Advancing enviromental DNA approaches for aptimizing aquatic ecosytem monitoring and ecological assessment

Mukeshkumar Bhendarkar PhD Thesis 2025 Advancing environmental DNA approaches for optimizing aquatic ecosystem monitoring and ecological assessment Supervisor Naiara Rodríguez-Ezpeleta PhD Thesis Advancing environmental DNA approaches for optimizing aquatic ecosystem monitoring and ecological assessment Presented by Mukeshkumar Parasram Bhendarkar Thesis supervisor Naiara Rodríguez-Ezpeleta Department Zoology and Animal Cell Biology PhD Program Marine Environment and Resources April 2025 (cc) 2025 Mukeshkumar Bhendarkar (cc by-nc-nd 4.0) i The research carried out in this Philosophiae Doctor thesis has been developed in AZTI -BRTA (Sukarrieta, Spain). Mukeshkumar Parasram Bhendarkar has been supported by Indian Council of Agricultural Research (ICAR) through the for his doctoral research. The research works has been funded by the INTERREG Atlantic Area - (EAPA_18/2018), by the Department of Economic Development and Infrastructure of the Basque - Development and application of genetic methods to improve h project - (CTM2017-89500-R), by the Game & Wildlife Conservation Trust, Queen Mary University (QMUL) of , by the Basque Water Agency (URA) through a convention with AZTI, by the European Union's Horizon Europe program (projects GES4SEAS with grant agreement no. 101059877 and OBAMA-NEXT with grant agreement no. 101081642). Recommended citation: Bhendarkar, M. (2025). Advancing environmental DNA approaches for optimizing aquatic ecosystem monitoring and ecological assessment. PhD Thesis. Department of Zoology and Animal Cell Biology, University of the Basque Country. Cover page designed by the author. Advancing environmental DNA approaches for optimizing aquatic ecosystem monitoring and ecological assessment ACKNOWLEDGEMENTS ....................................................................................................................... v GENERAL INTRODUCTION ................................................................................................................. 2 1. The significance of aquatic ecosystems ......................................................................................... 3 1.1 Ecological functions and services ............................................................................................. 3 1.2 Fish as in ecological indicators of aquatic ecosystems ............................................................. 5 1.3 The Economic Significance of Fish .......................................................................................... 5 1.4 Threats to fish biodiversity and fisheries sustainability ............................................................ 6 2. The importance of fish biodiversity monitoring in aquatic ecosystems ..................................... 9 2.1 Current traditional fish monitoring methods ............................................................................ 9 2.2 Environmental DNA (eDNA) analysis: a revolutionary approach for fish monitoring and ecological assessment ......................................................................................................................... 11 3. Rationale of the study ................................................................................................................... 13 4. Hypothesis, aim and objective ..................................................................................................... 13 4.1 Working hypothesis ................................................................................................................ 13 4.2 Overarching aim and objectives ............................................................................................. 13 5. Structure of the Thesis ................................................................................................................. 14 CHAPTER 1 ............................................................................................................................................. 16 EXPLORING UNCHARTED TERRITORY: NEW FRONTIERS IN ENVIRONMENTAL DNA FOR TROPICAL FISHERIES MANAGEMENT Abstract ................................................................................................................................................. 17 1. Introduction .................................................................................................................................. 18 2. Perspectives ................................................................................................................................... 20 2.1 What is eDNA and how is it analyzed? .................................................................................. 20 3. eDNA: a game changer for tropical fisheries studies? .............................................................. 22 3.1 Biomonitoring and conservation ............................................................................................. 23 3.2 Fish migration patterns ........................................................................................................... 25 3.3 Reproductive status ................................................................................................................ 26 3.4 Systematic detection of at-risk, rare, or cryptic species .......................................................... 27 3.5 Early-warning system of invasive and alien species ............................................................... 28 3.6 Interplay of diets and tropic interaction .................................................................................. 29 3.7 Population genetics and eDNA ............................................................................................... 29 3.8 Natural samplers DNA (nsDNA) ............................................................................................ 30 3.9 Additional applications of eDNA in the fisheries sector ........................................................ 31 4. Challenges and limitations of eDNA ........................................................................................... 32 4.1 Barcode reference libraries ..................................................................................................... 32 4.2 Abundance estimation ............................................................................................................ 34 4.3 Life stages ............................................................................................................................... 35 4.4 Uncertainty about the ecology of eDNA ................................................................................ 35 4.5 Standardization of methods .................................................................................................... 36 5. What lies ahead for tropical fisheries and ecology using eDNA? ............................................. 37 6. Conclusions ................................................................................................................................... 38 CHAPTER 2 ............................................................................................................................................. 41 LESSONS LEARNED FROM APPLYING EDNA SURVEYING TO DIADROMOUS FISH DETECTION ACROSS THE NORTH-EAST ATLANTIC REGION TABLE OF CONTENT iii Abstract .................................................................................................................................................42 1. Introduction .................................................................................................................................. 43 2. Material and Methods .................................................................................................................. 45 2.1 Sampling location and reference data set ............................................................................... 45 2.2 Water sample collection and DNA extraction ........................................................................ 47 2.3 Species-specific detection assay development........................................................................ 47 2.4 Quantitative PCR (qPCR) analysis ......................................................................................... 48 2.5 Digital PCR (dPCR) analysis ................................................................................................. 49 2.6 Quantification of dPCR and qPCR analysis ........................................................................... 50 2.7 Confusion matrix analysis ...................................................................................................... 50 3. Results............................................................................................................................................ 51 3.1 Comparative performance of eDNA analysis ......................................................................... 51 3.2 River specific detection rate ................................................................................................... 53 3.3 Insight from digital PCR (dPCR) and quantitative PCR (qPCR) assessment ......................... 54 3.4 eDNA abundance patterns along river stretches ..................................................................... 55 4. Discussion ...................................................................................................................................... 57 4.1 Detection discrepancies among species .................................................................................. 57 4.2 When and how to sample ........................................................................................................ 58 4.3 Methodological differences .................................................................................................... 59 4.4 Can eDNA be used as reliable sources of presence/absence for diadromous fish? ................ 60 CHAPTER 3 ............................................................................................................................................. 63 ADVANCING ECOLOGICAL ASSESSMENT: THE INTEGRATION OF EDNA METABARCODING INTO AN ESTUARINE FISH INDEX Abstract ................................................................................................................................................. 64 1. Introduction .................................................................................................................................. 65 2. Material and Methods .................................................................................................................. 68 2.1 Study area and sample collection ........................................................................................... 68 2.2 DNA extraction and amplicon library preparation ................................................................. 68 2.3 Read pre-processing and taxonomic assignment .................................................................... 69 2.4 AFI calculations ...................................................................................................................... 70 2.5 Statistical analysis .................................................................................................................. 71 3. Results............................................................................................................................................ 72 3.1 Sampling efficiency of eDNA and bottom trawling ............................................................... 72 3.2 Assessing trawl and eDNA-based estuarine ecological status ................................................ 73 4. Discussion ...................................................................................................................................... 76 4.1 Methodological contrasts ........................................................................................................ 76 4.2 Beyond the net: eDNA edge in estuarine ecological assessment ............................................ 79 5. Way forward ................................................................................................................................. 80 GENERAL DISCUSSION ....................................................................................................................... 83 1. Not just tools - Strategies: Methodological choices shape detection......................................... 85 1.1 Assay sensitivity and species detectability ............................................................................. 85 1.2 Different tool, different truths................................................................................................. 86 2. Detecting the undetectable: Interpretating false signal in eDNA data..................................... 87 2.1 False positives: context is everything ..................................................................................... 88 2.2 Uncovering false negatives ..................................................................................................... 88 3. Beyond species detection .............................................................................................................. 89 3.1 tropical ecosystems ............................................................... 90 4. The big picture: advancing eDNA science for the future .......................................................... 91 4.1 Improve understanding of eDNA fate and transport ............................................................... 92 Advancing environmental DNA approaches for optimizing aquatic ecosystem monitoring and ecological assessment 4.2 Enhance the quantitative power of eDNA ..............................................................................92 4.3 Expand and regionalize reference databases .......................................................................... 92 4.4 Integrate eDNA analysis into policy and monitoring frameworks ......................................... 92 4.5 Adopt automation and remote monitoring technologies ......................................................... 93 4.6 Promote interdisciplinary and inclusive collaboration............................................................ 93 4.7 Expand toward ecosystem-level, multi-trophic eDNA assessments ....................................... 93 4.8 Advance Global Standardization of eDNA Analysis .............................................................. 93 CONCLUSION AND THESIS ................................................................................................................ 95 REFERENCES ......................................................................................................................................... 