DOI: 10.5061/dryad.70rxwdbz3
title: Projected climate risk of aquatic food system benefits

description: Aquatic foods from marine and freshwater systems are critical to the
 nutrition, health, livelihoods, economies and culture of billions of
 people worldwide – but climate-related hazards may compromise
 their ability to provide these benefits. This analysis estimates
 national-level aquatic food system climate risk using a fuzzy logic
 modeling approach that connects climate hazards impacting marine
 and freshwater capture fisheries and aquaculture to their contributions to
 sustainable food system outcomes, and vulnerability to losing those
 contributions. Estimates are presented for a high and a low emissions
 scenario in three different time windows (2030, 2050,
 2090).  
description: This analysis computes quantitative indices of climate risk for
 four aquatic food system outcomes – nutrition & health, economic,
 social, and environmental – adopting a fuzzy logic modeling approach to
 implement the risk assessment framework used by the Intergovernmental
 Panel on Climate Change. In this framework, climate risk results from the
 interaction between climate-change induced hazards, exposure to those
 climate hazards, and vulnerabilities of components of the aquatic food
 systems. For our purposes, we conceptualized climate hazards as the
 dominant climate variables that impact aquatic food production and supply
 chains, exposure as the degree to which aquatic foods contribute to the
 various food system outcomes at a national-level, and vulnerability as a
 combination of sensitivity to and adaptive capacity of the
 nationally-aggregated food systems in the face of the loss of aquatic food
 contributions. Through two rounds of virtual workshops, the team of
 co-authors – who were selected for their expertise spanning marine and
 freshwater ecosystems, fisheries and aquaculture production systems, and
 multiple food system outcomes – selected hazard, exposure, and
 vulnerability indicators based on their expert knowledge, published
 literature, and data availability for most of the countries included in
 this study. <strong>Climate
 hazards</strong> Climate hazard scores were
 calculated for six different components of aquatic food systems: marine
 fisheries, freshwater fisheries, marine aquaculture, freshwater
 aquaculture, brackish aquaculture, post-production processes. The
 following variables were selected for each of these components:
 Marine fisheries: Maximum catch potential (from an
 ecology model based on ocean temperature, circulation, dissolved oxygen,
 net primary production in the top 100m, salinity and sea ice) ; surface
 and bottom pH; marine heatwave frequency Freshwater
 fisheries: Near-surface air temperature; freshwater balance; percent
 extraction of renewable freshwater Marine
 aquaculture: Maximum mariculture potential (from an ecology model based on
 ocean conditions, suitable marine area for farming, fishmeal and fish oil
 production) ; marine heatwave frequency; percent of population inundated
 by sea level; cyclone strength in Low Elevation Coastal Zone; global
 cropland temperature; feed Crude Protein index
 Freshwater aquaculture: Near-surface air temperature; freshwater
 balance; percent extraction of renewable freshwater; global cropland
 temperature; fishmeal/fish oil availability; feed Crude Protein
 index Brackish aquaculture: Near-surface air
 temperature; percent of population inundated by sea level; cyclone
 strength in Low Elevation Coastal Zone; global cropland
 temperature; fishmeal/fish oil availability; feed Crude Protein
 index Post-production: Near-surface air temperature;
 percent of population inundated by sea level; cyclone strength in Low
 Elevation Coastal Zone; change in sea ice extent; % of landings from
 small-scale operations Where possible,
 projections from three different Earth system models (ESM) were used to
 represent uncertainties in projections of environmental changes, all
 available from the Coupled Models Intercomparison Project Phase 6 (CMIP6):
 Geophysical Fluid Dynamics Laboratory (GFDL)-ESM4, The Institut
 Pierre-Simon Laplace (IPSL)-CM6A-LR, and Max Planck Institute
 (MPI)-ESM1-2-HR. We calculated climate hazards using two contrasting
 scenarios – Shared Socio-economic Pathway (SSP) 1 - Representative
 Concentration Pathway (RCP) 2.6 (SSP1-2.6) and SSP5-8.5. The SSP1-2.6 and
 SSP5-8.5 represent a ‘strong mitigation’ low-emissions pathway and a ‘no
 mitigation’ high-emissions pathway, respectively. For the marine heatwave
 variable, CMIP6 results were not yet available so CMIP5 equivalents were
 used. Results were calculated for the near future (2021-2040), middle
 (2041-2060) and end (2081-2100) of the 21st century. 
