Spatio-temporal connectivity of the aquatic microbiome associated with cyanobacterial blooms along a Great Lake riverine-lacustrine continuum.

Lake Erie is subject to recurring events of cyanobacterial harmful algal blooms (cHABs), but measures of nutrients and total phytoplankton biomass seem to be poor predictors of cHABs when taken individually. A more integrated approach at the watershed scale may improve our understanding of the conditions that lead to bloom formation, such as assessing the physico-chemical and biological factors that influence the lake microbial community, as well as identifying the linkages between Lake Erie and the surrounding watershed. Within the scope of the Government of Canada's Genomics Research and Development Initiative (GRDI) Ecobiomics project, we used high-throughput sequencing of the 16S rRNA gene to characterize the spatio-temporal variability of the aquatic microbiome in the Thames River-Lake St.

Ecological models for estimating breakpoints and prediction intervals.

The relationships between an environmental variable and an ecological response are usually estimated by models fitted through the conditional mean of the response given environmental stress. For example, nonparametric loess and parametric piecewise linear regression model (PLRM) are often used to represent simple to complex nonlinear relationships. In contrast, piecewise linear quantile regression models (PQRM) fitted across various quantiles of the response can reveal nonlinearities in its range of variation across the explanatory variable.

Characterization of sedimentary phosphorus in Lake Erie and on-site quantification of internal phosphorus loading.

Lake Erie harmful algal blooms and hypoxia are two major environmental problems, and have severe impacts on human health, aquatic ecosystems, and the economy. However, little is known about internal loading of phosphorus (P) from sediments, which pose a challenge for assessing the efficacy of current conservation measures on the improvement of lake water quality. A modified Hedley's extraction procedure was employed to analyze representative sediment samples collected from the Lake Erie basin for assessing sedimentary P stock, potential availability for release into lake water, and internal P loading.

Leveraging a Landscape-Level Monitoring and Assessment Program for Developing Resilient Shorelines throughout the Laurentian Great Lakes.

Traditionally, ecosystem monitoring, conservation, and restoration have been conducted in a piecemeal manner at the local scale without regional landscape context. However, scientifically driven conservation and restoration decisions benefit greatly when they are based on regionally determined benchmarks and goals. Unfortunately, required data sets rarely exist for regionally important ecosystems.

An expanded fish-based index of biotic integrity for Great Lakes coastal wetlands.

Biotic indicators are useful for assessing ecosystem health because the structure of resident communities generally reflects abiotic conditions integrated over time. We used fish data collected over 5 years for 470 Great Lakes coastal wetlands to develop multi-metric indices of biotic integrity (IBI). Sampling and IBI development were stratified by vegetation type within each wetland to account for differences in physical habitat.