Project Funding: 2008 - 2012

NRA: 2007 NASA: Decision Support through Earth Science Research Results   

Funded by NASA

Abstract:
Our ability to understand and mitigate adverse interactions with protected marine species is dependent on direct access to high-quality marine animal data, ocean observations, ecological models, and expert knowledge. The fusion of these diverse information streams into an integrated and spatially explicit decision support system is essential to meet the growing challenges of protected species and marine ecosystem-based management into the future. Through an ongoing collaboration between the Marine Geospatial Ecology Lab at Duke University and NOAA's Southwest Fisheries Science Center (SWFSC) we are actively expanding the use of earth observing data in decision support tools for marine ecosystem and protected species management. This new effort will build on the existing Ocean Biogeographic Information System OBIS-SEAMAP program (Duke University) and the integrated marine mammal modeling and spatial decision support systems programs supported by the Strategic Environmental Research and Development Program (projects SI-1390 Duke University and SI-1391 NOAA-SWFSC). We plan to significantly expand the scope, depth, and integration of remotely sensed data into our modeling and decision support system by: (1) incorporating and evaluating additional oceanographic measurements and indices for species-environment modeling; (2) implementing more robust automated workflows for processing earth observations for marine management use; and (3) expanding data dissemination and decision support functions using web services architectures. Our proposal will directly address priorities 5.1.6 Ecological Forecasting and 5.1.8 Coastal Management specified in the request for proposals. Our project will specifically improve an existing DSS for monitoring and assessing biodiversity at regional, national, and international scales as well as directly involve U.S. government agencies (NOAA, US-NAVY, ONR) and international organizations (OBIS, GBIF) with mandates for biodiversity monitoring and assessment. Our planned expansion of ocean observing data and analysis methods will provide a critical prototype for marine resource management decision systems development for the future.

Publications:

Beier, C. M., Signell, S. A., Luttman, A., DeGaetano, A. T. 2011. High-resolution climate change mapping with gridded historical climate products. Landscape Ecology. 27(3), 327-342. DOI: 10.1007/s10980-011-9698-8

Best, B., Halpin, P., Read, A., Fujioka, E., Good, C., LaBrecque, E., Schick, R., Roberts, J., Hazen, L., Qian, S., Palka, D., Garrison, L., McLellan, W. 2012. Online cetacean habitat modeling system for the US east coast and Gulf of Mexico. Endangered Species Research. 18(1), 1-15. DOI: 10.3354/esr00430

Bishop, D. A., Beier, C. M. 2013. Assessing Uncertainty in High-Resolution Spatial Climate Data across the US Northeast. PLoS ONE. 8(8), e70260. DOI: 10.1371/journal.pone.0070260

Ferreira, A., Garcia, C. A., Dogliotti, A. I., Garcia, V. M. 2013. Bio-optical characteristics of the Patagonia Shelf break waters: Implications for ocean color algorithms. Remote Sensing of Environment. 136, 416-432. DOI: 10.1016/j.rse.2013.05.022

Ferreira, A., Stramski, D., Garcia, C. A. E., Garcia, V. M. T., Ciotti, A. M., Mendes, C. R. B. 2013. Variability in light absorption and scattering of phytoplankton in Patagonian waters: Role of community size structure and pigment composition. Journal of Geophysical Research: Oceans. 118(2), 698-714. DOI: 10.1002/jgrc.20082

Goni, G. J., Trinanes, J. A., MacFadyen, A., Streett, D., Olascoaga, M. J., Imhoff, M. L., Muller-Karger, F., Roffer, M. A. 2015. Variability of the Deepwater Horizon Surface Oil Spill Extent and Its Relationship to Varying Ocean Currents and Extreme Weather Conditions in: Mathematical Modelling and Numerical Simulation of Oil Pollution Problems: The Reacting Atmosphere. Springer International Publishing, 1-22. DOI: 10.1007/978-3-319-16459-5_1

Habtes, S., Muller-Karger, F. E., Roffer, M. A., Lamkin, J. T., Muhling, B. A. 2014. A comparison of sampling methods for larvae of medium and large epipelagic fish species during spring SEAMAP ichthyoplankton surveys in the Gulf of Mexico. Limnology and Oceanography: Methods. 12(2), 86-101. DOI: 10.4319/lom.2014.12.86

Hong, B., Limburg, K. E., Hall, M. H., Mountrakis, G., Groffman, P. M., Hyde, K., Luo, L., Kelly, V. R., Myers, S. J. 2012. An integrated monitoring/modeling framework for assessing human-nature interactions in urbanizing watersheds: Wappinger and Onondaga Creek watersheds, New York, USA. Environmental Modelling & Software. 32, 1-15. DOI: 10.1016/j.envsoft.2011.08.006

Hsu, A. C., Boustany, A. M., Roberts, J. J., Chang, J., Halpin, P. N. 2015. Tuna and swordfish catch in the U.S. northwest Atlantic longline fishery in relation to mesoscale eddies. Fisheries Oceanography. 24(6), 508-520. DOI: 10.1111/fog.12125

