sm80n2-4391

Photo-physiological performance and short-term acclimation of two coexisting macrophytes (Cymodocea nodosa and Caulerpa prolifera) with depth

Fernando Tuya, Séfora Betancor, Federico Fabbri, Fernando Espino, Ricardo Haroun

Grupo en Biodiversidad y Conservación, IU-ECOAQUA, Universidad de Las Palmas de Gran Canaria, 35017, Las Palmas de G.C., Canary Islands, Spain. E-mail: ftuya@yahoo.es

Summary: Marine macrophytes are vertically distributed according to their ability to optimize their photosynthetic performance. We assessed the photo-physiological performance of the seagrass Cymodocea nodosa and the green seaweed Caulerpa prolifera at varying depth at Gran Canaria Island (Canary Islands, eastern Atlantic). The biomass of C. nodosa decreases with depth, while the opposite occurs for C. prolifera. Photochemical responses of both macrophytes were measured in shallow (5 m) and deep (20 m) waters at two times via chlorophyll a fluorescence and internal content of photoprotective pigments and antioxidant activity. We additionally carried out a reciprocal transplant experiment by relocating shallow and deep vegetative fragments of both macrophytes to assess their short-term photo-physiological acclimation. Overall, C. nodosa behaves as a ‘light-plant’, including a larger optimum quantum yield and ETRmax under scenarios of high photosynthetically active radiation and a larger antioxidant activity. In contrast, C. prolifera is a ‘shade-adapted’ plant, showing a larger carotene content, particularly in shallow water. Deep-water C. nodosa and C. prolifera are more photochemically efficient than in shallow water. The alga C. prolifera shows a rapid, short-term acclimation to altered light regimes in terms of photosynthetic efficiency. In conclusion, decreased light regimes favour the photosynthetic performance of the green alga when both species coexist.

Keywords: macroalgae; seagrass; photoacclimation; photo-biology; photoprotection; Atlantic Ocean.

Rendimiento foto-fisiológico y aclimatación a corto plazo de dos macrófitos coexistentes (Cymodocea nodosa y Caulerpa prolifera) con la profundidad

Resumen: Los macrófitos marinos se distribuyen verticalmente de acuerdo a sus capacidades para optimizar su rendimiento fotosintético. Evaluamos el rendimiento foto-fisiológico de la fanerógama marina Cymodocea nodosa y el alga verde Caulerpa prolifera a diferentes profundidades en la isla de Gran Canaria (Islas Canarias, Atlántico oriental). La biomasa de C. nodosa decrece con la profundidad, mientras que para C. prolifera ocurre lo contrario. Las respuestas foto-químicas de ambos macrófitos se midieron en aguas someras (5 m) y profundas (20 m), en dos tiempos, a través de la fluorescencia de la clorofila a y los contenidos internos en pigmentos fotoprotectores y la actividad antioxidante. Además, ejecutamos un experimento de trasplante recíproco, recolocando fragmentos vegetativos de ambos macrófitos entre aguas someras y profundas para determinar su aclimatación a corto plazo. En general, C. nodosa se comporta como “planta de sol”, con mayor rendimiento cuántico óptimo y ETRmax bajo escenarios de alta radiación PAR y mayor actividad antioxidante. Contrariamente, C. prolifera es una “planta de sombra”, mostrando mayor cantidad de carotenos, en particular a poca profundidad. Ejemplares profundos de ambos macrófitos son más eficientes foto-químicamente que los de aguas someras. El alga C. prolifera muestra una aclimatación rápida, a corto plazo, de su eficiencia fotosintética ante cambios en el régimen luminoso. En conclusión, regímenes depauperados lumínicamente favorecen el rendimiento fotosintético del alga verde.

Palabras clave: macroalgas; angiospermas; foto-aclimatación; foto-biología; fotoprotección; océano Atlántico.

Citation/Como citar este artículo: Tuya F., Betancor S., Fabbri F., Espino F., Haroun R. 2016. Photo-physiological performance and short-term acclimation of two coexisting macrophytes (Cymodocea nodosa and Caulerpa prolifera) with depth. Sci. Mar. 80(2): 247-259. doi: http://dx.doi.org/10.3989/scimar.04391.07A

Editor: E. Ballesteros.

Received: December 18, 2015. Accepted: March 15, 2016. Published: June 8, 2016.

Copyright: © 2016 CSIC. This is an open-access article distributed under the Creative Commons Attribution-Non Commercial Lisence (by-nc) Spain 3.0.

