Journal of Great Lakes Research最新文献

Microplastics are ubiquitous in the world’s aquatic environments, and their threat to aquatic biota is poorly understood, especially in freshwater ecosystems. In the environment, microbial biofilms can form on the surface of microplastics, which may sorb harmful toxins. While many laboratory-based studies use clean polymers under ecologically unrealistic conditions and concentrations, we incubated 500 μm polyethylene microplastic beads for 56 days in Muskegon Lake, Michigan, USA and used them to conduct a 28-day ingestion study with fathead minnows (Pimephales promelas). The study was conducted with a control group and two treatment groups, which received a low (4 beads) or high (16 beads) dose of weathered microplastics each day. We compared the treatment groups to the controls to assess the effects of weathered microplastic ingestion on growth (change in mass), condition factor, hematocrit, and fish gut microbial communities in both sexes. We also assessed the expression of three hepatic genes in males. Growth was lower in the high microplastic treatment group in male fathead minnows. The beta diversity of the gut microbial community was not impacted for either sex. There were some changes to alpha diversity metrics in males and several differentially abundant amplicon sequence variants (ASVs) in females. The expression of hepatic stress response genes was not altered in males. We also looked at the gut microbial community between sexes and over time within the control group and found clear differences, indicating that sex effects and environmental factors may have outweighed the impacts of microplastic ingestion on gut microbial diversity.

A coupled hydrodynamic-ecosystem model (GOTM-FABM-ERGOM) was applied to test the hypothesis that primary production in the upper mixed layers of Lake Tanganyika is primarily controlled by internal nutrient inputs. The model was calibrated (data: May 2015–April 2016) and validated (data: May 2016–April 2017) against monthly field data of water temperature, dissolved oxygen, nutrients (nitrate, ammonium, phosphate) and chlorophyll a collected from Kigoma Bay in the northern part of the lake. Data of nutrients and discharge from the rivers (Ruzizi and Malagarasi) and atmospheric dry and wet deposition were derived from the literature. The model generally showed good agreement with the observed data for water temperature, dissolved oxygen and nutrients during the calibration and validation periods. The model satisfactorily reproduced the lake’s seasonal dynamics (dry and wet seasons) induced by the lake’s hydrodynamic processes. We found that both internal and external sources contribute importantly to total nutrient loading in the lake. Our results indicate that nutrient supply from rivers into Lake Tanganyika is more important than previously known. However, we call for further studies to investigate the contribution of other sources of regenerated nutrients (e.g. N₂-fixation) to the overall primary productivity of Lake Tanganyika.

Lake water quality assessment requires quantification of phytoplankton abundance. Optical satellite imagery allows us to map this information within the entire lake area. The ESA Climate Change Initiative (ESA-CCI) estimates Chl-a concentrations, based on medium resolution satellite data, on a global scale. Chl-a concentrations provided by the ESA-CCI consortium were analyzed to assess their representativeness for water quality monitoring and subsequent phenology studies in Lake Geneva. Based on vertically resolved in-situ data, those datasets were evaluated through match-up comparisons. Because the underlying algorithms do not take into account the vertical distribution of phytoplankton, a specific analysis was performed to evaluate any potential biases in remote sensing estimation, and consequences for observed phenological trends. Different approaches to data averaging were performed to reconstruct Chl-a estimates provided by the remote sensing algorithms. Strong correlation (R-value > 0.89) and acceptable discrepancies (rmse ∼ 1.4 mg.m⁻³) were observed for the ESA-CCI data. This approach permitted recalibration of the ESA CCI data for Lake Geneva. Finally, merging satellite and in-situ data provided a consistent time series for long term analysis of phytoplankton phenology and its interannual variability since 2002. This combination of in-situ and satellite data improved the temporal resolution of the time series, enabling a more accurate identification of the timing of specific spring events characterising phytoplankton phenology.

