This session is about people, the environment, and respect for Nibi (Water). We recognize that humans and the land are deeply interconnected, bound together as relatives within a shared circle of life. We honour the teachings that remind us that what affects the Earth impacts us, and that by caring for the land and waters, we care for ourselves and future generations.
From long before the advent of modern scientific tools to today, Indigenous knowledge holders and community-based groups have led the way in monitoring aquatic systems, developing deep, place-based understandings of ecosystem change. Here we model a new paradigm as the scientific community shifts away from extractive research methods toward more collaborative, respectful, and cocreated approaches to data collection, analysis, and decision-making.
Concurrently, the field of molecular biology and environmental sensing is undergoing rapid progress. This includes environmental DNA (eDNA), high‑resolution remote sensing (such as satellite and UAV imagery), autonomous underwater vehicles (AUVs), drones, passive acoustic monitoring, machine learning data processing, and in situ sensor networks. These advancements are revolutionizing the way we observe freshwater ecosystems and biodiversity by offering unprecedented sensitivity, spatial coverage, and non‑invasive monitoring capacity.
Often developed independently, Indigenous knowledge systems, community‑based monitoring, and emerging technologies possess complementary strengths that can advance freshwater science in the 21st century. Thoughtful alignment of these approaches—including attention to scale, interpretation, and data stewardship—can enhance their collective value and relevance across diverse monitoring contexts. To ensure continuity and comparability with the data that currently guide environmental decision‑making, it is essential to integrate emerging data streams with existing long‑term monitoring programs.
The session will be used as a platform to identify opportunities for collaboration and synergies among researchers, Indigenous communities, practitioners, stakeholders participating in monitoring, and the emerging technologies they are developing. As such, this session will provide an opportunity for exchange on research that applies and integrates emerging technologies with existing community‑, Indigenous‑, or NGO‑led monitoring practices, as well as long‑term scientific monitoring programs.
Specifically, we envision co‑developing discussions related to the following themes:
· Novel approaches towards quantifying and/or qualifying species distributions and/or abundances;
· The development of methodological techniques and best practices for emerging methods in freshwater ecology;
· The role of emerging technologies in detecting and monitoring aquatic biodiversity;
· Identifying potential synergies between emerging methods for surveying freshwaters for holistic, non‑invasive ecosystem monitoring;
· Bridging current and emerging monitoring techniques with long‑term, community‑based, and Indigenous monitoring initiatives to extend monitoring capacity across spatial, temporal, and institutional scales
Lead Organizer: Jack Greenhalgh, McGill University (jackhalgh95@gmail.com)
Co-organizers:
Valérie Langlois, McGill University (valerie.langlois3@mail.mcgill.ca)
Geneviève D’Avignon, McGill University (genevieve.davignon@usherbrooke.ca)
Presentations
09:00 AM
From Genes to Satellites: Uncovering Microbial Drivers of Water Quality and Green House Gas Flux in Southeastern U.S. Reservoirs (10920)
Primary Presenter: Scott Gifford, The University of North Carolina at Chapel Hill (sgifford@email.unc.edu)
Microbial communities are fundamental drivers of the ecology and biogeochemistry of inland waters, yet their composition, functional potential, and spatial distribution remain poorly characterized. Current monitoring often relies on traditional methods like microscopy, which have low spatial resolution and can miss critical microbial "hotspots" or the precise genetic identity of toxin-producing organisms. This gap limits our ability to predict and manage water quality effectively. To address this challenge, our research integrates field sampling with a suite of advanced technologies: metagenomic sequencing, flow cytometry, high-throughput microscopy, and satellite remote sensing, in key reservoirs of the southeastern U.S. We aim to build a new framework to map microbial communities and their functions at a reservoir-wide scale, and how these spatial gradients map onto harmful agal blooms and associated greenhouse gas concentrations (CH4, N2O, CO2). Our initial findings from Jordan Lake, NC reveal substantial spatial variability in microbial cell abundance, identifying "hotspots" with microbial biomass double that of adjacent areas. This variability extends beyond typical river-to-dam gradients. Furthermore, metagenomic analysis of samples from the Jordan Lake and Haw River systems following a major storm event produced over 80 distinct microbial genomes. Critically, this included the assembled genome of the known toxin-producing cyanobacterium Raphidiopsis brookii. This integrated approach provides an exceptional view of microbial biodiversity and functional potential. By linking this "on-the-ground" genomic data to satellite-observable parameters, this work is developing a scalable, predictive capacity to assess water quality, identify emerging threats from harmful algal blooms, and provide powerful new tools for in-land water resource managers.
