November 2017 - Present
Gaborit, E., V. Fortin, A. Xu, F. Seglenieks, B. Tolson, L.M. Fry, T.S. HUNTER, F. Anctil, and A.D. GRONEWOLD. A Hydrological Prediction System Based on the SVS Land–Surface Scheme: Implementation and Evaluation of the GEM-Hydro platform on the watershed of Lake Ontario. Hydrology and Earth System Sciences (DOI:10.5194/hess-2016-508) (2017). https://www.glerl.noaa.gov/pubs/fulltext/2017/20170027.pdf
This work describes the implementation of the distributed GEM-Hydro runoff modeling platform, developed at Environment and Climate Change Canada (ECCC) over the last decade. The latest version of GEM-Hydro combines the SVS (Soil, Vegetation and Snow) land-surface scheme and the WATROUTE routing scheme in order to provide streamflow predictions on a gridded river network. SVS is designed to be two-way coupled to the GEM (Global Environmental Multi-scale) atmospheric model exploited by ECCC for operational weather and environmental forecasting. Although SVS has been shown to accurately track soil moisture during the warm season, it has never been evaluated before for hydrological prediction. This paper presents a first evaluation of its ability to simulate streamflow for all major rivers flowing into Lake Ontario. The skill level of GEM-Hydro is assessed by comparing the quality of simulated flows to that of two established hydrological models, MESH and WATFLOOD, which share the same routing scheme (WATROUTE) but rely on different land–surface schemes. All models are calibrated using the same meteorological forcings, objective function, calibration algorithm, and watershed delineation. Results show that GEM-Hydro performs well and is competitive with MESH and WATFLOOD. A computationally efficient strategy is proposed to calibrate the land-surface model of GEM-Hydro: a simple unit hydrograph is used for routing instead of its standard distributed routing component. The distributed routing part of the model can then be run in a second step to estimate streamflow everywhere inside the domain. Global and local calibration strategies are compared in order to estimate runoff for ungauged portions of the Lake Ontario watershed. Overall, streamflow predictions obtained using a global calibration strategy, in which a single parameter set is identified for the whole watershed of Lake Ontario, show skills comparable to the predictions based on local calibration. Hence, global calibration provides spatially consistent parameter values, robust performance at gauged locations, and reduces the complexity and computational burden of the calibration procedure. This work contributes to the Great Lakes Runoff Inter-comparison Project for Lake Ontario (GRIP-O) which aims at improving Lake Ontario basin runoff simulations by comparing different models using the same input forcings.
MANOME, A.F., L.E. FITZPATRICK, A.D. GRONEWOLD, E.J. ANDERSON, B.M. LOFGREN, C. Spence, J. Chen, C. Shao, D.M. Wright, and C. XIAO. Turbulent Heat Fluxes during an Extreme Lake Effect Snow Event. Journal of Hydrometeorology (DOI:10.1175/JHM-D-17-0062.1) (2017). https://www.glerl.noaa.gov/pubs/fulltext/2017/20170031.pdf (IN PRESS)
Proper modeling of the turbulent heat fluxes over lakes is critical for accurate predictions of lake-effect snowfall (LES). However, model evaluation of such a process has not been possible due to the lack of direct flux measurements over lakes. We conducted the first-ever comparison of the turbulent latent and sensible heat fluxes between state-of-the-art numerical models and direct flux measurements over Lake Erie, with a focus on a record LES event in southwest New York in November 2014. The model suite consisted of numerical models that were operationally and experimentally used to provide nowcasts and forecasts of weather and lake conditions. The models captured the rise of the observed turbulent heat fluxes, while the peak values varied significantly. This variation resulted in increased spread of simulated lake temperature and cumulative evaporation as the representation of the model uncertainty. The water budget analysis of atmospheric model results showed that a majority of the moisture during this event came from lake evaporation rather than a larger synoptic system. The unstructured-grid Finite Volume Community Ocean Model (FVCOM) simulations, especially those using the Coupled Ocean-Atmosphere Response Experiment (COARE)-Met Flux algorithm, presented better agreement with the observed fluxes, likely due to the model’s capability in representing the detailed spatial patterns of the turbulent heat fluxes and the COARE algorithm’s more realistic treatment of the surface boundary layer than those in the other models.
