Additional notes for Regional FishMIP Models [16]
The goal of FishMIP 2.0’s “Ocean System Pathways” (OSP) Protocol is to project climate change impacts to ecosystems and fisheries under different societal and fisheries management development scenarios. This simulation round extends our previous climate impact projections to include past and future fisheries development to enable us to identify key risks and explore adaptation to climate change including consequences for biodiversity, fisheries and food security.
The future scenarios we are using have been developed to complement and be consistent with the Shared Socioeconomic Pathways, but with socioeconomic drivers needed for fisheries and aquaculture. These are labelled Ocean System Pathways (OSPs) (Maury et al. 2024).
This protocol provides details on the experimental set-up and data forcings required to run each of these scenarios, with and without climate change.
Note that this protocol builds on the FishMIP’s Phase 1 ISIMIP 3b which focused primarily on results without fishing, for fast-track inclusion in the IPCC 6th Assessment (Tittensor et al. 2021). The historical component also contributes to FishMIP 2.0’s ISIMIP 3a protocol on “Model Evaluation, Detection, and Attribution” (Blanchard et al. 2024, Frieler et al. 2023).
Timelines for simulations: TO BE DISCUSSED
| Scenarios | Models | Date |
|---|---|---|
| OSP-Baseline (Table 1) | global, regional | 2025-2026 |
| OSP-Future (See Table 2) | global, regional | 2025-2026 |
| OSP-Fisheries and Food Security (See Table 3) | global, regional | TBD |
| OSP-Nature Future Framework(See Table 4) | global, regional | TBD |
To aid with progress we will hold specific technical workshops to:
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Ensure correct OSP integration inputs and access
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Ensure fishing drivers work (separate global and regional breakaway groups)
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Tool sharing & troubleshooting
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Check model outputs/issues
In this document we describe the general experimental and scenario set-up (Section 3). Further down in Section 4 we include the details of the specific input variables that modellers can use to implement scenarios. In Section 5 we describe the set of outputs to be created. Finally in Sections 6-7 we provide further notes and instructions on how to report and upload model results.
This protocol is a contribution to the wider Inter-Sectoral Model Intercomparison Project (ISIMIP3a and ISIMIP3b) simulation rounds, further details can be found here:
https://protocol.isimip.org/#ISIMIP3b/marine-fishery_regional/marine-fishery_global
For this simulation round, we are asking you to run XXXXXXXX
Each model experiment is a set of model simulations that has a particular goal (e.g. model evaluation). A scenario is a particular setting for forcing drivers that describes how each model run should be set up in the experiment, including both the type of climate forcing (CF) and the type of direct human forcing (DHF).
The OSP protocol is grouped into three simulation model experiments. The below text is taken from Maury et al. 2024.
A. OSP-baseline: This is designed to initialise and evaluate the two-way feedback between socioeconomic demand scenarios, markets, and fleets developed in a new simulation framework (Maury et al. 2024) to model dynamic fishing effort and evaluate it against available data. It also seeks to identify and disentangle the respective roles of climate and socio-economic factors in the historical evolution of marine ecosystems and fisheries. It includes components corresponding to the ISIMIP3a (e.g. the Realistic-baseline) and the ISIMIP3b (e.g. the Spin-up, Reference, Historical) protocols. Prior to the below simulation runs, a 100-year Spin-up of the MEMs without fishing, and using the pi-control climate forcing, is required.
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A 1850-2100 Reference simulation (without fishing and without climate change), following the spin-up and using the pi-control climate forcing.
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Three 1850-2014 Historical simulations:
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Historical-a with 1850-2014 historical climate forcing and fishing with 1850-2014 OSP drivers based on reconstructed and observed GDP and population. This simulation provides the 1957 initial conditions for the Realistic-baseline simulation (see below).
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Historical-b with 1850-2014 historical climate forcing and without fishing.
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Historical-c without climate change (pi-control climate) and with fishing according to 1850-2014 OSP drivers based on reconstructed and observed GDP and population.
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A 1958-2022 Realistic-baseline simulation with the reanalysis-driven ‘realistic’ climate forcing and fishing with 1958-2022 OSP drivers based on observed GDP and population. This simulation branches off from the Historical-after 1957.
