Micronekton diel vertical migration and active flux in the subtropical Northeast Atlantic

This thesis is about diel vertical migration, the most important synchronized animal movement in the ocean. The study focuses on migratory micronekton of the Canary Islands, a community that is mainly composed of small fish, shrimp and squid, which feed in shallow waters during the night and remain deep during the day. Through this process, the atmospheric carbon incorporated into shallow-living organisms is exported to deeper waters and thus affects the global carbon cycle. Here,Here, the author deals with the extent and magnitude of migrations, their role in carbon sequestration, and their variability accross diverse oceanographic features. The results show both the importance and sensitivity of vertical migratory micronekton in a changing ocean, highlighting the need to incorporate this community into future ecosystem models. Micronekton diel vertical migration and active flux in the subtropical Northeast Atlantic D. Jos´e Manuel Vergara Mart´ın, Secretario del Departamento de Biolog´ıa de la Universidad de Las Palmas de Gran Canaria, Certifica, Que el Consejo de Doctores del Departamento en sesi´on permanente tom´o el acuerdo de dar el consentimiento para su tramitaci´on, a la tesis doctoral titulada ”Micronekton diel vertical migration and active flux in the subtropical Northeast Atlantic” presentada por el doctorando D. Alejandro Vicente Ariza y dirigida por el Doctor Santiago Hern´andez Le´on. Y para que as´ı conste, y a efectos de lo previsto en el Art◦6 del Reglamento para la elaboraci´on, defensa, tribunal y evaluaci´on de tesis doctorales de la Universidad de Las Palmas de Gran Canaria, firmo la presente en Las Palmas de Gran Canaria, a 19 de Noviembre de 2015. i Universidad de Las Palmas de Gran Canaria Doctoral Thesis Micronekton diel vertical migration and active flux in the subtropical Northeast Atlantic Author: Alejandro Vicente Ariza Supervisor: Dr. Santiago Hern´ andez Le´ on A thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy Programa de Doctorado en Oceanograf´ıa Instituto de Oceanograf´ıa y Cambio Global November 16, 2015 Declaration of Authorship I, Alejandro Vicente Ariza, declare that this thesis titled, ’Micronekton diel vertical migration and active flux in the subtropical Northeast Atlantic’ and the work presented in it are my own. I confirm that: This work was done wholly or mainly while in candidature for a research degree at this University. Where any part of this thesis has previously been submitted for a degree or any other qualification at other institution, or for publication in a scientific journal, this has been clearly stated. Where I have consulted the published work of others, this is always clearly attributed. Where I have quoted from the work of others, the source is always given. With the exception of such quotations, this thesis is entirely my own work. I have acknowledged all main sources of help. Where the thesis is based on work done by myself jointly with others, this has been clearly indicated. Signed: Date: v ”The tow-net experiments carried out on board the Challenger during several years in all parts of the world led me to the conviction that these intermediate regions were inhabited” John Murray (1895) vii Contents Declaration of Authorship v Abstract ix Acknowledgements (Agradecimientos) xi Contents xv List of Figures xix List of Tables xxiii Abbreviations xxv Symbols xxvii I Introduction 1 Background 3 Diel vertical migration: History and the protagonists . . . . . . . . . . . . . . . 3 Factors governing diel vertical migration . . . . . . . . . . . . . . . . . . . . . . 4 Importance of diel vertical migration for marine foodwebs . . . . . . . . . . . . 7 Relation to the ocean carbon cycle and climate change . . . . . . . . . . . . . . 8 Thesis objectives and outline 12 xv Contents II Results 15 1 Vertical distribution, composition and migratory patterns of acoustic scattering layers in the Canary Islands. 17 2 Migrant biomass and respiratory carbon flux by zooplankton and micronekton in the subtropical northeast Atlantic Ocean (Canary Islands). 37 3 The submarine volcano eruption off El Hierro Island: Effects on the scattering migrant biota and the evolution of the pelagic communities. 61 4 Eddy-induced variability of the deep mesopelagic biota. 81 III Synthesis and further research 93 Overall discussion 95 Stratified vertical migration, stratified active flux . . . . . . . . . . . . . . . . . 95 Active flux beyond 1000 m depth . . . . . . . . . . . . . . . . . . . . . . . . . . 96 Sinking POC, zooplankton and micronekton: Towards an holistic approach . . 99 Environmental factors affecting micronekton . . . . . . . . . . . . . . . . . . . . 100 Conclusions 102 Future lines of research 104 IV Resumen en espa˜nol (Spanish summary) 109 Introducci´on 109 Migraci´on Vertical Diaria: Historia y protagonistas . . . . . . . . . . . . . . . . 109 Factores que gobiernan el proceso de migraci´on vertical . . . . . . . . . . . . . 110 Importancia de la migraci´on vertical en las redes tr´oficas marinas . . . . . . . . 113 Relaci´on con el ciclo del carbono en el oc´eano y con el cambio clim´atico . . . . 115 Objetivos y planteamiento de la investigaci´on 119 Metodolog´ıa 121 Muestreoac´ustico ..................................121 Muestreobiol´ogico ..................................122 Actividad del sistema de transporte de electrones . . . . . . . . . . . . . . . . . 123 Determinaci´on del flujo activo de carbono . . . . . . . . . . . . . . . . . . . . . 124 xvi Contenidos Resultados 125 1 Distribuci´on vertical, composici´on y patrones migratorios de las capas de reflexi´on ac´ustica en las Islas Canarias. . . . . . . . . . . . . . . . . . . . . 125 2 Biomasa migrante y flujo respiratorio de carbono del zooplancton y el micronecton en el Atl´antico nordeste subtropical (Islas Canarias). . . . . . . 132 3 El volc´an submarino de la isla de El Hierro, efectos sobre la biota migrante y evoluci´on de las comunidades pel´agicas. . . . . . . . . . . . . . . . . . . 137 4 Variabilidad de la fauna mesopel´agica profunda inducida por remolinos. . . . 143 S´ıntesis y discusi´on 149 Migraci´on vertical estratificada, flujo activo estratificado . . . . . . . . . . . . . 149 Flujo activo m´as all´a de los 1000 m de profundidad . . . . . . . . . . . . . . . . 150 Flujo pasivo, zooplancton y micronecton: hacia un enfoque hol´ıstico . . . . . . 154 Factores ambientales que afectan al micronecton . . . . . . . . . . . . . . . . . 155 Conclusiones 156 Futuras l´ıneas de investigaci´on 158 V Appendices 161 A: Species abundance raw data from Chapter 1 . . . . . . . . . . . . . . . . . . 163 Bibliography 167 xvii List of Figures I Introduction I1 First documented echogram and modern echogram. . . . . . . . . . . . . . 4 I2 The main fishes, decapods and cephalopods that undertake DVM in the subtropical northeast Atlantic . . . . . . . . . . . . . . . . . . . . . . . . . 5 I3 Daytime migration depth at global scale . . . . . . . . . . . . . . . . . . . 6 I4 Mesopelagic fish biomass as a function of primary production . . . . . . . 8 I5 Schematic of the biological carbon pump . . . . . . . . . . . . . . . . . . . 10 II Results 1.1 Situation of the Canary Islands, and study areas southwest off La Palma andTenerife................................... 21 1.2 Averaged profiles of temperature, dissolved oxygen and chlorophyll anear La Palma and Tenerife Islands . . . . . . . . . . . . . . . . . . . . . . . . 24 1.3 Echograms and hauls in waters nearby La Palma and Tenerife . . . . . . . 25 1.4 Echograms showing migratory pathways . . . . . . . . . . . . . . . . . . . 26 1.5 Classification of fishing hauls according to Bray-Curtis dissimilarity distances, and CPUEs of dominant species . . . . . . . . . . . . . . . . . . . 29 1.6 Modeled swimbladder resonance at 18 and 38 kHz . . . . . . . . . . . . . 31 1.7 Schematic of acoustic scattering layers in the Canary Islands . . . . . . . 34 2.1 Map showing the location of the Canary Islands west off Africa and Gran CanariaIsland.................................. 41 2.2 Temperature, chlorophyll a, and mean volume backscattering strength at 120kHz...................................... 43 2.3 Daily gravitational flux measured at 150 m depth . . . . . . . . . . . . . . 46 2.4 Abundance, biomass and electron transfer system activity of different zooplankton size fractions . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 2.5 Abundance, biomass and electron transfer system activity of three dominant taxa of migrant micronekton . . . . . . . . . . . . . . . . . . . . . . 50 2.6 Length distribution of dominant taxa collected with the WP-2 (zooplankton) and MOHT (micronekton) nets. . . . . . . . . . . . . . . . . . . . . . 51 xix List of Figures 2.7 Mass-specific respiration of micronekton. . . . . . . . . . . . . . . . . . . . 54 2.8 Migrant biomass and respiratory flux of zooplankton and micronekton. . . 59 3.1 Position of El Hierro Island and sampling points. . . . . . . . . . . . . . . 65 3.2 Sea Surface Reflectance from satellite imagery and acoustic transects performed throughout the volcanic plume. . . . . . . . . . . . . . . . . . . . . 67 3.3 38 kHz echogram and Sea Surface Reflectance on 7 November 2011 . . . . 70 3.4 38 kHz echogram and Sea Surface Reflectance on 18 November 2011 . . . 71 3.5 DSL depth throughout the volcanic plume. . . . . . . . . . . . . . . . . . 76 3.6 Temperature and dissolved oxygen profiles during the sampling period. . . 77 3.7 Time series with averaged parameters collected within the volcano-affected andnon-affectedarea. ............................. 78 4.1 Schematic of the Canary Eddy Corridor, Sea Level Anomaly, and first echogram sectioning the anticyclonic eddy . . . . . . . . . . . . . . . . . . 87 4.2 Echograms showing systematic acoustic sections across the eddy structure 90 4.3 Acoustic profiles on each eddy region . . . . . . . . . . . . . . . . . . . . . 92 III Synthesis and further research S1 Biota backscattering signal for a dawn descent at 18 kHz and daytime vertical distribution of fish. . . . . . . . . . . . . . . . . . . . . . . . . . . 96 S2 Vertical velocities and echo anomalies in bathypelagic waters of the CanaryBasin.................................... 98 S3 New schematic of the ocean carbon pump . . . . . . . . . . . . . . . . . . 99 IV Resumen en espa˜nol (Spanish summary) Introducci´on I1 Primer ecograma publicado y ecograma actual . . . . . . . . . . . . . . . 110 I2 Peces, dec´apodos y cefal´opodos dominantes que realizan migraciones verticales en el Atl´antico nordeste subtropical . . . . . . . . . . . . . . . . . . 111 I3 Profundidad de migraci´on a escala global . . . . . . . . . . . . . . . . . . 112 I4 Biomasa de peces mesopel´agicos en funci´on de la producci´on primaria . . 114 I5 Esquema de la bomba biol´ogica de carbono . . . . . . . . . . . . . . . . . 117 Resultados 1.1 Islas Canarias y ´area de estudio al suroeste de La Palma . . . . . . . . . . 126 1.3 Ecogramas a 18 y 38 kHz en aguas cercanas a La Palma y Tenerife . . . . 127 1.4 Ecogramas mostrando v´ıas de migraci´on vertical . . . . . . . . . . . . . . 128 xx Lista de Figuras 1.5 Clasificaci´on de los lances de pesca y CPUEs . . . . . . . . . . . . . . . . 129 1.7 Esquema de las capas de reflexi´on ac´ustica en las Islas Canarias . . . . . . 130 2.1 Situaci´on de las Islas Canarias, se˜nalando la isla de Gran Canaria . . . . . 133 2.4 Abundancia, biomasa y actividad del sistema de transporte de electrones en diferentes fracciones de tallas de zooplancton . . . . . . . . . . . . . . . 134 2.5 Abundancia, biomasa y actividad del sistema de transporte de electrones en tres especies dominantes de migradores verticales del micronecton . . . 136 2.8 Biomasa migrante y flujo respiratorio de zooplancton y micronecton . . . 137 3.2 Reflectancia de la superficie oce´anica seg´un datos de sat´elite y transectos ac´usticos realizados en torno a la pluma volc´anica . . . . . . . . . . . . . . 138 3.3 Ecograma a 38 kHz y reflectancia de la superficie oce´anica el 7 de noviembrede2011 ...................................139 3.4 Ecograma a 38 kHz y reflectancia de la superficie oce´anica el 18 de noviembrede2011 ...................................140 3.5 Profundidad de la capa de reflexi´on profunda en las inmediaciones de la erupci´onvolc´anica ...............................141 3.7 Serie temporal con par´ametros promediados dentro y fuera de la zona de afecci´onvolc´anica................................142 4.1 Esquema del corredor de remolinos de Canarias, anomal´ıa del nivel del mar y primer ecograma cortando el remolino anticicl´onico . . . . . . . . . 144 4.2 Ecogramas mostrando secciones sistem´aticas a lo largo de la estructura delremolino...................................146 4.3 Perfiles ac´usticos para cada regi´on del remolino . . . . . . . . . . . . . . . 147 S´ıntesis y discusi´on S1 Descenso al amanecer de capa ac´ustica a 18 kHz y distribuci´on vertical de peces durante el d´ıa. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150 S2 Velocidades verticales y anomal´ıas de eco en aguas batipel´agicas de la CuencadeCanarias ..............................152 S3 Nuevo esquema de la bomba oce´anica de carbono . . . . . . . . . . . . . . 153 xxi List of Tables II Results 1.1 Relative CPUE (%) and biomass (%) of species captured in the nocturnal shallow scattering layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 1.2 Dominant species forming each scattering layer, indicating relative abundances, modal lengths, and if present, the swimbladder condition . . . . . 28 2.1 Zooplankton abundance, biomass and electron transfer system activities. . 47 2.2 Percentages of abundance and biomass of micronekton species . . . . . . . 48 2.3 Comparison of migrant biomass, migratory and gravitational fluxes from theliterature .................................. 56 3.1 Averaged mesozooplankton abundance along the sampling period. . . . . 73 3.2 Averaged micronekton abundance within the MSL after the eruption . . . 73 IV Resumen en espa˜nol (Spanish summary) 2.3 Comparaci´on de la biomasa migrante, el flujo gravitacional y migratorio, de acuerdo con la literatura . . . . . . . . . . . . . . . . . . . . . . . . . . 135 V Appendices A: Species abundance raw data from Chapter 1 . . . . . . . . . . . . . . . . . . 163 xxiii Part I Introduction 1 Background Background Diel vertical migration: History and the protagonists Diel vertical migration (DVM) is the most important synchronized mass movement of animal populations in the ocean and probably represents the largest migration on the planet [Angel and Pugh, 2000, Hidaka et al., 2001, Hays, 2003]. The earliest documented evidence for DVM dates back to the late 19th century when increased night-time catches were observed at the sea surface during the Challenger Expedition [Murray and Hjort, 1912]. However, it was not until the development of modern sonar by the middle of 20th century that the vertical extent and timing of DVM was reported for the first time [Dietz, 1948, Eyring et al., 1948]. Acoustic recordings of marine biota, today called echograms, showed scattering layers occurring between 400-700 m depth during the day, and above 100 m depth at night. The layers were connected through a dusk ascent and a dawn descent (Fig. I1). This diel rhythm promptly suggested that the phenomenon was due to migrating organisms, a fact that was later corroborated by concurrent net trawling across the acoustic scattering layers [Tucker, 1951]. We know now that although the main cause of oceanic acoustic resonance is gas-bearing animals such as swimbladder fish or siphonophores [Hersey and Backus, 1954, Barham, 1966], a huge variety of planktonic and nektonic organisms are actually involved in DVM (Fig. I2). Copepods [Roe, 1984b], euphausiids [Roe et al., 1984b], decapods [Roe, 1984a], fish [Roe and Badcock, 1984] and cephalopods [Roper and Young, 1975] are the most common taxa that undertake interzonal migrations, that is, between the epipelagic (∼0-200 m) and the mesopelagic zone (∼200-1000 m). In fact, when taking into account the whole community regardless of their visibility on echograms, the entire mesopelagic zone is indeed inhabited by interzonal migrants, with each species covering different migratory ranges [Domanski, 1984]. However, although DVM is undertaken by a wide range of species and sizes, it is fair to say that the most abundant and extensive movements are performed by large zooplankton and micronekton, which mostly comprise crustaceans and fishes from 1 to 10 cm in length [Brodeur et al., 2005]. While krill (Euphausiidae) is probably the most important migrant group within the zooplankton, lanternfishes (Myctophidae) dominate within the micronekton, the latter accounting for almost 80% of total migrant biomass [Koslow et al., 1997, Hidaka et al., 2003]. Since myctophids are very numerous and their swimbladder properties make them highly resonant targets [Butler and Pearcy, 1972, Yasuma et al., 2010], they are indeed the main source of acoustic scattering layers, frequently masking the presence of other migrant groups in routine echograms [Godø et al., 2009, Kloser et al., 2009]. 3 Part I. Introduction Figure I1: (A) First documented echogram showing diel vertical migration (nocturnal ascent) from the mesopelagic zone to shallow waters in the central equatorial Pacific [Dietz, 1948]. (B) Modern echogram showing a dawn descent and a dusk ascent in oceanic waters around the Canary Islands. Sv (volume backscattering strength) indicates the echo intensity. Factors governing diel vertical migration The unveiling of the nature of acoustic scattering layers lead to questions about the triggers and adaptive significance of DVM. Since the first descriptions of DVM, the coincidence of vertical movements associated with dusk and dawn pointed to light as the main factor governing this behavior [Johnson, 1948]. Earlier hypotheses had suggested that DVM resulted from vertical habitat selection based on highly specific isolumes [Kampa and Boden, 1954, Boden and Kampa, 1967, Blaxter, 1974]. However, later studies showed that migrant biota were actually found within broad light intensity zones [Roe, 1983, Frank and Widder, 2002, Staby and Aksnes, 2011]. The isolume concept was therefore abandoned and today it is widely accepted that different mesopelagic species settle within preferred ranges of light intensities [Badcock, 1970, Foxton, 1970b]. Alternatively, a reasonable question raised was whether DVM was controlled by internal clocks (circadian rhythms) adjusted to natural light variations rather than by light per se [Neilson and Perry, 1990]. However, this hypothesis seemed unlikely to be true since acoustic scattering layers were observed to respond under unpredictable light fluctuations, such as variable cloudiness or solar eclipses [Kampa, 1975, Bali˜no and Aksnes, 1993]. Hence, that light is the main factor governing DVM is today a widely accepted fact. There is, however, ongoing debate concerning the adaptive significance of this behavior. 4 Background Figure I2: The main fishes, decapods and cephalopods that undertake DVM in the subtropical northeast Atlantic: (F1) Lobianchia dofleini, (F2) Hygophum hygomii, (F3) Ceratoscopelus warmingii, (F4) Vinciguerria attenuata, (D1) Systellaspis debilis, (D2) Oplophorus spinosus, (D3) Deosergestes corniculum, (C1) Onychoteuthis banksii, (C2) Abraliopsis morisii, and (C3) Pyroteuthis margaritifera. The most accepted explanation is that since light is essential for visual foraging, but also increases the likelihood of being seen by predators, DVM would be a habitat selection game consisting of a trade-off between the availability of food and the necessity to avoid predators [Clark and Levy, 1988, Hays, 2003]. The extent to which a particular species is exposed to a certain light level will depend on its prey detection threshold and its capacity for camouflage [Warrant and Locket, 2004], factors that will determine the depth and timing of the migration [Aksnes and Giske, 1993, De Robertis, 2002, Busch and Mehner, 2011]. On the other hand, the bioenergetic efficiency hypothesis ”hunt warm, rest cool” postulates that saving energy by staying in cold waters is the primary reason for the descent, rather than the avoiding of predators [Brett, 1971, Sims et al., 2006]. A reduced metabolism is a common feature in deep-sea animals. It is a consequence of low temperature and might be advantageous for saving energy [Childress, 1975, Torres et al., 1979, Childress and Seibel, 1998]. However, this does not necessarily imply that bioenergetics are the main reason for diel migration. A reasonable proposition is that none of the proposals can explain DVM in all cases, since there is a broad spectrum of species and circumstances. The ultimate causes for DVM probably encompass feeding opportunities, predator avoidance, and energy saving [Mehner, 2012]. In fact, as a consequence of changing prey distributions, light, and temperature regimes in marine ecosystems, varied migrant strategies have been observed in different oceanographic regions. The normal DVM pattern (NDVM) of ”a dusk ascent and a dawn descent” is therefore currently a generalized and simplistic description rather than a 5 Part I. Introduction model explaining all variants of this phenomenon. For instance, recent studies have described migratory patterns where some individuals remain at depth, not performing migration [NoDVM, Dypvik et al., 2012], as well as others where the total population migrates [TDVM, Dypvik and Kaartvedt, 2013]. Even inverse migrations [IDVM, Dypvik et al., 2011], or midnight sinking between the ascent and descent have been documented [Prihartato et al., 2015]. All of these strategies must be related to changing resources and physical features over the water column, which are expected to change according to seasons and ecosystems. Figure I3: Daytime diel vertical migration depth (colours) modeled from oceanographic variables such as subsurface oxygen, epipelagic temperature gradient, surface chlorophyll or mixed-layer depth. Contours show the surface (0 - 25 m) to upper mesopelagic zone (150 - 500 m) oxygen difference (mmol m−3). From Bianchi et al. [2013a]. On the other hand, light not only governs DVM on a temporal basis, but its influence is also evident over spatial scales. Changing turbidity at the sea surface modulates light irradiance, affecting in turn the vertical distribution of scattering layers at both small and large scales over the oceans [Kaartvedt et al., 1996, Dickson, 1972]. Aside of light, there are other oceanographic factors likely to affect the distribution of deep-sea animals, such as temperature, dissolved oxygen, or water masses [Fasham and Foxton, 1979, Bianchi et al., 2013a, Wang et al., 2014, Cade and Benoit-Bird, 2015]. Other studies have even reported variability in the deep scattering layers, apparently driven by mesoscale eddies [Godø et al., 2012, B´ehagle et al., 2014]. Recently, Bianchi et al. [2013a] modeled the daytime depth of migrants at global scale based on several oceanographic predictors. Most variance in their model was explained by oxygen concentration, which limited the depth of the migrants (Fig. I3). However, they found a weak correlation with light. The main constraint of this model is that it refers to the migration depth of specific targets detected with acoustic doppler current profilers (ADCP). As previously stated, migrants also extend above and below the scattering layers. Many of them are well adapted to oxygen minimum zones [Childress and Seibel, 1998, Ekau et al., 2010], 6 Background and are highly influenced by light [e.g., Roe, 1983, Frank and Widder, 2002, Staby and Aksnes, 2011]. Therefore, the model of Bianchi et al. [2013a] should be regarded as a fairly good illustration of the migration depth of a specific scattering layer, but not representative of the whole migrant biota. The