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Indicator Specification

Changes in fish distribution in European seas

Indicator Specification
  Indicator codes: MAR 011
Published 19 Feb 2019 Last modified 24 Jan 2020
2 min read
This indicator looks at the temporal development of the ratio between the number of Lusitanian and Boreal fish species within ICES Statistical rectangles and ICES divisions.

Assessment versions

Published (reviewed and quality assured)
  • No published assessments
 

Rationale

Justification for indicator selection

There is increasing evidence of a northward shift in the distribution of marine plant- and animal species over recent decades (Poloczanska et al., 2016). This northward movement has been attributed mainly to global warming in the terrestrial, limnic and marine environments (e.g. Brander et al. 2016). However, the change in distribution might not be attributable to the changing climate alone, as other environmental and biotic factors influence species distributions. A combination of climate change and the increasing impacts of multiple anthropogenic activities are still poorly understood and are expected to escalate in the future (Hoegh-Guldberg and Bruno, 2010). However, several studies indicate that the number of fish species (Hiddink & Hofstede, 2010) and the northward spread in distribution (Petitgas et al. 2012 and Petitgas et al., 2013) are related to the temperature rise over recent decades. What seems to be crucial in the cases of anchovies is an increase in the frequency of warm summers — which favour larvae and juvenile growth — as well as a decrease in the number of severe winters — which is likely to improve winter survival survival (Petitgas et al. 2012).


Most of the warming that has happened on Earth over the past 50 years has occurred in the oceans, where a significant rise in temperature has been reported over time (1993-2017) for waters from the sea surface to a depth of 700 meters and from 700-2 000 meters (Johnson et al., 2018). The present indicator includes information on the fish species' biogeographical affinity and trends in SST, in order to investigate the linkage between changes in temperature and changes in the shares of Lusitanian (warm-favouring) and Boreal (cool-favouring) fish species.

Scientific references

Indicator definition

This indicator looks at the temporal development of the ratio between the number of Lusitanian and Boreal fish species within ICES Statistical rectangles and ICES divisions.

Units

The spatial units used in this indicator are ICES Statistical Rectangles and ICES divisions (https://www.ices.dk/marine-data/maps/Pages/ICES-statistical-rectangles.aspx)

The units of measurement are the L/B ratio of the number of Lusitanian (L) fish species to Boreal (B) fish species.

 

Policy context and targets

Context description

United Nations Framework

The United Nations Framework Convention on Climate Change (UNFCCC, 1992) was a response to global concerns that change in the Earth’s climate and its adverse effects are a consequence of human activities. The convention entered into force in 1994. Currently, there are 197 Parties to the United Nations Framework Convention on Climate Change, including the EU. The objective of the UNFCCC is ‘to achieve stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the climate system’. The first international agreement that global temperatures should be not be allowed exceed 2 °C was accepted in 2010 (UNFCCC, 2010). The first legally binding agreement to reduce global emissions of carbon dioxide (CO2) and other greenhouse gases and an obligation to start adapting to climate change was signed at the Paris conference in 2015 (UNFCC, 2015). Action to combat climate change and its impacts is also included in the Agenda 2030 (UN GA, 2015).

In 2015, UN contracting parties agreed to aim to limit the increase to 1.5 °C above pre-industrial levels, since this would significantly reduce the risks and impacts of climate change (EC, 2015).

EU 2020 Biodiversity Strategy

The European Commission has adopted a strategy to halt the loss of biodiversity and ecosystem services in the EU by 2020 (EC, 2011b). There are six main targets and 20 actions to help Europe reach its goal. The six targets cover: (i) full implementation of EU nature legislation to protect biodiversity, (ii) better protection for ecosystems and more use of green infrastructure, (iii) more sustainable agriculture and forestry, (iv) better management of fish stocks, (v) tighter controls on invasive alien species and (vi) a bigger EU contribution to averting global biodiversity loss.

