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Estimates of nitrogen and phosphorus excretion rates in individual marine and estuarine animals

General Information
Data Package:
Local Identifier:knb-lter-sbc.172.8
Title:Estimates of nitrogen and phosphorus excretion rates in individual marine and estuarine animals
Alternate Identifier:DOI PLACE HOLDER
Abstract:

This dataset contains nitrogen and phosphorus excretion rate, as well as dry biomass, estimates for individual vertebrate and invertebrate animals in marine and estuarine environments. This dataset is a product of an LTER Synthesis Working Group aimed at evaluating the spatiotemporal variability in consumer nutrient dynamics in the wake of global change across eight long-term ecological research projects. These projects include seven long-term ecological research programs (LTER) funded by the National Science Foundation: (1) California Current Ecosystem, (2) Florida Coastal Everglades, (3) Moorea Coral Reef, (4) Northern Gulf of Alaska, (5) Plum Island Ecosystems, (6) Santa Barbara Coastal, and (7) Virginia Coast Reserve LTER projects. Additionally, the dataset includes data from (8) The Partnership for Interdisciplinary Science of Coastal Oceans (PISCO) research program. The temporal coverage of each time series data varies among projects, with the earliest record in 1999 and the most recent in 2023.

This data package also includes five R scripts used for data harmonization, identical to those in the Initial Release of the LTER Synthesis Working Group: Consumer-Mediated Nutrient Dynamics Project, v1.0.0. You can find the release in GitHub here: https://github.com/lter/lterwg-marine-cnd/releases/tag/v1.0.0.

Short Name:Nitrogen and phosphorus excretion rates
Publication Date:2024-06-26
Language:English
For more information:
Visit: https://sbclter.msi.ucsb.edu/
Visit: DOI PLACE HOLDER

Time Period
Begin:
1999-09-07
End:
2023-07-26

People and Organizations
Contact:Santa Barbara Coastal LTER [  email ]
Creator:White, Mack 
Creator:Kui, Li 
Creator:Chen, Angel 
Creator:Strickland, Bradley 
Creator:Peters, Joey 
Creator:Grier, Shalanda 
Creator:Capone, Dante 
Creator:Cawley, Grace 
Creator:Emery, Kyle A 
Creator:Enright, Lauren N 
Creator:Stajner, Anya 
Creator:Caselle, Jennifer 
Creator:Hopcroft, Russell 
Creator:Rehage, Jennifer 
Creator:Burkepile, Deron 
Creator:Lyon, Nicholas 
Organization:Santa Barbara Coastal LTER

Data Entities
Data Table Name:
Consumer excretion rate
Description:
Nitrogen and phosphorus excretion rates and dry biomass estimates for individual vertebrate and invertebrate animals
Other Name:
R scripts
Description:
Five R scripts used for process the consumer excretion rate dataset
Detailed Metadata

Data Entities


Data Table

Data:https://pasta-s.lternet.edu/package/data/eml/knb-lter-sbc/172/8/9fc5a5a28e42b885ae8b7af2e6eb5d51
Name:Consumer excretion rate
Description:Nitrogen and phosphorus excretion rates and dry biomass estimates for individual vertebrate and invertebrate animals
Number of Records:1863096
Number of Columns:31

Table Structure
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Table Column Descriptions
 ProjectHabitatraw filenameRow numberyearCalendar MonthCalendar DayDateSite codeSubsite level1Subsite level2Subsite level3Species codeScientific nameScientific nameCommon NameKingdomPhylumClassOrderFamilyGenusOrganism GroupDiet categoryDensity in num/mIndividual Dry MassTemperature in CDensity in num/m2Density in num/m3Nitrogen excretion ratePhosphorus excretion rate
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habitat  
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year  
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kingdom  
phylum  
class  
order  
family  
genus  
taxa_group  
diet_cat  
density_num/m  
dmperind_g/ind  
temp_c  
density_num/m2  
density_num/m3  
nind_ug/hr  
pind_ug/hr  
Definition:Projects includes the seven LTER sites and the coastalCA site from the PISCO projectHabitat that the data were collectedRaw data file names as we received/ downloaded themThe row number within each raw fileYear of measurementmonth of sampling formatted as MMday of sampling formatted as DDDate of the samplingSite code within each of the projectSubsite at level 1 within each of the projectSubsite at level 2 within each of the projectSubsite at level 3 within each of the projectSpecies code from individual projectTaxonomic scientific name that matches the ITIS databaseTaxonomic scientific name originated from individual projectcommon name of the organismKingdom name of taxon in Linnean taxanomic systemPhylum name of taxon in Linnean taxanomic systemClass name of taxon in Linnean taxanomic systemOrder name of taxon in Linnean taxanomic systemFamily name of taxon in Linnean taxanomic systemGenus name of taxon in Linnean taxanomic systemFunctional grouping term for observed taxonDiet catagory for observed taxonThe density taxon per meterDry biomass per individualAverage temperature in degreeCThe density taxon per squared meterThe density taxon per cubic meterNitrogen excretion rate per individualPhosphorus excretion rate per individual
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Accuracy Report:                                                              
Accuracy Assessment:                                                              
Coverage:                                                              
Methods:                                                              

