http://lod.bco-dmo.org/id/dataset/1009817 eng; USA utf8 dataset Highest level of data collection, from a common set of sensors or instrumentation, usually within the same research project Biological and Chemical Oceanography Data Management Office (BCO-DMO) Unavailable 508-289-2009 WHOI MS#36 Woods Hole MA 02543 USA info@bco-dmo.org http://www.bco-dmo.org Monday - Friday 8:00am - 5:00pm For questions regarding this resource, please contact BCO-DMO via the email address provided. pointOfContact 2026-10-13 ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data ISO 19115-2:2009(E) Results of a study examining how foundation species loss alters fDOM and heterotrophic bacteria counts based on sampling of tidepools in the Otter Rock Marine Reserve (ORMR) and Marine Garden, Oregon USA from June to August 2019 2026-10-13 publication 2026-10-13 revision Woods Hole Oceanographic Institution (WHOI BCO-DMO) 2026-10-14 publication https://doi.org/10.26008/1912/bco-dmo.1009817.1 Nyssa Silbiger University of Hawaiʻi at Mānoa principalInvestigator Jennifer Fields California State University Northridge principalInvestigator Craig E. Nelson University of Hawaiʻi at Mānoa principalInvestigator Linda Wegley Kelly University of California-San Diego Scripps principalInvestigator Biological and Chemical Oceanography Data Management Office (BCO-DMO) Unavailable 508-289-2009 WHOI MS#36 Woods Hole MA 02543 USA info@bco-dmo.org http://www.bco-dmo.org Monday - Friday 8:00am - 5:00pm For questions regarding this resource, please contact BCO-DMO via the email address provided. publisher Cite this dataset as: Silbiger, N., Fields, J., Nelson, C. E., Wegley Kelly, L. (2026) Results of a study examining how foundation species loss alters fDOM and heterotrophic bacteria counts based on sampling of tidepools in the Otter Rock Marine Reserve (ORMR) and Marine Garden, Oregon USA from June to August 2019. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2026-10-13 [if applicable, indicate subset used]. doi:10.26008/1912/bco-dmo.1009817.1 [access date] Methods and Sampling: &lt;p&gt;&amp;nbsp;fDOM samples were stored in amber glass vials at 4 °C until further processing. Heterotrophic bacterial counts were taken from 1.5 mL unfiltered seawater and stored in 0.5% paraformaldehyde (amended with 100 μL 8% ampulated paraformaldehyde, Electron MicroscopySciences, Hatfield, PA, USA) in a 2 mL polypropylene cryovial, mixed briefly and then frozen to -20 °C. All storage vials were triple rinsed with sample water prior to sample storage. fDOM samples were processed on a Horiba Aqualog scanning fluorometer with 1 cm quartz cuvettes at the University of Hawai’i at Mānoa following Nelson et al. (2015).&lt;/p&gt; &lt;p&gt;All samples were brought to room temperature prior to analysis. Prior to running samples, cuvettes were washed thoroughly with DI water and wiped clear with Kim wipes. Cuvettes were triple rinsed with DI between each sample. A DI blank was run after every 7 samples. Excitation-Emission Matrices (EEMS) were generated with excitation values ranging from 240 nm to 500 nm and emission values were measured ranging from 250 nm to 825 nm.&lt;/p&gt; &lt;p&gt;Excitation wavelengths were increased at 5 nm increments and measurements were integrated over 4 s at each increment. Inner filter correction was applied to account for fluorescence quenching by absorbance (Kothawala &lt;em&gt;et al.&lt;/em&gt; 2013). Fluorescence values were scaled to Raman Units by dividing by the integrated emission range of 381 nm to 426 nm at an excitation of 350 nm in averaged DI blanks. The average blank EEMs, from DI blanks run immediately before and after each set of samples, were subtracted from the sample EEMs.&lt;/p&gt; &lt;p&gt;Two biogeochemical informative indices were calculated for this study which included M:C (the relative amount of marine to terrestrial humics) (Burdige &lt;em&gt;et al.&lt;/em&gt; 2004) and BIX (biological index) (Huguet &lt;em&gt;et al.&lt;/em&gt; 2009). Heterotrophic bacterial counts were analyzed using flow cytometry on an Attune Acoustic Focusing Cytometer with Autosampler Attachment (Life Technologies, Eugene, OR, USA) with methods following Nelson et al. (2015)&lt;em&gt;.