Table of Contents

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

This is one of four datasets that were produced with the "Fourchon Nekton Turnover Workflow"  (v1.0.0, doi: https://doi.org/10.5281/ZENODO.18165331). The datasets and supplemental data produced by this workflow have had minor modifications to enhance the interoperability of the data (See more in section "BCO-DMO Processing"). The workflow contains the exact formats of the data files produced and used by the workflow scripts. It also contains scripts, configurations, readme files, and input/output files for four stages listed below. Each workflow stage corresponds to a dataset in the "Related Datasets" section.
​
"Fourchon Nekton Turnover Workflow" steps with corresponding dataset IDs:

• "1_raw_data" = includes raw drop-sampling data corresponding to BCO-DMO dataset 991168 (doi: 10.26008/1912/bco-dmo.991168​.1)
• "2_gbif_workflow" = includes GBIF species observation data corresponding to metadata in BCO-DMO dataset 991175 (doi: 10.26008/1912/bco-dmo.991175​.1)
• "3_CTI_calculations" = includes community temperature index (CTI) data corresponding to BCO-DMO dataset 941250 (doi: 10.26008/1912/bco-dmo.941250​.1)
• "4_species_of_interest" = includes the results of a species pool analysis identifying species of interest corresponding to BCO-DMO dataset 991182 (doi: 10.26008/1912/bco-dmo.991182.1)

The workflow release (v1.0.0) contains data and scripts used to run analyses and produce figures for publication Leavitt, H; Thomas, A; Doerr, J; Johnson, D; Nelson, J. (In press) Resilient Nekton Composition in the Face of Climate-Driven Foundation Species Shifts. Ecology. Accepted 2025-11-14

This dataset maintains the original source data licenses and rightsHolders specified at GBIF within the main dataset table 991175_v1_port-fourchon_cleaned-occurrence.csv. See the data user agreement and citation guidelines at GBIF:
GBIF Data User Agreement: https://www.gbif.org/terms/data-user  
GBIF data usage and citation guidelines: https://www.gbif.org/citation-guidelines

We downloaded all human observations and preserved specimens for each of the species observed from 2005 to the access date in 2025 from the Global Biodiversity Information Facility (GBIF)(Accessed on 6/6/2025).   See query parameters in supplemental file "gbif_source_metadata.csv."

Species occurrence records were downloaded from GBIF using the Interface to the Global Biodiversity Information Facility API (rgbif API, https://github.com/ropensci/rgbif; doi: 10.5281/zenodo.1045299) and subjected to a multi-stage quality-control workflow prior to analysis.  See Supplemental File "gbif_source_metadata.csv" for citations for each derived data query. Only post-2005 human observation records with valid geographic coordinates and no flagged geospatial issues were retained. Records lacking coordinates or returned as empty downloads were excluded.

We further filtered occurrences to retain only records with an occurrence status of “present” and removed fossil and captive/living specimen records. Spatial accuracy was enforced by removing records with coarse coordinate precision (>0.01 degrees) or large coordinate uncertainty, using a threshold of 1,000 m for most taxa and a relaxed threshold of 30,000 m for threatened taxa to avoid disproportionate data loss. Records with known placeholder or erroneous uncertainty values (e.g., 301, 999, 9999, 3036 m) and records with zero latitude or longitude were also removed.

To reduce common spatial artifacts, we applied automated coordinate cleaning using the CoordinateCleaner framework (Zizka et. al, 2023), excluding records falling within 2 km buffers of country centroids, capital cities, and known biodiversity institutions. Finally, duplicate records were removed based on identical longitude, latitude, species key, and dataset key combinations. The resulting cleaned datasets were saved for downstream analyses, and all GBIF download DOIs or citations were archived to ensure reproducibility and data provenance.

This dataset corresponds to Step "2_gbif_workflow" of the study's processing workflow 'Fourchon Nekton Turnover Workflow', doi: 10.5281/zenodo.18165331).  See "Description" and "BCO-DMO Processing" sections for context about the relationship between the workflow files and the data as published at BCO-DMO.

Workflow README for Step "2_gbif_workflow" :
Step 2: GBIF Downloads and Cleaning

Abstract

This step assembles GBIF occurrence records for all taxa detected in the Port Fourchon nekton surveys, cleans spatial artifacts, and delivers per-taxon CSVs ready for thermal niche extraction. The workflow expands harmonized taxon names into GBIF queries, submits authenticated bulk downloads, filters out problematic coordinates and land points, and documents all DOI citations needed for downstream analyses and reporting.

Purpose: fetch occurrence data for target taxa, apply coordinate/data-quality filters, and save cleaned per-taxon CSVs with citation logs.

Primary script

• gbif_download_BCODMO.R: annotated script that expands pooled taxa, submits GBIF downloads, cleans coordinates (CoordinateCleaner), and logs citations/DOIs.