Non-Categorized Data Resource

Name:R scripts
Entity Type:otherEntity
Description:Five R scripts used for process the consumer excretion rate dataset
Physical Structure Description:
Object Name:data_wrangling_script.zip
Size:28846 byte
Authentication:7d1dd9ad955d6f93ff79ea79b9aa0154 Calculated By MD5
Externally Defined Format:
Format Name:ZIP
Data:https://pasta-s.lternet.edu/package/data/eml/knb-lter-sbc/172/8/195fe21811a0b870f006a90e6c65f6cb

Data Package Usage Rights

This data package is released under the Creative Commons License Attribution 4.0 International (CC BY 4.0, see https://creativecommons.org/licenses/by/4.0/). This license states that consumers ("Data Users" herein) may distribute, adapt, reuse, remix, and build upon this work, as long as they give appropriate credit, provide a link to the license, and indicate if changes were made. If redistributed, a Data User may not apply additional restrictions or technological measures that prevent access.

The Data User has an ethical obligation to cite the data source appropriately in any publication or product that results from its use, and notify the data contact or creator. Communication, collaboration, or co-authorship (as appropriate) with the creators of this data package is encouraged to prevent duplicate research or publication. The Data User is urged to contact the authors of these data if any questions about methodology or results occur. The Data User should realize that these data may be actively used by others for ongoing research and that coordination may be necessary to prevent duplication or inappropriate use. The Data User should realize that misinterpretation may occur if data are used outside of the context of the original study. The Data User should be aware that data are updated periodically and it is the responsibility of the Data User to check for new versions of the data.

While substantial efforts are made to ensure the accuracy of data and associated documentation, complete accuracy of data sets cannot be guaranteed. This data package (with its components) is made available “as is” and with no warranty of accuracy or fitness for use. The creators of this data package and the repository where these data were obtained shall not be liable for any damages resulting from misinterpretation, use or misuse of the data package or its components.

Keywords

By Thesaurus:
LTER Controlled Vocabulary v1Air Temperature, long term ecological research, marine, organism, phosphorus
SBC-LTER Controlled VocabularyEcosystem Processes, Nearshore Ocean
Global Change Master Directory (GCMD) v6.0.0.0.0Air Temperature, Nitrogen, Nutrients
Knowledge Network for BiocomplexityNutrients
NBII BiocomplexityAquatic organisms, Nutrients
noneconsumer-derived nutrients, consumers, excretion, nutrient recycling, nutrient regeneration

Methods and Protocols

These methods, instrumentation and/or protocols apply to all data in this dataset:

Methods and protocols used in the collection of this data package
Description:

The dataset includes nitrogen and phosphorus excretion rate estimates from eight research programs and spans observations from 1999 to 2023. The appropriate datasets were identified during the 2022 LTER All-Scientists Meeting in Monterey, California. For information on dataset provenance, please see the Data Source section below. Datasets assessed for inclusion in working group efforts required size measurements (i.e., either mass or length) at the individual species level, alongside animal density estimates (# per unit area), in order to estimate nitrogen and phosphorus excretion rates using universal models published by Vanni & McIntyre (2016). These models required the following information to estimate excretion for individual animals: (1) individual dry biomass, (2) temperature, (3) vertebrate-invertebrate classification, and (4) coarse trophic guild categorization. For projects that recorded individual biomass but had missing values (i.e., due to field or data entry errors), we calculated the average mass for the given species within the program to estimate individual mass. For datasets that had length but no mass measurements, mass was calculated using length-weight coefficients published on FishBase or SeaLifeBase. Dry biomass was calculated for all individuals using project-level coefficients. In cases where wet-dry biomass coefficients were not available at the site, published coefficients were used to convert wet to dry mass. Temperature was held constant across each of the projects using mean water (for aquatic organisms) or air (for terrestrial organisms) temperature during the sampling period, using environmental data from the respective projects. Taxonomic classifications were determined using the taxize package in R, and the information was used to determine whether vertebrate or invertebrate coefficients were to be used in excretion rate calculations. Individual species were assigned to one of five trophic guilds (i.e., algivore/detritivore, invertivore, piscivore, piscivore/invertivore, and algivore/detritivore/insectivore/piscivore). The trophic guild of individual species was determined by project experts from each of the respective research programs. Once individual datasets contained the necessary information for excretion rate calculations, we performed zero-filled to permit calculation of areal excretion rate estimates for nitrogen and phosphorus in the unit of μg/m^2/hr. Next, standard column names were assigned to individual dataset in the data integration process.

