Contributors: A. Hall (TVUK), J. Marsh (TVUK), S. Sailley (Plymouth Marine Laboratory), J. A. Fernandes (AZTI), G. Chust (AZTI)

Issued by: Jenny Marsh (TVUK)

Issued Date: 31/07/2019

Ref: C3S_D422Lot2.PML.3.1_201907_Product_User_Guide_Fisheries_v1.1

Official reference number service contract: 2018/C3S_422_Lot2_PML/SC2

Introduction

This dataset contains model projections of fish catch and abundance for 28 species in European seas up to the end of 2098. The dataset was produced using the Size Spectra-Dynamic Bioclimate Envelop Model (SS-DBEM), a state-of-the-art model that projects the impact of changes in the environment and human activity on the abundance, biomass, and distribution of modelled species, whilst considering their ecology and physiology. Therefore, the SS-DBEM can project fish distribution and trends in response to climate change. It uses input data from the European Regional Seas Ecosystem Model (ERSEM).

Climate change is likely to have a significant impact upon the seas and oceans, affecting oceanic ecosystems and marine and coastal resources, such as fisheries and aquaculture. The SS-DBEM produces relative change of species abundance and species catch under three different scenarios considering different greenhouse gas concentrations and fisheries management practices. The three scenarios are:

• "World Markets": Fish stocks managed globally to prevent overfishing with business as usual emissions
• "National Enterprise": Fish stocks managed nationally resulting in overfishing with business as usual emissions
• "Global Sustainability": Fish stocks managed globally toward sustainability with mitigated emissions

The three scenarios were produced using inputs from two coupled marine models: the Proudman Oceanographic Laboratory Coastal Ocean Modelling System (POLCOMS)-ERSEM and the Nucleus for European Modelling of the Ocean (NEMO)-ERSEM. The POLCOMS-ERSEM is pan-European with an 11 km resolution. The NEMO-ERSEM covers the northwest European Shelf and northeast Atlantic at 7 km resolution. Both models can simulate regions in both the deep ocean and continental shelf, as well as modelling water temperature, salinity, chlorophyll-a, and currents.

The dataset is available to download from the Copernicus Climate Change Service Climate Data Store (CDS) as either as a zip file (.zip) or as a compressed tar file (.tar.gz). The default file format is NetCDF.

Reference Documents

The following is a list of reference documents with either a direct bearing on the content of this user guide, or additional information should it be required. Where referenced in the text, these are identified as RD-n, where 'n' is the number in the list below:

RD.1.User Guide for Products: NEMO-ERSEM and POLCOMS-ERSEM Dataset v1.1.

RD.2. Fernandes, J.A., Cheung, W.W., Jennings, S., Butenschön, M., de Mora, L., Frölicher, T.L., Barange, M. and Grant, A., 2013. Modelling the effects of climate change on the distribution and production of marine fishes: accounting for trophic interactions in a dynamic bioclimate envelope model. Global change biology, 19(8), pp.2596-2607. https://doi.org/10.1111/gcb.12231

RD.3. Cheung W.W.L., Close C., Kearney K., Lam V., Sarmiento J., Watson R., Pauly D., 2009. Projections of global marine biodiversity impacts under climate change scenarios. Fish and Fisheries, 10, 235–251. https://doi.org/10.1111/j.1467-2979.2008.00315.x

RD.4.IPCC, 2013: Annex I: Atlas of Global and Regional Climate Projections [van Oldenborgh, G.J.Collins, J. Arblaster, J.H. Christensen, J. Marotzke, S.B. Power, M. Rummukainen and T. Zhou (eds.)]. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

Fish Abundance and Catch Dataset

This dataset contains model projections of fish catch and abundance in European seas from 2006 to the end of 2098. Dataset specifications can be found in Table 1. The dataset was produced using the Size Spectra-Dynamic Bioclimate Envelop Model (SS-DBEM), which can project fish distribution and trends in response to climate change. It is important to note that the model is the full species distribution not specific stocks. The model does not try to simulate the exact number of individuals of a given species, but rather the relative number of individuals compared to other areas and other times. As such, while model units are expressed as "Number of individuals", they are not to be used to predict future stock; rather, trends in response to changes in climate and fishing management.

