The use of AARS activity as a proxy for zooplankton and ichthyoplankton growth rates

Tesis Doctoral The use of AARS activity as a proxy for zooplankton and ichthyoplankton growth rates Inmaculada Herrera Rivero Las Palmas de Gran Canaria 2014 Anexo I D. Jose Manuel Vergara Martín SECRETARIO DEL DEPARTAMENTO DE BIOLOGÍA DE LA UNIVERSIDAD DE LAS PALMAS DE GRAN CANARIA, CERTIFICA, Que el Consejo de Doctores del Departamento en su sesión extraordinaria tomó el acuerdo de dar el consentimiento para su tramitación, a la tesis doctoral titulada “The use of AARS activity as a proxy for zooplankton and ichthyoplankton growth rates” (Uso de la actividad AARS como índice de crecimiento para zooplancton e ictioplancton) presentada por la doctoranda Dña. Inmaculada Herrera Rivero y dirigida por los Doctores D. Santiago Hernández-León y Dña. Lidia Yebra Mora. Y para que así conste, y a efectos de lo previsto en el Artº 73.2 del Reglamento de Estudios de Doctorado de esta Universidad, firmo la presente en Las Palmas de Gran Canaria, a 13 de Junio de dos mil catorce. Anexo II Programa de Doctorado en Oceanografía Bienio 2006/2008 con Mención de Calidad de la ANECA. Título de la tesis: “The use of AARS activity as a proxy for zooplankton and ichthyoplankton growth rates” (Uso de la actividad AARS como índice de crecimiento para zooplancton e ictioplancton). Tesis Doctoral presentada por Dña. Inmaculada Herrera Rivero para obtener el grado de Doctor por la Universidad de Las Palmas de Gran Canaria. Dirigida por Dr. D. Santiago Hernández León Dra. Dña. Lidia Yebra Mora El/la Director/a El/la Co-Director/a El/la Doctorando/a ! A mis padres A la vida XVI Resumen El zooplancton tiene un papel clave en el medio marino y en los flujos biogeoquímicos. Estos organismos tienen una posición central en el ecosistema marino ya que ejercen parcialmente un control sobre los productores primarios y son alimento de especies de interés comercial. La variabilidad en la distribución, producción y crecimiento de las comunidades y poblaciones de zooplancton se ven afectadas por cambios en el medio marino. Por tanto, el cambio climático puede impactar sobre el ecosistema marino a través de cambios en el zooplancton. Dada la necesidad de entender la variabilidad en la producción del zooplancton como respuesta a cambios ambientales en el ecosistema marino, en esta tesis, se ha validado la actividad de las enzimas aminoacil-ARNt sintetasas como índice de crecimiento en los primeros estadios del zooplancton. Esto nos ha permitido estudiar el crecimiento de la comunidad planctónica en el medio marino, tanto en superficie como en aguas profundas. Asimismo, hicimos una revisión de todos los estudios publicados que relacionan el crecimiento y la actividad AARS, con el fin de ensayar la posibilidad de obtener una ecuación global que permita inferir la tasa de crecimiento somático de las comunidades planctónicas a partir de su actividad AARS. Los resultados de esta tesis contribuyen al avance del uso de la actividad AARS como índice de crecimiento para zooplancton e ictioplancton. XVII Thesis Preview This thesis entitled “The use of AARS activity as a proxy for zooplankton and ichthyoplankton growth rates” compiles different studies carried out in the frame of the research projects Lucifer (CTM2008-03538/MAR) and Procomex (CONACyT #200662152). These projects were granted to Dr. Santiago Hernández León and Dr. Jaime FärberLorda respectively. The present study has been co-supervised by Dr. Santiago Hernández León (Universidad de Las Palmas de Gran Canaria) and Dr. Lidia Yebra Mora (Instituto Español de Oceanografía). This Thesis was developed mainly in English to apply for the European Doctor Mention (BOULPGC. Art.1 Chap.4, November 5th 2008). The general structure begins with an Introduction, followed by Objectives, Original Scientific Contributions, Results, General Discussion and Conclusions, to end with Future Research. In addition, a Spanish section is included, as required by the PhD Thesis Regulations from the University of Las Palmas de Gran Canaria (BOULPGC. Art.2 Chap.1, November 5th 2008). XVIII Presentación de la tesis La presente tesis titulada “Uso de la actividad AARS como índice de crecimiento para zooplancton e ictioplancton”, resulta de la recopilación de una serie de trabajos encuadrados dentro de los proyectos de investigación Lucifer (CTM2008-03538/MAR) y Procomex (CONACyT #2006-62152) dirigidos por los doctores Santiago Hernández León y Jaime Färber-Lorda respectivamente. El estudio que aquí se presenta ha sido codirigido por el Dr. Santiago Hernández León (Universidad de Las Palmas de Gran Canaria) y por la Dra. Lidia Yebra Mora (Instituto Español de Oceanografía). Esta tesis se ha desarrollado mayoritariamente en inglés con el fin de poder optar a la Mención Europea del Título de Doctor de acuerdo a la normativa de la Universidad de Las Palmas de Gran Canaria (BOULPGC. Art.1 Cap. 4, 5 de noviembre 2008). Además, sigue la estructura exigida por este Reglamento: Introducción, Objetivos, Contribuciones científicas originales realizadas, Resultados, Discusión general, Conclusiones y Futuras Líneas de Investigación. También se presenta una sección en castellano, requerida por el Reglamento de Elaboración, Tribunal, Defensa y Evaluación de Tesis Doctorales de la Universidad de Las Palmas de Gran Canaria (BOULPGC. Art.1 Cap. 4, 5 de noviembre 2008). XIX Contents/ Índice Aknowledgements/ Agradecimientos XI Abstract/ Resumen XV Thesis preview/ Presentación de la tesis XVII I. Introduction 1 Objectives and Outline of this Thesis 13 Original Scientific Contributions 15 II. Results 17 Chapter 1 Effect of temperature and food concentration on Paracartia grani nauplii growth and protein synthesis rates. 19 Chapter 2 Aminoacyl-tRNA synthetases (AARS) activity as an index of Atlantic herring (Clupea harengus) larvae growth. 49 Chapter 3 The effect of a strong warm year on subtropical mesozooplankton biomass and metabolism. 75 Chapter 4 Potential grazing, respiration and growth of Euphausia distinguenda in relation to the oxygen minimum zone at the Eastern Tropical Pacific off Mexico. 101 XIX Chapter 5 The use of aminoacyl-tRNA synthetases (AARS) activity as an index of zooplankton growth. 123 III. General Discussion 147 Conclusions 157 Future Research 159 IV. Spanish Summary/ Resumen en Español 161 Introducción 163 Objetivos de la Tesis 175 Contribuciones Científicas Originales 176 Planteamiento y Metodología 177 Resultados 183 Discusión 195 Conclusiones 207 Futuras Líneas de Investigación 209 V. References/ Referencias 211 ! I. Introduction ! I. Introduction! ! 3 Introduction Zooplankton are small organisms that inhabit the water column and are transported by water masses. These organisms can be divided according to their size (Sieburth et al., 1978). Hence, microzooplankton comprises very diverse organisms between 0.02 and 0.2 mm, such as ciliates, copepod nauplii or meroplanktonic larvae. Mesozooplankton, between 0.2 and 20 mm in length, include copepods, cladocerans and appendicularians among others; and macrozooplankton, whose organisms are larger than 20 mm, correspond mainly to fish larvae, decapods or euphausiacea. Zooplanktonic organisms are also classified according to their life cycle, being known as holoplankton, those that are planktonic during their entire life cycle (e.g. copepods, ostracods, cladocerans) (Longhurst, 1985), and meroplankton, those organisms that are planktonic only for a part of their life cycle, usually eggs and larvae, such as fish, echinoderms, cnidarians or molluscs (Raymont, 1983). Plankton studies are of great importance for humans because they are the base of the marine trophic webs. Zooplankton have a central role in the marine ecosystem, (1) exercising a partial control on primary producers, (2) being prey for higher trophic levels, and (3) representing an important link between the classic trophic chain and the microbial loop. Moreover, zooplankton (4) export particulate organic matter (POM), used by bacteria, and (5) excrete nutrients that can be recycled by phytoplankton (Fig. 1). In addition, zooplankton include all the larval stages of nektonic and benthic organisms. Therefore, the development of the exploitable marine resources also depends on the variability of zooplankton production. I. Introduction! ! 4 Figure 1. The importance of zooplankton in the marine ecosystem The variability of the planktonic community is determined by abiotic and biotic factors. The former factors affect at different scales (Dickey and Bidigare, 2005), from the global scale to mesoand microscale. Physical forcing (Bonnet et al., 2005) including mesoscale structures like eddies and fronts that concentrate biomass (Yebra et al., 2005), enhance metabolism (Hernández-León et al., 2002; Landry et al., 2008) and vertical migration (Isla et al., 2004), and increase the active flux mediated by migrant zooplankton to deep waters (Yebra et al., 2005) promote this variability. At microscale, turbulence affects the predator-prey encounter rates, and therefore feeding rates (Kiørboe and Saiz, 1995; Visser et al., 2009). Also temperature (Parrilla et al., 1994; Drinkwater, 2005), salinity (Hirst and Lucas, 1998), light (Hernández-León, 2008; Hernández-León et al., 2001, 2004, 2010), I. Introduction! ! 5 nutrients (Duarte et al., 2006), oxygen concentration (Teuber et al., 2013) and carbon dioxide (González-Dávila et al., 2006) affect directly to the planktonic community. The biomass of the planktonic community is also affected by biotic factors, which regulate their organisms metabolism. This is influenced by food distribution and abundance (phytoand microplankton), as it will determine their growth (Vidal, 1980; Hirst et al., 2003; Lin et al., 2013). Besides, biomass is also affected by mortality by predation (Hirst and Kiørboe, 2002; Runge et al., 2004; Maar et al., 2014). All these factors determine the population dynamics and the community structure, which also affect the carbon fluxes mediated by zooplankton in the ocean. Given the central position of zooplankton in the trophic web, the study of zooplankton production is essential to evaluate the fluxes of energy and matter through pelagic ecosystems. The assessment of zooplankton production will increase our understanding and capacity to develop models coupling physical and biological variables with the goal of evaluating the impacts of zooplankton population dynamics over higher trophic levels. In this sense, zooplankton production is defined as: P = (B1-B0)+M (eq.1) where P is the zooplankton production, B1 and B0 are the biomass in time 1 and 0 respectively, and M is the mortality. Thus, biomass at a given time is: B1 = B0 + (B0·g) – (B0·m) (eq.2) being g and m the growth and the mortality rates, respectively. There are several direct methods to assess zooplankton growth and production estimations (Omori and Ikeda, 1984; Runge and Roff, 2000). Among these methods the most common is the one developed by Heinle (1966) who, following the growth concept, measured the variations of weight over time. Another method used for in situ growth ! I. Introduction! ! 13 Objectives and Outline of this Thesis The thesis has been structured following the normative for a PhD thesis as a compendium of publications. The main objective of the present thesis was to improve our knowledge on the use of AARS activity as a proxy for zooplankton and ichthyoplankton growth rates conducting laboratory and field studies. In the general introduction we provided a general review of zooplankton and ichthyoplankton metabolism importance. The results of this thesis are presented as five scientific articles organized in five central chapters, as follow: 1. In Chapter 1, we studied the effect of food concentration on the growth of Paracartia grani nauplii. In addition, we validated, in the laboratory, the enzymatic aminoacyl-tRNA synthetases (AARS) activity as proxy of growth rate for early stages of copepods. 2. In Chapter 2, we studied the effect of food concentration on the growth of Atlantic herring (Clupea harengus) larvae. In addition, we validated, in the laboratory, the enzymatic aminoacyl-tRNA synthetases (AARS) activity as proxy of growth rate for early stages of fish. 3. In Chapter 3, we studied the effect of temperature on zooplankton metabolism. 