conjunction of all these factors (light, temperature, oxygen, water masses, and mesoscale activity) may lead to patchy distributions of the migrant biota. In summary, DVM is not simply a vertical movement of resonant fish in the ocean. It is a much more complex mechanism involving a huge variety of species, covering different depth ranges, while occurring through diverse migratory modalities in the world ocean. Importance of diel vertical migration for marine foodwebs While zooplanktonic migrants mainly feed on phytoplankton and microzooplankton, alternating between the second and the third trophic level [Vinogradov, 1962, Wilson et al., 2010], most micronekton are zooplanktivorous occupying the third position in oceanic food webs [Kozlov, 1995, Burghart et al., 2010, Choy et al., 2012]. As such, interzonal migrants can be classified as first or second order consumers. This means that primary productivity in shallow waters is transformed into mesopelagic biomass at most through two intermediate steps, such that it is a short trophic pathway which implies an effective energy transfer from the surface to the deep ocean (Fig. I4). In fact, very recent midwater fish biomass estimates suggest that transfer efficiencies between primary producers and the mesopelagic fauna in oligotrophic regions are actually much higher than previously assumed [Davison et al., 2013, Irigoien et al., 2014]. However, not all the biological production derived from DVM ends below the euphotic zone. In addition to deep predators such as midwater fishes [Choy et al., 2013] or cephalopods [Passarella and Hopkins, 1991], interzonal migrants are also preyed upon by many shallow living animals that either dive down into the mesopelagic zone or wait within the epipelagic to hunt them during the nocturnal ascent. Amongst the deep diving predators are marine mammals [Santos et al., 2001] and tuna species [Matsumoto et al., 2013], while the most common nocturnal shallow predators are small pelagic fishes [Cabral and Murta, 2002], dolphins [Pusineri et al., 2007], swordfish and also tuna [Potier et al., 2007]. Indeed, a significant mortality risk is faced in shallower waters because migrants there are highly motile during feeding periods, and therefore, more easily tracked by predators. Hence, interzonal migrants play an important role in pelagic ecosystems not only because they occupy a key trophic status, but also because their migratory behavior converts 7 Part I. Introduction Figure I4: Mesopelagic fish biomass as a function of primary production. Black dots are in-situ acoustic biomass estimates. The red line is the modeled biomass assuming a transfer efficiency of 0.1 and considering that 90% of primary production enters the food web. From Irigoien et al. [2014]. them into an essential food supply in both the epipelagic and mesopelagic zones. Indeed, their trophic interactions suggest that they are also important for driving primary production into the deep ocean [Irigoien et al., 2014], as well as for sustaining global fisheries [Pauly and Christensen, 1995, Lam and Pauly, 2005]. Relation to the ocean carbon cycle and climate change The ocean carbon pump refers to a conjunction of physiological, ecological and physical processes through which atmospheric carbon dioxide (CO2) is sequestered into the deep sea (Fig. I5). The sequestration begins at the surface with the fixation of inorganic carbon by photosynthesis (see equation below) and its subsequent transformation by foodweb associated processes into different forms of organic carbon, either forming part of living organisms or as inert organic matter in the water column. Through this process, photosynthetic organisms displace the equilibrium of the carbonate system in seawater, in this way accelerating CO2diffusion from the atmosphere into the ocean [Millero, 1995]. After this point, the organic carbon may be remineralized back via respiration of epipelagic consumers and microbial activity [del Giorgio and Duarte, 2002], or it may be exported to the ocean interior through three main mechanism, namely: (1) ocean dynamics, (2) gravity, or (3) mediation by DVM. CO2+ H2O respiration  photosynthesis CH2O+O2 8 Background The first mechanism refers to dissolved organic or inorganic carbon (DOC and DIC) exported by physical processes, such as convective mixing [Ar´ıstegui et al., 2003], watermass sinking [Sarmiento et al., 2004], or isopycnal diffusion [Arcos-Pulido et al., 2014]. The second, known as the ”passive” or ”gravitational flux”, occurs with the formation of particulate aggregates of organic carbon (POC) with highly specific sinking rates [Fowler and Knauer, 1986]. In the last case, the so-called ”active” or ”migratory flux”, the organic carbon is incorporated into the tissues and gut contents of interzonal migrants, and is later released in deeper waters through respiration [Longhurst et al., 1990], defecation [Steinberg et al., 2000], excretion [Turner, 2002] and mortality [Zhang and Dam, 1997]. When carbon export is exclusively driven by physical processes, we refer to it as the physical pump, whereas both the passive and active flux are known as the biological pump. Understanding the processes involved in the air-sea CO2balance is not a trivial matter. The oceans contain about 50 times as much carbon as the atmosphere, which means that small changes in the ocean carbon cycle could have large atmospheric consequences. This is of paramount importance considering that CO2is the main gas responsible for the current global warming scenario, and its partial pressure levels in the atmosphere are expected to double by the end of this century [IPCC, 2014]. In this respect, the oceanic carbon pump not only plays a key role in global climate, but it is also expected to be altered in a future high CO2world, though the nature of the change is still controversial [Robinson et al., 2010, Doney et al., 2012]. Approximately two-thirds of the carbon vertical gradient in the ocean is attributed to the biological pump with the rest due to the physical pump [Passow and Carlson, 2012]. Consequently, international research programs about the oceanic role in climate change (JGOFS, GLOBEC, IMBER) have been focused on the biological processes involved in carbon sequestration [Steinberg et al., 2001, Weingartner et al., 2002]. However, while the passive flux has been the object of much attention, the role of DVM has scarcely been considered by the developers of oceanic carbon budgets. Current estimates indicate that migrant zooplankton might be exporting roughly between 10 and 50% of the integrated passive flux down to the mesopelagic zone in subtropical waters [Steinberg et al., 2000, Hern´andez-Le´on et al., 2001, Steinberg et al., 2008]. Therefore, in recent studies this export mechanism has been considered in biogeochemical conceptual models [Ar´ıstegui et al., 2009, Robinson et al., 2010, Passow and Carlson, 2012], yet its contribution is rarely considered in oceanic global budget calculations. However, even summing up carbon fluxes mediated by migrant zooplankton and sinking POC, the total carbon export continues to be lower than global estimates derived through ecosystem modeling [Schlitzer, 2002, Falkowski et al., 2003, Usbeck et al., 9 Part I. Introduction Figure I5: Schematic of the biological carbon pump. Note that active flux is not considered beyond 1000 m depth, while micronekton are not represented in the diel vertical migration, only zooplankton. From Passow and Carlson [2012]. 2003]. Discrepancies are also evident below the mesopelagic zone, where both the carbon pool and microbial carbon demand cannot be sustained by the passive flux alone [Baltar et al., 2009]. All these imbalances have traditionally been ascribed to artifacts in the measurement of sinking POC [Buesseler et al., 2007], to unaccounted lateral inputs of POC [Alonso-Gonz´alez et al., 2009], and ultimately to biased carbon inputs mediated by migratory zooplankton [Steinberg et al., 2008]. However, the micronekton are rarely considered as an option (see Fig. I5). Micronekton are known to be involved in DVM and, therefore, in the active flux since the first faunistic descriptions of migrant scattering layers in the ocean [Tucker, 1951, Hersey and Backus, 1954, Barham, 1966]. Hence, it was not ignorance that kept the micronekton out of the scope of biogeochemical oceanographers. In reality, difficulties associated with sample collection were most likely the reason why the micronekton have been systematically excluded from carbon budgets. This community exhibits faster swimming capacity than the zooplankton, therefore requiring larger, more expensive and time-consuming trawls for sampling [Koslow et al., 1997, Pakhomov et al., 2010, Kaartvedt et al., 2012b]. However, precisely due to their high mobility, the micronekton are able to undertake extensive migrations from surface to deep waters, even beyond 1000 m depth [Badcock and Merrett, 1976, Kinzer and Schulz, 1985, Burghart, 2006]. 10 Chapter 1 Vertical distribution, composition and migratory patterns of acoustic scattering layers in the Canary Islands. Alejandro Ariza, Jos´e Mar´ıa Landeira, Alejandro Esc´anez, Rupert Wienerroither, Natacha Aguilar, Anders Røstad, Stein Kaartvedt, and Santiago Hern´andez-Le´on (2015). Submitted to Journal of Marine Systems. Abstract Diel vertical migration (DVM) facilitates biogeochemical exchanges between shallow waters and the deep ocean. An effective way of monitoring the migrant biota is by acoustic observations although the interpretation of the scattering layers poses challenges. Here we combine results from acoustic observations at 18 and 38 kHz with net sampling in order to unveil the origin of acoustic phenomena around the Canary Islands, subtropical northeast Atlantic Ocean. Trawling data revealed a high diversity of fishes, decapods and cephalopods (152 species), although few dominant species likely were responsible for most of the sound scattering in the region. We identified four different acoustic scattering zones in the mesopelagic realm: (1) at 400-500 m depth, a swimbladder resonance phenomenon at 18 kHz produced by gas-bearing migrant fish such as Vinciguerria spp. and Lobianchia dofleini, (2) at 500-600 m depth, a dense 38 kHz layer resulting likely from resonance of the gas-bearing and non-migrant fish Cyclothone braueri, and to a 17 Part II. Results lesser extent, from fluid-like migrant fish and decapods, (3) between 600-800 m depth, a weak signal at both 18 and 38 kHz ascribed either to migrant fish or decapods, and (4) below 800 m depth, a weak non-migrant layer at 18 kHz which was not sampled. All the dielly migrating layers reached the epipelagic zone at night, with the shorterrange migrations moving at about 4 cm s−1and the long-range ones at nearly 12 cm s−1. This work reduces uncertainties interpreting standard frequencies in mesopelagic studies, while enhances the potential of acoustics for future research and monitoring of the deep pelagic fauna in the Canary Islands. Introduction Acoustic scattering from marine organisms are caused by body structures with densities notably different from water, such as gas bladders or lipid inclusions [Simmonds and MacLennan, 2005]. Thanks to this phenomenon, the vertical distribution of pelagic animals can be easily monitored using scientific echosounders [Kloser et al., 2002, Kaartvedt et al., 2009, Cade and Benoit-Bird, 2015]. Two reflecting regions are normally visible in the ocean, the shallow and the deep scattering layers (SSLs and DSLs) occurring respectively in the epipelagic and the mesopelagic domains (0-200 and 200-1000 m depth), with the latter often portioned into multiple layers. Part of the biota forming the DSLs feed between dusk and dawn in the epipelagic zone, producing a thicker and more intense SSLs during the night. This displacement is known as Diel Vertical Migration (DVM), occurring on a daily basis around the world’s oceans and performed by a large variety of zooplankton and micronekton species [Tucker, 1951, Barham, 1966, Roe, 1974, Pearre, 2003]. DVM promotes trophic interactions and biogeochemical exchanges between the upper layers and the deep ocean [Ducklow et al., 2001, Robinson et al., 2010], and its study is therefore important for understanding pelagic ecosystems functioning. Micronekton, the migrating component studied here, is expected to account for a substantial export of carbon to the deep ocean as they comprise a significant fraction of the migrant biomass [Angel and Pugh, 2000] and cover more extensive depth ranges than zooplankton [Badcock and Merrett, 1976, Roe, 1984b, Domanski, 1984]. In fact, the importance of micronektonic fishes and decapods in mediating carbon export has been recently highlighted by several studies [Hidaka et al., 2001, Davison et al., 2013, Schukat et al., 2013, Hudson et al., 2014, Ariza et al., 2015]. Therefore, using acoustic observations for monitoring their distribution and migrations may be a powerful tool for the ocean carbon pump assessment. 18 Chapter 1 The present study was conducted in waters nearby the Canary Islands, a region in the subtropical northeast Atlantic exhibiting open-ocean and olygotrophic gyre characteristics [Barton et al., 1998, Davenport et al., 2002, Neuer et al., 2007]. Due to its position between temperate a tropical waters, this faunal province presents a high diversity of mesopelagic species in comparison to other latitudes [Backus and Craddock, 1977, Badcock and Merrett, 1977, Landeira and Fransen, 2012]. In the Canary Islands, the vertical distribution of fishes [Badcock, 1970], decapods [Foxton, 1970a,b], cephalopods [Clarke, 1969] and euphausiids [Baker, 1970] were thoroughly studied during the SOND cruise in the mid-sixties [Foxton, 1969], providing valuable knowledge about DVM in the area. More recent studies have contributed to a more detailed catalogue of mesopelagic species illustrating community differences between neritic and oceanic realms around the Canary Islands [Bordes et al., 2009, Wienerroither et al., 2009]. However, the lack of an integrated study combining acoustic data and biological information from net sampling has prevented the identification of the specific organisms responsible for each scattering layer occurring in the archipelago. This study describes acoustic scattering layers at 18 and 38 kHz occurring from the surface to 1000 m depth in the Canary Islands, as well as their diel migrant movements between the epipelagic and the mesopelagic zone. We also present the first attempt to identify organisms causing these layers by trawling. The assessment of species composition of the scattering biota was complemented with a swimbladder resonance model, and also contrasted with previous reports of the micronekton vertical distribution in the region. Methods Survey The survey was conducted in two locations southwest of La Palma and Tenerife Islands (Canary Islands), between the 1000 and 2000 m isobaths (Figure 1.1). From the 9th to the 18th of April, hydrographic and acoustic data, as well as micronekton samples were collected on board the R/V Cornide de Saavedra. Hydrography Vertical profiles of conductivity and temperature were collected using a SeaBird 9/11plus CTD equipped with dual conductivity and temperature sensors. CTD sensors were calibrated at the SeaBird laboratory before the cruise. A sensor for measurements of 19 Part II. Results dissolved oxygen (SeaBird SBE-43) and fluorometer for chlorophyll aestimations (WetLabs ECO-FL) were linked to the CTD unit. Seawater analyses of dissolved oxygen (Winkler titrations) and chlorophyll aextractions were performed to calibrate the voltage readings of both sensors. Analyses were carried out in accordance with the JGOFS recommendations [UNESCO, 1994]. Temperature, dissolved oxygen and chlorophyll a profiles were averaged from 3 CTD casts performed within each sampling area off La Palma and Tenerife Islands (Figure 1.2). Acoustics Hull-mounted SIMRAD EK60 echosounders operating at 18 and 38 kHz (11◦and 7◦ beam width, respectively) were used for recording acoustic data. Configuration was set at 1024 µs pulse duration and one ping every 3 seconds. Due to the draft of the transducer and to prevent near-field effects [Simmonds and MacLennan, 2005], acoustic data for the first 10 meters depth were not available. In order to avoid the rangeincreasing noise [Korneliussen, 2000], maximum depth of data used was 1000 m, and minimum threshold was set to -80 dB. The echosounders were calibrated in-situ by standard techniques [Foote et al., 1987]. Since acoustic records covered several days while trawling in each location, we opted for showing a composite echogram per location, which were obtained by averaging the daily acoustic data every minute (Figure 1.3 and 1.4). Fragments with scattering layers visibly affected by steaming noise or interferences from other acoustic devices were removed before averaging. Echograms were shown at 18 kHz and 38 kHz, and also as the difference between both frequencies (18 kHz minus 38 kHz). In order to calculate approximate vertical migration velocities, we manually marked sets of points over different migratory traces observed at 18 and 38 kHz. The velocities were extracted by averaging the slopes along the curves fitted to these points. All acoustic data were processed using customized applications in Matlab software. Biological sampling Micronekton was captured using a pelagic trawl with 300 m2mouth area and 45 m length. The mesh size was 80 cm near the opening, decreasing to 1 cm in the cod end. Hauls were performed horizontally along narrow depth ranges within the different scattering layers according to information provided by the echosounders and the Scanmar depth sensor attached to the trawl headline. Depth and time of each haul are pointed out by boxes overlaying a 24 hours echogram shown in Figure 1.3. Since the trawl had no opening-closing system, deploying and lifting were conducted minimizing towing to reduce the by-catch from non-desired strata. The towing speed varied between 2 and 20 Chapter 1 Figure 1.1: (A) Map showing the situation of the Canary Islands west off Africa. (B) Study areas southwest off La Palma and Tenerife Islands where acoustic recordings and net trawling were conducted (striped rectangles). 3 knots and the effective fishing time was one hour. Samples were frozen on board at -20◦C. Once in the laboratory, they were fixed in 4% buffered formalin and later transferred to 70% ethanol for species identification, enumeration, weighing and length measurements. Catch results were not standardized by water volume filtered since the effective mouth size was uncertain due to the decreasing meshes along the trawl. Number of individuals were instead shown as ”catch per unit effort” (CPUE), where effort was fishing time. Non-migrant species were excluded from abundances and biomass of the nocturnal epipelagic hauls (Table 1.1). For this, we checked the diel vertical distribution of micronekton species consulting the existing literature in the region [Clarke, 1969, Badcock, 1970, Foxton, 1970a,b, Badcock and Merrett, 1976, Roe and Badcock, 1984, Roe, 1984a]. We also excluded other non-migrant species that were detected in shallow waters during hauling tests performed at daytime. The naming convention for hauls was, a first letter depicting whether the tow was conducted during the day (D) or during the night (N), followed by a 3-digit number indicating the averaged depth, and finally a letter indicating if the location was La 21 Part II. Results Palma (P) or Tenerife (T). For example, D450T would be a daytime haul conducted at an averaged depth of 450 m depth in Tenerife. Community analyses Community assemblage structure was analyzed through hierarchical agglomerative and unweighted arithmetic average (UPGMA) clustering based on the Bray-Curtis similarity matrix [Bray and Curtis, 1957]. Significant clusters were afterwards tested using the similarity profile procedure [SIMPROF, Clarke et al., 2008]. The high diversity of the sampled community posed difficulties for illustrating CPUE results for all the species identified in this study (152). Many of these species showed very low CPUE, presumably contributing poorly to acoustic scattering and migrations. For this reason, after clustering we focused the graphical results on dominant fishes, decapods and cephalopods involved in diel vertical migrations in the region, and also on the most abundant nonmigrant species occupying the mesopelagic domain. Nevertheless, raw data of the entire community are also provided in supplementary material. Multivariate analyses were performed with Fathom toolbox for Matlab [Jones, 2014]. Source of scattering analysis A target much smaller than its incident wavelength produces a weak echo that increases rapidly with higher frequencies. On the contrary, for large targets the frequency has little effect [Simmonds and MacLennan, 2005]. Besides, targets with densities very different from those of seawater resonate (high scattering) when their dimensions are shorter but near the wavelength of a given frequency. This is typically caused by ”gas-bearing organisms”, such as some swimbladdered fish found in this study. On the other hand, weaker scattering should be caused by ”fluid-like organisms”, which have a density similar to seawater [Stanton and Chu, 2000, Lavery et al., 2002, Korneliussen and Ona, 2003]. This is the case of crustaceans, squid or non gas-bearing fish also found in our samples. Accordingly, the frequency response at 18 and 38 kHz, together with the information from trawling, was used here to investigate the species most likely causing scattering. The condition and the equivalent spherical radius (ESR) of the swimbladder, if present, was noted for the dominant species inhabiting each scattering layer. Three different swimbladder conditions (gas-filled, contracted or fat-invested) were assigned according to the species and size consulting swimbladders studies of Marshall [1960], Kleckner and Gibbs [1972], and Badcock and Merrett [1977]. The ESRs were estimated on the basis of standard lengths using species-specific equations given by Saenger [1989]. If equations were not available from a given specie, the radius was obtained from swimbladder spherical 22 Chapter 1 volumes of same size fishes given by Kleckner and Gibbs [1972] and using simple sphere calculations. Since swimbladder resonance also depends on the ambient pressure and the water density, a given swimbladdered fish may resonate or not depending on depth and frequency. Therefore, we also modeled the swimbladder scattering along depth at 18 and 38 kHz in order to investigate the cause of resonance on each strata. This was achieved following the model developed by Andreeva [1964], later adapted for prolate spheroids by Weston [1967], and applied as in Kloser et al. [2002]. TS = 10 log10(σbs) (1.1) σbs =a2 es fp f2 −12 +1 Q2!−1 (1.2) fp=fo21 2e−1 3(1 −e2)1 4 ln1 + (1 −e2)1 2 1−(1 −e2)1 2!−1 2 (1.3) fo=1 2πaes 3γP + 4µ1 ρ1 2(1.4) P= (1 + 0.103D)105(1.5) TS is the target strength of the swimbladder. σbs is the acoustic backscattering crosssection at the incident acoustic frequency (f) of an equivalent spherical swimbladder volume of radius aes with a prolate resonant frequency (fp), and a resonance quality factor of Q. The prolate resonant frequency is a function of the prolate spheroid roundness (e) and the spherical resonant frequency (fo) at a hydrostatic pressure (P) for fish depth (D) and fish tissue density (ρ), with a ratio of specific heats for the swimbladder gas (γ) and the real part of the complex shear modulus of the fish tissue defined by µ1. The values assumed were: µ1= 105 Pa, γ= 1.4, ρ= 1.075 kg m−3, and Q= 5, following Kloser’s et al. (2002) settings. We assumed eto be 0.3 according to swimbladder roundness values ranging from 0.2 to 0.4 for most mesopelagic fish species found in this study [Kleckner and Gibbs, 1972, Brooks, 1977]. Resonance was modeled for swimbladders of ESR from 0.3 to 1.8 mm, and from the surface to 1000 m depth. 