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This study utilizes satellite data to investigate water quality conditions in the San Francisco Estuary and its upstream delta, the Sacramento-San Joaquin River Delta. To do this, this study derives turbidity from the European Space Agency satellite Sentinel-2 acquired from September 2015 to June 2019 and conducts a rigorous validation with in situ measurements of turbidity from optical sensors at continuous monitoring stations. This validation includes 965 matchup comparisons between satellite and in situ sensor data across 22 stations, yielding R 2 = 0.63 and 0.75 for Nephelometric Turbidity Unit and Formazin Nephelometric Unit (FNU) stations, respectively. This study then applies remote sensing to evaluate patterns in turbidity during the Suisun Marsh Salinity Control Gates Action ("Gates action"), a pilot study designed to increase habitat access and quality for the endangered Delta Smelt. The basic strategy was to direct more freshwater into Suisun Marsh, creating more low salinity habitat that would then have higher (and more suitable) turbidity than upstream river channels. For all seven acquisitions considered from June 29 to September 27, 2018, turbidity conditions in Bays and Sloughs subregions were consistently higher (and more suitable) (26-47 FNU) than what was observed in the upstream River region (13-25 FNU). This overall pattern was observed when comparing images acquired during similar tidal stages and heights.

Field studies were conducted in 2016 and 2017 in Clinton, NC, to determine the interspecific and intraspecific interference of Palmer amaranth (Amaranthus palmeri S. Watson) or large crabgrass [Digitaria sanguinalis (L.) Scop.] in ‘Covington’ sweetpotato [Ipomoea batatas (L.) Lam.]. Amaranthus palmeri and D. sanguinalis were established 1 d after sweetpotato transplanting and maintained season-long at 0, 1, 2, 4, 8 and 0, 1, 2, 4, 16 plants m⁻¹ of row in the presence and absence of sweetpotato, respectively. Predicted yield loss for sweetpotato was 35% to 76% for D. sanguinalis at 1 to 16 plants m⁻¹ of row and 50% to 79% for A. palmeri at 1 to 8 plants m⁻¹ of row. Weed dry biomass per meter of row increased linearly with increasing weed density. Individual dry biomass of A. palmeri and D. sanguinalis was not affected by weed density when grown in the presence of sweetpotato. When grown without sweetpotato, individual weed dry biomass decreased 71% and 62% from 1 to 4 plants m⁻¹ row for A. palmeri and D. sanguinalis, respectively. Individual weed dry biomass was not affected above 4 plants m⁻¹ row to the highest densities of 8 and 16 plants m⁻¹ row for A. palmeri and D. sanguinalis, respectively.

Processes of spread and patterns of persistence of invasive species affect species and communities in the new environment. Predicting future rates of spread is of great interest for timely management decisions, but this depends on models that rely on understanding the processes of invasion and historic observations of spread and persistence. Unfortunately, the rates of spread and patterns of persistence are difficult to model or directly observe, especially when multiple rates of spread and diverse persistence patterns may be co-occurring over the geographic distribution of the invaded ecosystem. Remote sensing systematically acquires data over large areas at fine spatial and spectral resolutions over multiple time periods that can be used to quantify spread processes and persistence patterns. We used airborne imaging spectroscopy data acquired once a year for 5 years from 2004 to 2008 to map an invaded submerged aquatic vegetation (SAV) community across 2220 km2 of waterways in the Sacramento-San Joaquin River Delta, California, USA, and measured its spread rate and its persistence. Submerged aquatic vegetation covered 13-23 km2 of the waterways (6-11%) every year. Yearly new growth accounted for 40-60% of the SAV area, ~50% of which survived to following year. Spread rates were overall negative and persistence decreased with time. From this dataset, we were able to identify both radial and saltatorial spread of the invaded SAV in the entire extent of the Delta over time. With both decreasing spread rate and persistence, it is possible that over time the invasion of this SAV community could decrease its ecological impact. A landscape-scale approach allows measurements of all invasion fronts and the spatial anisotropies associated with spread processes and persistence patterns, without spatial interpolation, at locations both proximate and distant to the focus of invasion at multiple points in time.

Cyanobacterial harmful algal blooms (cyanoHABs) can harm people, animals, and affect consumptive and recreational use of inland waters. Monitoring cyanoHABs is often limited. However, chlorophyll‐a (chl‐a) is a common water quality metric and has been shown to have a relationship with cyanobacteria. The World Health Organization (WHO) recently updated their previous 1999 cyanoHAB guidance values (GVs) to be more practical by basing the GVs on chl‐a concentration rather than cyanobacterial counts. This creates an opportunity for widespread cyanoHAB monitoring based on chl‐a proxies, with satellite remote sensing (SRS) being a potentially powerful tool. We used Sentinel‐2 (S2) and Sentinel‐3 (S3) to map chl‐a and cyanobacteria, respectively, classified chl‐a values according to WHO GVs, and then compared them to cyanotoxin advisories issued by the California Department of Water Resources (DWR) at San Luis Reservoir, key infrastructure in California's water system. We found reasonably high rates of total agreement between advisories by DWR and SRS, however rates of agreement varied for S2 based on algorithm. Total agreement was 83% for S3, and 52%–79% for S2. False positive and false negative rates for S3 were 12% and 23%, respectively. S2 had 12%–80% false positive rate and 0%–38% false negative rate, depending on algorithm. Using SRS‐based chl‐a GVs as an early indicator for possible exposure advisories and as a trigger for in situ sampling may be effective to improve public health warnings. Implementing SRS for cyanoHAB monitoring could fill temporal data gaps and provide greater spatial information not available from in situ measurements alone. Plain Language Summary: Lakes often have algal blooms that create a water quality concern, especially when they contain cyanobacteria, which can be toxic to both humans and animals. These harmful algal blooms are of great concern in areas with limited water supply in states such as California. While it is often difficult and costly to collect and monitor toxin concentrations, monitoring concentrations of chlorophyll‐a (chl‐a) –a measure of how much algae are present—is relatively common and can even be accomplished using satellite remote sensing. There have been multiple studies that have found a relationship between toxins produced by cyanobacteria and chl‐a. The World Health Organization (WHO) has recently released (2021) an updated release of their previous 1999 guidance values for toxin monitoring based on chl‐a concentration. With satellite data, we were able to measure chl‐a concentration in a major reservoir in California, and then classify the chl‐a measurements into the WHO's guidance values for toxins. We compared the satellite‐based guidance values to the public advisory levels currently set by the California Department of Water Resources. Our results indicate that SRS of chl‐a is a reasonable substitute for cyanobacteria toxin advisories, and our framework can be applied to similar cyanobacteria dominated lakes. Key Points: The World Health Organization (WHO) updated cyanobacteria harmful algal blooms (cyanoHABs) guidelines for chlorophyll‐a (chl‐a) as a proxyWith satellite remote sensing (SRS), we estimated and classified chl‐a to compare cyanotoxins advisories used by CaliforniaThis study provides a framework for evaluating public health utility of SRS for enhancing cyanotoxin monitoring globally [ABSTRACT FROM AUTHOR]

Summary [ABSTRACT FROM AUTHOR]