98 Appendix A .............................................................................................................................................. i Appendix B .......................................................................................................................................... xxii ACKNOWLEDGEMENTS v Embarking on a PhD journey far from home has been one of the most transformative experiences of my life. Coming from India to Spain, this journey was not just about earning a degree it was about growth, adaptation, and constant learning. For me, more than the PhD title itself, it was the process, the people, and the experiences that truly mattered. First and foremost, I would like to express my deepest gratitude to my supervisor. Some people may not explain everything in words, yet their presence, aura, and personality become a silent yet powerful guide. You have been one of those people teaching through example, leadership, and character. Thank you for showing me the value of quiet strength and thoughtful precision. To my research group, I feel incredibly lucky to have walked this path with such inspiring colleagues and friends. Cristina, ate me later those small acts of kindness meant more than words. Oriol, your sharp insights and attention to detail were like a double-edged sword challenging me to improve while guiding me with precision. Inaki, the master of the lab your hands-on support and patience helped me navigate so many challenges. Alice, thank you for being a motivator your energy and encouragement kept me going. Specieal thanks to Marina, Natalia Díaz Arce, Natalia Gutierrez, Iker thank you for being part of this journey and for your suggestion time to time and warmth. I would also like to thank all the wonderful people at AZTI who stood by me through the highs and lows over these years. Your support, both personal and professional, truly shaped my thinking and my experience. I am especially grateful to Lorena, Roger, Elsa, Xavi, María, Isa, Ane, Iosu, Adri, and Uxue. A heartfelt thank you to César, for ensuring I never lacked anything when it came to technical support especially when dealing with official Indian websites. Your help was often the quiet force that kept things running smoothly. To my friends in Bermeo even though you may not have fully known what I was doing, their support, friendship, and company gave me a sense of belonging. A heartfelt thanks to Kamaran Bhai from Pakistan your warmth and friendship made me feel at home in a foreign land. You reminded me that home is not always a place I also wish to acknowledge the friends who were there when it mattered the most Karan, Yogesh, Pramod, Hemant, and Lohith Sir thank you for your constant tele-support, motivation, and friendship throughout the ups and downs of this PhD. I extend my sincere gratitude to the then Director of my institute, and to the Director General, ICAR, Dr. Pathak Sir, for making my international research visit possible. My heartfelt thanks to Bhaskar Sir, Pawar Sir, Kurade Sir, Nirmale Sir, Kakade Sir, and Prashant Sir scientists from ICAR-NIASM, Baramati who stood by every step of the way and supported me in administrative work from India. Advancing environmental DNA approaches for optimizing aquatic ecosystem monitoring and ecological assessment I would also like to acknowledge the Indian Council of Agricultural Research (ICAR) for funding this PhD. thankful to the administrative staff at ICAR-NIASM, Baramati, for their patience, cooperation, and support throughout the process. To my big family back home thank you for your constant encouragement, prayers, and belief in me. Your love has been a silent strength during the toughest days. To my mother your endless love, sacrifices, and unwavering support have been the And finally, to my wife and son you were my anchor during this journey. Thank you for your love, patience, and sacrifices. Your understanding during the long hours, your encouragement when I doubted myself, and your presence kept me going. Ishaan, your innocent smiles gave me hope on the hardest days. This accomplishment is as much yours as it is mine. This PhD was never just about academic achievement. It was a lesson in resilience, humility, and above all, human connection. Thank you all for being a part of it. This thesis is dedicated to my mother 1 Advancing environmental DNA approaches for optimizing aquatic ecosystem monitoring and ecological assessment 8 stressors that can be lethal or sub-lethal to fish. Industrial effluents, agricultural runoff laden with fertilizers and pesticides, sewage, and plastics all contribute to the pollution burden in waterways. In many regions, basic wastewater treatment is lacking more than 80% of global wastewater is discharged untreated into rivers or oceans (UNESCO, 2017). most marine life, and over 400 such hypoxic zones have been reported worldwide (Diaz & Rosenberg, 2008). Unsustainable fishing remains a critical threat to both marine and freshwater fish species. Advances in fishing technology and effort have led to the depletion of many target species and considerable bycatch (the unintentional capture of non-target species, including juveniles and endangered species). Currently, 37.7% of global fish stocks are exploited beyond biologically sustainable levels (FAO, 2024). Many commercially significant species, such as tuna and cod, have suffered dramatic population declines, disrupting marine ecosystems and global fisheries. In inland waters, overharvesting fish (for food, aquarium trade, or bait) has driven some species to rarity or extinction, e targeted species; it can alter community structure and ecosystem function. The removal of large predatory fish can cause mesopredator release (smaller fish and invertebrates increase, potentially overgrazing habitat), while the loss of herbivorous fish on coral reefs contributes to algal overgrowth and reef decline (McCauley et al., 2010). The introduction of non-native species into aquatic ecosystems can disrupt native fish populations through predation, competition, or disease. Invasive predators or competitors may outcompete native fish for food or habitat, often because the natives have not evolved defenses against them. Nearly 33% of freshwater fish extinctions in the past century have been attributed to invasive species (IUCN, 2023). Among these threats, climate change poses a pervasive and growing threat to fish biodiversity across the globe (Pigot et al., 2023). Warming water temperatures, shifting precipitation patterns, and more frequent extreme events (droughts, floods, storms) are already impacting aquatic ecosystems profoundly. Many fish are sensitive to temperature, relying on specific thermal ranges for optimal growth and reproduction. As waters warm, species are being pushed out of their historical ranges studies have documented GENERAL INTRODUCTION 9 poleward and depth range shifts for numerous marine fish at an average rate of tens of kilometers per decade as they track cooler habitats (Pinsky et al., 2013). Some species benefit from warming and expand, while others decline or are forced into shrinking refugia. Additionally, 17% of threatened freshwater fish species are directly affected by climate change, experiencing habitat loss due to decreasing water levels, rising sea levels pushing seawater into rivers, and shifting seasonal patterns (IUCN, 2023). Faced with this confluence of pressures, fish populations serve as sentinels of ecosystem change and their monitoring is crucial for safeguarding aquatic ecosystem. 2. The importance of fish biodiversity monitoring in aquatic ecosystems Given the widespread threats to aquatic ecosystems, monitoring fish biodiversity is critically important for understanding ecosystem health, detecting emerging problems, and guiding conservation efforts (Brodersen & Seehausen, 2014). Fish are often one of the first groups to respond to environmental change declines in sensitive fish species or shifts in community composition can serve as an early indicator of ecological disturbances, including declining water quality, habitat degradation, and climate-driven shifts (Okwuosa et al., 2019). Monitoring in this context means systematically surveying fish species presence, abundance, and demographics in each habitat over time. Such data allows us to establish baselines, detect deviations, and assess the outcomes of management interventions. 2.1 Current traditional fish monitoring methods Humans have long monitored and managed fish populations using a variety of traditional survey methods, each developed to observe or sample fish in different habitats. These conventional techniques have provided invaluable data for fisheries management and ecological research (Fig 2). These approaches encompass various techniques, each with distinct advantages and limitations. Visual surveys, such as snorkeling and diving, allow direct observation of fish species, abundance, and behavior but are often limited by water clarity and species identification challenges (Thurow et al., 2012). A variety of nets are employed to capture fish for monitoring, including gill nets, seine nets, and trawl nets, to capture fish for population studies. Gill nets are set stationary in the water; fish that attempt to swim through become entangled by their gills. Seine nets are large mesh Advancing environmental DNA approaches for optimizing aquatic ecosystem monitoring and ecological assessment 10 curtains that investigators drag through shallow water or enclose an area to herd fish into the net. Trawl nets are towed behind boats (e.g., bottom trawls along the seafloor, or midwater trawls) to sample fish over larger areas in open water or benthic habitats. Each netting technique, however, has biases for instance, gill nets might miss very small or very large fish, and trawls may not work well in structurally complex habitats (reefs, weed beds) where nets would snag. Importantly, netting is invasive and can be non-selective: it often captures non-target species (bycatch) and can injure or kill the fish caught (Balasch & Tort, 2019). In freshwater systems, electrofishing is a standard method for surveying fish, especially in streams and rivers. It temporarily immobilizes fish for study but must be carefully executed to minimize stress and account for species-specific variability in effectiveness. Various trapping techniques (like fyke nets, minnow traps, or crab pots) and line fishing (rod and reel surveys) are also traditional ways to sample fish. Although not a survey method per se for community assessment, mark-recapture techniques are a traditional approach to estimate population size and track fish movements (Thorsteinsson, 2002). Figure 2. Traditional fish monitoring techniques across aquatic environments. The illustration depicts various conventional sampling methods: electrofishing and cast netting in freshwater ecosystems, and bottom trawling, purse seining, and diver-based observations in marine environments. GENERAL INTRODUCTION 11 These conventional methods have collectively built the foundation of fisheries science and aquatic ecology. They have allowed scientists to catalog species, monitor trends, and manage fisheries for decades. For example, conducting extensive netting surveys across many sites requires significant manpower and can only cover limited spatial areas at a time (Schramm Jr et al., 2002). Many methods also demand taxonomic expertise to identify species morphologically, which can be difficult for larval or cryptic species. Some habitats (deep waters, large rivers at flood stage, polar seas under ice) are logistically hard or dangerous to sample with traditional means, leaving gaps in monitoring coverage. Additionally, as noted, methods like trawling or electrofishing can disturb habitats and stress non-target fish group (Fiona, 2014; Muntadas et al., 2014). While conventional monitoring remains essential and irreplaceable in many contexts (and provides the baseline to which new methods are compared), integrating more efficient and less intrusive techniques can improve our ability to monitor fish biodiversity on larger scales and with lower impact. One of the most groundbreaking innovations in this field is the use of environmental DNA (eDNA), which has opened new frontiers for aquatic monitoring by detecting species through genetic traces in the environment rather than direct observation or capture (Díaz-Ferguson & Moyer, 2014). 2.2 Environmental DNA (eDNA) analysis: a revolutionary approach for fish monitoring and ecological assessment eDNA analysis has rapidly emerged as a transformative approach for monitoring fish and other aquatic organisms (Rodríguez-Ezpeleta et al., 2021). Environmental DNA refers to genetic material that organisms shed into their surroundings for instance, in the form of skin cells, scales, mucus, feces, urine, eggs/sperm, or decaying tissue. In an aquatic context, this DNA is suspended in water (or bound to sediments) and can persist for days to weeks before degrading. By collecting environmental samples (water, sediments, air) and extracting DNA, we can detect species by identifying their unique genetic markers, all without needing to capture or even see the organisms (Deiner et al., 2021). This approach provides a non-invasive, highly sensitive, and cost-effective alternative to traditional fish monitoring techniques. eDNA methodologies generally fall into two broad categories depending on the monitoring goals: targeted detection and community-wide metabarcoding (Figure 3). Advancing environmental DNA approaches for optimizing aquatic ecosystem monitoring and ecological assessment 12 Figure 1. Schematic overview of eDNA analysis for monitoring aquatic biodiversity: This figure illustrates how a single drop of water containing DNA from biological materials (e.g., skin, scales, tissue, microbial cells, and metabolic waste) is analyzed. The extracted eDNA is processed using qPCR or metabarcoding to identify species through genetic markers: 12S rDNA (MiFish) for vertebrates, COI (Leray/Folmer) for invertebrates, and 18S and 16S rDNA for microbial communities. Adapted from Chavez et al. (2021). Targeted eDNA detection uses quantitative PCR (qPCR) or digital PCR (dPCR) to test for a specific DNA sequence unique to a taxon of interest. Whereas eDNA metabarcoding allows to assess community composition through the simultaneous amplification of DNA from multiple species (Chavez et al., 2021). The advantages of eDNA sampling extend beyond non-invasiveness; its high sensitivity allows for the detection of species at very low population densities, making it particularly useful for identifying elusive, migratory, or cryptic species that might not be captured by traditional methods (Furlan et al., 2019; Hinlo et al., 2017). Additionally, eDNA-based monitoring is highly scalable and efficient, requiring significantly less field effort and cost compared to traditional survey methods while enabling rapid biodiversity assessments across large spatial and temporal scales (Bálint et al., 2018). It also facilitates early detection of invasive species, allowing for proactive management before these species become established and cause ecological or economic damage and long-term tracking, informing conservation policies and ecosystem management (Deiner et al., 2017; Tsuji et al., 2024). As sequencing technologies advance, eDNA-based approaches are increasingly being integrated into global biodiversity monitoring programs, complementing and, in some cases, replacing traditional fish monitoring methods (Suominen et al., 2024). Its ability to provide precise, rapid, and cost-effective ecological insights makes eDNA an indispensable approach for fisheries management, conservation, and ecosystem sustainability. GENERAL INTRODUCTION 13 3. Rationale of the study Effective biodiversity monitoring is foundational for fisheries management and conservation planning. However, traditional fish survey methods while valuable are often limited by logistical constraints, species-specific biases, and low sensitivity, particularly for rare or cryptic taxa. Environmental DNA (eDNA) analysis has emerged as a transformative approach that can overcome many of these challenges by detecting species from genetic material in water samples. Yet, despite its promise, eDNA remains underutilized and unevenly validated across ecological contexts and geographical regions. This thesis addresses critical questions about the feasibility, reliability, and broader applicability of eDNA-based monitoring. Through global synthesis and targeted empirical studies, it explores how eDNA performs under real-world conditions, how it compares to conventional methods, and how it can be integrated into ecosystem assessments and fisheries frameworks. The work spans species-specific detection, community-level analysis, and ecological status evaluation providing a multidimensional perspective 4. Hypothesis, aim and objective 4.1 Working hypothesis eDNA analysis is a sensitive, non-invasive approach that, when methodologically optimized, assess fish biodiversity across riverine and estuarine systems, capturing both species-specific signals and community-level variation beyond the reach of conventional surveys. 