4. In Chapter 4, we studied the effect of oxygen concentration (oxygen minimum zone) on euphausiids metabolism. I. Introduction! ! 14 5. In Chapter 5, we pursued the possibility of finding a general relationship between the zooplankton community growth rate and its aminoacyl-tRNA synthetases activity, in order to facilitate the study of the whole community evolution. In the general discussion, we relate the results obtained from the preceding chapters, evaluate the initial goals of the thesis, and discuss the meaning of these findings in the context of zooplankton and ichthyoplankton growth rate. To conclude, we highlight the main conclusions of the thesis. I. Introduction! ! 15 Original Scientific Contributions 1. Herrera, I., Yebra, L., Hernández-León, S., 2012. Effect of temperature and food concentration on Paracartia grani nauplii growth and protein synthesis rates. Journal of Experimental Marine Biology and Ecology 416-417, 101-109. 2. Herrera, I., Borchardt, S., Santana del Pino, A., Peck, M.A., Yebra, L., HernándezLeón, S. Aminoacyl-tRNA synthetases (AARS) activity as an index of Atlantic herring (Clupea harengus) larvae growth. In preparation to be submitted to Journal of Fish Biology. 3. Herrera, I., López-Cancio, J., Yebra, L., Hernández-León, S. The effect of a strong warm year on subtropical mesozooplankton biomass and metabolism. Submitted to Journal of Plankton Research. 4. Herrera, I., Antezana, T., Giraldo, A., Beier, E., Yebra, L., Hernández-León, S., Färber-Lorda, J. Potential grazing, respiration and growth of Euphausia distinguenda in relation to the oxygen minimum zone at the Eastern Tropical Pacific off Mexico. In preparation to be submitted to PlosOne. 5. Hernández-León, S., Yebra, L., Herrera, I., Bécognée, P. The use of aminoacyl-tRNA synthetases (AARS) activity as an index of zooplankton growth. In preparation to be submitted to Marine Biology. ! ! II. Results ! ! Chapter 1 Effect of temperature and food concentration on Paracartia grani nauplii growth and protein synthesis rates Inma Herrera, Lidia Yebra and Santiago Hernández-Léon J. Exp. Mar. Biol. Ecol. 416-417, 101-109; 2012. ! Chapter 1 ! ! 21 Abstract The in situ activity of the enzymes aminoacyl-tRNA synthetases (AARS) and the growth rates of naupliar stages of the planktonic marine copepod Paracartia grani were measured in the laboratory under different temperature and food concentrations. We assessed the effect of these parameters on growth and protein synthesis rates of P. grani nauplii. Growth and protein synthesis rates of P. grani nauplii depended on temperature and food concentration. AARS activity is valid as an index of somatic growth for P. grani nauplii when growth is not limited by food availability. However, the relationship between proteinspecific AARS activity and nauplii growth varied according to food availability levels. The degradation of proteins during starvation and/or the ß-oxidation of fatty acids affected the relationship between specific AARS activity and growth rates. The results presented here add to previous studies showing that the AARS activity is a useful tool for estimating somatic growth of this and other key copepod species. Nevertheless, further research is required to elucidate the validity of AARS activity as a universal proxy for growth. Keywords: AARS, food concentration, growth, Paracartia grani, protein metabolism, temperature. Chapter 1 ! ! 28 3. Results 3.1. Effect of temperature on nauplii rates Weight-specific growth rates (slope of each regression line in Fig. 1), varied from 0.28 to 0.85 d-1 between 12 and 28ºC (Table 1). Figure 1. Paracartia grani nauplii. Carbon content (ng C) increases at different temperatures. Chapter 1 ! ! 29 The protein-specific AARSs (spAARSs, Table 1) ranged from 24.35 to 106.44 nmol PPi ·mg prot-1·h-1 and the individual AARSs increased from 0.003 to 0.019 nmol PPi·ind-1·h-1. Temperature (ºC) had a significant positive effect on growth rates (G, d-1) of nauplii (Fig. 2A): G = -0.188 + 0.038 · T, r2 = 0.984, p < 0.001 (eq.1) Also spAARSs (nmol PPi·mg prot-1·h-1) and individual AARSs (nmol PPi·ind-1·h-1) were significantly affected by temperature (Figs. 2B, 2C): spAARSs = -42.51 + 5.44 · T, r2 = 0.942, p < 0.001 (eq.2) AARSs·ind-1 = -0.010 + 0.001 · T, r2 = 0.852, p < 0.001 (eq.3) Figure 2. Paracartia grani nauplii. Effect of temperature on A) growth (d-1), B) spAARSs (nmol PPi·mg prot-1·h-1), C) individual AARSs (nmol PPi·ind-1·h-1). Chapter 1 ! ! 30 The Q10 value obtained within the 16 and 26ºC range was the same for growth rate and specific AARSs (2.1) and was 2.4 for individual AARSs. 3.2. Effect of food concentration on nauplii rates Weight-specific growth rates (slope of regression lines in Fig. 3) varied from -0.01 to 0.68 d-1 with increasing food concentrations (Fig. 4A) and the average spAARSs ranged between 32.24 and 59.60 nmol PPi·mg prot-1·h-1 (Table 2). The average AARSs per individual increased from 0.003 to 0.006 nmol PPi·ind-1·h-1 (Table 2) and presented high variability within experiments. The assumption that the aliquots frozen for biochemical assays contained a fixed amount of 1,000 nauplii was not always correct, as observed on the protein content of the sample replicates (data not shown). This was mostly noted in the growth experiment conducted at a food concentration of 440 µg C·L-1, which was excluded from fit calculations in Fig. 4C. Growth rates (d–1) relative to food concentrations (C, µg C·L–1) followed a saturation curve (Ivlev’s equation, 1955) expressed by the function: G = 0.65 · (1 – e(–0.013·C)), r2 = 0.986, p < 0.001 (eq.4) where 0.65 is the maximum growth rate (d–1) and 0.013 is a constant that indicates the rate at which growth approaches the maximum rate. Naupliar growth became saturated at a food concentration level of 220 µg C·L–1 (Fig. 4A). Individual AARSs (nmol PPi·ind-1·h-1) activities also increased with increasing food concentration (Fig. 4C), following a logarithmic model: AARSs·ind-1 = 0.0032 + 0.0004 ln(C), r2 = 0.907, p < 0.05 (eq.5) In contrast, specific AARSs (nmol PPi·mg prot-1·h-1) exhibited three different values in relation to food concentration (Fig. 4B). Specific AARS showed maximum values (59.31±0.29) from 0 to 11 µg C·L–1, while between 55 and 110 µg C·L–1 the average Chapter 1 ! ! 31 spAARSs was 46.27±0.24. Above 220 µg C·L–1 spAARSs remained low and rather constant (33.78±0.78). Figure 3. Paracartia grani nauplii. Carbon content (ng C) increases under different food concentrations. r -- / , -- -- -- , / -- '/ / o -- . / / -- / , -- -- Days after hatchin g Chapter 1 ! ! 32 Figure 4. Paracartia grani nauplii. Effect of food concentration on A) growth (d-1), B) spAARSs (nmol PPi·mg prot-1·h-1), C) individual AARSs (nmol PPi·ind-1·h-1); open circle: value not included in fit (see text). 3.3. Relationship between nauplii growth and protein synthesis rates Positive significant relationships were found between growth rates (d-1) and both spAARSs (nmol PPi·mg prot-1·h-1) and individual AARSs (nmol PPi·ind-1·h-1) activities under food saturating conditions within the 12-28ºC range (Fig. 5): G = 0.13 + 0.007 · spAARSs, r2 = 0.945, p < 0.001 (eq.6) G = 0.25 + 31.65 · AARSs·ind-1, r2 = 0.833, p < 0.001 (eq.7) Chapter 1 ! ! 33 A positive relationship between growth rates (d-1) and individual AARSs (nmol PPi·ind-1·h-1) was also found within the 0 - 4,000 cels·mL-1 (0 - 880 µg C·L–1) food concentration range (Fig. 6B): G = -0.59 + 204.46 · AARSs·ind-1, r2 = 0.951, p < 0.001 (eq.8) Figure 5. Paracartia grani nauplii. Relationship between growth rates (d-1) and A) specific AARSs activities (nmol PPi·mg prot-1·h-1), B) individual AARSs (nmol PPi·ind-1·h-1) at different temperatures (ºC). However, the relationship between growth rates (d-1) and spAARSs activities (nmol PPi·mg prot-1·h-1) was negative (Fig 6A): G = 1.49 - 0.025 · spAARSs, r2 = 0.958, p < 0.0001 (eq.9) Chapter 1 ! ! 34 Figure 6. Paracartia grani nauplii. Relationship between growth rates (d-1) and A) specific AARSs activities (nmol PPi·mg prot-1·h-1), B) individual AARSs (nmol PPi·ind-1·h-1) under different food concentrations (µg C·L1); open circle: value not included in fit (see text). Specific AARSs activities (nmol PPi·mg prot-1·h-1) also showed a negative relationship with nauplii individual biomass (µg proteins · ind-1), presenting higher spAARSs activities and lower individual biomass in starved organisms, and lower enzyme activities and higher protein content in the nauplii growing at food saturating levels (Fig 7A): spAARSs= 64.3 – 165.0 · individual biomass, r2 = 0.490, p < 0.0001 (eq.10) Chapter 1 ! ! 35 The relationship between daily growth rates and spAARSs in relation to the levels of food availability showed three different relationships (Fig 7B): Starvation level (0-11 µg C·L–1): G = -0.141 + 0.0024 · spAARSs, r2 = 0.458, p = 0.095 (eq.11) Intermediate level (55 - 110 µg C·L–1): G = -0.027 + 0.008 · spAARSs, r2 = 0.146, p = 0.351 (eq.12) Saturation level (>220 µg C·L–1): G = -0.57 + 0.038 · spAARSs, r2 = 0.799, p = 0.003 (eq.13) Figure 7. Paracartia grani nauplii. A) Relationship between specific AARSs activities (nmol PPi·mg prot-1·h-1) and individual biomass (µg proteins · ind-1); B) Relationships between daily growth rates (d-1) and specific AARSs activities (nmol PPi·mg prot-1·h-1) under different food concentrations (open circles: starvation level, triangles: intermediate level, filled circles: saturation level); arrows: values not included in fit. Chapter 1 ! ! 36 4. Discussion We assessed the effect of temperature and food concentration on somatic growth (calculated from length measurements) and protein synthesis rates (AARS activity) of Paracartia grani nauplii. A strong relationship was observed between growth rate and specific AARS activity at saturating food concentration and at a wide range of temperatures. However, this strong relationship was not observed at different food levels, except for those incubated at saturation. High specific AARS activities were found at low growth rates under limiting food concentration and low individual biomass. Early nauplii stages do not feed but develop consuming lipid reserves. Whether this feature influences the relationship between growth rates and specific AARS activity seems the key to understanding the high activity observed in the present and other works (e.g., Holmborn et al., 2009) at low levels of food and growth. 4.1 Effect of temperature Acartia species present isochronal development and exponential growth when reared at ad libitum food concentrations, and it has been shown that both growth and development rates depend on temperature (Sekiguchi et al., 1980; Klein Breteler and Schogt, 1994; Leandro et al., 2006, Leandro and Tiselius, 2006). Temperature had a positive effect on the naupliar growth and on the protein synthesis rates of these species when they were fed ad libitum. This naupliar growth rates were similar to those of other Acartia species nauplii (Table 3). The results obtained by Berggreen et al. (1988) and Leandro and Tiselius, 2006 for Acartia tonsa agree with the rates of P. grani observed by Calbet and Alcaraz (1997) and those found in the present work within the 10-18ºC temperature range. However, at 22ºC A. tonsa grew faster (Leandro and Tiselius, 2006) than P. grani. This might be due to the Chapter 1 ! ! 37 different quality of the food supplied (Table 3), but also to the different responses that these species may have with increasing temperature. Table 3. Summary of published Acartia spp. nauplii growth rates under saturating food levels. For example, A. tonsa is distributed worldwide (Kouwenberg, 2011), while P. grani is found in coastal NE Atlantic and Mediterranean Sea waters (Walter and Boxshall, 2011). Also, the temperature quotients (Q10) observed for both growth and protein synthesis rates in P. grani (2.1 between 16-26 ºC) were lower than the Q10 values reported by Leandro and Tiselius, 2006 (3.66 between 10-22 ºC). However, the use of Q10 values calculated across different temperature ranges could result in errors when comparing the temperature effects on physiological rates, as the Q10 has been shown to be temperature dependent, decreasing when temperature rises (Almeda et al., 2010). 4.2 Effect of food availability As expected, growth rates of Paracartia grani depended on the food availability. At low food concentration a low growth rate was observed in P. grani nauplii. This fact might be Chapter 1 ! ! 