Introduction
Small and medium pelagic fish (SMPF) are important species for commercial fisheries worldwide and are key elements for the food security and for the functioning of marine ecosystems linking lower and upper trophic level species (Cury et al., Reference Cury, Bakun, Crawford, Jarre, Quiñones, Shannon and Verheye2000; FAO, 2020). Thus, variations in their populations can impact the dynamics of the whole ecosystem structure and promoting large ecological and socioeconomic consequences (Pita et al., Reference Pita, Silva, Prellezo, Andrés, Uriarte and Ganias2014). In addition, these species are known to be highly sensitive to the environmental conditions throughout their life history, with specific tolerance windows for temperature, salinity, oxygen and pH (among others), which define their bioclimatic envelope (Sekadende et al., Reference Sekadende, Scott, Anderson, Aswani, Francis, Jacobs, Jebri, Jiddawi, Kamukuru, Kelly, Kizenga, Kuguru, Kyewalyanga, Noyon, Nyandwi, Painter, Palmer, Raitsos, Roberts, Sailley, Samoilys, Sauer, Shayo, Shaghude, Taylor, Wihsgott and Popova2020). Therefore, due to their short generation times and tight coupling to lower trophic levels, populations of SMPF display large boom-and-bust dynamics that are closely linked to climate variability, promoting different responses by species and stocks (Peck et al., Reference Peck, Alheit, Bertrand, Catalán, Garrido, Moyano, Rykaczewski, Takasuka and van der Lingen2021; Ma et al., Reference Ma, Tian, Li, Ju, Sun, Ye, Liu and Watanabe2022). In this context, climate change and fishing are the two dominant processes by which humans affect marine life, which have not stopped increasing for last century (FAO, 2022; Mann, Reference Mann2024). In particular, the pelagic zone (i.e. the largest living space of the planet) holds half of the global primary production and sustains most of the animal biomass on Earth, including SMPF and, of course, their forage (Ariza et al., Reference Ariza, Lengaigne, Menkes, Lebourges-Dhaussy, Receveur, Gorgues, Habasque, Gutiérrez, Maury and Bertrand2022). Numerous researchers investigate the SMPF responses (which vary depending on species and areas) in a scenario where, although fisheries' catches are unlikely to increase much beyond current levels, the earth will warm, the oceans will acidify and hydrology will continue changing (Checkley et al., Reference Checkley, Alheit, Oozeki and Roy2009, Reference Checkley, Asch and Rykaczewski2017; Alheit et al., Reference Alheit, Lorenzo, Rykaczewski and Sundby2019; Albo-Puigserver et al., Reference Albo-Puigserver, Bueno-Pardo, Pinto, Monteiro, Ovelheiro, Teodósio and Leitão2022).
In the research of describing the influence of environmental conditions on the abundance and biomass variability in marine organisms, Sea Surface Temperature (SST and their anomalies) and primary production proxies (such as chlorophyll a concentration) are commonly the most used environmental variables. Probably because these data can be obtained indirectly from satellite images, and are freely available from several open libraries such as NASA-EarthData (https://www.earthdata.nasa.gov/) or IRI/LDEO Climate Data Library (https://iridl.ldeo.columbia.edu/). In particular, the relationship between SMPF and temperature has been a subject of extensive scientific research because it affects their growth, reproduction, distribution, and overall abundance. Regarding geographic distribution shifts, northward expansion of SMPF has been described for several thermophilic species in the northeast Atlantic Ocean (such as Scomber colias and Sardinella aurita), which are being monitored since beginning 2000 as study cases of the global warming effect on SMPF (Houssa et al., Reference Houssa, Kifani, Tojo, Lakhigue and Charouki2013; ICES, 2021; among others). Obviously, they alter their geographic distribution following the latitudinal change of sea temperature, occupying waters masses where they can develop their normal metabolic and biological cycles in accordance to their temperature tolerance limits (Schickele et al., Reference Schickele, Leroy, Beaugrand, Goberville, Hattab, Francour and Raybaud2020). Consequently, as waters warm, SMPF may migrate poleward, but also to deeper waters in search of suitable temperatures (Sekadende et al., Reference Sekadende, Scott, Anderson, Aswani, Francis, Jacobs, Jebri, Jiddawi, Kamukuru, Kelly, Kizenga, Kuguru, Kyewalyanga, Noyon, Nyandwi, Painter, Palmer, Raitsos, Roberts, Sailley, Samoilys, Sauer, Shayo, Shaghude, Taylor, Wihsgott and Popova2020). Moreover, during their life span and linked to breeding/feeding purposes, SMPF sometimes reach quite deep waters (Froese and Pauly, Reference Froese and Pauly2023), as has been observed for Trachurus picturatus and S. colias in the Azorean surroundings (Arkhipov et al., Reference Arkhipov, Kozlov, Shnar and Sirota2002).