The realistic-baseline simulation will be used to evaluate the simulation framework against fishery catches (FAO, 2020, 2024a), reconstructed fishing effort (Rousseau et al., 2024) and observed prices (FAO, 2024b).
To attribute climate effects, fishing effects and their potential interactions (whether antagonistic or synergistic), a counterfactual approach will be employed. The difference between the Historical-b and the Reference simulation over the same time period will allow the identification of historical climate effects on the ecosystem. The difference between the Historical-c and the Reference simulation over the same time period will allow the identification of historical fishing effects on the ecosystem. The difference between the Historical-a simulation and the sum of the climate and fishing effects (Hist-a minus Historical-b minus Historical-c plus 2 Reference) will provide the interactive effects of climate and fishing on the ecosystem.
Further to this, the difference between the Historical-a and the Historical-b simulations will enable the identification of fishing impacts on the ecosystem experiencing climate change, and the difference between the Historical-a and the Historical-c simulations will allow the identification of climate change impacts on the coupled social-ecological fishery system.
Table 1: OSP-Baseline simulations. Control run and historical simulation experimental set-up. Note that each simulation is specified by the Climate forcing and Fishing forcing. Definitions of the specifiers (e.g. nat, picontrol etc.) that are used for ISIMIP filenaming are provided in Tables 3 and 4 below.
| No. | Simulation | Short d escription | T ime-period and specifiers | Priority level |
|---|---|---|---|---|
| 1 | Pre- industrial control | Climate: No climate change, fixed 1850s
CO Fishing: No fishing |
1850-2100 picontrol nat |
2 |
| 2 | Historical fishing dynamics, no climate | Climate: No climate change, fixed 1850s
CO Fishing: Historical fishing dynamics, forced by OSP drivers |
1850-2014 picontrol histsoc |
2 |
| 3 | Historical climate only | Climate: Simul ated/rea nalysis? historical climate change Fishing: No fishing |
1850-2014 reanalyis nat |
2 |
| 4 | Historical climate and fishing dynamics | Climate: Simulat ed/rea nalysis? historical climate change Fishing: Historical fishing dynamics, forced by OSP drivers |
1850-2014 reanalyis histsoc |
1 |
| 5 | Realistic |
For fishing effort prior to 1850 hold fishing at 1850 levels. [need to DISCUSS above states no fishing, this is from 3a]
For the ‘no fishing’ runs (nat), the spin-up should not use any fishing effort.
B. OSP-future: This second thread is dedicated to carrying out scenario simulations from the perspective of the IPCC. The aim is to estimate the impact of climate change and the socio-economic context on marine ecosystems, fisheries and the benefits they provide to societies worldwide. It contributes to ISIMIP3b, which focuses on assessing the climate change impacts, and involves running:
Scenario-a: The five OSP scenarios (2015-2100) with fishing and SSP climate change, starting from the Historical-a simulation. This simulation is designed to simulate the impacts of climate change on fishery and food consumption in the different socio-economic OSP contexts.
Scenario-b: The five OSP scenarios (2015-2100) without fishing but with SSP climate change, starting from the Historical-b simulation. This simulation is designed to simulate the impacts of different levels of future climate change on marine ecosystems.
Scenario-c: The five OSP scenarios (2015-2100) with fishing but no climate change (pi-control climate), starting from the Historical-c simulation. This simulation is designed to highlight the effects of the various socio-economic OSP contexts on fisheries.
Comparing the Scenario-a and Reference simulations during the same time period will allow for the identification of the combined effects of different climate change and socio-economic contexts. Comparing the Scenario-b and Reference simulations will allow for the assessment of climate impacts on the ecosystem at different levels of climate change. Additionally, comparing Scenario-c and the Reference simulation will enable the characterisation of the impact of distinct socio-economic contexts on the social-ecological fishery system. The interactive effects of climate and the socio-economic context on the social-ecological fishery system can be determined by calculating the difference between the Scenario-a simulation and the sum of the climate and fishing effects (Scenario-a minus Scenario-b minus Scenario-c plus 2 Reference).
Finally, the difference between the Scenario-a and the scenario-b simulations will enable the identification of fishing impacts on the ecosystem experiencing different levels of climate change, and the difference between the Scenario-a and the Scenario-c simulations will allow the identification of climate change impacts on the coupled social-ecological fishery system.