4.2 Overarching aim and objectives To evaluate and advance the application of eDNA analysis as a practical and scientifically rigorous approach for monitoring fish biodiversity and assessing ecological condition, with a focus on methodological performance, ecosystem-level insights, and regional applicability. To achieve the overall aim, the study defines the following specific objectives: Synthesize the current state and advancements in eDNA applications for biodiversity monitoring, with a focus on methodological developments in temperate ecosystems Advancing environmental DNA approaches for optimizing aquatic ecosystem monitoring and ecological assessment 14 and their implications for application in tropical fisheries, (Objective 1), which is addressed in chapter 1. Evaluate the efficacy, scalability, and practical applications of eDNA based monitoring with different context, identifying methodological strengths, limitations, and its application (Objective 2), which is addressed throughout chapters 2 and 3. To assess detection reliability and potential methodological biases in eDNA-based monitoring by comparing molecular data with conventional survey techniques (Objective 3), which is addressed throughout chapters 2 and 3. To explore the integration of eDNA-derived community data into ecological assessment frameworks and fisheries management strategies, demonstrating its application in ecological indices (Objective 4), which is addressed in chapter 3. Together, these objectives provide multi-level investigation from global context to local application of how eDNA can be strategically employed to improve the monitoring and management of fish biodiversity in both data-rich and data-deficient environments. 5. Structure of the Thesis This dissertation is structured into three main chapters, with each chapter addressing aspects of multiple research objectives outlined above. Each chapter is written in the format of an independent scientific study (with its own introduction, methods, results, and discussion) to allow in-depth focus on the specific research question, though some methodological details may overlap between chapters. Following the three core chapters, a general discussion will synthesize the findings in the context of the overarching themes of the thesis. The thesis is structured as follows: Chapter 1: Exploring uncharted territory: new frontiers in environmental DNA for tropical fisheries management Chapter 2: Lessons learned from applying eDNA surveying to diadromous fish detection across the north-east Atlantic region Chapter 3: Advancing ecological assessment: The integration of eDNA metabarcoding into an estuarine fish index GENERAL INTRODUCTION 15 CHAPTER 1 16 This manuscript was published as: Bhendarkar, M., Rodriguez-Ezpeleta, N. Exploring uncharted territory: new frontiers in environmental DNA for tropical fisheries management. Environ Monit Assess 196, 617 (2024). https://doi.org/10.1007/s10661-024-12788-8 Exploring uncharted territory: new frontiers in environmental DNA for tropical fisheries management 17 Abstract Tropical ecosystems host a significant share of global fish diversity contributing substantially to the global fisheries sector. Yet their sustainable management is challenging due to their complexity, diverse life history traits of tropical fishes, and varied fishing techniques involved. Traditional monitoring techniques are often costly, labourintensive, and/or difficult to apply in inaccessible sites. These limitations call for the adoption of innovative, sensitive, and cost-effective monitoring solutions, especially in a scenario of climate change. Environmental DNA (eDNA) emerges as a potential game changer for biodiversity monitoring and conservation, especially in aquatic ecosystems. However, its utility in tropical settings remains underexplored, primarily due to a series of challenges, including the need for a comprehensive barcode reference library, an understanding of eDNA behaviour in tropical aquatic environments, standardized procedures, and supportive biomonitoring policies. Despite these challenges, the potential of eDNA for sensitive species detection across varied habitats is evident, and its global use is accelerating in biodiversity conservation efforts. This review takes an in-depth look at the current state and prospects of eDNA-based monitoring in tropical fisheries management research. Additionally, a SWOT analysis is used to underscore the opportunities and threats, with the aim of bridging the knowledge gaps and guiding the more extensive and effective use of eDNA-based monitoring in tropical fisheries management. Although the discussion applies worldwide, some specific experiences and insights from Indian tropical fisheries are shared to illustrate the practical application and challenges of employing eDNA in a tropical context. CHAPTER 1 24 (ICAR-NBFGR, 2016), and this number is continuously bolstered by reports of new of biodiversity (Chandra et al beyond finfish, encompassing a wide array of 2934 crustaceans, 5070 molluscs, 765 echinoderms, 486 sponges, and 844 seaweeds (Jena & Gopalakrishnan, 2012). Despite this rich aquatic biodiversity, India is grappling with severe threats to biodiversity loss. These threats range from habitat destruction, invasive alien species, overexploitation, climate change, and pollution, all of which are interconnected and caused directly or indirectly by human actions (UNEP, 2008). So far, 120 freshwater fish species (Lakra et al., 2010) and 36 marine fish species (IUCN, 2021) from Indian waters have been listed as threatened. Recent studies (Raj et al., 2021; Verma & Trivedi, 2016) habitats. This highlights the urgent need to find alternative approaches to boost fish biodiversity conservation and management. The application of fish eDNA analysis has been demonstrated as an effective approach for aquatic biodiversity monitoring and surveillance around the world, particularly in the face of changing environments (Biggs et al., 2015; Deiner et al., 2015; et al., 2020; Minamoto et al., 2012; Sigsgaard et al., 2015; Thomsen et al., 2012a, 2012b; Tréguier et al., 2014). Studies have used eDNA to detect specific species of fish (Ardura, 2019; Brys et al., 2021) and crustaceans (King et al., 2022) to detect whole communities (Bessey et al., 2020; Li et al., 2022; Zainal Abidin et al., 2022), with different habitat such as rivers (Cantera et al., 2019; Goutte et al., 2020), reservoirs (Li et al., 2022), lakes (Fujii et al., 2019), estuaries (Ruan et al., 2022; Zou et al., 2020), deep sea (Kawato et al., 2021), marine protected areas (Gold et al., 2021; Marwayana et al., 2022; Pascher et al., 2022), and coral reef (West et al., 2020). Most of these studies concluded that eDNA approaches outperformed standard capture-based biomonitoring fish surveys. Furthermore, certain fish species were not observed using the fish capture approach, although eDNA-based approaches detected them (Aglieri et al., 2021; Yao et al., 2022). The increased species detection sensitivity of eDNA compared to traditional methods results in variations in species abundance or distribution, particularly concerning rare species, which are often of concern for being endangered or non-native potentially leading to uncertainties in conservation and resource management decisions (Jerde et al., Exploring uncharted territory: new frontiers in environmental DNA for tropical fisheries management 25 2011). The absence of specific fish species in monitoring efforts can lead to misguided management decisions based on inadequate data, which can negatively impact the conservation of those species and the ecosystems they inhabit (De Silva & Medellín, 2001; Mora et al., 2009). The detection of species through eDNA analysis, not captured by traditional methods, may indicate hidden biodiversity, highlighting the importance of integrating complementary techniques for holistic monitoring and future management strategies. 3.2 Fish migration patterns Fish migration is commonly observed in many species, where fish migrate from one place or water body to another. This movement can occur daily to an annual basis, or even once in a lifetime, and transverse distances range from a few meters to thousands of kilometres, from horizontal to vertical (Dingle & Drake, 2007; Myers, 1949). The cause for movement is mainly related to feeding or reproducing; in certain circumstances, the reason for migration remains unknown (Brönmark et al., 2014; Ordeix & Casals, 2024). Therefore, gaining insight into the migratory ecology of fish species and understanding how, when, and why they migrate are crucial (Lennox et al., 2019). In India, a significant portion of indigenous fish species, especially smaller ones, move locally regularly to meet their fundamental biological needs. Apart from a few exceptions, the majority of Indian migratory fishes are potamodromous (Bhendarkar et al., 2020; Das & Hassan, 2008). From the review of existing literature, we found that there is a dearth of information accessible on migration behaviour patterns of Indian fishes, with the exception of a few observations on the spawning migrations of the Indian shad Tenualosa ilisha (Bhaumik, 2015; Sarkar et al., 2021) and Indian mottled eel Anguilla bengalensis (Abdul Kadir et al., 2017; Arai & Abdul Kadir, 2017). Regrettably, diadromous fishes worldwide are under threat due to human activities such as habitat destruction, overfishing, and climate change (Tamario et al., 2019). As such, it is critical to monitor their spawning migrations non-invasively to understand their behaviour and assess population health. In temperate regions, researchers address this need by employing eDNA analysis to investigate the migration barriers of critically endangered European eels (Halvorsen et al., 2020), the reproductive migration of threatened endemic fish, and the spawning migrations of Danube bleak and vimba bream (Maruyama et al., 2018; Thalinger et al., 2019; Yatsuyanagi et al., 2020). Recent studies have demonstrated the efficacy of eDNA CHAPTER 1 26 in probing and understanding the ecological habitats of complex and hard-to-reach ecosystems, such as the mesopelagic and deep-sea environments (Allan et al., 2021; Canals et al., 2021), where traditional methods such as deep-sea trawler have limits in information about deep-sea ecology. Drawing from the successful applications of eDNA analysis in temperate regions, its potential application in tropical areas is evident. In tropical regions, understanding the migratory patterns of indigenous fish species, particularly species like the Indian shad and Indian mottled eel within large riverine networks, is paramount for effective conservation efforts. Employing eDNA analysis offers a non-invasive approach to monitoring spawning migrations and movement patterns, effectively filling the ecological information gap highlighted earlier. 3.3 Reproductive status Comprehensive assessment of fish stocks usually requires information on reproductive parameters, as understanding the reproductive capability of individual fishes within the spawning population impacts recruitment (Bhendarkar et al., 2013; Witthames ascertain the spatial and temporal distribution of spawning events (Grant et al., 2009; Harrison et al., 1984; Rose, 1993) to determine population establishment for both invasive and translocated native species and design and evaluate management actions (Kearse et al., 2012; King et al is crucial for the conservation and management of species and/or populations (Bylemans et al., 2017). However, there is a significant gap in understanding the influence of fishing on the reproductive potential of commercially important species in Indian waters (Gopalakrishna Pillai & Satheeshkumar, 2012; Sathianandan et al., 2021). This understanding is essential for making informed management decisions and ensuring resource sustainability. The use of regular and rapid monitoring techniques is necessary to avoid delays in estimating these parameters and improve stock management capabilities (Hoggarth, 2006). However, typical capture surveys are labour-intensive, time-consuming, and vulnerable to monitoring biases such as observer bias, geographical restrictions, and false spawning miscounts (Bylemans et al., 2017; Caswell et al., 2004; Diana et al., 2015; Ko et al., 2013; Koster et al., 2013; Miller et al., 2012). Additionally, these procedures can increase mortality among the spawning stock and eggs, particularly for rare and Exploring uncharted territory: new frontiers in environmental DNA for tropical fisheries management 27 endangered species, risking the survival of populations (Engstedt et al., 2014; Tsukamoto, 2006; Wei et al., 2009). Consequently, non-invasive monitoring techniques like eDNA sampling can provide crucial information without disrupting the spawning process or endangering the survival of species or populations. Several recent studies in temperate waters have demonstrated the utility of eDNA analysis in monitoring spawning events for various species, including endangered Macquarie perch (Bylemans et al., 2017), European perch and whitefish (Vautier et al., 2022), sockeye salmon (Tillotson et al., 2018), the timing of breeding season of Chinese sturgeon (Yu et al., 2021), and Danube bleak and vimba bream (Thalinger et al., 2019). In tropical regions, where fishes often exhibit diverse reproductive strategies and breeding habitats are not well understood (Winemiller et al., 2008), eDNA analysis could offer a valuable tool for monitoring spawning events. The observed increases in eDNA concentration-comparable to patterns found in temperate studies-are often interpreted as indicators of reproductive activity, including spawning aggregations, active spawning, or the presence of ichthyoplankton. However, the diversity of reproductive strategies among tropical fish can complicate these interpretations. Additionally, environmental factors such as temperature and water flow (Lema et al., 2024) add further complexity to eDNA transport and fate, introducing potential biases and uncertainties in its detection and quantification (Barnes & Turner, 2016; Kirtane et al., 2023). 3.4 Systematic detection of at-risk, rare, or cryptic species The cultural and historical significance of biodiversity conservation in India has been emphasized for a long time, with literature, religious writings, and Vedic scriptures promoting nature conservation (Dhee et al., 2019). However, as recently highlighted at a Dialogue Earth forum, India is one of the countries most threatened by biodiversity loss (Nikhil, 2020). Current traditional monitoring methods reliant on invasive sampling face limitations due to the conservation status of these species and challenge implementation across all habitats. In this context, the application of eDNA not only overcomes the limitations of previous approaches but also minimizes the risk to the species being monitored. In recent years, multiple eDNA-based studies in temperate areas have successfully monitored endangered fish (Akamatsu et al., 2020; Boyer et al., 2013; Sigsgaard et al., 2015; Thomsen et al., 2012a, 2012b) and improving the detection and quantification of rare fish species in remote locations (Balasingham et al., 2018; Bergman CHAPTER 1 28 et al., 2016; Castañeda et al., 2020; Wilcox et al., 2013) using species-specific primers and a probe. 