Sampling method for each program:

FCE

Florida Coastal Everglades LTER (FCE) is a subtropical estuary in southwest Florida, USA. FCE has collected fish community data since 2004. Sampling occurs throughout the year at 15 fixed sites across the upper Shark River and Tarpon Bay, a large shallow estuarine bay. Three primary sampling events occur at the end of the wet season when water levels are at or near peak (i.e., November or December), during transitional periods when water levels are intermediate (i.e., February or March), and when water levels are at or near lows (i.e., April, May, or June). Fish are sampled using standardized electrofishing along three 100 m transects at each of the sites resulting in a total of 45 transects shocked during primary sampling events. Additional monthly samples are collected during the dry season during months not covered by the primary sampling at a subset (n = 5) of sites in the upper river to monitor inter- and intra-annual variability in community composition at the marsh-mangrove interface as marsh taxa seek refuge from desiccation as a result of falling water levels in adjacent marsh habitats, and estuarine taxa track the resulting prey subsidy. Collected fish are identified to species, measured (i.e., length to nearest mm and weight to nearest mg), and released at the approximate point of capture. An extreme cold event in South Florida during January 2010 caused mass mortality in tropical fishes and shifted community structure (Boucek et al., 2013). In September 2017, Hurricane Irma brought devastating wind, rain, and storm surge to FCE as the eye passed within 60 km of Shark River (Massie et al. 2019). The storm had major impacts on the distribution and movement of several large-bodied estuarine consumers across the estuary. Further, extreme drought events in 2010 and 2015 had large effects on community structure and biomass as a result of greatly diminished production in adjacent marsh habitats (Boucek et al., 2013; Boucek et al., 2016).

PISCO

The Partnership for Interdisciplinary Studies of Coastal Oceans (PISCO) conducts long-term and large-scale studies to understand the functioning of the coastal marine ecosystem along the U.S. west coast, focused on the biological and oceanographic drivers of rocky intertidal and kelp forest ecosystems. Here we focus on kelp forest and rocky reef fishes in central and southern California (Malone et al. 2021). Surveys are conducted annually, generally from June to late October from 1999 through present. To comprehensively and quantitatively characterize the ecological community and geological features at each kelp forest site, five different sampling methods are employed, all of which are conducted visually by SCUBA divers. Sites are surveyed for fishes and benthic organisms separately, with differing transect replication for the two methods. Transects are laid in a stratified random design with non-fixed transects at specified locations (sites) and targeted depth zones. The number and arrangement of these zones depends on the width and slope of the rocky reef at each site. Fish transects and benthic macroalgae and invertebrate transects overlap with, but are spatially distinct from one another. 

The density of all conspicuous fishes (i.e., species whose adults are longer than 10 cm and visually detectable by SCUBA divers) are visually recorded along replicate 2m wide by 2m tall by 30m long transects. In pairs, one diver surveys this volume along the reef surface (searching within cracks and crevices), while other surveys the same volume roughly one third to one half up into the water column (i.e., “mid-water”) above the benthic diver, depending on visibility and bottom depth. Canopy transects of the same dimensions as the mid-water and bottom transects are surveyed at a subset of sites, mainly to target juvenile fish recruiting to the kelp canopy. Canopy transects are only done where kelp canopy extends to the surface and are usually completed separately from the bottom and midwater transects. Typically, for each portion of the water column sampled, three 30m long transects are distributed end-to-end and 5-10m apart at each of the 5m, 10m, 15m, and 20m isobaths. At sites with narrow kelp beds, particularly in parts of the Northern Channel Islands, only two zones are sampled, with four transects in each depth zone for a total of eight replicate transects. Counts on mid-water and bottom transects are eventually combined, thereby generating 8-12 replicate transects for each site for analyses. Fish transects are generally only conducted with at least 3m of horizontal visibility. The total length (TL) of each fish observed is estimated to the closest 1cm. For each transect, divers record the transect depth, horizontal visibility along each transect, water temperature, and sea state (surge), and percent of the transect volume occupied by kelp.

SBC

The Santa Barbara Coastal LTER (SBC) consists of nearshore rocky reefs dominated by giant kelp (Macrocystis pyrifera) and sandy beaches in the Santa Barbara Channel, California, USA. SBC’s focus is on understanding the ecology of nearshore kelp forests and their connectivity to adjacent coastal ecosystems. Giant kelp, as a foundation species, facilitate high biodiversity and abundance of sessile and mobile invertebrates as well as numerous fish and elasmobranch species (Millers et al. 2018). Annual kelp forest biodiversity monitoring began in 2000 and consists of diver surveys of benthic invertebrate and fish at 11 study sites in replicate, fixed 40 m by 2 m transects (See the data source for SBC dataset). Along each transect, divers count and estimate size of organisms within each transect. Fish surveys are restricted to two meters above the bottom. Species-specific biomass values are estimated from size measurements using allometric relationships (Nelson et al. 2021). Export of giant kelp NPP to adjacent sandy beach ecosystems serves as the base of the food web for this ecosystem which has little to no in situ primary production. SBC began conducting regular surveys at two sandy beach sites in 2013 (~ every six to eight weeks) of kelp wrack consumer (beach hoppers, Megalorchestia spp.) populations. Sediment cores (n = 10) are collected along three replicate transects, sieved, and frozen. In the laboratory, samples are sorted to species level, counted, and weighed to the nearest mg (wet weight). To test the sensitivity of our universal excretion estimates, we compared them to empirical excretion data for kelp forest benthic invertebrates (Peters et al. 2019) and sandy beach invertebrates (Lowman et al. 2019). 