Table 2: OSP-Future simulation experimental set-up. Note that each simulation is specified by the Climate forcing and Fishing forcing. Definitions of the specifiers (e.g. nat, picontrol etc.) that are used for ISIMIP filenaming are provided in Tables 3 and 4 below.
| No. | Simulation | Short d escription | Time period and specifiers | Phase |
|---|---|---|---|---|
| 1-5 | All SSPs (1-5), no climate change, OSP1 fishing | Climate: No climate change Fishing: OSP1-5 future fisheries dynamics (following on from historical OSP) |
2015-2100 picontrol osp1soc |
2 |
| 6-10 | All SSPs with climate change (SSP1-2.6, SSP5-8.5), no fishing | | Climate: SSP-RCP climate scenarios (e.g. SSP1-2.6, SSP5-8.5) Fishing: No fishing |
2015-2100 ssp <scen> nat | 2 |
| 11-15 | All SSPs with climate change (SSP1-2.6, SSP5-8.5) and OSP1-5 fishing | Climate: SSP-RCP climate scenario, (e.g. SSP1-2.6, SSP5-8.5) Fishing: OSP1-5 future fisheries dynamics (matched to each SSP, e.g. SSP1RCP2.6 would use OSP1) |
2015-2100 ssp <scen> o sp<x>soc |
2 |
The following additional policy-targeted experimental sensitivity runs will be updated in due course.
C. OSP-management & food security: This third thread is devoted to scenario simulations from the FAO perspective. It aims to focus on the effects of fishery management on food security, in the “conventional trends” context of OSP2. It involves running:
The OSP2 scenario (2023-2100) with fishing, no management, and climate change (RCP4.5).
The OSP2 scenario (2023-2100) with fishing, fully compliant MSY management, and climate change (RCP4.5).
Comparing these two simulations with the OSP2 Scenario-a simulation (with present-day management) will provide insights into the risks of fishery management failure and the potential gains of fully compliant MSY management on global food security.
D. OSP-Nature Future Framework: This fourth thread is dedicated to mapping the OSP scenario simulations to the IPBES perspective and the NFF. The aim here is to compare three ways of envisioning the “Sustainability First” OSP1 scenario, corresponding to the three perspectives on Nature of the “Nature Futures Framework” from the IPBES (“Nature for Nature”, “Nature as Culture”, and “Nature for Society”, Pereira et al., 2020; Kim et al., 2023). While the definitive setup of this set of simulations has not yet been fully determined, it would involve running:
The OSP1 scenario (2023-2100) with fishing, management transitioning to 50% of the ocean in fully protected MPAs, and moderate climate change (SSP1-2.6). This simulation corresponds to the IPBES NFF “Nature for Nature” pathway.
The OSP1 scenario (2023-2100) with fishing, artisanal fisheries managed at MSY and no industrial fisheries, and moderate climate change (SSP1-2.6). This simulation corresponds to the IPBES NFF “Nature as Culture” pathway.
The OSP1 scenario (2023-2100) with fishing, the management of both artisanal and industrial fisheries at Maximum Economic Yield (MEY), and moderate climate change (SSP1-2.6). This simulation corresponds to the IPBES NFF “Nature for Society” pathway.
Comparing these three simulations will bring insights into the performances of the three NFF strategies, in terms of food supply, biodiversity conservation, employment and economic benefits generated in the context of the OSP1 mild climate change.
Throughout the protocol we use ‘specifiers’ that are shortened names used to denote a particular scenario, variables, or other parameter in the filenames of model inputs and outputs. It is crucial that you also use the same specifiers in your output files.
Correct formatting and naming of output files are essential for model intercomparison and analysis.
Tables 2-4 describe the different scenarios for the model runs described in Table 1. These specifiers are used in the file names of the corresponding input files and should also be used for the names of the output files (see 7. Reporting model results).
Scenario specifier picontrol |
Description Pre-industrial climate as simulated by the Earth System Models (ESMs) |
| historical | Historical climate as simulated by the ESMs, starting in 1950. |
| ssp126 | SSP1-2.6 climate as simulated by the ESMs |
| ssp245 | SSP2-4.5 climate as simulated by the ESMs. |
| ssp370 | SSP3-7.0 climate as simulated by the ESMs. |
| ssp460 | SSP4-6.0 climate as simulated by the ESMs. |
| ssp585 | SSP5-8.5 climate as simulated by the ESMs. |
| Scenario specifier | Description |
|---|---|
| histsoc | Varying direct human influences in the historical period (1850-2014) (i.e. historical estimates of fishing drivers). |
| 2015soc | Fixed year-2015 direct human influences (i.e. fishing effort). |
| o sp<x>soc | Future fishing determined by SSP and OSP driver forcings for OSP<x>, where <x> is 1-5. |
| nat | No fishing (naturalized run). |
Please remember to use these same specifiers in your output files. More on reporting data can be found at the end of this document.
