This repository contains the code and data for reproducing McDonald, et al. 2019 (Conservation Biology): "Catalyzing sustainable fisheries management through behavior change interventions" (https://doi.org/10.1111/cobi.13475).
The DOI for this code and data repository is managed through Zenodo with DOI number 10.5281/zenodo.3635980 (https://doi.org/10.5281/zenodo.3635980).
Title: Catalyzing sustainable fisheries management though behavior change interventions
Authors: Gavin McDonald, Molly Wilson, Diogo Veríssimo, Rebecca Twohey, Michaela Clemence, Dean Apistar, Stephen Box, Paul Butler, Fel Cesar Cadiz, Stuart J. Campbell, Courtney Cox, Micah Effron, Steve Gaines, Raymond Jakub, Roquelito H. Mancao, Pablo T. Rojas, Rocky Sanchez Tirona, Gabriel Vianna
Abstract: Small-scale fisheries are an important livelihood and primary protein source for coastal communities in many of the poorest regions in the world, yet many suffer from overfishing, requiring effective and scalable management solutions. Positive ecological and socioeconomic responses to management typically lag behind immediate costs borne by fishers from fishing pressure reductions necessary for fisheries recovery. These short-term costs challenge the long-term success of these interventions. However, social marketing may increase perceptions of management benefits before ecological and socioeconomic benefits are fully realized, driving new social norms and ultimately long-term sustainable behavior change. Using ecological surveys and community-perceived measures of management support and socioeconomic conditions, we assess the impact of a standardized small-scale fisheries management intervention that was implemented across 41 sites in Brazil, Indonesia, and the Philippines. The intervention combines TURF-reserves (community-based Territorial Use Rights for Fishing coupled with no-take marine reserves) with locally-tailored social marketing behavior change campaigns. Leveraging data across diverse indicators, our results suggest that communities were developing new social norms and fishing more sustainably, even before long- term ecological and socioeconomic benefits of fisheries management had materialized.
fisheries-behavior-change
|__ data
|__ output_figures
|__ r
|__ output_tables
This analysis was performed in R. The script for fully reproducing the paper analysis can be found in r/analysis.R
.
The data
folder contains four input data files, with full metadata given below:
monitoring_data.csv
: All monitoring data for sites from the Community Support, Sustainable Fishing Practices, Sustainable Ecosystems, or Sustainable Livelihoods impact surveyssite_data.csv
: Descriptive demographics and statistics for each sitesurvey_question_lookup.csv
: A lookup table that matches specific socioeconomic survey questions from each site to specific indicatorsphils_matching_data.csv
: Site attribute scores used for control site selection for the 3 sets of matched impact / control sites for the Philippines sustainable ecosystems and sustainable livelihoods survey
Each row contains an individual monitoring observation, with the following schema:
country
: Country (Brazil, Indonesia, or Philippines)site
: 6-letter site codesurvey
: Survey (Community Support, Sustainable Fishing Practices, Sustainable Ecosystem, or Sustainable Livelihoods)before_after
: Binary for before (0) or after (1) the interventioncontrol_impact
: Binary for control (0) or impact (1) sitereplicate
: Replicate for analysis (anonymized indivudal for Community Support, Sustainable Fishing Practices, and Sustainable Livelihoods surveys, and dive site location for Sustainable Ecosystems surveys)indicator_full
: Full indicator name, breaking community support and sustainable fishing practices indicators out across 6 different behavior changes (Licensing; Catch Reporting; Enforcement; NTZ Compliance; TURF Compliance; Management Participation)indicator_condensed
: Condensed indicator name, aggregating together community support and sustainable fishing practices indicators across 6 different behavior changes
Each row contains descriptive statistics and demographics for a single site, with the following schema:
country
: Country (Brazil, Indonesia, or Philippines)site
: 6-letter site codelat
: Latitude for centroid of sitelon
: Longitude for centroid of sitesite_type
: One of either "Intervention" or "Control"fishers_ff_target_communities
: Number of fishers in Fish Forever target communitiesarea_current_turfs_ha
: Area of TURFs, as of 2017area_current_reserves_ha
: Area of reserves (NTZs), as of 2017
Each row contains the exact survey question that was asked at a particular site, and which survey and indicator the question corresponds to, with the following schema:
country
: Country (Brazil, Indonesia, or Philippines)site_code
: 6-letter site codesurvey
: Survey (Community Support, Sustainable Fishing Practices, Sustainable Ecosystem, or Sustainable Livelihoods)indicator_full
: Full indicator name, breaking community support and sustainable fishing practices indicators out across 6 different behavior changes (Licensing; Catch Reporting; Enforcement; NTZ Compliance; TURF Compliance; Management Participation)indicator_condensed
: Condensed indicator name, aggregating together community support and sustainable fishing practices indicators across 6 different behavior changesfull_question
: Full survey question, as presented to the survey participantsurvey_question_code
: Cleaned version offull_question
that removes spaces, capital letters, and special charactersresponse_options
Full survey response options, as presented to the survey participant
Each row contains the attribute score used for base characteristics used during the control site selection for the Philippines sustainable ecosystems and sustainable livelihoods survey, with the following schema:
site
: 6-letter site codecontrol_impact
: Binary for control (0) or impact (1) sitecountry
: Country (Philippines)survey
: Survey (Sustainable Ecosystem or Sustainable Livelihoods)baseline_characteristic
: Name of baseline characteristicvalue
: Attribute score (ranked 1 to 5)
The software code contained within this repository is made available under the MIT license. The data and figures are made available under the Creative Commons Attribution 4.0 license.
Please note: To ensure reproducibility and in order to manage package dependencies, we use the renv
package. When you first clone this repo onto your machine, run renv::restore()
to ensure you have all correct package versions installed in the project. Please see the renv
page for more information: https://rstudio.github.io/renv/articles/renv.html.