CCE

The California Current Ecosystem (CCE) LTER is a pelagic eastern boundary current upwelling biome (32.8736, -120.28) along the California, USA coast. The site was established in 2004, building upon the historic California Cooperative Oceanic Fisheries Investigations (CalCOFI) time series (1949–present). Biological and hydrographic data are collected by both CalCOFI (quarterly) and the CCE-LTER program (every 2-3 years). The CalCOFI sampling grid consists of 6 lines extending from onshore to offshore, with onshore stations spaced 20 nautical miles (nm) and offshore spaced 40 nm apart. From the grid, Line 80 and Line 90 are sampled for mesozooplankton analysis. Mesozooplankton (>0.2 mm) were collected during quarterly CalCOFI cruises (2005–present) using a 50 cm diameter, 202 µm mesh, 3 m length PRPOOS (Planktonic Rate Processes in Oligotrophic Ocean Systems) Net. The net collects an integrated zooplankton community down to 210 m depth (using a descent rate of 40 m/min, held at depth for 20 sec, and then an ascent rate of 50 m/min). Upon collection, zooplankton are preserved in formaldehyde and maintained in the Scripps Institution of Oceanography Pelagic Invertebrate Collection. Zooplankton samples preserved in formaldehyde were imaged using a Zoooscan (Gorsky et al., 2010). Measurements of abundance (individuals/m2) estimated carbon biomass (mgC/m2), ferret diameter (mm), and individual carbon content (µg/individual) were downloaded from Zooscan Database on January 24th, 2024 for appendicularians, bryozoan larvae, chaetognaths, calanoid copepods, eucalanid copepods, harpacticoid copepods, oithona-like copepods, poecilostomatoid copepods, other copepods, other crustaceans, doliolids, euphausiids, ostracods, polychaetes, pteropods, pyrosomes, rhizarians, and salps. Measurements of individual carbon content (were transformed into dry mass (g/individual) to compare to other sites biomass data, using conversations rates in literature (Brey et al. 1988; Mansour et al. 2021; Uye 1982; Larson 1986). 

MCR

The Moorea Coral Reef LTER (MCR-LTER) is a tropical coral reef ecosystem in Moorea, French Polynesia (17°30 S, 149°50 W), located in the central South Pacific. Since 2005, the MCR-LTER has conducted ongoing fish surveys as a part of the MCR-LTER fish monitoring program. Annual fish surveys are conducted during the dry season from late July to early August between 0900 and 1600 hours (local time) on SCUBA. Fish are counted at 4 replicate transects 50m in length, across coral reef types. The island of Moorea has three distinct sides North, Southeast and Southwest. Fish are surveyed on all three sides of the island at two locations on the fringing reef, backreef and forereef for a total of 72 individual surveys. Annual fish surveys conducted on the fringing reef, back reef and fore reef are completed at a depth of 1.5m, 10m and 12m, respectively. To better estimate the fish community and promote diver safety two divers perform the fish survey using two swaths (one swath per diver). A 5m and 1m swaths are used at each transect to count mobile fish and cryptic fish species. However, prior to 2021 all fish surveys were completed by a single diver on SCUBA using a 5m swath. For each transect, species abundance and estimated sizes of fishes are recorded. Additional data collected at each transect are wind, sea state, swell height, cloud cover, and visibility. 

         From 2007-2009, a crown of thorns sea star outbreak caused massed coral mortality events on the island of Moorea. This outbreak affected sites across the island resulting in significant coral mortality and shifts in the fish community (Adam et al 2014). In 2010, Moorea experienced a severe tropical cyclone event that significantly decreased live coral cover at sites along the N shore. This loss in coral structure had a large impact on fish functional groups that depend on coral structure such as coral dwellers and corallivores (Adam et al. 2014) In 2019, there was an extreme heat wave that resulted in mass mortality of large coral colonies (Speare et al. 2022). 

