Proportion de gros poisson (Indice de gros poisson)
Contexte
La mortalité par pêche limite la structure par âge des communautés halieutiques, réduisant la proportion d’individus plus gros et plus âgés des espèces impactées. OSPAR utilise actuellement plusieurs indicateurs communs relatifs à la taille des poissons et à la composition des espèces pour évaluer les impacts de la pêche sur les communautés de poissons au sein du réseau trophique.
L’indice de gros poisson (LFI) a été développé afin de répondre aux pressions exercées par la pêche sur la proportion de gros poisson dans les communautés halieutiques démersales (espèces vivant sur le sol marin ou à proximité) (Rochet et al., 2010). Des séries temporelles remontant aux années 1920 ont révélé que la proportion de gros poissons s'est appauvrie dans les années 1980 et 1990 en mer du Nord (Greenstreet et al., 2011) et dans le Firth of Clyde (Heath et Spiers, 2014). On considère que la pêche au rendement maximal durable conduira à un rétablissement de l'indicateur (Spence et al., 2021). En revanche, on considère que le changement climatique déprimera la reconstitution de l'indicateur à long terme (Queirós et al., 2018).
La méthodologie de l’indicateur LFI a été appliquée pour la première fois en mer du Nord (Greenstreet et al., 2011), et a ensuite été adaptée pour étendre l'indicateur aux mers celtiques (Shephard et al., 2011), au golfe de Gascogne et à la côte ibérique (Modica et al., 2014), et à l'Atlantique au large (Mindel et al., 2018). Des études au sein de la mer Méditerranée ont également démontré l'applicabilité de l'indicateur (Bitetto et al., 2019).
The LFI uses estimates of fish abundance-at-length provided by international bottom trawl surveys. These are standardised monitoring programmes that occur each year in the same period taking representative samples according to specific guidelines (see CEMP).
Indicator Metric and Data Collection
The Large Fish Index (LFI) was developed for the North Sea (Greenstreet et al., 2011, 2012), and uses estimates of fish biomass density-at-length provided by trawl surveys. The assessment of each survey requires the suite of species constituting the demersal fish community and the length threshold (LT) defining ‘large fish’ to be selected. The LFI is simply:
where B is biomass density (as kg/km2), l is length (in cm) of the individual fish size class, Lmin and Lmax are the minimum and maximum length of fish in the dataset.
The LFI time series were determined for multiple groundfish surveys carried out across four OSPAR Regions: the Greater North Sea, Celtic Seas, the Bay of Biscay and Iberian Coast, and Wider Atlantic. Multiple LFI time series were derived for each Region (Table a).
Region | Survey Acronym¹ | Assessment Period | Length threshold (cm) |
---|---|---|---|
Bay of Biscay and Iberian Coast | BBIC(n)SpaOT4 | 2011 – 2018 | 35 |
BBIC(s)SpaOT1 | 2000 – 2020 | 50 | |
BBIC(s)SpaOT4 | 2002 – 2020 | 45 | |
BBICPorOT4 | 2002 – 2018 | 35 | |
BBICFraBT4 | 2011 – 2020 | 40 | |
BBICFraOT4² | 1997 – 2020 | 35 | |
Celtic Seas | CSFraOT4² | 1997 – 2020 | 40 |
CSEngBT1 | 2016 – 2019 | 35 | |
CSEngBT3 | 1993 – 2019 | 35 | |
CSEngBT3-Bristol Channel | 1993 – 2000 | 35 | |
CSIreOT4 | 2003 – 2020 | 30 | |
CSNIrOT1 | 2008 – 2020 | 45 | |
CSNIrOT4 | 2009 – 2020 | 40 | |
CSScoOT1 | 1985 – 2020 | 35 | |
CSScoOT4 | 1995 – 2020 | 40 | |
Greater North Sea | GNSEngBT3 | 1990 – 2020 | 45 |
GNSFraOT4 | 1988 – 2020 | 50 | |
GNSGerBT3 | 1997– 2020 | 30 | |
GNSBelBT4 | 2004 – 2020 | 45 | |
GNSIntOT1 | 1983 – 2020 | 50 | |
GNSIntOT1-Channel | 2007 – 2020 | 50 | |
GNSIntOT3 | 1998 – 2020 | 50 | |
GNSNetBT3 | 1999 – 2020 | 45 | |
Wider Atlantic | WAScoOT3 | 1999 – 2020 | 35 |
WASpaOT3 | 2001 – 2020 | 40 | |
None | None | None | None |
1 Survey acronym convention: First 2 to 4 capitalised letters indicate the OSPAR Region (BBIC: Bay of Biscay and Iberian Coast; CS: Celtic Seas; GNS: Greater North Sea; WA – Wider Atlantic). Next capitalised and lowercase letters signify the country involved (Spa: Spain; Bel: Belgium, Por: Portugal; Fra: France; Eng: England; Ire: Republic of Ireland; Nir: Northern Ireland; Sco: Scotland; Ger: Germany; Int: International; Net: The Netherlands. International refers to the two international bottom trawl surveys carried out in the Greater North Sea under the International Council for the Exploration of the Sea (ICES). In the Bay of Biscay and Iberian Coast Region, Spanish surveys are further delimited by (n) for surveys operating in the northern Iberian Coast area and (s) for surveys operating in the southern Iberian Coast area. Next two capitalised letters indicate the type of survey (OT: otter trawl; BT: beam trawl). Final number indicates the season in which the survey is primarily undertaken (1: January to March; 3: July to September; 4: October to December).
