Identifying lakes at risk of toxic cyanobacterial blooms using satellite imagery and field surveys across the United States.

Harmful algal blooms caused by cyanobacteria are a threat to global water resources and human health. Satellite remote sensing has vastly expanded spatial and temporal data on lake cyanobacteria, yet there is still acute need for tools that identify which waterbodies are at-risk for toxic cyanobacterial blooms. Algal toxins cannot be directly detected through imagery but monitoring toxins associated with cyanobacterial blooms is critical for assessing risk to the environment, animals, and people. The objective of this study is to address this need by developing an approach relating satellite imagery on cyanobacteria with field surveys to model the risk of toxic blooms among lakes. The Medium Resolution Imaging Spectrometer (MERIS) and United States (US) National Lakes Assessments are leveraged to model the probability among lakes of exceeding lower and higher demonstration thresholds for microcystin toxin, cyanobacteria, and chlorophyll a. By leveraging the large spatial variation among lakes using two national-scale data sources, rather than focusing on temporal variability, this approach avoids many of the previous challenges in relating satellite imagery to cyanotoxins. For every satellite-derived lake-level Cyanobacteria Index (CI_cyano) increase of 0.01 CI_cyano/km2, the odds of exceeding six bloom thresholds increased by 23-54 %. When the models were applied to the 2192 satellite monitored lakes in the US, the number of lakes identified with ≥75 % probability of exceeding the thresholds included as many as 335 lakes for the lower thresholds and 70 lakes for the higher thresholds, respectively. For microcystin, the models identified 162 and 70 lakes with ≥75 % probability of exceeding the lower (0.2 µg/L) and higher (1.0 µg/L) thresholds, respectively. This approach represents a critical advancement in using satellite imagery and field data to identify lakes at risk for developing toxic cyanobacteria blooms. Such models can help translate satellite data to aid water quality monitoring and management.

Denitrification and DNRA in Urban Accidental Wetlands in Phoenix, Arizona.

Denitrification and dissimilatory nitrate reduction to ammonium (DNRA) both require low oxygen and high organic carbon conditions common in wetland ecosystems. Denitrification permanently removes nitrogen from the ecosystem as a gas while DNRA recycles nitrogen within the ecosystem via production of ammonium. The relative prevalence of denitrification versus DNRA has implications for the fate of nitrate in ecosystems. Unplanned and unmanaged urban accidental wetlands in the Salt River channel near downtown Phoenix, Arizona, USA receive high nitrate relative to non-urban wetlands and have a high capacity for denitrification, but unknown capacity for DNRA. We conducted in-situ push-pull tests with isotopically labelled nitrate to measure denitrification and DNRA rates in three of the dominant vegetative patch types in these urban accidental wetlands. DNRA accounted for between 2 and 40% of nitrate reduction (DNRA plus denitrification) with the highest rates measured in patches of Ludwigia peploides compared to Typha spp. and non-vegetated patches. The wetland patches were similar with respect to dissolved organic carbon concentration but may have differed in carbon lability or strength of reducing conditions due to a combination of litter decomposition and oxygen supply via diffusion and aerenchyma. The ratio of DNRA to denitrification was negatively correlated with nitrate concentration, indicating that DNRA may become a more important pathway for nitrate attenuation at low nitrate concentration. Although DNRA was generally lower than denitrification, this pathway was an important component of nitrate attenuation within certain patches in these unmanaged urban accidental wetlands.