&lt;/em&gt;&lt;/p&gt; &lt;p&gt;Flow cytometry samples were analyzed on fixed 1ml samples run on a Cytoflex Flow Cytometer stained with 7 μL of 40 μL mL&lt;sup&gt;−1&lt;/sup&gt; Hoechst 34580 (1 μg mL&lt;sup&gt;−1&lt;/sup&gt; , final concentration) following standard protocols (Nelson &lt;em&gt;et al.&lt;/em&gt; 2015; Selph 2021)&lt;em&gt;.&lt;/em&gt;&lt;/p&gt; &lt;p&gt;Stained cells were distinguished from instrument noise using stained and unstained blank water, and autofluorescent cells containing phytopigments were subtracted from the total to derive the subset of heterotrophic bacterioplankton.&lt;/p&gt; Funding provided by NSF Division of Ocean Sciences (NSF OCE) Award Number: OCE-2044837 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=2044837 completed Nyssa Silbiger University of Hawaiʻi at Mānoa 818-677-2901 HI USA silbiger@hawaii.edu pointOfContact Jennifer Fields California State University Northridge (408) 316-8659 229 Plaza la Posada Los Gatos CA 95032 USA jenn.b.fields@gmail.com pointOfContact Craig E. Nelson University of Hawaiʻi at Mānoa 805-705-3497 Center for Microbial Oceanography: Research & Education Dept of Oceanography & UH Sea Grant Honolulu HI 96822 USA cen@hawaii.edu pointOfContact Linda Wegley Kelly University of California-San Diego Scripps 858-246-4655 9500 Gilman Dr #0202 La Jolla CA 92093-0202 USA lwegley@ucsd.edu pointOfContact asNeeded Dataset Version: 1 Unknown ISO_DateTime_UTC pool_id foundation_spp LSID aphiaID day_night before_after removal_control time_point sampling_date sampling_time_local heterotrophic_bacterioplankton_micro_l m_c bix Cytoflex Flow Cytometer Horiba Aqualog Scanning Fluorometer theme None, User defined ISO_DateTime_UTC Site_ID taxon Life Science Identifier (LSID) taxon_code sample description treatment tide date time_local abundance No BCO-DMO term featureType BCO-DMO Standard Parameters Flow Cytometer Fluorometer instrument BCO-DMO Standard Instruments otherRestrictions otherRestrictions Access Constraints: none. Use Constraints: Please follow guidelines at: http://www.bco-dmo.org/terms-use Distribution liability: Under no circumstances shall BCO-DMO be liable for any direct, incidental, special, consequential, indirect, or punitive damages that result from the use of, or the inability to use, the materials in this data submission. If you are dissatisfied with any materials in this data submission your sole and exclusive remedy is to discontinue use. CAREER: Predicting ecosystem metabolism of rocky intertidal communities in warming and acidifying oceans. https://osprey.bco-dmo.org/project/876576 CAREER: Predicting ecosystem metabolism of rocky intertidal communities in warming and acidifying oceans. <p><strong>NSF Award Abstract:</strong><br /> This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).</p> <p>The devastating impacts of global warming and ocean acidification (OA) on rocky intertidal ecosystems are expected to increase as the oceans continue to warm and acidify. Further, loss of critical foundation species as a result of anthropogenic stressors lead to changes in local conditions that alter ecosystem functioning. While data exist on the physiological response of individual organisms to OA and warming in rocky systems, far less research has been conducted on community and ecosystem-scale metabolic responses. The proposed work provides a critical step in understanding how altered environmental conditions affect ecosystem functioning in rocky intertidal systems through the combination of controlled laboratory studies, field experiments, and a synthetic modeling approach integrating experimental results with pre-existing time-series data. The proposed work is focused on the overarching question: How does shifting environmental variability and loss of foundation species interact to affect ecosystem functioning in rocky intertidal communities? The PI is integrating research with ecological and quantitative educational opportunities including classroom and hands-on training in lab/field methods in marine ecology, and data science and coding bootcamps for undergraduate students. Importantly, these opportunities financially and educationally support traditionally underrepresented students at one of the largest minority-serving institutions in the country. This project provides support for intensive mentoring and training for 35 undergraduate students (25 in data science and 10 in field/lab science, all paid), 2-3 masters students, and hands-on marine ecology opportunities in the classroom (~125 students). In addition to formal education, the PI is collaborating with an artist-in-residence to communicate science to the broader public through interactive and immersive art installations in Los Angeles.