2 This is a single survey that operates across both the Celtic Seas and the Bay of Biscay and Iberian Coast Regions, from the southern coast of the Republic of Ireland and down the western Atlantic coast of France. For indicator assessment purposes, this single survey was split into its two regional components.
Standard data collected on these surveys comprise numbers of each species of fish sampled in each trawl sample, measured to defined length categories (i.e., 1 cm below, so a fish with a recorded length of 14 cm would be between 14,00 cm and 14,99 cm in length). By dividing these species catch numbers-at-length by the area swept by the trawl on each sampling occasion, the catch data are converted to standardised estimates of fish density-at-length, by species, at each sampling location. Summing these trawl-sample species density-at-length estimates across all trawl samples collected within each sampling stratum per year (e.g., ICES statistical rectangles) and dividing by the number of trawl samples within each stratum per year, gives the average estimates of the density (of each species and length category) within each sampling stratum per year (i.e., by statistical rectangle in the North Sea or surveyed depth strata elsewhere, see CEMP). The sample stratum density estimates are then multiplied by the area of the stratum to give estimated Ns,lof fish per stratum. These abundances are converted to biomass data, Bs,l, by applying species weight-at-length relationships (of the form w = alb, where w is weight and a and bare species-specific parameters).
Summing these sample stratum biomass estimates across all sampling strata sampled in each year, provides estimates of the biomass of each species (s) and length category (l), in each year, across the whole area covered by the survey. The biomass in each length category is summed across species to give the estimates (Bl) that are used in the calculation of each survey LFI time series.
Deciding on the species to be included in the analysis is the first step in calculating each survey LFI time series. The FishBase website (www.fishbase.org) provided an ‘ecotype’ classification for all species encountered. The LFI has been designed as an indicator of size composition within demersal fish communities, so species assigned to the Pelagicand Bathypelagic ecotypes were automatically excluded, while species assigned to the Demersal and Bathydemersal ecotypes were automatically included. Species belonging to the Benthopelagic ecotype were generally included, but with the exceptions of Clupea harengus, Dysomma brivirostre, Hyperoplys immaculatus, Ammodytidae (family-level ID code), Salmo (genus-level ID code), Salmo salar and Sarpa salpa, which were all excluded on the basis that these species are relatively poorly sampled by the survey gear.
Various options to set the length threshold have been suggested: a cut-off to represent change in functional groups from piscivores to prey (Rochet et al., 2010) a signal to noise approach to identify the least noisy time series (Greenstreet et al., 2011). The latter approach was used by OSPAR IA2017 to identify length cut-offs (LT) to define ‘large fish’ for surveys in the Greater North Sea and Celtic Seas (IA2017). For surveys that were not previously assessed LT was set to whichever value led to 20% of the total surveyed biomass to fall within the numerator, the LT was then rounded down for consistency with the previous assessments. The full list applied is given in Table a.
Spatial Scope: Assessment Units
LFI time series was derived for each survey and grouped within Regions to determine an overall assessment outcome for each OSPAR Region.
Baselines and threshold values
The published study in the Greater North Sea (Greenstreet et al., 2011) established the early 1980s as the reference period for the LFI derived from the North Sea first quarter (Q1) international bottom trawl survey (GNSIntOT1). This period was selected by Greenstreet et al., (2011) on the basis that this was the last time that ICES advice for setting fish quotas was to maintain status quo; i.e., to carry on fishing at prevailing levels because stocks were not considered to be unduly depleted. Selection of this reference period led to the adoption of an LFI (with LT=40 cm) score of >0,3 as the threshold for the North Sea (Heslenfeld and Enserink, 2008). During OSPAR IA2017, the LT for this survey was raised to 50 cm. This survey is assessed here.