44 Hawkins, A.J.S., 1985. Relationships between the synthesis and breakdown of protein, dietary absorption and turnovers of nitrogen and carbon in the blue mussel, Mytilus edulis L. Oecologia 66, 42-49. Heinle, D.R., 1966. Production of the calanoid copepod, Acartia tonsa, in the Patuxent River estuary. Chesapeake Science 7, 59-74. Hirst, A.G., McKinnon, A.D., 2001. Does egg production represent adult female copepod growth? A call to account for body weight changes. Mar. Ecol. Prog. Ser. 223, 179-199. Hirst, A.G., Bunker, A.J., 2003. Growth of marine planktonic copepods: Global rates and patterns in relation to chlorophyll a, temperature, and body weight. Limnol. Oceanogr. 48, 1988-2010. Hirst, A.G., Roff, J.C., Lampitt, R.S., 2003. A synthesis of growth rates in marine epipelagic invertebrate zooplankton. Adv. Mar. Biol. 44, 1-142. Holmborn, T., Dahlgren, K., Holeton, C., Hogfors, H., Gorokhova, E., 2009. Biochemical proxies for growth and metabolism in Acartia bifilosa (Copepoda, Calanoida). Linmol. Oceanogr. Methods 7, 785-794. Huntley, M., Boyd, C., 1984. Food-limited growth of marine zooplankton. Am. Nat. 124, 455-478. Ismar, S.M.H., Hansen, T., Sommer, U., 2008. Effect of food concentration and type of diet on Acartia survival and naupliar development. Mar. Biol. 154, 335-343. Ivlev, V. S., 1955. Experimental ecology of the feeding of fishes. Yale University Press, New Jones, M.E., 1980. Pyrimidine nucleotide biosynthesis in animals: genes, enzymes, and regulation of UMP biosynthesis. A. Rev. Biochem. 49, 253–279 Klein Breteler, W.C.H., Gonzalez, S.R., 1982. Influence of cultivation and food concentration on body length of calanoid copepods. Mar. Biol. 71, 157-161. Chapter 1 ! ! 45 Klein Breteler, W.C.M., Schogt, N., 1994. Development of Acartia clausi (Copepoda, Calanoida) cultured at different conditions of temperature and food. Hydrobiol. 292, 469–47. Kleppel, G.S., Burkart, C.A., Houchin, L., 1998. Nutrition and the regulation of egg production in the calanoid copepod Acartia tonsa. Limnol. Oceanogr. 43, 1000-1007. Kouwenberg, J., 2011. Acartia (Acanthacartia) tonsa Dana, 1849, in: Walter, T.C., Boxshall, G. (Eds) (2011). World Copepoda database. Landry, M.R., 1978. Population dynamics and production of a planktonic marine copepod, Acartia clausi, in a small temperate lagoon on San Juan Island; Washington. Int. Rev. ges. Hydrobiol. 63, 77-119. Leandro, S.M., Queiroga, H., Rodríguez-Graña, L., Tiselius, P., 2006. Temperaturedependent development and somatic growth in two allopatric populations of Acartia clausi (Copepoda: Calanoida). Mar. Ecol. Prog. Ser. 322, 189–197. Leandro, S.M., Tiselius, P., 2006. Growth and development of nauplii and copepodites of the estuarine copepod Acartia tonsa from southern Europe (Ria de Aveiro, Portugal) under saturating food conditions. Mar. Biol. 150, 121-129. Lowry, P.H., Rosenbrough, N.J., Farr, A.L., Randall, R.J., 1951. Protein measurement with Folin phenol reagent. J. Biol. Chem. 193, 265-275. Marshall, S.M., Orr, A.P., 1955. The biology of a marine copepod - Calanus finmarchicus Gunnerus. Oliver & Boyd, London. Mente, E., Houlihan, D.F., Smith, K., 2001. Growth, feeding frequency, protein turnover, and amino acid metabolism in European lobster Homarus gammarus L. J. Exp. Zool. 289, 419-432. Oosterhuis, S. S., Baars, M. A., Klein Breteler, W. C. M., 2000. Release of the enzyme chitobiase by the copepod Temora longicornis: characteristics and potential tool for Chapter 1 ! ! 46 estimating crustacean biomass production in the sea. Mar. Ecol. Prog. Ser. 196, 195– 206. Paffenhöfer, G.A., Stearns, D.E., 1988. Why is Acartia tonsa (Copepoda: Calanoida) restricted to nearshore environments?. Mar. Ecol. Prog. Ser. 42, 33–38. Postel, L., Fock, H., Hagen, W., 2000. Biomass and abundance, in: Harris, R.P., Wiebe, P.H., Lenz, J., Skjoldal, H.R., Huntley, M. (Eds.). ICES Zooplankton Methodology Manual. Academic Press, London San Diego, pp 83-192. Rosamma, S., Rao, T.S.S., 1985. On the species of Acartiidae (Copepoda: Calanoida) collected during the international Indian Ocean expedition. Mahasagar Bulletin of the National Institute of Oceanography 18, 467-476. Runge, J.A., Roff, J.C., 2000. The measurement of growth and reproductive rates, in: Harris, R.P., Wiebe, P.H., Lenz, J., Skjoldal, H.R., Huntley, M. (Eds.). ICES Zooplankton Methodology Manual. Academic Press, London San Diego, pp 401-454. Rutter, W.J., 1967. Protein determinations in embryos, in: Wilt, F.H., Wessels, N.K. (Eds.). Methods in developmental biology. Academic Press, London, pp. 671-684. Saiz, E., Calbet, A., Trepat, I., Irigoien, X., Alcaraz, M., 1997. Food availability as a potential source of bias in the egg production method for copepods. J. Plankton Res. 19, 1-14. Saiz, E., Calbet, A., Fara. A., Berdalet, E., 1998. RNA content of copepods as a tool for determining adult growth rates in the field. Limnol. Oceanogr. 43, 465-470. Sastri, A.R., Roff, J.C., 2000. Rate of chitobiase degradation as a measure of development rate in planktonic Crustacea. Can. J. Fish. Aquat. Sci. 57, 1965–1968. Sars, G.O., 1904. Description of Paracartia grani, G.O. Sars, a peculiar calanoid occurring in some of the oyster-beds of western Norway. Bergens Museums Aarbog 4, 1-16, 6 pls. Sekiguchi, H., McLaren, I.A., Corkett, C.J., 1980. Relationships between rates of growth and reproduction in the copepod Acartia clausi hudsonica. Mar. Biol. 58, 133-138. Chapter 1 ! ! 47 Stottrup, J., Jensen, J., 1990. Influence of algal diet on feeding and egg-production of tha calanoid copepod Acartia tonsa Dana. J. Exp. Mar. Biol. Ecol. 141, 87-105. Teixeira, P.F., Kaminski, S.M., Avila, T.R., Cardozo, A.P. Bersano, G.F., Bianchini, A., 2010. Diet influence on egg production of the copepod Acartia tonsa (Dana, 1896). Annals of the Brazilian Academy of Sciences 82, 333-339. Villate, F., 1982. Contribución al conocimiento de las especies de Acartia autóctonas de zonas salobres: Acartia (Paracartia) grani, G.O. Sars en la ría de Mundaka (Vizcaya, España). Kobie 12, 76-81. Wagner, M.M., Campbell, R.G., Boudreau, C.A., Durbin, E. G., 2001. Nucleic acids and growth of Calanus finmarchicus in the laboratory under different food and temperature conditions. Mar. Ecol. Prog. Ser. 221, 185–197. Walter, T.C., Boxshall, G., 2011. Paracartia grani Sars G.O., 1904, in: Walter, T.C., Boxshall, G. (Eds) (2011). World Copepoda database. Yebra, L., Harris, R.P., Smith, T., 2005. Growth of Calanus helgolandicus later developmental stages (CV-CVI): comparison of four methods of estimation. Mar. Biol. 147, 1367-1375. Yebra, L., Hernández-León, S., 2004. Aminoacyl-tRNA synthetases activity as a growth index in zooplankton. J. Plankton Res. 26, 351-356. Yebra, L., Hirst, A.G., Hernández-León, S., 2006. Assessment of Calanus finmarchicus growth and dormancy using the aminoacyl-tRNA synthetases method. J. Plankton Res. 28, 1191-1198. Yebra, L., Berdalet, E., Almeda, R., Pérez, V., Calbet, A., Saiz, E., 2011. Protein and nucleic acid metabolism as proxies for growth and fitness of Oithona davisae (Copepoda, Cyclopoida) early developmental stages. J. Exp. Mar. Biol. Ecol. 406, 87-94. ! ! ! Aminoacyl-tRNA synthetases (AARS) activity as an index of Atlantic herring (Clupea harengus) larvae growth Inma Herrera, Stephanie Borchardt, Angelo Santana del Pino, Myron A. Peck, Lidia Yebra and Santiago Hernández-Léon Chapter 2 ! Chapter 2 ! ! 51! Abstract Specific growth rates (SGR) and specific aminoacyl-tRNA synthetases (AARS) activities of herring (Clupea harengus) larvae were studied in laboratory experiments. The larvae were kept at 7 and 17ºC feeding ad libitum, and at 12ºC were offered three different food concentrations of nauplii and copepodites of Acartia tonsa (0.1, 0.3 and 2 prey·mL-1). Both SGR and AARS activities showed significant differences between 7ºC and 12-17ºC. Furthermore, SGR and AARS activities followed a similar pattern in relation to food concentration, with no statistically significant differences between treatments at 0.1 and 0.3 prey·mL-1 levels, while at the 2.0 prey·mL-1 food level both variables increased significantly. In addition, AARS activities and specific growth rates were influenced by protein degradation under food deprivation. Nevertheless, SGR and AARS activity were significantly correlated. Keywords: AARS, feeding levels, growth, herring larvae, temperature. Chapter 2 ! ! 52! 1. Introduction Atlantic herring (Clupea harengus) is one of the most abundant and commercially important fish species in the North Atlantic (Brandt and McEvoy, 2006; Overholtz and Link, 2007). This species plays an important role in the trophodynamics of many systems including the Baltic Sea, where it can exert a top-down control upon the crustacean zooplankton community (Hansson et al., 1990; Arrhenius and Hansson, 1993). Recruitment of springspawning Baltic Sea herring is thought to be regulated by processes occurring during the early larval period. Therefore, obtaining robust estimates of the nutritional status and growth rates of herring larvae may not only help to reveal processes affecting recruitment but also to help forecast year-class success. Atlantic herring is a well-known species (see review by Geffen, 2009) and previous studies have obtained larval growth rates by applying a variety of techniques, including otolith micro-structure analysis (Moksness and Wespestad, 1989; Campana and Moksness, 1991; Suneetha et al., 1999; Johanneseen et al., 2000). Folkvordet al. (2004) suggested that most of the variability in growth rates of early stages of Atlantic herring could be explained by temperature. Some previous studies (Johannessen et al., 2000; Folkvordet al., 2004; Fox et al., 2003) have examined growth rates within a limited range of temperatures (8-12ºC), but recent time-series analyses of larval cohorts of spring-spawning herring by Oeberst et al. (2009) indicates that 12-15 mm larvae normally experience much warmer temperatures (15 to 19°C). Unfortunately, no laboratory studies have examined growth rates or attempted to calibrate growth indices for herring at such higher temperatures. Chapter 2 ! ! 53! Proxies for growth in fish larvae have focused on the ratio RNA:DNA, which gives a measure of the protein synthetic capacity of the cell (Buckley, 1984; Ferron and Leggett, 1994; Clemmesen and Doan, 1996; Buckley et al., 1999). Growth rate has a close relationship with the protein synthesis (Love, 1970) and the RNA content per cell varies with the amount of protein synthesis. Because DNA is relatively constant within a cell, the RNA content is normally standardized using DNA (Clemmensen, 1987). The RNA:DNA ratio has been used as a proxy for growth rate and condition in fish larvae (Buckley, 1979; Westerman and Holt, 1994; Clemmensen, 1996). Besides that, there are other biochemical indices related to growth rate based on enzymatic activities such as lactate deshydrogenase (LDH), or citrate synthase (CS). All of these methods have constraints, some are too time consuming, and others require large samples or are valid only for particular larval stages. During the last decade the activity of the enzyme aminoacyl-tRNA synthetases (AARS), which catalyze the first step of protein synthesis, has been used in a variety of aquatic organisms. Here, we use AARS activity because the results obtained in previous works showed its suitability as an index of growth rate in freshwater and marine crustaceans, such as Daphnia magna (Yebra and Hernández-León, 2004), Calanus helgolandicus (Yebra et al., 2005) Euphausia superba, (Guerra, 2006), Calanus finmarchicus (Yebra et al., 2006) Oithona davisae (Yebra et al., 2011) and Paracartia grani (Herrera et al., 2012). The objective of this work was to study whether AARS could be used to explain changes in growth of Atlantic herring larvae reared at different temperatures and at different prey levels. This study specifically included experiments testing the growth response of larvae at warmer water temperatures, feeding on calanoid copepods to better match the conditions experienced in the field by the Baltic spring-spawning larvae. Chapter 2 ! ! 