i
Moving Towards Dynamic Ocean Management: How Well Do Modeled Ocean Products Predict Species Distributions?
-
2016
Source: Remote Sens. 8(2), 1-26
[PDF-4.06 MB]
Details:
-
Journal Title:Remote Sensing
-
Personal Author:
-
NOAA Program & Office:
-
Description:Species distribution models are now widely used in conservation and management to predict suitable habitat for protected marine species. The primary sources of dynamic habitat data have been in situ and remotely sensed oceanic variables (both are considered “measured data”), but now ocean models can provide historical estimates and forecast predictions of relevant habitat variables such as temperature, salinity, and mixed layer depth. To assess the performance of modeled ocean data in species distribution models, we present a case study for cetaceans that compares models based on output from a data assimilative implementation of the Regional Ocean Modeling System (ROMS) to those based on measured data. Specifically, we used seven years of cetacean line-transect survey data collected between 1991 and 2009 to develop predictive habitat-based models of cetacean density for 11 species in the California Current Ecosystem. Two different generalized additive models were compared: one built with a full suite of ROMS output and another built with a full suite of measured data. Model performance was assessed using the percentage of explained deviance, root mean squared error (RMSE), observed to predicted density ratios, and visual inspection of predicted and observed distributions. Predicted distribution patterns were similar for models using ROMS output and measured data, and showed good concordance between observed sightings and model predictions. Quantitative measures of predictive ability were also similar between model types, and RMSE values were almost identical. The overall demonstrated success of the ROMS-based models opens new opportunities for dynamic species management and biodiversity monitoring because ROMS output is available in near real time and can be forecast.
-
Source:Remote Sens. 8(2), 1-26
-
Document Type:
-
Rights Information:CC BY
-
Compliance:Library
-
Main Document Checksum:urn:sha256:307f26e66f0e7580f0987c9c4094307d1cdaabc2bae2d29ac0238277c1a59ddb
-
File Type:
Supporting Files
-
No Additional Files
More +
Related Documents
-
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...Personal Author:Caldwell, Jamie ;Heron, Scott...2016 | Remote Sens. 8(2), 1-15Description:Predicting wildlife disease risk is essential for effective monitoring and management, especially for geographically expansive ecosystems such as cora...
More +
You May Also Like
Fisheries ecosystem model of the Chesapeake Bay methodology, parameterization, and model exploration
Cite
Personal Author:
Christensen, Villy
2009 | NOAA tech. memo. NMFS-F/SPO ; 106
Description:
"This report describes an ecosystem model of the Chesapeake Bay, the Chesapeake Bay Fisheries Ecosystem Model (CBFEM), prepared using the Ecopath with...
Checkout today's featured content at repository.library.noaa.gov