</p> <p>Because rocky intertidal systems provide important ecosystem services including food production, coastal protection, and tourism, it is critical to understand how warming (both air and ocean), acidification, and altered community states affect reef-scale ecosystem metabolism. While information exists on responses of a variety of individual intertidal taxa to temperature stress, ocean acidification, and habitat loss, there is notably less on the response of ecosystem metabolism (e.g. NEP and NEC) to these stressors. This proposed work is focused on a series of conceptual knowledge gaps and tests mechanisms through which different warming regimes, lowered pH, and community disturbance lead to altered community metabolism and ultimately affect ecosystem function. Specifically, this study: 1) Describes community thermal performance curves of multiple ecosystem functions under differing pH conditions in experimental mesocosms, 2) characterizes drivers of ecosystem functioning (e.g. Net Ecosystem Production [NEP] and Net Ecosystem Calcification [NEC]) in situ using natural changes in environmental variability before and after a disturbance, and 3) integrates 16 years of publicly available community composition and environmental time-series data with lab and field data to hindcast ecosystem metabolic rates and predict how ecosystem metabolism may change in the future.</p> <p>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.</p> TIDES largerWorkCitation project eng; USA oceans -124.066111 -124.066111 44.752528 44.752528 2019-07-09 2019-08-06 California, USA 0 BCO-DMO catalogue of parameters from Results of a study examining how foundation species loss alters fDOM and heterotrophic bacteria counts based on sampling of tidepools in the Otter Rock Marine Reserve (ORMR) and Marine Garden, Oregon USA from June to August 2019 Biological and Chemical Oceanography Data Management Office (BCO-DMO) Unavailable 508-289-2009 WHOI MS#36 Woods Hole MA 02543 USA info@bco-dmo.org http://www.bco-dmo.org Monday - Friday 8:00am - 5:00pm For questions regarding this resource, please contact BCO-DMO via the email address provided. pointOfContact http://lod.bco-dmo.org/id/dataset-parameter/1009829.rdf Name: ISO_DateTime_UTC Units: unitless Description: <p>Datetime of sample collection in UTC derived from the local date and time values.</p> http://lod.bco-dmo.org/id/dataset-parameter/1009831.rdf Name: pool_id Units: unitless Description: <p>Unique identifier for each experimental tide pool or ocean reference sample.</p> http://lod.bco-dmo.org/id/dataset-parameter/1009832.rdf Name: foundation_spp Units: unitless Description: <p>Dominant foundation species associated with the sampling location (e.g., Phyllospadix, Mytilus, Ocean).</p> http://lod.bco-dmo.org/id/dataset-parameter/1009833.rdf Name: LSID Units: unitless Description: <p>LSID of foundation_spp value.</p> http://lod.bco-dmo.org/id/dataset-parameter/1009834.rdf Name: aphiaID Units: unitless Description: <p>AphiaID of foundation_spp value</p> http://lod.bco-dmo.org/id/dataset-parameter/1009835.rdf Name: day_night Units: unitless Description: <p>This field indicates if sampling took place during the day or at night.</p> http://lod.bco-dmo.org/id/dataset-parameter/1009836.rdf Name: before_after Units: unitless Description: <p>Sampling period before or after experimental foundation species removal.</p> http://lod.bco-dmo.org/id/dataset-parameter/1009837.rdf Name: removal_control Units: unitless Description: <p>Experimental treatment indicating removal or control plot.</p> http://lod.bco-dmo.org/id/dataset-parameter/1009838.rdf Name: time_point Units: unitless Description: <p>Unique sampling event inidicating the start or end of low tide</p> http://lod.bco-dmo.org/id/dataset-parameter/1009839.rdf Name: sampling_date Units: unitless Description: <p>Calendar day on which the sample was collected.</p> http://lod.bco-dmo.org/id/dataset-parameter/1009840.rdf Name: sampling_time_local Units: unitless Description: <p>Time of sample collection. Pacific Time.