3.5 Early-warning system of invasive and alien species The introduction of non-native species into freshwater habitats has had a significant impact on the distribution and the existence of numerous native fish species (Gupta & Everard, 2019; Knight, 2010). These impacts can be seen at various levels including genetic, individual, population, community, and ecological changes (Cucherousset & Olden, 2011; Marr et al., 2013; Smart et al., 2006). The issue of the invasion of foreign species, either intentionally or accidentally, is subject to intense debate. Reasons for introducing these species range from expanding species diversity in aquaculture, stocking in lakes and reservoirs, enriching of sport fishery base, to augmentation of the variety in the aquarium industry. Nevertheless, these introductions pose serious threats to the conservation of native Indian species (Dahanukar et al., 2011; Raj et al., 2020, 2021), where more than 500 species (13.6%) of non-native species have been identified (Joshi et al., 2021). The early detection of these species in freshwater habitats is critical to preventing their establishment and mitigating their detrimental effects on indigenous species. Despite the existence of guidelines for the import or introduction of aquatic organisms in India (Ponniah & Sood, 2002), monitoring such expansive aquatic resources remains challenging. However, invasive species are usually not detected until they have already become widespread. Nevertheless, local fishermen (from primary fisheries cooperative societies) play a crucial role in reporting invasive species sightings in their nets. In this context, the use of eDNA to monitor the presence of non-native species acts as an alarming system. In temperate waters, Thomas et al. (2020) used a portable eDNA device to detect invasive species in a few hours, even in habitats where traditional approaches to detection are difficult and labour-intensive. For instance, eDNA identification has been used to detect alien crayfish and their activity patterns in largescale screening of lotic systems (Chucholl et al., 2021). Early detection of invasive species is essential to prevent their establishment and mitigate their negative impact. The eDNA approach plays a significant role in this process by allowing for efficient monitoring of the distribution and population dynamics of invasive species, which can Exploring uncharted territory: new frontiers in environmental DNA for tropical fisheries management 29 inform decision-making to protect native species and ecosystems (Amberg, 2019; Ardura, 2019; Nardi et al., 2019; Trebitz et al., 2017; Xia et al., 2018). 3.6 Interplay of diets and tropic interaction Ecosystem functioning significantly relies on trophic webs, which reveal the biotic relationships between the living creatures in the environment. Traditional methods of trophic web analyses rely on food and feeding studies based on stomach analyses, still widely used today (Bhendarkar et al., 2014). However, this method can be timeconsuming and challenging, especially for identifying digested food items from rare, small, or cryptic organisms (Berry et al., 2017; Boyer et al., 2013). Moreover, techniques such as radioisotopes, stable isotope analysis, direct species observations, and fatty acid analysis have also been used to a lesser extent (Mondal & Bhat, 2021; Neufeld et al., 2007). More recently, DNA extracted from gut, stomach, or faecal contents, known as gut eDNA, has facilitated its widespread adoption across diverse ecosystems (Huyghe et al., 2023; Jo et al., 2016). It also aids in revealing novel trophic interactions and enhancing taxonomy. Studies have shown that eDNA metabarcoding of food items offers valuable insight into the feeding behaviour of species like green sea turtles (Díaz-Abad et al., 2022) and catfishes (Guillerault et al., 2017). When compared with traditional methods, it has been noted that eDNA can detect a broader range of food items, making et al., 2017; Yoon et al., 2017). 3.7 Population genetics and eDNA The application of eDNA in population genetics is still in its early phases (Adams et al., 2019; Wang et al., 2021). However, this emerging area of eDNA, on the other hand, has the potential to enhance our comprehension of past distributions (Pawlowski et al., 2021), present status (Dussex et al., 2016; Thomsen & Willerslev, 2015), and behavioural, ecological, and evolutionary processes (Adams et al., 2019) and inform conservation efforts. Population genetics studies require the collection of tissue samples from study organisms, which can be logistically difficult, resource-intensive, and potentially detrimental to both the organisms and their environments. Recent studies in Indian population genetic research have predominantly employed genetic methods for stock identification, focusing on commercially important fish species along the Indian CHAPTER 1 30 coast (SriHari et al., 2022). These studies have unveiled genetic differentiation between environmental barriers influencing migration patterns and larval dispersal (CMFRI, 2023). In this context, eDNA analysis emerges as a promising option, either complementing or in some cases replacing it as a non-invasive, cost-effective alternative to traditional population genetics approaches. Moreover, in biodiverse regions like India, where biodiversity loss is a pressing concern, eDNA analysis can serve as a valuable tool for monitoring changes in population size, assessing genetic diversity, and guiding conservation strategies. eDNA analysis presents an attractive alternative to the traditional approach of population genetics research, as it offers a non-invasive and cost-effective way to study genetic variation within and between populations of different species. For instance, Sigsgaard et al. (2017) used eDNA extracted from seawater to estimate the population size and haplotype variation of whale sharks, while other studies have used similar techniques to investigate various species in different regions and assign them to known haplotypes (Berry et al., 2017; Parsons et al., 2018). Some studies have started to explore the use of eDNA as a means of estimating population size (Rourke et al., 2022; Spear et al., 2021). However, a major restriction of this approach is the uncertainty of how many individuals contribute to the detected eDNA, making it difficult to confidently compare results with those obtained by genotyping known individuals. Furthermore, while metabarcoding has the potential to reveal fine-scale diversity patterns, its effectiveness is limited by the lack of comprehensive reference databases for tropical species, a limitation highlighted next in the section on barcode reference libraries. 3.8 Natural samplers DNA (nsDNA) In the context of environmental DNA studies, natural samplers would be an emerging complementary approach to biodiversity monitoring and assessment. These natural samplers could be for example sponges (Mariani et al., 2019) or gut contents of invertebrates (Calvignac-Spencer et al. 2013; Carvalho et al., 2022; Rodríguez-Castro et al., 2023), which act as filters retaining eDNA from the environment, which can then be extracted for community analyses. Recent studies in the tropics have explored the use of natural samplers eDNA; for example, Turon et al. (2020) extracted DNA from sponges to assess the marine fish diversity in Nha Trang Bay (Vietnam), whereas Meekan et al. (2017) conducted a study in Baa Atoll, Maldives, focusing on the population structure of Exploring uncharted territory: new frontiers in environmental DNA for tropical fisheries management 31 whale sharks by isolating and sequencing whale shark DNA from a copepod, Pandarus rhincodonicus and natural samplers can enhance the understanding of fish populations and ecosystems, thereby providing valuable insights for biodiversity monitoring and conservation efforts. 3.9 Additional applications of eDNA in the fisheries sector The adoption of eDNA in aquatic research is rapidly expanding. The eDNA analysis approach has shown potential in various sectors, such as aquaculture, disease surveillance, seafood industries, and the detection of organic carbon in the ocean. Globally, diseases are major constraint and pose significant challenges to the aquaculture sector, including in India (Bagum et al., 2013; Bohara et al., 2024; Sahoo et al., 2013; Stentiford et al., 2020). For instance, shrimp culture in India suffered a staggering total loss worth US$ 1.02 billion, with an annual loss of 0.21 Mt of shrimp attributed to diseases (Patil et al., 2021). Numerous studies have showcased the potential of eDNA for the identification and quantification of potential pathogens in aquaculture sites, which is crucial for disease risk assessment (Díaz-Ferguson & Moyer, 2014; Dully et al., 2021; Huver et al., 2015; Peters et al., 2018; Schuster et al., 2023; Shea et al., 2020; Taengphu et al., 2022; Trujillo-González et al., 2019). In 2022, the World Organisation for Animal outlined its benefits and limitations (Bohara et al., 2024). The integration of eDNA methodologies offers promise for revolutionizing disease surveillance and enhancing animal health monitoring systems in aquaculture, especially in India where diseases pose significant challenges. However, further research and consideration of both benefits and limitations are essential to fully harness the potential of eDNA in disease-related challenges. Furthermore, eDNA has been used to identify the source of organic carbon in et al., 2021; Geraldi et al., 2019; Reef et al., 2017). All coastal wetlands, including mangroves, marshes, and seagrass, are considered blue carbon ecosystems (Adame et al., 2024). Among these, tropical coastal wetlands are particularly productive (Woodroffe, 2019) and serve as potential sources of blue carbon (Adame et al., 2019, 2024). However, identifying organic matter sources in these ecosystems is complex due to variable isotopic values among plant species, tissues, and microhabitats (Blair & Aller, 2012; Marchand et al., 2003). Distinguishing CHAPTER 1 32 (Saintilan et al., 2013). Complementary methods, like eDNA and compound-specific isotopes, can reduce uncertainty in identifying sources (Reef et al., 2017), enhancing our understanding of carbon fluxes in marine systems. In addition, eDNA analysis has been used to test the feasibility of a wide range of fish species diversity in seafood. By detecting and identifying the DNA of fish species in seafood products, eDNA analysis can help improve food safety and traceability, prevent fraud, and provide information on the sustainability of fisheries (Lee et al., 2021; Richards et al., 2022). By integrating complementary methods and advancing scientific understanding, eDNA analysis can contribute significantly to enhancing the sustainability and resilience of the fisheries sector in tropical regions. 4. Challenges and limitations of eDNA While eDNA analysis holds promising prospects for advancing the understanding of aquatic ecosystems, it is important to note its associated challenges. This is particularly evident in the context of India, where certain specific hurdles must be overcome for effective implementation. In the context of this review, we bring into focus the principal issues and major challenges that arise up right away and currently limit the utility of eDNA in the Indian scenario. These challenges are outlined below. 4.1 Barcode reference libraries One of the most significant challenges in using eDNA analysis for aquatic biomonitoring is the lack of comprehensive reference databases for numerous taxa (Jerde et al., 2021; Stoeckle et al., 2020; Thomsen & Sigsgaard, 2019). This gap limits the accurate identification of species based on eDNA. Although the ICAR-National Bureau of Fish Genetic Resources (ICAR-NBFGR) has created a database on Indian fish species (Jena & Gopalakrishnan, 2012), there is still a need for comprehensive DNA barcode reference libraries for Indian aquatic fauna to fully harness metabarcoding for aquatic biomonitoring. At present, the cumulative list of fish species found in Indian waters, encompassing freshwater, marine, and brackish environments, is recorded at 2617 species (Froese & Pauly, 2023). The data we have for the COI, 12S, 16S, and cytb gene records show 67,576; 11,823; 9745; and 33,772 sequences, respectively. While some genes like COI have relatively high species coverage (73%), others like 16S, 12S, and cytb, with Exploring uncharted territory: new frontiers in environmental DNA for tropical fisheries management 33 coverage ranging from 49 to 55%, demonstrate substantial room for improvement. This uneven distribution of gene records may lead to biases in species detection and quantification, making a holistic understanding of biodiversity challenging (Figure 3). These findings underscore the pressing need to expand the reference sequence library with a balanced inclusion of all four genes for a more nuanced and accurate community composition assessment. Figure 3. Gap analysis of reference database for fish species found in Indian waters obtained as in Claver et al. (2023). Each bar indicates the percentage of species for which at least one sequence for each gene sequence is available, with the total number of species with available sequences and the number of sequences shown above the bar in black or in colour Despite ongoing efforts to expand the coverage of the references database, more rigorous efforts are needed to exploit eDNA analysis as a truly effective tool for the assessment of biodiversity and the conservation of Indian water bodies. Several countries, such as Austria (ABOL), Finland (FinBOL), Norway (NorBOL), Germany (GBOL), and Australia (NBDL-https://research.csiro.au/dnalibrary/), have established their own Lessons learned from applying eDNA surveying to diadromous fish detection across the north-east Atlantic region 40 41 This manuscript was preprint as: Bhendarkar, M., Claver, C., Mendibil, I., Fraija-Fernández, N., Nachón, D. J., A., Ardaiz, J., Diaz, E., Lambert, P., Lassalle, G., & Rodriguez-Ezpeleta, N. (2025). Lessons learned from applying eDNA surveying to diadromous fish detection across the north-east Atlantic region. bioRxiv (Cold Spring Harbor Laboratory). https://doi.org/10.1101/2025.01.31.635873 CHAPTER 2 Lessons learned from applying eDNA surveying to diadromous fish detection across the north-east Atlantic region 42 Abstract Regular monitoring of diadromous fishes is critical to inform their management and conservation. Yet, the in-situ data collection these species is challenging due to their complex life cycle and low abundance. Focusing on the sea lamprey (Petromyzon marinus, Petromyzontidae) and the European shads (Alosa alosa and A. fallax, Clupeidae), emblematic diadromous fishes in the Northeast Atlantic region, this study leverages the use of water environmental DNA (eDNA) samples to monitor their distribution range. For that aim, we developed quantitative PCR (qPCR) and digital PCR (dPCR) assays and applied them to detect sea lamprey and European shad DNA in a network of 44 river basins across Spain, France, Ireland, and the UK. We found that qPCR efficiently detected presence/absence of shads, while the higher sensitivity of dPCR was essential for detecting the lower abundant and partly sessile behaving sea lamprey in the amount of water collected. Moreover, sea lamprey showed significantly lower eDNA copies per litre of water compared to shads, probably due to their larvae spending several years burrowed within soft sediments, reducing eDNA shedding into the water column. The integration of historical datasets with this snapshot wide-ranging study enhances our understanding of the distribution of sea lamprey and European shad in Atlantic rivers. Importantly, the lessons learned within this international collaboration are critical towards a prevailing framework for conservation of migratory fishes, highlighting the need of well-designed sampling strategies coupled with species-specific assays applied to eDNA samples to bust long-term monitoring efforts of diadromous species. CHAPTER 2 43 1. Introduction Anthropogenic activities, together with climate change, can significantly modify natural habitats and ecosystems (Chu et al., 2005; Dodds et al., 2013). This is particularly critical for diadromous species, whose complex life cycles, involving a variety of habitats between rivers and open ocean, make them more vulnerable to any alterations (ChaparroPedraza & de Roos, 2019; Limburg & Waldman, 2009; Tamario et al., 2019). Diadromous fishes are emblematic species with crucial ecological roles, providing numerous ecosystem services (Almeida et al., 2023; Ashley et al., 2023; Naiman et al., 2002). Thay can either be catadromous (migrating to sea to spawn) or anadromous (migrating to rivers to spawn). The sea lamprey (Petromyzon marinus Linnaeus, 1758) and European shads (Alosa alosa Linnaeus, 1758 and A. fallax Lacépède, 1803) are ecologically, evolutionarily, and economically important anadromous species, which are present along the eastern Atlantic coast (Almeida P R & Rochard, 2015; Wilson & Veneranta, 2019). Their distributions and abundances have decreased over time due to the synergistic effect of anthropogenic impacts, including climate change, so that their core distributions are now restricted to southwestern Europe