Contents

Summary
Resumen
Introduction
Materials and methods
Results
Discussion
Acknowledgements
References
Appendices

INTRODUCTIONTop

A variety of marine macrophytes (e.g. seagrasses and macroalgae) typically coexist in the same habitat; their distribution, however, may fluctuate under varying environmental conditions (e.g. light, nutrients), operating at a range of spatial and temporal scales (Lüning 1990Lüning K. 1990. Seaweeds: their environment, biogeography, and ecophysiology. Wiley-Interscience, New York, NY.). Marine macrophytes acclimate and adapt their photosynthetic apparatus to prevailing irradiance conditions (Betancor et al. 2015Betancor S., Domínguez B., Tuya F., et al. 2015. Photosynthetic performance and photoprotection of Cystoseira humilis (Phaeophyceae) and Digenea simplex (Rhodophyceae) in an intertidal rock pool. Aquat. Bot. 121: 16-25.), which define species’ niche requirements, including photoprotective mechanisms under high levels of UV and photosynthetically active radiation (PAR) (Häder et al. 1997Häder D.P., Porst M., Herrmann H., et al. 1997. Photosynthesis of Mediterranean green alga Caulerpa prolifera measured in the field under solar irradiation. J. Photoch. Photobio. B 37: 66-73.). In turn, zonation patterns (or vertical distribution) of marine macrophytes are often related to their ability to resist high radiation stress (Hanelt 1998Hanelt D. 1998. The capability for dynamic photoinhibition in Arctic macroalgae is related to their depth distribution. Mar. Biol. 131: 361-369.), e.g. upper-shore species are more resistant to elevated solar UV. In addition to their physiological responses, marine macrophytes show a certain degree of morphological flexibility that reflect long-term adaptations to varying environmental scenarios, including decreased light with depth in subtidal habitats (Olesen et al. 2002Olesen B., Enríquez S., Duarte C.M., et al. 2002. Depth-acclimation of photosynthesis, morphology and demography of Posidonia oceanica and Cymodocea nodosa in the Spanish Mediterranean Sea. Mar. Ecol. Prog. Ser. 236: 89-97.).

Under varying environmental scenarios, ecophysiological approaches that integrate estimates of light absorption efficiency, pigment contents and mechanisms to dissipate excess energy (Hanelt 1998Hanelt D. 1998. The capability for dynamic photoinhibition in Arctic macroalgae is related to their depth distribution. Mar. Biol. 131: 361-369.) provide useful insight to assess changes in the distribution of marine macrophytes. This is particularly pertinent under scenarios of global change, in which the intensity and frequency of anthropogenic perturbations are increasing. For example, increasing turbidity in coastal areas alters the dominance and functioning of seascapes dominated by submersed vegetation, particularly those constituted by marine angiosperms (seagrasses) (Duarte et al. 2008Duarte C.M., Dennison W.C., Orth R.J., et al. 2008. The charisma of coastal ecosystems. Estuar. Coasts 31: 233-238., Silva et al. 2013Silva J., Barrote J., Costa M.M., et al. 2013. Physiological responses of Zostera marina and Cymodocea nodosa to light-limitation stress. PLoS ONE 8(11): e81058.). Understanding the physiological response of seagrasses and accompanying seaweeds to altered light regimes is therefore important (Collier et al. 2012Collier C.J., Waycott M., Giraldo Ospina A. 2012. Responses of four Indo-West Pacific seagrass species to shading. Mar. Poll. Bull. 65: 342-354.).

