i
Satellite SST-Based Coral Disease Outbreak Predictions for the Hawaiian Archipelago
-
2016
Source: Remote Sens. 8(2), 1-15
[PDF-1.23 MB]
Details:
-
Journal Title:Remote Sensing
-
Personal Author:
-
NOAA Program & Office:
-
Description:Predicting wildlife disease risk is essential for effective monitoring and management, especially for geographically expansive ecosystems such as coral reefs in the Hawaiian archipelago. Warming ocean temperature has increased coral disease outbreaks contributing to declines in coral cover worldwide. In this study we investigated seasonal effects of thermal stress on the prevalence of the three most widespread coral diseases in Hawai’i: Montipora white syndrome, Porites growth anomalies and Porites tissue loss syndrome. To predict outbreak likelihood we compared disease prevalence from surveys conducted between 2004 and 2015 from 18 Hawaiian Islands and atolls with biotic (e.g., coral density) and abiotic (satellite-derived sea surface temperature metrics) variables using boosted regression trees. To date, the only coral disease forecast models available were developed for Acropora white syndrome on the Great Barrier Reef (GBR). Given the complexities of disease etiology, differences in host demography and environmental conditions across reef regions, it is important to refine and adapt such models for different diseases and geographic regions of interest. Similar to the Acropora white syndrome models, anomalously warm conditions were important for predicting Montipora white syndrome, possibly due to a relationship between thermal stress and a compromised host immune system. However, coral density and winter conditions were the most important predictors of all three coral diseases in this study, enabling development of a forecasting system that can predict regions of elevated disease risk up to six months before an expected outbreak. Our research indicates satellite-derived systems for forecasting disease outbreaks can be appropriately adapted from the GBR tools and applied for a variety of diseases in a new region. These models can be used to enhance management capacity to prepare for and respond to emerging coral diseases throughout Hawai’i and can be modified for other diseases and regions around the world.
-
Keywords:
-
Source:Remote Sens. 8(2), 1-15
-
Pubmed Central ID:PMC5651227
-
Document Type:
-
Place as Subject:
-
Rights Information:CC BY
-
Compliance:PMC
-
Main Document Checksum:urn:sha256:66f90b2b477ed34d3965effe423bd21ae15b10a6a9dc47d9f99b7414d7d2c37c
-
File Type:
Supporting Files
-
No Additional Files
More +
Related Documents
-
Personal Author:Becker, Elizabeth ;Forney, Karin...2016 | Remote Sens. 8(2), 1-26Description:Species distribution models are now widely used in conservation and management to predict suitable habitat for protected marine species. The primary s...2016 | Remote Sens. 8(1), 1-20Description:Moderate Resolution Imaging Spectroradiometers (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) radiometers, flown onboard Terra/Aqua and...Personal Author:Obata, Kenta ;Miura, Tomoaki...2016 | Remote Sens. 8(1), 1-17Description:In this study, the Visible Infrared Imaging Radiometer Suite (VIIRS) Enhanced Vegetation Index (EVI) was spectrally cross-calibrated with the Moderate...Personal Author:Heidinger, Andrew ;Foster, Michael...2016 | Remote Sens. 8(6), 1-18Description:An important component of the AVHRR PATMOS-x climate date record (CDR)—or any satellite cloud climatology—is the performance of its cloud detectio...Personal Author:Liang, Xingming ;Ignatov, Alexander...2016 | Remote Sens. 8(3), 1-13Description:Clear-sky brightness temperatures (BT) in five bands of the Advanced Himawari Imager (AHI; flown onboard Himawari-8 satellite) centered at 3.9, 8.6, 1...Personal Author:Claverie, Martin ;Matthews, Jessica...2016 | Remote Sens. 8(3), 1-12Description:In-land surface models, which are used to evaluate the role of vegetation in the context of global climate change and variability, LAI and FAPAR play ...Personal Author:Ignatov, Alexander ;Zhou, Xinjia...2016 | Remote Sens. 8(4), 1-17Description:In response to its users’ needs, the National Oceanic and Atmospheric Administration (NOAA) initiated reanalysis (RAN) of the Advanced Very High Res...Algorithm Development of Temperature and Humidity Profile Retrievals for Long-Term HIRS ObservationsCitePersonal Author:Shi, Lei ;Matthews, Jessica...2016 | Remote Sens. 8(4), 1-17Description:A project for deriving temperature and humidity profiles from High-resolution Infrared Radiation Sounder (HIRS) observations is underway to build a lo...2016 | Remote Sens. 8(9), 1-17Description:In this study, six Arctic sea ice thickness products are compared: the AVHRR Polar Pathfinder-extended (APP-x), ICESat, CryoSat-2, SMOS, NASA IceBridg...Personal Author:Adler, Robert ;Sapiano, Mathew...2018 | Atmos., 9(4), 1-14Description:The new Version 2.3 of the Global Precipitation Climatology Project (GPCP) Monthly analysis is described in terms of changes made to improve the homog...Sensor Stability for SST (3S): Toward Improved Long-Term Characterization of AVHRR Thermal BandsCitePersonal Author:He, Kai ;Ignatov, Alexander...2016 | Remote Sens. 8(4), 1-21Description:Recently, the National Oceanic and Atmospheric Administration (NOAA) performed sea surface temperature (SST) reanalysis (RAN1) from seven AVHRR/3s onb...Personal Author:Koner, Prabhat K. ;Harris, Andy2016 | Remote Sens. 8(9), 1-17Description:Global sea-surface temperatures (SST) from MODIS measured brightness temperatures generated using the regression methods, have been available to users...Personal Author:O’Donnell, John P. R. ;Schalles, John F.2016 | Remote Sens. 8(6), 1-22Description:We examined the influence of abiotic drivers on inter-annual and phenological patterns of aboveground biomass for Marsh Cordgrass, Spartina alterniflo...Personal Author:Heron, Scott ;Johnston, Lyza...2016 | Remote Sens. 8(1), 1-16Description:Satellite monitoring of thermal stress on coral reefs has become an essential component of reef management practice around the world. A recent develop...
More +
You May Also Like
Personal Author:
Wang, Zhipeng ;
Iturbide-Sanchez, Flavio
...
2022 | Remote Sens. 2022, 14(4), 876
Description:
Radiometric intercomparison between satellite remote sensing instruments has become an increasingly common practice to monitor the stability and even ...
Personal Author:
Banzon, Viva ;
Smith, Thomas M.
...
2020 | Journal of Atmospheric and Oceanic Technology, 37(2), 341-349.
Description:
Arctic sea surface temperatures (SSTs) are estimated mostly from satellite sea ice concentration (SIC) estimates. In regions with sea ice the SST is t...
Checkout today's featured content at repository.library.noaa.gov