Hexbyte Glen Cove Big data-derived tool facilitates closer monitoring of recovery from natural disasters thumbnail

Hexbyte Glen Cove Big data-derived tool facilitates closer monitoring of recovery from natural disasters

Hexbyte Glen Cove

Credit: CC0 Public Domain

By analyzing peoples’ visitation patterns to essential establishments like pharmacies, religious centers and grocery stores during Hurricane Harvey, researchers at Texas A&M University have developed a framework to assess the recovery of communities after natural disasters in near real time. They said the information gleaned from their analysis would help federal agencies allocate resources equitably among communities ailing from a disaster.

“Neighboring communities can be impacted very differently after a natural catastrophic event,” said Dr. Ali Mostafavi, associate professor in the Zachry Department of Civil and Environmental Engineering and director of the Urban Resilience.AI Lab. “And so, we need to identify which areas can recover faster than others and which areas are impacted more than others so that we can allocate more resources to areas that need them more.”

The researchers have reported their findings in the Journal of The Royal Society Interface.

The metric that is conventionally used to quantify how communities bounce back from nature-caused setbacks is called resilience and is defined as the ability of a community to return to its pre-disaster state. And so, to measure resilience, factors like the accessibility and distribution of resources, connection between residents within a community and the level of community preparedness for an unforeseen disaster are critical.

The standard way of obtaining data needed to estimate resilience is through surveys. The questions considered, among many others, are how and to what extent businesses or households were affected by the natural disaster and the stage of recovery. However, Mostafavi said these survey-based methods, although extremely useful, take a long time to conduct, with the results of the survey becoming available many months after the disaster.

“For allocating funds, recovery information is actually needed in a faster and more near real-time fashion for communities that are trailing in the recovery process,” said Mostafavi. “The solution, we thought, was to look for emerging sources of data other than surveys that could provide more granular insights into community recovery at a scale not previously investigated.”

Mostafavi and his collaborators turned to community-level , particularly the information collected by companies that keep track of visits to locations within a perimeter from anonymized cell phone data. In particular, the researchers partnered with a company called SafeGraph to obtain location data for the people in Harris County, Texas, around the time of Hurricane Harvey. As a first step, they determined “points of interest” corresponding to the locations of establishments, like hospitals, gas stations and stores, that might experience a change in visitor traffic due to the hurricane.

Next, the researchers mined the big data and obtained the number of visits to each point of interest before and during the hurricane. For different communities in Harris County, they calculated the time taken for the visits to return to the pre-disaster level and the general resilience, that is, the combined resilience of each point of interest based on the percent change in the number of visits due to the hurricane.

Their analysis revealed that communities that had low resilience also experienced more flooding. However, their results also showed that the level of impact did not necessarily correlate with recovery.

“It’s intuitive to assume, for example, that businesses impacted more will have slower recovery, which actually wasn’t the case,” said Mostafavi. “There were places where visits dropped significantly, but they recovered fast. But then others that were impacted less but took longer to recover, which indicated the importance of both time and general in evaluating a community’s recovery.”

The researchers also noted that another important finding was that the areas that are in close proximity to those that had flooding are also impacted, suggesting that the spatial reach of flooding goes beyond flooded areas.

“Although we focused on Hurricane Harvey for this study, our framework is applicable for any other natural disaster as well,” said Mostafavi. “But as a next step, we’d like to create an intelligent dashboard that would display the rate of recovery and impacts in different areas in near real time and also predict the likelihood of future access disruption and patterns after a heavy downpour.”

More information:
Cristian Podesta et al, Quantifying community resilience based on fluctuations in visits to points-of-interest derived from digital trace data, Journal of The Royal Society Interface (2021). DOI: 10.1098/rsif.2021.0158

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Hexbyte Glen Cove 'Animal-stress' signal improves plant drought resilience thumbnail

Hexbyte Glen Cove ‘Animal-stress’ signal improves plant drought resilience

Hexbyte Glen Cove

Credit: Pixabay/CC0 Public Domain

A team of Australian and German researchers has discovered a novel pathway that plants can use to save water and improve their drought tolerance.

The research published today in Nature Communications shows that the molecule GABA (gamma-aminobutyric acid), most commonly associated with relaxation in animals, can control the size of the pores on to minimise .

Matthew Gilliham, Director of the Waite Research Institute at the University of Adelaide, who led the research team, said they found: “GABA minimised openings in a range of crops such as barley, broad bean and soybean, and in lab that produce more GABA than normal. This led to the lab plants using less water from the soil and surviving longer in the drought experiments.”

“We found plants that produce lots of GABA reduce how much their pores open, thereby taking a smaller breath and reducing water loss.”

In an earlier study, members of the team found that GABA—known as a nerve signal in animals—could act as plant GABA receptors. This led to renewed speculation that GABA could be a signal in plants as well as in animals.

Lead author on the study, Dr. Bo Xu, a Postdoctoral Researcher at the Australian Research Council (ARC) Centre of Excellence in Plant Energy Biology adds: “Both plants and animals produce GABA and they put it to different uses. Plants don’t have nerves, instead they appear to use GABA to match their energy levels with their response to the environment.”

“GABA doesn’t close pores on leaves like other stress signals, it acts in a different way—how much a plant accumulates GABA when it is stressed determines how much it applies the brake pedal to reduce the pore opening the following morning, and water loss that day—like a stress memory of the day before.”

During drought, the signalling molecule GABA is produced and inhibits the opening of leaf pores (left). If the enzyme GAD2, which converts glutamate to GABA, is genetically switched off, the pores remain open even during drought – the plants lose more water (centre). If the gene for GAD2 is reintroduced into the closing cells, the defect is reversed. The experiment shows that the sphincter cells autonomously perceive stress and react to it with GABA production. Credit: Rainer Hedrich / University of Wuerzburg

Professor Rainer Hedrich at the University of Würzburg, a pioneer in studying how plants regulate loss, led the German component of the study.

“I’ve been studying how plants regulate their stomatal pores for over 35 years. To find a completely new and unexpected way that they are regulated has certainly been one of our most surprising discoveries. I look forward to seeing how this translates out in the field.”

The team recently received a new grant from the Australian Federal Government to partner with researchers at the University of Cambridge, UK, and are looking for new Ph.D. students to join the team to discover new components of the signalling pathway and to trial its impact in crops.

More information:
Nature Communications (2021). DOI: 10.1038/s41467-021-21694-3

‘Animal-stress’ signal improves plant drought resilience (2021, March 29)
retrieved 29 March 2021
from https://phys.org/news/2021-03-animal-stress-drought-resilience.html

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