Cymodocea nodosa (Ucria) Ascherson is a seagrass distributed across the entire Mediterranean Sea and the contiguous eastern Atlantic coasts, including the oceanic archipelagos of Madeira and the Canary Islands (Tuya et al. 2013aTuya F., Hernández-Zerpa H., Espino F., et al. 2013a. Drastic decadal decline of the seagrass Cymodocea nodosa at Gran Canaria (Eastern Atlantic): interactions with the green alga Caulerpa prolifera. Aquat. Bot. 105: 1-6.). Meadows constituted by C. nodosa are found on shallow sandy substrates throughout the Canary Islands (Barberá et al. 2005Barberá C., Tuya F., Boyra A., et al. 2005. Spatial variation in the structural parameters of Cymodocea nodosa seagrass meadows in the Canary Islands: a multiscaled approach. Bot. Mar. 48: 122-126.), supporting diverse invertebrate and fish assemblages (Tuya et al. 2006Tuya F., Martín J.A., Luque A. 2006. Seasonal cycle of a Cymodocea nodosa seagrass meadow and of the associated ichthyofauna at Playa Dorada (Lanzarote, Canary Islands, eastern Atlantic). Cien. Mar. 32: 695-704., Gardner et al. 2013Gardner A., Tuya F., Lavery P.S., et al. 2013. Habitat preferences of macroinvertebrate fauna among seagrasses with varying structural forms. J. Exp. Mar. Biol. Ecol. 439: 143–151., Tuya et al. 2013bTuya F., Viera-Rodríguez M.A., Guedes R., et al. 2013b. Seagrass responses to nutrient enrichment depend on clonal integration, but not flow-on effects on associated biota. Mar. Ecol. Prog. Ser. 490: 23-35.). Across its distribution range, declines in the presence of C. nodosa may result in increases in the biomass of green algae, particularly those of the genus Caulerpa, including native (Lloret et al. 2005Lloret J., Marin A., Marin-Guirao L., et al. 2005. Changes in macrophytes distribution in a hypersaline coastal lagoon associated with the development of intensively irrigated agriculture. Ocean. Coast. Manage. 48: 828-842., García-Sánchez et al. 2012García-Sánchez S., Korbee N., Pérez-Ruzafa I.M., et al. 2012. Physiological response and photoacclimation capacity of <em>Caulerpa prolifera</em> (Forsskål) J.V. Lamouroux and <em>Cymodocea nodosa</em> (Ucria) Ascherson meadows in the Mar Menor lagoon (SE Spain). Mar. Environ. Res. 79: 37-47.) and non-native species (Ceccherelli and Cinelli 1997Ceccherelli G., Cinelli F. 1997. Short-term effects of nutrient enrichment of the sediment and interactions between the seagrass Cymodocea nodosa and the introduced green alga Caulerpa taxifolia in a Mediterranean bay. J. Exp. Mar. Biol. Ecol. 217: 165-177.). Species within the genus Caulerpa usually show rapid growth in high nutrient conditions (Lapointe et al. 2005Lapointe B.E., Barile P.J., Littler M.M., et al. 2005. Macroalgal blooms on southeast Florida coral reefs: II. Cross-shelf discrimination of nitrogen sources indicates widespread assimilation of sewage nitrogen. Harmful Algae 4: 1106-1122.). Caulerpa prolifera (Forsskål) J.V. Lamouroux is a native species from continental Europe, occurring in the Mediterranean Sea and the adjacent Atlantic Ocean. This coenocytic alga is a slow-growing, nitrophilic species with considerable morphological plasticity (Collado-Vides 2002Collado-Vides L. 2002. Morphological plasticity of Caulerpa prolifera (Caulerpales, Chlorophyta) in relation to growth form in a coral reef lagoon. Bot. Mar. 45: 123-129., Malta et al. 2005Malta E.J., Ferreira D.G., Vergara J.J., et al. 2005. Nitrogen load and irradiance affect morphology, photosynthesis and growth of Caulerpa prolifera (Bryopsidales, Chlorophyta). Mar. Ecol. Prog. Ser. 298: 101-114.), which may be connected with a large physiological plasticity when environmental conditions change (Malta et al. 2005Malta E.J., Ferreira D.G., Vergara J.J., et al. 2005. Nitrogen load and irradiance affect morphology, photosynthesis and growth of Caulerpa prolifera (Bryopsidales, Chlorophyta). Mar. Ecol. Prog. Ser. 298: 101-114.). This alga has a prostrate axis (stolon) with rhizoids and upright axes (fronds) that are potentially independent units; the whole plant can regenerate after a frond or stolon is lost (Collado-Vides 2002Collado-Vides L. 2002. Morphological plasticity of Caulerpa prolifera (Caulerpales, Chlorophyta) in relation to growth form in a coral reef lagoon. Bot. Mar. 45: 123-129.). In the Canary Islands, the presence of C. nodosa has decreased in the last two decades, particularly in certain areas, correlating with a significant increase in the abundance of C. prolifera (Tuya et al. 2013aTuya F., Hernández-Zerpa H., Espino F., et al. 2013a. Drastic decadal decline of the seagrass Cymodocea nodosa at Gran Canaria (Eastern Atlantic): interactions with the green alga Caulerpa prolifera. Aquat. Bot. 105: 1-6., Tuya et al. 2014Tuya F., Ribeiro-Leite L., Arto-Cuesta N., et al. 2014. Decadal changes in the structure of Cymodocea nodosa seagrass meadows: Natural vs. human influences. Estuar. Coast. Shelf Sci. 137: 41-49.). In this region, C. nodosa typically inhabits shallower waters than C. prolifera, though the two macrophytes can be found intermixed (Tuya et al. 2013aTuya F., Hernández-Zerpa H., Espino F., et al. 2013a. Drastic decadal decline of the seagrass Cymodocea nodosa at Gran Canaria (Eastern Atlantic): interactions with the green alga Caulerpa prolifera. Aquat. Bot. 105: 1-6.). In the Mar Menor (Mediterranean Sea), C. nodosa is mainly restricted to shallow-water areas (<1 m), while slightly deeper areas (2-5 m) are dominated by mono specific meadows of C. prolifera (García-Sánchez et al. 2012García-Sánchez S., Korbee N., Pérez-Ruzafa I.M., et al. 2012. Physiological response and photoacclimation capacity of Caulerpa prolifera (Forsskål) J.V. Lamouroux and Cymodocea nodosa (Ucria) Ascherson meadows in the Mar Menor lagoon (SE Spain). Mar. Environ. Res. 79: 37-47.). It has been demonstrated that C. nodosa typically behaves as a ‘light-plant’, whereas C. prolifera behaves as a ‘shade-plant’, based on the differences in the way PAR is absorbed, the pigment composition, and the subsequent physiological mechanisms for dissipating excess light energy between the two macrophytes (Malta et al. 2005Malta E.J., Ferreira D.G., Vergara J.J., et al. 2005. Nitrogen load and irradiance affect morphology, photosynthesis and growth of Caulerpa prolifera (Bryopsidales, Chlorophyta). Mar. Ecol. Prog. Ser. 298: 101-114., García-Sánchez et al. 2012García-Sánchez S., Korbee N., Pérez-Ruzafa I.M., et al. 2012. Physiological response and photoacclimation capacity of Caulerpa prolifera (Forsskål) J.V. Lamouroux and Cymodocea nodosa (Ucria) Ascherson meadows in the Mar Menor lagoon (SE Spain). Mar. Environ. Res. 79: 37-47.).