60! Figure 2. Effect of temperature on SGR (day-1) and spAARS activity (nmol PPi·mg prot-1·h-1). The SGR at 7ºC showed significant differences with the SGR at 12 and 17ºC (p<0.05). The model used to analyze the results showed no differences among replicates at each temperature. Specific AARS activity (spAARS, Table 1) ranged from 98.42 to 169.21 nmol PPi·mg prot-1·h-1, and showed a similar pattern to SGR. There were statistically significant differences between average AARS activities at different temperatures (p<0.05). 3.2. Effect of food concentration on fish larvae The relationship between dry weight (µg dw) and day post hatching (14-32 DPH) of C. harengus larvae is shown in Fig. 3 for the 3 experimental food levels tested (0.1, 0.3, 2 prey·mL-1), including both replicates per experiment. Chapter 2 ! ! 61! Figure 3. Relationship between dry weight (µg dw) of C. harengus and day post hatching under different food levels (prey·mL-1). All regressions were highly significant (p<0.05). The specific growth rates considered as the slope of these linear regressions are shown in Table 1. SGR varied from 0.08 to 0.17 day-1 (Fig. 4). Figure 4. Effect of food concentration on SGR (day-1) and spAARS activity (nmol PPi·mg prot-1·h-1). Chapter 2 ! ! 62! The SGR at 0.1 and 0.3 prey·mL-1 food levels showed significant differences in relation to SGR at 2.0 prey·mL-1 (p<0.05). The model used to analyze the results showed no differences among replicates at each food concentration. Average spAARS ranged from 129.61 to 169.21 nmol PPi·mg prot-1·h-1 (Table 1) showing a similar pattern to SGR for the different food concentrations. AARS values at 0.1 and 0.3 prey·mL-1 showed significant differences in relation to 2 prey·mL-1 (p<0.05). High values of specific growth matched the high values of spAARS at the same food level. 3.3. Relationship between growth rates and specific AARS activities A positive relationship between specific growth rates (d−1) and spAARS activities (Fig. 5A) was observed at different temperatures. Specific growth rate = -0.1031 + 0.0017 · spAARS (r2=0.711; p<0.05) (eq.2) However, specific growth rates (d−1) and spAARS activities under different food levels (Fig. 5B) showed a slightly positive relationship but the slope was not significant (p=0.78). Specific growth rate = 0.0876 + 0.0003 · spAARS (r2=0.022) (eq.3) Using all data at different temperatures and under different food levels, specific growth rates (d−1) explained 42.5% of spAARS activity variance (p<0.05) (Fig. 5C). Specific growth rate = -0.0343 + 0.0011· spAARS (r2=0.425) (eq.4) Chapter 2 ! ! 63! Figure 5. Relationships between growth rates (day-1) and specific AARS activity (nmol PPi·mg prot-1·h-1) A: at different temperatures (ºC), B: under different food concentrations and C: all data pooled. The relationship between specific AARS activity and individual biomass (µg protein·ind-1) followed a negative exponential pattern (Fig. 6) at different temperatures (Fig. 6A), as well as under different food levels (Fig. 6B). This relationship showed that small Chapter 2 ! ! 64! larvae (<100-200 µg protein·ind-1) had the largest spAARS values; likewise lower and constant values were observed in larger individual biomass. Figure 6. Relationship between specific AARS activity (nmol PPi·mg prot-1·h-1) and individual biomass (µg protein·ind-1) A: at different temperatures (ºC), B: under different food concentrations (prey·mL-1). 600 ~ A 500 'o '-< o.. 400 bD a o:: 300 p... -o a 200 == '--' r:/J ~ ~ 100 o.. ~ tJ. • é 100 200 300 400 500 600 700 ¡.tg protein' ind·l A 'e... 7 oc 800'Q 12 oc 'A.. 17 oc 600 ,-----------------------------, ~ A 500 8 o.. 400 bfl a o:: 300 p... -o a == 200 '--' 50 • 100 150 200 ~lg protein . ind·l 250 [J [J B • 'e... 2 prey . IllL·1 300 'Q 0.3 prey . IllL·1 'A.. 0.1 prey . IllL·1 Chapter 2 ! ! 65! 3.4. Effect of food deprivation on fish larvae SGR of the starved larvae ranged from -0.15 to 0.07 day-1 (Table 2). Table 2. Atlantic herring larvae specific growth rate (SGR, d-1) and spAARS (nmol PPi·mg prot-1·h-1) under food deprivation; ‘n’ is the number of either individuals sized or samples analyzed. Data in italics correspond to experiments of 36 hours duration. T (ºC) SGR (d-1) (r2, n) spAARS ± SE (n) (nmol PPi·mg prot-1·h-1) 7 0.01 (0.39, 46) 238.51 ± 20.90 (24) 7 0.01 (0.46, 43) 245.72 ± 24.49 (24) 7 0.01 (0.37, 56) 253.29 ± 20.35 (26) 17 0.07 (0.73, 73) 307.82 ± 20.98 (26) 17 -0.15 (0.31, 60) 132.37 ± 12.91 (30) 17 0.05 (0.04, 64) 138.64 ± 17.29 (23) The relationship between spAARS and individual biomass (µg protein·ind-1) of unfed larvae showed a similar trend to the one observed for fed larvae (Fig. 7). Figure 7. Relationship between specific AARS activity (nmol PPi·mg prot-1·h-1) and individual biomass (µg protein·ind-1) under food deprivation. Chapter 2 ! ! 66! 4. Discussion We assessed the effect of temperature and food concentration on specific growth rates and specific AARS activities of Clupea harengus larvae. A positive relationship between SGR and AARS activity was observed at different temperatures under ad libitum food concentrations. However, this relationship was not significant at different food levels. Besides, under food deprivation, high specific AARS activities were found at low growth rates! Specific growth rates estimated in this study were similar to the observed by other authors (Suneetha et al., 1999; Folkvord et al., 2000; Johannessen et al., 2000; Arrhenius and Hansson, 1996; Kiørboe and Munk, 1986, Table 3). Table 3. Review of herring larvae growth rates under different food levels and temperatures. TºC Food concentration (prey·mL-1) Standard length (mm) SGR (% d-1) Reference 7 ad libitum 10-24 6.10 this study 8 ad libitum 7.1 Suneetha et al., 1999 8 0.04 12-19 4-6 Folkvord et al., 2000 8 1.2 15-23 5-8 Folkvord et al., 2000 8 0.02 - 0.04 9-24 1.5 Johannessen et al., 2000 8 1.2 - 2.0 9-24 7 Johannessen et al., 2000 11 ad libitum 6.6 Suneetha et al., 1999 12 0.1 9-21 12.20 this study 12 0.3 9-19 9.40 this study 12 2 9-21 16.70 this study 17 ad libitum 10-22 9.20 this study Chapter 2 ! ! 67! Furthermore, the specific growth rates of these fish larvae also depended on food availability. At low food concentration the growth rates observed were lower. The variability of the growth rates due to the food concentration was higher than in previous observations, showing that growth rate is affected by the amount of food concentration in the field (Kiørboe and Munk, 1986; Johannessen et al., 2000; Folkvord et al., 2000, Table 3). AARS activities were also positively affected by food concentration. However, when C. harengus larvae were starved, they showed high specific AARS activities coupled with low or negative growth rates. This high enzyme activity under starvation was also observed on nauplii and adult stages of calanoid copepods (Acartia bifilosa, Holmborn et al., 2009; Paracartia grani, Herrera et al., 2012). Herrera et al. (2012) suggested that organisms under food deprivation were sustained at the expense of accumulated endogenous energy reserves, resulting in either negative or almost nil growth rates despite the high specific AARS activities (Table 2). The negative SGR in starved fish larvae could be explained by protein degradation (Love, 1980). This catabolism was previously described in Clupea harengus larvae under food deprivation (Ehrlich, 1974). The effect of starvation on metabolism is more remarkable in early stages than in juveniles, probably due to the lower lipid reserves in juveniles (Gadomskia and Petersen, 1988; Richard et al., 1991). Starved larvae lost weight due to metabolic costs, presenting minimum levels of muscle fibre, which represent 60 to 70% of their body weight (Machado et al., 1988). It has been observed that muscle mass of fish larvae was the only variable showing differences between starved and fed organisms (Martin and Wright, 1987; Ferron and Leggett, 1994; Catalán, 2003; Pliego Cortés, 2005). This is because, in fish larvae, body weight is very sensitive to food deprivation due to the fast protein degradation (Love, 1980). It is also known that C. harengus larvae consume lipid reserves during starvation (Ehrlich, 1974). Whether this characteristic influences the relationship between growth rates and specific AARS activity under food deprivation Chapter 2 ! ! 68! conditions might be the key to understand the unexpected high AARS activities observed in organisms with low growth rates (Holmborn et al., 2009; Herrera et al., 2012). On the other hand, when larvae were not food limited, both SGR and AARS activity showed a positive relationship with temperature. A significant correlation was found between AARS activities and specific growth rates. This is accordance with previous works in different zooplankton species such as Daphnia magna (Yebra and Hernández-León, 2004), Calanus helgolandicus (Yebra et al., 2005), C. finmarchicus (Yebra et al., 2006), Oithona davisae (Yebra et al., 2011), Euphausia superba (Guerra, 2006) and Paracartia grani (Herrera et al., 2012). In summary, specific growth rates and specific AARS activities of C. harengus larvae depend on temperature and food concentration as expected. In addition, AARS activities and specific growth rates were influenced by protein degradation under food deprivation. Even so, SGR and AARS activities were positively correlated. Acknowledgments We thank the members of the Institute of Hydrobiology and Fisheries Science at the University of Hamburg (Hamburg, Germany). Special thanks to Philip Kastinger for his help during the experiments. This work was supported by the Canary Government (ACIISI) through a PhD fellowship to I. Herrera and projects Lucifer (CTM2008-03538/MAR) and Mafia (CTM2012-39587) from the Spanish Ministry of Economy and Competitiveness. Chapter 2 ! ! 69! References Arrhenius, F., Hansson, S., 1993. Food consumption of larval, young and adult herring and sprat in the Baltic Sea. Mar. Ecol. Prog. Ser. 96, 125-137. Arrhenius, F., Hansson, S., 1996. Growth and seasonal changes in energy content of young Baltic Sea herring (Clupea harengus L.). ICES J. Mar. Sci. 53, 792-801. Brandt, S., McEvoy, D., 2006. Distributional effects of property rights: Transitions in the Atlantic herring fishery. Mar. Policy. 30, 659-670. Bergeron, J.P., 1997. Nucleic acids in ichthyoplankton ecology: a review, with emphasis on recent advances for new perspectives. J. Fish Biol. 51, 284-302. Borchardt, S., 2010. Impacts of Temperature and Feeding on Growth and Condition of Larval Herring. Diploma Thesis. Buckley, L.J., 1979. Relationships between RNA/DNA ratio, prey density, and growth rate in Atlantic cod (Gadus morhua) larvae. J. Fish Res. Bd. Canada 36, 1497-1502. Buckley, L.J., 1984. RNA-DNA ratio: an index of larval fish growth in the sea. Mar. Biol. 80, 291-298. Buckley, L., Caldarone, E., Ong, T.L., 1999. RNA-DNA ratio and other nucleic acid-based indicators for growth and condition of marine fishes. Hydrobiologia 401, 265-277. Campana, S.E., Moksness, E., 1991. Accuracy and precision of age and hatch date estimates from otolith microstructure examination. ICES J. Mar. Sci. 48, 303-316. Catalán, I.A., 2003. Condition indices and their relationship with environmental factors in fish larvae. PhD Thesis, University of Barcelona. Clemmesen, C.M., 1987. Laboratory studies on RNA/DNA ratios of starved and fed herring (Clupea harengus) and turbot (Scophthalmus maximus) larvae. J. Cons. int. Explor. Mer. 43, 122-128. ! Chapter 3 ! 77 Abstract The winter of 2010 was the warmest of the last 30 years in the subtropical oceanic waters north off the Canary Islands. In this year, surface temperature was always above 19ºC, promoting a strong stratification and quite low values of chlorophyll during winter-spring. The late winter bloom, typical in these waters, was not observed. During the normal timing of the bloom, February-March, the indices of mesozooplankton grazing (gut fluorescence) and respiration (ETS activity) showed low values compared to previous years. However, relatively high mesozooplankton biomass (dry weight) was observed during the post bloom period (April-June). This paradox was explained by the input of dust deposition from the Sahara desert. These inputs are suggested to be indirectly responsible for the sustained growth rates (AARS activity) observed throughout the study period. Our findings show how climatic warming and dust events may interact affecting the intensity of the winter-spring bloom in subtropical waters. Keywords: AARS, biomass, dust deposition event, ETS, GF, lunar cycle, zooplankton Chapter 3 ! 