As of 2023, 188 non-native species have been identified in the Laurentian Great Lakes, with about half being considered benign. Some of these species have been elevated to the status of invasive (i.e. causing extreme negative effects). Here, we identified and quantitatively ranked in order of impact (highest to lowest), the top ten aquatic nonindigenous species (ANS) determined to have the most significant negative environmental and socio-economic effects. To accomplish this, we used an organism impact assessment (OIA) tool developed by the Great Lakes Aquatic Nonindigenous Species Information System (GLANSIS). The top ten identified species included: zebra mussel (Dreissena polymorpha); quagga mussel (Dreissena bugensis); alewife (Alosa pseudoharengus); sea lamprey (Petromyzon marinus); Japanese stiltgrass (Microstegium vimineum); grass carp (Ctenopharyngodon idella); water chestnut (Trapa natans); common reed (Phragmites australis australis); round goby (Neogobius melanostomus); and white perch (Morone americana). The taxonomic groupings, continent of origin, and vectors of introduction of these top ten invaders do not reflect the full diversity of all invasive species in the Great Lakes region. The most common shared negative effects were: direct hazards or threats posed to native species, alteration of predator/prey dynamics, aggressive competition with native species, and costly damage to human recreation, aesthetics, and economic activities. These quantitative rankings of the top ten most harmful ANS can serve as a reference point for researchers, educators and communicators as the Great Lakes continue to be affected by the spread of invasive species and other contemporary and future anthropogenic factors affecting the Great Lakes ecosystem.

Effective management of invasive species benefits from a comprehensive understanding of the species’ behavior and interactions with the invaded system. We investigated temporal dynamics of telemetry detections and the potential utility of a traitor approach for informing response efforts to the invasive grass carp (Ctenopharyngodon idella) population in the Sandusky River, a major tributary to Lake Erie. Telemetered grass carp exhibited heightened activity at night and early morning, suggesting that capture and removal be more effective during these time periods. Analysis of catch per unit effort (CPUE) across different removal methods, trammel nets, electrofishing, and hoop nets. suggested that incorporating the traitor approach could improve capture. Low catchability values (<0.026), based on the number of telemetered grass carp present in the river on a weekly basis and the number of those telemetered fish captured, suggest the species is difficult to capture. Optimizing response effort efficiency is important and refining catchability estimates will lessen errors in population models and improve interpretation of low CPUE data. Results from generalized additive models suggest capture could be improved using telemetry data, night removals, and by attempting exploratory removal efforts in fall and winter months. By incorporating telemetry data and acknowledging the complexities of grass carp behavior and ecology, we found that a multifaceted and data-driven approach to invasive species control could be beneficial, ultimately promoting conservation and sustainability in dynamic ecosystems like Lake Erie.

Life-history variation among four lake trout Salvelinus namaycush morphs was quantified at six geographically distant locations in Lake Superior (∼30 to 250 km apart), one of the largest freshwater lakes in the world (82,100 km²). Lake trout were sampled using standardized multi-mesh gillnets in three depth strata at six locations in Lake Superior that were known or thought to have multiple morphs. Life-history traits were estimated using length-age analysis of back-calculated growth from sagittal otolith increments. Morphs, assigned using statistical and visual assignment rules, included 122 humpers, 646 leans, 86 redfins, and 1154 siscowets. Density (CPUE) varied 11-fold among morphs, 7-fold among locations, and 3-fold among depths. Morphs seemed to fill the same ecological niche at all locations, because life-history traits related to weight (body condition, buoyancy, mean weight), age, and growth rate varied more among morphs than locations. However, abiotic and biotic variation among locations also seemed to exert control over life-history variation, because life-history traits related to length, maturity, and early life history varied more among locations than morphs. We conclude that lake trout morphs appeared to have a genetic component to their life history that was differentially expressed along environmental gradients.