Previous studies have demonstrated morphological plasticity with depth of both C. nodosa (Olesen et al. 2002Olesen B., Enríquez S., Duarte C.M., et al. 2002. Depth-acclimation of photosynthesis, morphology and demography of Posidonia oceanica and Cymodocea nodosa in the Spanish Mediterranean Sea. Mar. Ecol. Prog. Ser. 236: 89-97.) and C. prolifera (Collado-Vives 2002Collado-Vides L. 2002. Morphological plasticity of Caulerpa prolifera (Caulerpales, Chlorophyta) in relation to growth form in a coral reef lagoon. Bot. Mar. 45: 123-129.). In this study, we assessed the photo-physiological performance of both macrophytes between a shallow and a deep-water stratum (5 vs 20 m depth), which involve significant changes in light regimes. This bathymetric gradient is considerably larger than those previously considered to compare the photo-physiology of both C. nodosa (0.4 vs 3.8 m, Olesen et al. 2002Olesen B., Enríquez S., Duarte C.M., et al. 2002. Depth-acclimation of photosynthesis, morphology and demography of Posidonia oceanica and Cymodocea nodosa in the Spanish Mediterranean Sea. Mar. Ecol. Prog. Ser. 236: 89-97.; 0.5 vs 5 m, García-Sánchez et al. 2012García-Sánchez S., Korbee N., Pérez-Ruzafa I.M., et al. 2012. Physiological response and photoacclimation capacity of Caulerpa prolifera (Forsskål) J.V. Lamouroux and Cymodocea nodosa (Ucria) Ascherson meadows in the Mar Menor lagoon (SE Spain). Mar. Environ. Res. 79: 37-47.) and C. prolifera with depth (0.5 vs 5 m, García-Sánchez et al. 2012García-Sánchez S., Korbee N., Pérez-Ruzafa I.M., et al. 2012. Physiological response and photoacclimation capacity of Caulerpa prolifera (Forsskål) J.V. Lamouroux and Cymodocea nodosa (Ucria) Ascherson meadows in the Mar Menor lagoon (SE Spain). Mar. Environ. Res. 79: 37-47.). We followed a two-step strategy. First, the photo-physiological performance—here quantified through photochemical responses via in vivo chlorophyll a fluorescence of photosystem II, as well as the contents in carotenes (widely recognized photoprotective pigments) and antioxidant activity—of the two macrophytes was directly measured from shallow and deep-water specimens at two times. Second, we carried out a reciprocal transplant experiment on the same two occasions by relocating shallow (5 m) and deep (20 m) vegetative fragments of both macrophytes. Subsequently, the photo-physiological performance of both macrophytes was assessed as an indicator of short-term acclimation to chronic changes in light regimes. Integration of results from both approaches provides insight on the photophysiological performance of these two co-occurring macrophytes and potential responses under altered light regimes.

MATERIALS AND METHODSTop

Reciprocal transplants: field work

This study was performed at Gran Canaria Island, a subtropical island in the centre of the Canary Islands (eastern Atlantic, 28°N). Sea surface temperature typically varies between 18°C in winter and 24ºC in summer (Tuya et al. 2014Tuya F., Ribeiro-Leite L., Arto-Cuesta N., et al. 2014. Decadal changes in the structure of Cymodocea nodosa seagrass meadows: Natural vs. human influences. Estuar. Coast. Shelf Sci. 137: 41-49.). Vegetative fragments of C. nodosa (horizontal rhizomes ca. 10-15 cm long, including 5-7 shoots and associated leaves) and ramets of C. prolifera, including stolons, rhizoids and fronds (ca. 20-25 cm long), were collected by hand by SCUBA divers at 5 and 20 m depth at Gando Bay (27°55′49″N, 15°22′1″W). Neither species is typically found in shallower water in the study region, which is exposed to large oceanic swells that prevent long-term persistence. Collections of both macrophytes were immediately used to assess photochemical responses, as a way to infer their physiological status (see below). On the day of collection, we additionally carried out a reciprocal transplant experiment, in which 10-15 C. nodosa and C. prolifera vegetative fragments collected at 5 m were transplanted at 20 m depth and vegetative fragments collected at 20 m were transplanted at 5 m depth (hereafter called ‘allochthonous’ transplants). To control for potential artefacts during manipulations, C. nodosa and C. prolifera fragments from both depths were re-transplanted at the same depth (i.e. procedural controls, hereafter called ‘autochthonous’ transplants). All transplants were then subjected to the same manipulations. During transplants, the below-ground compartments of both macrophytes were gently buried inside the sediment by hand; to facilitate retention of below-ground tissues, plastic meshes covering horizontal rhizomes and stolons were secured to the bottom by metal stakes (Fig. 1). In all cases, the erect parts of both macrophytes (seagrass leaves and C. prolifera fronds) come out from the mesh to capture light with minimum perturbation. This experimental approach was repeated twice to evaluate the temporal consistency of results; the first started on 6 February 2014 and the second started on 15 May 2014. The duration of each transplant set varied slightly as a result of logistical constraints; on the first occasion (February 2014), transplants were maintained for 11 days; on the second occasion (May 2014), transplants were maintained for 14 days. During both periods, the amount of PAR reaching the bottom was measured by using Onset HOBO U12 4-channel external data loggers at 5 and 20 m depth, respectively.

