Forest Loss is Accelerating Along the US Gulf Coast.

Sea-level rise is impacting the longest undeveloped stretch of coastline in the contiguous United States: The Florida Big Bend. Due to its low elevation and a higher-than-global-average local rate of sea-level rise, the region is losing coastal forest to encroaching marsh at an unprecedented rate. Previous research found a rate of forest-to-marsh conversion of up to 1.

Satellite Remote Sensing for Coastal Management: A Review of Successful Applications.

Management of coastal and marine natural resources presents a number of challenges as a growing global population and a changing climate require us to find better strategies to conserve the resources on which our health, economy, and overall well-being depend. To evaluate the status and trends in changing coastal resources over larger areas, managers in government agencies and private stakeholders around the world have increasingly turned to remote sensing technologies. A surge in collaborative and innovative efforts between resource managers, academic researchers, and industry partners is becoming increasingly vital to keep pace with evolving changes of our natural resources.

A heat vulnerability index to improve urban public health management in San Juan, Puerto Rico.

Increased frequency and length of high heat episodes are leading to more cardiovascular issues and asthmatic responses among the population of San Juan, the capital of the island of Puerto Rico, USA. An urban heat island effect, which leads to foci of higher temperatures in some urban areas, can raise heat-related mortality. The objective of this research is to map the risk of high temperature in particular locations by creating heat maps of the city of San Juan.

Assessing climate variability effects on dengue incidence in San Juan, Puerto Rico.

We test the hypothesis that climate and environmental conditions are becoming favorable for dengue transmission in San Juan, Puerto Rico. Sea Level Pressure (SLP), Mean Sea Level (MSL), Wind, Sea Surface Temperature (SST), Air Surface Temperature (AST), Rainfall, and confirmed dengue cases were analyzed. We evaluated the dengue incidence and environmental data with Principal Component Analysis, Pearson correlation coefficient, Mann-Kendall trend test and logistic regressions.