Inputs

• ../1_raw_data/outputs/presence_pivot_merged_sp.csv: taxon list used to build download targets.
• Environment variables: GBIF_USER, GBIF_EMAIL, GBIF_PWD for GBIF API access.

Outputs

• gbif_downloads/clean_csvs/<taxon>_clean.csv: cleaned occurrences per taxon.  
• gbif_citations.txt: citations/DOIs for all downloads.

Software

• R >= 4.3 with rgbif, tidyverse, terra, sp, sdmpredictors, CoordinateCleaner.

Run order

1. Ensure Step 1 outputs are present.
2. Set GBIF credentials in the environment.
3. Run gbif_download_BCODMO.R; verify cleaned CSVs and gbif_citations.txt.

Version 1 (2026-01-08):

Data from the processing workflow were prepared and published at BCO-DMO after reorganization into datasets with minor changes performed to meet the required conventions implemented by BCO-DMO designed for interoperability, standardization, and a variety of data access methods.

Main data table "991175_v1_port-fourchon_cleaned-occurrence.csv" was created by merging submitted files.
Submitted folder "Fourchon Nekton Turnover Workflow/clean_csvs/" contained 75 csv files named with _clean.csv (one per species, a file per GBIF query, see gbif_source_metadata.csv). These were imported into the BCO-DMO data system, concatenated and additional columns added (GBIF_query_doi, AphiaID, LSID). Empty columns removed, columns subselected. The original format of the "Fourchon Nekton Turnover Workflow/clean_csvs/" is available in the Workflow package (doi: 10.5281/zenodo.18165331).

Submitted data files for this dataset correspond to the study's outputs in workflow (doi: 10.5281/zenodo.18165331) step 2:

The supplemental file "gbif_source_metadata.csv" contains additional information about the source GBIF data that was obtained by using the GBIF DOIs contained within workflow file "Fourchon Nekton Turnover Workflow/2_gbif_workflow/gbif_citations.txt" and adding additional information provided by the following APIs on 2026-01-09:
GBIF_API = "https://api.gbif.org/v1"
WORMS_API = "https://www.marinespecies.org/rest"

NSF Award Abstract:
Coastal marshes provide a suite of vital functions that support natural and human communities. Humans frequently take for granted and exploit these ecosystem services without fully understanding the ecological feedbacks, linkages, and interdependencies of these processes to the wider ecosystem. As demands on coastal ecosystem services have risen, marshes have experienced substantial loss due to direct and indirect impacts from human activity. The rapidly changing coastal ecosystems of Louisiana provide a natural experiment for understanding how coastal change alters ecosystem function. This project is developing new metrics and tools to assess food web variability and test hypotheses on biodiversity and ecosystem function in coastal Louisiana. The research is determining how changing habitat configuration alters the distribution of energy across the seascape in a multitrophic system. This work is engaging students from the University of Louisiana Lafayette and Dillard University in placed-based learning by immersing them in the research and local restoration efforts to address land loss and preserve critical ecosystem services. Students are developing a deeper understanding of the complex issues facing coastal regions through formal course work, directed field work, and outreach. Students are interacting with stakeholders and managers who are currently battling coastal change. Their directed research projects are documenting changes in coastal habitat and coupling this knowledge with the consequences to ecosystems and the people who depend on them. By participating in the project students are emerging with knowledge and training that is making them into informed citizens and capable stewards of the future of our coastal ecosystems, while also preparing them for careers in STEM. The project is supporting two graduate students and a post-doc.

The transformation and movement of energy through a food web are key links between biodiversity and ecosystem function. A major hurdle to testing biodiversity ecosystem function theory is a limited ability to assess food web variability in space and time. This research is quantifying changing seascape structure, species diversity, and food web structure to better understand the relationship between biodiversity and energy flow through ecosystems. The project uses cutting edge tools and metrics to test hypotheses on how the distribution, abundance, and diversity of key species are altered by ecosystem change and how this affects function. The hypotheses driving the research are: 1) habitat is a more important indirect driver of trophic structure than a direct change to primary trophic pathways; and 2) horizontal and vertical diversity increases with habitat resource index. Stable isotope analysis is characterizing energy flow through the food web. Changes in horizontal and vertical diversity in a multitrophic system are being quantified using aerial surveys and field sampling. To assess the spatial and temporal change in food web resources, the project is combining results from stable isotope analysis and drone-based remote sensing technology to generate consumer specific energetic seascape maps (E-scapes) and trophic niche metrics. In combination these new metrics are providing insight into species’ responses to changing food web function across the seascape and through time.

This project is jointly funded by Biological Oceanography and the Established Program to Stimulate Competitive Research (EPSCoR).

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.