The Canary Islands is an Atlantic archipelago composed by eight islands in NW African waters, located in the coastal transition zone of the Canary Current Eastern Boundary Upwelling System and, hence, influenced by the major Canary Current, the NW African upwelling and the eddies and currents among islands. The Canary Islands are characterized by a narrow oceanic shelf, with great depth among islands surrounded by oligotrophic waters, leading to a general low productive marine system (Figure 1) (Barton et al., Reference Barton, Arístegui, Tett, Cantón, García-Braun, Hernández-León, Nykjaer, Almeida, Almunia, Ballesteros, Basterretxea, Escánez, García-Weill, Hernández-Guerra, López-Laatzen, Molina, Montero, Navarro-Pérez, Rodríguez, van Lenning, Vélez and Wild1998; Brito et al., Reference Brito, Pascual, Falcón, Sancho and González2002). Increasing trends in calibrated SST have been registered in the north of the Canary Islands since the 1980’ (Vélez-Belchí et al., Reference Vélez-Belchí, González-Carballo, Pérez-Hernández, Hernández-Guerra, Valdés and Déniz-Gonzaléz2015). Regarding fisheries in the Canary Islands, after tuna fish, SMPF are the second group in importance on landings. They are mainly caught by the artisanal purse-seine fleet, which generally perform daily fishing trips in close waters to landing ports. Based on the official sale notes, most of the activity is concentrated around the main islands, i.e. Tenerife and Gran Canaria. Much effort has been paid to the characterization of this fishery in the archipelago, but only some works have analysed the influence of environmental variables on the biomass and life history traits of the SMPF inhabiting Canary waters (Brochier et al., Reference Brochier, Ramzi, Lett, Machu, Berraho, Fréon and Hernández-León2008, Reference Brochier, Colas, Lett, Echevin, Cubillos, Tam, Chlaida, Mullon and Fréon2009, Reference Brochier, Auger, Pecquerie, Machu, Capet, Thiaw, Cheikh Mbaye, Braham, Ettahiri, Charouki, ene NdawO, Werner and Brehmer2018; Jurado-Ruzafa et al., Reference Jurado-Ruzafa, González-Lorenzo, Jiménez, Sotillo, Acosta and Santamaría2019, Reference Jurado-Ruzafa, Canal, Quinzán, Sotillo, Santana-Arocha, Estil⋅las, Mañé, González-Lorenzo and Perales-Raya2022).
Figure 1. Map showing the Canary Islands allocation. Blue points represent the RAPROCAN stations for the acquisition of oceanographic data used in the present study.
The link between changes on the abundance, distribution and biological traits of SMPF and environmental and climatic conditions is a crucial topic to foresee variations which could strongly impact the marine ecosystems functioning as well as food security worldwide. However, although several monitoring programmes exist the Canary Islands, few interdisciplinary studies have been performed in the study area so far. In the present study we aim to investigate the potential relationship between the annual landings of SMPF in the Canary Islands with the SST, chlorophyll a concentration in the sea surface and, for the first time, with variables in deep waters.
Materials and methods
Fishery and environmental data
The most common SMPF species caught in the Canary Islands are (in order of importance in landings): S. colias, Trachurus spp, Sardinella spp and Sardina pilchardus. In the present work, we used the total landings of SMPF using the official sale notes from 2007 (when the official reporting system was implemented) to 2021. Effort data have not been considered, due to many shortfalls having been described for this fishery, and subsequent indices (such as landings per unit of effort, LPUE) should not be taken as reliable (Quinzán and Jurado-Ruzafa, Reference Quinzán and Jurado-Ruzafa2021).