In a study of the Celtic Seas, Shephard et al., (2011) noted a period of relatively stable LFI (with LT=50 cm) values during the late 1980s, which included the six highest LFI values recorded. The stability of the LFI, combined with these high values, led Shephard et al., (2011) to adopt this period prior to 1990 as their reference period for the Celtic Seas. However, the survey these authors studied has been discontinued.
For the Iberian Coast, Modica et al., (2014) investigated the Spanish north coast survey (BBIC(n)SpaOT4) and suggested a baseline of 1989. However, this was prior to the onset of the survey so through extrapolation they suggested targets of 0,34 to 0,41 for the LFI (with LT=35 cm). This survey is assessed here but data were only available publicly from 2011.
Time Series Assessment
The long-term trend in each time series was modelled through the application of a LOESS smoother (i.e., locally weighted scatterplot smoothing) with a simple ‘fixed span’ of one decade. Absolute threshold values for the LFI time series analysed here have been published for GNSIntOT1 and following the approach outlined in IA2017, the average of values between 1983 to 1985 was also used to assess change in GNSIntOT1 and due to the strong correlation between GNSIntOT1 and GNSIntOT3 this threshold was rescaled through regression and applied to the more recent Q3 survey also. For all other surveys, a trends-based approach with statistical detection for shifts in stable periods only was adopted in common with the assessment of Size composition in fish communities (Typical Length). Previously, for surveys in the Celtic Seas Region a baseline was trialled (equal to three times the early 1990s average), but the shift detection approach (below) is considered superior.
Breakpoint analyses uses data to define stable underlying periods (see Probst and Stelzenmüller, 2015). The method makes it possible to say whether there is a significant change in the time series state over time, namely whether the recent period is not significantly different from the historically observed period. The method avoids the arbitrary choice of reference periods for assessment (i.e., how many years to use to calculate an average) which can lead to subjective assessments. The shorter the period chosen, the more likely it is that noise in the data or natural fluctuations in the system are being compared against each other. However, too long a period and it could be that actual changes in state are averaged out. The minimum detectable period is defined in this analysis as six years and is assumed to be appropriate to capture the response of the fish community as opposed to noise and short-term fluctuations. The analysis uses two statistical approaches: First applying the ‘supremum F test’ to establish whether a non-stationary time series or a constant period for the entire time series is more suitable. If the former, then breakpoint analysis is applied to find periods of at least six years’ duration.
Résultats
Mer du Nord
En mer du Nord, les GNSIntOT1 et GNSIntOT3 restent tous deux inférieurs à leurs valeurs seuils (0,165 et 0,170 respectivement) dérivées du LFI moyen de la période 1983-1985.
L’étude la plus ancienne, à savoir GNSIntOT1, montre une diminution à long terme depuis le début des années 1980, avec un changement significatif vers une période de faibles valeurs pendant les années 1990 (Figures 1 et 2). Cette diminution à long terme est antérieure au début de l'étude GNSIntOT3 et des études au chalut à perche : GNSBelBT3, GNSGerBT3 et GNSNetBT3.
Une récupération du niveau minimum est évidente dans le GNSIntOT1 à partir du début des années 2000, et dans les séries temporelles plus courtes dérivées du GNSIntOT3 et du GNSBelBT3. Tant le GNSIntOT1 que le GNSIntOT3 s'approchent de leur seuil d'évaluation (0,165 et 0,170 respectivement) en 2015 et 2016 respectivement. Cependant, des baisses continues sont évidentes pour GNSGerBT3 et GNSNetBT3. Le LOESS (locally weighted scatterplot smoothing) montre des baisses distinctes dans les deux derniers points de données pour GNSIntOT1, GNSIntOT3, GNSGerBT3 et GNSNetBT3, ce qui indique que la reprise s'est potentiellement inversée ces dernières années.
Dans la Manche orientale, les récupérations en cours sont évidentes dans deux études (GNSIntOT1_channel et GNSFraOT4), sans changement dans GNSEngBT3.
Mers celtiques
L'étude CSScoOT1 est la seule étude ayant une valeur d'évaluation, et elle reste inférieure à la valeur d'évaluation (0,508) dérivée du LFI moyen de la période 1985-1987.