Representation of subsurface photosynthetically active radiation (PAR) in biophysical models of the Laurentian Great Lakes (LGL) is imperative to their utility as tools for research and management. Here we consolidated measured vertical profiles of subsurface PAR with concurrent water quality (WQ) data from four LGL. We estimated the diffuse attenuation coefficient of PAR (K_d(PAR)) by fitting an exponential function to measured PAR over depth, and evaluated 68 regressions predicting K_d(PAR) as a function of water quality variables (K_d-WQ regressions). We compare four of the top cross-lake calibrated regressions against two published regressions trained on western Lake Erie (WLE) data. Then, as a case study, we demonstrate the utility of our cross-lake calibrated K_d-WQ regressions with a simplified biophysical model of Lake Erie consisting of the Finite Volume Community Ocean Model with submodules for simulating suspended sediment and dissolved organic carbon (FVCOM-SS-DOC). Twenty-five K_d-WQ regressions were identified as candidates for use in biophysical models based on their skill determined via cross-validation. WLE-trained K_d-WQ regressions were less able to simulate K_d(PAR) and PAR in more transparent waters compared to cross-lake calibrated K_d-WQ regressions, which translated to considerable differences in primary production estimates for the central and eastern basins when using WQ data simulated by FVCOM-SS-DOC. A cross-lake calibrated K_d-WQ regression was installed into FVCOM-SS-DOC, which then simulated spatial patterns of suspended sediments and K_d(PAR). These calibrated K_d-WQ regressions can be used in a variety of biophysical models across optically-distinct waters of the LGL to support adaptive management of nutrient inputs and fisheries.

Mysids (Mysis diluviana) and dreissenids (Dreissena polymorpha and mostly D. bugensis) are important invertebrate taxa in the food webs of the Laurentian Great Lakes but there are uncertainties about the seasonal and spatial variability in their stable isotope signatures. We quantified δ¹³C and δ¹⁵N in 304 mysid and 366 dreissenid samples across five spatial ecoregions, varying site depth, and three seasons (spring, summer, and fall) in Lake Ontario in 2012 and 2013. Particulate organic matter (POM) was also collected across site depth and season from the Deep Hole ecoregion for use as an isotopic baseline. Lipid normalization models for δ¹³C were generated for both taxa to reduce lipid bias in our statistical analysis. Season was a significant predictor of POM stable isotopes, with δ¹³C lower in the summer and δ¹⁵N decreasing from spring to summer before increasing into fall. Mysid lipid normalized δ¹³C varied by site depth and ecoregion while δ¹⁵N decreased across season and did not vary by site depth or ecoregion. Dreissenid stable isotopes varied significantly across season, depth, and ecoregion, with site depth having positive relationship with δ¹⁵N. Mysids and dreissenids were two trophic positions higher than POM based on δ¹⁵N; this comparison was restricted to the one region where POM was collected. Isotopic variability suggested selective feeding within POM and differing trophic pathways between mysids and dreissenids. Collecting an appropriate taxon across all observed variables to serve as an isotopic baseline, particularly in spatial and temporal studies, is critical to the correct interpretation of trophic relationships.

Climate change has the potential to impact lacustrine fish populations by affecting both their physiologies and phenologies. Coldwater, stenothermic fishes that spawn in winter may be at the highest risk of being negatively impacted by predicted future climate warming. To investigate this subject, we tested the impact of temperature on the embryonic and larval stages of coldwater, stenothermic salmonid whitefishes (coregonines). Embryos of two coregonine species from Upper Lake Constance (a large, deep perialpine lake bordering Austria, Germany and Switzerland) were incubated at three temperatures approximating historic and potential future water temperatures. After hatching, larvae from all incubation treatments were transferred to two rearing temperature treatments. Hatching times were advanced by higher temperatures, whilst mortality and larval performance responses to higher temperatures were generally negative, suggesting that future climate warming will reduce coregonine recruitment in Upper Lake Constance. The two species tested varied in their specific responses to temperature and in the sensitivity of their responses to temperature. Additionally, we found that incubation temperature affected the performance of coregonine larvae up to two and a half months after hatching. Using our data on hatching times, we infer that future climate change could advance coregonine phenologies in Upper Lake Constance by up to two weeks by the end of the 21st century.