Annual mean values of SST and concentration of chlorophyll a (Chla) were obtained for the study area (between 27–29.5°N and 13–18.5°W) from the NASA database GIOVANNI (Acker and Leptoukh, Reference Acker and Leptoukh2007). Sea temperature and salinity in the 200–800 m depth water layer (ST_200–800 and Salinity_200–800) were taken in the framework of the RAPROCAN Program, which include a ‘Deep hydrographic section around the Canary Islands’ and whose aim is to establish the decadal and/or subdecadal variability in the eastern margin of the subtropical gyre. When possible, two hydrographic cruises per year (spring and fall), including a deep hydrographic section along the North of the archipelago (http://www.oceanografia.es/pedro/research_IROC2018_Canary.html) (Figure 1). Later, data is processed with the software SBE Data Processing from Sea-Bird Scientific following the recommendation given in Duarte et al. (Reference Duarte, Vélez, Fraile-Nuez, Álvarez, Dachs, Navarro, Blanco, Arrieta, Gasol and González-Gordillo2012), and MATLAB is used for the data analysis. For the present study, the data used from the RAPROCAN Program (time period: 2007–2021) was averaged for the selected depth layer, selected to avoid the influence of the seasonal thermocline, which spreads out to a depth of 170 to 200 metres (Villanueva and Ruiz, Reference Villanueva and Ruíz1994).
Statistical analyses
Linear correlations between the environmental variables and the SMPF landings in the Canary Islands (for the total and by species) were tested using the ρ-Pearson correlation coefficient. Likewise, correlation between the environmental variables was tested. For these statistical analyses and plots representations, IBM® SPSS® Statistics v. 25 and Microsoft Excel 2019 were used.
Analyses were also performed considering one-year lag to match SMPF landings with the environmental variables occurring the previous year (SMPF_landings−1). This additional analysis is based on the growth patterns of the species analysed, since catchable sizes are attained approximately one year later from the fish birth (Santamaría, Reference Santamaría1993; Lorenzo and Pajuelo, Reference Lorenzo and Pajuelo1996; Jurado-Ruzafa and Santamaría, Reference Jurado-Ruzafa and Santamaría2018; Jurado-Ruzafa et al., Reference Jurado-Ruzafa, Hernández, Duque-Nogal, Pascual-Alayón, Carrasco, Sancho and Santamaría2020, Reference Jurado-Ruzafa, Sotillo, Santana-Arocha, Mañé, Estil⋅las, González-Lorenzo and Perales-Raya2021).
Once correlated variables with the SMPF_landings−1 were identified (based on ρ-Pearson correlations), the significance of these relationships was investigated for the whole time series using a Generalized Linear Model (GLM) using the R-package glm2 (Marschner, Reference Marschner2011; R Core Team, 2023).
Results
The environmental data collated as well as the SMPF landings reported in the Canary Islands from 2007 to 2021 are represented in Figure 2. Regarding the ρ-Pearson correlation coefficients obtained (Table 1), significant correlations were only found when one-year time lag was considered between SMPF landings and the environmental variables, with the exception of SST, which was not correlated with landings in any case.
Figure 2. Annual mean values of chlorophyll a concentration (Chla), Sea Surface Temperature (SST), Sea Temperature and Salinity in the water layer between 200 and 800 m depth (ST_200–800 and Salinity_ 200–800, respectively) and landings of small pelagic fish in the Canary Islands. Time period: 2007–2021.
Table 1. Results of the ρ-Pearson correlation coefficient between the annual mean values of the environmental variables (SST, Sea Surface Temperature; ST_200–800, averaged sea temperature at 200–800 m depth; Salinity_200–800, averaged salinity at 200–800 m depth; Chla, chlorophyll a concentration) and the SMPF total landings, both for the corresponding year and assuming a 1-year time lag (SMPF_landings−1)
***bilateral significance P-value < 0.01; *bilateral significance P-value < 0.05
On the one hand, ρ-Pearson correlation coefficient between ST_200–800 and Salinity_200–800 was 0.806, with a P-value < 0.0001, confirming the expected strongly correlation between salinity and temperature (Stewart, Reference Stewart2008). For this reason, Salinity_200–800 was excluded from subsequent analyses. On the other hand, no significant correlation exist between ST_ 200–800 and Chla (t = 1.049, P-value = 0.3149).
Finally, regarding the GLM results (Table 2 and Figure 3), significant correlation was found only between SMPF_landings−1 and the concentration of Chla. The missing significant correlation with ST_200–800 may be explained because the shortness of the time series, or for the great contribution of the Chla to explain SMPF landings. Anyway, although the contribution to the model is not significant when Chla is considered, ST_200–800 is significantly correlated with the SMPF landings performed during the next year.
Table 2. Results of the Generalized Linear Model (GLM) between the annual mean values of the selected environmental variables (ST_200–800, sea temperature at 200–800 m depth; Chla, chlorophyll a concentration) and the SMPF the total landings assuming a 1-year time lag (SMPF_landings-1)
*P-value < 0.01.