Au nord de la Région, l’étude la plus ancienne, à savoir, CSScoOT1, montre une diminution à partir des années 1980, avec un changement significatif vers une période de faibles valeurs au cours des années 1990 (Figures 1 et 2), comme dans le cas de la mer du Nord. Cette diminution à long terme est également antérieure au début des études CSScoOT4 et CSIreOT4. Dans les trois études, des rétablissements continue sont évidents au cours des années 2000 et 2010 avec un changement significatif de l'état stable dans chacune d'elles (Figure 2). Une chute à court terme au cours des deux dernières années n'est observée que dans l'étude CSScoOT1.
Il n’existe pas de données d’études disponibles pour les années 1980 dans le sud de la région. Cependant, on observe une tendance générale à l'absence de changement jusqu'à ce que des augmentations commencent à se produire au cours des années 2010 (Figure 1). Un changement significatif vers un état plus élevé à long terme est évident dans la mer d'Irlande pour CSEngBT3 seulement (Figure 2).
Golfe de Gascogne et côte ibérique
Aucun changement à long terme n’a été observé (Figures 1 et 2)
Atlantique au large
Aucun changement à long terme n’a été observé (Figures 1 et 2).
Conclusion
Lorsque de longues séries temporelles sont disponibles (c'est-à-dire en mer du Nord et dans le nord des mers celtiques), un schéma commun de diminution du LFI entre les années 1980 et 2000 est cohérent entre les études. La tendance à la reconstitution, signalée en mer du Nord et dans le nord des mers celtiques dans l'évaluation intermédiaire de 2017, ne s'est pas poursuivie. Cependant, des preuves de la poursuite des reconstitutions dans la Manche orientale et le sud des mers celtiques demeurent.
Bien qu'il reste à voir si les déclins observés en mer du Nord et dans le nord des mers celtiques conduisent à de nouveaux états stables, les preuves suggèrent que des réductions de la pression de pêche sont nécessaires pour permettre un retour à une trajectoire de reconstitution.
Aucun changement à long terme n’a été observé dans le Golfe de Gascogne et la côte ibérique ou dans l’Atlantique au large.
Lacunes dans les connaissances
Les lacunes dans les connaissances portent sur : l’absence de données historiques (pour les mers autres que la mer du Nord et le Firth of Clyde) ou de modèles pertinents afin d’informer la détermination de la valeur d’évaluation du LFI ; les effets de la hausse de la température des mers sur les valeurs d’évaluation du LFI et sur le rythme de rétablissement de la répartition des tailles du poisson démersal; et une perception complète des rapports qui existent entre toutes les pressions anthropiques et leur impact sur l’ensemble de la communauté halieutique démersale, et pas seulement sur les stocks commerciaux.
Le développement futur de l’indicateur devrait envisager la possibilité d’utiliser les unités d’évaluation qui divisent les Régions OSPAR en zones plus petites, et l'inclusion de mesures de la pression de pêche.
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Contributeurs
Auteurs principaux : Chris Lynam and GerJan Piet.
Avec le soutien des groupes suivants : Intersessional Correspondence Group on the Coordination of Biodiversity Assessment and Monitoring (ICG-COBAM), OSPAR Biodiversity Committee (BDC)
Citation
Lynam. C.P. et Piet. G.J. 2023. Proportion de gros poisson (Indice de gros poisson). OSPAR, 2023: Bilan de santé. Commission OSPAR, Londres. Disponible via le lien suivant : https://oap.ospar.org/fr/evaluations-ospar/bilan-de-sante/2023/evaluations-des-indicateurs/proportion-de-gros-poisson/
Type d’évaluation | Évaluation d’Indicateur |
---|---|
Indicator Code | largefishindicatorqsr23-ospar |
Résumé des résultats | https://odims.ospar.org/en/submissions/ospar_lfi_msfd_2022_06_001/ |
Indicateur ODD | 14.2 D’ici à 2020, gérer et protéger durablement les écosystèmes marins et côtiers, notamment en renforçant leur résilience, afin d’éviter les graves conséquences de leur dégradation et prendre des mesures en faveur de leur restauration pour rétablir la santé la productivité des océans |
Activité thématique | Diversité biologique et écosystèmes |
Documentation pertinente d’OSPAR | OSPAR Agreement 2018-05 CEMP Guideline – FW3: |
Date de publication | 2023-06-30 |
Conditions d’accès et d’utilisation | https://oap.ospar.org/fr/politique-de-donnees/ |
Instantané de données | https://odims.ospar.org/en/submissions/ospar_lfi_snapshot_2022_06_001/ |
Résultats des données | https://odims.ospar.org/en/submissions/ospar_lfi_results_2022_06_001/ |