Coral reefs are among the most biologically diverse ecosystems on Earth. In the last few decades, a combination of stressors has produced significant declines in reef expanse, with declining reef health attributed largely to thermal stresses. We investigated the correspondence between time-series satellite remote sensing-based sea surface temperature (SST) datasets and ocean temperature monitored in situ at depth in coral reefs near La Parguera, Puerto Rico. In situ temperature data were collected for Cayo Enrique and Cayo Mario, San Cristobal, and Margarita Reef. The three satellite-based SST datasets evaluated were NOAA’s Coral Reef Watch (CoralTemp), the UK Meteorological Office’s Operational SST and Sea Ice Analysis (OSTIA), and NASA’s Jet Propulsion Laboratory (G1SST). All three satellite-based SST datasets assessed displayed a strong positive correlation (>0.91) with the in situ temperature measurements. However, all SST datasets underestimated the temperature, compared with the in situ measurements. A linear regression model using the SST datasets as the predictor for the in situ measurements produced an overall offset of ~1 °C for all three SST datasets. These results support the use of all three SST datasets, after offset correction, to represent the temperature regime at the depth of the corals in La Parguera, Puerto Rico.
The role of elevated sea temperatures in coral bleaching has been well documented. Many of the sea temperature records utilized for purposes of widespread, multi-species bleaching predictions in recent publications have been acquired through satellite remote sensing. Satellites estimate sea temperatures at only a narrow range of depths near the surface of the ocean and may therefore not adequately represent the true temperatures endured by the world's coral ecosystems. To better characterize sea temperature regimes that coral reef ecosystems experience, as well as better define the individual thresholds for each species that bleaches, in situ sea temperature sensors are required. Commercial sensors are expensive in large quantities, however, reducing the capacity to conduct large- scale research programs to elucidate the range of significant scales of temperature variability. At the National Oceanic and Atmospheric Administration's (NOAA) Atlantic Oceanographic and Meteorological Laboratory (AOML), we designed a low-cost (roughly US$9 in parts) and high- precision sea temperature sensor that uses an Arduino microprocessor board and a high accuracy thermistor. This new temperature sensor autonomously records temperatures onto a memory chip and provides better accuracy (+0.05 °C) than a comparable commercial sensor (+0.2 °C). Moreover, it is not difficult to build; anyone who knows how to solder can build the temperature sensor. In March 2019, students at middle and high schools in Broward County, Florida, built close to 60 temperature sensors. During 2019, these sensors will be deployed by Reef Check, a global-scale coral reef monitoring organization, as well as by other programs to determine worldwide sea temperature regimes through the Opuhala Project (https://www. coral. noaa. gov/opuhala). This paper chronicles results from the initial proof-of-concept deployments for these AOML-designed sensors.
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