78 1. Introduction Zooplankton grazing, respiration and growth in the open ocean have an important role in the ocean’s biogeochemical cycles. However, physiological information on zooplankton in the subtropical oligotrophic gyres remains rather limited (Welschmeyer and Lorenzen, 1985; Harrison et al., 2001; Huskin et al., 2001; Woodd-Walker et al., 2002). The Canary Islands are located in the subtropical gyre and exhibit oligotrophic characteristics (De León and Braun, 1973). These waters are characterized by a quasi-permanent thermocline caused by a strong surface heating through the year that restrains the pumping of nutrients to surface layers. During winter, the atmospheric cooling erodes the thermocline allowing a small enrichment of nutrients in the euphotic zone promoting the so-called late winter bloom (Ryther and Menzel, 1960). This process produces an increase in primary production and zooplankton biomass. This winter bloom is well known in the Canary Island waters from the stand point of plankton biomass and production (De León and Braun, 1973; Arístegui et al., 2001; Hernández-León et al., 1998, 2004, 2010; Moyano et al., 2009; Schmoker et al., 2012). The bloom starts when temperature falls below 19ºC in the upper 100 m, promoting chlorophyll values above 0.5 mg Chl a · m-3, and it is normally observed during February and March (Hernández-León et al., 2004, 2010). Microand mesozooplankton biomass also bloom during the late winter bloom as a consequence of the increased primary production (Arístegui et al., 2001; Schmoker et al., 2012). In mesozooplankton the timing of the bloom is also related to the lunar cycle (Hernández-León, 1998; Hernández-León et al., 2001, 2002, 2004, 2010). This relationship is explained by the effect of moonlight on diel vertical migrants (DVM) behaviour. During the illuminated period of the lunar cycle the migrants avoid the shallower layers (0-100 m) during the night. This promotes an increase in epipelagic zooplankton abundance and Chapter 3 ! 79 biomass due to the lower predatory pressure of migrants. However, the magnitude of the mesozooplankton bloom is related to climate as mixing during winter is stronger and lasts longer during cold years. In this sense, Schmoker and Hernández-León (2013) showed the mesozooplankton bloom to last three months during a cold year and only one month during a warm year. On the other hand, the proximity of the Canary Islands to the African continent makes this archipelago a suitable place to study Saharan dust deposition effects on ocean productivity. Dust increases the availability of carbon, nitrogen, silica and iron, among other nutrients (Duarte et al., 2006), promoting blooms of phytoand zooplankton (HernándezLeón et al., 2004, 2010; Giovagnetti et al., 2012). Besides that, we know the effect of dust storms on bacteria, unicellular diazotrophs and Trichodesmiun (Benavides et al., 2013), as well as on primary production and microzooplankton in the Canary Island waters (Hernández-León et al., 2004; Franchy et al., submitted). The objective of the present work was to study the mesozooplankton biomass and metabolism north off the Canary Islands from February to June 2010. Mesozooplankton biomass was estimated as dry weight, while gut fluorescence (GF), electron transport system (ETS), and aminoacyl-tRNA synthetases (AARS) activities where used as indices of grazing, respiration and growth, respectively. According to remote sensing data (www.oceanmotion.org/html/resources/ssedv.htm), the year 2010 presented the warmest winter of the last 30 years in the study area. The knowledge of the effect of a warming ocean on plankton productivity is of paramount importance in future scenarios, especially in the Canary Current where a general warming has been observed since 1986 (Arístegui et al., 2009; Demarcq, 2009). Hence, we emphasized this aspect by comparing with previous studies of the late winter bloom in the area. Chapter 3 ! 80 2. Materials and Methods Sampling took place from February to June 2010 in the oceanic waters north off Gran Canaria Island (Fig. 1). Four oceanographic stations, separated 10 miles, were monitored from coast to open ocean on board the RV Atlantic Explorer. Vertical profiles (0-300 m) of temperature, conductivity and fluorescence were obtained using a CTD Sea-Bird Electronics with SBE-25 probe. Samples for chlorophyll a concentration were taken at 20 m depth with a 4 L Niskin bottle, and used for calibration of the fluorescence profiles data from the fluorometer (Turner Self-Contained Underwater Fluorescence Apparatus, SCUFA) attached to the rosette and CTD. Unfortunately, CTD data from February were not available due to a CTD failure. However, Las Palmas de Gran Canaria port provided sea surface temperature information from a buoy close to our sampling area (Fig. 1). Figure 1. Location of the four oceanographic stations (circles), three atmospheric stations (triangles), and the buoy position (square) during the study period. Chapter 3 ! 81 Atmospheric total suspended particulate matter was collected onto Whatman GF/A fiberglass filters using a high volume sampler pumping system (MCV) at a flow rate of 50 m3·h-1. Each sampling period started at 08:00 h and lasted 24 h. The collectors were placed 10 m above the ground at three stations to the north of Gran Canaria Island (Fig. 1). For iron (Fe) analysis, the filters were processed with nitric and hydrochloric acid, according to the Beyer modified method (López Cancio et al., 2008). Zooplankton was sampled in vertical hauls (0-200 m; 0.6 m·s-1) using a double WP-2 net (UNESCO 1968, 100 µm mesh size) fitted with a TSK flowmeter. One cod-end was fractionated into different size categories (100-200, 200-500, 500-1000 and >1000 µm) and immediately frozen in liquid nitrogen (-196ºC) for later analysis in the laboratory. The sample from the second cod-end was fixed in formalin (1% in seawater), kept at 4ºC for 24 h and divided in two subsamples in the laboratory with a Folsom plankton splitter for taxonomy and dry weight (DW) measurements (Lovegrove 1966), respectively. At the laboratory, frozen samples were homogenized in Tris-HCl buffer (20 mM, pH 7.8) and a subsample of 0.2 mL was taken to determine gut fluorescence (GF, chlorophyll a plus phaeopigments), following the procedure given by Parsons et al. (1984) and Arar and Collins (1997). Pigments were extracted for 24 h in 10 mL of 90% acetone at 4ºC in the dark (Parsons et al., 1984). Chlorophyll a and phaeopigments were measured fluorometrically on a Turner Design fluorometer 10-AU digital, calibrated with pure Chl a (C-6144, SigmaAldrich) as suggested by Yentsch and Menzel (1963). The remaining sample was centrifuged (10 min, 0ºC) and subsamples where taken to measure (1) the electron transport system (ETS) activity according to Packard et al. (1971) taking into account the modifications of Kenner and Ahmed (1975), and (2) aminoacyl-tRNA synthetases activity (AARS) following the method of Yebra and Hernández-León (2004) modified by Yebra et al. (2011). AARS activity was calculated using the next equation: Chapter 3 ! 82 AARS!activity!(nmol!PPi!·!h!!)= !"#$ !"# ·!"!·!"·!!!" !!·!.!!·!·! ·V!"# where dAbs·min-1 is the rate of decay in absorbance per minute, 103 is the conversion of µmol to nmol, 60 is the conversion from minutes to hours, Vrm is the volume of the reaction mixture (mL), Vs is the volume of sample in the assay cuvette (mL), 6.22 is the millimolar absorptivity (L·mmol-1·cm-1) of NADH at 340 nm, 2 is the number of moles of β-NADH oxidized per mole of PPi consumed, 1 is the pathlength correction for the cuvette width (cm) and Vhom is the total volume of sample homogenate (mL). Biomass was measured as proteins following the method of Lowry et al. (1951) adapted for micro-assay by Rutter (1967) and using Bovine Serum Albumin (BSA) as standard. The enzymatic activities were recalculated for the in situ temperature using the Arrhenius equation and the corresponding activation energies for ETS (15 kcal · mol-1, Packard et al., 1975) and for AARS (8.57 kcal · mol-1, Yebra et al., 2005). An analysis of variance (ANOVA) was used to compare the evolution of each variable (chlorophyll a, biomass, GF, ETS and AARS) over time at the four stations sampled. There were no differences between the different stations (ANOVA, p>0.05), except for the chlorophyll a at the more coastal station (Table 1). Hence, we pooled the zooplankton data of all stations. For chlorophyll a, we averaged the three more oceanic stations. Chapter 3 ! 83 Table 1. Variance analysis (ANOVA) comparing differences between stations for each variable: chlorophyll a (mg Chl a · m-3), mesozooplankton biomass (mg DW · m-2), specific GF (µg pigment · mg prot-1), specific ETS (µL O2·mg prot-1·h-1) and specific AARS (nmol PPi · mg prot-1·h-1). In addition, interannual variability of environmental (temperature) and biological (chlorophyll, zooplankton biomass) variables was evaluated during the normal timing of the bloom (January-March) and afterwards (April-June), comparing our data with the literature. In order to compare the zooplankton biomass of this study (0-200 m) with Moyano and Hernández-León (2011) values (0-100 m depth), we used the relationship log-mg DW (0100)=0.0869+0.9452·log-mg DW (0-200), (R2=0.894, p<0.001, Hernández-León, unpubl.). To assess the differences between the different years, an analysis of variance (ANOVA) was performed using the statistical package R. ANOVA assumptions were verified using Levene’s test for homogeneity of variance. When a variable showed significant differences, Scheffe’s multiple range test was performed to determine differences among the average temperature, chlorophyll a and biomass for each year. When conditions for normality were not satisfied, the Kruskall-Wallis ANOVA by ranks was used to determine whether the differences were significant. Variable F p-value F crit Chl a (stations 1-4) 6.72 <0.05 2.78 Chl a (stations 2-4) 0.69 >0.05 3.25 Biomass 0.35 >0.05 2.80 GF 2.79 >0.05 2.79 ETS 0.86 >0.05 2.79 AARS 0.62 >0.05 2.79 Chapter 3 ! 84 3. Results Temperature and salinity showed rather high values in the upper 100 m (Fig. 2) during all the period sampled. Temperature was always higher than 19ºC during winter (Fig. 2a), preventing mixing during late winter. Figure 2. (a) Sea surface temperature from the oceanic buoy, (b) vertical sections showing the evolution of temperature (ºC) and (c) salinity at station 3. Dotted lines indicated the intervals of sampling time. Chapter 3 ! 85 Additionally, two important events of Saharan dust took place over the islands during January and March (Fig. 3a). Other weak events were measured on 22ndFebruary, 11th and 29th April, 17th May, and 4th June. Atmospheric total suspended particulate matter (TSM) reached over 500 µg·m-3 on 18th March, and consequently an increment of iron concentration was observed (Fig. 3a). Chorophyll a showed no clear response to these events during the period studied (Fig. 3b and c). Figure 3. (a) Atmospheric total suspended particulate matter and iron concentration; (b) vertical section showing the evolution of chlorophyll a at station 3; (c) average values of chlorophyll a (mg Chla · m-3 ± SE, at 20 m); dashed line showed chlorophyll a values at station 1 and solid line average values for the other three oceanic stations sampled. Chapter 3 ! 92 Table 2. Interannual variability of environmental and biological variables was evaluated during normal timing of the bloom (January-March) and afterwards (April-June). Average temperature (T; 20-30 m, °C ± SD), average chlorophyll a (Chl a; 20-30 m, mg Chl a · m-3± SD) and average zooplankton biomass (Biomass; 0-100 m, mg DW · m-2± SD) in 2005-2007 by Moyano and Hernández-León, 2011; and in 2010, this study. 