09:15 AM
HOW VEGETATION REMOVAL IMPACTS FRESHWATER SOUNDSCAPES: INSIGHTS FROM TWO ONTARIO LAKES USING SOUNDSCAPE ANALYSIS (11770)
Primary Presenter: Husnah Azmi, Toronto Metropolitan University (stephajm@gmail.com)
Freshwater lakes are vital for ecological balance and provide essential services, supporting diverse communities of sound-producing organisms and geophysical processes. Passive acoustic monitoring (PAM) offers a non-invasive way to study these soundscapes, yet many aspects of aquatic bioacoustics, especially in infra- and ultra-sonic ranges, remain understudied. This study analyzes broadband acoustic data (2 Hz–250 kHz) collected from Lake Scugog and Canal Lake, two Ontario lakes with excessive aquatic vegetation growth, to examine how vegetation removal influences soundscapes. Three methods of removal were used: aquatic thruster, weed sickle, and lake rake. Biweekly acoustic and water quality recordings were collected three times before and after removal using a Song Meter SM4 hydrophone and an EXO2 sonde. Vegetation removal was expected to reduce acoustic complexity by eliminating habitat and plant sound production, while potentially increasing detectability of remaining organisms. Preliminary analyses show a slight increase in detected sounds after removal in both lakes. Control sites remained acoustically stable, while treatment sites showed method-specific responses: in Lake Scugog, thruster and weed sickle sites showed post-removal declines, and in Canal Lake all methods showed a brief decline followed by recovery, with thruster sites exhibiting the strongest decrease. These results suggest that vegetation removal effects are subtle, variable across methods, and that temporal variation remains an important factor when interpreting freshwater soundscape patterns.
09:30 AM
Environmental and predator control of mysid shrimp vertical distribution in Lake Superior assessed from uncrewed surface vessels (11412)
Primary Presenter: Kayden Nasworthy, Cornell University (kcn33@cornell.edu)
Mysid shrimp (Mysis diluviana) are the dominant offshore zooplankton food item for planktivorous fish throughout Lake Superior. Understanding mysis vertical distribution throughout the lake is important for informing their habitat overlap with benthic and pelagic fish predators. We use active hydroacoustic data from two autonomous Uncrewed Surface Vessels (USV) collected in the western arm of Lake Superior from 11 August to 13 September 2022 to assess the vertical distribution of mysids and fish through several diel vertical migration (DVM) cycles. Low-noise data generated from USVs also made it possible to assess deep daytime mysid and fish distributions. Using satellite-derived surface light attenuation data and an astronomical surface illuminance model, we predicted the depths of mysids for both day and night using published mysid distribution models based on light and temperature preferences. We then used generalized additive models to compare USV-observed mysid depths with model-predicted mysid depths, and test for additional effects of fish depth and abundance. Surface light intensity and bathymetric depth significantly explained mysid depth both day and night. At night, mysid depth was further influenced by surface water temperature, fish depth, and fish biomass. Finally, during the day only fish depth further improved model fit. This enhanced view of mysid vertical distribution provides insight on trophic connectivity between fish and mysids as well as benthic-pelagic coupling in the offshore of Lake Superior.