 <strong>Exposure</strong> The
 following exposure indicators were selected for each of the four food
 system outcomes: Nutrition &
 health: Per capita supply of marine and freshwater aquatic
 foods; percentage of a nation’s consumption of vitamin B-12 and DHA+EPA
 fatty acids derived from aquatic foods Economic:
 Contribution of aquatic food production to Gross Domestic Product (GDP);
 economic multipliers of marine supply chains; net aquatic food trade
 balance relative to GDP Social: Contribution of
 marine fisheries, aquaculture, and inland fisheries to employment; ratio
 of indigenous to national-average consumption of seafood
 Environmental: Average greenhouse gas emissions, nitrogen and
 phosphorus emissions, land use and freshwater use of different types of
 wild-capture and farmed aquatic food production 
 <strong>Vulnerability</strong> The
 following vulnerability indicators were selected for each of the four food
 system outcomes: Nutrition &
 Health: Percent of population below national poverty line; percent
 secondary educational attainment; percent stunted children under 5;
 Summary Exposure Values for Vitamin B-12 and omega-3 fatty
 acids;  Economic: GDP per capita; GINI coefficient;
 percent of population with access to bank account; R&D
 expenditures relative to GDP; average of Worldwide Governance Indicators;
 percent of landings from small-scale operations
 Social: Percent of population below national poverty line; GINI
 coefficient; percent of population with access to bank account; average of
 Worldwide Governance Indicators; percent secondary educational attainment;
 percent of landings from small-scale operations
 Environmental: GDP per capita; GINI coefficient; R&D
 expenditures relative to GDP; average of Worldwide Governance Indicators;
 Environmental Performance Index – Biodiversity & Habitat,
 Fisheries, and Climate Change; percent landings from small-scale
 operations <strong>Fuzzy logic
 system</strong> The fuzzy logic modeling system
 consists of three steps: Categorizing each
 indicator variable into one or more levels of ‘low’, ‘medium’, ‘high’ and
 ‘very high’ simultaneously, with the degree of membership defined by fuzzy
 membership functions (“fuzzification”) Accumulating
 the degree of membership associated with each level using the MYCIN
 algorithm for each of the subcomponents of climate risk (hazard, exposure
 and vulnerability) and applying a set of heuristic rules to combine the
 components into an aggregate risk score (“fuzzy reasoning”)
 Calculating a final score from the accumulated memberships in
 order to express climate risk on a scale from 1 to 100
 (“defuzzification”). For more information
 on the fuzzy logic methodology, see:  Cheung, W. W. L.,
 Pitcher, T. J. & Pauly, D. A fuzzy logic expert system to estimate
 intrinsic extinction vulnerabilities of marine fishes to fishing. Biol.
 Conserv. 124, 97–111 (2005). Cheung, W. W. L., Jones,
 M. C., Reygondeau, G. & Fr.licher, T. L. Opportunities for
 climate-risk reduction through effective fisheries management. Glob.
 Chang. Biol. 24, 5149–5163 (2018). Jones, M. C.
 & Cheung, W. W. L. Using fuzzy logic to determine the
 vulnerability of marine species to climate change. Glob. Chang. Biol. 24,
 e719–e731 (2018).
description: The datafile contains 6 tabs, for combinations of 2 emissions
 scenarios (SSP1-2.6, low-emissions; SSP5-8.5, high-emissions) and 3 time
 frames (2030, 2050, 2090). Each tab contains 23 variables for 240
 countries and territories. All variables are of a unit-less score ranging
 from 1-100, where &lt;25 indicates 'Low', 25-50 indicates
 'Medium', 50-75 indicates 'High', and &gt;75
 indicates 'Very High'. Missing data are marked by empty cells,
 shaded grey. Countries and territories marked with an asterisk (*) are
 ones for which data availability was low, indicating reduced confidence in
 resulting risk scores. The following variables are
 included: Hazard - Aggregate: Climate
 hazard score aggregated across all production systems based on present-day
 production weights; in all countries the 'post-production'
 component is assigned a weight of 10% Hazard – Marine
 fisheries: Climate hazard score for marine fisheries
 Hazard – Freshwater fisheries: Climate hazard score for
 freshwater fisheries Hazard – Marine aquaculture:
 Climate hazard score for marine aquaculture Hazard
 – Freshwater aquaculture: Climate hazard score for freshwater
 aquaculture Hazard – Brackish aquaculture: Climate
 hazard score for brackish aquaculture Hazard –
 Post-production: Climate hazard score for post-production
 processes Exposure – Nutrition_Health: Exposure score
 for the Nutrition & Health food systems outcome
 Exposure – Economic: Exposure score for the Economic food
 systems outcome Exposure – Social: Exposure score for
 the Social food systems outcome Exposure –
 Environmental: Exposure score for the Environmental food systems
 outcome Exposure to Hazard – Nutrition_Health:
 Exposure to Hazard score for the Nutrition & Health food systems
 outcome; scores were aggregated across all production systems based on
 present-day production weights; in all countries the
 'post-production' component is assigned a weight of
 10% Exposure to Hazard – Economic: Exposure to Hazard
 score for the Economic food systems outcome; scores were aggregated across
 all production systems based on present-day production weights; in all
 countries the 'post-production' component is assigned a weight
 of 10% Exposure to Hazard – Social: Exposure to
 Hazard score for the Social food systems outcome; scores were aggregated
 across all production systems based on present-day production weights; in
 all countries the 'post-production' component is assigned a
 weight of 10% Exposure to Hazard – Environmental:
 Exposure to Hazard score for the Environmental food systems outcome;
 scores were aggregated across all production systems based on present-day
 production weights; in all countries the 'post-production'
 component is assigned a weight of 10% Vulnerability –
 Nutrition_Health: Vulnerability score for the Nutrition & Health
 food systems outcome Vulnerability – Economic:
 Vulnerability score for the Nutrition & Health food systems
 outcome Vulnerability – Social: Vulnerability score
 for the Nutrition & Health food systems outcome
 Vulnerability – Environmental: Vulnerability score for the
 Nutrition & Health food systems outcome Risk
 – Nutrition_Health: Climate risk score for the Nutrition & Health
 food systems outcome Risk – Economic: Climate risk
 score for the Nutrition & Health food systems outcome
 Risk – Social: Climate risk score for the Nutrition &
 Health food systems outcome Risk – Environmental:
 Climate risk score for the Nutrition & Health food systems
 outcome More information can be found in
 the associated README file.