Microorganisms in the water surrounding coral reefs provide valuable insights on the health state of reefs and surrounding ocean.

Sampling and analyzing reef water microbes can be done in a variety of ways ranging in cost and complexity, adding to their usability.

As many coral reefs experience prolonged bleaching due to heat stress, rising temperatures due to climate change, and other anthropogenic activities, having more accessible monitoring tools can improve coral conservation efforts.

The authors believe that microbe diagnostic techniques can be easily adopted by established organizations to bolster reef monitoring programs and add to a global database of knowledge about coral reef habitats that can inform policy decisions.

New York University scientists are using artificial intelligence to determine which genes collectively govern nitrogen use efficiency in plants such as corn, with the goal of helping farmers improve their crop yields and minimize the cost of nitrogen fertilizers.

Traditional methods of assessing damage after a disaster can take weeks or even months, delaying emergency response, insurance claims and long-term rebuilding efforts. New research from Texas A&M University might change that. Led by Dr. Maria Koliou, associate professor and Zachry Career Development Professor II in the Zachry Department of Civil and Environmental Engineering at Texas A&M, researchers have developed a new method that combines remote sensing, deep learning and restoration models to speed up building damage assessments and predict recovery times after a tornado. Once post-event images are available, the model can produce damage assessments and recovery forecasts in less than an hour.

Mississippi State Professor of Physics Dipangkar Dutta is a principal investigator on a groundbreaking experiment—revealing “symmetry” in physics doesn’t always behave as scientists once believed—recently published in the prestigious journal Physics Letters B.