For modellers new to FishMIP: to access all input data you first need to set up an account with ISIMIP to access the DKRZ server. Please follow the instructions here: https://www.isimip.org/dashboard/accessing-isimip-data-dkrz-server/
| Title | Spec ifiers | Institution | Or iginal reso lution |
|---|---|---|---|
| GF DLESM4 | gf dlesm4 | National Oceanic and Atmospheric Administration, Geophysical Fluid Dynamics Laboratory, Princeton, NJ 08540, USA | 2 88x180 |
| IPSL CM6ALR | ipslc m6a-lr | Institut Pierre Simon Laplace, Paris 75252, France | 1 44x143 |
| OT HERS?? |
Table 6. Climate forcing variables and units for FishMIP 3a simulations. All variables are available on a 0.25 and 1 degree horizontal grid, monthly and annual resolutions. Note: Some variables are available as specific layers extracted from vertically resolved data. Their variable names have been suffixed with -bot (ocean bottom, e.g. o2-bot), -surf (surface values, e.g. pH-surf) or -vint (vertically integrated, e.g. phyc-vint), respectively, or prefixed with int (vertically integrated, e.g. intpp). Temperature is suffixed with b or s for bottom (e.g. tob) or surface (e.g. tos) layers, respectively.
| Variable | Specifier | Unit | Resolution | ESM datasets |
|---|---|---|---|---|
| Mass Con centration of Total Phy toplankton Expressed as C hlorophyll | chl | kg m-3 | 0.25° , 1° grid | GFDL, IPSL |
| Sea Floor Depth | deptho | m | 0.25° , 1° grid | GFDL, IPSL |
| Downward Flux of P articulate Organic Carbon | exp c-bot | mol m-2 s-1 | 0.25° , 1° grid | GFDL, IPSL |
| P articulate Organic Carbon Content | * intpoc** | kg m-2 | 0.25° , 1° grid | GFDL, IPSL |
| Primary Organic Carbon Production by All Types of Phy toplankton | intpp | mol m-2 s-1 | 0.25° , 1° grid | GFDL, IPSL |
| Net Primary Organic Carbon Production by Diatoms | intp pdiat | mol m-2 s-1 | 0.25° , 1° grid | GFDL, IPSL |
| Net Primary Mole Pr oductivity of Carbon by D iazotrophs | intp pdiaz | mol m-2 s-1 | 0.25° , 1° grid | GFDL, IPSL |
| Net Primary Mole Pr oductivity of Carbon by Picoph y toplankton | intp ppico | mol m-2 s-1 | 0.25° , 1° grid | GFDL, IPSL |
| Maximum Ocean Mixed Layer Thickness Defined by Sigma T | mlotst | m | 0.25° , 1° grid | GFDL, IPSL |
| Dissolved Oxygen Con centration | o2, o 2-bot o2 -surf |
mol m-3 mol m-2 mol m-2 |
0.25° , 1° grid | GFDL, IPSL |
| pH | ph ph-bot ph -surf |
1 1 1 |
0.25° , 1° grid | GFDL, IPSL |
| Phy toplankton Carbon Co n centration | phyc phyc -vint |
mol m-3 mol m-2 |
0.25° , 1° grid | GFDL, IPSL |
| Mole Con centration of Diatoms expressed as Carbon in sea water |
phydiat -vint |
mol m-3 mol m-2 |
0.25° , 1° grid | GFDL, IPSL |
| Mole Con centration of D iazotrophs Expressed as Carbon in Sea Water |
phydiaz -vint |
mol m-3 mol m-2 |
0.25° , 1° grid | GFDL, IPSL |
| Mole Con centration of Picoph ytoplankto nExpressed as Carbon in Sea Water |
phypico -vint |
mol m-3 mol m-2 |
0.25° , 1° grid | GFDL, IPSL |
| Sea Water Salinity | so so-bot so -surf |
‰ ‰ % |
0.25° , 1° grid | GFDL, IPSL |
| Sea Water Potential T emperature | thetao | °C | 0.25° , 1° grid | GFDL, IPSL |
| Ocean Model Cell Thickness | thk cello | m | 0.25° , 1° grid | GFDL, IPSL |
| Sea Water Potential T emperature at Sea Floor | tob | °C | 0.25° , 1° grid | GFDL, IPSL |
| Sea Surface T emperature | tos | °C | 0.25° , 1° grid | GFDL, IPSL |
| Sea Water X Velocity | uo | m s-1 | 0.25° , 1° grid | GFDL, IPSL |
| Sea Water Y Velocity | vo | m s-1 | 0.25° , 1° grid | GFDL, IPSL |
| Mole Con centration of Meso z ooplankton expressed as Carbon in sea water | zmeso zm eso-vint |
mol m-3 mol m-2 |
0.25° , 1° grid | GFDL, IPSL |
