Dataset: Abalone Recruitment Modules

Name: Abalone recruitment data from Baja California and Baja California Sur, Mexico in 2019
Published: 2023-10-18
Keywords: abalone, Recruitment, Baja California, oceans

Cite This Dataset

DOI:10.26008/1912/bco-dmo.907383.1

Spatial Extent: N:29.79086 E:-113.70034 S:26.77558 W:-115.79903

Temporal Extent: 2019-06-18 - 2019-06-25

Project:

Collaborative Research: Evaluating how abalone populations in the California Current are structured by the interplay of large-scale oceanographic forcing and nearshore variability (Abalone Safe Places)

Principal Investigator:

Fiorenza Micheli (Stanford University)

Scientist:

Arturo Hernández-Velasco (Comunidad y Biodiversidad, A.C., COBI)

Laura Rogers-Bennett (University of California-Davis, UC Davis)

Alexandra Smith (Stanford University)

Technician:

Arquimedes Aguilar (Sociedad Cooperativa de Producción Pesquera Buzos y Pescadores de la Baja California, SCPP Buzos y Pescadores de la BC)

Miguel Bracamontes (Cooperativa Ensenada)

Ramon Martinez (Sociedad Cooperativa de Producción Pesquera Buzos y Pescadores de la Baja California, SCPP Buzos y Pescadores de la BC)

Alfonso Romero (Comunidad y Biodiversidad, A.C., COBI)

Data Manager:

Carolina Olguín Jacobson (Stanford University)

BCO-DMO Data Manager:

Amber D. York (Woods Hole Oceanographic Institution, WHOI BCO-DMO)

Version:

Version Date:

2023-10-18

Restricted:

Validated:

Yes

Current State:

Final no updates expected

Abalone recruitment data from Baja California and Baja California Sur, Mexico in 2019

Abstract:

Abalone support commercial and recreational fishery, however their population have decline dramatically since 1950's. To understand the recruitment of abalone populations, standarized abalone recruitment modules made of half cinder blocks inside cages were deployed in Baja California and Baja California Sur, Mexico. 12 cages were deployed at three sites (i.e., El Rosario, Isla Natividad and La Bocana) in Mexico. The abundances of abalone and invertebrates found in the cages were checked after 12months. This dataset presents all the information collected from the cages deployed at three sites (El Rosario, Isla Natividad and La Bocana) in Baja California and Baja California Sur, Mexico.

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Archival Copy

Version Date	Archive	Persistent Identifier (PID)	Date PID Issued
2023-10-18	Marine Biological Laboratory/Woods Hole Oceanographic Institution Library (MBLWHOI DLA)	10.26008/1912/bco-dmo.907383.1	2023-11-16

Methods & Sampling

LOCATION:
Baja California, Mexico. El Rosario
Baja California Sur, Mexico. Isla Natividad and La Bocana

DEPLOYMENT OF CAGES
Twelve cages per site were deployed between 5-40ft, at the three locations (El Rosario, Isla Natividad and La Bocana) and left for 12 months before surveys.

SURVEY OF CAGES
1. Diver 1 opens cage and holds the blocks 1 at a time while Diver 2 fills in the data sheet
2. Diver 2 fills in the datasheet and sets the blocks in a pile off to the side

Part 1 – count and measure focal species
▪ Stop measuring after 30 measurements
▪ Stop counting after 100 counts
▪ Organisms outside or on the cage should not sampled.

Part 2 – identify and qualitatively measure the dominant cover on each block
▪ For each block identify what the most common cover is (CCA, red algae, other)
▪ Determine whether it covers 25, 50, 75 or 100% of the block
▪ But a tally point in the corresponding cell
▪ Each block should only have 1 tally

Part 3 – note presence/absence of Macrocystis/Eisenia algae or sessile invertebrates for each block

3. Once the cage is empty divers inspect the cage and lines, making any minor repairs that are
possible

4. Diver 1 puts the blocks back into the cage 1 at a time while diver 2 keeps track (comments section) of the number of blocks and broken pieces.

5. Close the cage with line and cable ties, ascend for surface interval

INSTRUMENTS:
SCUBA diving equipment
Calipers (150mm)
Ruler
Mesh bag
Transect tape
Slate
Datasheet
Pencils
Snipes/knife
Cable ties
Extra line
GoPro camera

Data Processing Description

The data from each cage was checked and transferred into an excel file, to keep all the three sites (i.e., El Rosario, Isla Natividad, La Bocana) together.