Huang, M., Carmichael, G. R., Chai, T., Pierce, R. B., Oltmans, S. J., Jaffe, D. A., Bowman, K. W., Kaduwela, A., Cai, C., Spak, S. N., Weinheimer, A. J., Huey, L. G., Diskin, G. S. Impacts of transported background pollutants on summertime Western US air quality: model evaluation, sensitivity analysis and data assimilation DOI: 10.5194/acpd-12-15227-2012

Jarnevich, C. S., Esaias, W. E., Ma, P. L. A., Morisette, J. T., Nickeson, J. E., Stohlgren, T. J., Holcombe, T. R., Nightingale, J. M., Wolfe, R. E., Tan, B. 2013. Regional distribution models with lack of proximate predictors: Africanized honeybees expanding north. Diversity and Distributions. 20(2), 193-201. DOI: 10.1111/ddi.12143

Jin, H., Mountrakis, G., Li, P. 2012. A super-resolution mapping method using local indicator variograms. International Journal of Remote Sensing. 33(24), 7747-7773. DOI: 10.1080/01431161.2012.702234

Jin, H., Mountrakis, G., Stehman, S. V. 2014. Assessing integration of intensity, polarimetric scattering, interferometric coherence and spatial texture metrics in PALSAR-derived land cover classification. ISPRS Journal of Photogrammetry and Remote Sensing. 98, 70-84. DOI: 10.1016/j.isprsjprs.2014.09.017

Luo, L., Mountrakis, G. 2010. Integrating intermediate inputs from partially classified images within a hybrid classification framework: An impervious surface estimation example. Remote Sensing of Environment. 114(6), 1220-1229. DOI: 10.1016/j.rse.2010.01.008

Luo, L., Mountrakis, G. 2011. A multiprocess model of adaptable complexity for impervious surface detection. International Journal of Remote Sensing. 33(2), 365-381. DOI: 10.1080/01431161.2010.532177

Luo, L., Mountrakis, G. 2011. Converting local spectral and spatial information from a priori classifiers into contextual knowledge for impervious surface classification. ISPRS Journal of Photogrammetry and Remote Sensing. 66(5), 579-587. DOI: 10.1016/j.isprsjprs.2011.03.002

Madritch, M. D., Lindroth, R. L. 2015. Condensed tannins increase nitrogen recovery by trees following insect defoliation. New Phytologist. 208(2), 410-420. DOI: 10.1111/nph.13444

Mannocci, L., Roberts, J. J., Miller, D. L., Halpin, P. N. 2017. Extrapolating cetacean densities to quantitatively assess human impacts on populations in the high seas. Conservation Biology. 31(3), 601-614. DOI: 10.1111/cobi.12856

Moorcroft, P. R. 2012. Mechanistic approaches to understanding and predicting mammalian space use: recent advances, future directions. Journal of Mammalogy. 93(4), 903-916. DOI: 10.1644/11-mamm-s-254.1

Mountrakis, G., Im, J., Ogole, C. 2011. Support vector machines in remote sensing: A review. ISPRS Journal of Photogrammetry and Remote Sensing. 66(3), 247-259. DOI: 10.1016/j.isprsjprs.2010.11.001

Mountrakis, G., Li, Y. 2017. A linearly approximated iterative Gaussian decomposition method for waveform LiDAR processing. ISPRS Journal of Photogrammetry and Remote Sensing. 129, 200-211. DOI: 10.1016/j.isprsjprs.2017.05.009

Mountrakis, G., Luo, L. 2011. Enhancing and replacing spectral information with intermediate structural inputs: A case study on impervious surface detection. Remote Sensing of Environment. 115(5), 1162-1170. DOI: 10.1016/j.rse.2010.12.018

Mountrakis, G., Zhuang, W. 2012. Integrating Local and Global Error Statistics for Multi-Scale RBF Network Training: An Assessment on Remote Sensing Data. PLoS ONE. 7(8), e40093. DOI: 10.1371/journal.pone.0040093

Muhling, B. A., Brill, R., Lamkin, J. T., Roffer, M. A., Lee, S., Liu, Y., Muller-Karger, F. 2016. Projections of future habitat use by Atlantic bluefin tuna: mechanistic vs. correlative distribution models. ICES Journal of Marine Science. 74(3), 698-716. DOI: 10.1093/icesjms/fsw215

Muhling, B. A., Lamkin, J. T., Alemany, F., Garcia, A., Farley, J., Ingram, G. W., Berastegui, D. A., Reglero, P., Carrion, R. L. 2017. Reproduction and larval biology in tunas, and the importance of restricted area spawning grounds. Reviews in Fish Biology and Fisheries. 27(4), 697-732. DOI: 10.1007/s11160-017-9471-4