23 Part II. Results Results Hydrography Both fishing areas were placed leeward of the islands presenting therefore similar hydrographical features (Figures 1.1 and 1.2). Sea surface temperature ranged between 19.5 and 19.8◦C while seasonal thermoclines were not present in any location (mixing period). Subsurface chlorophyll maxima appeared between 50 and 100 m depth with values of 0.48 and 0.40 mg m−3near La Palma and Tenerife Islands, respectively. Oxygen minima of about 3.3 mL L−1were located between 700 and 800 m depth in both places. Values were well above hypoxia levels [<1.4 mL L−1, Ekau et al., 2010]. 3 3.6 4.2 4.8 5.4 Oxygen (mL L−1) 0 0.12 0.24 0.36 0.48 7 11 15 19 23 0 100 200 300 400 500 600 700 800 900 1000 Temperature (°C) Depth (m) La Palma Island A 3 3.6 4.2 4.8 5.4 0 0.12 0.24 0.36 0.48 7 11 15 19 23 Tenerife Island B Chlorophyll a (mg m−3) Figure 1.2: Averaged profiles of temperature, dissolved oxygen and chlorophyll anear (A) La Palma and (B) Tenerife Islands. Distribution of acoustic scattering layers and migrations According to the different responses shown at 18 and 38 kHz and the depth of occurrence, we distinguished one shallow scattering layer (SSL) in the epipelagic zone and four deep scattering layers (DSLs) in the mesopelagic zone. All of them occurring in waters around La Palma and Tenerife Islands (Figures 1.3 and 1.4). The SSL became denser and thicker at night as a consequence of the aggregation of migrant layers coming from deeper waters. This occurred roughly between the surface and 200 m depth coinciding with chlorophyll and oxygen maxima (Figure 1.2). 24 Chapter 1 In the mesopelagic we identified (Figure 1.3): a zone characterized by a high backscattering at 18 kHz roughly between 400 and 500 m depth (DSL1), a zone mainly visible at 38 kHz between 500 and 600 m depth (DSL2), a weak backscattering zone at 18 and 38 kHz between 600 and 800 m depth (DSL3), and finally, a weak echo at 18 kHz approximately from 800 to 1000 m depth (DSL4). As exemplified in the echograms registered near La Palma, some scattering layers also exhibited diel vertical movements between the mesopelagic and the epipelagic zone. At sunset (Figures 1.4a and 1.4c), shallow upward migrations (U1) were registered from DSL1, moving at an averaged velocity of 4.5±2.6 cm s−1. Simultaneously, deeper upward migrations (U2) moved from DSL3 to shallow waters at 11.4±4.4 cm s−1. At sunrise (Figures 1.4b and 1.4d), shallow and deep migrations were observed following similar patterns but moving downwards (D1, D2). DSL1 at 18 kHz and DSL3 at 38 kHz practically disappeared during nighttime (signal close or below the minimum threshold, -80 dB). On the contrary, DSL2 at 38 kHz and DSL4 at 18 kHz apparently did not exhibit vertical movements. DSL2 was however slightly weaker during nighttime. These migratory patterns were visible at both frequencies everyday and everywhere regardless the location surveyed (La Palma or Tenerife Islands). Figure 1.3: Echograms at 18 and 38 kHz in waters nearby La Palma (A and B) and Tenerife (C and D) Islands, and differential echograms (18 minus 38 kHz) from the same locations (E and F). Acoustic scattering layers are indicated according to frequency response and the depth of occurrence; one shallow scattering layer in the epipelagic (SSL), and four deep scattering layers in the mesopelagic (DSL1, DSL2, DSL3 and DSL4). Time and depth of fishing hauls are indicated with boxes, where the central lines are the trawling depth medians, the edges of the box are the 25th and 75th percentiles and the whiskers extend to the most extreme trawling depths not considered outliers. 25 Part II. Results Taxonomic composition of acoustic scattering layers A total of 8199 individuals were classified, resulting in 104, 26 and 22 identified species of fishes, decapods and cephalopods, respectively. CPUE data per haul of all species captured during the survey is shown in supplementary material. Figure 1.4: Same echograms at 38 (A and B) and 18 kHz (B and C) showing migratory pathways near La Palma Island. Different upward (U1, U2) and downward (D1, D2) tracks are indicated with dashed lines and their averaged migrant velocities are given in the legends. Distinct acoustic scattering layers (DSL1, DSL2, DSL3 and DSL4) are indicated according to divisions proposed in Figure 1.3. Text boxes over the echograms indicate depth and time of fishing hauls. Fishes were the prevailing group captured within the nocturnal SSL (Table 1.1), contributing more than 70% in both abundance (%A) and biomass ( %B). Myctophidae was the dominant fish family (54%A and 52%B), followed by Phosichthyidae (9%A and 4%B), Gonostomatidae (3%A and 5%B) and Sternoptychidae (1%A and 1%B). Among all fish species, only Ceratoscopelus warmingii,Lobianchia dofleini,Hygophum hygomii and Vinciguerria attenuata accounted for more than 30% of the migratory fish, both in abundance and biomass. Decapods were the second most important group in shallow waters at nigth (15%A and 9%B), dominated by the families Oplophoridae (9%A and 6%B) and Sergestidae (5%A and 1%B). The most abundant decapods were Oplophorus 26 Chapter 1 functional (gas-filled) could cause resonance at 18 kHz (Figure 1.6a). Although we lack such information (Table 1.2), the scattering levels below 600 m depth are not indicative of swimbladder resonance. This is consistent with the fact that swimbladders are usually contracted (atrophied) in myctophids reaching these depths (see discussion below). Therefore, it is probably that both fishes and decapods inhabiting this strata behave as fluid-like targets, but uncertain which one causes more reflection. Contracted swimbladders are a common feature in large myctophids, which is the same as saying that the functionality of the swimbladder decreases with migration depth [Marshall, 1960, Butler and Pearcy, 1972, Davison, 2011a]. This is especially true in our study area, where the smallest myctophid Lobianchia dofleini exhibits the shallower migration depth while largest species such as Ceratoscopelus warmingii or Notoscopelus resplendens reach bathypelagic waters [Badcock and Merrett, 1976]. Since a ”cottony tissue” (expanded fibrous submucosa) fills most of the lumen in contracted swimbladders, the external size of the organ is probably not an accurate indication of the gas volume contained [Capen, 1967, Kleckner and Gibbs, 1972]. According to swimbladder catalogues, gas-bearing fishes occurred in our study only above 600 m depth, while swimbladders regressions in both Cyclothone species and myctophids are a common feature at deeper waters (see Table 1.2). In acoustic terms, this means that the deep mesopelagic zone must be dominated by fluid-like targets, where resonance models are hardly applicable. It would also explain why the relative high abundances from net sampling does not result in high backscattering at these depths. The DSL4 (800-1000 m depth) was out of reach of our trawl and this impeded the assessment of the species producing reflection. Although the deeper migrations observed in this study are somewhat associated with the DSL3 and DSL4, the latter was clearly visible both during day and night. This suggests that the DSL4 would mainly be caused by non-migrating organisms. In this respect, literature may provide clues about the likely targets. Below 800 m depth, non-migrant fishes such as Cyclothone pallida and Sternoptyx diaphana are abundant, but also large migrant fishes which not conduct migrations every day, such as Ceratoscopelus warmingii or Notoscopelus resplendens [Badcock, 1970]. C. warmingii individuals dominated at night in the SSL but were scarce in our daytime mesopelagic hauls, suggesting that they must inhabit somewhere below 800 m depth. Besides, the DSL4 is the most frequented daytime foraging zone by short-finned pilot-whales in the Canary Islands (Globicephala macrorhynchus), whose diet is known to be mainly composed by squid but also large fishes [Aguilar Soto et al., 2008]. Hence, both fishes or squid might be responsible of the DSL4 but also many other targets. Deeper hauls with concurrent acoustic records are therefore required to unveil the specific origin of this reflection. 33 Part II. Results Figure 1.7: Distribution of shallow and deep scattering layers (SSL and DSLs) based on observations at 18 and 38 kHz in waters around the Canary Islands (threshold - 80 to -50 dB). Only dominant animals likely to contribute more to backscattering are indicated (main scatterers in black, and secondary ones in gray). Blue and orange depict 18 and 38 kHz frequencies respectively, with dark colors indicating high backscattering and light colors representing weak backscattering. See discussion for further details. Overall, the association of scattering layers and animals proposed here (Figure 1.7) is consistent with the vertical distribution previously observed during the SOND expedition in the Canary Islands and other surveys in nearby oceanic waters [Foxton, 1969, Badcock and Merrett, 1976, Roe et al., 1984a]. Specifically, Badcock [1970] and Badcock and Merrett [1976] noted that most myctophid species inhabited between 400 and 600 m depth, while less species of larger sizes appeared deeper than 700 m depth. Their abundance tables also evidenced the shallower distribution for Lobianchia dofleini and Vinciguerria spp., and showed a prominent peak of Cyclothone braueri between 500 and 600 m depth. This matches with our description of the DSL1 and the DSL2. On the other hand, Foxton [1970a] and Foxton [1970b] reported maximum densities of decapods below 650 m depth. In this respect, both Badcock’s and Foxton’s studies proposed a distinction between ”shallow and deep mesopelagic fauna”, which they ascribed to adaptations for different light conditions. Based on the above, the interphase of high and weak scattering seen here around 600 m depth might be outlying this ”biocline” [Lezama-ochoa et al., 2014], with small and gas-bearing animals above, and larger and fluid-like organisms below. In fact, the increased migrant velocity of the deeper scattering biota (about 11-12 cm s−1) also supports the idea of larger and non gas-bearing animals. They can move faster not only because of their increased size, but also for not requiring gas volume adjustments during vertical migrations [Marshall, 1960, Butler and Pearcy, 1972, Kleckner and Gibbs, 1972]. 34 Chapter 1 In conclusion, this study has revealed a high diversity within the micronekton mesopelagic community (152 species identified), yet with few dominant species likely being responsible for most of the acoustic phenomena in the region. We suggest that the DSL1 (400-500 m depth) is largely formed by swimbladder resonance, produced by the migrant fishes Vinciguerria spp. and Lobianchia dofleini. We ascribe the DSL2 (500-600 m depth) to resonance of the gas-bearing fish Cyclothone braueri, but also to high densities of fluid-like migrant fish and decapods. The DSL3 (600-800 m depth) was caused either by migrant fish or decapods, but as for other layers occurring deeper, the specific target identities remain unknown. All layers exhibiting diel vertical movements reached the epipelagic zone at night, with the shorter migrations moving at about 4 cm s−1and the larges ones at nearly 12 cm s−1. This work reduces uncertainties interpreting sound scattering, although more accurate results will be obtained with deeper and higher vertical resolution trawling, using multifrequency lowering echosounders, as well as improving scattering models for pelagic animals in the region. Acknowledgements: We are grateful to the officers and the crew of the R/V Cornide de Saavedra for their work and support at sea. Thanks are also due to Ver´onica Ben´ıtezBarrios, Jos´e Esc´anez, Laia Armengol and Erika Gonz´alez for hydrographic data collection and water samples analyses. We are as well indebted to ´ Angel Guerra, ´ Angel Gonz´alez, Madel Carmen Mingorance and Vailett M¨uller for their valuable work on board identifying species. This work was funded by the Spanish Government projects CETOBAPH (CGL2009-13112) and MAFIA (CTM2012-39587). Alejandro Ariza was supported by a postgraduate grant from the Spanish Ministry of Science and Innovation (BES2009-028908). 35 Chapter 2 Migrant biomass and respiratory carbon flux by zooplankton and micronekton in the subtropical northeast Atlantic Ocean (Canary Islands). Alejandro Ariza, Juan Carlos Garijo, Jos´e Mar´ıa Landeira, Fernando Bordes, and Santiago Hern´andez-Le´on (2015). Published in Progress in Oceanography 134:330-342. Abstract Diel Vertical Migration (DVM) in marine ecosystems is performed by zooplankton and micronekton, promoting a poorly accounted export of carbon to the deep ocean. Major efforts have been made to estimate carbon export due to gravitational flux and to a lesser extent, to migrant zooplankton. However, migratory flux by micronekton has been largely neglected in this context, due to its time-consuming and difficult sampling. In this paper, we evaluated gravitational and migratory flux due to the respiration of zooplankton and micronekton in the northeast subtropical Atlantic Ocean (Canary Islands). Migratory flux was addressed by calculating the biomass of migrating components and measuring the electron transfer system (ETS) activity in zooplankton and dominant species representing micronekton (Euphausia gibboides,Sergia splendens and 37 Part II. Results Lobianchia dofleini). Our results showed similar biomass in both components. The main taxa contributing to DVM within zooplankton were juvenile euphausiids, whereas micronekton were mainly dominated by fish, followed by adult euphausiids and decapods. The contribution to respiratory flux of zooplankton (3.4±1.9 mg C m−2d−1) was similar to that of micronekton (2.9±1.0 mg C m−2d−1). In summary, respiratory flux accounted for 53% (range 23 to 71) of the gravitational flux measured at 150 m depth (11.9±5.8 mg C m−2d−1). However, based on larger migratory ranges and gut clearance rates, micronekton are expected to be the dominant component that contributes to carbon export in deeper waters. Micronekton estimates in this paper as well as those in existing literature, although variable due to regional differences and difficulties in calculating their biomass, suggest that carbon fluxes driven by this community are important for future models of the biological carbon pump. Introduction The oceans play a key role in the global carbon cycle, sequestering roughly 30% to 50% of the total anthropogenic CO2since the beginning of the industrial revolution [Sarmiento, 1993, Sabine et al., 2004, Denman et al., 2007]. The biological pump is one of the most important pathways through which carbon is transported vertically into the ocean [Ducklow et al., 2001, Fasham, 2003]. Therefore, understanding how it functions is of paramount importance in developing accurate global carbon models [Usbeck et al., 2003]. Its process consists of the fixation of inorganic carbon into organic carbon by photosynthesis and its transport downwards by both passive and active mechanisms [Ducklow et al., 2001]. Much effort has been dedicated to the former mechanism, the socalled gravitational flux, which refers to the sedimentation of organic matter through the water column [Fowler and Knauer, 1986, Buesseler et al., 2007]. In contrast, the active flux has been largely neglected by those who have analyzed carbon budgets in oceanic ecosystems. This flux is also known as migratory flux and refers to organic material that is actively transported by animals. The photoassimilated carbon is ingested on the surface by herbivores and subsequently by carnivores that swim to deeper waters, where they release carbon by respiration [Longhurst et al., 1990], excretion [Steinberg et al., 2000], defecation [Turner, 2002] and mortality [Zhang and Dam, 1997]. The behavior involving this transport is known as diel vertical migration (DVM). This proccess occurs on a daily basis in all oceans and is performed by a large variety of species of zooplankton and micronekton [Tucker, 1951, Barham, 1966, Roe, 1974, Pearre, 2003]. Most research involving migratory flux has focused on zooplankton [Longhurst et al., 1990, Zhang and Dam, 1997, Hern´andez-Le´on et al., 2001, Steinberg et al., 2008], as its 38 Chapter 2 sampling is relatively simple compared to that of larger organisms. Micronekton, mainly composed of fish, crustaceans and cephalopods ranging from 2 cm to 10 cm [Brodeur et al., 2005], exhibit a faster swimming capacity, and require larger, more expensive and time-consuming trawls for sampling [Koslow et al., 1997, Pakhomov et al., 2010, Kaartvedt et al., 2012b]. Nevertheless, because of their high mobility, micronekton might export carbon to deeper waters than zooplankton does. In addition, most of the ingested carbon at the surface is exported to their maximum inhabiting depth, since their guts take from hours to days to be evacuated [Baird et al., 1975, Clarke, 1982], whereas gut clearances in zooplankton only take a few minutes [Dam and Peterson, 1988]. In view of the above, migrant micronekton, together with zooplankton, are expected to considerably increase current estimates of migratory flux. A few notable studies have recently reinforced this hypothesis. The work by Hidaka et al. [2001] in the western equatorial Pacific is to our knowledge unique, as it simultaneously evaluates gravitational and migratory fluxes by both zooplankton and micronekton. They reported respiratory flux due to total micronekton of 28% to 55% of the gravitational flux at 160 m depth, while summing up zooplankton, this value accounted for 46% to 89%. In the northeast Pacific, Davison et al. [2013] recently estimated a ”fish-mediated export” of about 18% to 19% of the gravitational flux at a similar depth. Whereas in the Benguela upwelling system, Schukat et al. [2013] estimated a respiratory flux by decapods of 79% of the gravitational flux. The most recent attempt to estimate carbon transport by fish was conducted by Hudson et al. [2014] along the Mid-Atlantic Ridge and determined an export flux mediated by myctophids of up to 8% of the gravitational flux in the vicinity of the Azores Islands. Although these estimates are somewhat variable, they confirm that micronekton account for a significant fraction of the total carbon export in oceanic ecosystems. To contribute to these emerging studies, we present in this paper the first simultaneous evaluation of the gravitational and migratory carbon flux north of the Canary Islands by including both zooplankton and micronekton. This region of the northeast subtropical Atlantic is located in the upstream Canary Current, 400 km west of the African coastal upwelling system and therefore exhibits open-ocean and oligotrophic gyre characteristics [Barton et al., 1998, Davenport et al., 2002, Neuer et al., 2007]. The composition of both communities is described and their migrant biomass estimated. We also measured the electron transfer system (ETS) activity in zooplankton and the dominant species representing micronekton (Euphausia gibboides,Sergia splendens and Lobianchia dofleini) in order to assess the respiratory carbon flux by both migrating components. 39 Part II. Results Methods Surveys and hydrography From 24 March to 2 June 2011, nine surveys were carried out on a weekly basis in the Canary Current waters, in an oceanographic station (28◦31’ N, 15◦22’ W) 30 nautical miles north of Gran Canaria island (see Fig. 2.1). During this period, hydrographic, acoustic and biological samplings were performed on board the R/V Atlantic Explorer. Water samples were obtained using a rosette of six 4-L Niskin bottles. Vertical profiles of conductivity, temperature and fluorescence were collected to a 200 m depth using a SeaBird SBE 25plus CTD and a Turner SCUFA fluorometer attached to the rosette. Seawater analyses of chlorophyll awere performed in accordance with JGOFS recommendations [UNESCO, 1994] in order to calibrate the voltage readings of the fluorometer. Acoustics Acoustic data were recorded using a SIMRAD EK60 echosounder (7◦beam width) operating at 120 kHz. The configuration was set at a 1024 µs pulse duration and 1 s−1 ping rate. Prior to sunset and net trawling, the transducer was deployed into the water at roughly a 4 m depth, hanging from the starboard side while the vessel remained stationary. Data above a 10 m depth were excluded to prevent vessel-caused bubbles and near-field effects [MacLennan and Simmonds, 1992]; the maximum recorded depth was set at 200 m to avoid range-increasing noise [Korneliussen, 2000]. Once the DVM (nocturnal ascent) was completed and the migrant scattering layer appeared above a 200 m depth, the echosounder continued recording for 30 min. The Volume Backscattering Strength (Sv, units: dB re 1 m−1) was used as a proxy for the relative density of the migrant fauna during the sampling period. The minimum detection threshold was set at -80 dB. Gravitational flux Sinking particles were collected at 150 m depth using a free-drifting sediment trap (Technicap) with a collecting area of 1.25 m2. The trap was equipped with a 24-bottle carousel programmed to sample at 12 h intervals during day (08:00 to 20:00 h) and night (20:00 to 08:00 h). Each bottle was filled with a preserving solution consisting of 3.5% buffered formalin in filtered seawater with 5 g/kg NaCl. Upon trap recovery, samples were filtered through pre-combusted 0.7 µm Whatman GF/F filters and swimming organisms >1 mm 40 Chapter 2 were manually removed under a microscope. Filters were wrapped in pre-combusted aluminum foil and frozen at -20◦C until POC analyses, which were subsequently performed using a CHN analyzer (Carlo Erba EA 1108 Elemental) and according to procedures described by Alonso-Gonz´alez et al. [2010]. Figure 2.1: (A) Map showing the location of the Canary Islands west off Africa and Gran Canaria island inside the white box. (B) The time-series station (white triangle) in oceanic waters north of Gran Canaria. Net sampling Zooplankton was sampled during day and night from 200 m depth to the surface using a double WP-2 with 0.25 m2mouth areas and equipped with 100-µm mesh nets [UNESCO, 1968]. The volume of water filtered was determined using a calibrated TSK flowmeter. One of the samples was used for abundance and biomass measurements and the other for ETS assays (see section below). The first sample was preserved in 4% buffered formalin and divided into two subsamples on board. In the laboratory, one subsample was sieved and 0.1 to 0.2, 0.2 to 0.5, 0.5 to 1.0 and >1 mm size-fractions were obtained. Each fraction was subsequently dry weighed by standard procedures [after 24 h at 60◦C, 41 Part II. Results Lovegrove, 1966]. The other subsample was digitized using a scanner at a resolution of 1200 dpi and the organisms were automatically counted, measured and classified using ZooImage software, according to the procedures described by Grosjean and Denis [2007]. Taxonomic groups were established by a manually performed training set, achieving a global error in the classification below 5%. The area of each organism was converted into dry weight using the equations provided by Hern´andez-Le´on and Montero [2006], subsequently improved by Lehette and Hern´andez-Le´on [2009]. The length distributions of faunistic groups were also obtained from image analysis. For this purpose, the long side of the rectangles enclosing the entire area of the organisms was used as a proxy of total length. The biomass of migrant zooplankton was estimated by averaging the biomass difference between day and night for each sampling day. For this calculation, we only considered the size fraction >1 mm, since it was the only one that systematically showed a greater biomass during nighttime (no significant differences for smaller fractions) and was also where we found large migrating organisms such as euphausiids (see Table 