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Viktor Hamburger to Rob Oppenheim, 1993
No full textHandwrittena copy of a letter to Ron Oppenheim, concerning a publication of Salme Waelsch2 pagesCorrespondanc
Viktor Hamburger to Martha Hamburger, 1932
Full text linkHandwrittenLetter and its translation to Martha Hamburger describing Hamburger's daily life, including his opinion on movies and symphonies2 pagesCorrespondanc
Single cell mass spectroscopy data collected to investigate metabolomics affected by cell-cell interactions in 2020 and 2021
Full text linkDataset: Single cell mass spec Cell-Cell interactionSingle-cell mass spectrometry (SCMS) was integrated with fluorescence microscopy to investigate metabolomics affected by cell-cell interactions in 2020 and 2021. These data were used to create a table in the publication of the results by Chen et al. (2022).
For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/890877NSF Division of Ocean Sciences (NSF OCE) OCE-163463
Echosounder data from goliath grouper aggregations in Jupiter, FL from August 31 until November 30, 2020.
No full textDataset: Hydroacoustic Survey Data 2020Echosounder data from goliath grouper aggregations in Jupiter, FL from August 31 until November 30, 2020.
For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/858599NSF Division of Ocean Sciences (NSF OCE) OCE-2006293, NSF Division of Ocean Sciences (NSF OCE) OCE-200629
Experimental and in situ seawater nutrient data collected as part of a study of pCO2 variability on the reef-building coral Pocillopora damicornis conducted at Heron Island Research Station, Heron Island, southern Great Barrier Reef in 2021
No full textDataset: In-field and experimental measurements of environmental conditions: nutrientsThis dataset contains experimental and in situ seawater nutrient data. These data were collected as part of a study of pCO2 variability on the reef-building coral Pocillopora damicornis conducted at Heron Island Research Station, Heron Island, southern Great Barrier Reef in 2021 (Brown et al., 2022).
Abstract for all data from the study (Brown et al., 2022) including this dataset:
Ocean acidification is a growing threat to coral growth and the accretion of coral reef ecosystems. Corals inhabiting environments that already endure extreme diel pCO2 fluctuations, however, may represent acidification resilient populations capable of persisting on future reefs. Here, we examined the impact of pCO2 variability on the reef-building coral Pocillopora damicornis originating from reefs with contrasting environmental histories (variable reef flat vs. stable reef slope) following reciprocal exposure to stable (218 ± 9) or variable (911 ± 31) diel pCO2 amplitude (μtam) in aquaria over eight weeks. This study measured: growth (net calcification, extension, CaCO3 density) and physiology (dark respiration, light-enhanced dark respiration, host soluble protein, mycosporine-like amino acids, net photosynthesis, photosynthetic efficiency, endosymbiont density, chlorophyll a concentration, intracellular pH) of P. damicornis across treatment and origin.
See all datasets related to this publication (https://www.bco-dmo.org/related-resource/885684).
For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/885669NSF Division of Ocean Sciences (NSF OCE) OCE-192374
Carbonate Chemistry Parameters from a heatwave experiment done September to November 2018 using reef building corals collected in Kāne'ohe Bay, O'ahu, Hawai'i.
No full textDataset: Heatwave Experiment: Carbonate Chemistry ParametersTwo common reef-building corals, Montipora capitata and Pocillopora acuta, were collected from six sites in Kāne'ohe Bay, O'ahu, Hawai'i. Fragments were allowed to acclimate in experimental tanks for two weeks prior to exposure to one of the following four treatments: Ambient Temperature Ambient pCO2 (ATAC), Ambient Temperature High pCO2 (ATHC), High Temperature Ambient pCO2 (HTAC), and High Temperature High pCO2 (HTHC). The treatment period lasted for a two month period, starting on September 22nd, 2018 and lasting through November 17th, 2018. Following the stress period, coral fragments were exposed to a two-month recovery period in ambient conditions.
Twice a week, water samples were taken and analyzed for carbonate chemistry parameters.
