This dataset includes information on over 100 species found in the intertidal zone on a rocky shoreline during community surveys conducted at 23 sites along the coast of California and Baja California, Mexico in 2022 and 2023. Community survey data includes visual estimates of percent area covered by various species with corresponding season and tide height.

Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • BCO-DMO Processing Description
  • Problem Description
• Data Files
• Supplemental Files
• Parameters
• Project Information
• Funding

The taxonomy of the species observed in the intertidal community survey dataset can be found in the supplemental file taxonomy_of_intertidal_community.csv.

This file contains an Organism_parameter column which lists the species name parameters used in the intertidal community survey files of 935622_suppl_intertidal_comm_survey_ca_and_baja_ca_mexico_2022_2023.csv and 935622_v1_unpivoted_intertidal_comm_survey_ca_and_baja_ca_mexico_2022_2023.csv.

Each row lists the species name parameter, the observed species, a note clarifying the observed species, since there may be an adjective describing the species or two species observed at once, and the matching taxonomy of the observed species using taxonomy information attained from WoRMS (World Register of Marine Species). Since some of the species name parameters represent two species, such as Balanus_and_Chthamalus_spp, there are two rows in the taxonomy file where the taxonomy is listed for each of the separate species.

The submitter’s file Community_survey_data_for_BCODMO_RangeShiftNSF_2024_0816.xlsx was an Excel spreadsheet with metadata columns and over 100 columns with species names as headers.

This file was processed with Excel first to alphabetize the species name columns, and then the sorted table was saved to a file named sorted_Community_survey_data_for_BCODMO_RangeShiftNSF_2024_0816.xlsx.

Overview

This file was then processed with BCO-DMO’s Laminar tool to create a primary dataset file in a long format (fewer columns) and a supplemental dataset file in a wide format (fewer rows).

Step 1

Renamed two species column headers to clarify two species were observed for coverage data.

Renamed the parameter Nucella_emarginata/ostrina to Nucella_emarginata_and_ostrina.

Renamed the parameter Dead_Balanus_Chthamalus to Dead_Balanus_and_Chthamalus.

Renamed Errant_Polychaete renamed Errant_Polychaetes by adding an ‘s’ to fix the spelling of the plural form.

The units “_m” were removed from the parameter names “Vert_Transect_Dist_m”, “Quad_Dist_m”, and “Quad_TH_m” to conform with the BCO-DMO parameter naming convention. The units will be noted in the parameters section on the dataset page.

The format of the dates in the column “Survey_Date” were reformatted from %m-%d-%y into the ISO 8601 date format of %Y-%m-%d.

This reformatted dataset table was saved as ‘survey_data’ in Laminar and was duplicated to create two files at the end of processing. One in long format and the other in wide format.

Step 2

One of the duplicated ‘survey_data’ tables was saved as the supplemental dataset file named 935622_supl_intertidal_comm_survey_ca_and_baja_ca_mexico_2022_2023.csv. This file is in a ‘wide’ format with many columns and fewer rows than an unpivoted version.

Definitions for the parameters in 935622_supl_intertidal_comm_survey_ca_and_baja_ca_mexico_2022_2023.csv are in the supplemental file parameter_definitions_for_supplemental_community_survey_data.csv.

Step 3

The other ‘survey_data’ table was unpivoted into a long format with fewer columns and more rows. This was achieved by unpivoting all the column parameters with species names. There are now two columns named “Organism_parameter” and “Coverage” where each “Organism_parameter” cell contains a species parameter name (maintaining the column name from before) and each “Coverage” cell contains a coverage percentage for each species name, location, and date. There are now many more rows than the submitted file, but fewer columns.

The ”Organism_parameter” column was duplicated as “Organism_name” and the underscores in “Organism_name” were replaced with spaces and any suffix of ‘spp’ was replaced with ‘spp.’ to result in the parameter “Organism_name” containing the species name spelling.

This table was saved as the primary dataset file named 935622_v1_unpivoted_intertidal_comm_survey_ca_and_baja_ca_mexico_2022_2023.csv.

Step 4

Taxonomic names in the dataset were checked using the World Register of Marine Species (WoRMS) taxon match tool at https://www.marinespecies.org/aphia.php?p=match. The species name of each organism in the intertidal community surveys dataset was uploaded to the WoRMS taxon match tool and the output saved as taxonomy_of_intertidal_community.csv. This file includes the column Organism_parameter which contains species names parameters used in the supplemental file 935622_supl_intertidal_comm_survey_ca_and_baja_ca_mexico_2022_2023.csv and in the primary file 935622_v1_unpivoted_intertidal_comm_survey_ca_and_baja_ca_mexico_2022_2023.csv.

For values in Organism_parameter that represented two observed species, e.g. Balanus_and_Chthamalus_spp, the parameter value was copied into a second row to separate out the taxonomy for each species on separate rows. The notes column provides clarifying information for the Organism_parameter when needed.

A corresponding column named Organism_species contains the species name of the Organism_parameter. This species name was created from the Organism_parameter entry by replacing underscores with spaces and replacing ‘spp’ with ‘spp.’. Clarifying information like ‘articulated’ in the Organism_parameter was removed in the Organism_species column. For cases where the Organism_parameter represented two observed species, one species name in the Organism_species column is used per duplicated Organism_parameter with the description in the ‘Notes’ column clarifying the species name used.

The Organism_species names are clarified as taxon accepted or unaccepted in WoRMS and their corresponding taxon, including AphiaID and LSID, are listed as of December 2024. The Organism_species Biofilm is a general term and had no match in WoRMS.

See the supplemental file parameter_definitions_for_taxonomy_of_intertidal_community_file.csv for the column definitions in the taxonomy file taxonomy_of_intertidal_community.csv.

Gaps in sampling are most likely due to:
(1) tidal and weather conditions, or that allowed us to survey plots to a lower elevation during some sampling events and not others, and/or
(2) inundation of areas by sand, that allowed us to survey plots during some sampling events and not others.

NSF Award Abstract:
This project will improve our ability to anticipate the impacts of shifts in the geographic range of coastal species in a changing climate. Although range shifts may be necessary for some species to avoid extinction as the climate warms, the arrival of new ones to an ecosystem can also lead to population declines and loss of biodiversity. The investigator is developing approaches to predict the impacts of range shifts along Pacific shorelines using techniques that have been previously validated for risk assessments for invasive species. The research objectives of this study are integrated with educational activities: engagement of undergraduate and graduate students in data collection and analysis and implementation of a hierarchical mentoring program to serve English Language Learners within the investigator’s Minority Serving Institution. The investigator is also partnering with outreach organizations in the U.S. and Mexico to educate K-12 students and multiple stakeholder groups about climate-driven range shifts and tools for predicting outcomes of redistribution, which can assist practitioners in creating management plans and policies.

This study is developing a framework for understanding the impacts of marine species redistribution with a focus on poleward-moving carnivorous whelk species in rocky shorelines from Northern California to Baja, Mexico. Project goals are to 1) quantify the impacts of shifting species on populations and communities in the expanded range; 2) assess whether impacts of shifting species differ between their native and expanded ranges; and 3) predict future impacts under climate warming. The investigator is addressing fundamental questions in community ecology about the degree to which species interactions are density- and context-dependent. She is combining observational and experimental approaches with a broader data synthesis effort to test whether the impacts of species redistribution can be predicted by key indicators of invasion impacts: abundance, trophic level, and impacts in the native range. Empirical data combined with paired demographic and distribution modeling will be used to project future impacts across the expanded ranges of these coastal marine species.