Seventh Environment Action Programme

In November 2013, the European Parliament and the European Council adopted the Seventh EU Environment Action Programme to 2020 ‘Living well, within the limits of our planet’ (EC, 2013b). This programme is intended to help guide EU action on the environment and climate change up to and beyond 2020 based on the following vision: ‘In 2050, we live well, within the planet’s ecological limits. Our prosperity and healthy environment stem from an innovative, circular economy where nothing is wasted and where natural resources are managed sustainably, and biodiversity is protected, valued and restored in ways that enhance our society’s resilience. Our low-carbon growth has long been decoupled from resource use, setting the pace for a safe and sustainable global society.’

EU and climate change

EU policies aim to achieve climate target goals as a key priority. After objectives under the Kyoto Protocol for the period 2008-2012 were achieved, the EU Adaption Strategy Package was endorsed (EC, 2013a). The Strategy (EC, 2013a) aims for a more climate-resilient system by anticipating the adverse effects of climate change and taking appropriate action to prevent and minimise the damages. As part of a framework of climate and energy policies, by 2030, the EU has committed to cut emissions in the EU territory by at least 40 % below 1990 levels. The long term targets for 2050 aim to cut EU emissions by at least 80 % compared with 1990 levels (EC, 2010; EC, 2011a). Adaptation aims to anticipate the adverse effects of climate change and take appropriate action to prevent or minimise the damage they can cause, or take advantage of opportunities that may arise (EC, 2013a). Mitigation and adaptation to climate change are built into sectoral policies in EU funds, in the biodiversity strategy (EC, 2011b; EC 2013b), in marine issues (EC, 2008; EC 2017) and in water issues (EC, 2000).

Climate change is considered in the Marine Strategy Framework Directive (EC, 2008; EC 2017b) as a pressure on the marine environment, which needs to be considered in the programmes of measures as well as in the determination of good environmental status. Threshold values should be set on the basis of the precautionary principle, reflecting the potential risks to the marine environment, including climate change. One of the criteria is related to the distributional range of species, where relevant. Distribution patterns should be in line with prevailing physiographic, geographic and climatic conditions (EC, 2017a). Environmental concerns for Arctic waters in relation to climate change may require action to ensure the environmental protection of the Arctic (EC, 2008).

Targets

Not applicable

Related policy documents

Key policy question

Are there observed changes in marine fish distribution in European seas and are they related to climate change?

 

Methodology

Methodology for indicator calculation

The changes in the number of Lusitanian versus Boreal species (L/B ratio) has been related to mean yearly water temperatures measured either as SST or temperature in the upper layer, i.e. the upper 0-100 m, using data from the ICES Report on Ocean Climate (IROC). The changes in the L/B ratio are also related to inflow data from the same source. However, changes in the L/B ratio seem related to temperature not inflow size. As experienced during data preparation for the ICES WKFISHDISH (ICES 2016), the use of several surveys for the same rectangles and sub-divisions introduces the risk of mixing data with biased catchability, and therefore, only one survey has been chosen for each ICES statistical rectangle and sub-division. The current survey is chosen based on the best temporal and spatial coverage. A list of the surveys used can be found in Table 1.

 Table 1. Overview of the different surveys used for the specific ICES Sub-divisions

mar011-tab01

 

The data have been collected through a range of trawl surveys carried out in western European waters, stretching from the southern part of the Baltic Sea to the entrance to the Mediterranean Sea (Figure 1). The purpose of these surveys has been/is to estimate the fish stocks and their recruitment. The actual data are stored in the DATRAS Database in ICES, where the data can be accessed. It should be noted that there are similar trawl surveys carried out in parts of the Mediterranean Sea, but these data reside in national databases and they are not easily accessible. The spatial and temporal scale varies but, in general, sampling has been relatively stable since 2000. The longest time series can be found from the North Sea where sampling began in 1965. Sampling takes place by trawling in the ICES statistical rectangles in a particular quarter(s) of the year. Apart from determining the species, the biomass and number of specimen per length class have been registered. There is no doubt that the taxonomic resolution changed over time, but it has been at the same (high) level since 1986.