</p> http://lod.bco-dmo.org/id/dataset-parameter/1009841.rdf Name: heterotrophic_bacterioplankton_micro_l Units: cells uL^-1 Description: <p>Abundance of heterotrophic bacterioplankton measured by flow cytometry.</p> http://lod.bco-dmo.org/id/dataset-parameter/1009842.rdf Name: m_c Units: unitless Description: <p>Freshness Index (M:C) ratio derived from fluorescence excitation-emission matrices measured with a HORIBA Aqualog fluorometer.</p> http://lod.bco-dmo.org/id/dataset-parameter/1009843.rdf Name: bix Units: unitless Description: <p>Biological Index (BIX) calculated from fluorescence excitation-emission matrices as an indicator of recently produced dissolved organic matter.</p> GB/NERC/BODC > British Oceanographic Data Centre, Natural Environment Research Council, United Kingdom Biological and Chemical Oceanography Data Management Office (BCO-DMO) Unavailable 508-289-2009 WHOI MS#36 Woods Hole MA 02543 USA info@bco-dmo.org http://www.bco-dmo.org Monday - Friday 8:00am - 5:00pm For questions regarding this resource, please contact BCO-DMO via the email address provided. pointOfContact https://doi.org/10.26008/1912/bco-dmo.1009817.1 download onLine dataset &lt;p&gt;&amp;nbsp;fDOM samples were stored in amber glass vials at 4 °C until further processing. Heterotrophic bacterial counts were taken from 1.5 mL unfiltered seawater and stored in 0.5% paraformaldehyde (amended with 100 μL 8% ampulated paraformaldehyde, Electron MicroscopySciences, Hatfield, PA, USA) in a 2 mL polypropylene cryovial, mixed briefly and then frozen to -20 °C. All storage vials were triple rinsed with sample water prior to sample storage. fDOM samples were processed on a Horiba Aqualog scanning fluorometer with 1 cm quartz cuvettes at the University of Hawai’i at Mānoa following Nelson et al. (2015).&lt;/p&gt; &lt;p&gt;All samples were brought to room temperature prior to analysis. Prior to running samples, cuvettes were washed thoroughly with DI water and wiped clear with Kim wipes. Cuvettes were triple rinsed with DI between each sample. A DI blank was run after every 7 samples. Excitation-Emission Matrices (EEMS) were generated with excitation values ranging from 240 nm to 500 nm and emission values were measured ranging from 250 nm to 825 nm.&lt;/p&gt; &lt;p&gt;Excitation wavelengths were increased at 5 nm increments and measurements were integrated over 4 s at each increment. Inner filter correction was applied to account for fluorescence quenching by absorbance (Kothawala &lt;em&gt;et al.&lt;/em&gt; 2013). Fluorescence values were scaled to Raman Units by dividing by the integrated emission range of 381 nm to 426 nm at an excitation of 350 nm in averaged DI blanks. The average blank EEMs, from DI blanks run immediately before and after each set of samples, were subtracted from the sample EEMs.&lt;/p&gt; &lt;p&gt;Two biogeochemical informative indices were calculated for this study which included M:C (the relative amount of marine to terrestrial humics) (Burdige &lt;em&gt;et al.&lt;/em&gt; 2004) and BIX (biological index) (Huguet &lt;em&gt;et al.&lt;/em&gt; 2009). Heterotrophic bacterial counts were analyzed using flow cytometry on an Attune Acoustic Focusing Cytometer with Autosampler Attachment (Life Technologies, Eugene, OR, USA) with methods following Nelson et al. (2015)&lt;em&gt;.&lt;/em&gt;&lt;/p&gt; &lt;p&gt;Flow cytometry samples were analyzed on fixed 1ml samples run on a Cytoflex Flow Cytometer stained with 7 μL of 40 μL mL&lt;sup&gt;−1&lt;/sup&gt; Hoechst 34580 (1 μg mL&lt;sup&gt;−1&lt;/sup&gt; , final concentration) following standard protocols (Nelson &lt;em&gt;et al.&lt;/em&gt; 2015; Selph 2021)&lt;em&gt;.&lt;/em&gt;&lt;/p&gt; &lt;p&gt;Stained cells were distinguished from instrument noise using stained and unstained blank water, and autofluorescent cells containing phytopigments were subtracted from the total to derive the subset of heterotrophic bacterioplankton.&lt;/p&gt; Specified by the Principal Investigator(s) &lt;p&gt;R code and data files used for statistical analysis and figure generation for the results publication Silbiger et al. (2025). The fDOM and heterotrophic bacteria in this BCO-DMO dataset were incorporated into the joined data file used for analysis and plotting. &amp;nbsp;All data and code are available at https://github.com/njsilbiger/Intertidal-Benthic-Pelagic and at https://doi.org/10.5281/zenodo.17717287 on Zenodo (Silbiger 2025).