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Fig. 1. – Experimental transplantation of vegetative fragments of C. nodosa and C. prolifera on a shallow-water soft bottom (5 m depth) at Gando Bay (Gran Canaria Island).

Bathymetric changes in macrophyte distribution and environmental drivers

To facilitate further interpretation of results, we described changes in the biomass of both C. nodosa and C. prolifera with depth at the study site. Samples (n=5) were collected through a 0.0125 m–2 core at 5, 10, 15 and 20 m in Gando Bay at both sampling times. All vegetation was dried (24 h at 70°C) and the dry weight was calculated. Additionally, sediment samples (n=2 cores, ca. 100 g) were collected, in February 2014, at 5, 10, 15 and 20 m to work out differences in the mean particle diameter (D50), the total N and P content and the organic matter content of sediments with depth. After thawing, sediment samples were sieved through a 0.5-mm sieve, and the fraction <0.5 mm was oven-dried at 90°C for 24 h. This fraction was then dry-sieved at 0.5 ϕ intervals, down to 1.0 ϕ (0.5 mm). The <0.5 mm fraction was freeze-dried and analysed on a Coulter LS130 laser sizer. The laser sizer results were combined with the dry sieve results to give the full particle size distribution. The method of Walkley and Black (1934)Walkley A., Black J.A. 1934. An examination of the Degtjareff method for determining soil organic matter and a proposed modification of the chromic titration method. Soil Sci. 37: 29-38. was used to calculate the organic matter content of sediments via rapid dichromate oxidation. Total N was determined following the Kjeldahl method (Bradstreet 1965Bradstreet R.B. 1965. The Kjeldahl method for organic Nitrogen. Academic Press, New York, 239 pp.) and total P was determined using a spectrophotometric method (Murphy and Riley 1962Murphy J., Riley J.P. 1962. A modified single solution method for the determination of phosphate in natural waters. Anal. Chem. Acta 27: 31-36.).

Photochemical responses

At the start (initial collections) and at the end of the transplantation experiments, between n=6 and 8 C. nodosa leaves (12-15 cm long with no necrosis signs) and n=6 and 8 C. prolifera fronds (5-8 cm long) from each depth and manipulation treatment were used to estimate their photochemical status. In vivo chlorophyll a fluorescence of Photosystem II (PSII) was assessed through a portable pulse amplitude modulation fluorometer (Diving-PAM, Waltz GmbH, Germany). After 15 min of dark adaptation (‘relaxed state’), the minimum (basal) fluorescence was measured (Fo) and the maximum fluorescence (Fm) was obtained immediately after applying a saturated pulse of actinic light (2,350 µmol photons m–2 s–1, 0.8 s). The optimum quantum yield was therefore calculated as Fv/Fm=Fm–Fo/Fm, which is an indicator of physiological stress (Maxwell and Johnson 2000Maxwell K., Johnson G. 2000. Chlorophyll fluorescence—a practical guide. J. Exp. Bot. 51: 659-668.). A rapid light curve (RLC) was initiated, involving 20 s of exposure to 9 successive irradiances, including 20, 66, 137, 224, 337, 469, 693, 942 and 1418 µmol photons m–2 s–1. RLCs were then obtained by calculating the electron transport rate (ETR) through the PSII for each level of actinic light through the formula:

ETR (µmol electrons m–2 s–1) = (ΔF/F′m) × E × A × FII

where ‘E’ is the irradiance; ‘A’ is the absorptance of each macrophyte (0.88±0.02 for C. nodosa and 0.93±0.03 for C. prolifera, calculated using the method of García-Sánchez et al. 2012García-Sánchez S., Korbee N., Pérez-Ruzafa I.M., et al. 2012. Physiological response and photoacclimation capacity of Caulerpa prolifera (Forsskål) J.V. Lamouroux and Cymodocea nodosa (Ucria) Ascherson meadows in the Mar Menor lagoon (SE Spain). Mar. Environ. Res. 79: 37-47.); and ‘FII’ is the fraction of chlorophyll associated with the PSII (0.5 for green seaweeds, according to Grzymski et al. 1997Grzymski J., Johnsen G., Sakshaug E. 1997. The significance of intracellular self-shading on the bio-optical properties of brown, red and green macroalgae. J. Phycol. 33: 408-414.). RLCs were fitted through the model provided by Jassby and Platt (1976)Jassby A., Platt T. 1976. Mathematical formulation of the relationship between photosynthesis and light for phytoplankton. Limnol. Oceanogr. 21: 540-547. to obtain the initial slope of the curve (αETR, i.e. the photosynthetic efficiency), the saturation irradiance (Ek) and the maximal ETR (ETRmax); the model of Platt and Gallegos (1980)Platt T., Gallegos I. 1980. Modelling primary production. In: Falkowski P.G. (ed.), Primary productivity in the sea. Plenum, pp. 339-351. was applied when photo-inhibition was detected.