Figure 3. Plotted results of the Generalized Linear Model (GLM) between the annual mean values of the selected environmental variables (ST_200–800: sea temperature at 200–800 m depth; Chla: chlorophyll a concentration) and the SMPF the total landings assuming a 1-year time lag (SMPF_landings-1).
Discussion
Understanding the relationship between water temperatures (in the surface, but also in deep layers) and SMPF abundance is crucial for predicting how these fish populations might respond to climate change. It involves complex interactions between oceanographic processes, food web dynamics, and the behavioural patterns of these species, making it a subject of extensive scientific research and monitoring.
In the Canary Islands, the available data about biomass and/or abundance of small SMPF estimated from fishery-independent information correspond to outdated studies which, in addition, did not covered the whole archipelago (González, Reference González2008). In the present study, fishery dependent data (derived from official SMPF landings) was used to assess the potential influence of several environmental variables in the SMPF biomass. In this sense, numerous authors (Grbec et al., Reference Grbec, Dulcic and Morovic2002; Ormaza-González et al., Reference Ormaza-González, Mora-Cervetto, Bermúdez-Martínez, Hurtado-Domínguez, Peralta-Bravo and Jurado-Maldonado2016; Teixeira et al., Reference Teixeira, Gamito, Leitão, Murta, Cabral, Erzini and Costa2016; Olmos et al., Reference Olmos, Ianelli, Ciannelli, Spies, McGilliard and Thorson2023; among others) have proven that although climate-dependence analyses of a fish population should be derived from biomass data, in its absence, landing data are useful as a first approximation. Indeed, catch statistics are recognized to be linked to fishing and environmental pressures (Borges et al., Reference Borges, Santos, Crato, Mendes and Mota2003; Gamito et al., Reference Gamito, Teixeira, Costa and Cabral2015; Fortibuoni et al., Reference Fortibuoni, Giovanardi, Pranovi, Raicevich, Solidoro and Libralato2017; Olmos et al., Reference Olmos, Ianelli, Ciannelli, Spies, McGilliard and Thorson2023) and Pilling et al. (Reference Pilling, Apostolaki, Failler, Floros, Large, Morales-Nin, Reglero, Stergiou, Tsikliras, Payne, Cotter and Potter2009) demonstrated the usefulness of using data derived from official sale notes to describe and analyse patterns in fish populations. Indeed, in a previous works in the region (Jurado-Ruzafa et al., Reference Jurado-Ruzafa, González-Lorenzo, Jiménez, Sotillo, Acosta and Santamaría2019, Reference Jurado-Ruzafa, Canal, Quinzán, Sotillo, Santana-Arocha, Estil⋅las, Mañé, González-Lorenzo and Perales-Raya2022), this data source has served to find out seasonal patterns in small pelagic landings. Even when the shortness of the time series and the biomass proxy used (subject to several shortfalls related to the official data collection system [González, Reference González2008; Quinzán and Jurado-Ruzafa, Reference Quinzán and Jurado-Ruzafa2021]) made the possibility of finding any correlation with environmental variables improbable, Chla has resulted a good indicator of the SMPF landings produced the following year in the Canary Islands. In addition, this one-year time lag correlation has been observed for the ST_200–800 and the Salinity_200–800, supporting the necessity of keeping the monitoring system. As commented in the ‘Introduction’ section, much of the SMPF species reach greater depths in different ontogeny stages and related to feeding/reproduction and, hence, the conditions from 200 to 800 m could influence the recruitment success of these species. Usually, relationship between marine pelagic species and environmental variables are performed using the conditions in the outermost water layer, which can be freely and easily obtained from open databases. Nevertheless, while in the present analysis in the Canary Archipelago no correlations between annual landings and SST were found in any case, statistically significant and positive correlation between the SMPF landings and the sea temperature in the 200–800 m layer one-year time-lag. Therefore, conditions in the water layer 200–800 m depth seem to influence SMPF landings' trends in the Canary Islands. This layer is less affected by atmosphere variations and probably influences on success of the SMPF spawning, the eggs and larvae survival and recruitment processes. In fact, legal catchable sizes are approximately attained by one-year-old individuals, explaining the one-year time-lag. Since most of the studies investigating this kind of relationships find significant influence of the environmental conditions in surface waters (Fernandes et al., Reference Fernandes, Frölicher, Rutterford, Erauskin-Extramiana and Cheung2020; Pennino et al., Reference Pennino, Coll, Albo-Puigserver, Fernández-Corredor, Steenbeek, Giráldez, González, Esteban and Bellido2020; Ramírez et al., Reference Ramírez, Pennino, Albo-Puigserver, Steenbeek, Bellido and Coll2021; Reference Ramírez, Shannon, van der Lingen, Julià, Steenbeek and Coll2022; Selvaraj et al., Reference Selvaraj, Rosero-Henao and Cifuentes-Ossa2022, among others), this is a highlightable finding. However, as commented, the availability of data routinely got for specific areas, and not derived from satellite images, is unusual and expensive information to obtain. There exist initiatives such as the ARGO Programme (https://www.aoml.noaa.gov/proj/argo/), but the drifting profiling floats position (and, hence, the data available) is dependent on the ocean currents drifting the buoys.