mostly (Almeida et al., 2021; Lassalle et al., 2008; Nachón et al., 2020). Despite being categorized by the International European level (Freyhof, 2010a; Freyhof, 2010b; Freyhof & Kottelat, 2008a, 2008b; NatureServe, 2013), these species European countries (Almeida P R & Rochard, 2015; Limburg & Waldman, 2009; OSPAR Commission, 2009a, 2009b). For instance, in France and Great Britain, A. alosa is listed P. marinus is et al., 2011; Nunn et al., 2023; UICN Comité français, 2019). This high level of conservation concern at national levels and across boundary distribution of the species calls for concerted interbasin conservation and management efforts (Guo et al., 2016; ICES, 2003; Kritzer et al., 2022; Ouellet et al., 2022). In this context of generalized decline, obtaining accurate information about diadromous species occurrence is essential to identify key periods and habitats when and where feeding, breeding and migration occur. Continual change, especially alterations in Lessons learned from applying eDNA surveying to diadromous fish detection across the north-east Atlantic region 44 species home river ranges due to various pressures, emphasizes the importance of understanding their movements and habitats (Beaulaton et al., 2008; ICES, 2003). Yet, characterizing the distribution of fish spatially and temporally is a challenging task, especially when considering factors like the scale of distribution, the complex life history of diadromous species, and resource constraints (Ciannelli et al., 2008). Conventional methods, such as mark recapture and electrofishing have been routinely used, but have their own challenges, including difficulties in deployment in all habitats (Lapointe et al., 2006; Pont et al., 2021). Moreover, these methods are not only intrusive but can also be costly and labour-intense (Lapointe et al., 2006; Pont et al., 2021), as well as inefficient in detecting low abundant species (Cantera et al., 2019; Piggott et al., 2021). Therefore, using a cost-effective, scalable and non-invasive sampling method that increases the probability of detection is key for monitoring rare aquatic species with such a temporally restricted while spatially wide distribution as anadromous fishes (Westhoff et al., 2022). The analysis of environmental DNA (eDNA) is a promising and rapidly evolving approach for aquatic species distribution monitoring (Bhendarkar & Rodriguez-Ezpeleta, 2024; Nagarajan et al., 2022; Pawlowski et al., 2021; Rodríguez-Ezpeleta et al., 2021), with potential adaptability in a changing world (Thomsen et al., 2024). Traces of organisms in the form of gametes, faeces, skin cells, saliva, blood, and other bodily substances contain eDNA (Bohmann et al., 2014) that can be utilized to determine the presence of a species within a specific area (Abbott et al., 2021; Davison et al., 2019). This methodology has been instrumental in examining spatio-temporal patterns around spawning habitats in rivers for P. marinus (Bracken et al., 2019; Moser et al., 2021) and Alosa spp. (Antognazza et al., 2021; Antognazza et al., 2019). Moreover, eDNA-based monitoring has made it possible to identify prospective nursery grounds and distribution of sea lamprey larvae (Baltazar-Soares et al., 2022). Conversely, the eDNA-based approach is also used to assess surveillance and control measures for invasive populations of sea lamprey in other parts of the globe where the species is considered as a pest (Gingera et al., 2016; Schloesser, 2018; Tkachuk & Dunn, 2020). In this study, we conducted a broad-scale survey using eDNA to monitor the geographical distribution of sea lamprey and European shads in their known range of the North-East Atlantic region. By using eDNA-based surveys, the goal was to provide a noninvasive, efficient and scalable approach to monitor these species across multiple river CHAPTER 2 45 basins in Spain, France, Ireland and the UK. We aimed to address four objectives: i) to assess the regional distribution of sea lamprey and European shads; ii) to evaluate the efficacy of eDNA analysis as a biomonitoring tool within this context; iii) to compare the variability of eDNA detections between quantitative PCR (qPCR) and digital PCR (dPCR) methods; iv) to determine freshwater migration limits of sea lamprey and shads within river-estuary systems during their upstream migration. The first two objectives were achieved by comparing qPCR-based eDNA detections with evidence-based knowledge of species occurrence across 44 river basins in Spain, France, Ireland and the UK, while the third and fourth objectives were based on dPCR-based eDNA detections from river estuaries within Spain. As methodology continues to evolve, the integration of eDNA-based monitoring is likely to become increasingly essential in the assessment of diadromous species. This work improves our understanding of the practicality and efficiency of eDNA analysis at a river basin scale, providing a robust framework for future research and highlighting the importance of a multi-approach to eDNA analysis interpretation. 2. Material and Methods 2.1 Sampling location and reference data set Water samples were collected from a network of 44 river basins across Spain (20 rivers; 168 samples), France (2 rivers; 9 samples), the UK (15 rivers; 53 samples), and Ireland (7 rivers; 68 samples including 3 at sea close to the river mouth). In the Basque region (Spain), additional water samples were taken from four estuaries: Bidasoa, Oiartzun, Urola and Deba (15 samples) to investigate the abundance and distribution of eDNA along the stretch of river leading to the upstream sites through digital PCR. The sampling occurred over different years (2019 to 2021) in different regions, resulting in a total of 313 samples (Figure 1; Table S1). The selection of sampling sites was based on the known historic distribution of sea lamprey and shads in their native range within these basins coupled with opportunistic sampling (Table S1). Further details on transboundary eDNA sampling and analytical methods can be found in the DIADES Project manual (https://diades.eu/wp-content/uploads/2020/04/WP6_1_Manual_Final_Versioncompress%C3%A9.pdf). Lessons learned from applying eDNA surveying to diadromous fish detection across the north-east Atlantic region 46 Figure 1. Geographical location of river basins sampled for in this study; main stems are represented with a blue line. Each section of the bar charts indicates a sampling point analysed through qPCR. Darker sections indicate sea samples taken near the river mouth (Slaney and Suir rivers) and lighter sections indicate sampling points located in affluents of the main river basin (Oria river). See Table S1 for additional details. CHAPTER 2 47 To place eDNA-based findings in the context of expected presence or absence, a historical evidence reference database for the sea lamprey and shads for each eDNA sampling site was created by combining presence/absence data from electrofishing, traps, and net operations, as well as presence of downstream barriers; evidence has been sourced from the scientific literature or from database repositories (Table S1). For each species, of the presence or absence of the species. 2.2 Water sample collection and DNA extraction The volume of water sample filtered ranged from 1 to 30 litres (Table S2). Spanish VigiDNA® crossflow filtration capsules, respectively. Irish samples filtered through 1.50 filters were utilized (Table S2). All filters were kept frozen until further processing. For DNA extraction, the Qiagen QIAamp DNA kit was used for Spanish and Irish samples, while the French samples were processed using an in-house procedure (Pont et al., 2018), and UK samples were extracted using the DNeasy Power Water Sterivex kit (Qiagen) meticulously performed within a specialized hood to prevent contamination. Each filter was extracted and analyzed individually, ensuring the integrity of the DNA extracts from each separate water samples. The extracted DNA was then transported to AZTI in Spain for further analysis. The concentration of the extracted DNA was quantified using UV spectrometry (Thermo Scientific NanoDrop ND-1000) and QubitTM fluorometer (Life Technologies), and its quality was assessed through agarose gel electrophoresis. 2.3 Species-specific detection assay development To detect both species of European shads inhabiting European waters (A. alosa and A. fallax), we designed genus-specific primers and a probe for Alosa spp. targeting a 94bp fragment of the mitochondrial cytochrome b (cytb) gene. To do so, all Alosa cytb available sequences were retrieved from GenBank (https://www.ncbi.nlm.nih.gov). These sequences were aligned and a suitable region in which to develop the specific assay was identified using the BioEdit software (Kirmani, 2015). To ensure the specificity of Lessons learned from applying eDNA surveying to diadromous fish detection across the north-east Atlantic region 48 the primer and probe sets, an in silico analysis was performed using BLAST (Altschul SF, 1990), and no potential amplification of non-target DNA was detected. For the detection of P. marinus, we utilized the assay developed by Moser et al. (2021). The sequences of the primers and probes used in this study are detailed in Table 1. Table 1. Primer and probe sequences used for specific amplification and detection of European shads Alosa spp. and sea lamprey Petromyzon marinus Primer Name Nucleoide sequence 5´to 3´ Reference Alosa_For ACATTTCAGTTTGATGAAACTTCGG This study (Alosa spp.) Alosa_Rev GAAGTGTAGTGTATAGCCAGGAA Alosa_probe AGGAATGTGTTTAGCGGCAC Pma_For TTGGAGGCTTTGGCAACTG (Gustavson et al., 2015) (Petromyzon marinus) Pma_Rev TGTTTATACGAGGGAAGGCCATA Pma_Probe CTAATACTTGGTGCTCCTG 2.4 Quantitative PCR (qPCR) analysis Quantitative PCR analyses were performed by combining the 5 µl of TaqMan Fast Advanced Master Mix (Applied Biosystems), 0.2µl of each primer (forward and reverse) and probe (10 µM), 2 µl extracted DNA (10 ng) and 2.4 µl Milli-Q water, to adjust the total reaction volume to 10 µl. The procedure was carried out independently to detect the Alosa spp. and P. marinus under the following conditions: for Alosa spp., initial 50°C for 2 min and 95°C for 10 min, followed by 50 cycles alternating between 95°C for 3 s and 60°C for 20 s; and for P. marinus, 50 cycles alternating between 95°C for 3 s and 55°C for 20 s. A total of five PCR replicates were analyzed for each sample, along with positive and negative controls. Genomic DNA (gDNA) extracted from tissue samples of specimens collected in 2019 from the river basins in the Basque Country by EKOLUR Environmental Consulting (Spain) was used as a positive control, with a 10-fold standard dilution series included on each qPCR plate. A sample was considered positive for the species if at least one qPCR replicate yielded a cycle threshold (Ct-value, indicating the number of cycles in qPCR needed to detect the DNA signal) value less than 40 (Takahara CHAPTER 2 49 et al., 2020; Westhoff et al., 2022). To validate that the PCR was not inhibited, an additional analysis adding a known amount of DNA (0.1 ng) of a targeted species (Internal Positive Control - IPC) to each sample was performed. The composition of the PCR mixture as well as the thermocycling conditions were the same as above, but the reaction included 2 µl of IPC, with an adjustment to the volume of water. A sample was identified as inhibited if the Ct value was delayed or failed to amplify in this PCR. 2.5 Digital PCR (dPCR) analysis Digital PCR (dPCR), utilizing the QIAcuity One, 5plex (Qiagen), was used to validate and compare the detection sensitivities between qPCR and dPCR on samples collected from Spanish rivers. Additionally, we analyzed a new set of samples that were collected along transects extending from the estuaries of rivers Bidasoa, Oiartzun, Urola and Deba. The primer and probe sets utilized in the dPCR assays were consistent with those used in the qPCR analyses, with ROX-labelled probes designated for Alosa detection and Cy5-labelled probes for P. marinus detection. Each dPCR reaction contained 10 µl of QIAcuity Probe PCR Kit, 3.2 µl of probe mix, 2 µl of extracted DNA, and 24.8 µl of Milli-Q water, resulting in a total reaction volume of 40 µl. This 40 µl reaction volume was then transferred into microfluidic dPCR nanoplates (QIAcuity) capable of accommodating 24 samples, with each well divided into up to 26,000 partitions. Each of these partitions enables individual PCR reactions to occur within them. The nanoplate was then loaded onto the digital PCR instrument (QIAcuity One, 5plex) and subjected to an automated workflow after quantifying the cycling protocol. The thermal cycle was executed under the following conditions: an initial step at 95°C for 2 minutes, followed by 40 cycles alternating between 95°C for 15 seconds and 60°C for 60 seconds. Each plate included positive controls (standard dilution series with tissue samples) and negative controls (no template controls, NTC). For detection, the ROX fluorescence channel was engaged to monitor Alosa spp. amplification, whereas the Cy5 fluorescence channel was used for P. marinus amplification. Fluorescent images from all PCR wells were acquired and analyzed; partitions indicating the presence of the target molecule were discerned by their elevated fluorescence intensity. The common threshold value of fluorescent intensity (RFU) was set manually, in accordance with Qiagen handbook recommendations (Qiagen, 2022), with both negative and positive controls in each reaction (Passera et al., 2023). This choice allowed us to Lessons learned from applying eDNA surveying to diadromous fish detection across the north-east Atlantic region 56 Figure 5. Spatial abundance patterns of eDNA detections using dPCR across Spanish sampling sites, where the dot size represents the eDNA concentration (copies/L) for a) lamprey and b) shads in each sampling point and red crosses indicate samples where no DNA was detected (ND). For Bidasoa river in 2020, the dots represent the average concentration (mean) of the five sampling dates within the year in which water was collected. Accordingly, the connected scatterplots show a breakdown of the results for the sampling dates within the year. Only results for those dates for which three sampling points were sampled and had at least one of them positive are shown. Statistical analysis revealed no significant differences between replicates for either P. marinus (p-value = 0.9428) or Alosa spp. (p-value = 0.3887), confirming the consistency of our sampling methodology. Overall, eDNA concentrations of P. marinus were significantly lower than those of Alosa spp. (Figure 5). In the Basque Country, P. CHAPTER 2 57 marinus eDNA was mainly detected in the Bidasoa, Oiartzun, Urumea, Oria, Barbadun and Kadagua rivers, whilst in Galicia, positive detections were recorded in the Eo, Anllóns, Umia, Ulla and Tambre rivers (Figure 5a). On the other hand, Alosa spp. displayed a more restricted distribution, with detections confined to the downstream of the Bidasoa and Deba rivers in both years, while no detections were recorded in the estuary of any of the basins in 2019 (Figure 5b). A consistent pattern of eDNA detection was observed, with higher concentrations found at downstream sites and progressively lower concentrations upstream, regardless of the sampling period (Figure 5). 4. Discussion In this study, we built on existing knowledge of P. marinus and Alosa spp. distribution through a research initiative spanning 44 river systems across Europe. This effort was made possible through international collaboration among researchers, enabling a large-scale application of the eDNA approach to assess the distribution of two diadromous fishes, both of significant conservation concern in the Northeast Atlantic region. Here we share key practical lessons from this ambitious endeavour, with the goal of guiding similar applications of eDNA for monitoring diadromous fish in similar and other contexts. 