Carotenes and antioxidant activity

The carotene content was determined spectro-photometrically. The analyses were carried out by extracting pigments from plants (ca. 20 mg dry weight [DW], n=3) using 1 ml of saturation solution of acetone 90% + C4Mg4O12 and maintaining them in darkness at 4°C for 12 h. After centrifugation at 4000 rpm for 20 min, each supernatant was used to measure carotenes in a spectrophotometer at an absorption of 480 and 750 nm. The carotene concentration, expressed as mg g–1 DW, was calculated using the equation provided by Parsons and Strickland (1963)Parsons T.R., Strickland J.D.H. 1963. Discussion of spectrophometric determination of marine-plant pigments, with revised equations for ascertaining chlorophyll-a and carotenois. J. Mar. Res. 21: 105-156..

Thalli of C. nodosa and C. prolifera (ca. 0.25 g FW, n=3) were ground with a mortar and a pestle in sand at 4°C and extracted overnight in centrifuge tubes with 2.5 ml of 80% (v/v) methanol. The mixture was centrifuged at 4000 rpm (30 min) and the supernatants were collected (Sigma 2-16PK, Göttingen, Germany). The DPPH (2,2-diphenyl-1-picrylhydrasyl) free-radical scavenging assay was carried out in triplicate, according to the method of Blois (1958)Blois M. 1958. Antioxidant determinations by the use of a stable free radical. Nature 181: 1199-1200.. Briefly, 150 µL of each methanolic extract was mixed with 1.5 mL of 90% methanol and 150 µL of DPPH solution prepared daily at 1.27 mM. The reaction was complete after 30 min in darkness at room temperature, and the absorbance was registered at 517 nm. The calibration curve made with DPPH was used to calculate the remaining concentration of DPPH in the reaction mixture after incubation. Values of DPPH concentration (µM) were plotted against plant extract concentration (mg DW mL–1) to obtain the EC50 value (oxidation index), which represents the concentration of the extract (mg mL–1) required to scavenge 50% of the DPPH in the reaction mixture. Ascorbic acid was used as a positive control.

Statistical analyses

A three-way ANOVA tested for differences in the biomass of C. nodosa and C. prolifera across depth; the model included the factors ‘Species’ (fixed factor), depth (fixed factor) and ‘Time’ (random factor). Linear regression models tested whether the mean particle diameter (D50), the mean total N and P content and the mean organic matter content of sediments varied with depth. To test for initial differences (‘start’ collections) in physiological responses between macrophytes (C. nodosa vs C. prolifera), depths (5 vs 20 m) and times (February vs May 2014), three-way ANOVAs were carried out. Each model incorporated the factors ‘Species’ (fixed factor), depth (fixed factor) and ‘Time’ (random factor). A three-way ANOVA tested separately for each macrophyte for significant differences in physiological responses between depths (two levels: 5 vs 20 m), times (two levels: February vs May) and the origin of the transplant (autochthonous = procedural control vs. allochthonous) at the end of the transplants. The model incorporated the same factors as above, in addition to ‘Origin’ (fixed factor with two levels). For all ANOVAs, data were transformed to avoid heterogeneous variances (see Tables 1, 2 and 3 for specific transformations); Cochran’s C test was used in this sense. If no transformation rendered homogeneous variances, the significance level was set at 0.01 rather than the 0.05 level to avoid increasing a type I error (Underwood 1997Underwood A.J. 1997. Experiments in Ecology: their logical design and interpretation using Analysis of Variance. Cambridge Univ. Press., Cambridge, UK.). Pairwise comparisons were carried out via Student-Newman-Keul (SNK) tests wherever necessary.

RESULTSTop

PAR patterns, sediment characteristics and vegetated biomass with depth

In February 2014, integrated mean PAR values at 5 m were ca. 2.57 times larger than at 20 m (Fig. 2A; means =124.50 vs 48.40 μ mol photons m–2 s–1), whereas in May 2014 they were ca. 2.24 times larger (Fig. 2B; means =251.72 vs 111.89 μ mol photons m–2 s–1). In general, maximum daily peaks in PAR increased from February to May 2014; for example, at 5 m, peaks increased from <1300 µmol photons m–2 s–1 to ~2000 µmol photons m–2 s–1. Sediments were dominated by fine sands at all depths (Appendix 1).

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Fig. 2. – Incident PAR (mmol photons m–2 s–1) patterns through experimentation at 5 and 20 m depth in February (A) and May 2014 (B).

The biomass of both macrophytes varied between depth strata following different trends (‘Sp×De’, F3,64= 66.89, P<0.0001, Fig. 3). The biomass of the seagrass C. nodosa was larger at 5 and 10 m than at 15 and 20 m (SNK tests, Fig. 3). The biomass of C. prolifera showed a minimum at 5 m and similar values at 10, 15 and 20 m (SNK tests, Fig. 3). These patterns were consistent through times (‘Species×Time’, F1,64=0.19, P=0.6657, ‘De×Ti’, F3,64=0.11, P=0.9556), reinforcing the generality of these observations.

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Fig. 3. – Changes in the biomass of C. nodosa and C. prolifera between depth strata at Gando Bay (Gran Canaria Island). Error bars are +SE of means (n=5). Times were pooled, as a result of lack of significant effects. Different letters above bars denote significant differences for each macrophyte.