Table 1: Dataset description

SS-DBEM use the following environmental conditions data from the European Regional Seas Ecosystem Model (ERSEM):

• Primary production
• Bottom temperature
• Surface temperature
• Sea water pH
• Sea water Salinity
• Oxygen concentration
• Ocean currents

ERSEM is an ecosystem model of marine biogeochemistry and the lower trophic levels of the marine food web. It simulates the cycles of carbon and nutrient elements such as nitrogen, phosphorous, and silicon within the marine environment. Organisms at the bottom of the marine food web (phytoplankton) play an integral role in these cycles, therefore, are represented in the model. Organisms that feed upon phytoplankton are also represented as they provide a vital link to commercially exploited species higher trophic levels in the food web. More information regarding ERSEM is available in RD.1.

Multiple species can be modelled simultaneously using SS-DBEM, allowing competition for food resources (primary production) between species to be considered. SS-DBEM produces relative changes in species abundance and species catch under three different climate and fishing management scenarios. These scenarios are based on the climate change scenarios (Representative Concentration Pathway (RCP)) and the Maximum Sustainable Yield (MSY) concepts. An RCP is a greenhouse gas concentration (not emission) trajectory used by the Intergovernmental Panel on Climate Change (RD.4) to describe different climate scenarios, all of which are considered possible depending on how much greenhouse gases could be emitted in the future. RCP 8.5 refers to 'business as usual' with emissions continuing to rise, whereas RCP 4.5 assumes mitigation measures have been applied with emissions peaking in 2040. The MSY is the maximum catch that can be sustained over time while maintaining fish stocks. A MSY value of 1 means that the fish stocks are managed in a way where maximum yield is ensured without risking overfishing; a MSY value >1 indicates overfishing while a MSY value <1 indicates a case where the stock is managed in a sustainable way. The three combined climate and management scenarios available are:

• "World Markets": RCP 8.5 and MSY 0.8 (fish stocks managed globally to prevent overfishing)
• "National Enterprise": RCP 8.5 and MSY 1.1 (fish stocks managed nationally resulting in overfishing)
• "Global Sustainability": RCP 4.5 and MSY 0.6 (fish stocks managed globally toward sustainability)

The three scenarios were run using inputs from two separate coupled marine models: the Proudman Oceanographic Laboratory Coastal Ocean Modelling System (POLCOMS)-ERSEM, and the Nucleus for European Modelling of the Ocean (NEMO)-ERSEM. The POLCOMS-ERSEM is pan-European with an 11 km resolution. The NEMO-ERSEM covers the northwest European Shelf and northeast Atlantic at a 7 km resolution. These domains are displayed in Figure 1.

Figure 1: Pan-European (left) and northwest European shelf and northeast Atlantic (right) domains

Further information on the NEMO and POLCOMS coupled models is available in RD.1. A full production workflow is shown in Figure 2.

Figure 2. Workflow of the production of fish catch and abundance in European seas up to 2098 under different scenarios.

The dataset is provided through the Copernicus Climate Change Service CDS. Details on how to access the data are provided in section 4.1.

Climate Impact Indicators

Climate Impact Indicators (CIIs) are observed or projected measures that indicate an environmental, human, or economic impact that can be linked to changes in the climate. The following CIIs are available to download as part of the fisheries dataset.

Species Abundance

Species abundance refers to the number of individuals of the given species per grid cell to calculate relative changes over time, space and across scenarios. The available species are:

• Main species of interest: Atlantic Cod (Gadus morhua), saithe (Pollachius virens), haddock (Melanogrammus aeglefinus), European hake (Merluccius merluccius), Atlantic mackerel (Scomber scombrus), Atlantic herring (Clupea harengus), common sole (Solea solea), European plaice (Pleuronectes platessa);

• Other species: Shrimp (Crangon crangon), turbot (Scophthalmus maximus), common dab (Limanda limanda), veined Squid (Loligo forbesii), common cuttlefish (Sepia officinalis), European squid (Loligo vulgaris), blue whiting (Micromesistius poutassou), capelin (Mallotus villosus), Atlantic horse mackerel (Trachurus trachurus), European sprat (Sprattus sprattus), red mullet (Mullus barbatus), Atlantic halibut (Hippoglossus hippoglossus), European seabass (Dicentrachurs labrax), Atlantic salmon (Salmo salar), meagre (Argyrosomus regius), gilt-head seabream (Sparus aurata), European sardine (Sardina pilchardus), European anchovy (Engraulis encrasicolus), common dolphinfish (Coryphaena hippurus), Bluefin tuna (Thunnus thynnus).

