From Wisconsin to Washington D.C., pollen counts were quite high this spring, making seasonal allergies brutal for many people. Recent research shows that changes in the onset of spring—both early and late—can extend allergy misery and lead to more severe asthma for some people.
Warm springtime temperatures signal shrub buds to burst, trees to leaf-out, and flowers to bloom. As plants produce and release pollen, our bodies can mistakenly identify it as a dangerous intruder to our respiratory systems. Our immune systems produce chemicals to fight it, inducing sneezing, watery eyes, and stuffy noses. Research also shows allergenic pollen is also among the leading risk factors known to worsen asthma.
Amir Sapkota, a professor of public health at the University of Maryland, and his colleagues investigated how changes in the timing of spring onset affected asthma hospitalizations in Maryland over the past decade. The team used the Normalized Difference Vegetation Index (NDVI), which shows the relative “greenness” of vegetation, to determine the timing of the spring onset. (The data come from the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Aqua and Terra satellites.) The team combined the satellite data with pollen counts and inpatient hospital admissions from the Maryland Department of Health.
They found that very early onset of spring (10 days early) was associated with a 17 percent increase in asthma hospitalizations in Maryland from 2001-2012, while late onset (3 days later) was associated with a 7 percent increase.
Sapkota explained that the hospitalization risk increased because of changes in pollen dynamics. Tree pollen is common in spring, while grass and weed pollen are more common during summer and fall. According to Sapkota, an early onset of spring leads to earlier and longer tree pollen seasons. At the other end, late onset causes different species of trees to bloom at the same time, thus increasing overall pollen levels in the environment. Both scenarios can lead to increases in asthma hospitalizations.
Under normal conditions, water quality tests find, at most, a few hundred K. brevis cells per liter of water—not enough to cause problems. But in August 2018, in the midst of one of the most severe red tide outbreaks to hit Florida’s Gulf Coast in a decade, water samples regularly contained more than one million K. brevis cells per liter.
That was enough to stain large swaths of coastal waters shades of green and brownish-red and leave beaches littered with rotting fish carcasses. Roughly 100 manatees, more than 200 sea turtles, and at least 12 dolphins have been killled by red tides, according to preliminary estimates. For much of August, the toxic bloom stretched about 130 miles (200 kilometers) along Florida’s Gulf coast, from roughly Tampa to Fort Myers. Though the bloom has been active since October 2017, it intensified rapidly in July 2018. The damage grew so severe and widespread that Florida’s governor declared a state of emergency in mid-August.
One of the best ways to test for the presence of K. brevis is to analyze water samples collected from boats or beaches. State environmental agencies do this on a regular basis, but understanding the full extent and evolution of fast-changing blooms, or predicting where they will move with ground sampling alone is a challenge.
Sampling red tide in 2018 (left). An aerial view of red tide in 2005 (right). Photo credits: Florida Fish and Wildlife Conservation Commission.
A screenshot from the University of South Florida’s Near Real-Time Integrated Red tide Information System (IRIS). The image shows various types of data captured by MODIS sensor on Terra on August 19, 2018. Solar-stimulated fluorescence data (NFLH) is particularly useful for locating algal blooms. Image Credit: USF/IRIS
Despite the utility of satellite observations, there are some significant challenges to interpreting satellite data of algal blooms in shallow, coastal waters, explained oceanographer Chuanmin Hu of the University of South Florida. Chief among them: it can be quite difficult to distinguish between algal blooms, suspended sediment, and colored dissolved organic matter (CDOM) that flows into coastal areas.
The Karenia brevis bloom expanded and intensified in late-July. This fluorescence data comes from the OCLI sensor on Sentinel 3. Image courtesy of Rick Stumpf, NOAA.
To get around this problem and make satellites better at pinpointing algal blooms, Hu and colleagues at the University of South Florida have developed a red tide monitoring system that makes use of MODIS observations of fluorescence, which algal bloom emit in response to exposure to sunlight. “If we have fluorescence data to go along with a natural-color image from MODIS, we can say with a high degree of confidence where the algal blooms are and where the sensor is just detecting sediment or CDOM,” he said. When fluorescence data is available, the Florida Fish and Wildlife Commission pushes it out to the public as part of its red tide status updates (see the August 21 update below).
Likewise, NOAA has combined a fluorescence method with a long-standing technique that identifies recent increases in chlorophyll concentration, the combination improves the identification of likely K. brevis blooms — information that then gets incorporated in NOAA’s HAB Forecast System, noted Richard Stumpf, an oceanographer with NOAA.
K. brevis cell abundance shown on an ocean color satellite image from the IRIS system. Warmer colors indicate higher levels of chlorophyll a, an indicator of algae. Cloudy areas are gray. Circles indicate locations where officials tested water samples on the ground. Image Credit: FFW/USF/IRIS.
However, that still leaves some big problems—only about ten percent of MODIS passes collect usable fluorescence data. The rest of the time images are marred by either sunglint or clouds. And the algorithm that scientists use to detect algal blooms with MODIS does not work well within one kilometer of the coast—the part that is of the greatest interest to beachgoers and boaters.
After recording, HABscope uploads videos to a cloud-based server for automatic analysis by computer software. The software rapidly counts the number of K. brevis cells in a water sample by using technology similar to that found in facial recognition apps. But rather than focusing on facial features, the software looks for a particular pattern in the movement of K. brevis cells.
K. brevis are vigorous swimmers, often using a pair of long, whip-like flagella to migrate vertically about 10 to 20 meters (33 to 66 feet) each day. They chart a zig-zagging, corkscrew-shaped path that allows the software to easily pick them out amidst the cast of other phytoplankton found in Gulf of Mexico water samples.
The data about K. brevis abundance at various locations along the coast is then fed into a respiratory distress forecasting tool managed by NOAA. “Respiratory distress forecasts can now be produced 1 to 2 times per day for specific beaches along the Florida Gulf Coast,” said Stumpf. “Previous to this project, these forecasts were issued at most twice a week, and only as general statements about risk within a county. The combination of earth observations with rapid field monitoring will increase the accuracy and usefulness of the forecasts.”
The research team that developed the HABscope app included oceanographers, ecologists, computer application developers, and public health experts. Photo Credit: Mote Marine Laboratory.