Muhling, B. A., Roffer, M. A., Lamkin, J. T., Ingram, G. W., Upton, M. A., Gawlikowski, G., Muller-Karger, F., Habtes, S., Richards, W. J. 2012. Overlap between Atlantic bluefin tuna spawning grounds and observed Deepwater Horizon surface oil in the northern Gulf of Mexico. Marine Pollution Bulletin. 64(4), 679-687. DOI: 10.1016/j.marpolbul.2012.01.034

Nightingale, J. M., Esaias, W. E., Wolfe, R. E., Nickeson, J. E., Ma, P. L. A. 2008. Assessing Honey Bee Equilibrium Range and Forage Supply using Satelite-Derived Phenology. IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium. DOI: 10.1109/igarss.2008.4779460

Perez-Santos, I., Schneider, W., Valle-Levinson, A., Garces-Vargas, J., Soto, I., Montoya-Sanchez, R., Melo Gonzalez, N., Muller-Karger, F. 2014. Chlorophyll-a patterns and mixing processes in the Yucatan Basin, Caribbean Sea. Ciencias Marinas. 40(1), 11-31. DOI: 10.7773/cm.v40i1.2320

Roberts, J. J., Best, B. D., Mannocci, L., Fujioka, E., Halpin, P. N., Palka, D. L., Garrison, L. P., Mullin, K. D., Cole, T. V. N., Khan, C. B., McLellan, W. A., Pabst, D. A., Lockhart, G. G. 2016. Habitat-based cetacean density models for the U.S. Atlantic and Gulf of Mexico. Scientific Reports. 6(1). DOI: 10.1038/srep22615

Shi, Y., Song, Q., Jin, T., Zhou, Z. 2011. The AdaBoost Classification of Land-mine Target with Adaptive Feature Selection. Journal of Electronics & Information Technology. 33(8), 1798-1802. DOI: 10.3724/sp.j.1146.2010.01423

Torrecilla, E., Stramski, D., Reynolds, R. A., Millan-Nunez, E., Piera, J. 2011. Cluster analysis of hyperspectral optical data for discriminating phytoplankton pigment assemblages in the open ocean. Remote Sensing of Environment. 115(10), 2578-2593. DOI: 10.1016/j.rse.2011.05.014

Uitz, J., Claustre, H., Gentili, B., Stramski, D. 2010. Phytoplankton class-specific primary production in the world's oceans: Seasonal and interannual variability from satellite observations. Global Biogeochemical Cycles. 24(3). DOI: 10.1029/2009gb003680

Uitz, J., Stramski, D., Gentili, B., D'Ortenzio, F., Claustre, H. 2012. Estimates of phytoplankton class-specific and total primary production in the Mediterranean Sea from satellite ocean color observations. Global Biogeochemical Cycles. 26(2). DOI: 10.1029/2011gb004055

Uitz, J., Stramski, D., Reynolds, R. A., Dubranna, J. 2015. Assessing phytoplankton community composition from hyperspectral measurements of phytoplankton absorption coefficient and remote-sensing reflectance in open-ocean environments. Remote Sensing of Environment. 171, 58-74. DOI: 10.1016/j.rse.2015.09.027

Weiss, D. J., Crabtree, R. L. 2011. Percent surface water estimation from MODIS BRDF 16-day image composites. Remote Sensing of Environment. 115(8), 2035-2046. DOI: 10.1016/j.rse.2011.04.005

Zhuang, W., Mountrakis, G. 2014. An accurate and computationally efficient algorithm for ground peak identification in large footprint waveform LiDAR data. ISPRS Journal of Photogrammetry and Remote Sensing. 95, 81-92. DOI: 10.1016/j.isprsjprs.2014.06.004

Zhuang, W., Mountrakis, G. 2014. Ground peak identification in dense shrub areas using large footprint waveform LiDAR and Landsat images. International Journal of Digital Earth. 8(10), 805-824. DOI: 10.1080/17538947.2014.942716

Zhuang, W., Mountrakis, G., Wiley, J. J., Beier, C. M. 2015. Estimation of above-ground forest biomass using metrics based on Gaussian decomposition of waveform lidar data. International Journal of Remote Sensing. 36(7), 1871-1889. DOI: 10.1080/01431161.2015.1029095

2011 NASA Carbon Cycle & Ecosystems Joint Science Workshop Poster(s)

• Integrating Ocean Observing Data into Habitat-Based Models of Cetacean Density for the Central North Pacific and US Atlantic   --   (Elizabeth A. Becker, Karin A. Forney, David G. Foley, Jay Barlow, Ben D. Best, Jason J. Roberts, Andre M. Boustany, Pat N. Halpin)   [abstract]
• Toward a National Animal Telemetry Observing Network (ATN) for our Oceans, Coasts and Great Lakes   --   (Hassan Moustahfid, Churchill Grimes, John Kocik, Barbara Block, Kim Holland, John Payne, Dewayne Fox, Andrew Seitz, Charles Alexander)   [abstract]

More details may be found in the following project profile(s):

• NASA Biological Diversity & Ecological Conservation (BDEC) Project Profile