It should be noted that that the model is of species distribution rather than specific stocks and exact numbers of individuals. While we model abundance of fish species, it is best to use the model outputs to estimate the change in estimated abundance compared to the present day (2000-2015 time period or another as defined by the user between 1990 and 2015) and not as absolute values.

• Units: Relative change in number of fish within this grid size

Species Catch

Species catch refers to the number of fish caught per grid cell. The species list covered by this CII is the same as above. It should be noted that this CII refers to the potential change in catch and not actual catch. Similarly to species abundance, the numbers provided cannot be considered absolute values, the model outputs are to be used to estimate the relative change in comparison to the present day (2000-2015 time period or another as defined by the user between 1990 and 2015) and not absolute values.

• Units: Relative change in number of fish caught within the grid cell

Quality Assurance

Size Spectra-Dynamic Bioclimate Envelop Model

The Dynamic Bioclimate Envelop Model modelling approach has a number of inherent assumptions and uncertainties that may affect the performance of the model (RD.3). Firstly, the model is based on the assumption that the current predicted species distributions depict the environmental preferences of the species and are in equilibrium. Secondly, the underlying biological hypothesis, represented by the model structure and input parameters, may be uncertain. Moreover, the models did not consider the potential for phenotypic and evolutionary adaptations of the species.

Theoretical and empirical data were used to model trophic interactions. The modelling approach does not incorporate the full range or complexity of interactions among species, but avoids the difficulties of formalising transient and complex species-specific predatory interactions at large-scales. It also requires no assumptions about the extent to which species-specific trophic interactions that are currently observed will persist in the future. Furthermore, at the system level, size-based processes account for much of the variation in prey choice and trophic structure.

Further information regarding the quality assurance of the model and associated uncertainties is available in RD.2.

European Regional Seas Ecosystem Model

ERSEM uses Coupled Model Inter-comparison Project Phase 5 data as an input, which is a standard experimental framework for studying the output of coupled atmosphere-ocean general circulation

models. The POLCOMS-ERSEM model has been validated through comparison to satellite values from the European Space Agency Climate Change Initiative Ocean Colour project and the Operational Sea Surface Temperature and Sea Ice Analysis dataset, using monthly values for years 1998-2015. The model broadly reproduces the temporal and spatial patterns of chlorophyll concentration and sea surface temperatures across the region.
The POLCOMS-ERSEM model contains the following known issues in model outputs:

• Mediterranean phosphate values are too high. The effect of this is that the modelled ecosystem is limited by nitrogen instead of phosphorus. However, tests suggest that the resulting productivity is similar.
• Nutrients and pH near river mouths are inaccurate. River discharge volume and physical model outputs such as temperature and salinity are not affected.

Further quality assurance information regarding the NEMO-ERSEM and POLCOMS-ERSEM can be found in RD.1.

Dataset User Guide

CDS Catalogue Download

Origin

There are two models available to select, SS-DBEM-NEMO (SS-DBEM model paired with the NEMO- ERSEM model) and SS-DBEM-POLCOMS (SS-DBEM model paired with the POLCOMS-ERSEM model). A description of these models can be found in section 3. In short, the SS-DBEM-NEMO model covers the northwest European shelf and northeast Atlantic for years up to 2049. The SS-DBEM-POLCOMS model covers the full pan-European domain up to 2098.

Variable

A full description of the CIIs available under the 'Variable' heading can be found in this user guide in section 3.1. For this dataset, there are two options: Species abundance or Species catch. The species of choice can be specified in the 'Species' selection section.

Experiment

There are two future greenhouse gas concentration scenarios available to download, RCP 4.5 and RCP
8.5. RCP 4.5 envisions peak emissions at 2040 before declining due to mitigating measures. RCP 8.5 is an extreme scenario that envisions emissions continuing to rise throughout the century.

Maximum Sustainable Yield

There are three MSY options to choose from as part of the three scenarios offered. MSY 0.6 represents fish stocks managed globally toward high sustainability and resilience with low fishing pressure, MSY 0.8 represents fish stocks managed globally to avoid overfishing and considering multispecies MSY with medium fishing pressure, and MSY 1.1 represents fish stocks managed nationally resulting in overfishing with non-perfect management or information for MSY achievement. The available MSY options depend on the 'Experiment' selection, as not all combinations of RCPs and MSYs are available.