In the current climate change scenario, in which water warming in the Canary area has been proven (Vélez-Belchí et al., Reference Vélez-Belchí, González-Carballo, Pérez-Hernández, Hernández-Guerra, Valdés and Déniz-Gonzaléz2015), the possibility of SMPF-schools migration following cooler waters to northern latitudes (Walther et al., Reference Walther, Post, Convey, Menzel, Parmesan, Beebee, Fromentin, Hoegh-Guldberg and Bairlein2002) or to deeper waters (Sekadende et al., Reference Sekadende, Scott, Anderson, Aswani, Francis, Jacobs, Jebri, Jiddawi, Kamukuru, Kelly, Kizenga, Kuguru, Kyewalyanga, Noyon, Nyandwi, Painter, Palmer, Raitsos, Roberts, Sailley, Samoilys, Sauer, Shayo, Shaghude, Taylor, Wihsgott and Popova2020) should be monitored. On the one hand, latitudinal expansion of S. colias and S. aurita (Zardoya et al., Reference Zardoya, Castilho, Grande, Favre-Krey, Caetano, Marcato, Krey and Patarnello2004; Sabatés et al., Reference Sabatés, Martín, Lloret and Raya2006; Zeeberg et al., Reference Zeeberg, Corten, Tjoe-Awie, Coca and Hamady2008; Blanchet et al., Reference Blanchet, Primicerio, Smalås, Arias-Hansen and Aschan2019; ICES, 2021; among others). On the other hand, the presence of bigger individuals of S. colias and T. picturatus has been observed in deep waters around seamounts surrounding other Atlantic archipelagos (Jesus, Reference Jesus1992; Arkhipov et al., Reference Arkhipov, Sirota, Kozlov and Shnar2004; Menezes et al., Reference Menezes, Sigler, Silva and Pinho2006). So much so that there are longline fisheries specialized in capturing this fraction of the populations (Jesus, Reference Jesus1992; Garcia et al., Reference Garcia, Pereira, Canha, Reis and Diogo2015). However, this point has not been verified in the Canary Islands so far. These kinds of behaviour changes may substantially reduce the catchability of these fish by the artisanal fishers with simple gear and boats (Sekadende et al., Reference Sekadende, Scott, Anderson, Aswani, Francis, Jacobs, Jebri, Jiddawi, Kamukuru, Kelly, Kizenga, Kuguru, Kyewalyanga, Noyon, Nyandwi, Painter, Palmer, Raitsos, Roberts, Sailley, Samoilys, Sauer, Shayo, Shaghude, Taylor, Wihsgott and Popova2020). Since this movement can affect local fisheries and disrupt established ecosystems, understanding the relationship between global warming and small pelagic fish is crucial not only for the conservation of these species but also for the communities and industries that depend on them.
Ecosystem and population models have found that temperature and primary production (here represented by Chla) are often the main drivers of change in SMPF distribution and abundance at global and regional scales, being precise and realistic to inform long-term fisheries management (Fernandes et al., Reference Fernandes, Frölicher, Rutterford, Erauskin-Extramiana and Cheung2020). In this sense, much effort must be done to truly understand the intricate processes driving the primary production in Canary waters and the linkages with SMPF distribution and abundance. In general, it is assumed that a certain water warming should promote the primary production in marine waters (Liu et al., Reference Liu, Chen, Smith, Yuan, Chen, Zhou, Alam, Lin, Zhao, Zhou, Chu, Ma and Liu2019), but in the oligotrophic waters surrounding the archipelago, other factors should be analysed to understand the Chla decreasing trend recorded during the last decade. For example, in the Mediterranean Sea, important effects on future trends of anchovy and sardine have been related to other factors such as river discharge or climate-driven changes in water currents (advection/retention dynamics) which impact on survival of the pre-recruitment stages (Lloret et al., Reference Lloret, Palomera, Salat and Sole2004). Based on an extensive review by Peck et al. (Reference Peck, Reglero, Takahashi and Catalán2013), few studies have examined the direct effects of salinity, temperature and/or light on growth, feeding and survival in juveniles' stages of SMPF; however, the results obtained in the present analysis support the fact that, mainly primary production, but also temperature in deep waters seem to play a pivotal role in the juveniles' survival of the SMPF in the archipelago.