2.1). Total migrant biomass was calculated using the standard dry-weighing procedure, whereas dry weight derived from image analyses was used only for comparing the relative biomass of different taxonomic groups. Micronekton were collected using a 5 m2Matsuda Oozeki Hu trawl [MOHT, Oozeki et al., 2004] with a 4-mm mesh size. According to the information provided by the echosounder, trawls were always performed 1 h after the nocturnal ascent and were towed obliquely across the acoustic scattering layer, distributed approximately from surface to 150 m depth. Towing speed was kept between three and four knots and the incoming water volume was measured using a calibrated General Oceanics flowmeter, mounted at the mouth of the trawl. The catch was sorted onboard into family taxa levels and once in the laboratory, wet-weight was immediately measured. Subsequently, samples were fixed in 4% buffered formalin and after two weeks were transferred into 70% ethanol for species identification, enumeration and length measurements. Due to the underestimation caused by extrusion through meshes and net avoidance [Pakhomov et al., 2010, Kaartvedt et al., 2012b], the catch biomass was corrected according to the MOHT capture efficiencies provided by Davison [2011b]: 14% for gas-bearing animals and 38% and 80% for large and small no gas-bearing animals. These efficiencies were applied in this instance to fish, decapods and euphausiids, respectively (see discussion for further details). Only vertically migrating micronekton were included in calculations (e.g., epipelagic fish and gelatinous organisms were removed). For this task, we checked the diel vertical distribution of micronekton species in the region according to the following literature: Badcock [1970], Foxton [1970a,b], Badcock and Merrett [1976], Baker [1970], Clarke [1969], Roe [1984a], Roe and Badcock [1984], Roe et al. [1984b] 42 Chapter 2 After correcting the MOHT sampling bias, we found that the largest contribution to the micronekton migrant biomass corresponded to fish, followed by small contributions by shrimps and krill (Fig. 2.8b). Abundance (ind m−3) A) 0 300 600 900 1200 D) Biomass (mg DW m−3) B) 0 3 6 9 12 E) 07−Apr 17−Apr 27−Apr 07−May 17−May 27−May 0 2 4 6 8 Days ETS (µL O2 mg DW−1 h−1) C) 0.1−0.2 mm 0.2−0.5 mm 0.5−1.0 mm >1.0 mm 0.1−0.2 mm 0.2−0.5 mm 0.5−1.0 mm >1.0 mm F) 0.1−0.2 0.2−0.5 0.5−1.0 >1.0 Figure 2.4: On the left: weekly time-series showing: (A) abundance, (B) biomass and (C) electron transfer system activity of different zooplankton size fractions captured during nighttime (at in situ temperatures ranging from 18◦C to 20◦C). On the right: (D, E, F), the same parameters averaged in a boxplot. In each box, the central diamonds represent the mean, the central lines the medians, the edges of the box are the 25th and 75th percentiles, the whiskers extend to the most extreme data points not considered outliers and outliers are plotted individually (circles). Considering all the migrant biota, the mean respiratory carbon flux out of the euphotic zone was 6.4±2.9 mg C m−2d−1, which represents 53% (range 23 to 71) of the mean gravitational flux in the area. About 29% and 25% of this flux corresponded to zooplankton and micronekton, respectively (Fig. 2.8c). Within the micronektonic component, fish were by far the major contributors to the respiratory carbon flux, accounting for 23% of the gravitational flux (Fig. 2.8d). Discussion Methodological approaches and constraints The WP-2 efficiently sampled migrant zooplankton such as juvenile euphausiids, but exhibited low performance for adult euphausiids, as they can easily avoid most of plankton 49 Part II. Results Abundance (ind 10−3 m−3) A) 0 3 6 9 12 D) Biomass (mg DW m−3) B) 0 0.1 0.2 0.3 0.4 E) 07−Apr 17−Apr 27−Apr 07−May 17−May 27−May 0 2 4 6 8 Days ETS (µL O2 mg DW−1 h−1) C) Myctophidae Sergestidae Euphausidae L. dofleini S. splendens E. gibboides Myc Ser Eup F) Figure 2.5: On the left: weekly time-series showing: (A) abundance, (B) biomass and (C) electron transfer system activity of three dominant taxa of migrant micronekton (at in situ temperatures ranging from 18◦C to 20◦C). On the right: (D, E, F), the same parameters are averaged in a boxplot. Capture-efficiency corrections are not applied in this figure. In each box, the central diamonds represent the mean, the central lines the medians, the edges of the box are the 25th and 75th percentiles, the whiskers extend to the most extreme data points not considered outliers and outliers are plotted individually (circles). nets [Brinton, 1967, Mathew, 1988]. This fraction and other large migrant species were collected using the MOHT, a sampling device that has proved to be highly effective at capturing krill and juvenile fish [Oozeki et al., 2004, Yamamura et al., 2010]. In fact, our results showed that these small organisms are an important component of migrant micronekton, which has been systematically biased in previous studies using large commercial trawls [see Bordes et al., 2009, Wienerroither et al., 2009, Landeira and Fransen, 2012, Ariza et al., 2014]. However, these studies also revealed that the MOHT sampled the adult fraction of several myctophid species and other large migrating fish poorly (e.g., Gonostoma or Chauliodus). Squid were also notably undersampled. In summary, the combination of both nets properly sampled migrant specimens from 1 to 50 mm. However, it left a gap in euphausiids from 6 to 12 mm and showed less efficiency for micronekton larger than 50 mm (Fig. 2.6). Micronekton net-sampling always involves biomass losses, either via the escapement of small animals through meshes or because of the evasion of large fast-swimmers [Koslow 50 Chapter 2 0 10 20 30 40 50 Frequency (%) Copepoda WP−2 0 10 20 30 40 50 Chaetognatha 0 1 2 3 4 5 6 7 0 10 20 30 40 50 Length (mm) Euphausidae Myctophidae MOHT Sergestidae 12 18 24 30 36 42 48 Euphausidae Figure 2.6: Length distribution (mm) of dominant taxa collected with the WP-2 (zooplankton) and MOHT (micronekton) nets. Measurements refer to total length, except for myctophids, which refer to the standard length. et al., 1997, Kloser et al., 2009, Pakhomov et al., 2010, Kaartvedt et al., 2012b]. Captureefficiency correction factors must therefore be applied in order to obtain more reliable results. For the present paper, we adopted those provided by Davison [2011b], who compared the MOHT catch with acoustic-based biomass estimations. Davison reported capture efficiencies of 14%, 38% and 80% for the following respective acoustic groups: (I) gas-bearing targets; (II) non-gas-bearing large targets; (III) non-gas-bearing small targets. According to our trawl data, group I corresponded to fish with inflated swimbladders and group III to euphausiids. We also extended the group I capture efficiency to the rest of fish, regardless of the absence of inflated swimbladders, as it is reasonable to assume that all of these would have similar avoidance capabilities. Major uncertainties are included in group II, which most likely includes non-gas-bearing fish, large crustaceans and cephalopods. Therefore, the estimated capture efficiency will likely result from the avoidance capabilities of these faunal groups together. Despite this problem, we adopted group II capture efficiency for decapods in the absence of more accurate correction factors. Squid were not corrected, as their occurrence was anecdotal and meaningless within the context of the surveys. Even though the uncertainty concerning decapods and squid biomass, the correction factors applied here for fish and euphausiids, the groups apparently more contributing to migrant biomass, are well supported by other studies. Similar to Davison [2011b], other acoustic surveys report fish biomass one order of magnitude higher than net-based estimates [Koslow et al., 1997, Kloser et al., 51 Part II. Results 2009, Yasuma and Yamamura, 2010, Kaartvedt et al., 2012b]. Concerning euphausiids, Yamamura et al. [2010] also reported capture-efficiencies close to 100% using the MOHT in the Bering Sea. Nevertheless, we consider our estimates to be somewhat conservative, since Davison [2011b] used a 1.7-mm mesh size and we used 4.0 mm; thus, our real capture-efficiencies will have been even lower due to higher escapement through meshes. In fact, Gartner et al. [1989] showed that the catch of myctophids smaller than 30 mm (standard length) increased by a factor of 2.7 if the mesh size of the trawl was reduced from 4.0 mm to 1.6 mm. The true in situ fish biomass will therefore be substantially higher considering that most myctophids caught for the current study were below this size (Fig. 2.6). Aside from the biomass underestimation, the size-bias also involved other limitations for the assessment of the active flux. On the one hand, smaller migrants might have a higher metabolism [Ikeda, 1989], thereby increasing the respiratory flux, while the missing large fraction is expected to cover longer migratory ranges, sequestering carbon to deeper waters. Respiratory rates along the different sizes of myctophids roughly ranged from 1 to 3 µL O2mg DW−1h−1, according to data collected from the literature (Fig. 2.7a), while the respiration predicted for the average weight of myctophids studied here (31±7 mg DW) was 1.98 µL O2mg DW−1h−1, as derived from the regression equation of these data. It might therefore be expected that our estimates of fish-mediated export fluctuated by roughly 50% depending on the fish sizes analyzed. However, respiration in crustaceans seemed to not change within the size range showed in Figure 2.7b. Concerning the depth of the carbon inputs, we assumed a range of 400 m to 500 m as the DVM depth, regardless of the fact that deeper migrant scattering layers had also been observed in the region (Ariza et al., unpub.). Therefore, our approach is considered conservative on this respect. We also assumed in our calculations that the migrant biomass measured at night in the upper 150 m depth would reach mesopelagic waters during the day, thereby disregarding the predation factor in our calculations. Some studies suggest that mesopelagic fish remove about 1% to 4% of the zooplankton biomass in the upper 200 m depth , but it is unclear which part of this consumption would affect the zooplankton migrant fraction [Hopkins and Gartner, 1992, Watanabe et al., 2002, Hudson et al., 2014]. Other authors have also addressed the predation impact on vertically migrating micronekton; unfortunately, none of these studies were quantitative [Kozlov, 1995, Sutton and Hopkins, 1996, Choy et al., 2013]. Considering the poor knowledge on this respect, we decided no to apply correction factors. This might constitute therefore a possible source of overestimation. 52 Chapter 2 Concerning zooplankton fluxes, they were calculated only in organisms larger than 1 mm in length, because the day-night biomass ratios only evidenced migrant activity within this fraction (Table 2.1). Using analogous sampling settings, Hern´andez-Le´on et al. [2002] also observed increases in nocturnal biomass only in large zooplankton. We also proposed the equation (2.4) for estimating the mass-specific ETS activity due only to the migrant part of the sample, which was apparently primarily formed by juvenile euphausiids. This was motivated due to ETS>1mm activities being systematically higher during the night than during the day (Table 2.1), likely reflecting the fact that the migrant biota had higher metabolism rates than their non-migrant relatives, a fact also observed by Minutoli and Guglielmo [2009] in the Mediterranean Sea. In this sense, we believe that the increase in zooplankton active flux (139%) following the application of the equation (2.4) is justified, as it reflects the higher metabolism of the migrant fraction. Certainly, the equation considers the ETS contribution of migrant and non-migrant organisms based on their biomass ratio, but disregards the metabolic differences among species. However, most of the variance in respiration rates among zooplankton is due to body weight, habitat temperature, habitat depth and physiological activity, whereas taxonomy is of lesser importance [Bode et al., 2013, Ikeda, 2014]. These explanatory parameters are likely to be distinctive between migrant and non-migrant zooplankton groups, regardless of the species. Additionally, performing the ETS analyses at species level in zooplankton was not as approachable as in the case of micronekton, since the time required for isolating the specimens can considerably decrease enzymatic activity [Ahmed et al., 1976, B˚amstedt, 1980]. We therefore considered that our approach was the most suitable, taking into account such difficulties. Respiration rates can be derived from ETS activities using correlations, or by directly measuring the oxygen uptake of living animals. Although the predictive accuracy of the first approach has been questioned due to the intraand interspecific variability of such correlations [B˚amstedt, 1980, Hern´andez-Le´on and G´omez, 1996, Bode et al., 2013], the in vivo experiments also involve important operational difficulties. Stress, starvation, crowding or bacterial growth can introduce substantial errors to the incubation-based measurements. In addition, certain animals such as mesopelagic fish, are extremely difficult to maintain alive for long enough periods to acquire reliable data [Torres et al., 1979, Donnelly and Torres, 1988]. The ETS approach was therefore adopted in the present study to circumvent these problems, but using a conservative R/ETS ratio of 0.5 for all taxa, according to averaged values ranging from 0.46 to 0.65 in mixed large zooplankton [Hern´andez-Le´on and G´omez, 1996], euphausiids (Hern´andez-Le´on et al., unpub.) and fish [Ikeda, 1989]. In fact, Figure 2.7 shows that the differences between our estimates and those based on in vivo experiments were not prominent [Donnelly and Torres, 1988]. 53 Part II. Results 0.1 0.5 1 5 10 Respiration at 20°C (µL O2 mg DW−1 h−1) Myctophids Myctophidae (Ikeda, 1989) Myctophidae (Donnelly and Torres, 1988) L. dofleini (This study) y= −0.0018x + 2.0355, n= 31, R2= 0.4644 1 5 10 50 100 500 1000 0.1 0.5 1 5 10 Body dry weight (mg) Crustaceans Deep−sea crustaceans (Herrera et al., 2014) Euphausiidae and Sergestidae (Donnelly and Torres, 1988) E. gibboides and S. splendens (This study) y= 0.0005x + 1.2459, n= 52, R2= 0.0429 Figure 2.7: Mass-specific respiration of micronekton normalized to 20◦C; includes own data (dark color) and estimates from existing literature (gray color). Values from Donnelly and Torres [1988] refers to oxygen consumption in vivo measurements, while those from Ikeda [1989] and Herrera et al. [2014] are respiration rates derived from ETS activities. Regression lines with 95% confidence intervals for literature data were also plotted (thick and thin lines, respectively). See methods section for further information about how the data from other sources were obtained. Particularities of zooplankton and micronekton active flux In terms of respiration, zooplankton and micronekton export similar amounts of carbon out of the euphotic zone, with the former’s flux (3.4±1.9 mg C m−2d−1) slightly higher than that of the latter (2.9±1.0 mg C m−2d−1). This resulted because both zooplankton and micronekton also provided similar biomass and respiratory rates. However, there are other mechanisms of carbon export that are expected to differ markedly where zooplankton and micronetkon are concerned. Gut flux refers to the downward transport of non-assimilated food in the gut of animals and later released by defecation. Unlike respiration, which produces dissolved inorganic carbon (DIC), the gut flux contributes to the particulate organic carbon (POC) pool. This flux is expected to work more efficiently in micronekton, because of their slower gut clearance rates compared to that of zooplankton, which means a higher proportion of fecal matter actively exported below the seasonal pycnocline. In fact, gut clearance only takes a few minutes in copepods [Dam and Peterson, 1988] and about 30 min to 90 min in euphausiids [Gurney et al., 2002, Pakhomov et al., 2004], while in fish, estimates range from 12 h to days [Baird et al., 1975, Clarke, 1982]. If we assume a nocturnal distribution at roughly a 50 m depth and a mean downwards migration velocity of 5 cm s−1[Davison et al., 2013], organisms trespassing the base of the mixed layer (∼150 m depth) will take about 30 min. This infers that no fecal matter will be actively exported by copepods, euphausiid gut flux 54 Chapter 2 will be partial, while most non-assimilated food in the fish guts will be released into the mesopelagic zone. Gut flux was not measured for the present study, however, using energy budgets, defecation can be roughly estimated from respiration. According to energy budgets listed by Brett and Groves [1979], carnivorous fish defecate approximately an amount equivalent to 40% of the respired carbon. As only half of the daily respiration occurs in the mesopelagic zone, but most fecal matter is actively transported there, the gut flux of fishes will as a result represent about 80% of their respiratory carbon flux, which in the present study corresponds to 2.1±0.7 mg C m−2d−1. Together with the respiratory flux mediated by both zooplankton and micronekton, this will account for 8.5±3.6 mg C m−2d−1, meaning about 70% of the gravitational flux measured at 150 m depth. Below this depth and after defecation, the fast sinking fecal pellets would reinforce the already weakened gravitational flux coming from surface, bypassing carbon from active to passive flux at mesopelagic depths [see Alonso-Gonz´alez et al., 2013]. At this point, there are also important differences between zooplankton and micronekton since larger animals produce larger fecal pellets, which are expected to sink faster and to reach greater depths before decomposition [Small et al., 1979, Robison and Bailey, 1981, Røstad and Kaartvedt, 2013]. Other exporting mechanisms such as the carbon inputs via excretion [Steinberg et al., 2000] and mortality [Williams and Koslow, 1997] still remain to be considered. Beyond discussions regarding the amount of exported carbon, the depth range of active flux is another important issue that should be considered when comparing zooplankton and micronekton. Sameoto et al. [1987] found that juvenile euphausiids performed shallower migrations (170 m) than adults (350 m). Fish migrate to even deeper waters (>500 m) as they increase in size [Moteki et al., 2009]. In fact, the largest myctophid species inhabit bathypelagic (>1000 m) waters during the day [Badcock and Merrett, 1976]. Therefore, as juvenile euphausiids were in this instance the primary contributing component to zooplankton flux, while adult euphausiids and other larger species contributed to micronekton flux, we suggest that zooplankton flux may operate at a lower depth range than that of micronekton. This might be irrelevant in migratory flux calculations across the base of the euphotic zone (∼150 m depth), but nonetheless suggests that at deeper waters, micronekton might be the main carbon-exporting component. In addition, the active to passive flux ratio must be considerably higher at these depths since the gravitational flux decays exponentially with depth [Suess, 1980, Antia et al., 2001]. 55 Part II. Results Taxa Terms Migrant biomass (mg C m−2) Migratory flux (mg C m−2d−1) Gravitational flux (mg C m−2d−1) Migratory/Gravitational (%) Location Source Zooplankton R 107-412 (266±126.6) 1.13-4.45 (3.44±1.94) 6.31-26.70 (11.89±5.84) 10-37 (29) Canary Islands This study R,E,M 126 3.2-13.6 18.0 11-44 Hawaii Steinberg et al. [2008] R,E,M 1280 31.1-91.6 23.1-61.8 26-200 N. W. Pacific Steinberg et al. [2008] R 580 - 1280 1.85-8.28 15.8 11-52 Canary Islands Yebra et al. [2005] R 261 1.92 - 4.29 9.5-12.0 16-45 Canary Islands Hern´andez-Le´on et al. [2001] R 145-448 7.3-19.05 54.8 13-35 W. Eq. Pacific Hidaka et al. [2001] R,E,F,M 158 3.6 23.7 15 Hawaii Al-Mutairi and Landry [2001] R,E 49-123 2.0-9.9 25.6 9-39 Bermuda Steinberg et al. [2000] R 47 3.1 49.2 6 W. Eq. Pacific Le Borgne and Rodier [1997] R 53 6.3-7.9 204.0 3-4 E. Eq. Pacific Le Borgne and Rodier [1997] R,M 96-155 7.1-12.7 22.8-28.8 31-44 E. Eq. Pacific Zhang and Dam [1997] R 82-536 (191±147) 6.2-40.6 (14.5±11.1) 25-58 (39±10) 18 - 70 (34±16) Bermuda Dam et al. [1995] R - 2.8-8.8 64.0-86.0 4-14 Sargasso Sea Longhurst et al. [1990] Euphausiids R 6-19 (10±4) 0.06-0.19 (0.11±0.04) 6.31-26.70 (11.89±5.84) 0.5-1.6 (0.9) Canary Islands This studya‡ R 33-159 0.10-0.46 54.8 0.2-0.8 W. Eq. Pacific Hidaka et al. [2001]b§ E, F, M - 1-32 - - N. E. Atlantic Angel and Pugh [2000]e‡ Decapods R 15-28 (23±5) 0.09-0.17 (0.14±0.03) 6.31-26.70 (11.89±5.84) 0.4-1.4 (1.2) Canary Islands This studya‡ R 291 13 8.3 79 Northern Benguela Schukat et al. [2013]d† R 44-96 0.12-0.26 54.8 0.2-0.5 W. Eq. Pacific Hidaka et al. [2001]b§ E, F, M - 1-6 - - N. E. Atlantic Angel and Pugh [2000]e‡ Fishes R 88-242 (168±58) 1.41-3.86 (2.68±0.92) 6.31-26.70 (11.89±5.84) 12-32 (23) Canary Islands This studya‡ R 285 0.33-1.94 (0.92) 86.0-259.0 0.3-1.0 North Azores Hudson et al. [2014]b‡ R, F, M 15-276 (92±72)* 8.0-30.8 45.5-166.0 18-19 N. E. Pacific Davison et al. [2013]c‡ R 1778-3304 7.6-14.1 54.8 14-26 W. Eq. Pacific Hidaka et al. [2001]b§ E, F, M - 2-43 - - N. E. Atlantic Angel and Pugh [2000]e‡ M 299 3.1-11.1 - - Tasmania Williams and Koslow [1997]e§ Micronekton R 115-264 (201±61) 1.61-4.02 (2.92±0.95) 6.31-26.70 (11.89±5.84) 14-34 (25) Canary Islands This studya‡ R 2137-3614 15.2-29.9 54.8 28-55 W. Eq. Pacific Hidaka et al. [2001]b§ Total R 222-676 (467±187) 2.748.47 (6.36±2.89) 6.31-26.70 (11.88±5.84) 23-71 (53) Canary Islands This studya‡ R 2282-4062 22.5-49.0 54.8 41-89 W. Eq. Pacific Hidaka et al. [2001]b§ a14, 38 and 80% capture efficiency assumed for fishes, decapods and euphausiids. b14% Capture efficiency assumed. cCapture efficiency adjusted to concurrent acoustic biomass estimates. Migratory flux obtained from ”fish-mediated export” by vertical migrating fishes. d33% Capture efficiency assumed. eCapture efficiency not corrected. †Small frame trawl,‡big frame trawl,§commercial-sized midwater trawl *Calculated from MOHT nocturnal shallow tows showed in supplementary Table A2 of Davison et al. (2013). Table 2.3: Comparison of migrant biomass and migratory and gravitational fluxes from the literature. In the ”Terms” column, ”R” refers to respiratory flux, ”E” to excretion, ”F” to fecal, and ”M” to mortality. Fluxes refers to carbon export beneath the epipelagic zone (150 m to 200 m depth, depending on the study). The type of trawl and capture efficiency corrections are indicated for micronekton data. Values are given as ranges, as well as means (in parentheses). 