Understanding and predicting ecosystem responses to global change is a major challenge in aquatic ecology. Trait-based approaches have emerged as useful for understanding aquatic ecosystem functions, including primary productivity, methanogenesis, nutrient cycling, and food web dynamics, amongst others. Specifically, functional traits are recognized as a necessary link for scaling the interactions between organisms and the environment from individuals to ecosystems. For example, functional traits of bacteria and phytoplankton, such as size, growth rate, temperature optima, and stoichiometry, are understood to influence community assembly and ecosystem elemental cycling. Similarly, growth rates and feeding rates of zooplankton can help inform trophic transfer of energy and nutrients. This session aims to integrate across disciplines and scales of organization to highlight the “bio” in biogeochemistry and showcase studies which provide mechanistic understanding of global change impacts on aquatic populations, communities, and ecosystems. To this end, we welcome contributions that use any study system, from micro- to macro-organisms, and any combination of field, laboratory, and/or process-modeling approaches to explicitly consider how variation in organismal traits influences ecosystem function. We particularly encourage submissions by early career researchers as well as by researchers from BIPOC, LGBTQIA+, and other marginalized identities.
Lead Organizer: Brittni Bertolet, University of California Irvine (brittnibertolet@gmail.com)
Co-organizers:
Celia Symons, University of California Irvine (csymons@uci.edu)
Carly Olson, University of Nebraska Lincoln (carlyrolson2@gmail.com)
Presentations
05:30 PM
Phytoplankton Community Dynamics in the Black Sea: Insights from High-Performance Liquid Chromatography (HPLC) Data Analysis across 12 Oceanographic Campaigns (7736)
Primary Presenter: Elisabetta Canuti, Joint Research Centre, European Commission (elisabetta.canuti@gmail.com)
The marine ecosystem of the Black Sea houses a diverse phytoplankton community crucial for regional biogeochemical processes. Recent efforts have focused on understanding the taxonomy and dynamics of this community. High-performance liquid chromatography (HPLC) emerges as a powerful tool for pigment separation and identification in phytoplankton samples. This study examines HPLC pigment data collected during 12 oceanographic bio-optic campaigns in the Black Sea occurred from 2006 to 2019. The primary objective is to understand the taxonomic composition and community structure of the phytoplankton community. Analysis involved employing various statistical techniques and bioinformatics tools, including clustering, network-based community detection. These methods aimed to identify distinct phytoplankton groups and their relative abundance across the campaigns. Results reveal that the Black Sea phytoplankton community is predominantly composed of diatoms and dinoflagellates, with varying contributions from other groups such as prasinophytes, haptophytes (coccolitophores), and chlorophytes. Additionally, different patterns of community composition and pigment ratios were investigated across the campaigns, indicating spatial variations in phytoplankton community structure influenced by environmental factors. This study aims to contribute to our understanding of the extent to which advanced multivariate analysis techniques can be applied to the investigation of the taxonomy and community structure of Black Sea phytoplankton.
05:30 PM
Trait-based microbial interactions and their influence on ecosystem function intensifies under stress (7968)
Primary Presenter: Brittni Bertolet, University of California Irvine (brittnibertolet@gmail.com)
A major challenge in ecology is to understand how different populations interact to determine ecosystem function, particularly in communities with large numbers of co-occurring populations. We use a trait-based model of microbial litter decomposition (DEMENT) to quantify how different populations impact ecosystem function. DEMENT is a spatially explicit, individual-based process model that specifically highlights the interactions of microbial functional guilds over exo-enzymes. Using such a model, we conduct simulation experiments to build a novel framework that highlights the interplay between population traits and environmental conditions, focusing on their combined influence on community interactions and ecosystem function. Our results suggest that the impact of a population is driven by its resource acquisition traits and the community functional capacity, but that physiological stress amplifies the impact of both positive and negative interactions. Further, net positive impacts on ecosystem function can arise even as populations have negative pairwise interactions with neighboring populations. As communities shift in response to global climate change, our findings reveal the potential to predict the biogeochemical functioning of communities from population traits and interactions.