NGA

Northern Gulf of Alaska (NGA LTER) research cruises conducted in the Gulf of Alaska in 1997-2022. The data were collected to determine the distribution, abundance and biomass of zooplankton from traditional microscopy on samples obtained from a Multinet samples and QuadNet. For Multinet sampling, a 0.25-m2 Hydrobios Multinet system with 0.5 mm mesh nets were fished at night to assess large zooplankton and micronekton such as euphausiids that are important components in the diet of many fish, sea-birds and marine mammals. Night-time collections are essential to collect diel migrators and minimize avoids by higher-speed visually-responsive species. The Multinet is equipped with five nets that can be programmed to open and close at specific depths, or opened and closed electronically from the deck if a conducting cable is available. Depth, flow meter counts, and volume filtered are recorded at 1 second intervals. Prior to 2018, at each station, 5 samples were collected at 20 m depth intervals from 100 m depth to the surface. Starting in 2018, stratified were modified to 200-100-60-40-20-0 m. All zooplankton samples were preserved in 10% formalin for later analysis by microscopy to the lowest taxonomic category possible. For QuadNet, Day-time zooplankton samples were collected with a Quadnet consisting of two 25 cm diameter, 150 um mesh nets and two 25 cm diameter, 53 um mesh nets (all aspect ratios 10:1) equipped with General Oceanics flowmeters that were towed vertically through the water column from a target depth of 100 meters to the surface. All samples were immediately preserved in 10% formalin for later analysis.

The zooplankton samples were processed as follows: Each sample was poured into a sorting tray and large organisms, primarily shrimp and jelly fish, were removed and enumerated. The sample was then sequentially split using a Folsom splitter until the smallest subsample contained about 100 specimens of the most abundant taxa. The individual organisms were identified and measured using a microscope and a digitizing tablet. Each larger subsample was examined to identify and enumerate the larger, less abundant taxa, while ceasing to consider those adequately enumerated in prior subsamples. Abundance was calculated from the counts of each taxon in the sample fraction divided by the volume of water filtered by the net. Wet weights were calculated from existing in-house length-weight equations, or where they did not exist, from direct weights.

Data Source:

Florida Coastal Everglades: https://pasta.lternet.edu/package/data/eml/knb-lter-fce/1164/12/de8a81c56378979f369fff30bbde9f01

Moorea Coral Reef: https://doi.org/10.6073/pasta/75644add7e7f90c568bf5045264d359a

Plum Island Ecosystems: https://doi.org/10.6073/pasta/de6b4cbb10fa240a63c95ffdd6152432

Santa Barbara Coastal (ocean): https://doi.org/10.6073/pasta/9ddf2268b69115670be27cdfd29ad104

Santa Barbara Coastal (beach): https://doi.org/10.6073/pasta/d84164f4099a98817e3f0afa49546b94

Virginia Coast Reserve: https://portal.edirepository.org/nis/mapbrowse?packageid=knb-lter-vcr.236.14

The Partnership for Interdisciplinary Science of Coastal Oceans (PISCO): https://doi.org/10.25494/P6/MLPA_kelpforest.5

California Current Ecosystem:

https://oceaninformatics.ucsd.edu/zooscandb/secure/login.php

Plankton sample analysis supported by NSF grants to M.D. Ohman, Scripps Institution of Oceanography and by the CCE-LTER site.

Northern Gulf of Alaska (The data from 2018-2021 were published on DataOne):

Russell Hopcroft. (2021). Zooplankton abundance and biomass observations obtained from the QuadNet, as analyzed by traditional microscopy, during NGA LTER seasonal cruises in the Northern Gulf of Alaska, 2018-2021. Research Workspace. 10.24431/rw1k587, version: 10.24431_rw1k587_20230930T230143Z.

Russell Hopcroft. (2021). Zooplankton abundance and biomass observations determined traditional microscopy, from Multinet samples collected during research cruises for the Northern Gulf of Alaska LTER site, 2018-2021. Research Workspace. 10.24431/rw1k591, version: 10.24431_rw1k591_20230930T225433Z.

References:

Vanni, M. J., & McIntyre, P. B. (2016). Predicting nutrient excretion of aquatic animals with metabolic ecology and ecological stoichiometry: A global synthesis. Ecology, 97(12), 3460–3471. https://doi.org/10.1002/ecy.1582

Massie JA, Strickland BA, Santos R, Hernandez J, Viadero N, Boucek RE, Willoughby H, Heithaus MR, Rehage JS. Going downriver: patterns and cues in hurricane-driven movements of common snook in a coastal river. Estuar Coasts. 2019. https://doi.org/10.1007/s12237-019-00617-y.

Malone, Daniel P., Kathryn Davis, Steve I. Lonhart, Avrey Parsons-Field, Jennifer E. Caselle, and Mark H. Carr. 2022. Large-Scale, Multidecade Monitoring Data from Kelp Forest Ecosystems in California and Oregon (USA). Ecology, 103(5): e3630. https://doi.org/10.1002/ecy.3630

Miller, R. J., Lafferty, K. D., Lamy, T., Kui, L., Rassweiler, A., Reed, D. C. (2018). Giant Kelp, Macrocystis pyrifera, Increases Faunal Diversity Through Physical Engineering. Proceedings of the Royal Society B: Biological Sciences. 285:20172571. DOI: 10.1098/rspb.2017.2571

Nelson, C, D. Reed, S. Harrer, R. Miller. 2021. SBC LTER: Reef: Coefficients for estimating biomass from body size or percent cover for kelp forest species ver 3. Environmental Data Initiative. https://doi.org/10.6073/pasta/0fe9233dabe35df5d61fb3b07f8fb51e