4.1 Detection discrepancies among species Here, we concurrently monitored the presence of both P. marinus and Alosa spp. using the same eDNA sample. Both species are anadromous and exhibit similar habitat preferences during their spawning migrations. During spring, adult Alosa spp. and P. marinus migrate to rivers to spawn, after which most die (Silva et al., 2013). After hatching, juvenile Alosa then migrate to the sea in late summer and autumn (Aprahamian et al., 2003), while P. marinus larvae (ammocoetes) remain buried in the riverbed for years before becoming parasitic juveniles (OSPAR Commission, 2009). This buried larval stage (Almeida et al., 2023; Limburg & Waldman, 2009), and the fact that we conducted surface water eDNA sampling, might result in low eDNA detection rates for P. marinus. Conversely, Alosa spp., with a primarily pelagic habitat and high mobility during spawning, are more likely to release eDNA into the water column during migrations. According to these predictions, in our study, eDNA detection rates between Lessons learned from applying eDNA surveying to diadromous fish detection across the north-east Atlantic region 58 the two species differed: Alosa spp. was detected in 40% of the sites where it was expected whereas P. marinus was detected in 29%. While other valid arguments could be made, these results and initial interpretations highlight the importance of incorporating speciesspecific behaviour patterns and habitat preferences into eDNA sampling design and result analysis (Baltazar-Soares et al., 2022; Clemens et al., 2022). 4.2 When and how to sample The opportunistic nature of this international monitoring survey of diadromous fish led to distinct sampling approaches by each institution, which may have influenced detection rates. These variations included sampling times, locations, collected water volumes, and filter pore sizes and types. Efforts were made to synchronize most of the eDNA sampling with the migration period of both species, assuming higher eDNA shedding rates during this time (Thalinger et al., 2019). However, this synchronization was not fully achieved for P. marinus (Kelly & King, 2001; McIntyre et al., 2007; Silva et al., 2019; Silva et al., 2013; Taverny & Elie, 2009). In the Basque Country only, sampling was performed during upstream and downstream migration, while all other regions were sampled only during downstream migration. Both Alosa spp. and P. marinus eDNA were detected during upstream migration at expected locations, but sea lamprey was largely undetected on downstream migration, likely due to mismatches in timing with peak downstream migration and lower eDNA shedding rates in surface water. In contrast, the successful detection of sea lamprey was reported in Galicia as well as in the Tamar and Dee rivers, likely due to the high population density in these areas, which increased the likelihood of eDNA presence in the water samples. Interestingly, the detection rates did not appear to be significantly influenced by While larger pore sizes can facilitate the filtration of greater water volumes, thereby increasing total eDNA yield (Capo et al., 2020; Mächler et al., 2016), our results suggest that single-species PCR detection is more dependent on DNA concentration than on filtration parameters (Eichmiller et al., 2016). Despite using same pore size (0.45 ), French samples, which used 30L of water volume, resulted in lower eDNA detection rates at expected sites than Spanish samples, which used 1-2L of water volume. This CHAPTER 2 59 observation suggests that sampling larger volumes of water does not necessarily improve detection, and that other factors, such as population density, timing, and eDNA degradation, may play more substantial roles. Although we did not observe a clear improvement in detection with increased water volume or pore size across all cases, in contexts where target species are at low abundance such as outside the peak migration period or in estuarine habitats it may still be beneficial to maximize filtered water volume and consider larger pore sizes to increase the chances of eDNA capture. However, this recommendation should be taken cautiously, as it is not yet supported by consistent empirical evidence across systems, and further research is needed to evaluate the impact of filtration parameters under lowconcentration scenarios. 4.3 Methodological differences The comparison between results of qPCR and dPCR revealed inter-specific differences. For Alosa spp., results of both approaches are similar with 96% of the samples resulting in concordant results. In this case, only 6 out of 158 samples exhibited inconsistent results. The four qPCR-positive but dPCR-negative results may represent false positives, as they were characterized by only one or two positive replicates and high cycle threshold (Ct) values. Conversely, the two dPCR-positive results that were not detected by qPCR may be attributed to low DNA quantities that were below the detection limit of qPCR. For P. marinus, the concordance rate dropped to 80%, with differing results in 31 out of 158 samples. Interestingly, 8 samples were positive by qPCR but negative by dPCR. Of these, six samples had only one or two positive qPCR replicates; however, two samples had three and four positive replicates with lower Ct values, indicating potential dPCR false negatives. dPCR utilizes extensive sample dilutions divided into thousands of independent partitions assessed through Poisson statistics (Qiagen, 2024). Significant dilution can produce partitions that do not contain the target DNA, especially at low initial concentrations (Whale et al., 2013), which might explain the observed false negatives. Additionally, 23 P. marinus samples that were positive in dPCR but negative in qPCR highlight potential limitations in the sensitivity of the qPCR method for detecting low concentrations of DNA. Overall, dPCR demonstrates superior efficacy compared to qPCR for detecting species occurring at low abundance. dPCR is also advantageous as it provides precise quantification of number of eDNA copies, which Lessons learned from applying eDNA surveying to diadromous fish detection across the north-east Atlantic region 60 allows absolute abundance comparisons between samples. Yet, to ensure reliable dPCR results, sample concentrations must be maintained within the dynamic range to reduce partitioning errors, particularly for samples of unknown concentration (Qiagen, 2024). Systematic optimisation of dilution factors improves the confidence of dPCR in identifying low target DNA concentrations, thereby reducing false negative rates. This optimization process involves adjusting the dilution levels to achieve the desired sensitivity and precision, which is particularly important when dealing with lowabundance targets (Jiang et al., 2022). While dPCR generally provides higher sensitivity and accuracy, qPCR may still be chosen in some contexts due to its lower cost, particularly in large-scale monitoring scenarios where affordability is a key consideration (Zhang et al., 2024). This trade-off between cost and accuracy highlights the importance of selecting the appropriate method based on specific research objectives and available resources. 4.4 Can eDNA be used as reliable sources of presence/absence for diadromous fish? The finding from this survey revealed inconsistencies between eDNA detection and expected occurrences of P. marinus and Alosa spp. Focusing on sites where the species were expected, we identified false negatives, which could be attributed to low abundance of the species, resulting in low eDNA concentrations in the dPCR or qPCR assays. Because false negatives can misrepresent species presence and hinder conservation efforts (Desrochers et al., 2010), it is important to reduce them by adapting sampling times to coincide with peak migration, especially during spawning periods, filtering large volumes of water, and applying more sensitive methods such as dPCR. Focusing on the sites where the species was not present, only in the case of shad we detected three apparent false positives; however, one of them occurs only in the qPCR results, only in one replicate field sample of two, only in one out of five qPCR replicates, and with high Ct values (39); the other two apparent false positive locations (Inny and Ilen rivers, Ireland) did not have dPCR results available, but the qPCR positives were based on a single replicate out of five and with high Ct values (37 & 39). In view of this, all these three apparently false positives can be considered true negatives instead. Focusing on the sites for which presence or absence in the species was unknown, all cases resulted negative for P. marinus. However, for Alosa spp., we revealed new sites where CHAPTER 2 61 the species could be present. Interestingly, in river Deba (Spain), the initial assessment of Alosa agency to return to the river where they found Alosa spp. (Ekolur, personal communication). For this study, the availability of a comprehensive reference database has enhanced our understanding of the eDNA-based results, facilitated interpretation and identification of potential causes of false negatives and positives. Therefore, we propose eDNA as a complementary information source for diadromous species monitoring, which can be applied to increase time and space coverage due to its easy logistic, noninvasiveness and cost-effectiveness. Advancing ecological assessment: The integration of eDNA metabarcoding into an estuarine fish index 62 CHAPTER 3 63 This manuscript was preprint as: Bhendarkar, M., Canals, O., Jurado, C., Mendibil, I., Uriarte, A., Borja, A., & Rodriguez-Ezpeleta, N. (2025). Advancing ecological assessment: The integration of eDNA metabarcoding into an estuarine fish index. bioRxiv, 2025.2003.2031.645977. https://doi.org/10.1101/2025.03.31.645977. Advancing ecological assessment: The integration of eDNA metabarcoding into an estuarine fish index 64 Abstract In the face of increasing anthropogenic pressures on estuarine ecosystems, the need for efficient and reliable methods to assess their ecological status is essential. This study dex (AFI) to assess its ecological status in estuarine ecosystem of the Basque Country, Spain. Surface water eDNA sample and bottom trawl survey were performed across the multiple estuaries, resulting species data were used to calculate AFI scores under different scenarios. eDNA metabarcoding consistently detected higher fish species richness than trawling, while bottom trawling remained more effective at capturing demersal species. However, ecological classifications from eDNAand bottom trawl derived data displayed low concordance, largely due to differing species assemblages and metrics contributions. These results emphasize the respective strengths and weaknesses of each methodology and the necessity for method-specific calibration. Considering that the AFI is calibrated using bottom trawl data, its direct application to eDNA-derived species lists may lead to some inconsistencies. This study underscores the critical necessity to establish eDNAspecific reference conditions and to recalibrate index thresholds accordingly. While eDNA approach may not entirely replace traditional methods, its scalability, sensitivity, and minimal ecological disturbances establish it as an essential complementary application within monitoring programs. This research strongly supports the urgent advancement of eDNA-based indices and the critical enhancement of reference conditions for their effective incorporation into ecological assessment frameworks under the Water Framework Directive. Graphical abstract CHAPTER 3 65 1. Introduction Estuaries, functioning as transitional zones between freshwater and marine environments, are amongst the most productive ecosystems on Earth, offering vital ecosystem services to nearby communities (Adey, 2024; Barbier et al., 2024). The ecological importance of estuaries lies not only in their biodiversity but also in their ability to regulate water quality and provide habitats for various species. However, anthropogenic activities and environmental stressors increasingly threaten these ecosystems, leading to significant reductions in ecosystem services (Allen et al., 2023; Elliott & Kennish, 2024; Jennerjahn & Mitchell, 2013). Additionally, climate change exacerbates these threats, raising concerns on the sustainability of estuarine supply of services (Siemes et al., 2024). In this context, assessing the ecological status of estuaries is a priority, and various assessment methods have been established under the European Water Framework Directive (WFD) for different biological elements (Birk et al., 2012) such as phytoplankton, benthic flora, benthic invertebrates and fish. Each of these methods varies between countries due to differences in the response of indicator species to relevant stressors, local species composition, sampling methods and available taxonomic resolution based on regional knowledge of flora and fauna (Birk et al., 2012; Borja et al., 2013). which is specific to each aquatic ecosystem, from which Ecological Quality Ratio (EQR) is derived by assessing the deviation of the calculated value from this reference (European Commission, 2000; Van De Bund & Solimini, 2007). However, all of them have been harmonized through intercalibration among countries using them (European Commission, 2024). Several fish-based indices have been proposed in Europe (Pérez-Domínguez et al., 2012) and globally (Cabral et al., 2022) developed primarily for evaluating ecological quality in the Basque Country estuaries, in Spain (Borja et al., 2004; Uriarte & Borja, 2009). Nowadays, AFI is one of the most widely used indices for assessing the ecological quality and biotic integrity of transitional waters (Souza & Vianna, 2020). It assesses EQR using composition and abundance data from bottom trawl surveys. However, sampling in estuarine environments presents significant logistical and technical challenges associated with physical capture of species Advancing ecological assessment: The integration of eDNA metabarcoding into an estuarine fish index 72 differences in AFI metrics (richness, pollution indicators, flatfish, omnivorous, piscivorous, and resident species) between the eDNA-AFI and trawl survey. The Relative Contribution Ratio (RCR) was calculated to determine the proportional contribution of each ecological metric to the AFI scores (Luo et al., 2015). For each method, RCR was computed as the percentage contribution of a given metric to the total AFI score. 3. Results 3.1 Sampling efficiency of eDNA and bottom trawling All samples together, eDNA metabarcoding yielded a total of 16,496,674 reads corresponding to 73 taxa (60 taxa taxonomically assigned to the species level and 13 at the genus level) from 30 orders and 37 families (Table S7). Mullets were the dominant group and accounted for approximately 46% of the reads, with Chelon ramada (35.1%) and Chelon labrosus (7.7%) being the most abundant. Other frequently detected species with significant proportion of reads included Sardina pilchardus (8.8%), Dicentrarchus labrax (6.8%), and Solea solea (6.7%). On the other hand, the trawling survey captured 310 individual fish classified into 23 species or genus (1 specimen was identified to family level and two specimens remained unclassified). Gobies were the dominant group in the catches, with Pomatochistus sp. and Gobius niger being the leading species, representing 26% and 22% of total catch, respectively. Other abundant captures were the flat fish Solea solea (20%), and the seabream Diplodus sargus (14%). As expected, eDNA metabarcoding consistently detected significantly higher fish species richness compared to the traditional trawling approach (p < 0.05) in all sampling sites except in three of them: AME (Barbadun), AOKI (Oka) and OIAE (Oiartzun) (Figure S1). A total of 43 fish species identified through the eDNA survey are listed in the AFI database of which 24 were not recorded in the trawl-based historical database (Figure 2). CHAPTER 3 73 Figure 2. Venn diagram showing the number of species obtained in the eDNA metabarcoding (orange) and bottom trawling (green) surveys, with each method supported by a comprehensive reference database. The reference includes historical trawl catch data from 2002-2019, while the eDNA survey utilizes a local sequence database from the Northeast Atlantic. It is important to note that the trawling reference database excludes species that remain unclassified up to the genus and/or species level. Only seven species were recorded using both methods, yet they accounted for 87% of the trawl caught individuals and 24% of the eDNA sequence reads. The trawling survey captured 16 fish taxa that were not detected through eDNA metabarcoding. Of these, eight taxa were absent in the reference database, while the remaining eight, despite being in the reference database, were not observed in the eDNA metabarcoding. Conversely, eDNA metabarcoding exclusively detected 12 taxa within the historical database and 30 additional taxa not listed in the AFI database, many of which accounted for less than 1% of total reads (Figure 2; Table S7). 