitoring methods in Finland – Vision and action plan for 2022–2025

37. Marine monitoring in transition: On the verge of technological revolution?

38. The pathway of molecular methods from research to routine use

39. Technical challenges when scaling up macroinvertebrate DNA metabarcoding

40. A practical guide to DNA-based methods for biodiversity assessment

41. Figure 1 from: Laamanen T, Norros V, Suikkanen S, Tolkkinen M, Vuorio K, Vihervaara P, Sirkiä P, Jørgensen K, Kortelainen P, Reunamo A, Järvinen M, Meissner K (2021) A pilot for implementing environmental DNA (eDNA) based methods into environmental and biomonitoring. ARPHA Conference Abstracts 4: e64800. https://doi.org/10.3897/aca.4.e64800

42. A pilot for implementing environmental DNA (eDNA) based methods into environmental and biomonitoring

44. A Synthesis of Marine Monitoring Methods With the Potential to Enhance the Status Assessment of the Baltic Sea

45. Human experts vs. machines in taxa recognition

46. Automatic image‐based identification and biomass estimation of invertebrates

47. Deep learning and computer vision will transform entomology

48. Metabarcoding for use in Nordic routine aquatic biomonitoring - a validation study​

49. A Synthesis of Marine Monitoring Methods With the Potential to Enhance the Status Assessment of the Baltic Sea

50. Science Advances

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