Scientific community is conscious that, although more information is needed to make reliable predictions regarding the future state of marine ecosystems, there exist evidences about sensitivity and vulnerability of pelagic species and ecosystems to climate change (Checkley et al., Reference Checkley, Alheit, Oozeki and Roy2009). It is worth to note that the Canary Islands are under the influence of one of the major Eastern Boundary Upwelling Systems in the world, which seem to make the region a ‘thermal refugia’ from global warming for the marine organisms inhabiting these waters (García-Reyes et al., Reference García-Reyes, Koval, Sydeman, Palacios, Bedriñana-Romano, DeForest, Montenegro Silva, Sepúlveda and Hines2023). However, climate change challenges fisheries management and requires adaptive strategies able to incorporate changes in the distribution and abundance of these species. At present, the stock status of the SMPF in the Canary Islands remains not assessable using the available mathematical models (Quinzán and Jurado-Ruzafa, Reference Quinzán and Jurado-Ruzafa2021). To achieve reliable scientific advice, improvement on data consistency is needed. But studies to understand the population structure of the SMPF in the Central and Northeast Atlantic (including the Macaronesian archipelagos) and their potential changes are also necessary, as well as to investigate spatial migration processes and monitor distribution patterns shifts. Since sustainable fishing practices must ensure human wellbeing by safeguarding the integrity of marine life-supporting systems, a significant challenge to fisheries management is that sustainable fishing levels can decline, often synergistically, by co-occurring with climate-driven environmental stressors (Ramírez et al., Reference Ramírez, Pennino, Albo-Puigserver, Steenbeek, Bellido and Coll2021). Due to disentangling climatic and fishing (human)-induced impacts on marine populations is probably impossible, making interdisciplinary studies becomes crucial.
To conclude, keeping the monitoring programmes both on the ecosystem communities and the environmental conditions is critical to understand, foresee and anticipate potential variations in the fishery resources and to aim the sustainable exploitation of the SMPF populations, especially to face the climate change challenges.
Acknowledgements
Authors wanted to thank the research vessels' crews involved in the RAPROCAN surveys and to José Manuel González Irusta for the useful advice in the statistical analysis. Likewise, sincere thanks to the anonymous reviewers for their insightful comments, enriching the analyses and the text.
Authors’ contributions
Conceptualization: Alba Jurado-Ruzafa and Pedro Vélez-Belchí; methodology: Alba Jurado-Ruzafa; investigation: Alba Jurado-Ruzafa, Pedro Vélez-Belchí, Sebastián Jiménez-Navarro, Begoña Sotillo, Carmen Presas-Navarro and Ángela Mosquera-Giménez; resources: Pedro Vélez-Belchí and Sebastián Jiménez-Navarro; data curation: Alba Jurado-Ruzafa, Sebastián Jiménez-Navarro, Begoña Sotillo, Carmen Presas-Navarro and Ángela Mosquera-Giménez; writing – original draft preparation: Alba Jurado-Ruzafa; writing – review and editing: all authors; funding acquisition: Pedro Vélez-Belchí, Sebastián Jiménez-Navarro and Pablo Martín-Sosa. All authors have read and agreed to the published version of the manuscript.
Financial support
Part of this study has been partially funded by the EU through the European Maritime and Fisheries Fund (EMFF) within the National Program of collection, management and use of data in the fisheries sector and support for scientific advice regarding the Common Fisheries Policy. In addition, it has been carried out as part of the RAPROCAN Project, the Canary Islands component of the core observational program of the Instituto Español de Oceanografía (IEO, CSIC). Finally, part of the study has been performed in the framework of the LIFE IP INTEMARES project, coordinated by the Biodiversity Foundation of the Ministry for the Ecological Transition and the Demographic Challenge. It receives financial support from the European Union's LIFE program (LIFE15 IPE ES 012).
Competing interest
None.
Ethical standards
This research was not covered by any regulation and formal ethical approval was not required.
Data availability
Data availability on request from the authors.
Open access