3.2 Assessing trawl and eDNA-based estuarine ecological status AFI scores were calculated using both eDNA metabarcodingand bottom trawlderived data with and without the inclusion of crustaceans. For eDNA metabarcoding, the Advancing ecological assessment: The integration of eDNA metabarcoding into an estuarine fish index 74 analysis accounted for 35 different taxa according to the AFI list and 17 different taxa based on the historical database (genus-based). The bottom trawling based AFI computations included 25 fish taxa, in addition to 13 crustacean species. Disparities in ecological status classifications between these methodologies were observed. For instance, eDNAstatus, whereas trawl- - derived data (Figure 3). Notably, when the AFI calculations were restricted to fish catch data, excluding status, with the exception of sampling site ANE, which indicated a high status, and sites ABM, OIAE, OIAI2, and UROM, which exhibited good status (Figure 3b). Figure 3a). The two eDNA-based AFI computations exhibited near0.90), reflecting consistent results across the two datasets. In contrast, the two trawl-based indicating variability in ecological status assessments when crustaceans were considered. Crucially, no agreement was observed between eDNAand trawl-derived AFI values, with kappa values ranging from -0.07 to -0.53 (Figure 3b). Additionally, significant differences were observed in some ecological metrics t-test, p < 0.05, Figure 4), namely species richness, pollution indicator species, proportions of flatfish, piscivorous species, and estuarine residents. The RCR analysis further revealed the influence of individual metrics on AFI scores. CHAPTER 3 75 Figure 3 AFI listed species), eDNA-B (considering historical database species), Trawl with crustacean, and Trawl only fish (without crustaceans). a) the level of inter-rater concordance between eDNA metabarcoding and bottom trawlnt. b) AFI scores across various sampling stations, with bars representing different computation approaches. Scores range from 0 ('Bad' status) to 1 ('High' status), with a colour gradient indicating ecological status. Some data points overlap due to identical AFI scores at different sites. Jitter (width = 0.01, height = 0.01) was applied to reduce overlap. Advancing ecological assessment: The integration of eDNA metabarcoding into an estuarine fish index 76 Figure 4 Pollution Indicator Species (%), (C) Introduced Species (%), (D) Flat Fish Species (%), (E) Omnivorous Species (%), (F) Piscivorous Species (%), (G) Number of Resident Species, and (H) Resident Species The scores assigned indicate the overall status (see Table 1), with blue representing a score of 5, yellow a score of 3, and red a score of 1. For eDNA-based assessments, omnivorous species contributed the most, accounting for 52.8% to 56.7% of the AFI score. Piscivorous species and resident species were secondary contributors, with 17.9% to 16.5% and 12.2% to 13.5%, respectively. In trawl-based assessments, contributions were more evenly distributed. Resident species had the highest impact (43.7% in fish-only analyses), followed by flatfish (28 %) and omnivorous species (17.6%). 4. Discussion 4.1 Methodological contrasts This study demonstrates the distinct capabilities of eDNA metabarcoding and bottom trawling in capturing estuarine fish assemblages, driven by their inherent methodological differences. eDNA metabarcoding detected over three times more fish species than bottom trawling, emphasizing its broader taxonomic reach. These findings align with previous studies demonstrating that eDNA consistently detects a higher number of fish species compared to conventional methods in estuaries (Gibson et al., CHAPTER 3 77 2024; Gibson et al., 2023; Saunders et al., 2024; Zou et al., 2020). However, this difference should not be interpreted as an inherent superiority of one method over the other, but rather as a reflection of their fundamentally differences in sampling approaches: eDNA was collected from the surface water during high tide and mainly detected pelagic and water-column-associated species, while bottom trawling primarily captured bottomdwelling fish. In addition, eDNA detects genetic material present in the water column, allowing for the identification of species that may not be physically present at the time of sampling (Jerde, 2021); in contrast to bottom trawling, which is based on physical captures. Among the identified species, only seven were common to both methods. These seven taxa, all demersal, were among the most abundant fish in bottom trawl catches (representing 87% of the total catch), yet they accounted for only 24% of total eDNA reads. Since eDNA concentration in the water is generally assumed to correlate with biomass (Nakagawa et al., 2022), their detection through eDNA metabarcoding suggests that highly abundant demersal species are more amenable to be detected in eDNA surface water samples than less abundant ones, which might remain undetected. Despite eDNA metabarcoding capturing a higher number of species overall, it still failed to detect 16 taxa captured by trawling, predominantly demersal (including flatfish) species. Among these, 8 species lacked reference sequences in publicly available genetic databases, preventing its detection, which reinforces the dependence of eDNA metabarcoding on comprehensive and regionally relevant reference databases for accurate species identification (Bhendarkar & Rodriguez-Ezpeleta, 2024; Claver et al., 2023; Marques et al., 2021). The remaining 8 species, despite being present in the reference database used for taxonomic classification, were not detected in eDNA samples likely due to their low abundance (and therefore expected low DNA concentration in the water) and/or limited vertical transport of their genetic material to surface water, suggesting the need of incorporating bottom water layers in eDNA sampling strategy to improve demersal species detection efficiency. On the other hand, eDNA metabarcoding detected 12 species not captured by bottom trawling but previously recorded in the historical database, demonstrating its potential to detect species that may evade physical capture due to their behaviour, rarity, or habitat preference. These results align with previous studies suggesting that bottom Advancing ecological assessment: The integration of eDNA metabarcoding into an estuarine fish index 78 trawling, while effective for demersal species, may overlook species better detected through eDNA (Afzali et al., 2021; Ip et al., 2024; Zhou et al., 2022). An additional 24 taxa previously unrecorded in the historical database were also detected through genetic . For instance, the most abundant species detected via eDNA metabarcoding Chelon ramada and Sardina pilchardus were not captured by bottom trawl and have not been previously documented in the historical database. The absence of C. ramada in bottom trawl surveys may be due to challenges associated with identifying mugilids through morphological traits, as they have historically been classified only to the family level in trawl records. In contrast, the absence of S. pilchardus in bottom trawl catches is likely attributable to its pelagic nature and ability to avoid bottom trawling gear (Haugland & Misund, 2011). While eDNA metabarcoding improves biodiversity detection, it also introduces uncertainties regarding the origins and ecological relevance of detected eDNA signals. One of the primary challenges in interpreting eDNA-based detections is the possible influence of eDNA transport mechanisms, particularly in estuarine environments characterized by complex hydrodynamics (McCartin et al., 2024). Thus, some species detections may result from eDNA fragments transported from upstream freshwater sources or introduced through tidal movements from the marine environment, rather than indicating actual species presence at the sampling location (Jeunen et al., 2019; Polanco et al., 2021). Additionally, contamination from anthropogenic sources such as sewage effluents or food waste could introduce foreign DNA, potentially inflating species richness estimates (Inoue et al., 2023). These factors highlight the need for refined analytical approaches to differentiate resident species from transient or external DNA sources, particularly in dynamic coastal ecosystems where water movement can significantly impact detection probabilities. The observed differences in species composition between surface water eDNA sampling and bottom trawling emphasize the impact of methodological choices on biodiversity assessments (Aubry et al., 2024). It is arguable that relying exclusively on either method may under-represent species diversity, indicating a complementary perspective. Surface water sampling was chosen for its ease and efficiency, making it a non-invasive, more cost-effective and much less time-demanding option compared to bottom trawling. However, its limitations in detecting benthic species suggest that including eDNA samples from bottom water layers could improve detection of demersal CHAPTER 3 79 taxa and help bridge some of the methodological gaps observed. While this study did not incorporate bottom-layer eDNA sampling, the suggestion to include it reflects the broader aim of assembling a toolkit that captures a more comprehensive view of estuarine biodiversity. Overall, the significant differences in species composition between surface water eDNA metabarcoding and bottom trawling highlight the methodological scope, species detection capabilities, and inherent biases of each approach. 4.2 Beyond the net: eDNA edge in estuarine ecological assessment The integration of eDNA metabarcoding within the AFI framework has revealed distinct differences in ecological status compared to traditional bottom trawl-based assessments. As previously discussed, these differences are primarily driven by variation in species assemblages captured by each method, which subsequently influence the index computation. This influence has contributed to the lack of agreement between eDNAand trawltwo methods assess ecological status based on different species assemblages rather than providing directly comparable results. The RCR analysis provides further insight into how different species groups influenced overall AFI scores across the two methods. In bottom trawl-derived AFI assessments, resident species (43.7%) had the strongest influence, largely driven by crustaceans. The relevance of crustaceans in the bottom trawl-based AFI was evident that there was poor agreement when bottom trawl AFI calculations without crustaceans, underscoring their critical role, particularly as key component of the AFI for the ecological assessment of some Basque estuary types (Borja et al., 2004). In contrast, crustaceans were not represented in our eDNA results due to the use of fish-specific primers (teleo region of the 12S gene; Valentini et al., 2016), which were selected to target vertebrates. Instead, eDNA-derived AFI scores were primarily influenced by its ability to detect species from multiple trophic levels by capturing genetic material dispersed in the water column. These findings underscore the necessity of calibrating eDNA-based assessments to account for taxonomic exclusions and differences in community representation. Advancing ecological assessment: The integration of eDNA metabarcoding into an estuarine fish index 80 A major challenge in integrating eDNA-based ecological assessments is the lack of specific reference conditions. Since the AFI was originally developed using bottom trawl-derived data, its classification thresholds and ecological quality class boundaries are calibrated for datasets dominated by demersal and benthic species. However, eDNA metabarcoding detects species that may not be well represented in bottom trawl surveys. Consequently, applying trawl-derived reference conditions to eDNA-based species lists may introduce classification inconsistencies and differences in ecological assessments. Establishing eDNA-specific reference conditions is therefore essential to ensure that eDNA-based assessments produce ecologically meaningful and comparable results. Once specific eDNA-based reference conditions are implemented, greater convergence between eDNAand bottom trawl-derived ecological status is expected. Beyond reference conditions, the integration of eDNA into AFI assessments also requires careful intercalibration with traditional methods (Lepage et al., 2016). Since trawl-based AFI has already been calibrated with other morphological fish sampling techniques under European regulatory frameworks (European Commission, 2024), extending this process to eDNA metabarcoding would help refine indicator species weightings, detection thresholds, and index calculations. Such adjustments are essential for ensuring regulatory compatibility and methodological consistency across monitoring programs. Despite the challenges discussed in the previous section, eDNA metabarcoding presents a compelling alternative in scenarios where conventional capture techniques are impractical or ecologically disruptive. Its non-invasive nature minimizes habitat disturbance while offering a scalable and cost-effective tool for estuarine ecological assessments. 5. Way forward This study highlights the transformative potential of eDNA metabarcoding for estuarine ecological assessment, but strategic advances are needed to ensure its effective integration and long-term applicability. First, the development of eDNA-specific reference conditions is essential to ensure that ecological status classifications are comparable to traditional AFI assessments. This requires the development of intercalibration protocols, recalibration of quality class boundaries and refinement of detection thresholds to improve compatibility and consistency of ecological assessments. Second, addressing taxonomic gaps in genetic reference databases remains a priority to minimize false CHAPTER 3 81 negatives and misclassifications. Additionally, optimizing sampling strategies by incorporating bottom water samples could improve the detection of demersal taxa, underrepresented in eDNA samples collected from the water surface. Moving forward, we recommend the development of novel eDNA-specific indices tailored to molecular data characteristics, which will enhance their application in estuarine ecological assessment. With these advancements, eDNA metabarcoding can evolve into a standardized, non-invasive tool for long-term estuarine monitoring and assessment. Advancing environmental DNA approaches for optimizing aquatic ecosystem monitoring and ecological assessment 88 provided with a baseline for evaluating eDNA detections aligned with known community composition. 