A lifelong interest in conserving marine ecosystems has driven my involvement in the development of robotic water sampling systems like the Gulper Autonomous Underwater Vehicle and the Environmental Sample Processor. Joining these technological advancements with molecular genetic assays enables us to assess how environmental factors affect the biodiversity and abundances of planktonic organisms. Autonomous sampling software development allows our robotic platforms to monitor their surrounding environment and adaptively collect water samples with high precision. By targeting hydrographic features such as upwelling fronts, or biological features such as chlorophyll thin-layers, we can monitor how physical and chemical processes affect zooplankton and phytoplankton responsible for supporting life in the ocean. Sampling and Identifying Marine Zooplankton is one such project aimed at improving methods for water sample collection and developing molecular tools to more effectively monitor variation in the biodiversity and abundances of zooplankton. The complex multivariate, multidisciplinary data we collect has also motivated noteworthy advances in database development, management and visualization, resulting in development of the Spatial, Temporal Oceanographic Query System at MBARI.
MBARI homepage news report on research led by Julio
Marine ecosystem biology and conservation, plankton ecology, robotic sampling platform development, molecular detection, invasive and harmful species, fisheries resource management, evolutionary genetics, coevolution of marine symbioses.
2004 University of California Santa Cruz, PhD, Ecology and Evolutionary Biology
1996 University of California Berkeley, BS, Integrative Biology
1994–1995 Lund University, Sweden
McCann M, Schramm R, Cline D, Michisaki R, Harvey J, Ryan J (2014). Using STOQS (The spatial temporal oceanographic query system) to manage, visualize, and understand AUV, glider, and mooring data. Autonomous Underwater Vehicles (AUV), Institute for Electrical and Electronics Engineers Oceanic Engineering Society Meeting, Oxford, Massachusetts. http://dx.doi.org/10.1109/auv.2014.7054414
Ryan JP, Harvey JBJ, Zhang Y, Woodson CB (2014). Distributions of invertebrate larvae and phytoplankton in a coastal upwelling system retention zone and peripheral front. Journal of Experimental Molecular Biology and Ecology 459: 51–60. http://dx.doi.org/10.1016/j.jembe.2014.05.017
Ryan JP, McManus MA, Kudela RM, Lara Artigas M, Bellingham JG, Chavez FP, Doucette G, Foley D, Godin M, Harvey JBJ, Marin III R, Messié M, Mikulski C, Pennington T, Py F, Rajan K, Shulman I, Wang Z, Zhang Y (2014). Boundary influences on HAB phytoplankton ecology in a stratification-enhanced upwelling shadow. Deep-Sea Research II 101: 63–79. http://dx.doi.org/10.1016/j.dsr2.2013.01.017
Harvey JBJ (2014). A 96–well plate format for detection of marine zooplankton with the sandwich hybridization assay. In: Stricker, S.A. and D. Carroll (Eds.), Methods in Molecular Biology: Developmental biology of the sea urchin and other marine invertebrates. Humana Press Inc., New York. http://dx.doi.org/10.1007/978-1-62703-974-1_18
Das J, Harvey JBJ, Py F, Vathsangam H, Graham R, Rajan K, and Sukhatme GS (2013). Hierarchical probabilistic regression for AUV-based adaptive sampling of marine phenomena. Proceedings of the 2013 Institute for Electrical and Electronics Engineers International Conference on Robotics and Automation, Karlsruhe, Germany. http://dx.doi.org/10.1109/icra.2013.6631377
Harvey JBJ, Djunaedi AF and Vrijenhoek RC (2013). Validation of a sandwich hybridization assay for marine copepod detection. Journal of Experimental Molecular Biology and Ecology 446: 306–310. http://dx.doi.org/10.1016/j.jembe.2013.06.005
Johnson SB, Won Y-J, Harvey JBJ and Vrijenhoek RC (2013). A hybrid zone between Bathymodiolus mussel lineages from eastern Pacific hydrothermal vents. BMC Evolutionary Biology 13: 21. http://dx.doi.org/10.1186/1471-2148-13-21
Zhang Y, Ryan JP, Bellingham JG, Harvey JBJ and McEwen RS (2012). Autonomous detection and sampling of water types and fronts in a coastal upwelling system by an autonomous underwater vehicle. Limnology Oceanography: Methods 10: 934–951. http://dx.doi.org/10.4319/lom.2012.10.934
Harvey JBJ, Zhang Y and Ryan JP (2012). AUVs for ecological studies of marine plankton communities: Intelligent algorithms on Dorado and Tethys AUVs enable precise water sampling for plankton research. Sea Technology September 2012: 51–54.
Harvey JBJ, Ryan JP, Marin III R, Preston CM, Alvarado N, Scholin CA and Vrijenhoek RC (2012). Robotic sampling, in situ monitoring and molecular detection of marine zooplankton. Journal of Experimental Molecular Biology and Ecology 413: 60–70. http://dx.doi.org/10.1016/j.jembe.2011.11.022
Lundsten L, Schlining KL, Frasier K, Johnson SB, Kuhnz L, Harvey JBJ, Clague G and Vrijenhoek RC (2010). Time-series analysis of six whale fall communities in Monterey Bay, California, USA. Deep Sea Research I 57: 1573–1584. http://dx.doi.org/10.1016/j.dsr.2010.09.003
Ryan JP, Johnson SB, Sherman A, Rajan K, Py F, Thomas H, Harvey JBJ, Bird L, Paduan JD and Vrijenhoek RC (2010). Mobile autonomous process sampling within coastal ocean observing systems. Limnology and Oceanography Methods 8: 394–402. http://dx.doi.org/10.4319/lom.2010.8.394
Harvey JBJ and Goff LJ (2010). Genetic covariation of the marine fungal symbiont Haloguignardia irritans (Ascomycota, Pezizomycotina) with its algal hosts Cystoseira and Halidrys (Phaeophyceae, Fucales) along the west coast of North America. Fungal Biology 114: 82–95. http://dx.doi.org/10.1016/j.mycres.2009.10.009
Harvey JBJ, Hoy MS and Rodriguez R (2009). Molecular detection of native and invasive marine invertebrate larvae present in ballast and open water environmental samples collected in Puget Sound. Journal of Experimental Marine Biology and Ecology 369: 93–99. http://dx.doi.org/10.1016/j.jembe.2008.10.030
Harvey JBJ and Goff LJ (2006). A reassessment of species boundaries in Cystoseira and Halidrys (Fucales, Phaeophyceae) along the North American west coast. Journal of Phycology 42: 707–720. http://dx.doi.org/10.1111/j.1529-8817.2006.00215.x