Differences in initial photo-physiological responses

The seagrass C. nodosa showed a larger optimum quantum yield (Fv/Fm) than C. prolifera, particularly in May 2014 (‘Ti×Sp’, P=0.001, Table 1; Fig. 4), independently of depth (all terms involving ‘De’, P>0.05, Table 1; Fig. 4). Similarly, C. nodosa showed a significantly larger ETRmax than C. prolifera in May 2014 (‘Ti×Sp’, P=0.0008, Table 1; Fig. 4), regardless of depth (all terms involving ‘De’, P>0.05, Table 1; Fig. 5). The seagrass C. nodosa also had a larger αETR than C. prolifera (‘Sp’, P<0.00001, Table 1; Fig. 6), which was particularly accentuated in May 2014 (‘Ti×Sp’, P=0.001, Table 1; Fig. 6). Both macrophytes were more photosynthetically efficient, i.e. larger αETR at 20 than 5 m depth (‘De’, P=0.0230, Table 1; Fig. 6). Appendix 2 includes means and SE of means of all photosynthetic parameters. The carotenoid content was significantly larger in C. prolifera than in C. nodosa (‘Sp’, P=0.001, Table 1; Fig. 7). While C. nodosa increased its carotene content from 5 to 20 m depth at both times, C. prolifera decreased it (‘De×Sp’, P<0.00001, Table 1; Fig. 7). The antioxidant activity of C. nodosa was significantly greater than that of C. prolifera (‘Sp’, P=0.0001, Table 1; Fig. 8).

Table 1. – Three-way ANOVAs testing the effect of ‘Time’ (Ti), ‘Depth’ (De) and ‘Species’ (Sp) on the optimum quantum yield of chlorophyll a fluorescence (Fv/Fm), the maximum electron transport rate (ETRmax), the photosynthetic efficiency calculated from ETR-E relationship (αETR), the carotenoid content and the antioxidant activity (EC50) of Cymodocea nodosa and Caulerpa prolifera. Significant values are highlighted in bold (P<0.05).

Fv/Fm ETRmax αETR Carotenoids EC50
No transformation C=0.3781 (n.s.) No transformation C=0.1811 (n.s.) No transformation C=0.3261 (n.s.) Ln(x+1), C=0.5953 (P<0.05) Ln(x+1) C=0.7288 (P<0.01)
MS F P MS F P MS F P MS F P MS F P
Ti 0.0000 0.04 0.8502 14.8712 1.88 0.1898 0.0000 0.04 0.8502 0.0006 0.08 0.7753 0.0076 2.97 0.1039
De 0.0017 79.25 0.0712 2.5585 241.73 0.0409 0.0017 6.32 0.0230 0.0167 2.18 0.1592 0.0017 0.66 0.4298
Sp 0.0202 4.78 0.2732 452.34 3.32 0.3197 0.0202 76.48 0.0000 0.2114 27.63 0.0001 0.1466 57.35 0.0000
Ti×De 0.0000 0.08 0.7813 0.0106 0.00 0.9713 0.0000 0.08 0.7813 0.0103 1.34 0.2639 0.0091 3.57 0.0769
Ti×Sp 0.0042 16.01 0.0010 136.393 17.20 0.0008 0.0042 16.01 0.0010 0.0298 3.89 0.0660 0.0105 4.11 0.0596
De×Sp 0.0000 0.15 0.7660 4.5920 0.35 0.6601 0.0000 0.12 0.7364 0.3046 39.83 0.0000 0.0014 0.54 0.4727
Ti×De×Sp 0.0002 0.79 0.3868 13.1394 1.66 0.2163 0.0002 0.79 0.3868 0.0012 0.15 0.7003 0.0049 1.9 0.1871
Residual 0.0003 7.9290 0.0003 0.0076 0.0026

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Fig. 4. – Optimum quantum yield of chlorophyll a fluorescence of the seagrass Cymodocea nodosa and the green alga Caulerpa prolifera at 5 and 20 m depth in February 2014 (A) and May 2014 (B). Error bars are +SE of means (n=6). Different letters above bars denote significant differences.

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Fig. 5. – The maximum electron transport rate (ETRmax) of the seagrass Cymodocea nodosa and the green alga Caulerpa prolifera at 5 and 20 m depth in February 2014 (A) and May 2014 (B). Error bars are +SE of means (n=6). Different letters above bars denote significant differences.

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Fig. 6. – Photosynthetic efficiency calculated from ETR-E relationship (αETR) of the seagrass Cymodocea nodosa and the green alga Caulerpa prolifera at 5 and 20 m depth in February 2014 (A) and May 2014 (B). Error bars are +SE of means (n=6). Different letters above bars denote significant differences.

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Fig. 7. – Carotenoids content of the seagrass Cymodocea nodosa and the green alga Caulerpa prolifera at 5 and 20 m depth in February 2014 (A) and May 2014 (B). Error bars are +SE of means (n=6). Different letters above bars denote significant differences.

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Fig. 8. – Antioxidant activity (EC50 index) of the seagrass Cymodocea nodosa and the green alga Caulerpa prolifera at 5 and 20 m depth in February 2014 (A) and May 2014 (B). Error bars are +SE of means (n=6). The lower the EC50 index, the larger the antioxidant activity. Different letters above bars denote significant differences.