Illustration 1. Overview of the ICES divisions and statistical rectanglesMAR011-98493-ICES-divisions-overview

 

It is obvious that the taxonomic references to the species caught varies over such a long timeframe. Even though the exchange of data involves the use of AphiaID (species code used by the World Register of Marine Species (WoRMS), not all of the codes are valid. This means that several species occur as duplicates in the database, e.g. that one species occurs under 3 different AphiaIDs. With the purpose of unifying these species codes, a table has been created to transform all non-accepted codes to one valid AphiaID. A total of 603 fish taxa have been identified from these trawl surveys. It should be emphasised that this is not 603 species, as both synonyms and the occurrence of genus and higher taxonomic levels add to the list of taxa. About 8 % of the used Aphia Codes were not valid. It should be mentioned that several epibenthic non-fish species have been recorded in the surveys. All these species have been filtered out for the purpose of this investigation. The total fish and non-fish taxa adds up to more than 1 100 taxa.

Based on the described catchability issues highlighted in the previous section it was decided to summarise the data to presence/absence scores. The basic data used for this method is therefore the presence/absence of a given species within a specific rectangle in a given year (basically, was the species found in that rectangle that year?). Due to the fluctuation in the occurrence of fish species in each single rectangle, some data analyses have been aggregated to a higher level. The ICES division has been used for this aggregation (Ilustration 1).

The species have been classified according to biogeographical affinity, using the classification made by the RECLAIM project (RECLAIM, 2008). A list of the classifications of species can be found in Annex 1 to RECLAIM (2008) report. It is clear that not all species have been classified in this overview but it is likely that the biogeographical affinity of these unclassified species can be found through a literature review.

Statistical test used: Mann-Kendall test for monotonic trends. The p-value represents probability that there is no time change and the value is based on random fluctuations only. If the p-value is under 0.05, the alternative hypothesis, i.e. that the trend is significant, is accepted.


 

Methodology for gap filling

Not applicable

Methodology references

 

Data specifications

EEA data references

  • No datasets have been specified here.

External data references

Data sources in latest figures

 

Uncertainties

Methodology uncertainty

The methods used are considered rather robust as they transform the catches to presence/absence of species rather than using the fish species abundance. Abundance would likely result in more noise in the data, as the number of specimens caught in a trawl haul influences greatly the actual physical conditions on that day (e.g. current direction and time of day).

Data sets uncertainty

It should be emphasised that catch in these trawl surveys does not represent exactly the fish fauna that is present in a given area. Several factors influence the catchability of a certain fish. The data collected have to be evaluated in light of some constraints in the way the survey has been carried out:

• The trawls used in the surveys are benthic trawls, so it is less likely that they have the same catchability as e.g. pelagic species such as mackerel and herring. However, the pelagic species are caught to some extent and even species like the Atlantic blue fin tuna and swordfish appear in the species list (Annex 1 to RECLAIM (2008) report). However, it is important to emphasise that there is no reason to expect catchability to change over time in the same habitat and using the same gear.

• The data coverage in space and time is limited, but has been quite stable over the last 15 years

• It is most likely that the catchability of species varies between different surveys due to the different gear used. However the restriction to use only one survey for each division ensures that the catchability should be the same over time

• The catchability of some species most probably varies between different habitats (bottom types). However, it is not likely that the habitats change within the same division.

Rationale uncertainty

none

Further work

Short term work

Work specified here requires to be completed within 1 year from now.

Long term work

Work specified here will require more than 1 year (from now) to be completed.

General metadata

Responsibility and ownership

EEA Contact Info

Monika Peterlin

Ownership

European Environment Agency (EEA)

Identification

Indicator code
MAR 011
Specification
Version id: 1

Frequency of updates

Updates are scheduled every 3 years

Classification

DPSIR: Impact
Typology: Descriptive indicator (Type A - What is happening to the environment and to humans?)

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