&lt;/p&gt; Specified by the Principal Investigator(s) Curation Actions Performed on Data File - Loaded fDOM_bacteria_Silbiger2026.csv using the first row as headers and treating empty strings and NA as missing values. The table was named 1009817_v1_tidal_fdom_and_heterotrophic_bacteria_counts. - Converted sampling_day to a date formatted as %Y-%m-%d and sampling_time to a time formatted as %H:%M:%S. Renamed these fields to sampling_date and sampling_time_local, respectively. - Combined the local sampling date and time, interpreted in the Canada/Pacific timezone, into a new ISO_DateTime_UTC field formatted as %Y-%m-%dT%H:%M:%SZ. - Standardized column order and assigned appropriate data types, including strings for categorical and identifier fields, numbers for bacterial counts and fluorescence-related measurements, and date, time, and datetime types for temporal fields. - Added taxonomic metadata based on foundation_spp: LSIDs and AphiaIDs for Mytilus and Phyllospadix, with &quot;none&quot; for Ocean samples. Taxonomic level and status values were also evaluated during processing. - Removed the intermediate taxon_level, status, and rand columns and finalized the column order and data types. - Updated parameter metadata, including descriptions, standard names, and units, and designated ISO_DateTime_UTC as a primary parameter. - Saved the processed data as 1009817_v1_tidal_fdom_and_heterotrophic_bacteria_counts.csv. Specified by BCO-DMO Data Managers asNeeded 7.x-1.1 Biological and Chemical Oceanography Data Management Office (BCO-DMO) Unavailable 508-289-2009 WHOI MS#36 Woods Hole MA 02543 USA info@bco-dmo.org http://www.bco-dmo.org Monday - Friday 8:00am - 5:00pm For questions regarding this resource, please contact BCO-DMO via the email address provided. pointOfContact Cytoflex Flow Cytometer Cytoflex Flow Cytometer PI Supplied Instrument Name: Cytoflex Flow Cytometer PI Supplied Instrument Description:Used for flow cytometric quantification of microbial cells in water samples based on fluorescence and light scatter characteristics. Data acquisition and analysis were performed using CytExpert software. The CytoFLEX platform utilizes avalanche photodiode (APD) detectors for high-sensitivity fluorescence detection.  Calibration: Instrument performance was verified using the manufacturer's daily quality control (QC) procedures with fluorescent calibration beads according to Beckman Coulter recommendations prior to sample analysis.   Instrument Name: Flow Cytometer Instrument Short Name:Flow Cytometer Instrument Description: Flow cytometers (FC or FCM) are automated instruments that quantitate properties of single cells, one cell at a time. They can measure cell size, cell granularity, the amounts of cell components such as total DNA, newly synthesized DNA, gene expression as the amount messenger RNA for a particular gene, amounts of specific surface receptors, amounts of intracellular proteins, or transient signalling events in living cells. Description from: http://www.bio.umass.edu/micro/immunology/facs542/facswhat.htm Community Standard Description: http://vocab.nerc.ac.uk/collection/L05/current/LAB37/ Horiba Aqualog Scanning Fluorometer Horiba Aqualog Scanning Fluorometer PI Supplied Instrument Name: Horiba Aqualog Scanning Fluorometer PI Supplied Instrument Description:Manufacturer: HORIBA Scientific Model: Aqualog® Scanning Fluorometer Purpose: Used to measure excitation-emission matrices (EEMs) and absorbance spectra of fluorescent dissolved organic matter (fDOM) in water samples.  Calibration: Instrument calibration was performed using HORIBA-recommended procedures, including quinine sulfate fluorescence standardization and wavelength/intensity calibration as appropriate. Instrument software automatically applies corrections for inner-filter effects and Rayleigh/Raman scattering. Instrument Name: Fluorometer Instrument Short Name:Fluorometer Instrument Description: A fluorometer or fluorimeter is a device used to measure parameters of fluorescence: its intensity and wavelength distribution of emission spectrum after excitation by a certain spectrum of light. The instrument is designed to measure the amount of stimulated electromagnetic radiation produced by pulses of electromagnetic radiation emitted into a water sample or in situ. Community Standard Description: http://vocab.nerc.ac.uk/collection/L05/current/113/