1. Projecting global fish stocks and catches up to 2100
Jorn Bruggeman
Supporting Blue Growth with innovative applications based on EU e-infrastructures
14-15 February 2018, Brussels

2. Background Published in 2009, most downloaded FAO report
2018 update expected to influence policy world-wide
Outline
global projections
regional chapters
aquaculture implications
PML: catch projections per Exclusive Economic Zone
25/10/2019

3. Fish modelling Process-based modelling with simple rules
differentiate fish by size, not species
small fish feed on plankton, large fish on fish
metabolism is temperature dependent
Blanchard et al J Animal Ecol 78(1): 270–280
Blanchard et al Phil Trans Roy Soc B 367(1605): 2979–2989
25/10/2019

4. Data requirements Variables Space and time
abundance of plankton types of different sizes
temperature
Space and time
domain: global
period: present till 2100
temporal resolution: monthly or finer
spatial scale: ideally depth-explicit, aggregated per EEZ
25/10/2019

5. Sourcing climate projections
Coupled Model Intercomparison Project: CMIP5
20 climate models
historical run and multiple scenarios (RCPs):
gridded data (1°, 2°)
monthly data for surface ocean biogeochemistry
yearly data for depth-explicit biogeochemistry
25/10/2019

6. Workflow CMIP5 archive, 3.3 PB EEZ shapefile FAO FishStat internet
esgf-index1.ceda.ac.uk
EEZ shapefile
FAO FishStat
1. select & download
models: GFSL/IPSL/CMCC scenarios: RCP 2.6, 8.5
ocean biogeochemistry only
local cluster
5. validate catch against historical records
time series of stocks and catches per EEZ, 500 MB
± 800 GB
3. average over each Exclusive Economic Zone
8.75 GB
2. extract key variables:
temperature, plankton
± 80 GB
4. simulate fish per EEZ from 1850 to 2100
25/10/2019

7. Workflow CMIP5 archive, 3.3 PB EEZ shapefile FAO FishStat internet
esgf-index1.ceda.ac.uk
EEZ shapefile
FAO FishStat
UK Janet network
1. select & download
models: GFSL/IPSL/CMCC scenarios: RCP 2.6, 8.5
ocean biogeochemistry only
Python
local cluster
5. validate catch against historical records
Python
time series of stocks and catches per EEZ, 500 MB
± 800 GB
3. average over each Exclusive Economic Zone
8.75 GB
Python + Fortran
3.5 sec/simulated yr
parallelized
NetCDF Operators
2. extract key variables:
temperature, plankton
± 80 GB
4. simulate fish per EEZ from 1850 to 2100
25/10/2019

8. Projected change in catch
2050
2100
RCP 2.6
RCP 8.5 %
change
25/10/2019

9. FAO global capture production database
Present-day catches?
correlation: 0.57
Sources of uncertainty and error
observations: reporting per fishing nation, not EEZ; underreporting
inputs: plankton and temperature from climate models
parameterization: present and future fishing mortality (F = 0.2 yr-1)
FAO global capture production database
25/10/2019

10. Role of fishing mortality
F = 0.2 yr-1
F = 0.4 yr-1
F = 0.8 yr-1
Why does fishing not have more of an impact?
Stock and recruitment are decoupled: production of eggs and juveniles is set by plankton availability, not stock size
Predications of relative change are thus robust
25/10/2019

11. Key findings
surface temperature ↑
stratification ↑
surface nutrients ↓
plankton ↓
fish ↓
However:
Due to interplay between plankton and temperature, lower latitudes (poorer nations) are disproportionally affected
This becomes even more pronounced if we account for habitat change – tropical regions lose the most species
25/10/2019

12. Towards a service
Contract: develop a Marine, Coastal, Fisheries module for European seas
phase I: consult stakeholders
phase II: implementation and projection delivery
Potential follow ups
from European domain to global
regular updates
25/10/2019

13. Service design climate drivers
meteorology, river run-off, boundary conditions
CMIP, EURO-CORDEX, E-HYPE
Service developed by PML
hydrodynamics and biogeochemistry
European Regional Seas Ecosystem Model
Physics and biogeochemistry
temperature, plankton
fish modelling
eutrophication
ocean fronts
Climate Impact Indicator suite
Climate Data Store (CDS)
Use cases – developed with partners and stakeholders
Fisheries, Eutrophication, Marine Spatial Planning, Natural Capital Accounting
25/10/2019

14. Thank you https://www.surveymonkey.com/r/C3S_MCF_SIS
Manuel Barange, FAO
Momme Butenschön, Centro Euro-Mediterraneo sui Cambiamenti Climatici
William Cheung, University of British Columbia
Julia Blanchard, University of Tasmania
25/10/2019