4. Discussion 2010 was an atypical year, it showed the warmest winter sea surface temperature of the last 30 years (www.oceanmotion.org/html/resources/ssedv.htm), which also coincided with the minimum NAO recorded since 1950 (http//www.cpc.ncep.noaa.gov/data/teledoc/nao _ts.shtml). A low NAO index has been related with high temperatures and low trade winds during winter in the NW African upwelling zone (26-25 ºN), including the Canary Island region (Cropper et al., 2014). Hence, the winter-spring period studied did not show the typical conditions that produce the so-called late winter bloom in this latitude. Consistent with low chlorophyll values, Franchy et al. (submitted) found extremely low values of pico-, nanoand microplankton biomass during the same period of study. Temperature and salinity were higher than previously observed in the Canary Islands waters in winter (see Moyano and Hernández-León, 2011; Schmoker and Hernández-León, 2013). The interannual variability also showed that 2010 was the warmest year of the four years compared (Table 2), presenting surface values higher than 19ºC. However, despite the high temperatures, strong stratification, and low chlorophyll values, Franchy et al. (submitted) observed relatively high Chapter 3 ! 93 values of primary production coinciding with heavy dust deposition events during this winterspring period. Such events were more intense than in previous years, especially in March (http://earthobservatory.nasa.gov/) and promoted an increased Fe deposition as well as an increase in diatoms (Franchy et al., submitted). However, the maximum value of chlorophyll a found in this study (0.25 mg·m3) was considerably lower than the usually found in the area (Arístegui et al., 2001; Hernández-León et al., 2004, 2010; Neuer et al., 2007; Moyano and Hernández-León, 2011; Schmoker et al., 2012). In addition, relatively high chlorophyll a values were observed during cold years suggesting that warm temperatures restricted the vertical nutrient flux to the surface layers (Cianca et al., 2007), limiting the phytoplankton growth. Maximum total zooplankton biomass values were recorded during the first month reaching values higher than 1000 mg DW · m-2, similar to that observed by Hernández-León et al. (2004). Also, during the whole study the total biomass presented rather high values (over 600 mg DW · m-2). In this sense, the pattern described by Arístegui et al. (2001) and Hernández-León et al. (2004) showed two clear periods. During the first one, from January to March, maximum biomass values were recorded coinciding with maximum mixing. However, during our study, biomass showed values lower than expected because of the strong stratification observed. The second period, from April to June, characterized by higher temperatures, always showed relatively lower biomass values compared to the bloom period (Hernández-León et al., 2004; Moyano and Hernández-León, 2011). In our interannual comparison, the post-bloom period during 2010 also showed higher temperatures, denoting higher stratification. However, average zooplankton biomass for this period was within the range of previous years, despite the stronger stratification. This suggests that dust deposition allowed a surplus production (Franchy et al., submitted) and slightly higher mesozooplankton biomass than that expected based only on hydrographic factors. Chapter 3 ! 94 Additional evidence of the lack of winter bloom during 2010 was the low values of the indices of grazing (GF) and respiration (ETS activity). Specific GF during the whole period showed values as low as previously reported for the post-bloom period (April to June) in these subtropical waters (Hernández-León et al., 2004). The latter authors showed maximum GF values from January to March, and thereafter values decayed by 2-fold. Although size fractionated GF values in 2010 were lower compared to previous years, the expected pattern of decreasing GF values as size fraction increases was maintained. Similarly, the specific ETS activity also showed low values compared to previous years in the same area. Hernández-León et al. (2004) observed the maximum specific ETS values coinciding with the mixing period prior to the zooplankton biomass outburst, whereas in our work, specific ETS values only increased coinciding with increments of zooplankton biomass. In addition, specific AARS activity showed relatively high values, suggesting that the recurrent dust input events allowed for sustained growth rates during both the bloom and post-bloom periods. Unfortunately, there are no prior zooplankton growth studies during the late winter bloom to compare with. Hence, we could not ascertain the possible effects of warming over the zooplankton production in the area. Besides, mesozooplankton biomass increased in parallel to the moon illumination during February-March, the usual timing of the late winter bloom, as previously seen in subtropical waters (Hernández-León, 1998; Hernández-León et al., 2001, 2002, 2004, 2010). However, no clear match with the lunar cycle was observed thereafter, probably due to the slightly high biomass stock maintained during most of the post-bloom period. The higher than expected biomass is suggested to be a consequence of the increased primary production observed by Franchy et al. (submitted). Thus, it seems that dust depositions during the postbloom period would enhance the transfer of energy and matter to the mesozooplankton. However, the way this transfer occurs is not clear, as chlorophyll and specific GF values Chapter 3 ! 95 remained low. In summary, the high warm winter temperature and the strong stratification of the water column precluded the typical late winter bloom during that year. On the contrary, an intense frequency of dust deposition events promoted an increase of primary production and a higher than expected mesozooplankton biomass during the post-bloom period (April to June). Our findings show some clues about how under a warming environment scenario the frequency of dust events may gain importance in shaping the intensity of the winter-spring bloom in subtropical waters in the near future. Acknowledgements We are indebted to L. Nieves, G. Franchy and A. Ariza who collected samples, often under severe weather conditions. This work was supported by the Canary Government (ACIISI) through a PhD fellowship to I. Herrera and projects Lucifer [CTM200803538/MAR] and Mafia [CTM2012-39587] from the Spanish Ministry of Economy and Competitiveness. Chapter 3 ! 96 References Arar, E.J., Collins, G.B., 1997. Method 445.0. In vitro determination of chlorophyll a and pheophytin a in marine and freshwater algae by fluorescence. U.S. Environmental Protection Agency, Cincinnati, OHIO. Arístegui, J., Hernández-León, S., Montero, M.F., Gómez, M., 2001. The seasonal planktonic cycle in coastal waters of the Canary Islands. Sci. Mar. 65, 51-58. Arístegui, J., Barton, E.D., Alvarez-Salgado, X.A., Santos, A.M.P., Figueiras, F.G., Kifani, S., Hernández-León, S., Mason, E., Machu, E., Demarcq, H., 2009. Sub-regional ecosystem variability in the Canary Current upwelling. Prog. Oceanogr. 83, 33-48. Benavides, M., Arístegui, J., Agawin, N.S.R., López Cancio, J., Hernández-León, S., 2013. Enhancement of nitrogen fixation rates by unicellular diazotrophs versus Trichodesmium after a dust deposition event in the Canary Islands. Limnol. Oceanogr. 58, 267-275. Cianca, A., Helmke, P., Mouriño, B., Rueda, M.J., LLinás, O., Neuer, S., 2007. Decadal analysis of hydrography and in situ nutrient budgets in the western and eastern North Atlantic subtropical gyre. J. Geophys. Res. Oceans. 112 Cropper, T.E., Hanna, E., Bigg, G.R., 2014. Spatial and temporal seasonal trends in coastal upwelling off Northwest Africa,1981–2012. Deep-Sea Res. Part I 86, 94-111. De León, A.R., Braun, J.G., 1973. Ciclo anual de la producción primaria y su relación con los nutrientes en aguas Canarias. Bol. Inst. Esp. Oceanogr. 167, 3-24. Demarcq, H., 2009. Trends in primary production, sea surface temperature and wind in upwelling systems (1998-2007). Prog. Oceanogr. 83, 376-385. Chapter 3 ! 97 Duarte, C.M., Dachs, J., Llabres, M., Alonso-Laita, P., Gasol, J.M., Tovar-Sánchez, A., Sañudo-Wilhemy, S., Agustí, S., 2006. Aerosol inputs enhance new production in the subtropical Northeast Atlantic. J. Geophys Res. 111, G04006. Franchy, G., Ojeda, A., López-Cancio, J., Hernández-León, S., Submitted. Plankton community response to Saharan dust fertilization in subtropical waters off the Canary Islands. Giovagnetti, V., Brunet, C., Conversano, F., Tramontano, F., Obernosterer, I., Ridame, C., Guieu, C., 2012. Assessing the role of dust deposition on phytoplankton ecophysiology and succession in a low-nutrient low-chlorophyll ecosystem: a mesocosm experiment in the Mediterranean Sea. Biogeosciences 9, 19199-19243. Harrison, W.G., Arístegui, J., Head, E.J.H., Li, W.K.W., Longhurst, A.R., Sameoto, D.D., 2001. Basin-scale variability in plankton biomass and community metabolism in the sub-tropical North Atlantic Ocean. Deep-Sea Res. Part II. 48, 2241-2269. Hernández-León, S., 1998. Annual cycle of epiplanktonic copepods in Canary Island waters. Fish Oceanogr. 7, 252-257. Hernández-León, S., Almeida, C., Bécogneé, P., Yebra, L., Arístegui, J., 2004. Zooplankton biomass and indexes of grazing and metabolism during a late winter bloom in subtropical waters. Mar. Biol. 145, 1191-1200. Hernández-León, S., Almeida, C., Yebra, L., Aristegui, J., 2002. Lunar cycle of zooplankton biomass in subtropical waters: biochemical implications. J. Plankton Res. 24, 935-939. Hernández-León, S., Almeida, C., Yebra, L., Arístegui, J., Fernández de Puelles, M.L., García-Braun, J., 2001. Zooplankton abundance in subtropical waters: Is there a lunar cycle?. Sci. Mar. 65, 59-63. Chapter 3 ! 98 Hernández-León, S., Franchy, G., Moyano, M., Menéndez, I., Schmoker, C. and Putzeys, S., 2010. Carbon sequestration and zooplankton lunar cycles: Could we be missing a major component of the biological pump?. Limnol. Oceanogr. 55, 2503-2512. Huskin, I., Anadón, R., Woodd-Walker, R.S., Harris, R.P., 2001. Basin-scale latitudinal patterns of copepod grazing in the Atlantic Ocean. J. Plankton Res. 23, 1361-1371. Kenner, R., Ahmed, S., 1975. Measurements of electron transport activities in marine phytoplankton. Mar. Biol. 33, 119-127. López Cancio, J., Castellano, V., Hernández, M.C., Bethencourt, R.G., Ortega, E.M., 2008. Metallic species in atmospheric particulate matter in Las Palmas de Gran Canaria. J. Hazard. Mater. 160, 521-528. Lovegrove, T., 1966. The determination of the dry weight of plankton and the effect of various factors on the values obtained. In: Barnes H (ed) Some contemporary studies in marine science. Allen and Unwin, London. pp 429-467. Lowry, P.H., Rosenbrough, N.J., Farr, A.L., Randall, R.J., 1951. Protein measurement with a Folin phenol reagent. J. Biol Chem. 193, 265-275. Moyano, M., Hernández-León, S., 2011. Interannual and seasonal variations on the larval fish assemblages in an oceanic island in the NE Atlantic. Mar. Biol. 158, 257-273. Moyano, M., Rodriguez, J.M., Hernández-León, S., 2009. Larval fish abundance and distribution during the late winter bloom off Gran Canaria Island, Canary Islands. Fish Oceanogr. 18, 51-61. Neuer, S., Cianca, A., Helmke, P., Freudenthal, T., Davenport, R., Meggers, H., Knoll, M., Santana-Casiano, J.M., Gonzalez-Davila, M., Rueda, M.J., Llinas, O., 2007. Biogeochemistry and hydrography in the eastern subtropical North Atlantic gyre. Results from the European time-series station ESTOC. Prog. Oceanogr. 72, 1-29. Chapter 3 ! 99 Packard, T.T., Healy, M.L., Richards, F.A., 1971. Vertical distribution of the activity of the respiratory electron transport system in marine plankton. Limnol. Oceanogr. 16, 60-70. Packard, T.T., Devol, A., King, F., 1975. The effect of temperature on the respiratory electron transport system in marine plankton. Deep-Sea Res. 22, 237-249. Parsons, T.R., Maita, Y., Lalli, C.M., 1984. A Manual of Chemical and Biological Methods for Seawater Analysis. Pergamon Press, Oxford, 173 pp. Rutter, W.J., 1967. Protein determinations in embryos. In: Methods in Developmental Biology. Wittand F.H., Wessels N.K. (eds.). Academy Press, New York. pp. 681-684. Ryther, J.H., Menzel, D.W., 1960. The seasonal and geographical range of primary production in the western Sargasso Sea. Deep-Sea Res. 6, 235-238. Schmoker, C., Arístegui, J., Hernández-León, S., 2012. Planktonic biomass variability during a late winter bloom in the subtropical waters off the Canary Islands. J. Mar. Syst. 95, 24-31. Schmoker, C., Hernández-León, S., 2013. Stratification effects on the plankton of the subtropical Canary Current. Prog. Oceanogr. 119, 24-31. UNESCO. 1968. Zooplankton sampling. Oceanographic Methods, vol.2, UNESCO, Paris, 174 pp. Welschmeyer, N.A., Lorenzen, C.A., 1985. Chlorophyll budgets: zooplankton grazing and phytoplankton growth in a temperate fjord and the Central Pacific Gyres. Limnol. Oceanogr. 