56 Chapter 2 Migratory fluxes: comparisons among different studies Zooplankton flux variability among different studies mainly relies on the terms used for calculations (respiration, defecation, excretion or mortality), as well as on the hydrographic characteristics of the region (Table 2.3). For example, our migrant biomass and ETS measurements for zooplankton were quite similar to those reported by Hern´andezLe´on et al. [2001] in waters around the Canary Islands and therefore, the respiratory fluxes were also similar. Zooplankton flux was also within the range of most estimates for similar oligotrophic regions, such as Hawaii and Bermuda. However, mesotrophic waters such as the subarctic North Pacific [Steinberg et al., 2008], or inside eddies with enhanced biological production [Yebra et al., 2005], yielded much greater biomass and fluxes. Concerning micronekton, fluxes exhibited more variability than those of zooplankton (Table 2.3). In some cases, these differences were related to hydrographic conditions, such as the pronounced biomass of decapods in the highly productive Benguela upwelling system [Schukat et al., 2013]. However, in other cases, estimations conducted in similar oligotrophic regions also showed order-of-magnitude differences in biomass [e.g., Hidaka et al., 2001]. This variability was particularly pronounced among fish, and likely reflects the inherent sampling problem of micronekton: escapement and avoidance [Pakhomov et al., 2010, Kaartvedt et al., 2012b]. The different sampling gears used and the uncertainty concerning their capture efficiencies are most likely the major constraint to making valid comparisons across the globe. To our knowledge, the first attempts to assess micronekton export flux were performed by Williams and Koslow [1997] and Angel and Pugh [2000]; however, these estimates are not comparable to the results in the present paper, as neither were based on respiration. As in the present study, Hidaka et al. [2001] estimated respiratory fluxes for dominant taxa belonging to micronekton in the western equatorial Pacific. These results are comparable to ours, as both were performed in low-productive and open-ocean areas, although Hidaka et al. [2001] used a commercial-sized midwater trawl. In this case, fluxes mediated by crustaceans were similar to ours, but that of fish was fourto fivefold higher, because their corrected biomass was also much higher. As a result of this difference among fish (the major component of DVM), and likely because Hidaka et al. [2001] also included a substantial flux that was mediated by squid (not found in the present paper); their estimate for the total respiratory flux of micronekton was roughly one order of magnitude higher compared to that in the present study (see values in Table 2.3). 57 Part II. Results Recently, Davison et al. [2013] estimated fish-mediated exports in both oceanic and productive coastal upwelling areas of the northeast Pacific. Using the same sampling gear as in the current study, their corrected biomass was similar to ours, while the estimated migratory flux in oceanic waters was 8 mg C m−2d−1, about three-fold higher than the carbon export by migrant fish here (Table 2.3). Our results and those of Davison et al. [2013] are not as different considering that they also included defecation, excretion and mortality in their flux calculations. According to fish energy budgets [Brett and Groves, 1979], the fish-mediated flux estimated here would be about two-fold higher if these exporting mechanisms were included. The most recent attempt to estimate carbon transport by fish was made by Hudson et al. [2014] along the Mid-Atlantic Ridge. Using a frame trawl with a 6x6 m mouth opening, this study reported a corrected migrant biomass close to our estimate, while based on the oxygen consumption rates reported by Donnelly and Torres [1988], a respiratory flux twoto five-fold lower than in the present study was calculated (Table 2.3). It is therefore difficult to provide valid comparisons of migratory fluxes without evaluating the mechanisms involved (respiration, defecation, excretion, mortality), the components analyzed (copepods, euphausiids, decapods, fish, squid), the affecting hydrographic factors or the sampling gear used. Regardless of this variability, the fluxes estimated in the present study for micronekton, as well as those from previous studies (Table 2.3), all indicate values within the range of zooplankton fluxes. These results highlight the importance of including micronekton together with zooplankton when studying active carbon export. Active and passive flux Migratory fluxes vary regionally with changes in temperature and productivity [Davison et al., 2013], as does gravitational flux [Suess, 1980, Pace et al., 1987]; therefore, the former are often presented relative to the latter in order to clarify comparisons between different areas. Gravitational POC flux in this study was 11.9±5.8 mg C m−2d−1, which is similar to other estimates found around the Canary Islands [Neuer et al., 1997, Alonso-Gonz´alez et al., 2010]. Respiratory flux by zooplankton ranged from 10% to 37% (mean 29%) of gravitational flux measured at 150 m depth, which was found to be in reasonable agreement with values reported for the Canary Islands and to most other oligotrophic studies listed in Table 2.3. In summary, the respiratory flux of zooplankton and micronekton ranged from 23% to 71% (mean 53%) of the gravitational flux. This percentage was close to the range suggested by Hidaka et al. [2001] in the west equatorial Pacific (41% to 89%). On the other hand, our active flux estimates concurred with those of Hern´andez-Le´on et al. [2010] found in Canary Islands waters. Based on the modeled 58 Chapter 3 Figure 3.1: Position of El Hierro Island (A) and sampling points (B). The yellow star marks the position of the volcano. Symbols and arrows indicate oceanographic stations and locations of trawl tows, respectively. Colors refer to different surveys performed during the sampling period. Solid and dashed frames delimit experimental (volcano affected) and control (non-affected) zones, where satellite and acoustic data were collected along time-series. that, remaining missing data were calculated by linear interpolation of the bordering pixels. Processing of satellite imagery was performed with SeaDAS software. Acoustic sampling Hull-mounted SIMRAD EK60 echosounders (7◦beam width) operating at 38 and 200 kHz were used for recording acoustic data (detection ranges of about 200 and 1000 m depth, respectively). The configuration was set at a 1024 µs pulse duration and a 1 s−1ping rate. Acoustic data were not available for the upper 15 m due to the depth of the transducers (8 m on the R/V Ram´on Margalef and 5 m on R/V Cornide de Saavedra) and because data down to 7 m below the transducers were excluded due to vessel-caused bubbles and near-field effects [MacLennan and Simmonds, 1992]. Since the volcano eruption was an unforeseen event, the R/V Ram´on Margalef performed its first mission at sea without prior in situ acoustic calibration. For that reason, the acoustic data collected with this vessel were calibrated using correction factors obtained by standard calibration techniques [Foote et al., 1987] after the surveys. Echo sounders 65 Part II. Results on the R/V Cornide de Saavedra were calibrated prior to the cruise, also using standard procedures. Net sampling Epipelagic mesozooplankton was sampled from 200 m depth to the surface using a WP-2 plankton net equipped with 100 µm mesh. Samples were immediately fixed in 4% buffered formalin. In the laboratory, samples were digitalized using a scanner at a resolution of 1200 dpi and the organisms were automatically counted, measured and classified using ZooImage software according to the procedures described by Grosjean and Denis [2007]. Taxonomic groups were established by a manually entered training set, achieving a global error rate of only 4.7% in the classification. The area of the organisms was then converted into biomass using the equations given by Lehette and Hern´andez-Le´on [2009]. Vertical migrant micronekton was captured using a midwater trawl with a 300 m2mouth area and ∼45 m length. The mesh size was 80 cm near the opening, decreasing to 1 cm in the cod end. In the last survey, two tows were performed obliquely in the MSL. The trawl was monitored by a Scanmar depth sensor and was guided into the MSL by information provided by the echosounders. The trawling speed varied between 2 and 3 knots and the effective fishing time was one hour. Samples were fixed in 4% buffered formalin for later identification and enumeration. Acoustic analysis Anomalies in the distribution of acoustic targets were observed with the 38 kHz frequency related to the increment of surface turbidity and the oxygen depletion. For that reason, acoustic transects were made throughout the emission plumes, and their timebased echograms were displayed at this frequency together with corresponding latitudelongitude SSR from satellite imagery and spatially coincident profiles of dissolved oxygen. The acoustic measuring unit was the Volume Backscattering Strength (Sv, units: dB re 1 m−1) and the minimum detection threshold was set at -80 dB. Acoustic, satellite and hydrographic data were integrated and plotted using MATLAB software. In Fig. 3.2, two acoustic transects are shown: one between the main plume surrounding the volcano and an anticyclonic eddy, which was advecting emissions toward the open ocean (Fig. 3.3), and the other crossing a secondary plume, which drifted to the north side of the island (Fig. 3.4). 66 Chapter 3 The upper depth of the DSL (i.e., the part of the deep scattering apparently not involved with DVM) was mapped together with the contour of the plume to depict their geographical coupling. Since the upper part of the DSL appeared to be shallow beneath the plume (see Results), we manually traced the top boundary along the 38 kHz echogram using LSSS software. The averaged upper depth every 0.2 nm was afterwards map-projected and interpolated using the DIVA algorithm [Troupin et al., 2012]. Day and nighttime DSL depths were interpolated together as we did not observe significant differences between the two. Nevertheless, original data points are shown in the map in black (night) and white (day) to distinguish them (Fig. 3.5a). The outer limit of the plume was set in the SSR isoline of 0.2 10−3sr−1because this was the averaged sea surface reflectance found in clean waters near the plume. In addition, the relationship between the DSL depth and the geographically coincident SSR was plotted and linear regressions were run for both day and nighttime values (Fig. 3.5b). Figure 3.2: Sea Surface Reflectance (SSR) from satellite imagery. SSR indicates the degree of water turbidity and reveals the distribution of volcanic emissions. Red dots are CTD stations and black lines depict acoustic transects performed between them. Echograms corresponding to the transect lines and oxygen profiles from each station are shown in Fig. 3.3 (7 Nov.) and 3.4 (18 Nov.). 67 Part II. Results In addition to the net sampling (see above), the presence of epipelagic mesozooplankton and vertical migrant micronekton was also assessed using acoustics. The acoustic density of the former was calculated using the 200 kHz frequency, as the average length of members of this community (0.2-2 cm) fit quite well with its lowest resolution limit (wavelength of 0.75 cm). Fluid-like elongated mesozooplankton was the most abundant group collected by net sampling (see results). The detection threshold was therefore lowered to -100 dB in order to cover the weak backscattering caused by this group [Stanton and Chu, 2000]. To exclude noise and echoes from mesopelagic migrants, only daytime acoustic data collected above 100 m depth were used and fish-like schools were removed before the echo integration. Vertical migrant micronekton (2-10 cm) was monitored by acoustic sampling, but during the last survey, the composition of this community was assessed by trawlings in the MSL. The MSL acoustic density was estimated with 38 kHz (wavelength of 3.9 cm) as that frequency has been shown to be optimal for fish detection [Love et al., 2004, Simmonds and MacLennan, 2005]. Fish was the main group forming the MSL in the Canary Islands according with our results and previous works [Bordes et al., 2009, Wienerroither et al., 2009]. Only nighttime data collected above 200 m depth was used and the minimum threshold for integration was set at -80 dB to exclude weaker echoes caused by smaller organisms. Acoustic processing (noise removal and animal group allocation) was achieved using LSSS software [Korneliussen, 2000, Korneliussen et al., 2009]. The averaged form of Sv, i.e., the mean volume backscattering strength (MVBS), was used as an indicator of animal density. We therefore refer to MVBS200 kHz and MVBS38 kHz as proxies for the density of epipelagic mesozooplankton and vertical migrant micronekton, respectively. Because full species discrimination was not possible using the acoustics, these allocations should be interpreted as approximations based on the dominant communities found in net samples rather than exclusive taxonomic groups (i.e., macrozooplankton and gelatinous taxa were also expected to be within the MSL, but micronekton was the dominant group, and they were likely the most visible targets of the 38 kHz frequency). Monitoring of the pelagic biota Temperature, oxygen, chlorophyll a, epipelagic mesozooplankton and vertical migrant micronekton were measured during six months covering the eruptive and post-eruptive phases. As an indicator of the degree of volcanic emissions, five-day averaged SSRs are also shown (Fig. 3.6 and 3.7). Two zones were set for collecting samples and data: the experimental zone, in the south bay of the island where the erupted material remained blocked most of the time, and the control zone outside the bay, to the east of La Restinga front (see Fig. 3.1). Although the magmatic eruptive phase officially stopped on 5 March 68 Chapter 3 2012 [Rivera et al., 2013], waters along the south bay of the island were significantly cleaner around early February (according to SSR data). To study the effects on the surrounding pelagic biota, we designate the post-eruptive phase as starting in February 2012. Chlorophyll acollected at 5 m depth and from remote sensing data was used as a proxy for the phytoplankton biomass. During the third and fifth cruises, in situ measurements of chlorophyll awere not available, so we derived the data from the fluometer sensor, which was calibrated using regression equations derived from chlorophyll ameasurements performed during adjacent surveys. Epipelagic mesozooplankton and vertical migrant micronekton densities were assessed from both acoustic and net sampling approaches (see above). All those variables were replicated in the two zones. Data from water and net samplings were averaged from oceanographic stations that were selected within each zone. Satellite and acoustic data were also collected within those zones. The MVBS acoustic data were averaged from cells collected every 0.2 nm along the zones. Results Acoustic tracks and echograms The 38 kHz echogram (Fig. 3.3) recorded during the acoustic transect on 7 November 2011 (Fig. 3.2b) was dominated by two scattering layers: the DSL at around 300-700 m depth during both day and night and the MSL above 200 m during nighttime. According to catches (Table 3.2) those scattering layers were composed of small fishes, cephalopods and shrimps, but they were largely dominated by myctophids. The echogram registered the upward and downward migrations of the MSL respectively coinciding with the sunset and sunrise. In addition to the typical DVM behavior, two anomalies were observed in the nocturnal echogram associated with the plume: a strong weakening of the MSL (73 ±18 %) and an elevation of the upper limit of the DSL (∼100-150 m). During the first and fourth CTD cast (in the plume) both anomalies occurred, coinciding with an increase of the SSR (the surface was more turbid) and a dramatic decrease in the dissolved oxygen around 70-80 m depth (∼50%). The second and third casts were performed during daytime, when we observed a weaker scattering layer above 50 m depth produced by non-migrant biota. This scattering layer and the DSL did not display anomalies at the second station (outside the plume), nor did the oxygen profile or the SSR. Nevertheless, at the third station (the anticyclonic eddy), the DSL increased again and the Svalso decreased in shallow waters. That coincided with an increase of SSR but this time the oxygen profile remained unchanged. 69 Part II. Results Depth (m) A MSL DSL 100 200 300 400 500 600 700 800 900 Sv (dB) −80 −75 −70 −65 −60 −55 −50 2 3 4 5 1 Oxygen (mL/L) 2345 2 2 3 4 5 3 2345 4 0 1 2 3 4 SSR (10−3 sr−1) B 00 03 06 09 12 15 18 21 00 Time (h) Figure 3.3: 38 kHz echogram (A) and Sea Surface Reflectance (B) on 7 November 2011 along the acoustic transects indicated in Fig. 3.2b. The color scale refers to backscattering strength (Sv). Migrant and Deep Scattering Layers (MSL and DSL) as well as both diel migrations (∗) are indicated. Acoustic anomalies are also indicated: the MSL weakening (yellow triangles) and the elevations of the DSL (red triangles). Red lines depict the dissolved oxygen profiles established during the acoustic track. The black color in the time scale refers to nighttime and white to daytime. According to remote sensing data, the plume was less dense on the northern side of the island by 18 November 2011 (Fig. 3.2a). The 38 kHz echogram (Fig. 3.4) revealed the same scattering layers as in previous results and the acoustic anomalies also occurred with an increase in SSR accompanied by hypoxia (see station 6 and 7). No anomalies were detected in the scattering biota where the waters remained clean and normoxic (station 8). In the case of the station 5, the oxygen sensor registered a decrease while SSR was quite low (no water dimming). Here, the MSL was depleted but the upper limit of the DSL remained in its normal depth range. DSL depth and SSR coupling The upper limit of the DSL shown in Fig. 3.5a was markedly closer to the surface beneath the volcanic plume than in the surrounding non-affected waters. The upper 70 Chapter 3 fringe of the DSL was well above 200 m in the plume, but around 400 m outside. This pattern occurred both day and night and did not differ in magnitude with the diel cycle. Furthermore, the relationship between the depth of the DSL and the SSR followed a positive logarithmic curve, becoming shallower both during the day and night (Fig. 3.5b). It is noteworthy that a small increase in the sea surface reflectance, by about 0.3 10−3units above the turbidity level under normal conditions, was enough to raise the DSL up to 300 m below the surface. Depth (m) AMSL DSL 100 200 300 400 500 600 700 800 900 Sv (dB) −80 −75 −70 −65 −60 −55 −50 3 4 5 5 Oxygen (mL/L) 3 4 5 6 3 4 5 7 3 4 5 8 0. 0 0. 5 1. 0 1. 5 SSR (10−3 sr−1) B 21 00 03 06 09 12 Time (h) Figure 3.4: 38 kHz echogram (A) and Sea Surface Reflectance (B) on 18 November 2011 along the acoustic transects indicated in Fig. 3.2a. The color scale refers to backscattering strength (Sv). Migrant and Deep Scattering Layers (MSL and DSL) as well as the downward diel migration (∗) are indicated. Acoustic anomalies are also indicated: the MSL weakening (yellow triangles) and the elevations of the DSL (red triangles). Red lines depict the dissolved oxygen profiles established during the acoustic track. The black color in time scale refers to nighttime and white to daytime. Temporal changes in the pelagic biota During the eruptive phase, the water column was characterized by a strong thermocline at around 80-90 m depth and high deoxygenation from 80 to 170 m depth (Fig. 3.6). The first sign of the eruption on the sea surface appeared on 12 October 2011, when the SSR increased from 0.1 10−3to 0.5 10−3sr−1, reaching the highest degree of water 71 Part II. Results dimming by the end of October (0.8 10−3sr−1). Around one week later, two consecutive biological samplings were performed (Fig. 3.7). Chlorophyll awas below 0.1 mg m−3and mesozooplankton values ranged 700-950 ind m−3and 3.0-4.2 mg m−3(dry weight). The acoustic proxy for epipelagic mesozooplankton density (MVBS200 kHz) was below -67 dB while the vertical migrant micronekton (MVBS38 kHz) registered higher scattering levels, around -54 dB. Values for MVBS200 kHz in the control zone (outside the plume) did not differ significantly from those collected in the plume, while MVBS38 kHz was lower inside the plume than in the non-affected area. According to SSR, mantle-derived materials continued spilling over the sea surface, but with progressively decreasing intensity pulses until the eruption stopped in early February. During this time, small turbidity pulses were also registered within the control zone. Shortly before the end of the eruption, the concentration of in situ chlorophyll ain the volcano-affected area started to increase moderately but was still somewhat lower than in the control zone (January). Afterwards, chlorophyll ameasurements were slightly higher in the affected area, reaching an average maximum of 0.33 mg m−3during late February, when the eruption stopped. Remote sensing chlorophyll ameasurements during March in the affected area were similar to in situ adjacent measurements, but slightly increased to 0.40 mg m−3in the control zone. MVBS200 kHz also started to recover by January, registering a relative maximum backscattering (-63 dB) coinciding with the chlorophyll apeak. The same pattern was found in epipelagic mesozooplankton abundances and biomass, where average maxima were 2370 ind m−3and 5.8 mg m−3. MVBS38 kHz also increased, but the maximum average backscattering (-48 dB) was reached one month after the eruption ceased (early April). During the post-eruptive phase, both acoustic proxies revealed considerably higher backscattering in the volcano-affected zone compared with those in the control zone. It should be noted that relative peaks of all biological parameters also coincided with the breakdown of the thermocline and with normoxic conditions in the water column (See Fig. 3.6 from February on). Mesozooplankton and Micronekton composition Concerning epipelagic mesozooplankton, no significant differences (Student’s t-test) were found when comparing the relative abundances of each taxa among the sampling surveys, nor between the experimental and control areas. Their averaged relative abundances are given for the whole sampling period (Table 3.1). Copepods largely dominated the community (94%), followed by chaetognaths (3%) and other organisms with abundances well below 1%. 