| Mole Con centration of Microz ooplankton expressed as Carbon in sea water | zmicro zmi cro-vint |
mol m-3 mol m-2 |
0.25° , 1° grid | GFDL, IPSL |
| Z ooplankton Carbon Con centration | zooc z ooc-vint |
mol m-3 mol m-2 |
0.25° , 1° grid | GFDL, IPSL |
| Net Downward Shortwave Radiation at Sea Water Surface | rsntds | W m-2 | 0.25° , 1° grid | GFDL, IPSL |
| Sea Ice Area Fraction | siconc | % | 0.25° , 1° grid | GFDL, IPSL |
The climate forcing input files can be found using the following pattern:
levante:/work/bb0820/ISIMIP/ISIMIP3b/InputData/climate/ocean/uncorrected/<glob
al or regional>/monthly/<climate-scenario>/<climate-forcing>/<climateforcing>_<ensemble-member>_<climate-scenario>_<climatevariable>_global_monthly_<start-year>_<end-year>.nc
The variables deptho and thkcello are fixed through time and can be found in the “fixed/” folder (rather than monthly/).
Production and carbon data for large and small phytoplankton can be derived from the variables in Table 1 by the following:
large = diatoms + diazotrophs
small = picophytoplankton
The GFDL model treats diazotrophs as large phytoplankton as part of their food-web processes.
For regional models, only specific grid cells will be needed from the above global outputs. Please let us know if you require assistance to extract results (e.g. using bounding boxes, masks or shapefiles). This functionality is now partially available (bounding box) through the ISIMIP web-based data portal.
A simple worked example on how to do this for specific regions in R is provided here: https://github.com/Fish-MIP/FishMIP_extracting-data
| Specifier | Included variables (short names) and definitions | Time period /Resolution | Filename |
|---|---|---|---|
| histsoc | NomActive = Nominal fishing effort of the active fleet d is-aggregated by:
functional group
|
|
|
| 2015soc | Final year of values from histsoc repeated until 2100 |
|
|
| Historical Population | |||
| Historical GDP | |||
| SSP<x> Population | |||
| SSP<x>GDP | |||
| MPAs | |||
| OS P<x>Drivers |
| Va riable Name | Long name | Unit | Description/notes |
|---|---|---|---|
| Year | (End of the) year when the f ishing effort is occ urring | Number code | |
| Sector | The f ishing sector d efined by the law of the c ountry | Name code | I = Industrial and A = artisanal, where artisanal include powered and unpowered artisanal fleets |
| LME | Large Marine Eco system Number | Number code | A number code of the Large Marine ecosystem in which the Effort is occurring |
| eez_ countr y_name | Exc lusive Ec onomic Zone | Name code | The country-level exclusive economic zone (or high seas) name in which fishing effort is occurring |
| SAUP | A number code for the f ishing co untry, fol lowing Sea Around Us num bering | Number code | Ex supranational entities (USSR, Yugoslavia) are disaggregated to their constituent countries. Serbian Fishing Effort included with Montenegro. Crimea included with Ukrainian. |
| Gear | The f ishing gear | Name code | Gear names |
| FGroup | The ta rgeted func tional group | Name code | Functional groups are in accordance with those used by the Sea Around Us Project |
| Nom Active | N ominal f ishing effort (i.e., not inc luding the t echnol ogical creep) of the active fleet | Days at sea X kW | NomActive (of the active fleet; i.e., total) = P (engine power of active the fleet; i.e., total) x DAS (average days at sea of one vessel). Average DAS for one vessel ~ 200 DAS/year. NomActive corresponds to the total (reported, IUU, discards) catch. To find NomActive in DAS do (NomActive/P) X NV |
Table 9: Details for OSP relative change in drivers of fishing effort variables. HOW TO DESCRIBE HOW WE WILL VARY MANAGEMENT IN THE MODELS ACROSS OSPs??
