Data from: Expert priorities for coral reef conservation under climate change: A discrete choice experiment
Data files
Oct 22, 2026 version files 320.38 KB
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README.md
11.96 KB
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Supp1_Simulator_unformatted_version.xlsx
90.70 KB
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Supp1_Simulator.xlsx
138.52 KB
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Supp2_Data.xlsx
79.20 KB
Abstract
Conservation management in the Anthropocene requires resolving trade-offs between climate mitigation and ecosystem intervention. As the first major ecosystem approaching climate-driven collapse, coral reefs offer crucial early lessons for global conservation efforts. We surveyed 136 coral reef experts globally using a discrete choice experiment, forcing realistic budget allocation decisions across conservation strategies. Biobanking—preserving coral genetic material—emerged as the top intervention priority, with surveyed experts preferring combined live banking and cryopreservation. Restoration ranked second, with scenarios lacking active intervention strongly disfavored. This consensus transcended regional and professional boundaries, with Caribbean experts particularly favoring active restoration following recent mass bleaching. Experts converged on allocating 60% of budgets to traditional management and 40% to novel interventions, empirically rejecting either/or thinking that has polarized conservation debates. These findings provide quantitative guidance for global frameworks including the UN Decade on Ecosystem Restoration, demonstrating that sustainability requires both addressing root causes and active interventions to maintain ecosystem function in the face of persistent threats. The dominance of biobanking signals a paradigm shift from reactive protection to proactive preservation of evolutionary potential—essential insurance for safeguarding coral reefs under accelerating climate change.
Dataset DOI: 10.5061/dryad.bnzs7h4rd
Description of the data and file structure
Data were collected from an online discrete choice experiment surveying coral reef conservation experts worldwide. The study aimed to quantify expert priorities for coral reef conservation strategies when facing resource allocation trade-offs. Between December 2024 and February 2025, 136 coral reef scientists, managers, policymakers, and restoration practitioners completed the survey, which was distributed through the 2024 Reef Futures conference and professional networks including the Coral Restoration Consortium.
Participants evaluated hypothetical conservation portfolios varying across four attributes: biobanking approach (none, live banking, cryopreservation, or combined), hand outplanting effort (none, small-scale, or large-scale), research and development priorities (genetic interventions, disease management, stress hardening, or symbiont manipulation), and budget allocation between novel interventions and traditional management. Each participant completed 10 choice tasks, yielding 1,360 total choice observations. Data were analyzed using Hierarchical Bayesian modeling to estimate preference weights and part-worth utilities for each conservation attribute and level.
Files and variables
File: Supp2_Data.xlsx
Description: Raw survey response data from the discrete choice experiment, exported from Sawtooth Software. Contains individual-level choice task responses and demographic information for 136 coral reef expert respondents.
File structure
Supp2_Data.xlsx contains two worksheets:
Sheet2: primary data sheet. One row per respondent (136 rows), 55 columns, variable names in row 1.Sheet1: identical copy of the same data without a variable-name row (row 1 is blank). It contains no additional information.
Blank cells mean the question was not answered, or the field was not used. No other missing-value codes are used.