72 Chapter 3 Group Abundance (%) Average SD Chaetognatha 3.01 1.22 Copepoda 94.23 1.50 Euphausiids like 0.29 0.22 Gelatinous 0.65 0.26 Others 1.98 0.69 Table 3.1: Averaged mesozooplankton abundance along the sampling period. Data are shown in percentage of total abundance. The micronektonic composition (Table 3.2) corresponding to the MSL during the last survey was dominated by Lanternfishes of the family Myctophidae (70%). The family Enoploteuthidae was the most important within squids (11%), while shrimps from the family Oplophoridae were the most abundant group of decapods (8%). Other minor groups also appeared but in quite low abundances (.1%). Group Family Abundance (%) Average SD Fishes Myctophidae 71.30 2.28 Gonostomatidae 1.33 1.22 Decapods Oplophoridae 8.19 4.33 Sergestidae 1.02 0.64 Cephalopods Enoploteuthidae 11.16 9.99 Others - 7.07 1.52 Table 3.2: Averaged micronekton abundance within the MSL during the last survey. Data are shown in percentage of total abundance. Trawls are indicated as blue arrows in the map showed in Fig 3.1b. Discussion The weakening of the Migrant Scattering Layer Based on the measured parameters, we related the weakening of the MSL to low oxygen concentrations in the upper layers. However, we consider the shallow hypoxia as a tracer of perturbations from the eruption rather than as a unique factor affecting the pelagic biota. Hypoxia was not the only perturbation observed in shallow waters during the submarine eruption. Fraile-Nuez et al. [2012] observed temperature anomalies in the vicinity of the volcano (+3◦C at 75 m depth) and chemical compounds containing Fe, Cu, Cd, Pb and Al were observed at the sea surface. Santana-Casiano et al. [2013] also reported that emissions of reduced sulfur compounds promoted a decrease in both the redox potential and the concentration of dissolved oxygen. Moreover, changes in the 73 Part II. Results carbonate system contributed to the water acidification (-0.5 units at 75 m depth along the plume). The depletion of the scattering biota was evidence of the harmful effects of the volcano. By comparing the acoustic densities of the volcano-affected MSL with the neighboring non-affected zones, we observed that the former had a MVBS38 kHz that was 71 ±11% lower than that of the latter. That was partially balanced in the mesopelagic zone since the MVBS38 kHz of the DSL was 41 ±19% higher in the affected areas than in the nonaffected areas. It seems feasible that part of the normally migrant biota remained in the midwaters when the emissions covered the surface. Nevertheless, another part (∼30%) just disappeared from the ensonified volume. This disappearance could be explained by (1) horizontal migrations to find surrounding clean waters, as well as by (2) mortality caused by extreme physical-chemical perturbations. Support for the latter possibility was the occurrence of many mesopelagic species (mainly myctophids, hatchetfishes and deep-sea squids) floating dead at the surface during the strongest episodes of volcanic unrest (Esc´anez, pers. comm.). This is not surprising, because it is probable that the magnitude of the eruption did not leave scope for adaptation although deep-sea animals have a high tolerance threshold for varying oxygen [Ekau et al., 2010] and temperature conditions [Watanabe et al., 1999]. Many mesopelagic organisms tolerate hypoxia by reducing their metabolism as the consequence of lower temperatures in the deep ocean [Ekau et al., 2010], but in warmer waters, the oxygen consumption increases dramatically [Torres et al., 1979, Donnelly and Torres, 1988]. Presumably, the oxygen demands of vertical migrants during feeding activity were therefore much higher than in existing reserves in shallow waters of El Hierro Island. Besides, it has recently been documented in myctophids (main group forming the MSL) that heat shock responses under warm conditions might be triggered by the oxidative stress that occurs in normoxic waters [Lopes et al., 2013]. It thus seems likely that the natural plasticity of the migrant biota no longer worked under the atypical scenario of low oxygen and high temperature. This, along with adverse effects of ocean acidification [Fabry et al., 2008, Hall-Spencer et al., 2008] and the presence of toxic chemical compounds, suggests that both vertical and horizontal evasion would be the only means to avoid death. The elevation of the Deep Scattering Layer The presence of unusual acoustic scattering layers up to 200 m above the normal upper limit of the DSL might be interpreted both as an elevation of the DSL or as a lowering of the MSL. Since that phenomenon also occurred during daytime, when there was no migration, we are inclined to favor the former hypothesis although we do not reject the idea that during nighttime backscattering was also induced by arrested migrants. Those 74 Chapter 4 Eddy-induced variability of the deep mesopelagic biota. Alejandro Ariza, Javier Ar´ıstegui, Pablo Sangr`a, B`arbara Barcel´o-Llull and Santiago Hern´andez-Le´on (2015). In preparation. Abstract Eddies are common but hidden structures traveling through the oceans. These mesoscale features (100 km) are capable to force physical and biogeochemical gradients, providing singular ecosystems for pelagic organisms. The influence that eddies exerts over plankton and top predators is fairly well documented. However, there is a lack in knowledge at intermediate trophic levels such as micronekton, which mainly include small fish, decapods and squid. Studies with limited spatial resolution suggest that eddies may affect the abundance and the species composition of micronekton, but little is known about how these animals adjust their distribution with respect to the eddy structure. Here we combine hydrographic and acoustic in-situ measurements with satellite remote sensing to investigate, for the first time, the micronekton distribution along mesoscale features of the Canary Eddy Corridor. The three-dimensional structure of the scattering biota was analyzed by sectioning systematically an anticyclonic eddy from the surface to 1000 m depth with a 38 kHz echosounder. We observed horizontal differences in scattering layers between 700 a 900 m depth, with the most important gradients finely tuned to the eddy borders. Acoustic gradients outlined three different regions for micronekton, one inside and two outside the eddy. Assuming that these regions were composed by 81 Part II. Results the same species, the eddy structure and its surrounding waters may produce up to three-fold biomass differences in animals inhabiting between 700 and 900 m depth. Regardless of whether this variability reflected different biomass or different species, the pattern observed here suggests a high level of micronekton patchiness over the eddy field. Our results also highlight that eddies may shape the distribution of animals inhabiting down to 900 m depth, even though these structures hardly extend to 400 m depth. We hypothesized that the interaction between eddies and micronekton may occur near the surface at night, through the vertical migration that these animals conduct on a daily basis Introduction The Canarian Archipelago , acts as barrier to the southwestward flowing Canary Current. As a consequence, mesoscale eddies (10-100 km) are generated downstream the Islands, enhancing the hydrographic variability and the biological production of an otherwise oligotrophic region [Barton et al., 2004, Neuer et al., 2007]. Cyclonic and anticyclonic eddies, are recurrently spun off from the islands with a period ranging from days to weeks [Ar´ıstegui et al., 1997]. Most of the eddies drift westward forming part of an eddy corridor with life spans of at least several months [Sangr`a et al., 2007]. This ”Canary Eddy Corridor” is considered an stable oceanic system, responsible of about one fourth of the Canary Current mass transport, while accounting for a primary production similar to that of the NW Africa coastal upwelling at the same latitudinal range [Sangr`a et al., 2009]. At earlier formation stages, cyclonic eddies pump cold nutrient-rich waters into their surface cores and thus enhancing the primary production. On the contrary, anticyclonic eddies accumulate surface warm waters in their centers, deepening the mixed layer, and reducing production [Ar´ıstegui and Montero, 2005]. However, during more mature stages wind-stress curl may cause downward and upward velocities inside cyclonic and anticyclonic eddies, respectively, reversing the effect of the role of cyclones/anticyclones in eddy productivity [McGillicuddy et al., 2007]. Anticyclonic eddies can also, entrain chlorophyll-rich waters from the islands’ shelf, or from upwelling filaments, transporting them towards open-ocean [Ar´ıstegui et al., 1997]. This mechanism also concentrate and transport zooplankton, enhancing diel vertical migration (DVM), and consequently, the carbon export to deeper waters [Hern´andez-Le´on et al., 2001, Yebra et al., 2005, Landeira et al., 2010]. On the other hand, tagging and sighting studies at other regions with high mesoscale activity have proved that top predators such as tuna, seabirds, seals 82 Chapter 4 or whales seek these vortices for foraging purposes [Kai and Marsac, 2010, Woodworth et al., 2012, Bertrand et al., 2014, Cott´e et al., 2015]. All these clues indicate that eddies may catalyze energy from primary producers to the top of the food chain. However, little is known about the role of intermediate trophic levels such as micronekton [Brodeur et al., 2005]. They are mainly small fish, decapods and squid belonging to third and fourth trophic positions [Burghart, 2006, Choy et al., 2012], and which are also considered as a key component in the redistribution of energy and organic matter through the deep ocean [Hidaka et al., 2001, Davison et al., 2013, Schukat et al., 2013, Irigoien et al., 2014, Ariza et al., 2015]. Few studies based in trawl sampling suggest that mesoscale eddies may affect the species composition of pelagic fish and decapods [Brandt, 1983, Griffiths and Wadley, 1986]. Unfortunately, little is known about the mechanisms governing this variability, or how animals adjust their distribution to the eddy shape. This requires different methodological approaches able to finely resolve mesoscale structures. Low frequency echosounders proved very sensitive to micronekton layers dominating the epipelagic (0-200 m depth) and mesopelagic (200-1000 m depth) waters of the Canary Islands [Ariza et al., in prep.; Ariza et al., 2014] Mounted on moving vessels, they can successfully resolve hundred kilometers sections within hours, at vertical and horizontal resolutions of meters [Godø et al., 2014]. Therefore, they could be a powerful tool to assess biophysical interactions along eddies. Few studies have used this approach. In the Mozambique Channel (Indian Ocean), patchy fish aggregations and varying acoustic densities have been observed along eddies [Sabarros et al., 2009, B´ehagle et al., 2014]. Also at mesopelagic waters in the North Atlantic, the scattering biota peaked near eddy regions [Conte et al., 1986, Fennell and Rose, 2015]. Unfortunately, the lack of accurately georeferenced outputs prevented to finely relate the micronekton distribution to mesoscale structures. Recently, Godø et al. [2012] shed some light on this respect working on anticyclonic eddies near Iceland and Norway. Coupling accurately acoustics to physical gradients, they reported shallow scattering layers intensifying along the inner periphery, and deep ones sinking below the cores. In conjunction, sound layers acquired a characteristic ”bowl” or ”wheel shape” with increased biomasses below the vortices. With just one observation so far, the question arising is whether this phenomenon is widespread, or variable along different mesoscale systems and pelagic communities. Here we combine hydrographic and acoustic in-situ measurements with satellite remote sensing to investigate, for the first time, biophysical interactions between eddies and micronekton in the Canary Islands. The study focuses on an intrathermocline eddy (ITE), the typical anticyclonic structure for the Canary Eddy Corridor, characterized by dome-shaped isotherms above the thermocline and bowl-shaped below (Barcel´o-Llull 83 Part II. Results et al., in prep.). The three-dimensional structure of the scattering biota was analyzed by sectioning systematically the ITE from the surface to 1000 m depth with a 38 kHz echosounder. These recordings were afterwards translated to specific animal groups based on regional descriptions of acoustic layers, and also on previous reports about the vertical distribution of micronekton. Methods Remote sensing monitoring Mesoscale activity around the Canary Eddy Corridor was routinely monitored five months prior to the survey. Sea level anomaly (SLA) imagery were downloaded and examined from the archiving, validation, and interpretation of satellite oceanographic remote sensing service (AVISO), in order to find potential eddies to be investigated. On 6 June 2014, an anticyclonic eddy (ITE) just generated at Tenerife Island was detected and selected as the subject of this study. Hydrography The hydrographic sampling was carried out on board the R/V Hesp´erides from the 1th to the 20th of September 2014, with the ITE being 3-months old (mature stage) and located approximately at 26◦N and 20◦W according to merged altimeters images (Fig. 4.1). The survey comprised five legs, which were used to study further physical and biogeochemical properties of the ITE (Ar´ıstegui et al., in prep.; Barcel´o-Llull et al., in prep.). In the present study we address the legs one and three. Conductivity, temperature and depth fields were recorded using two CTDs (SeaBird 9/11-plus), one towed from the stern in a SeaSoar undulating system while the vessel was performing transects, and the other attached to a rosette of 24-10-liter Niskin bottles for vertical profiles at stations. Both CTDs were further equipped with fluorometers for chlorophyll aestimations (WetLabs ECO-FL). The SeaSoar was towed at 7-8 knots, and undulated from the surface to 400 m depth in cycles of approximately 12-15 min. This achieved an horizontal resolution of a about 3 km. The voltage readings of the CTD fluorometer were calibrated with chlorophyll aconcentrations measured from extracted pigments. For this, 500 ml of seawater were filtered through 25 mm Whatman GF/F filters using low vacuum. The filters were frozen at -20◦C before pigments were extracted in 90% acetone for 24 h in the dark at 4◦C. Chlorophyll aconcentrations (mg m−3) 84 Chapter 4 were estimated by fluorometry in a Turner Designs fluorometer calibrated with pure chlorophyll a(Sigma Chemical). During the leg one, the vessel conducted a transect starting and finishing at two cyclonic structures, and crossing in the middle the ITE that we were interested in. This was performed following the preliminary positions derived from SLA images (Fig. 4.1). In this phase, the ITE was for the first time in-situ located, as derived from temperature anomalies. The leg three consisted of nine parallel transects separated 10 nautical miles between them and disposed along the north-south axis of the eddy (Fig. 4.2). The first six transects were performed using the SeaSoar and hull-mounted sensors, but due to a malfunction of the former, the last three transects (B-D in Fig. 4.2) were completed with 400 m depth vertical casts separated 10 nautical miles one from the other. Echosounder A hull-mounted SIMRAD EK60 echosounder operating at 38 kHz was used for recording acoustic scattering layers occurring in epipelagic and mesopelagic waters. Data were stored at a 6-s ping interval with a pulse duration of 1024 µs. Considering that the vessel navigated from 7 to 8 knots during the hydrographic transects, the spatial resolution of the echosounder ranged between 22 and 25 meters. In order to present distance-based echograms, first, we removed those pings recorded during station time or at another circumstance where the vessel was not performing transects. Secondly, we calculated the distance increments between pings based on longitude and latitude coordinates. And finally, we allocated the closest pings in a monotonically increasing distance vector of 100 m resolution. No ping was included if the closest ping was at 100 m or more from a given distance point. Due to the draft of the transducer, and to prevent near-field effects [Simmonds and MacLennan, 2005], acoustic data for the first 6 meters depth were not included. In order to avoid range-increasing noise [Korneliussen, 2000], maximum depth of data used was 1000 m. Minimum detection threshold was set to -80 dB. All echograms show an upper bar with white and black colors indicating respectively whether it was day or night, and also a symbol consisting in 3 consecutive angles where the vertexes point to the recording direction. The last indication was necessary because the echograms from westward transects were exceptionally displayed from right to left in order to facilitate the georeferencing of the acoustic data. Special care must be taken with these figures (vertexes pointing left) because, although the projection is correct in spatial terms, time is inverted. This means that upward migrations look like downward migrations and vice versa. 85 Part II. Results Echograms were projected using the logarithmic unit ”Volume backscattering strength” (Sv, dB re 1 m−1). However, acoustic density comparisons between zones were conducted using the linear unit ”nautical area backscattering coefficient” (NASC, m2nmi−2). Units nomenclature and conversions were applied according to Maclennan et al. [2002]. Since we detected mesoscale variability in a scattering layer between 700 and 900 m depth, we developed an acoustic anomaly index (AAI) to quantify the magnitude of changes along transects during the leg three. First, we calculated and integrated NASC from 700 to 900 m depth. AAI was afterwards calculated as the ratio of NASC to the total averaged NASC minus one, and expressed in terms of percentage (see equation 4.1). AAI = 100 NASCi 1 nn X i=1 NASCi −1!(4.1) Prior to any echogram projection or analysis, interferences from other acoustic instruments, typically looking as vertical sticks of relative high backscattering, were removed using an algorithm which based its detection sensitivity on differences among consecutive pings and the vertical repetitions of these differences. Detection thresholds were adjusted by visualizing echograms and checking that only the interferences were removed while minimizing loss of data. Missing values were replaced by linear interpolation between side pings. Steaming noise episodes did not compromise any result since all occurred out of transect time. All acoustic data were processed using customized applications in Matlab software. Results Zonal section across the eddy field First anomalies observed with the 38kHz echosounder occurred at the eddy reconnaissance transect during the leg one (Fig. 4.1). The westward recorded echogram took approximately one day and a half, covering two upward and one downward migration events. Three distinct scattering regions were identified (Fig. 4.1C), a shallow scattering layer above 150 m depth (SSL), and two deep scattering layers in the mesopelagic zone (DSL). The first DSL was approximately between 400 and 600 m depth, presenting a relative high acoustic density (-70 to -60 dB), while the second one lied from 700 to 900 m depth, exhibiting less sound reflection (-75 to -70 dB). Regardless of whether it was day or night, acoustic scattering at 700-900 m depth enhanced inside eddies, while 86 Chapter 4 diminished between them. The enhancement of the deep layer was similar for both side cyclonic eddies and the ITE. Figure 4.1: (A) Schematic of the Canary Islands location, the Canary Current, and the Canary Eddy Corridor. (B) Sea level anomaly showing the anticyclonic eddy selected for this study at 26◦N-20◦W, and two cyclonic eddies on both sides. The black line indicates an acoustic transect from east to west. (C) 38 kHz echogram showing anomalies in scattering layers between 700 and 900 m depth. The location of these anomalies are indicated with red triangles in the upper right panel. White and black at the top of the echogram depict day and night, respectively. SR and SS stand for sunrise and sunset. Angles in a row point to the recording direction of the echogram. Systematical transects across the ITE In the leg three, transects across the ITE showed the same layout of acoustic scattering layers than in the leg one. Anomalies also concentrated between 700 and 900 m depth. The most abrupt changes within this strata occurred systematically along the ITE periphery. The distribution of subsurface chlorophyll maxima also outlined the eddy borders (Fig. 4.2A). Positive acoustic anomalies surrounded the northeast frontier, indicating higher backscattering below 700 m depth in this area (see transects B to E in Fig. 4.2). However, negative anomalies disposed outlining the southwest boundary. They were characterized by a short weakening of the layer near the border and followed by a permanent attenuation of acoustic backscattering once outside the ITE (see transects F to J in Fig. 4.2). We did not registered important anomalies inside the 87 Part II. Results vortex, where the acoustic scattering always exhibited similar density and structure. All described anomalies occurred regardless of whether it was day or night. Acoustic profiles among ITE regions In general, the 38 kHz profiles among the different regions of the ITE were quite similar except between 700 and 900 m depth (Fig. 4.3). Within this interval, southwest profiles peaked slightly deeper (800-900 m) than those in the northeast or at the ITE core (700800 m). The integrated acoustic backscattering between 700 and 900 m depth (NASC) doubled at the ITE core and tripled in the northeast periphery with respect to the southwest region. Differences described among profiles occurred both during day and night. Discusion Acoustics, what we see and what we do not see The advantage of using acoustics to evaluate pelagic fauna is the high spatio-temporal resolution. This allows quasi-synoptic views of animal structures extending hundred kilometers at scales below one meter [Godø et al., 2014]. In return, difficulties arise when translating from decibels to organisms without net catches. Therefore, groundtruthing by trawling is a prerequisite to give biological significance to sound scattering in the ocean [Davison et al., 2015]. There is extensive literature relating low frequency scattering layers to micronekton throughout the oceans. In particular, the 38 kHz constitutes an standard for the detection of small pelagic fish [Kloser et al., 2002, Kaartvedt et al., 2009, Pe˜na et al., 2014]. This frequency was recently associated to specific taxa in the Canary Islands by concurrent acoustic and net samplings (Ariza et al., in prep.). The strong deep scattering layer between 500 and 600 m depth was mainly attributed to Cyclothone braueri, a nonmigrant small fish highly abundant in mesopelagic waters. The weak layer below, which exhibited variability along the eddy, was linked either to migrant fish or decapods, or maybe both. Probably from families Myctophidae and Sergestidae, according to conclusions in Ariza et al. (in prep.), and also to previous reports of micronekton vertical distribution in the region [Badcock, 1970, Foxton, 1970b]. It does not mean, however, that the investigated eddy exclusively affected fish or decapods inhabiting between 700 and 900 m depth. The whole mesopelagic zone is inhabited by many species not responding at the insonifying frequency [Korneliussen and 88 Chapter 4 Ona, 2003, Benoit-Bird, 2009], while others are simply masked by stronger and more numerous scatterers such as Cyclothone braueri. On the contrary, the 38 kHz echogram must be regarded as a biased view, raising the question of whether other animals might be influenced by the physical gradients of eddies. Eddy interaction with deep mesopelagic animals Probably the main finding of this study is that anticyclonic eddies may shape the distribution of animals inhabiting the deep mesopelagic zone. Within the ITE, and between 700 and 900 m depth, the scattering biota exhibited distinctive features in comparison to those of surrounding waters (Fig. 4.1 and 4.2). This biota, was finely tuned to the eddy shape, with changes along the scattering layers occurring near submesoscale (<10 km). Only in the ITE and its surrounding waters, we identified three different regions, which suggest a high degree of micronekton patchiness along eddy field. After these observations, questions arise regarding the mechanisms behind this patchy distribution, or in what sense the mesopelagic communities are different across these structures. Varying scattering levels in a given layer may result from different abundances of same organisms. However, this may also reflects distinct organisms, either a change in the species assemblage, or different age structures within the same population. For instance, juvenile fish bearing gas-filled swimbladders may produce much more sound reflection than adults with atrophied swimbladders, or decapods with sizes near the wavelength of the insonifying frequency may cause higher reflection than specimens shorter or larger [Kloser et al., 2002, Korneliussen and Ona, 2003, Simmonds and MacLennan, 2005]. Unfortunately, without net sampling, it is impossible to know whether this acoustic variability reflected different densities or different organisms. If acoustic targets were the same along the surveyed area, it would imply that mesoscale structures may produce from twoto threefold higher micronekton biomass between 700 and 900 m depth (see Fig. 4.3). According to this assumption, it seems that the deep mesopelagic biota concentrated beneath eddies, no matter if cyclonic or anticyclonic. Or seem from a different viewpoint, animals may disperse across front regions. This is easily appreciated in the zonal section across the eddy field, as well as in the southermost transects along the ITE (Fig. 4.1 and 4.2F-J). However, the enhanced acoustic densities in the outer northeast part contrasts to the observations at the southwest (Fig. 4.2B-E). This might be related with the asymmetric structure of the ITE. Notice that the eddy is elliptical with its major axis oriented in the NW-SE direction (Fig. 4.2A), and according to Barcel´o-Llull et al. (in prep.), velocity fields indicates that the circulation accelerates in the southwest part, while 89 Part II. Results Figure 4.2: (A) ITE structure as derived from density anomalies at 200 m depth (contour lines). Grayscale background shows the distribution of subsurface chlorophyll, and blue-red colored bars represent acoustic anomalies at 700-900 m depth along nine transects conducted throughout the ITE. (B-J) 38 kHz echograms corresponding to these nine transects. Horizontal black lines delimit the range depth where the acoustic anomaly index in panel A was calculated. White and black at the top of the echograms depict day and night, respectively. SR and SS stand for sunrise and sunset. Angles in a row point to the recording direction of the echogram. decelerates dramatically in the northeast part, being nearly stagnant. Therefore, planktonic organisms are expected to accumulate in the northeast slow part, while they will tend to disperse in the southwest. This could increased predator-prey encounters in the northeast periphery, leading to a higher trophic efficiency and attracting micronekton. 