| OSP | Management |
|---|---|
| OSP1 | All stocks fished at Fmsy or B/B0 > 0.5?? |
| OSP5 | Fmsy or B/B0?? |
TO DO: We provide code examples showing how to implement the OSPs?
The monthly fishing effort forcing files for the spin-up and experiments (Table 1) of this simulation protocol can be found on DKRZ here:
levante:/work/bb0820/ISIMIP/ISIMIP3b/InputData/socioeconomic/fishing/histsoc/
For global models, the above spatially aggregated fishing effort can be spatially allocated into 0.25 grid cells. This can be achieved using different approaches such as a simple gravity model – e.g. see Coll et al. 2020 but details will depend on model structure.
We are developing a simplified worked example for global modellers to explore and contribute to. This will be made available on github/FishMIP in due course.
While we recommend using the above spatially aggregated effort, for global models that cannot technically carry out spatial allocation of effort, gridded total industrial and artisanal nominal active effort have been provided in the same folder as the file above and are saved as netcdf files. These can be allocated to functional groups (e.g. according to relative biomass) depending on model structure.
Downscaling of the above fishing effort to match regional model inputs is likely to be needed. We request that regional modellers work together in their specific regions to ensure we have clear and common methodologies.
We are developing a worked example for regional modellers to explore and contribute to for their region which will be made available on github/FishMIP in due course.
Modellers are permitted to calibrate or tune their models using historical fisheries catch data (that will also be used for model evaluation) on the condition that only years up to and including 2004 are used in model calibration/tuning.
Modelling groups must keep detailed documentation on how their model was calibrated (e.g. input forcing, calibration data, time domain, spatial domain, fish grouping (size, functional types, total), optimization metric(s), weighting schemes, etc.) to be included in manuscript methods. Written description of sources of calibration data and methods used need to be provided with all simulation outputs. A template will be provided for this documentation in due course.
The fisheries catch data .csv file that can be used for model calibration is here:
levante:/work/bb0820/ISIMIP/ISIMIP3a/InputData/socioeconomic/fishing/histsoc/calibration_catch_histsoc_1850_2004.csv.
The fisheries catch data are already aggregated into the functional groups and spatial zones as the above effort forcing data. The original reference including links to full database is Watson & Tidd, 2018, Marine Policy, 93: 171-177.
Large marine ecosystem (LME) masks in four different spatial resolutions. 0.1°, 0.25°, 0.5° and 1° are available here:
/work/bb0820/ISIMIP/ISIMIP3a/InputData/geo_conditions/fishmip_regions/
Each region has its own variable within each file.
We have also provided conversion tables that can be used to look up LME and SAUP names according to the numeric codes used in the catch and effort files (e.g. LME 22 – North Sea). These files (SAUPnames.csv and LMEnames.csv) are also available here:
/work/bb0820/ISIMIP/ISIMIP3a/InputData/geo_conditions/fishmip_regions/
All spatially gridded outputs should be created as netcdf files. More information on how to prepare these files can be found here. Aspatial regional model results may be saved as .csv files.
In the output files, please label the time variable as “days since 1841-1-1 00:00:00” if the output covers the spin-up and transition period (1841-1960) or “days since 1901-1-1 00:00:00” if the output covers the experiment period (1961-2010).