2.1 False positives: context is everything When eDNA detected species not previously recorded in a given site, it raised important questions: were these detections evidence of previously undocumented presence, or were they artifacts caused by contamination, DNA transport, or methodological error? While contamination remains a concern in PCR-based methods, we minimized this risk through strict protocols including field blanks, negative controls, and decontamination procedures (Ficetola et al., 2015). Still, the interpretation of these unexpected detections required caution and context. For instance, eDNA detection of shad at three sites (chapter 2) where it was historically absent initially appeared promising. However, further analysis confirmed these as spurious results, likely stemming from trace contamination or sampling error. Similarly, Chapter 3 revealed 30 taxa absent from historical data, most of which contributed less than 1% of sequence reads. Some of these detections likely reflected DNA transported from upstream freshwater sources or the adjacent marine environment, or even human-induced contamination e.g., sewage or food waste (Inoue et al., 2023; Jeunen et al., 2019; Polanco et al., 2021). These cases highlight the importance of interpreting eDNA presence with ecological and environmental context in mind. It's also crucial to distinguish between molecular-level false positives (e.g., contamination or lab error) and ecological inference false positives, where DNA is correctly detected, but the species may not be actively using the sampled habitat (Darling et al., 2021). For example, the detection of 24 pelagic species via eDNA in estuaries despite their absence from historical trawl data was not necessarily incorrect. Rather, it reflected the limitations of bottom trawling, which primarily targets demersal species. As Darling et al. (2021) emphasize communicating this distinction clearly only that it went undetected by that method. 2.2 Uncovering false negatives On the other hand, false negatives where eDNA fails to detect a species known to be present can result from low DNA concentrations, poor assay design, incomplete GENERAL DISCUSSION 89 reference libraries, or seasonal absence (Ficetola et al., 2015). In chapter 2, qPCR failed to detect sea lamprey at 41 sites and shad at 21 sites where historical records confirmed presence, initially raised the possibility of false negatives instances where the species was present but went undetected by the assay. For sea lamprey, dPCR successfully detected the species at 23 sites out of 41 where qPCR had failed, confirming these as methodological false negatives rather than ecological absence likely caused by the limited sensitivity of qPCR. However, in case of shad, these historically presence sites remain undetected even with dPCR. This consistent absence across both assays suggests a potential ecological decline rather than a methodological limitation, pointing toward a possible true negative scenario at those locations. In Chapter 3, some species remained undetected by eDNA simply due to a lack of reference sequences, which prevented identification despite their DNA being present. Taken together, these examples underscore the value of using eDNA data in conjunction with historical records and other contextual information. Misinterpretation can be minimized by distinguishing between different types of errors and by understanding the limitations of both molecular and traditional methods. Ultimately, eDNA should not be viewed in isolation but as part of an integrated monitoring framework that balances sensitivity with ecological understanding. 3. Beyond species detection Beyond simply cataloguing species, this thesis explored how eDNA data can be integrated into estuarine ecological assessments. Chapter 3 explored the feasibility of using eDNA data to inform ecological status assessments, comparing results with those derived from traditional bottom trawl surveys. The findings revealed that the choice of method as discussed above can significantly influence the ecological status and conclusions drawn. The differences in ecological status are not flaws, but reflections of how each method samples biodiversity differently, and particularly how existing indices interpret eDNA-derived community data compared to traditional sources. Most indices were originally designed with traditional survey data in mind. If eDNA is to be integrated meaningfully into these tools, we must consider how its broader detection capacity interacts with existing scoring systems. Interpreting eDNA-derived indices requires an understanding of DNA transport, degradation, and persistence, particularly in dynamic environments like estuaries. At the same time, these findings offer a major opportunity. Advancing environmental DNA approaches for optimizing aquatic ecosystem monitoring and ecological assessment 90 -invasive, scalable nature makes it well-suited for large-scale and repeatable ecosystem assessments (Thomsen et al., 2024). Rather than replacing traditional surveys, eDNA analysis would be seen as a complementary data stream one that can expand and refine how we evaluate ecosystem condition. But this integration will require recalibrating existing assessment frameworks, developing method-specific reference points, and building confidence in molecular data through continued validation and crossmethod comparisons (Lepage et al., 2016). 3.1 Realizing Despite rapid advancements in eDNA technology, its global application remains uneven. The majority of studies have been developed and tested in temperate regions, leading to methodological frameworks that may not directly translate to tropical ecosystems where biodiversity is not only richer but also more at risk (Robson et al., 2016). This thesis highlights both the need and the complexity of extending eDNA analysis into tropical regions. Chapter 1 provided a global synthesis, revealing how tropical countries, despite being biodiversity hotspots and major contributors to global fisheries are underrepresented in eDNA research. From the finding, one of the most significant limitations is the lack of comprehensive genetic reference databases. Therefore, even when eDNA is successfully sequenced, the absence of matching barcode data prevents accurate species-level identification. For example, India stands out as a significant player in the global fisheries sector, yet it grapples with substantial gaps in its reference databases, which significantly hindering the application of eDNA-based biodiversity monitoring. In tropical aquatic systems, high temperatures, elevated microbial loads, and hydrological turbulence interact to accelerate eDNA degradation. As shown by Barnes and Turner (2016) and Strickler et al. (2015), these environmental stressors significantly shorten the eDNA detection window, posing unique challenges for biodiversity monitoring in tropical regions. Species that are transient, present at low densities, or characterized by minimal DNA shedding pose a higher risk of going undetected particularly in warm, high-turnover environments where degradation rates are elevated (Hunter et al., 2017; Tsuji et al., 2017). This makes false negatives a critical limitation GENERAL DISCUSSION 91 for eDNA monitoring in tropical and dynamic aquatic systems. As demonstrated in Chapter 2, detection sensitivity plays a pivotal role in overcoming these challenges. The superior performance of molecular assay in detecting low-concentration DNA suggests that more sensitive molecular approaches are essential for reliable monitoring in tropical environments. Additionally, hydrological complexity, including high sediment loads, seasonal flow variability, and strong tidal influence can cause eDNA to be transported over long distances or entrapped in sediment layers, creating spatial mismatches between where a species is detected and where it is actually present. As shown in Chapter 3, such transport dynamics complicate species localization and interpretation in estuarine ecosystems. These effects are likely even more pronounced in tropical systems, especially during monsoon seasons or within highly connected river networks, further complicating accurate ecological inference. The lessons drawn from this thesis emphasize the need for adaptation rather than replication when applying eDNA methodologies across diverse ecological contexts. While Chapters 2 and 3 focused on temperate ecosystems, they provide methodological insights such as assay sensitivity, interpretive rigor, and the critical importance of comprehensive reference databases that are highly relevant to tropical regions. These insights demonstrate that eDNA monitoring is not a one-size-fits-all solution, but rather a framework that must be tailored to local environmental and biological conditions. When integrated with the global synthesis presented in Chapter 1, the findings underscore the urgency of developing region-specific workflows for eDNA application in tropical ecosystems. 4. The big picture: advancing eDNA science for the future As this thesis has shown, eDNA offers a new lens for understanding the way we approach from enhancing species detection to broadening ecological assessments. While many of the directions outlined here are already being pursued in specific contexts particularly in temperate systems or research-intensive regions they have yet to be universally implemented, standardized, or adapted to the full spectrum of ecological and policy settings. The following priorities are not presented as novel ideas but as key areas that require broader attention, coordination, and investment. Advancing environmental DNA approaches for optimizing aquatic ecosystem monitoring and ecological assessment 92 4.1 Improve understanding of eDNA fate and transport Despite rapid growth in eDNA applications, significant uncertainties remain around how eDNA behaves in different environments. Research is needed to clarify how long eDNA persists, how far it travels, and how environmental variables (e.g., temperature, sediment, microbial activity) influence its detectability. Combining eDNA research with hydrological, Lagrangian, and sediment transport models will be essential for improving spatial interpretation and reducing inference errors (Andruszkiewicz et al., 2019; Perry et al., 2024). 4.2 Enhance the quantitative power of eDNA Most current eDNA applications focus on presence absence detection, which limits their usefulness for monitoring population trends. Future work should establish links between eDNA signal strength and species abundance or biomass. Tools such as dPCR, occupancy modeling, and machine learning offer promise but require broader ecological validation. Developing standardized quantification frameworks will be key to using eDNA in stock assessments and conservation planning (Yates et al., 2019). 4.3 Expand and regionalize reference databases Accurate eDNA species identification depends on the availability of complete and curated genetic reference databases. In many regions particularly the tropics barcode coverage is sparse. Even when sequencing is successful, limited databases result in false negatives or ambiguous detections. Significant investment in taxon-specific barcoding and regional database development is foundational for scaling eDNA monitoring globally (Claver et al., 2023). 4.4 Integrate eDNA analysis into policy and monitoring frameworks For eDNA to transition from academic research into environmental policy, it must be supported by formal standards, legal guidance, and regulatory integration. Currently, inconsistent methods hinder its use in environmental reporting and conservation law. As Theroux et al. (2025) argue, standardized protocols are crucial for data credibility, reproducibility, and regulatory trust. GENERAL DISCUSSION 93 4.5 Adopt automation and remote monitoring technologies The future of eDNA lies in automated, real-time sampling platforms that integrate remote sensing and rapid analysis. These innovations allow for broader spatial and temporal coverage, early detection of invasive species, and biodiversity tracking in hardto-reach areas. Advances in sensor design and automated processing are already underway and will be key to scalable eDNA deployment (Preston et al., 2023; Sepulveda et al., 2020). 4.6 Promote interdisciplinary and inclusive collaboration eDNA science thrives through collaboration between ecologists, molecular biologists, data scientists, hydrologists, and local communities. Involving stakeholders especially those in biodiversity-rich but infrastructure-limited areas can improve data coverage, reduce costs, and support inclusive conservation. Community-based sampling efforts in the Neotropics and sub-Saharan regions are examples of this collaborative future. 4.7 Expand toward ecosystem-level, multi-trophic eDNA assessments Beyond species lists, future eDNA frameworks could assess ecosystem health by analyzing multiple trophic levels (e.g., microbes, invertebrates, fish, mammals) from a single sample. This would support more holistic ecological indicators and offer new ways to monitor environmental change and restoration success. 4.8 Advance Global Standardization of eDNA Analysis One of the most critical global needs is the harmonization of eDNA methods across field sampling, laboratory workflows, and data analysis. Currently, methodological inconsistency reduces the comparability of eDNA results between regions, limiting its policy utility and undermining reproducibility. As outlined by the USGS and international partners, globally recognized standards covering QA/QC, contamination control, assay calibration, and reporting are foundational to the future of eDNA as a cross-border monitoring approach (Theroux et al., 2025). Advancing environmental DNA approaches for optimizing aquatic ecosystem monitoring and ecological assessment 94 CONCLUSION AND THESIS 95 Advancing environmental DNA approaches for optimizing aquatic ecosystem monitoring and ecological assessment 96 The overarching aim of this study was to evaluate and advance the use of environmental DNA (eDNA) analysis as a practical and reliable approach for monitoring fish biodiversity and assessing ecological conditions in estuarine ecosystems. The study assessed the methodological performance of eDNA analysis, its ecological applicability, and potential integration into conservation and fisheries management frameworks. Based on the synthesis, empirical investigations, and methodological comparisons conducted throughout the three core chapters, the following conclusions were drawn: 1) eDNA analysis presents significant opportunities for tropical fisheries management by providing a non-invasive, cost-effective approach to fisheries resource management in data-limited regions; however, challenges such as methodological inconsistencies, limited reference databases, and geographical biases present challenges to its region-specific adoption. 2) Assay sensitivity plays a critical role in species detection, particularly for lowabundance or cryptic species. The comparison between qPCR and dPCR in detecting diadromous fishes revealed that dPCR significantly improved detection of sea lamprey in low-concentration scenarios, underscoring the importance of aligning assay selection with species ecology. 3) Broad-scale eDNA surveys revealed concerning patterns of species absence in historically occupied habitats across 44 river basins, especially for conservationpriority species such as European shad and sea lamprey. These findings support evidence of population declines and demonstrate the value of eDNA for longterm, basin-wide monitoring. 4) eDNA metabarcoding improved species detection by capturing a broader taxonomic range than bottom trawl surveys, making it a valuable approach for enhancing catchability estimates and providing a more comprehensive assessment of target species assemblages. 5) eDNA metabarcoding offers a promising non-invasive approach for contributing to estuarine ecological assessment indices as a complement rather than a replacement for conventional methods, and calibration efforts are needed for regulatory applications under frameworks like the European Water Framework Directive (WFD) to align eDNA-based biodiversity assessments with existing ecological indices. CONCLUSION AND THESIS 97 6) Applying eDNA analyses across different aquatic environments confirmed its potential and limitations, emphasizing the need for methodological refinement, including species-specific detection biases, the influence of sampling strategy on DNA recovery, and the necessity for improved regional reference databases to enable more precise taxonomic resolution and ecological interpretation. The conclusions reached on this thesis dissertation allowed working towards the stated hypothesis, being the thesis that: for monitoring fish biodiversity across riverine and estuarine systems. 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