90 Overall discussion biomass in our region (see Table 1.1). Species biomass is not a common output in deepsea studies, but other reports in the region also refer to C. warmingii as a dominant fish in the migratory layers at night according to abundance tables [Badcock, 1970, Bordes et al., 2009, Wienerroither et al., 2009]. Assuming our biomass calculations, the vertical migration of C. warmingii would imply a substantial amount of carbon exported to the ocean interior. Later, based on the same collections used by Badcock and Merrett [1976] and other samples collected aboard the RRS Discovery in the North Atlantic, Kinzer and Schulz [1985] documented other myctophid species undertaking extensive diel vertical migrations. According to their results, several Lampanyctus species also inhabited near or beyond 1000 m depth during daytime (in addition to C. warmingii and N. resplendens ). Kinzer and Schulz [1985] also confirmed the extensive migrations of these large myctophids based on the finding of shallow-living prey in their stomach contents. All this suggests that the migrant biomass entering the bathypelagic domain could be much larger than previously assumed in the context of biogeochemical oceanography. However, none of the echograms collected during the present thesis have indicated this important migration into the bathypelagic zone (see example in Fig. S1a). First, because range-increasing noise at 38 kHz makes it difficult to detect targets beyond 1000 m depth [Korneliussen, 2000] and, secondly, because although 18 kHz can see deeper, there are reasons to believe that the species involved in this migration might not be detectable at this frequency. The reasons for this, amongst other factors, could be the change of resonance with depth, atrophy of the swimbladder in large fishes, and the signal to sampling volume ratio, which at these depths could be below the detection threshold of the echosounder (see discussion in chapter 1). There is however evidence indicating that the extensive migrations documented by Badcock and Merrett [1976] were not location specific. First, Ceratoscopelus warmingii and Notoscopelus resplendens extend at least along 40◦N - 40◦S, and there are also other large bathyal lanternfish that occupy similar ecological niches around the world’s oceans [Froese and Pauly, 2014]. For instance, Burghart [2006] also found large lanternfish in the Gulf of Mexico at depths below 1000 m during daytime, together with many migrant decapods. Secondly, recordings from acoustic doppler current profilers (ADCP) at higher frequencies (67-75 kHz) have shown migratory patterns near 1200 m depth in the subtropical Pacific and Atlantic oceans [see Fig. S2; Plueddemann and Pinkel, 1989, Ochoa et al., 2013, van Haren, 2007, van Haren and Compton, 2013]. Unfortunately, without biological samples, understanding the nature of these scattering layers results almost impossible. In the case of Plueddemann and Pinkel [1989], they attributed this phenomenon to a large variety of species, from zooplankton to nekton, while other authors have assumed that the scattering was most likely caused by zooplankton. Species 97 Part III. Synthesis and further research allocation is not a trivial matter. If C. warmingii is involved, in addition to other organisms, it would mean that one of the species contributing more to migrant biomass in the subtropical northeast Atlantic would be performing one-step diel vertical migrations from the surface to the bathypelagic zone. Consequences for the active flux would be that a substantial input of carbon would be reaching bathyal waters without losses derived from trophically-interconnected migrations, such as the ”Ladder of migrations” or the ”Bucket brigade” models [Vinogradov, 1962, Ochoa et al., 2013]. Figure S2: 24-h vertical velocities (w) and echo anomalies (dl) in bathypelagic waters of the Canary Basin. Winter/spring seasons on the left and summer on the right. ”t” indicates nautical twilight, while ”s” depicts sunrise and sunset. From van Haren [2007]. Another clue supporting the argument that the active flux might be important below 1000 m depth comes from the vertical profiles of particulate organic carbon (POC). During an oceanographic survey, Alonso-Gonz´alez et al. [2009] sampled these compounds moving laterally through discrete layers in mesopelagic and bathypelagic waters of the Canary Current. Each time they detected a POC peak at 500 and 700 m depth, near the deep scattering layer, a replicate also appeared at 1200 m depth (see Figs. 2 and 6 of their study). The last signal occurred within the depth range and in the same oceanographic region where both net sampling (Fig. S1b) and ADCP recordings (Fig. S2) show migratory activity. Alonso-Gonz´alez et al. [2009] proposed several sources of POC fueling these layers, either from continental margins, or from diverse mesoscale processes. Since it seems that there is also important migratory activity near 1200 m depth, we propose diel vertical migration as another mechanism for the transfer of carbon to bathyal waters. Organic matter bypassed by interzonal migrants has been proposed in the past to explain carbon peaks in mesopelagic waters [Steinberg et al., 2000, Alonso-Gonz´alez et al., 2013]. Here, the same mechanism is proposed, but we extend its influence beyond 1000 m depth. Accordingly, biogeochemical models for the deep ocean should be revised since the active flux has so far been only considered down to the mesopelagic zone [Koppelmann and Frost, 2008, Ar´ıstegui et al., 2009, Robinson 98 Overall discussion et al., 2010, Passow and Carlson, 2012]. Based on the above, the present thesis proposes a new biogeochemical model that includes the active flux, mediated by both zooplankton and nekton, within the mesopelagic realm and beyond 1000 m depth (see Fig. S3). Figure S3: New schematic of the ocean carbon pump. Adapted from Ar´ıstegui et al. [2009] and Passow and Carlson [2012], with migratory fluxes established according to the present thesis proposals. Dissolved inorganic and organic carbon (DIC and DOC) at the surface is exported to deeper waters by physical processes (mixing), while particulate organic carbon (POC) is exported via passive fluxes (sedimentation). Once in deep waters, biological processes convert POC into suspended or dissolved carbon pools that are susceptible to lateral transport, in this way decreasing the sinking rates of particles. However, all these carbon pools are also fueled by the active flux of vertical migrants, reinforcing the passive flux with sinking fecal pellets (defecation), while releasing DIC (respiration) and DOC (excretion). Migrants are able to transport carbon into the mesopelagic and bathypelagic zones, but while the zooplankton flux into bathyal waters works through trophically-interconnected migrations, the nekton flux might also operate by direct migration. The top predators can also move carbon back to surface by feeding in the mesopelagic zone, and afterwards respiring, defecating and excreting in shallow waters. Flux out of the epipelagic zone is called the export flux (10 to 100 years for atmospheric ventilation), whereas the flux out of the mesopelagic is called the sequestration flux (100 to 1000 years). Sinking POC, zooplankton and micronekton: Towards an holistic approach The importance of micronekton in the active flux is not only a consequence of their extensive vertical migrations (section above), but also of their relative contribution to migrant biomass and particular ecophysiology. In Chapter 2 we highlighted how the migrant biomasses of zooplankton and micronekton were quite similar, while the gut flux of the latter might be more efficient due to their slower evacuation rates and fastsinking fecal pellets. All these features provide evidence that the micronekton may 99 Part III. Synthesis and further research play an important role in the biological carbon pump; however, as summarized in Table 2.3 (references therein), most research involving the active flux has been exclusively dedicated to zooplankton. The inclusion of micronekton in this work, as a contributory mechanism for the active flux, has filled gaps in our knowledge about carbon export in subtropical Atlantic waters and, it may reconcile, at least in part, current imbalances in the oceanic carbon budget. For instance, prior to the present thesis, Hern´andez-Le´on et al. [2010] predicted a carbon export mediated by migrants on the order of the gravitational flux. The micronekton flux was estimated in this study based on the mortality rates of epipelagic zooplankton. Now we estimate that migrant zooplankton and micronekton export, via respiration, about 50% of the gravitational flux measured at 150 m depth (Chapter 2). DOC and POC peaks in mesopelagic and bathypelagic waters [Ar´ıstegui et al., 2003, AlonsoGonz´alez et al., 2009] also suggest the intervention of migrants, among other mechanisms (see section above). On the other hand, global estimates of carbon export, based on ecosystem modeling, are approximately two times higher than those measured from sediment traps [Schlitzer, 2002, Falkowski et al., 2003, Usbeck et al., 2003]. Direct geochemical-based measurements are even higher [Maiti et al., 2009]. We believe that the inclusion of carbon export mediated by zooplankton and micronekton, together with the sinking POC, might reduce this imbalance. Very recent studies are raising the role of micronektonic fishes [Davison et al., 2013, Hudson et al., 2014] and decapods [Podeswa, 2012, Schukat et al., 2013] in ocean carbon export, but to our knowledge, only the work of Hidaka et al. [2001] in the equatorial west Pacific and the present thesis in the subtropical northeast Atlantic have addressed the flux of micronekton together with that of zooplankton and sinking POC. Holistic approaches encompassing all passive and active mechanisms are needed because both fluxes are interconnected, and may feedback upon each other in many ways, such as the reprocessing or bypassing of POC by interzonal migrants [Steinberg et al., 2008, Robinson et al., 2010, Alonso-Gonz´alez et al., 2013]. We therefore advocate for integrative rather than comparative studies in order to better understand the functioning of the biological carbon pump. Environmental factors affecting micronekton During the course of the present thesis we have had the opportunity to test the behavior of scattering layers under the influence of distinct environmental factors. We studied the effects under the uncommon but natural event of a submarine volcano eruption that 100 Overall discussion occurred at the island of El Hierro, and also across common oceanic structures such as mesoscale eddies. The abundance, vertical distribution and migratory behavior of the scattering biota were strongly affected by the volcanic plume (Chapter 3). Aspects that, as explained above, have important implications for the biogeochemical exchanges between the upper layers and the deep ocean. Temperature, dissolved oxygen, or light irradiance were some of the oceanographic properties altered during this event. All have been identified as being amenable to change under global warming conditions [Levitus et al., 2000, Keeling et al., 2010, Stramma et al., 2008], and also as important factors governing DVM [Dickson, 1972, Roe, 1983, Watanabe et al., 1999, Bianchi et al., 2013a]. Therefore, the acoustic anomalies observed during the volcanic unrest might be of value in predicting future changes in mesopelagic ecosystem functioning. On the other hand, common and widespread oceanic structures such as eddies are proven to efficiently affect animals inhabiting waters down to 900 m depth. The variability found in this limited sampling space suggests a high degree of patchiness within this community across the eddy field (Chapter 4). Since micronekton are involved in the redistribution of organic matter and energy between shallow and deep waters [Hidaka et al., 2001, Davison et al., 2013, Schukat et al., 2013, Irigoien et al., 2014, Ariza et al., 2015], we should therefore reconsider the role of eddies in ecological and biogeochemical processes occurring in the ocean. The factors that govern abundance, distribution and diel vertical migration at global scales are of importance due to the recent interest in developing oceanographic predictors for the functioning of the biological pump in future global warming scenarios [Bianchi et al., 2013a,b, Doney and Steinberg, 2013]. 101 Part III. Synthesis and further research Conclusions The main conclusions that arise from this thesis are: 1.- Three scattering zones have been identified associated with different mesopelagic fauna in the Canary Islands: (1) at 400-500 m depth, a resonant layer at 18 kHz mainly formed by gas-bearing migrant fishes such as Vinciguerria spp. and Lobianchia dofleini, (2) at 500-600 m depth, a dense layer at 38 kHz primarily resulting from resonance of the gas-bearing and non-migrant fish Cyclothone braueri, and (3) between 600-800 m depth, a weak signal at both 18 and 38 kHz ascribed either to migrant fish or decapods. 2.-Diverse active flux pathways have been observed connecting these mesopelagic zones with epipelagic waters. The shallower migrations, from 400-600 m depth, were moving at about 4 cm s−1, while the deeper ones, from 600-800 m depth, were moving approximately at 12 cm s−1. 3.- Zooplankton and micronekton contributions to migrant biomass are quite similar in the Canary waters. The main component that contributed to diel vertical migration within zooplankton were juvenile euphausiids, whereas micronekton were mainly dominated by fish, followed by a small contribution from adult euphausiids and decapods. 4.- Respiratory carbon fluxes from both zooplankton and micronekton accounted for 82% (range 47-166%) of the gravitational flux measured at 150 m depth in oligotrophic waters of the Canary basin, with zooplankton being the major contributor (58%) due to their higher respiration rates. However, the extensive diel vertical migrations undertaken by micronekton in comparison with those of zooplankton suggest that micronekton should be the dominant contributor to the active flux in deeper waters. 5.-Light attenuation in the water column due to varying turbidity at the sea surface strongly affects the vertical distribution of the mesopelagic biota. Extreme environmental factors in shallow waters, such as temperature, oxygen, or pH, also affect the normal functioning of diel vertical migration, shortening the nocturnal ascent while undermining organisms performing migration. 6.-Mesoscale eddies can shape the distribution of animals inhabiting depths down to 900m, even though these structures barely extend to 400 m depth. Interactions between 102 Conclusions eddies and micronekton must therefore occur near the surface at night, through diel vertical migration. 7.-Mesoscale eddies introduce a high degree of patchiness to the deep mesopelagic fauna, with changes along acoustic scattering layers finely tuned to the eddy borders. This patchiness may increase the spatial variability of biogeochemical processes involving micronekton across mesoscale systems. 103 Part III. Synthesis and further research Future lines of research According to the present findings and the literature revision conducted during the course of this thesis, three important subjects have been identified as major constraints on the assessment of diel vertical migration and its implications for ocean carbon export. These are: (1) biomass underestimation, (2) limited knowledge of ecophysiology and (3) scant monitoring of DVM patterns at long-term and global scales. Biomass underestimation of fast-swimming organisms has traditionally been of major concern in fisheries management due to the requirement for accurate estimates in order to establish adequate fishing quotas. This issue is today also of interest for biological oceanographers, since recent studies are raising the important role that micronekton play in the ocean carbon budget [Hidaka et al., 2001, Bianchi et al., 2013a, Davison et al., 2013, Schukat et al., 2013, Irigoien et al., 2014, Ariza et al., 2015]. However, although both issues are of paramount importance for ocean ecosystems assessment, much uncertainty still remains about the accuracy of different sampling procedures currently available for biomass estimates. Inter-calibration of micronekton sampling gears has been conducted only for small-sized frame trawls originally designed to sample macrozooplankton or juvenile fish, which besides biasing abundance estimates towards the smaller fraction of the micronekton, also shows order-of-magnitude differences in catch quantities [Wiebe et al., 2002, Pakhomov et al., 2010]. Large pelagic trawls are the only ones that efficiently capture the adult micronekton fraction, however there are no standard definitions regarding dimensions, mesh characteristics and sampling procedures. Standardization is not only important for comparisons between different studies, but also because existing correction factors for pelagic trawls [Koslow et al., 1997, Kloser et al., 2009, Kaartvedt et al., 2012b] are hardly applicable if sampling procedures can not be exactly reproduced. In addition to this, acoustic-based correction factors also involve considerable uncertainty since the migrant community is composed of a large variety of species with different sizes and acoustic properties. This makes it highly difficult to accurately estimate biomass [see Davison et al., 2015]. Using multifrequency instruments together with a better understanding of the acoustic properties of animals may lead to improvements in discrimination between acoustic groups, thus gaining precision in biomass estimates. The problem is that high frequencies (>100 kHz) can barely cover the epipelagic zone when the instrument is mounted on the vessel. Hence, in order to provide more reliable biomass estimates, two actions are specially recommended: First, to agree on the best performance pelagic trawl and trawling settings in order to establish a standard for micronekton sampling, similarly to what was 104 Future lines of research done in the late sixties for zooplankton sampling [UNESCO, 1968]. Secondly, major development of lowered multifrequency instruments, and implementation of backscattering models for the deep-sea fauna. This will allow a better discrimination of different acoustic groups and, therefore, more accurate biomass estimates. Ecophysiology and metabolism in migrant micronekton is a profound lack in knowledge. This is particularly evident for mesopelagic fishes since it is extremely difficult to keep them alive in captivity for sufficient time to measure physiological rates [Robison, 1973, Torres et al., 1979]. Crustaceans, on the other hand, have been subject to further study as they exhibit greater resistance during in-vivo experiments. Nevertheless, most knowledge about the physiological energetics of crustaceans is biased towards zooplankton [Ikeda and Motoda, 1978, Omori and Ikeda, 1984, Ikeda and Kirkwood, 1989, Hern´andez-Le´on and Ikeda, 2005] while metabolic budgets of deep-sea decapods are scarce [Ikeda, 2013]. As a result, it is common practice to use general fish energy budgets to calculate carbon export mediated by mesopelagic fishes [Davison et al., 2013] or adopting zooplankton metabolic rates for estimates with decapod [Schukat et al., 2013]. The most common input parameter used in metabolic budgets to calculate other physiological rates is respiration (R), a measurement which is hard to obtain on board due to the difficulties explained above. That is why the enzymatic activity of the Electron Transfer System (ETS) is widely used as a proxy for respiration [Packard, 1985, G´omez et al., 1996, Hern´andez-Le´on and G´omez, 1996]. Unfortunately, few R/ETS ratios for migrant micronekton are available in the literature. To our knowledge, there is only one ratio reported for coral fishes that has been used for mesopelagic fishes [Ikeda, 1989], and one ratio for migrant decapods of the Benguela upwelling system [Schukat et al., 2013]. Although the use of these energy budgets and R/ETS ratios can be deemed appropriate under the current lack of better solutions, it is evident that more accurate models would considerably increase the reliability of active carbon flux estimates. Thus, research lines developing specific metabolic budgets and R/ETS ratios for vertical migrant micronekton are highly recommended. This is of particular importance for mesopelagic fishes as they are the main contributors to DVM and their metabolic rates are specially unknown. Monitoring DVM patterns and migrant biomass of both zooplankton and micronekton is essential to address biogeochemical processes in the ocean. Several studies indicate that DVM is subject to change on monthly, seasonal and annual basis [van Haren, 2007, Staby et al., 2011, Wang et al., 2014], while spatial variations from regional to global scales have also been observed [Dickson, 1972, Kaartvedt et al., 1996, Bianchi et al., 2013a]. In addition to this, the vertical distributions of pelagic biota is 105 Part III. Synthesis and further research also likely to shift as a result of global climate change, although the nature of these changes is controversial [Robinson et al., 2010, Doney et al., 2012, Doney and Steinberg, 2013]. The assessment of DVM at such spatial and temporal scales requires systematic monitoring of the migrant biota that can not be approached through traditional oceanographic cruises. In this regard, it is necessary to develop predictive models of DVM depth and migrant biomass based on oceanographic parameters governing these organisms such as temperature, light irradiance, dissolved oxygen or primary production [Bianchi et al., 2013a]. These parameters can today be remotely sensed from satellites, or are available from ocean atlases. These predictive models would allow continuous monitoring of DVM at global and long-term scales. There is also an urgent need for the inclusion of echosounders and optical instruments in permanent oceanographic stations. This will help to obtain in-situ zooplankton and micronekton metrics in conjunction with other parameters routinely collected through oceanic time-series operations [Karl and Lukas, 1996, Steinberg et al., 2001]. 