Species

The SS-DBEM was used to project possible changes in biogeography (species distribution) and biomass (species catch) associated with climate change for the 28 listed species in section 3.1.1. At least one species of interest must be selected.

Format

The dataset can be downloaded either as a zip file (.zip) or as a compressed tar file (.tar.gz). The default file format is NetCDF.

Dataset Applications

The fisheries dataset can be used in the following use cases:

Fisheries and Aquaculture

The European Union (EU) requires fishing to be environmentally friendly, economically viable and socially sustainable to provide long-term European food security given prevailing and future climatic conditions. EU Policies also aim to boost aquaculture, and Strategic Guidelines have been published outlining the common priorities and general objectives.

Climate change may create new opportunities for commercial exploitation, in terms of the availability of new species to fisheries (range shifts) and conditions more suitable to the growth of new farmed products (e.g. warm water fishes and shellfish in temperate coastal and offshore areas). However, climate change is also expected to affect our overall capacity to achieve these ambitions. Consequently, a greater understanding is urgently required to ensure that management measures remain appropriate and achievable.

The Fish Abundance and Catch dataset can be used within the Fisheries and Aquaculture use case to further understand and aid future management measures. The dataset contains species abundance and species catch estimates modelled up to 2098 for the pan-European domain from the SS-DBEM- POLCOMS-ERSEM model (2049 for the SS-DBEM-NEMO-ERSEM model). These estimates partly take into account the ecology and physiology of species in three climate and fishing pressure scenarios.

Marine Spatial Planning

Marine spatial planning is one of the most important activities for marine-focussed policy-makers and regulators. Marine spatial planning, including the designation of conservation areas, is usually undertaken with a base on the current uses of territorial waters, advising exclusive use or co-location of multiple uses based on trade-offs across economic sectors, as well as maximising environmental sustainability.

This approach may be informed by stock assessment processes, expected spatial distribution of commercially interesting species, and other scientific advice that considers the progression of an ecosystem and its resources to present time. However, based on this information alone, it is difficult to consider within planning mechanisms how pervasive and wide-scaled processes linked to climate change are and will continue to modify the distribution and availability of marine living resources, as well as the distribution of habitats suitable for species of conservation value. This is because climate change imposes combinations of environmental stressors and ecosystem conditions on marine species that may be markedly different from those historically observed within a region.

Marine spatial planning commitments can often take no account of how resources could change in time. This is important since changes happening in the ocean, driven by pressures associated with climate change, will modify the future distribution of marine resources underlying the conservation, fisheries and aquaculture sectors.

Modelling approaches can be used to support marine spatial planning by providing a sound scientific basis with which to assess dependencies between the status of exploited marine ecosystems and environmental conditions that may affect fisheries returns and marine conservation effectiveness, including present and future climate change. The Fish Abundance and Catch dataset models current and future fish stocks and can be used for the designation of conservation areas, fishing, and aquaculture zones. It also takes into account changes over time from climate change and fishing pressure, making it suitable for use in guiding marine spatial planning commitments. Models can also offer the possibility to explore management scenarios and anticipate 'surprises', such as regime shifts, trophic cascades and bottlenecks in human responses resulting from the pressures of climate change on marine species.

Natural Capital Accounting

Natural capital refers to the world's stocks of natural assets, which provide goods and services fundamental to supporting economic development and human well-being. Natural Capital Accounting provides a structured approach to recording and monitoring the extent and condition of natural resources and ecosystems over time.

In the past, measures of human interactions with natural capital in the marine domain have been restricted to measurements of the income generated for the use of the natural resource, such as income from the sale of wild caught fish. It has long been recognised, though, that focusing solely on measuring income omits changes in the stocks of natural assets, often leading to their mismanagement. This is most clearly seen in the instances of overexploitation of fisheries in the pursuit of income growth. More recently, the physical assessments of marine natural capital accounts are based on the ecosystem condition (compiled from key characteristics) and extent. The Fish Abundance and Catch dataset could therefore be used in Natural Capital Accounting to monitor and predict the future marine properties from a fisheries perspective.

Copernicus Climate Change Service

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