Peters, J. R., Reed, D. C., Burkepile, D. E. (2019). Climate and fishing drive regime shifts in consumer-mediated nutrient cycling in kelp forests. Global Change Biology. 25:3179--3192. DOI: 10.1111/gcb.14706

Lowman, H. E., Emery, K. A., Kubler-Dudgeon, L., Dugan, J. E., Melack, J. M. (2019). Contribution of Macroalgal Wrack Consumers to Dissolved Inorganic Nitrogen Concentrations in Intertidal Pore Waters of Sandy Beaches. Estuarine, Coastal and Shelf Science. 219:363 - 371. DOI: 10.1016/j.ecss.2019.02.004

Adam, T. C., Brooks, A. J., Holbrook, S. J., Schmitt, R. J., Washburn, L., & Bernardi, G. (2014). How will coral reef fish communities respond to climate-driven disturbances? Insight from landscape-scale perturbations. Oecologia, 176, 285-296.

 

Speare, K. E., Adam, T. C., Winslow, E. M., Lenihan, H. S., & Burkepile, D. E. (2022). Size‐dependent mortality of corals during marine heatwave erodes recovery capacity of a coral reef. Global Change Biology, 28(4), 1342-1358.

Brey, T., Rumohr, H. and Ankar, S., 1988. Energy content of macrobenthic invertebrates: general conversion factors from weight to energy. Journal of Experimental Marine Biology and Ecology, 117(3), pp.271-278.

Mansour, J.S., Norlin, A., Llopis Monferrer, N., L'Helguen, S. and Not, F., 2021. Carbon and nitrogen content to biovolume relationships for marine protist of the Rhizaria lineage (Radiolaria and Phaeodaria). Limnology and Oceanography, 66(5), pp.1703-1717.

Uye, S.I., 1982. Length-weight relationships of important zooplankton from the Inland Sea of Japan. Journal of the Oceanographical Society of Japan, 38, pp.149-158.

Larson RJ (1986) Water content, organic content, and carbon and nitrogen composition of medusae from the northeast Pacific. J Exp Mar Bio Ecol 99(2): 107–120.

Gorsky, G., Ohman, M.D., Picheral, M., Gasparini, S., Stemmann, L., Romagnan, J.B., Cawood, A., Pesant, S., García-Comas, C. and Prejger, F., 2010. Digital zooplankton image analysis using the ZooScan integrated system. Journal of plankton research, 32(3), pp.285-303.

People and Organizations

Publishers:
Organization:Environmental Data Initiative
Email Address:
info@edirepository.org
Web Address:
https://edirepository.org
Id:https://ror.org/0330j0z60
Creators:
Individual: Mack White
Address:
Department of Earth & Environment Florida International University,
Miami, FL 33181 US
Email Address:
mwhite@fiu.edu
Id:https://orcid.org/0000-0002-6617-7023
Individual: Li Kui
Address:
Marine Science Institute University of California,
Santa Barbara, CA 93106-6150 US
Email Address:
lkui@ucsb.edu
Id:https://orcid.org/0000-0002-5894-4907
Individual: Angel Chen
Address:
National Center for Ecological Analysis and Synthesis University of California Santa Barbara,
Santa Barbara, CA 93101 US
Email Address:
anchen@nceas.ucsb.edu
Id:https://orcid.org/0000-0003-3515-6710
Individual: Bradley Strickland
Address:
National Park Service South Florida Natural Resources Center,
Homestead, FL 33033 US
Email Address:
bradley_strickland@nps.gov
Id:https://orcid.org/0000-0001-6443-7672
Individual: Joey Peters
Address:
Great Ecology,
San Diego, CA 92103
Email Address:
jpeters.ecology@gmail.com
Id:https://orcid.org/0000-0002-9625-1626
Individual: Shalanda Grier
Address:
Department of Ecology, Evolution and Marine Biology University of California,
Santa Barbara, CA 93106 US
Email Address:
shalandagrier@ucsb.edu
Id:https://orcid.org/0000-0002-9754-5482
Individual: Dante Capone
Address:
Scripps Institution of Oceanography Univeristy of California San Diego,
San Diego, CA 92093
Email Address:
dcapone@ucsd.edu
Id:https://orcid.org/0009-0005-1232-359X
Individual: Grace Cawley
Address:
Scripps Institution of Oceanography Univeristy of California San Diego,
San Diego, CA 92093
Email Address:
gcawley@ucsd.edu
Id:https://orcid.org/0000-0002-8813-1579
Individual: Kyle A Emery
Address:
Marine Science Institute University of California,
Santa Barbara, CA 93106 USA
Email Address:
emery@ucsb.edu
Id:https://orcid.org/0000-0003-0536-317X
Individual: Lauren N Enright
Address:
Department of Ecology, Evolution and Marine Biology University of California,
Santa Barbara, CA 93106 US
Email Address:
laurenenright@ucsb.edu
Id:https://orcid.org/0009-0007-2442-2805
Individual: Anya Stajner
Address:
Scripps Institution of Oceanography Univeristy of California San Diego,
San Diego, CA 92093
Email Address:
Astajner@ucsd.edu
Id:https://orcid.org/0000-0002-8755-5548
Individual: Jennifer Caselle
Address:
Marine Science Institute University of California,
Santa Barbara, CA 93106-6150 US
Email Address:
jenn.caselle@ucsb.edu
Id:https://orcid.org/0000-0002-1364-3123
Individual: Russell Hopcroft
Address:
Department of Oceanography University of Alaska Fairbanks,
Fairbanks, AK 99775 US
Email Address:
rrhopcroft@alaska.edu
Id:https://orcid.org/0000-0001-5021-6000
Individual: Jennifer Rehage
Address:
Department of Earth & Environment Florida International University,
Miami, FL 33181 US
Email Address:
rehagej@fiu.edu
Individual: Deron Burkepile
Address:
Marine Science Institute University of California,
Santa Barbara, CA 93106 US
Email Address:
deron.burkepile@lifesci.ucsb.edu
Id:https://orcid.org/0000-0002-0427-0484
Individual: Nicholas Lyon
Address:
National Center for Ecological Analysis and Synthesis University of California Santa Barbara,
Santa Barbara, CA 93101 US
Email Address:
lyon@nceas.ucsb.edu
Id:https://orcid.org/0000-0003-3905-1078
Contacts:
Organization:Santa Barbara Coastal LTER
Address:
Marine Science Institute,
University of California,
Santa Barbara, California 93106-6150 United States
Email Address:
sbclter@msi.ucsb.edu
Web Address:
https://sbclter.msi.ucsb.edu/
Id:https://ror.org/05hnkta08
Associated Parties:
Organization:Santa Barbara Coastal LTER
Address:
Marine Science Institute University of California,
Santa Barbara, CA 93106 USA
Email Address:
sbclter@msi.ucsb.edu
Role:publisher, curator