Table 9: Mandatory output variables for Fisheries and Marine Ecosystem models (global and regional). See notes on additional optional model outputs below. Please use the value 1.e+20 for missing data within your output files. All biomasses are in wet weight (not g C).
| Variable long name | Variable spe cifier | Unit | Resolution | Comments |
|---|---|---|---|---|
| Total Consumer Biomass Density | tcb | g m-2 | 0.25° grid monthly |
All consumers (trophic level >1, vertebrates and in vertebrates) |
| Total Consumer Biomass Density in log10 Weight Bins | tcblog10 | g m-2 | 0.25° grid monthly |
Level dimensio ns: (time, bins, lat, lon). If the model is size -structured, please provide biomass in equal log 10 g weight bins (1-10g, 10-100g, 100g-1kg, 1-10kg, 10-100kg, >100kg) |
| Total Pelagic Biomass Density | tpb | g m-2 | 0.25° grid m onthly |
All pelagic consumers (trophic level >1, vertebrates and in vertebrates) |
| Total Demersal Biomass Density | tdb | g m-2 | 0.25° grid m onthly |
All demersal consumers (trophic level >1, vertebrates and in vertebrates) |
| Total Catch Density (all commercial functional groups / size classes) | tc | g m-2 | 0.25° grid m onthly |
Catch at sea (all catch as a result of all effort including reported and IUU) summed for both Industrial and Artisanal sector. |
| Total Industrial Catch Density (all commercial functional groups / size classes) | tic | g m-2 | 0.25° grid m onthly |
Catch at sea (all catch as a result of all effort including reported and IUU) for Industrial sector only. |
| Total Catch Density in log10 Weight Bins across both sectors |
|
g m-2 | 0.25° grid m onthly |
Level dimensio ns: (time, bins, lat, lon). If the model is size -structured, please provide biomass in equal log 10 g weight bins (1-10g, 10-100g, 100g-1kg, 1-10kg, 10-100kg, >100kg) |
| Total Pelagic Density Catch across Artisanal and Industrial sectors | tpc | g m-2 | 0.25° grid m onthly |
Catch at sea of all pelagic consumers (trophic level >1, vertebrates and in vertebrates) |
| Total Demersal Catch Density across Artisanal and Industrial sectors | tdc | g m-2 | 0.25° grid m onthly |
Catch at sea of all demersal consumers (trophic level >1, vertebrates and in vertebrates) |
| Optional output from global and regional models. All biomasses are in wet weight, not g C. | ||||
| Biomass Density of Small Pelagics <30cm | bp30cm | g m-2 | 0.25° grid monthly |
If a pelagic species and L infinity is <30 cm, include in this variable |
| Biomass Density of Medium Pelagics >=30cm and <90cm | bp30to 90cm | g m-2 | 0.25° grid monthly |
If a pelagic species and L infinity is >=30 cm and <90cm, include in this variable |
| Biomass Density of Large Pelagics >=90cm | bp90cm | g m-2 | 0.25° grid monthly |
If a pelagic species and L infinity is >=90cm, include in this variable |
| Biomass Density of Small Demersals <30cm | bd30cm | g m-2 | 0.25° grid m onthly |
If a demersal species and L infinity is <30 cm, include in this variable |
| Biomass Density of Medium Demersals >=30cm and <90cm | bd30to 90cm | g m-2 | 0.25° grid m onthly |
If a demersal species and L infinity is >=30 cm and <90cm, include in this variable |
| Biomass Density of Large Demersals >=90cm | bd90cm | g m-2 | 0.25° grid m onthly |
If a demersal species and L infinity is >=90cm, include in this variable |
| Catch Density of Small Pelagics <30cm | cp30cm | g m-2 | 0.25° grid m onthly |
Catch at sea of pelagic species with L infinity <30 cm |
| Catch Density of Medium Pelagics >=30cm and <90cm | cp 30to90cm | g m-2 | 0.25° grid m onthly |
Catch at sea of pelagic species with L infinity >=30 cm and <90 cm |
| Catch Density of Large Pelagics >=90cm | cp90cm | g m-2 | 0.25° grid m onthly |
Catch at sea of pelagic species with L infinity >=90 cm |
| Catch Density of Small Demersals <30cm | cd30cm | g m-2 | 0.25° grid m onthly |
Catch at sea of demersal species with L infinity <30 cm |
| Catch Density of Medium Demersals >=30cm and <90cm | cd 30to90cm | g m-2 | 0.25° grid m onthly |
Catch at sea of demersal species with L infinity >=30 cm and <90 cm |
| Catch Density of Large Demersals >=90cm | cd90cm | g m-2 | 0.25° grid m onthly |
Catch at sea of demersal species with L infinity >=90 cm |
More specific protocols for each regional model type will be developed through our monthly online regional modeller sessions. Please contact regional FishMIP coordinators for more information.