Meyer, K.A., T.W. DAVIS, S.B. Watson, V.J. Denef, M.A. Berry, and G.J. Dick. Genome sequences of lower Great Lakes Microcystis sp. reveal strain-specific genes that are present and expressed in western Lake Erie blooms. PLoS One (DOI:10.1371/journal.pone.0183859) (2017). https://www.glerl.noaa.gov/pubs/fulltext/2017/20170032.pdf
Blooms of the potentially toxic cyanobacterium Microcystis are increasing worldwide. In the Laurentian Great Lakes they pose major socioeconomic, ecological, and human health threats, particularly in western Lake Erie. However, the interpretation of “omics” data is constrained by the highly variable genome of Microcystis and the small number of reference genome sequences from strains isolated from the Great Lakes. To address this, we sequenced two Microcystis isolates from Lake Erie (Microcystis aeruginosa LE3 and M. wesenbergii LE013-01) and one from upstream Lake St. Clair (M. cf aeruginosa LSC13-02), and compared these data to the genomes of seventeen Microcystis spp. from across the globe as well as one metagenome and seven metatranscriptomes from a 2014 Lake Erie Microcystis bloom. For the publically available strains analyzed, the core genome is ~1900 genes, representing ~11% of total genes in the pan-genome and ~45% of each strain’s genome. The flexible genome content was related to Microcystis subclades defined by phylogenetic analysis of both housekeeping genes and total core genes. To our knowledge this is the first evidence that the flexible genome is linked to the core genome of the Microcystis species complex. The majority of strain-specific genes were present and expressed in bloom communities in Lake Erie. Roughly 8% of these genes from the lower Great Lakes are involved in genome plasticity (rapid gain, loss, or rearrangement of genes) and resistance to foreign genetic elements (such as CRISPR-Cas systems). Intriguingly, strain-specific genes from Microcystis cultured from around the world were also present and expressed in the Lake Erie blooms, suggesting that the Microcystis pangenome is truly global. The presence and expression of flexible genes, including strain-specific genes, suggests that strain-level genomic diversity may be important in maintaining Microcystis abundance during bloom events.
Props, R., M.L. Schmidt, J. Heyse, H.A. VANDERPLOEG, N. Boon, and V.J. Denef. Flow cytometric monitoring of bacterioplankton phenotypic diversity predicts high population-specific feeding rates by invasive dreissenid mussels. Environmental Microbiology (DOI:10.1111/1462-2920.13953) (2017). https://www.glerl.noaa.gov/pubs/fulltext/2017/20170034.pdf (IN PRESS)
Species invasion is an important disturbance to ecosystems worldwide, yet knowledge about the impacts of invasive species on bacterial communities remains sparse. Using a novel approach, we simultaneously detected phenotypic and derived taxonomic change in a natural bacterioplankton community when subjected to feeding pressure by quagga mussels, a widespread aquatic invasive species. We detected a significant decrease in diversity within 1 h of feeding and a total diversity loss of 11.6 ± 4.1% after 3 h. This loss of microbial diversity was caused by the selective removal of high nucleic acid populations (29 ± 5% after 3 h). We were able to track the community diversity at high temporal resolution by calculating phenotypic diversity estimates from flow cytometry (FCM) data of minute amounts of sample. Through parallel FCM and 16S rRNA gene amplicon sequencing analysis of environments spanning a broad diversity range, we showed that the two approaches resulted in highly correlated diversity measures and captured the same seasonal and lake-specific patterns in community composition. Based on our results, we predict that selective feeding by invasive dreissenid mussels directly impacts the microbial component of the carbon cycle, as it may drive bacterioplankton communities toward less diverse and potentially less productive states.
Soranno, P.A., (among 23 others), and C.A. STOW. A multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of U.S. lakes. GigaScience (DOI:10.1093/gigascience/gix101) (2017). https://www.glerl.noaa.gov/pubs/fulltext/2017/20170033.pdf (In Press)
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