Variables
Respondent characteristics
| Column | Description | Values |
|---|---|---|
sys_RespNum |
Anonymous respondent ID, the sequential number Sawtooth assigned when the survey was started. Unique, but not numbered 1 to 136 (range 32 to 692; gaps are people who started but did not complete the survey). | Integer |
AttendConference |
Attended the 2024 Reef Futures conference | 1 = Yes (n = 73); 2 = No (n = 63) |
Location |
Respondent's current location | Free text |
Experience |
Years of experience in coral conservation, management, or science | 1 = Less than 1 year (n = 5); 2 = 1–5 years (n = 31); 3 = 6–10 years (n = 38); 4 = 11–15 years (n = 17); 5 = more than 15 years (n = 45) |
Interest |
Primary geographic area of interest, study or work (the regional grouping used in the paper) | 1 = Greater Caribbean (n = 76); 2 = Indo-Pacific (n = 42); 3 = Great Barrier Reef (n = 18) |
Affiliation |
Primary professional affiliation | 1 = Academic (n = 71); 2 = Government (n = 27); 3 = Non-profit (n = 31); 4 = Other (n = 7) |
Affiliation_4_other |
Free-text affiliation given when Affiliation = 4 |
Free text; blank otherwise |
Feedback |
Optional comments on the survey | Free text; 120 respondents commented |
Choice task responses
| Column | Description | Values |
|---|---|---|
CBC_Random1 to CBC_Random10 |
Option chosen in each of the 10 tasks, in order of presentation | 1, 2 or 3 = portfolio in that screen position; 4 = "none" option. Across all 1,360 choices: 1 = 368, 2 = 354, 3 = 360, 4 = 278 |
sys_CBCDesignID_CBC |
Choice design identifier | CBC1_1730120147_6 for all respondents |
sys_CBCVersion_CBC |
Version (block) of the design shown to the respondent (range 9 to 294; some versions were shown to more than one respondent) | Integer |
All respondents answered all 10 tasks. The number recorded is screen position only; the attribute levels shown in each position are defined by the design.
Survey administration (generated by Sawtooth)
| Column | Description |
|---|---|
sys_StartTime, sys_EndTime |
Survey start and end, as text in Pacific Standard Time (DD Mon YYYY - HH:MM:SS PST) |
sys_StartTimeStamp, sys_EndTimeStamp |
Same times as Unix timestamps (seconds since 1 Jan 1970, UTC) |
sys_ElapsedTime |
Seconds from start to end. Includes time the survey was left open, so it is not time-on-task. |
sys_SumPageTimes |
Total seconds on survey pages (equals the sum of sys_pagetime_1 to sys_pagetime_17 for all but two respondents) |
sys_pagetime_1 to sys_pagetime_17 |
Seconds on each survey page, in order of presentation |
sys_DataSource, sys_RespStatus, sys_RespRemoved, sys_LastQuestion, sys_UserJavaScript |
Constant for all rows (1; 5 = completed interview; FALSE; Bye; TRUE). Only completed respondents are included. |
Empty columns. Interest_1, Interest_2, Interest_3, MostEffective, Characteristics, sys_DispositionCode, sys_CAPIDeviceID and sys_pagetime_1 contain no data. They are retained to match the original export.
File: Supp1_Simulator.xlsx
Description: Interactive decision support tool allowing users to simulate expert preferences for different coral reef conservation scenarios. Based on Hierarchical Bayesian model outputs from 136 expert respondents.
Variables:
- Attribute levels for Hand Outplanting, Biobanking, Research & Development, and Cost
- Simulated shares of preference
- Segmentation options by region and affiliation
File: Supp1_Simulator_unformatted_version.xlsx
Description: This is the original, unmodified version of “Supp1_Simulator.xlsx,” without the changes we made to enhance interactivity and usability. It is the native export from Sawtooth Software and cannot be saved as a .csv or other simpler format because formulas link the first sheet to the other four.
Variables:
- Attribute levels for Hand Outplanting, Biobanking, Research & Development, and Cost
- Simulated shares of preference
- Segmentation options by region and affiliation
Code/software
Microsoft Excel or compatible spreadsheet software (e.g., Google Sheets, LibreOffice Calc) is required to view and interact with the data files. The interactive simulator (Supp1_Simulator.xlsx) uses Excel formulas and does not require macros or additional software.
Survey data were collected using Sawtooth Software Lighthouse Studio and analyzed using the Sawtooth Software CBC/HB module for Hierarchical Bayesian estimation.
Human subjects data
This study was approved by the University of Southern California Institutional Review Board (IRB). All participants provided informed consent prior to participation, which included explicit notification that de-identified data would be archived in a public repository.
Data were collected anonymously through the Sawtooth Software platform. No personally identifiable information (names, email addresses, IP addresses, or specific institutional affiliations) was collected or retained. Demographic variables are reported only at aggregate categorical levels (geographic region of work, broad professional affiliation, and binned years of experience) that prevent identification of individual respondents. Participants could skip any questions they did not wish to answer and could withdraw at any time.
The dataset contains only anonymized survey responses and cannot be linked to individual participants.