Temporal, Geographic and Taxonomic Coverage

Temporal, Geographic and/or Taxonomic information that applies to all data in this dataset:

Time Period
Begin:
1999-09-07
End:
2023-07-26
Geographic Region:
Description:Marine and estuarine environments: Marine and estuarine environments in the Pacific and Atlantic Ocean
Bounding Coordinates:
Northern:  59.05Southern:  -17.49
Western:  -149.83Eastern:  -70.89

Project

Parent Project Information:

Title:Santa Barbara Coastal Long Term Ecological Research Project
Personnel:
Individual:Dr. Robert Miller
Address:
Marine Science Institute,
University of California,
Santa Barbara, California 93106-6150 United States
Email Address:
miller@msi.ucsb.edu
Role:Principal Investigator
Individual:Dr. Dan Reed
Address:
Marine Science Institute,
University of California,
Santa Barbara, California 93106-6150 United States
Email Address:
dan.reed@lifesci.ucsb.edu
Role:Co-principal Investigator
Individual:Dr. Adrian Stier
Address:
Department of Ecology, Evolution and Marine Biology,
University of California,
Santa Barbara, California 93106-9260 United States
Email Address:
adrian.stier@lifesci.ucsb.edu
Role:Co-principal Investigator
Individual:Dr. Gretchen Hoffman
Address:
Department of Ecology, Evolution and Marine Biology,
University of California,
Santa Barbara, California 93106-9620 United States
Email Address:
hofmann@lifesci.ucsb.edu
Role:Co-principal Investigator
Individual:Dr. David Siegel
Address:
Institute for Computational Earth System Science,
University of California,
Santa Barbara, California 93106-3060 United States
Email Address:
davey@icess.ucsb.edu
Role:Co-principal Investigator
Abstract:

The Santa Barbara Coastal LTER (SBC LTER) is an interdisciplinary research and education program established in April 2000 with the goal of developing a predictive understanding of how environmental drivers interact with terrestrial and oceanic processes to alter material flows and influence the ecology of coastal ecosystems. SBC LTER's principal study domain is the semi-arid coast and nearshore waters of the Santa Barbara Channel in southern California, and its diverse and productive marine forests of giant kelp (Macrocystis pyrifera) serve as the focal study ecosystem. Analyses of our long-term data have identified many of the environmental drivers and ecological processes underlying the production and community dynamics of kelp forests. The research proposed to address this question is integrated in a conceptual framework that focuses on the causes and ecological consequences of the dynamics of a relatively short-lived foundation species in a setting of long-term climate change and human use.

Funding:

SBC LTER is supported by the National Science Foundation.