As a first step, regional modellers will need to provide shapefiles for their respective model domains for us to help with spatial extraction of the above global climate and fishing effort forcing inputs.
Region-specific climate forcing variables will be made available here:
/work/bb0820/ISIMIP/ISIMIP3b/InputData/climate/ocean/<obsclim> or <ctrlclim>/regional/
A .csv file with fishing effort extracted for regional model ecosystems
is also available in the same folder as the global fishing effort data
(../fishing/histsoc), for regional models that have provided
shapefiles.
Regional modellers may wish to make their raw unaggregated output available for more detailed analyses, including for example, a wider range of functional groups/size classes/species and ecosystem indicators. Please discuss this with FishMIP regional coordinators before uploading files.
The specification on how to submit the data, as well as further information and instructions are given on the ISIMIP website at:
https://www.isimip.org/protocol/preparing-simulation-files
It is important that you comply precisely with the formatting specified there, to facilitate the analysis of your simulation results in the ISIMIP framework. Incorrect formatting can seriously delay analyses. The ISIMIP Team will be glad to assist with the preparation of these files if necessary.
File names consist of a series of identifier, separated by underscores. Things to note:
-
Report one variable per file.
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In filenames, use lowercase letters only.
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Use underscore (_) to separate identifiers.
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Variable names consist of a single word without hyphens or underscores.
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Use hyphens (-) to separate strings within an identifier, e.g. in a model name.
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Data model is NETCDF4_CLASSIC with minimum compression level of 5.
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NetCDF file extension is .nc.
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The relative time axis’ reference date is days since 1841-1-1 00:00:00 if the output covers the spin-up and transition period (1841-1960) or days since 1901-1-1 00:00:00 if the output covers the experiment period (1961-2010). We have provided .csv files to be used for the time dimension in creating NetCDF files based on the 365 days calendar. Please see time_axix_spinup.csv and time_axis_experiment.csv in this repository. The script time_axis.r was used to create these files.
Please name the files in the Fisheries and Marine Ecosystems sector according to the following pattern:
Global models
<model>_<climate-forcing>_<bias-adjustment>_<climate-scenario>_<soc-scenario>_<sens-scenario>_<variable>_<global>_<time-step>_<start-year>_<end-year>.nc
Example:
boats_gfdl-mom6_cobalt2_none_obsclim_histsoc_default_tcb_global_monthly_1961_2010.nc
Regional models
<model>_<climate-forcing>_<bias-adjustment>_<climate-scenario>_<soc-scenario>_<sens-scenario>_<variable>_<region>_<time-step>_<start-year>_<end-year>.nc
Example:
osmose_gfdl-mom6_cobalt2_none_obsclim_histsoc_default_tcb_benguela_monthly_1961_2010.nc
Please see the climate-scenario, soc-scenario, sens-scenario and variable identifiers given in the tables of this document.
Global models
The output files covering the spin-up period (1841-1960) can be saved on DKRZ here:
/work/bb0820/ISIMIP/ISIMIP3a/UploadArea/marine-fishery_global/model_name/temp2
The output files covering the experiment period (1961-2010) can be saved on DKRZ here
/work/bb0820/ISIMIP/ISIMIP3a/UploadArea/marine-fishery_global/model_name/temp
Regional models
The output files covering the spin-up period (1841-1960) can be saved on DKRZ here:
/work/bb0820/ISIMIP/ISIMIP3a/UploadArea/marine-fishery_regional/model_name/temp2
The output files covering the experiment period (1961-2010) can be saved on DKRZ here
/work/bb0820/ISIMIP/ISIMIP3a/UploadArea/marine-fishery_regional/model_name/temp
Please contact FishMIP coordinators or ISIMIP data managers directly (isimip-data@pik‐potsdam.de) if you have any questions or clarifications before submitting files or if you do not find your model’s path on DKRZ as described above.
Please contact FishMIP coordinators if you would like to participate in this simulation round but have encountered issues with any aspect of the protocol.
(For fishing): please provide all assumptions about catchability, technological creep, and model calibration.
Please provide any conversion factors that you have used to convert units.
FishMIP is entirely community-driven, and we appreciate the effort of all involved.