106 Introducci´on Por otro lado, la luz no solo gobierna la migraci´on a escala temporal, sino que su influencia es tambi´en evidente a escala espacial. La turbidez variable en la superficie del mar modula la radiaci´on lum´ınica en la columna de agua, afectando a su vez a la distribuci´on vertical de las capas de reflexi´on profunda. Esto ocurre tanto a peque˜na [Kaartvedt et al., 1996] como a gran escala [Dickson, 1972] en el oc´eano. Aparte de la luz, hay otros factores oceanogr´aficos que tambi´en determinan la distribuci´on de los migradores, como la temperatura, el ox´ıgeno disuelto o las distintas masas de agua [Fasham y Foxton, 1979, Bianchi et al., 2013a, Wang et al., 2014, Cade y Benoit-Bird, 2015]. Tambi´en se han documentado cambios en la distribuci´on de capas ac´usticas al cruzar remolinos oce´anicos [Godø et al., 2012, B´ehagle et al., 2014]. Recientemente, Bianchi et al. [2013a] modelaron la profundidad de los migradores a escala global, bas´andose en par´ametros oceanogr´aficos. La mayor´ıa de la variabilidad en el modelo se explicaba por la concentraci´on de ox´ıgeno, donde los valores m´ınimos limitaban la extensi´on en profundidad de los migradores (Fig. I3). Sin embargo, la luz presentaba una correlaci´on muy baja de acuerdo con los autores de este estudio. La mayor limitaci´on de este modelo es que se refiere a la profundidad de capas de reflexi´on detectadas con perfiladores ac´usticos de corriente (ADCP). Como hemos dicho anteriormente, otros migradores se encuentran tambi´en por encima y por debajo de estas capas a pesar de no ser detectados. Muchos de ellos est´an muy bien adaptados a las zonas m´ınimas de ox´ıgeno [Childress y Seibel, 1998, Ekau et al., 2010], adem´as de estar fuertemente influenciados por la luz [e.g., Roe, 1983, Frank y Widder, 2002, Staby y Aknes, 2011]. Por tanto, el modelo de Bianchi et al. [2013a] podr´ıa reproducir con fidelidad la profundidad de migraci´on de un grupo ac´ustico determinado, pero no ser´ıa representativo para el resto de la comunidad migrante. La conjunci´on de todos estos factores (luz, temperatura, ox´ıgeno, masas de agua y remolinos) puede resultar, por tanto, en patrones de migraci´on y distribuciones muy variadas. En resumen, la migraci´on vertical no es simplemente un movimiento vertical de peces resonantes en el oc´eano. Ahora sabemos que se trata de un mecanismo mucho m´as complejo que implica a una enorme variedad de especies, cubriendo diferentes rutas migratorias en la columna de agua, y con variadas modalidades de migraci´on a lo largo del oc´eano. Importancia de la migraci´on vertical en las redes tr´oficas marinas Mientras que el zooplancton migrador se alimenta fundamentalmente de fitoplancton y de microzooplancton, alternando entre el segundo y tercer nivel tr´ofico [Vinogradov, 1962, Wilson et al., 2010], la mayor´ıa del micronecton es zooplanct´ıvoro, ocupando la tercera posici´on en las redes tr´oficas marinas [Kozlov, 1995, Burghart et al., 2010, Choy 113 Part IV. Resumen en Espa˜nol (Spanish summary) et al., 2012]. De acuerdo con esto, los migradores interzonales pueden ser considerados como consumidores de primer y de segundo orden. Esto supone que la producci´on primaria en aguas someras es transformada en biomasa mesopel´agica, como mucho, a trav´es de dos niveles intermedios. Una v´ıa tr´ofica relativamente corta que se traduce en una eficiente tranferencia de energ´ıa desde la superficie hasta el oc´eano profundo (Fig. I4). De hecho, estimaciones recientes de la biomasa de peces mesopel´agicos han puesto de manifiesto que la eficiencia de transferencia entre los productores primarios en superficie y la fauna profunda es m´as alta de lo que se hab´ıa asumido tradicionalmente en los ecosistemas oligotr´oficos [Davison et al., 2013, Irigoien et al., 2014]. Figura I4: Biomasa de peces mesopel´agicos en funci´on de la producci´on primaria. Los puntos negros son estimaciones ac´ustica de biomasa in-situ, mientras que la l´ınea roja representa la biomasa modelada asumiendo una eficiencia de transferencia de 0.1 y considerando que el 90 % de la producci´on primaria se incorpora en las redes tr´oficas. Extra´ıdo de Irigoien et al. [2014]. Sin embargo, no toda la producci´on biol´ogica dirigida por los migradores verticales acaba debajo de la zona euf´otica. Aparte de los depredadores profundos como peces [Choy et al., 2013] y calamares [Passarella y Hopkins, 1991] mesopel´agicos, los migradores tambi´en son predados por muchos animales que viven en la superficie del oc´eano, los cuales o bien se sumergen en la zona mesopel´agica para comer, o bien esperan el ascenso nocturno para alimentarse de ellos en superficie. Entre los depredadores de buceo profundo hay muchos mam´ıferos marinos [Santos et al., 2001] y varias especies de t´unidos [Matsumoto et al., 2013], mientras que los depredadores superficiales m´as comunes son peque˜nos peces pel´agicos [Cabral y Murta, 2002], delfines [Pusineri et al., 2007], peces espada y atunes [Potier et al., 2007]. De hecho, los migradores deben afrontar un riesgo de mortalidad relativamente alto en las aguas superficiales dado que es all´ı donde aumentan su movilidad durante el periodo alimenticio, siendo por tanto m´as f´acilmente localizados por sus depredadores. En resumen, los migradores interzonales juegan un papel fundamental en los ecosistemas pel´agicos no solo porque ocupan una posici´on relevante en las redes tr´oficas, sino porque 114 Introducci´on su naturaleza migradora los convierte en un aporte alimenticio fundamental tanto para la zona epipel´agica como para la mesopel´agica. De hecho, las interacciones tr´oficas sugieren que los migradores son igualmente importantes para conducir la producci´on primaria al oc´eano profundo [Irigoien et al., 2014], as´ı como para sustentar la actividad pesquera a escala global [Pauly y Christensen, 1995, Lam y Pauly, 2005]. Relaci´on con el ciclo del carbono en el oc´eano y con el cambio clim´atico La bomba oce´anica de carbono se refiere al conjunto de procesos fisiol´ogicos, ecol´ogicos y f´ısicos mediante los cuales el di´oxido de carbono atmosf´erico (CO2) es secuestrado en el oc´eano profundo (Fig. I5). El proceso de secuestro comienza en superficie con la fijaci´on del carbono inorg´anico mediante fotos´ıntesis (ver ecuaci´on abajo) y su posterior transformaci´on mediante procesos tr´oficos en diferentes formas de carbono org´anico. Bien formando parte de organismos vivos, o como materia org´anica inerte en la columna de agua. Mediante este proceso, los organismos fotosint´eticos desplazan el equilibrio del sistema del carbonato en el mar, acelerando de este modo la difusi´on del CO2de la atm´osfera al oc´eano [Millero, 1995]. Llegados a este punto, el carbono org´anico puede ser remineralizado otra vez mediante la respiraci´on de consumidores epipel´agicos o por la actividad microbiana [del Giorgio y Duarte, 2002]. Sin embargo, tambi´en puede ser exportado hacia el interior del oc´eano por tres mecanismos: (1) mediante la din´amica del oc´eano, (2) por gravedad, o (3) intermediado por el proceso de migraci´on vertical. CO2+ H2O respiraci´on  fotos´ıntesis CH2O+O2 El primer mecanismo se refiere al carbono org´anico e inorg´anico disuelto (DOC, DIC) que se exporta mediante procesos f´ısicos, como la mezcla convectiva [Ar´ıstegui et al., 2003], el hundimiento de masas de agua [Sarmiento et al., 2004], o la difusi´on a trav´es de isopicnas [Arcos-Pulido et al., 2014]. El segundo mecanismo, conocido como ”flujo pasivo” o ”gravitacional”, ocurre con la formaci´on de agregados de carbono org´anico particulado (POC) con tendencia a hundirse [Fowler y Knauer, 1986]. En el ´ultimo mecanismo, conocido como ”flujo activo” o ”migratorio”, el carbono org´anico viaja formando parte de los tejidos y del contenido digestivo de los migradores verticales, el cual es liberado posteriormente en aguas profundas mediante los procesos de respiraci´on [Longhurst et al., 1990], defecaci´on [Steinberg et al., 2000], excreci´on [Turner, 2002] y mortalidad [Zhang y Dam, 1997]. Cuando la exportaci´on de carbono es exclusivamente dirigida mediante procesos f´ısicos hablamos de la ”bomba f´ısica”, mientras que al flujo pasivo y activo se le conoce como la ”bomba biol´ogica”. 115 Part IV. Resumen en Espa˜nol (Spanish summary) Comprender los procesos que determinan el equilibrio del CO2entre la atm´osfera y el oc´eano no es un asunto trivial. Los oc´eanos almacenan alrededor de 50 veces m´as carbono que la atm´osfera, lo que implica que peque˜nos cambios en el ciclo oce´anico del carbono pueden tener consecuencias atmosf´ericas de gran impacto. Esto adquiere a´un m´as importancia si consideramos que el CO2es el principal gas responsable del actual escenario de calentamiento global, y que adem´as se espera que su presi´on parcial en la atm´osfera se duplique para finales del presente siglo [IPCC, 2014]. Adem´as, la bomba oce´anica de carbono no solo juega un papel clave en el cambio clim´atico, sino que tambi´en es susceptible de verse alterada en futuros escenarios con altos niveles de CO2atmosf´erico, aunque la naturaleza de los cambios es a´un un controvertido asunto de debate [Robinson et al., 2010, Doney et al., 2012]. Aproximadamente dos tercios del flujo vertical de carbono en el oc´eano se debe a la bomba biol´ogica, mientras que el resto es debido a la bomba f´ısica [Passow y Carlson, 1912]. En consecuencia, en las dos ´ultimas d´ecadas, los programas internacionales que investigaban el papel del oc´eano en el cambio clim´atico (JGOFS, GLOBEC, IMBER) se han centrado en el estudio de los procesos biol´ogicos involucrados en el secuestro de carbono [Steinberg et al., 2001, Weingartner et al., 2002]. Sin embargo, mientras que el flujo pasivo ha sido objeto de mayor atenci´on, el papel de los migradores ha sido pobremente considerado por aquellos que estudiaban los balances del carbono en el oc´eano. Las estimas actuales indican que el zooplancton migrador puede estar exportando hacia la zona mesopel´agica aproximadamente entre el 10 y el 50 % del flujo pasivo en las aguas subtropicales [Steinberg et al., 2000, Hern´andez-Le´on et al., 2001, Steinberg et al., 2008]. En consecuencia, los ´ultimos estudios est´an comenzando a considerar este mecanismo de exportaci´on en los modelos biogeogu´ımicos conceptuales [Ar´ıstegui et al., 2009, Robinson et al., 2010, Passow y Carlson, 2012]. Pese a ello, su contribuci´on raramente es considerada en los c´omputos globales. Si sumamos los flujos de carbono mediados por el zooplancton y los debidos al hundimiento de las part´ıculas, el carbono exportado resultante continua siendo menor que las estimaciones globales que se han realizado mediante modelos ecol´ogicos [Schlitzer, 2002, Falkowski et al., 2003, Usbeck et al., 2003]. Las discrepancias tambi´en son evidentes debajo del dominio mesopel´agico, donde tanto los niveles de carbono org´anico, como la demanda microbiana de carbono no pueden sustentarse solo mediante el flujo gravitacional [Baltar et al., 2009]. Todos estos desequilibrios han sido justificados por errores en las medidas de flujo pasivo [Buesseler et al., 2007], por no considerar las entradas de carbono mediante transporte lateral [AlonsoGonz´alez et al., 2009], y recientemente, por no incluir en los c´alculos los aportes de 116 Introducci´on Figura I5: Esquema de la bomba biol´ogica de carbono. N´otese que el flujo activo no es considerado por debajo de los 1000 m de profundidad, mientras que el micronecton tampoco es representado en el proceso de migraci´on vertical, solamente el zooplancton. Extra´ıdo de Passow y Carlson [2012]. carbono transportados por el zooplancton migrador [Steinberg et al., 2008]. Sin embargo, el carbono exportado por el micronecton nunca ha sido considerado como una opci´on (Fig I5). Se sabe que el micronecton realiza migraciones verticles, y por tanto, que est´a involucrado en el flujo activo, desde las primeras descripciones faun´ısticas de las capas migrantes de reflexi´on ac´ustica en el oc´eano [Tucker, 1951, Hersey y Backus, 1954, Barham, 1966]. No ha sido pues el desconocimiento lo que ha mantenido al micronecton fuera del punto de mira de la oceanograf´ıa biogeoqu´ımica. Lo cierto es que las dificultades que conlleva su muestreo es probablemente la raz´on por la que el micronecton ha sido exclu´ıdo de los c´omputos de carbono en el oc´eano. Esta comunidad posee mucha m´as capacidad natatoria que el zooplancton, por lo que se necesitan redes mayores y m´as caras que requieren mucho tiempo de maniobra para muestrear adecuadamente [Koslow et al., 1997, Pakhomov et al., 2010, Kaartvedt et al., 2012b]. Sin embargo, precisamente por su alta movilidad, el micronecton es capaz de realizar migraciones de gran magnitud, incluso m´as all´a de los 1000 m de profundidad [Badcock y Merret, 1976, Kinzer y Schulz, 1985, Burghart, 2006]. Esto convierte potencialmente al micronecton migrador en un mecanismo altamente eficiente para el secuestro de carbono en el oc´eano profundo. 117 Part IV. Resumen en Espa˜nol (Spanish summary) Para nuestro conocimiento, el ´unico trabajo que combina el flujo activo del zooplancton y del micronecton fue realizado por Hidaka et al. [2001] en el Pac´ıfico oeste ecuatorial, sus estimaciones se duplicaron cuando incluy´o a ambos componentes migratorios. En el Atl´antico nordeste subtropical, Hern´andez-Le´on et al. [2010] se˜nal´o al micronecton como un importante componente que faltaba en la bomba biol´ogica, bas´andose en la tasas de mortalidad que esta comunidad causaba sobre el zooplancton. Recientemente se han publicado otros estudios sobre la contribuci´on de los peces [Davison et al., 2013, Hudson et al., 2014] y los dec´apodos [Schukat et al., 2013] a la exportaci´on de carbono, en el Pac´ıfico nordeste, al norte de la Dorsal Atl´antica, y en el afloramiento de Benguela. Desafortunadamente, las pocas estimas existentes difieren ´ordenes de magnitud entre ellas, dependiendo del grupo analizado, de la regi´on oceanogr´afica y del dispositivo de muestreo usado. Lo ´ultimo, siendo probablemente la mayor fuente de variabilidad debido a la incertidumbre que existe acerca de las eficiencias de captura de las redes [Pakhomov et al., 2010]. En este aspecto, las estimaciones de zooplancton est´an m´as consolidadas ya que existen muchos m´as estudios disponibles, y a que las medidas est´an basadas en procedimientos est´andar m´as precisos [UNESCO, 1968]. Adem´as, la mayor´ıa de las estimaciones de flujo activo se refieren a la exportaci´on de carbono por debajo de la zona euf´otica (<150 o 200 m de profundidad), mientras que muy poco se sabe acerca de la magnitud y la extensi´on de este transporte por debajo de esa cota. Esto ´ultimo ser´ıa de especial inter´es en el caso del micronecton ya que esta comunidad puede cubrir mayores rangos de migraci´on en comparaci´on con el zooplancton, incrementando de este modo la eficiencia de la bomba biol´ogica. Por tanto, la evaluaci´on de la exportaci´on del carbono en el oc´eano requiere una mayor investigaci´on del proceso de migraci´on vertical, prestando especial atenci´on a la contribuci´on del micronecton a lo largo de la regi´on mesopel´agica y batipel´agica. De no ser as´ı, podr´ıamos estar ignorando a uno de los mayores componentes de la bomba biol´ogica de carbono. 118 Objetivos y planteamiento de la investigaci´on Objetivos y planteamiento de la investigaci´on La evaluaci´on eficiente del flujo activo de carbono implica conocer la composici´on de las capas migrantes de reflexi´on ac´ustica en una regi´on determinada, as´ı como la extensi´on y la magnitud de la exportaci´on de carbono que realiza cada componente migrador. Sin embargo, se sabe muy poco de la biota ac´ustica mesopel´agica en el Atl´antico nordeste subtropical. Casi toda la investigaci´on concerniente al flujo activo se ha centrado fundamentalmente en la exportaci´on del zooplancton y por debajo de la capa f´otica. El objetivo de esta tesis es investigar el papel de la comunidad micronect´onica en la migraci´on vertical y en el flujo de carbono en el Atl´antico nordeste subtropical, centr´andonos en su composici´on, los factores ambientales que gobiernan su distribuci´on, as´ı como en la magnitud y la extensi´on de las migraciones a lo largo de las zonas mesopel´agica y batipel´agica. Conforme a esto, los objetivos espec´ıficos de este trabajo pretenden dar respuesta a las siguientes preguntas: ¿Cu´al es la composici´on faun´ıstica de las capas de reflexi´on ac´ustica que se observan en el Atl´antico nordeste subtropical y que patrones de migraci´on siguen? Cap´ıtulo 1 Para responder a esta pregunta describimos los fen´omenos ac´usticos observados en aguas superficiales y mesopel´agicas de las Islas Canarias mediante la combinaci´on de registros ac´usticos con frecuencias de 18 y 38 kHz, y tambi´en con muestreo de redes en differentes profundidades a lo largo del d´ıa y la noche. ¿Cu´al es la contribuci´on del zooplancton y del micronecton a la biomasa migrante y a la exportaci´on de carbono en el Atl´antico nordeste subtropical? Cap´ıtulo 2 Para responder a esta cuesti´on medimos simult´aneamente el flujo pasivo y activo a lo largo de varias campa˜nas de muestreo en aguas oce´anicas al norte de la isla de Gran Canaria. La biomasa migrante del zooplancton y del micronecton fue estimada mediante el uso de una nueva red rectangular de arrastre, mientras que la exportaci´on de carbono fue estimada a partir de las tasas de respiraci´on medidas en especies migradoras dominantes. ¿De qu´e modo las perturbaciones ambientales afectan al proceso de migraci´on vertical y a la fauna mesopel´agica? Cap´ıtulo 3 Esta cuesti´on fue abordada gracias a un estudio de oportunidad acontecido durante la presente tesis: La erupci´on volc´anica submarina de la Isla de El Hierro provoc´o alteraciones en el r´egimen lum´ınico del mar, en la temperatura y en el ox´ıgeno disuelto, 119 Part IV. Resumen en Espa˜nol (Spanish summary) anomal´ıas que produjeron cambios en el ecosistema pel´agico. Las respuestas de la biota migrante fueron estudiadas mediante muestreo ac´ustico y de redes. ¿Qu´e efecto causan los remolinos oce´anicos sobre la fauna mesopel´agica? Cap´ıtulo 4 Combinando medidas hidrogr´aficas y ac´usticas in-situ con par´ametros de sat´elite se ha podido investigar, por primera vez, las interacciones entre los remolinos y el micronecton en las Islas Canarias. Se analiz´o la estructura tridimensional de la fauna mesopel´agica seccionando sistem´aticamente un remolino anticicl´onico, desde superficie hasta 1000 m de profundidad, con una ecosonda de 38 kHz. ¿Cu´al es el rol del micronecton en la exportaci´on de carbono a lo largo de la zona mesopel´agica y m´as all´a de los 1000 m de profundidad? Discusi´on general Bas´andonos en los resultados de la presente tesis, as´ı como revisando las distribuciones verticales del micronecton en la regi´on, discutimos acerca de la contribuci´on relativa del micronecton a la exportaci´on de carbono a lo largo de la zona mesopel´agica y m´as all´a de los 1000 m de profundidad. 120 Metodolog´ıa Metodolog´ıa Con el fin de lograr los objetivos planteados, durante la presente tesis se recurrieron a diversos procedimientos metodol´ogicos. A continuaci´on describimos en t´erminos generales las t´ecnicas usadas: Muestreo ac´ustico El uso de ecosondas cient´ıficas para la observaci´on de las capas de reflexi´on ac´ustica en el oc´eano ha sido una de las t´ecnicas clave para el estudio de la distribuci´on, densidad y comportamiento de la biota pel´agica. Durante esta tesis se han usado ecosondas EK60 SIMRAD de haz dividido en dos configuraciones seg´un la campa˜na oceanogr´afica: con los transductores (encargados de la transmisi´on y recepci´on de la se˜nal ac´ustica) instalados en el casco de los buques de investigaci´on, o con transductores sumergidos en el agua colgando de un cabo, en el caso de embarcaciones menores no provistas de instalaci´on ac´ustica. Se han usado frecuencias de 18, 38, 120 y 200 kHz en los diferentes estudios. El uso de la multifrecuencia persigue la discriminaci´on de los diferentes objetivos ac´usticos seg´un su tama˜no. Esto se basa en la longitud de onda (λ) de cada frecuencia, que determina el tama˜no m´ınimo que el objetivo ac´ustico debe tener para poder ser detectado. Las frecuencias bajas poseen mayor longitud de onda que las altas (e.g., λ18 kHz ∼80 mm; λ200 kHz ∼8 mm), de modo que las primeras se usan para estudiar organismos mayores normalmente pertenecientes al necton, y las segundas para los organismos menores del plancton. Tambi´en se han usado otras propiedades ac´usticas para diferenciar organismos, como puede ser la resonancia de estructuras gaseosas como la vejiga natatoria de los peces, que son capaces de producir ecos muy intensos. Adem´as, la forma de los registros ac´usticos (formando bancos o capas), la intensidad del eco recibido en cada frecuencia, o la distribuci´on vertical tambi´en se han usado como indicativos para la identificaci´on de los grupos animales. Ver Simmonds y MacLennan [2005] para m´as informaci´on acerca de las t´ecnicas de idetificaci´on en ac´ustica. Por ´ultimo, la composici´on de las capas de reflexi´on ac´ustica era comprobada mediante muestreo directo con redes de plancton y de necton (ver siguiente secci´on). Una vez interpretados los distintos grupos ac´usticos se proced´ıa a estudiar las abundancias de cada grupo animal, su distribuci´on y comportamiento migratorio. Para las abundancias usamos el volumen de eco reflejado (Sv) como indicador de la densidad relativa de animales. La distribuci´on de la biota ac´ustica en funci´on de par´ametros oceanogr´aficos como la turbidez en superficie o perfiles verticales de temperatura, ox´ıgeno 121 Part IV. Resumen en Espa˜nol (Spanish summary) y clorofila, se realizaba mediante la combinaci´on de los datos ac´usticos con mediciones realizadas por sat´elite o por diferentes instrumentos hidrogr´aficos presentes en los buques de investigaci´on. El comportamiento migratorio diario se estudiaba mediante la proyecci´on de ecogramas en escala temporal de 24 horas, calculando as´ı la velocidad de migraci´on y observando la sincronizaci´on de los moviemientos verticales en funci´on del amanecer y anochecer. El proceso de filtrado e interpretaci´on de datos, as´ı como el c´alculo de densidades de los diferentes grupos ac´usticos se realiz´o usando el programa comercial LSSS. La proyecci´on de ecogramas, as´ı como la combinaci´on de los datos ac´usticos con datos satelitales e hidrogr´aficos, o el c´alculo de velocidades de migraci´on se ha realizado con diversas aplicaciones desarrolladas para estos fines en lenguaje de programaci´on MATLAB. Muestreo biol´ogico El muestreo biol´ogico se refiere a los procedimientos de captura, conservaci´on, procesado e identificaci´on de las muestras de zooplancton y de micronecton durante la presente tesis. Las muestras de zooplancton eran obtenidas mediante pescas verticales desde 200 m de profundidad hasta la superficie, ascendiendo a una velocidad de 50 m por minuto. El modelo de red usada fue la WP-2 [UNESCO, 1968], con una luz de malla de 100 µm, y que est´a indicada para el muestreo de mesozooplancton. Con el fin de obtener datos de abundancia estandarizados por metro c´ubico, el volumen de agua filtrado por la red era calculado mediante un medidor de flujo entrante TSK instalado en la boca de la red. Las muestras obtenidas eran fijadas inmediatamente en formaldeh´ıdo tamponado al 4 % en agua de mar y eran almacenadas en oscuridad hasta su posterior procesamiento. Una vez en el laboratorio, las muestras eran digitalizadas mediante esc´aner a una resoluci´on de 1200 puntos por pulgada y los organismos eran identificados, contados y medidos usando el programa de procesamiento de im´agenes Zooimage [Grosjean y Denis, 2007]. Los grupos taxon´omicos eran identificados gracias a una sesi´on manual de aprendizaje del programa en la que se ingresaban im´agenes ya identificadas de organismos t´ıpicos de la regi´on, logrando un margen de error de identificaci´on menor al 5 %. El ´area de cada individuo era posteriormente transformada a peso seco mediante las ecuaciones dadas por Hern´andez-Le´on y Montero [2006], as´ı como por Lehette y Hern´andez-Le´on [2009]. Las muestras de micronecton fueron colectadas mediante arrastres oblicuos por popa con dos tipos de redes seg´un el estudio: (1) una red de marco modelo MOHT [Oozeki 122