Additional Award Information:
Funder:National Science Foundation
Funder ID:https://dx.doi.org/10.13039/100000001
Number:1831937
Title:LTER: Environmental drivers and ecological consequences of kelp forest dynamics (SBV IV)
URL:https://www.nsf.gov/awardsearch/showAward?AWD_ID=1831937
Additional Award Information:
Funder:National Science Foundation
Funder ID:https://dx.doi.org/10.13039/100000001
Number:1232779
Title:LTER: Land/Ocean Interactions and the Dynamics of Kelp Forest Ecosystems (SBC III)
URL:https://www.nsf.gov/awardsearch/showAward?AWD_ID=1232779
Additional Award Information:
Funder:National Science Foundation
Funder ID:https://dx.doi.org/10.13039/100000001
Number:0620276
Title:LTER: Land/Ocean Interactions and the Dynamics of Kelp Forest Communities
URL:https://www.nsf.gov/awardsearch/showAward?AWD_ID=0620276
Additional Award Information:
Funder:National Science Foundation
Funder ID:https://dx.doi.org/10.13039/100000001
Number:9982105
Title:LTER: Land/Ocean Interactions and the Dynamics of Kelp Forest Ecosystems
URL:https://www.nsf.gov/awardsearch/showAward?AWD_ID=9982105
Other Metadata

Additional Metadata

additionalMetadata
        |___text '\n      '
        |___element 'metadata'
        |     |___text '\n         '
        |     |___element 'unitList'
        |     |     |___text '\n            '
        |     |     |___element 'unit'
        |     |     |     |  \___attribute 'abbreviation' = 'C'
        |     |     |     |  \___attribute 'constantToSI' = '273.18'
        |     |     |     |  \___attribute 'id' = 'celsius'
        |     |     |     |  \___attribute 'multiplierToSI' = '1'
        |     |     |     |  \___attribute 'name' = 'celsius'
        |     |     |     |  \___attribute 'parentSI' = 'kelvin'
        |     |     |     |___text '\n               '
        |     |     |     |___element 'description'
        |     |     |     |     |___text 'SI-derived unit of temperature'
        |     |     |     |___text '\n            '
        |     |     |___text '\n            '
        |     |     |___element 'unit'
        |     |     |     |  \___attribute 'abbreviation' = 'g/ind'
        |     |     |     |  \___attribute 'id' = 'gramsPerInd'
        |     |     |     |  \___attribute 'multiplierToSI' = '0.001'
        |     |     |     |  \___attribute 'name' = 'gramsPerInd'
        |     |     |     |  \___attribute 'parentSI' = 'kilogramsPerInd'
        |     |     |     |  \___attribute 'unitType' = 'massSpecificCount'
        |     |     |     |___text '\n               '
        |     |     |     |___element 'description'
        |     |     |     |     |___text 'grams Per Individual'
        |     |     |     |___text '\n            '
        |     |     |___text '\n            '
        |     |     |___element 'unit'
        |     |     |     |  \___attribute 'id' = 'microgramsPerHour'
        |     |     |     |  \___attribute 'multiplierToSI' = '0.001'
        |     |     |     |  \___attribute 'name' = 'microgramsPerHour'
        |     |     |     |  \___attribute 'parentSI' = 'gramsPerHour'
        |     |     |     |  \___attribute 'unitType' = 'massFlux'
        |     |     |     |___text '\n               '
        |     |     |     |___element 'description'
        |     |     |     |     |___text 'micrograms per hour'
        |     |     |     |___text '\n            '
        |     |     |___text '\n            '
        |     |     |___element 'unit'
        |     |     |     |  \___attribute 'id' = 'numberPerMeter'
        |     |     |     |  \___attribute 'name' = 'numberPerMeter'
        |     |     |     |  \___attribute 'unitType' = 'arealDensity'
        |     |     |     |___text '\n               '
        |     |     |     |___element 'description'
        |     |     |     |     |___text 'Number per meter'
        |     |     |     |___text '\n            '
        |     |     |___text '\n            '
        |     |     |___element 'unit'
        |     |     |     |  \___attribute 'id' = 'numberPerMeterCubed'
        |     |     |     |  \___attribute 'multiplierToSI' = '1'
        |     |     |     |  \___attribute 'name' = 'numberPerMeterCubed'
        |     |     |     |  \___attribute 'unitType' = 'volumetricDensity'
        |     |     |     |___text '\n               '
        |     |     |     |___element 'description'
        |     |     |     |     |___text 'number per meter cubed'
        |     |     |     |___text '\n            '
        |     |     |___text '\n            '
        |     |     |___element 'unit'
        |     |     |     |  \___attribute 'id' = 'numberPerMeterSquared'
        |     |     |     |  \___attribute 'multiplierToSI' = '1'
        |     |     |     |  \___attribute 'name' = 'numberPerMeterSquared'
        |     |     |     |  \___attribute 'unitType' = 'arealDensity'
        |     |     |     |___text '\n               '
        |     |     |     |___element 'description'
        |     |     |     |     |___text 'number per meter squared'
        |     |     |     |___text '\n            '
        |     |     |___text '\n         '
        |     |___text '\n      '
        |___text '\n   '

EDI is a collaboration between the University of New Mexico and the University of Wisconsin – Madison, Center for Limnology:

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