05:30 PM
FRESHWATER ZOOPLANKTON DIEL VERTICAL MIGRATION AND CARBON FLUX UNDER VARYING LEVELS OF PLANKTIVORY: A MESOCOSM-BASED APPROACH (7975)
Primary Presenter: Anna Schmidt, University of Vermont (anna.schmidt@uvm.edu)
Zooplankton often exhibit diel vertical migration (DVM) in lakes, whereby they reside in deeper waters during the day to avoid fish predation and migrate to surface waters at night to feed on phytoplankton. Zooplankton are expected to exhibit more pronounced DVM behavior in lakes with higher predation risk from planktivorous fish. However, zooplankton trait-based groups differ in their evasion capabilities, which may drive diverse behavioral responses to planktivory. Zooplankton DVM behavior contributes to the downward transport of organic carbon to deep waters and sediments in the ocean, but DVM-mediated carbon flux has not been quantified in freshwater systems. We manipulated densities of planktivorous fish in 14 large enclosures (9 m diameter x 20 m deep) at the LakeLab in Lake Stechlin, Germany for six weeks in spring 2023 to investigate differences in DVM behavior of zooplankton functional groups, and to quantify impacts of DVM on carbon cycling. DVM was quantified using AI-supported high-resolution in situ video (MDPI). Preliminary results indicate stronger migration responses for larger individuals and taxa with weaker evasion capabilities. We use zooplankton respiration and fecal pellet production models, combined with physical parameters and particulate and dissolved carbon concentrations, to investigate how DVM drives carbon flux dynamics through changes in respiration and excretion across time and space. Our results will contribute to better understanding impacts of fish community changes on zooplankton behavioral dynamics and roles in lake ecosystem function.
05:30 PM
A trait-based approach to understanding the drivers of phytoplankton communities on agricultural landscapes (7977)
Primary Presenter: Grace Jackson, Iowa State University (ghj@iastate.edu)
As phytoplankton form the base of aquatic food webs, their response to global change is of central importance to the healthy functioning of freshwater ecosystems. There are a myriad of internal and climatic factors that determine how communities are assembled, and freshwaters must also contend with anthropogenic changes across their broader catchments. For instance, runoff from agricultural lands can degrade downstream water quality, resulting in eutrophic conditions that impact algal growth. While organisms respond to these inputs in different ways, the phenotypic traits of phytoplankton offer critical insights into both how communities react to environmental changes and their functional ramifications. To better understand the biodiversity and functioning of phytoplankton communities on landscapes facing intensive agriculture, we leveraged data from the Iowa Ambient Lake Monitoring Program, which has collected water quality and phytoplankton samples from over 120 lakes and reservoirs since the year 2000. We applied a trait-based approach, combining environmental and compositional data with species traits to investigate the influence of water quality parameters, including nitrogen and phosphorus, on functional diversity. Our study of phytoplankton trait-environment relationships provides new insights into the consequences of shifting nutrients and other environmental conditions, such as the potential for harmful, toxin-producing blooms of cyanobacteria.
05:30 PM
FROM CELLULAR TRAITS TO POPULATION DYNAMICS: INTRASPECIFIC VARIATION IN THE EFFECTS OF CO2 AND NITROGEN ON A TOXIC CYANOBACTERIUM (8013)
Primary Presenter: Savannah Sarkis, Netherlands Institute of Ecology (NIOO-KNAW) (s.sarkis@nioo.knaw.nl)
Eutrophication and elevated pCO2 impact aquatic ecosystem functioning in a multitude of ways, including proliferation of harmful cyanobacterial blooms. These alterations in biogeochemical cycles impact harmful cyanobacteria, which manifests as shifts in a range of their traits like growth, nutrient uptake, and toxin production. As such, we can use a trait-based approach to mechanistically understand the cellular processes underlying the success of toxic cyanobacterial species along environmental gradients. In this study, we assessed how changes in CO2 levels combined with low and high nitrogen (N) availabilities affected growth, nitrogen uptake, cellular elemental stoichiometry, and toxin production in three toxic strains of Microcystis aeruginosa. Our findings showed interactive effects between CO2 and N on growth, stoichiometry, and toxin production consistently across strains. Regarding nitrogen growth affinities, the three strains showed differential responses, which likely will have implications for population dynamics across increasing CO2 levels. So far, our findings show stoichiometrically predictable responses in key traits, notably toxin synthesis, which will support our understanding of the future combined effects of CO2 and nitrogen variation on cyanobacterial growth, population dynamics, and bloom toxicity.