30, 1-21. Woodd-Walker, R.S., Ward, P., Clarke, A., 2002. Large-scale patterns in diversity and community structure of surface water copepods from the Atlantic Ocean. Mar. Ecol. Prog. Ser. 236, 189-203. Chapter 3 ! 100 Yebra, L., Harris, R.P., Smith, T., 2005. Growth of Calanus helgolandicus later developmental stages (CV–CVI): comparison of four methods of estimation. Mar. Biol. 147, 1367-1375. Yebra, L., Hernández-León, S., 2004. Aminoacyl-tRNA synthetases activity as a growth index in zooplankton. J. Plankton Res. 26, 351-356. Yentsch, C.S., Menzel, D.W., 1963. A method for the determination of phytoplankton chlorophyll and phaeophytin fluorescence. Deep-Sea Res. 10, 221-231. ! Chapter 4 Potential grazing, respiration and growth of Euphausia distinguenda in relation to the oxygen minimum zone at the Eastern Tropical Pacific off Mexico Inma Herrera, Tarsicio Antezana, Alan Giraldo, Emilio Beier, Lidia Yebra, Santiago Hernández-León and Jaime Färber-Lorda Chapter 4 ! 108 among the average for each variable. 3. Results Temperature (0-500 m) varied between 27.7 and 10ºC, with a thermocline located between 70 and 100 m depth (Fig. 2). Figure 2. Vertical sections of temperature (ºC) and oxygen concentration (mL O2· L-1) from 0 to 500 m depth in each sampled transect. Chapter 4 ! 109 An abrupt decrease of the dissolved oxygen concentration was observed between 75 and 100 m depth. Oxygen concentration varied between 4.19 and 0.03 mL O2·L-1 in the water column (Fig. 2). There was a quite strong oxycline located between 100-200 m, beneath which the oxygen concentration was below 1 mL O2·L-1. Extreme hypoxic conditions (<0.1 mL O2·L-1) occurred between 150 and 500 m. Total euphausiid abundance showed a clear difference between day and night, with the mean value during the night (21:00-6:00 hrs) in the first 50 m being 0.40±0.37 ind·m-3 and a mean value of 2.30±2.71 ind·m-3 during the day (8:00-19:00 hrs) at different depths (Table 1, Fig. 4a). The percentage of species showed clearly that Euphausia distinguenda was the most abundant euphausiid species, between 40-100% of the sampled organisms (Table 1). Individual protein content showed a normal distribution (Fig. 3) with values varying from 0.13 to 1.89 mg prot · ind-1 (mean 0.50 ± 0.26). Individual protein biomass did not show statistical significant differences (p>0.05) between day (0.59±0.02 mg prot · ind-1) and night times (0.61±0.04 mg prot · ind-1) for each station (Fig. 4b). However, during nighttime, all organisms of E. distinguenda were found above the oxycline at 50 m, but through the day they were found in different layers (150 - 200, 200 – 300 and 300 – 400 m, Fig. 4a). Figure 3. Histogram of individual E. distinguenda biomass (mg prot · ind-1). Chapter 4 ! 110 Chapter 4 ! 111 Figure 4. Spatial distribution, 0-500 m depth, of a) average abundance (ind · m-3 ± SE from table 1); b) average individual biomass (mg prot · ind-1 ± SE); c) average specific gut fluorescence (ng pigment · mg prot-1 ± SE); d) average specific electron transport system activity (µL O2·mg prot-1·h-1 ± SE) and e) average specific aminoacyltRNA synthetases activity (nmol PPi·mg prot-1·h-1 ± SE), for each transect where N (night station), D (day station). Chapter 4 ! 112 Specific gut fluorescence (GF) vertical profiles did not show statistical significant differences between day and night periods (p>0.05; Fig. 4c). We observed similar values during night (23.47±3.48 ng pigment · mg prot−1) and day (22.48±3.05 ng pigment · mg prot−1). The vertical profile of average specific GF (Fig. 5a) did not show statistical significant differences and remained practically constant with depth. Pooling all stations together we found that the average GF also showed a high variability with time with not significant differences between day and night (p>0.05: Fig. 6a). ! Figure 5. Vertical profiles of a) average specific gut fluorescence (ng pigment·mg prot-1 ± SE); b) average specific electron transport system activity (µL O2·mg prot-1·h-1 ± SE); c) average specific aminoacyl-tRNA synthetases activity (nmol PPi·mg prot-1·h-1 ± SE) and oxygen concentration (mL O2·L-1). Full squares (night station), open squares (day station). ! ! Chapter 4 ! 113 On the contrary, specific ETS activity vertical profiles showed significant differences (p<0.05) between day and night periods (Fig. 4d). We observed higher values during the night (5.28±0.33 µL O2·mg prot-1·h-1) than by day (1.28±0.06 µL O2·mg prot-1·h-1). The vertical profile of average specific ETS activity (Fig. 5b) showed statistically significant differences (p<0.05). ETS decreased gradually with depth, similar to the oxygen concentration (mL O2·L-1). The variations over time of average ETS activities also showed the same pattern (Fig. 6b), presenting statistical significant differences (p<0.05). ! Figure 6. Time variation of a) average specific gut fluorescence (ng pigment·mg prot-1 ± SE); b) average specific electron transport system activity (µL O2·mg prot-1·h-1 ± SE); c) average specific aminoacyl-tRNA synthetases activity (nmol PPi·mg prot-1·h-1 ± SE); and oxygen concentration (mL O2·L-1) per time (h). Full squares (night station), open squares (day station). Chapter 4 ! 114 Similarly, specific AARS activity showed high values during the night (187.88±18.02 nmol PPi·mg prot-1·h-1) over 50 m, and lower values during the day (116.76±15.11 nmol PPi·mg prot-1·h-1, Fig. 4e) with statistical significant differences (p<0.05). The vertical profile of average specific AARS activity (Fig. 5c) also showed significant differences between 50 m and the deeper samples, decreasing gradually with depth. However, when pooling all stations together, the average specific AARS activities over time (Fig. 6c) presented a high variability, showing not significant differences between sampling times (p>0.05). 4. Discussion The spatial distribution of temperature and oxygen did not show differences along the transects, following the typical pattern of the Eastern Tropical Pacific off Mexico (Fiedler and Talley, 2006; Kessler, 2006). Euphausia distinguenda was the most abundant euphausiid species in the sampled area, as observed in previous studies by Ambriz-Arreol et al. (2012). Färber-Lorda (in prep.) observed clear vertical migrations of euphausiids during the same cruise. This is a common observation, as it is known that euphausiids have high swimming and strong vertical migration capacities, being able to reach 200 m depth in about one hour (Ritz, 1994). In the current study the values of specific GF suggested that E. distinguenda did not show significant grazing differences between day and night. Antezana (2002b) found slight or no differences in the stomach content of Euphausia mucronata collected in the OMZ during daytime and in surface layers at nighttime. In addition the GF values observed in E. distinguenda were lower than values found by Hernández-León et al. (2013) on Euphausia superba in a similar size range. Euphausiids show different feeding strategies and for instance, Euphausia pacifica changes their feeding preferences from phytoplankton to Chapter 4 ! 115 zooplankton during DVM (Nakagawa et al., 2001, 2002). Moreover, Hernández-León et al. (2001) suggested that E. superba fed on phytoplankton during the day, and change to carnivore feeding during nighttime. The rather low values of GF in E. distinguenda observed here should be related to the common observation of euphausiids feeding on microand mesozoplankton (Hernández-León et al., 2001, 2013). Our results also showed that potential respiration (ETS activity) was significantly higher at the surface and decreased when the oxygen concentration decreased with increasing depth. King et al. (1978) found similar results and suggested that it was due to a decrease of individual biomass. On the contrary, Teal and Carey (1967) suggested that metabolism depended on temperature; the organisms (Euphausia mucronata) decreased the respiration rate when temperature decreased. According to Torres and Childress (1983), DVM is energetically expensive. Staying in the cold deep during the day is associated with low food concentrations, low growth and low metabolism (Lampert, 1989), and low oxygen (Seibel, 2011). In addition, Teuber et al. (2013) also found that copepod ETS activities were higher above the OMZ and decreased in the core and below OMZ while increasing their anaerobic metabolism (lactate dehydrogenase activity, LDH). Recently, Seibel (2011) suggested that oceanic organisms (such as Euphausiids) could survive in the OMZ by two situations: First, they would suppress their metabolism, which would be very much like hibernation in other organisms (e.g. Dosidicus gigas, Euphausia eximia). Second, converting food into energy normally requires more oxygen concentration; however these organisms would use a different process, anaerobic glycolysis, allowing them to use only a low oxygen concentration. Seibel (2011) also found that these organisms could survive in hypoxic waters from hours up to days, using the oxygen available with anaerobic metabolic pathways. Studies about aerobic and anaerobic metabolic processes in crustaceans (Teuber et al., 2013; Yannicelli et al., 2013), medusae (Thuesen et al., 1994), jumbo squid, Dosidicus gigas Chapter 4 ! 116 (Rosa and Seibel, 2010), polychaete (Quiroga et al., 2007) showed that these organisms could survive in the OMZ by using anaerobic metabolic pathways. Anaerobic glycolysis involves transformation of glucose to pyruvate, and the further conversion from pyruvate to lactate. This pathway takes place in complete oxygen’s absence or in limited supply of it. For the anaerobic metabolic pathway is necessary less energy, only 2 ATP, whilst for the aerobic metabolic pathway are necessary 38 ATP molecules (Lenhinger, 1975, 1977). There are no previous studies about the growth rate of zooplankton related to the OMZ. Nevertheless, it is an important physiological process that might be affected by oxygen levels in water. Specific AARS activity in E. distinguenda showed a similar relationship with the oxygen concentration than the ETS. This suggests that the AARS of E. distinguenda was also conditioned by the OMZ. The AARS enzymes catalyze the first step of the protein synthesis. The contribution that protein synthesis makes to the oxygen consumption of different marine fish species has been estimated in previous works (Houlihan, 1991; Smith and Houlihan, 1995). The enzymatic activities rely on ATP production. Not enough ATP production due to low oxygen concentration produced low values of protein synthesis rate (AARS activity) and consequently reduced translation step (Anderson et al., 2009), supporting the diminished spAARS activities observed for E. distinguenda within the OMZ. Translation is the second step of protein synthesis. Messenger RNA (mRNA) produced by transcription is decoded by a ribosome complex to produce a specific protein (Crick, 1958). Anderson et al. (2009) suggested that a translational suppression in hypoxia conditions would inhibit or reduce the protein synthesis of the organism, as well as the AARS activity. Nevertheless, when the oxygen concentration starts to increase the protein synthesis recovers its levels, as observed by Koumenis et al. (2002). This would allow E. distinguenda to rapidly resume their protein synthesis activity when migrating to oxygenate waters above the OMZ. Chapter 4 ! 117 In summary, our results suggest that the oxygen minimum zone conditions the euphausiid physiological processes. Both proxies for respiration and growth rates were significantly reduced within the OMZ. However, the metabolism of euphausiids might be effective using both aerobic and anaerobic pathways, thus allowing this species to inhabit within the OMZ during daytime. Further research would be needed to fully comprehend the effects of hypoxia on the in situ aerobic and anaerobic metabolism in euphausiids and its relationships with the mechanisms regulating respiration and growth of migrant organisms in the OMZ. Acknowledgments This work was supported by the Canary Government (ACIISI) through a PhD fellowship to I. Herrera and projects Procomex (CONACYT # 2006-62152), from the National Council of Science and Technology of México, Lucifer (CTM2008-03538/MAR) and Mafia (CTM2012-39587) from the Spanish Ministry of Economy and Competitiveness. ! Chapter 5 ! 