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| griddap | Subset | tabledap | Make A Graph | wms | files | Accessible | Title | Summary | FGDC | ISO 19115 | Info | Background Info | RSS | Institution | Dataset ID | |
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| log in | [Flume experiment water chemistry July 2023] - Water chemistry and temperature measured within and above dense aggregation of mussels from a flume experiment conducted July 2023 (Collaborative Research: Microscale interactions of foundation species with their fluid environment: biological feedbacks alter ecological interactions of mussels) | The project investigates how the metabolic activity of dense aggregations of marine organisms alter the water chemistry of their interstitial spaces, and how these microscale alterations feedback to affect the organisms' interactions in coastal ecosystems. The research evaluates whether corrosive chemical microclimates (such as low oxygen or low pH) are most extreme in low flow, high temperature conditions, especially for dense aggregations of mussels with large biomass and/or high respiration rates, and if they negatively impact mussel beds and the diverse biological communities they support. In order to address these questions, a flume experiment was conducted at Friday Harbor Laboratories where flow and chemical gradients were measured within and above a dense aggregation of mussels (Mytilus trossolus). Twenty profiles were taken over five days with 5 profiles taken for each of the four experimental flume speeds (0.25, 0.5, 1, and 1.5 inch/sec). Approximately 3-minute-long measurements were taken of velocity, dissolved oxygen, temperature, and pH every centimeter within the bed and two measurements were taken above the bed. Ambient conditions (dissolved oxygen, temperature, pH and conductivity) were also measured continuously using an array of HOBO loggers.\n\ncdm_data_type = Other\nVARIABLES:\nTrial (unitless)\nDay_of_week (unitless)\nFlow_speed (centimeters per second (cm/s))\nElevation (centimeters (cm))\nPyro_Date_UTC (unitless)\nPyro_Dissolved_Oxygen (percent air saturation)\nPyro_Temp (degrees Celsius (°C))\nPyro_pH (dimensionless)\nPyro_Adj_DO (milligrams per liter (mg/L))\nHOBO_Date_UTC (unitless)\nHOBO_Temp_pH_sensor (dimensionless)\nHOBO_pH_Millivolts (millivolts (mV))\nHOBO_pH (dimensionless)\nHOBO_DO_conc (milligrams per liter (mg/L))\n... (9 more variables)\n | BCO-DMO | bcodmo_dataset_982681_v1 | ||||||||||||
| https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_922819_v1 | https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_922819_v1.graph | https://erddap.bco-dmo.org/erddap/files/bcodmo_dataset_922819_v1/ | public | [Macrophytes' amelioration of seawater acidity: Residence time and irradiance] - Macrophytes' amelioration of seawater acidity: Water residence time and irradiance of Saccharina latissima from the Gulf of Maine in November 2018 (REU Site: Bigelow Laboratory for Ocean Sciences - Undergraduate Research Experience in the Gulf of Maine and the World Ocean) | An experiment examining the effects of water residence time upon Saccharina latissima capacity to ameliorate seawater acidity under ambient and simulated future scenarios of climate change in a gradient of irradiance was conducted indoors using tanks with a flow-through seawater system based at the Bigelow facilities in November 2018. In a previous experiment (experiment 1), we explored the individual capacities of four species of marine macrophytes (Ulva lactuca, Zostera marina, Fucus vesiculosus and Saccharina latissima) to ameliorate seawater acidity in experimentally elevated pCO2. Then in this experiment 2, we used the most responsive species (i.e., Saccharina latissima) to assess the effects of high and low water residence time on the amelioration of seawater acidity in ambient and simulated future scenarios of climate change across a gradient of irradiance.\n\nThis dataset includes data from experiment 2, residence time and irradiance, described in the manuscript: Optimizing marine macrophyte capacity to locally ameliorate ocean acidification under variable light and flow regimes: Insights from an experimental approach (Ricart, A. M. et al. 2023).\n\ncdm_data_type = Other\nVARIABLES:\nSpecies (unitless)\nlatitude (degrees_north)\nlongitude (degrees_east)\nDate (unitless)\nAquaria (unitless)\nFuture_Ambient (unitless)\nKelp_Control (unitless)\nKelp_biomass_wet (grams (g))\nKelp_biomass_dry (grams (g))\nPAR (micromols m-2 s-1 (uM m-2 s-1))\nFlow_level (unitless)\nSalinity (unitless)\nTemperature (degrees Celsius (°C))\n... (7 more variables)\n | https://erddap.bco-dmo.org/erddap/metadata/fgdc/xml/bcodmo_dataset_922819_v1_fgdc.xml | https://erddap.bco-dmo.org/erddap/metadata/iso19115/xml/bcodmo_dataset_922819_v1_iso19115.xml | https://erddap.bco-dmo.org/erddap/info/bcodmo_dataset_922819_v1/index.htmlTable | https://www.bco-dmo.org/dataset/922819
| https://erddap.bco-dmo.org/erddap/rss/bcodmo_dataset_922819_v1.rss | https://erddap.bco-dmo.org/erddap/subscriptions/add.html?datasetID=bcodmo_dataset_922819_v1&showErrors=false&email= | BCO-DMO | bcodmo_dataset_922819_v1 |