05:30 PM
Distribution and Biogeochemical Impacts of Viruses in the Laurentian Great Lakes (8360)
Primary Presenter: Alice Turnham, University of Chicago (aturnham@uchicago.edu)
Viruses are the most abundant biological entities on earth and can have important effects on microbial populations and biogeochemical cycling. Significant efforts have been made to understand the diversity of viruses in natural environments, but freshwater viruses remain understudied compared to oceans. The biogeochemical impacts of viruses are a crucial missing component in the understanding of the microbial communities and nutrient cycling in these ecosystems. The Laurentian Great Lakes are a useful model for studying viral ecology across lake ecosystems because of the wide range of environmental conditions and diverse microbial communities. Using metagenomics, we characterized viral diversity in the Great Lakes across years, seasons, and depths. We recovered thousands of dereplicated viral genome fragments and 196 complete viral genomes which are predicted to infect a range of hosts spanning eight bacterial phyla including the highly abundant heterotroph genus Fonsibacter. Great Lakes viral communities are dominated by double-stranded head-tail bacteriophage and contain a large abundance of mega-viruses. Viral community structure differed by lake, suggesting local-scale infection dynamics predominate in this interconnected system. Auxiliary metabolic genes, including those involved in carbon fixation and photosynthesis, are present in viruses across the lakes, suggesting that phages have the potential to play an important role in carbon cycling. Our findings provide a first step to incorporating the effects of viral infection to predict the ecology and biogeochemistry of the Great Lakes.
05:30 PM
PATTERNS OF ANOXYGENIC PHOTOTROPHY IN THE LAURENTIAN GREAT LAKES (8403)
Primary Presenter: Corey Rundquist, University of Chicago (crundquist@uchicago.edu)
Bacteria that use bacteriochlorophyll for anoxygenic phototrophy, known as AAPB, can support a range of unique metabolic strategies in aquatic environments and remain an understudied and ecologically important group. 341 dereplicated metagenome assembled genomes (MAGs) from the Laurentian Great Lakes were analyzed for the presence of 27 anoxygenic photosystem genes with Kegg orthologs. This search revealed that 64 of the 341 MAGs found across three different taxonomic classes indicated having the capability for anoxygenic phototrophy. A majority of these AAPB were found in the order Burkholderiales in the Gammaproteobacteria, with the rest residing in the Alphaproteobacteria and Gemmatimonadetes classes. Across the five lakes, these bacteria were primarily found in samples from lakes Erie, Michigan, and Huron with a majority of the group found in epilimnion samples. Additionally, there was a wide diversity of distribution patterns for the AAPB MAGs across different samples including some species that were found in nearly all the samples, species found in only samples from Lake Erie, and others found in only the surface samples. Furthermore, within individual taxonomic clades, closely related taxa of AAPB showed a lake-driven partitioning of their abundances. The AAPB MAGs showed distinct genome characteristics, including a large genome size, high GC-content, as well as low carbon in their proteomes. The overall abundance of AAPB in a sample was positively correlated with temperature, phosphorus and chlorophyll, and negatively correlated with depth and oxidized nitrogen, highlighting their role as surface-dwelling organoheterotrophs.
SS27P - Highlighting the “Bio” in Biogeochemistry: Trait-Based Insights Into Aquatic Ecosystem Functioning and Its Response to Global Change
Description
Time: 5:30 PM
Date: 6/6/2024
Room: Madison Ballroom D