BCO-DMO Processing

* "907383_v1_abalone_recruitment_modules_COJ_18Oct2023.csv" was imported into the BCO-DMO data system with values "NA" as missing data values.
** Missing data values are displayed differently based on the file format you download. They are blank in csv files, "NaN" in MatLab files, etc.
* After discussion with the submitter about identifications with name Organism_Identification "megastrea" or "megastrae" or "Megastraea sp." and taxon id Megastraea gibberosum/giberosum or "Megastraea spp", the decision was made to changes these to Organism_Identification: "turban snail", and Taxonomic_name: "Turbininae spp." which is the subfamily since not all the snails identified could be narrowed down to genus Megastrea. And several species in Megastrea had been transitioned to other genera over time.
* Taxonomic names checked with World Register of Marine Species (WoRMS) taxa match tool on 2023-09-28. Species list added as a supplemental file which contains taxonomic identifiers for names used in the dataset along with the accepted synonym if a currently unnaccepted synonym was used.
* After discussion with submitter, two duplicate rows were dropped from the data table corresponding to these rows in the originally submitted file:
El Rosario, number:1, Kelletia kelletii individual 1 = row 91 duplicated in row 254
El Rosario, number:1, Kelletia kelletii individual 2 = row 92 duplicated in row 255

Data Files

File
Abalone Recruitment Monitoring 2019 filename: 907383_v1_abalone_recruitment_modules.csv (Comma Separated Values (.csv), 188.95 KB) MD5:71d88976efdca4bd17565a6e0482f47b Primary data table for 907383 version 1. This file contains information for the abalone recruitment monitoring. In three site in Baja California, Mexico (El Rosario, Isla Natividad and La Bocana).

Supplemental Files

File

Abalone species list
filename: abalone_species_list.csv

(Comma Separated Values (.csv), 1.34 KB)
MD5:a2c939dd37e6f9d7718e334b3edcfd64

Species list table for identifications in this dataset.  

Column information:

ScientificName_in_dataset, Taxonomic name used in the dataset

AphiaID, The World Register of Marine Species (WoRMS) taxonomic identifier for the name in the dataset

Taxon_status_20230928, Status of the name in the dataset as of 2023-09-28. Indicates if the name is the currently accepted name or an unaccepted synonym. 

ScientificName_accepted, The accepted name (differs from ScientificName column if unaccepted synonym used there)

AphiaID_accepted_name,  The World Register of Marine Species (WoRMS) taxonomic identifier for the accepted name  (differs from AphiaID column if unaccepted synonym used in the dataset)

LSID_accepted_name, The Life Sciences Identifier (LSID) for the accepted name

More Information about this dataset

Funding Sources

Funding Source	Award Number
NSF Division of Ocean Sciences	OCE-1736830

Deployments

None available yet

Instruments

Camera

Supplied Name: GoPro camera

Supplied Description:

Instrument Type

Generic Name: Camera

Acronym: camera

Community Identifier: http://vocab.nerc.ac.uk/collection/L05/current/311/

Generic Description:

All types of photographic equipment including stills, video, film and digital systems.

Self-Contained Underwater Breathing Apparatus

Supplied Name:

Supplied Description:

Instrument Type

Generic Name: Self-Contained Underwater Breathing Apparatus

Acronym: SCUBA

Generic Description:

The self-contained underwater breathing apparatus or scuba diving system is the result of technological developments and innovations that began almost 300 years ago. Scuba diving is the most extensively used system for breathing underwater by recreational divers throughout the world and in various forms is also widely used to perform underwater work for military, scientific, and commercial purposes.

Reference: https://oceanexplorer.noaa.gov/technology/technical/technical.html

Parameters

Date and time formats are described in python strftime() syntax.

Supplied Name	Supplied description	Supplied Units	Standard Name
date	date when the survey was done. Date in ISO 8601 format. Format: %Y-%m-%d	unitless	date
Site	Site when the survey was done	unitless	site
Bouy	Bouy when the survey was done, more specific place	unitless	buoy_id
divers	divers that did the survey	unitless	person
BART_transect	If the survey was done by BART or by transect	unitless	transect
number	number of BART or transect	unitless	transect_code
depth	depth in ft	feet (ft)	depth
camera	camera use for the survey (could be done "insitu" = none)	unitless	Sensor_Id
lat	latitude	decimal degrees	lat
long	longitude	decimal degrees	lon
Organism_Identification	Name of species observed in the survey	unitless	sample_descrip
Taxonomic_name	Scientific name of the species observed in the survey	unitless	taxon
Species_note	Any special note about the species	unitless	sample_descrip
individual_num	The number of individual species counted in the survey	unitless	count
size_mm	The size (in mm) of the individual species counted in the survey. Individual measurements or ranges.	millimeters (mm)	length
size_mm_note	Any special note about the size of the individual species	unitless	comment