09:45 AM
Can different molecular identification approaches to aquatic insects effectively supplement morphology-based biomonitoring in a multi-gradient river system in Japan? (11012)
Primary Presenter: John Claude Renan Salluta, University of Yamanashi (g23dtka4@yamanashi.ac.jp)
Aquatic ecosystems are under immense pressure brought by anthropogenic stressors. In Japan’s Fujikawa River Basin, significant land use change such as flood-mitigating structures and river dredging in the past decade are present. This in turn affects the riverine biological and nutrient continuity. Aquatic insects are widely used as biological indicators because they inhabit diverse ecological niches. However, complexity arising from morphology-based monitoring limits ecological implications due to coarse taxonomic identification. Here, the study applied DNA metabarcoding (DM) and species delimitation (SD) with the aim to supplement morpho-based biomonitoring in 25 stream sites across the river basin. DNA for each morpho-taxa was extracted, with 16s rRNA and Cytochrome Oxidase I (COI) region amplified and sequenced using NGS. Then, sequence data were filtered, clustered into Amplicon Sequence Variants (ASVs), and matched to species by BLAST (≥ 97% identity). For SD, a combination of phylogenetic analyses and ABGD species delimitation were performed and assigned in Molecular Operational Taxonomic Units (MOTUs). Based on the Chironomid data, DM findings has 25 taxa while SD-based data has 52 MOTUs. Forward selection CCA revealed that DM-based model has sensitivity with pH and Cl- while for SD-based result, it was pH, Cl-, and water velocity. Negative binomial GLM showed that most biodiversity indices based from molecular identification had contrasting response with Cl- and pH. These findings highlight the sensitivity of molecular approaches in supplementing morphology-based biomonitoring.
10:00 AM
THE POTENTIAL OF UNDERWATER IMAGERY FOR THE CHARACTERIZATION OF NEOTROPICAL FRESHWATER FISH COMMUNITIES (11380)
Primary Presenter: Maryanne Doyon, Université du Québec à Trois-Rivières (maryanne.doyon@uqtr.ca)
With freshwater ecosystems among the most threatened globally, the need for a low-cost, low-effort, large-scale survey tool has never been more present. Underwater imagery is a promising tool that could expand the scope of monitoring programs, yet its efficiency has mostly been demonstrated in marine environments, with comparatively less research in freshwater systems. This research aims to evaluate the reliability of underwater videos for the characterization of neotropical freshwater fish communities, i.e., to estimate fish abundance and community composition and to collect simple morphological trait data. To do so, we will compare community and trait data collected with underwater videos to data obtained from more “traditional” sampling methods: minnow traps and ex situ fish photographs. A secondary goal of this study is to test whether this method can detect changes in fish communities across environmental gradients that drive fish community composition in streams. Sampling had two components: a temporal part tracking seasonal variations of a single rivers fish community, and a spatial part comparing fish communities across sites with differing abiotic parameters expected to shape fish assemblages. Fieldwork took place in the Stann Creek District of Belize, where the selected streams were sampled from November 2024 to May 2025. Overall, this study adds to a growing body of literature evaluating the optimal conditions for underwater imagery to be applicable in freshwater and may guide the deployment of biodiversity monitoring programs and citizen science initiatives.
10:15 AM
Using open-source camera traps to detect Endangered Lake Chubsucker, Erimyzon sucetta, in the Old Ausable Channel, Ontario (11527)
Primary Presenter: Jessica Reemeyer, CIEE Living Data Project - University of Regina (jessica.reemeyer@mail.mcgill.ca)
Monitoring of imperilled species is important for their conservation, but traditional sampling methods are often challenging and resource intensive. Camera trapping provides an alternative, non-invasive method of monitoring species in their environment. In this study, we developed open-source camera traps with integrated temperature and dissolved oxygen sensors and deployed them in the Old Ausable Channel, a freshwater system in Southwest Ontario. Using the cameras we were able to detect juvenile and adult Lake Chubsucker, Erimyzon sucetta, a species listed as Endangered under Canada’s Species at Risk Act. The study was conducted between June and July of 2022. We detected juvenile Lake Chubsucker at 14 of the 18 study sites, at temperatures ranging between 19.81 °C and 27.92 °C and at dissolved oxygen levels between 0.89 % and 150.24 % air saturation. Juvenile Lake Chubsucker and Common Carp tended not to be detected at the same sites (negative association probability of -0.16). Overall, the use of cameras in aquatic systems for non-invasive monitoring is an exciting and developing field.
SS055A Integrative Approaches to Freshwater Monitoring: Emerging Technologies, Community Based Programs, and Indigenous Knowledge Systems
Description
Time: 9:00 AM
Date: 16/5/2026
Room: 519A