125 Abstract The search for an index of growth in zooplankton and fish larvae has been a challenge for decades. In order to match physical, chemical, or even other biological measurements, the actual estimation of growth is rather tedious to carry out on board oceanographic vessels. Therefore, different enzymatic (e.g., DNA polymerase, aspartate transcarbamylase, and aminoacyl-tRNA synthetases activities) and non-enzymatic (e.g., radiochemical methods, RNA/DNA ratio among others) were assayed and correlated to growth with quite different results. Here, we review the experiments performed to relate the activity of the enzyme aminoacyl-tRNA synthetases (AARS) to growth rates in freshwater (Daphnia magna) and marine (Calanus finmarchicus, Calanus helgolandicus, Oithona davisae, Euphausia superba, Paracartia grani) zooplankton, and fish larvae (Clupea harengus). In order to further investigate this relationship between AARS activity and growth rate, we allowed to grow Sparus aurata larvae to grow at a constant rate in order to account for differences in specific AARS activities during their development. The result of these experiments showed quite high enzymatic values during the first phases of development, corresponding to low growth rates. The same pattern was observed in other fish larvae (Clupea harengus) as well as in different species of copepods. High protein degradation during the first phases of development is suggested to promote the mismatch between growth and specific AARS activity. However, these two parameters were significantly correlated, thereafter shedding some light to the use of these enzymes activity as a proxy for growth rate. Keywords: AARS, growth, zooplankton Chapter 5 ! 126 1. Introduction Zooplankton growth estimation in nature is a rather difficult task because the assessment of changes in body weight with time need long incubations (days) under simulated conditions of temperature and food. Those conditions are quite difficult to maintain in the laboratory. Moreover, there is a requirement for a large collection of animals in order to prolong the experiment to promote statistical confidence. Those problems are almost irresolvable in oceanography for the routine work at sea. Therefore, the search for a proxy of zooplankton growth has been a challenge for decades. The use of the egg production method, although it gives valuable information, is a poor tool because of the problems of relating body weight changes with reproduction of adult females. Growth rates for females and other naupliar and copepodite stages are quite different for a given species (Hutchings et al., 1995). The artificial cohort (Kimmerer and McKinnon, 1987) and the physiological (Le Borgne, 1982) methods also require long and tedious incubations, preventing their use in oceanography in order to match physical and chemical data output. Several methods were assayed to find an index of growth in zooplankton. The measurement of RNA and DNA was the first attempt to develop a suitable index (Sutcliffe, 1970; Dagg and Littlepage, 1972) and it has been in use until present with different results. In general, this ratio was found to be a poor predictor of growth (Ota and Landry, 1984, Anger and Hirche, 1990, Wagner et al., 2001). However, some authors found predictive relationships in fishes (Peck et al., 2003) and crustaceans (Yebra et al., 2011). However, the latter author observed that this relationship differed between naupliar and copepodite stages, precluding its use in mixed populations. The release and degradation of chitobiase have also been proposed as a growth index (Oosterhuis et al., 2000; Sastri and Roff, 2000) showing good relationships and being quite Chapter 5 ! 127 sensitive. However, organisms cannot be preserved for later analysis and the procedure is not routinely used in oceanography because it is rather tedious for the work at sea. Sapienza and Mague (1979) proposed the use of the activity of the enzyme DNA polymerase, and concomitantly Bergeron and Buestel (1979) the measurement of aspartate transcarbamylase (ATC). Unfortunately, the former enzyme was not the subject of later work and ATC activity also gave some contradictory results. Although Bergeron and Alayse-Danet (1981) and Bergeron (1982) found strong relationships between growth and ATC in the mantle and gonad of mollusks and fish larvae, Alayse-Danet (1980) and Hernández-León et al. (1995) found poor relationships in Artemia and copepods. The enzymatic approach in oceanography has some drawbacks as activities are measured at cell substrate saturation, something not expected to occur in nature. The results found in other enzymatic approaches such as the electron transfer system (ETS) and glutamate dehydrogenase (GDH) activities as proxies of respiration and ammonia excretion (see Hernández-León and Gómez, 1996, Hernández-León and Torres, 1997) were quite similar to the one found by Hernández-León et al. (1995) for ATC activity. Different relationships appeared depending on the nutritional status of organisms in the environment, therefore influencing the cell substrate saturation level. Yebra and Hernández-León (2004) proposed the measurement of the activity of the enzymes aminoacyl-tRNA synthetases (AARS) as index of Daphnia magna growth. Since this seminal paper, other calibrations between zooplankton growth and AARS activity were obtained in Calanus helgolandicus (Yebra et al., 2005), Calanus finmarchicus (Yebra et al., 2006), Euphausia superba (Guerra, 2006), Oithona davisae (Yebra et al., 2011), Paracartia grani (Herrera et al., 2012), and the larvae of Clupea harengus (Herrera et al., Chapter 2 in this volume). Different relationships were also observed in those papers but the latter authors suggested that degradation of proteins during starvation or the effect of fatty acids on the Chapter 5 ! 128 measurement of AARS activity could promote the absence of a close relationship with growth. Rather high AARS activity values were found at low growth rates but also those large values were observed in early stages of copepods. These organisms could promote an important synthesis of proteins as observed from their high AARS activity, but these proteins are also metabolized and not used to build body structures. Alternatively, oxidation of fatty acids could produce pyrophosphate (PPi), which is the end product of the reaction in the AARS assay, thus interfering the enzymatic activity assessment. Thus, the importance of young individuals affecting the relationship between growth and AARS activity should be confirmed. In the present work, we review the existing calibrations between growth rates and AARS activity after a decade of effort. Because of the high activities at low growth rates observed in previous studies (see Herrera et al., 2012; Herrera et al., Chapter 2 in this volume), we seek to test if similar results were observed in previous calibrations. We also test experimentally the latter observation. We allowed fish larvae to grow at high food levels, at relatively high and constant growth rates in order to evidence the increased activities in small individuals as observed in previous studies. 2. Material and methods We reviewed the available relationships between growth rates and specific AARS activities for zooplankton (cladocerans and copepods) and fish larvae (see Introduction). AARS activities were always measured following the method of Yebra and Hernández-León (2004) and Yebra et al. (2011) recalculated using the equation given by Herrera et al. (Chapter 3 in this volume). Individual biomass is always expressed as protein content, as measured using the method of Lowry et al. (1951) adapted for micro-assay by Rutter (1967). Chapter 5 ! 129 We also present here additional experiments using fish larvae (Sparus aurata) in order to test the variability of AARS activity in organisms growing at almost constant growth rates. Larvae of S. aurata were reared in the laboratory at 22±1oC and 24 h photoperiod (100-500 lux) under high food concentration. Three days after hatching, near complete yolk sac consumption, rotifers (Brachiounus plicatilis) were provided as food for the fish larvae at saturated densities. Artemia nauplii were provided after day 16 jointly with rotifers. Fish larvae, rotifers and Artemia were cultured in phytoplankton medium to provide a rich food environment in order to attain high growth rates (Parra and Yúfera, 2001). Every 1-3 days three to six fish larvae were gently captured from the tank and frozen in liquid nitrogen (-196oC) for later analysis of individual biomass and specific AARS activity as the proxy for growth rate. AARS activity was also measured following the method of Yebra and Hernández-León (2004), and using the equation given by Herrera et al. (Chapter 3 in this volume). Individual biomass as dry weight was calculated from a lengthweight relationship. 3. Results A review of literature values of growth versus specific AARS activity showed a rather high scatter of data (Fig.1), and a significant but poor predictive regression among those parameters (growth= 0.040+0.0019·spAARS; r2= 0.346; p< 0.001). Chapter 5 ! 130 Figure 1. Relationship between growth rate (d-1) and specific AARS activity (nmol PPi·mg prot-1·h-1) in the different calibrations performed taken form the literature. Taking into account the experimental food level used in the experiments (as stated in the original publications), no relationship was observed between growth rates and specific AARS activity (Fig. 2). Nevertheless, low and medium food was only 20% of data precluding a thorough analysis. No pattern was also observed between low-medium and high food concentration. Chapter 5 ! 131 Figure 2. Growth rate (d-1) versus specific AARS activity (nmol PPi·mg prot-1·h-1) at low, medium, and high food levels. However, differences were found in relation to species and/or experiments carried out. We compared the slopes of the significant relationships published between growth and specific AARS activity. The relationships for C. finmarchicus, P. grani nauplii under food saturation and E. superba were significantly similar (ANOVA, p>0.05) and grouped together showed a significant positive correlation (r2=0.937; p<0.0001). Also the relationships for C. helgolandicus, O. davisae and C. harengus larvae were similar (ANOVA, p>0.05) and together showed a positive correlation between growth and AARS activity (r2=0.275; p<0.005), although the slope was lower. The slopes of the relationships for D. magna and P. Chapter 5 ! 132 grani nauplii at varying food concentrations were significantly different from the rest of experiments and were not merged with any of the former two groups (Fig. 3). Figure 3. Relationships found between growth rate (d-1) and specific AARS activity (nmol PPi·mg prot-1·h-1) after grouping significantly similar published calibrations. C.he.: Calanus helgolandicus, O.d.: Oithona davisae, C.ha.: Clupea harengus, C.f.: Calanus finmarchicus, E.s.: Euphausia superba, D.m.: Daphnia magna, P.g.: Paracartia grani under food saturation, P.g.F: Paracartia grani under varying food concentrations (relationship not shown in figure for clarity). In order to test the high AARS activity sometimes observed at low growth rates (e.g., Fig. 3), larvae of Sparus aurata were induced to grow at constant and near maximum rates in two experiments. Individual biomass of fish larvae increased along 26 days at g= 0.132 d-1 (r2=0.976; p<0.001) in experiment 1 (Fig. 4a), and at g= 0.139 d-1 (r2=0.975; p<0.001) for experiment 2 (Fig. 4b). AARS was measured in both experiments and despite the constant growth, quite high specific AARS activity values were observed during the first 12-15 days Chapter 5 ! 133 after hatching (Fig. 4). Thereafter, specific AARS activity became almost constant in both experiments. Small larvae (<100 µg dry weight·individual-1) showed the largest specific AARS activity values, having lower and rather constant values at higher individual biomass (Fig. 5). Figure 4. Individual biomass (µg dry weight·individual-1) and specific AARS activity (nmol PPi·mg prot-1·h-1) of Sparus aurata larvae during development. Observe the high specific AARS activities during the first 12-17 days of life in organisms <100 µg dry weight·individual-1.