For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/884411NSF Division of Ocean Sciences (NSF OCE) OCE-175662
Perceive, predict, and plan: robotic expeditionary science in oceanic spatiotemporal fields
Full text linkSubmitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Autonomous Systems at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution February 2023.An improved understanding of our ocean would allow us to characterize the largest habitable biosphere on planet Earth, quantify the geochemical processes that control Earth’s climate, and develop responsible regulations for controlling the natural resources
stored in its depths. Expeditionary science is the art of collecting in situ observations of an environment to build approximate models of underlying properties that move us towards this understanding. Robotic platforms are a critical technology for collecting
observations of the ocean. Depth-capable autonomous underwater vehicles (AUVs) are commonly used to build static maps of the seafloor by executing pre-programmedsurveys. However, there is growing urgency to generate rich data products of spatiotemporal distributions that characterize the physics and chemistry of the deep ocean biogeosphere. In this thesis, the problem of charting dynamic deep sea hydrothermal plumes with depth-capable AUVs is investigated. Effectively collecting samples of geochemical plumes using the operationally preferred strategy of pre-specifying surveys requires access to a dynamics model of the advective currents, bathymetric updrafts, and turbulent mixing at a hydrothermal site. In practice, however, access to this information is unavailable, imperfect, or only partially known, and so a model of plume dynamics must be inferred from observations and subsequently leveraged to improve future sampling performance. As most in situ scientific instruments yield point-measurements, considerable uncertainty is placed over the form of the dynamics in purely data-driven solutions.
Challenges related to planning under uncertainty for geochemical surveys in the deep ocean are addressed in this thesis by embedding scientific knowledge as a strong inductive prior for tractable model learning and decision-making. Algorithmic contributions of this thesis show how plumes can be perceived from field data, their fate predicted far into the future (e.g., multiple days), and informative fixed trajectories planned which place an AUV in the right place at the right time. Scientific assessment of observational data collected with AUV Sentry during field trials in the Guaymas Basin, Gulf of California are interwoven with algorithmic analyses, demonstrating how intelligent perception, prediction, and planning enables novel insights about hydrothermal plumes.Financial support for my research was provided by the National Defense Graduate Fellowship Program and the MIT Martin Family Society of Fellows for Sustainability. Research activities for the RR2107 cruise were funded by NSF OCE OTIC #1842053, a
WHOI Innovation Technology Award, NOAA Ocean Exploration #NA18OAR0110354, and Schmidt Marine Technology Partners Award #G-21-62431
Quantifying pelagic primary production and respiration via an automated in-situ incubation system
Full text linkSubmitted in partial fulfillment of the requirements for the degree of Master of Science at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution February 2023.Pelagic photosynthesis and respiration serve critical roles in controlling the dissolved oxygen concentration (DO) in seawater. The consumption and production via pelagic primary production are of particular importance in surface ocean and in shallow aquatic ecosystems where photosynthetically active radiation (PAR) is abundant. However, the dynamic nature and large degree of heterogeneity in these ecosystems pose substantial challenges for providing accurate estimates of marine primary production and metabolic state. The resulting lack of data in these systems hinders efforts in scaling and including primary production in predictive models. To bridge the gap, we developed and validated a novel automated water incubator that measures in-situ rates of photosynthesis and respiration. The automated water incubation system uses commercially available optodes and microcontrollers to record continuous measurements of DO within a closed chamber at desired intervals. With fast response optodes, the incubation system produced measurements of photosynthesis and respiration with hourly resolution, resolving diel signals in the water column. The high temporal resolution of the timeseries also enabled the development of Monte-Carlo simulation as a new data analysis technique to calculate DO fluxes, with improved performance in noisy timeseries. Deployment of the incubator was conducted near Ucantena Island, Massachusetts, USA. The data captured diel fluctuations in metabolic fluxes with hourly resolution, allowed for a more accurate correlation between oxygen cycling and environmental conditions, and provided improved characterization of the pelagic metabolic state.This thesis work was supported by NSF OTIC grant 1841092 to PI Collin Ward and Matt Long and WHOI Academic Office. The early work was also supported by NSF-REU Summer Student Fellowship program at WHOI. The subsequent development portion of this project was supported by WHOI-ADI OCIA to PI Matt Long and Ben Van Mooy
Physiology color score extracted from pictures taken during a thermal stress experiment using reef building corals collected in Kāne'ohe Bay, O'ahu, Hawai'i.
No full textDataset: Thermal Stress Experiment: Color Score PhysiologyUnderstanding the response of the coral holobiont to environmental change is crucial to inform conservation efforts. The most pressing problem is “coral bleaching,” usually precipitated by prolonged thermal stress. This dataset spans a five week thermal stress experiment in which images were taken of coral individuals and analyzed for a "color score".
For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/884220NSF Division of Ocean Sciences (NSF OCE) OCE-175662