Differences in photo-physiological responses at the end of transplants

The optimum quantum yield of C. nodosa did not differ either between depth strata or between the origin of the vegetative fragment (all terms involving ‘De’ and ‘Or’, P>0.05, Table 2; Fig. 9A, B); significant differences only occurred between times (‘Ti’, P<0.00001, Table 2; Fig. 9A, B), including a decay in the optimum quantum yield in May in comparison with February (2014). The optimum quantum yield of C. prolifera varied between depths inconsistently from time to time (‘Ti×De’, P=0.0011, Table 3; Fig. 9C, D): in February 2014, the optimum quantum yield was larger for specimens collected at 20 than at 5 m, whereas in May 2014 no significant differences were detected (SNK tests, Fig. 9C, D). Thalli of C. prolifera increased the optimum quantum yield when transplanted from 5 to 20 m, while the opposite pattern was detected when thalli from 20 m were transplanted at 5 m (Fig. 9C, D). The ETRmax of both macrophytes was larger in May than in February 2014 (‘Ti’, P<0.01, Tables 2 and 3; Fig. 10), regardless of depth and the origin of the vegetative fragments. The photosynthetic efficiency of C. nodosaETR) varied exclusively between times; larger αETR values were observed in May (2014) (‘Ti’, P<0.00001, Table 2; Fig. 11A, B). Irrespective of times, however, C. prolifera showed a larger photosynthetic efficiency at 20 than at 5 m (‘De’, P=0.0066, Table 3; Fig. 11C, D). Thalli of C. prolifera increased their photosynthetic efficiency when transplanted from 5 to 20 m, while the opposite pattern was observed for thalli transplanted from 20 to 5 m (Fig. 11C, D); however, this pattern was not detected statistically (all terms involving ‘De’ and ‘Or’, P>0.05, Table 3; Fig. 11C, D). Appendix 3 includes means and SE of means of all photosynthetic parameters. The carotene content of C. nodosa differed between depths according to the origin of vegetative fragments from time to time (‘Ti×De×Or’, P=0.0004, Table 3; Fig. 12A, B). The magnitude of differences between depth levels depended on the origin (‘De×Or’, P=0.08, Table 3; Fig. 12C, D); differences in the carotene content between allochthonous and autochthonous fragments were more accentuated at 5 than at 20 m depth (SNK tests, Fig. 12C, D). The carotene content of C. prolifera differed exclusively between times (‘Ti’, P=0.00025, Table 3; Fig. 12C, D); a decrease in the carotene content was observed with increasing depth, but it was not statistically significant (‘De’, P=0.2084, Table 3; Fig. 12C, D). The antioxidant activity of both macrophytes varied between depths according to times, regardless of the origin of the vegetative fragments (‘Ti×De’, P<0.00001, Tables 2 and 3; Fig. 13); differences in the antioxidant activity between 5 and 20 m depth were significant in February but not in May 2014 (SNK tests, Fig. 13).

Table 2. – Three-way ANOVAs testing the effect of ‘Time’ (Ti), ‘Depth’ (De) and ‘Origin’ (Or) on the optimum quantum yield of chlorophyll a fluorescence (Fv/Fm), the maximum electron transport rate (ETRmax), the photosynthetic efficiency calculated from ETR-E relationship (αETR), the carotenoid content and the antioxidant activity (EC50) of Cymodocea nodosa at the end of the reciprocal transplants. Significant values are highlighted in bold (P<0.05).

Fv/Fm ETRmax αETR Carotenoids EC 50
No transformation C=0.3084 (n.s.) No transformation C=0.2602 (n.s.) No transformation C=0.2849 (n.s.) No transformation C=0.1730 (n.s.) Ln(x+1) C=0.4114 (P<0.05)
MS F P MS F P MS F P MS F P MS F P
Ti 0.0217 23.00 0.0000 1866.33 94.49 0.0000 0.0272 29.07 0.0000 0.0038 0.18 0.6757 0.0268 10.59 0.0023
De 0.0001 0.08 0.8264 31.7493 231.81 0.0418 0.0004 4.32 0.2855 0.0674 0.19 0.7410 0.1944 3.33 0.3190
Or 0.0003 0.19 0.7411 7.5986 2.03 0.3899 0.0032 2.74 0.3460 0.0244 1.36 0.4510 0.0001 0.37 0.6531
Ti×De 0.0009 0.98 0.3275 0.1370 0.01 0.9341 0.0001 0.09 0.7650 0.3634 17.09 0.0002 0.0583 23.02 0.0000
Ti×Or 0.0015 1.57 0.2170 3.7498 0.19 0.6654 0.0012 1.26 0.2678 0.0179 0.84 0.3640 0.0003 0.12 0.7313
De×Or 0.0008 1.29 0.4592 11.1554 0.21 0.7268 0.0036 14.47 0.1637 0.1158 0.37 0.6539 0.0022 0.24 0.7086
Ti×De×Or 0.0006 0.68 0.4159 53.2945 2.70 0.1083 0.0003 0.27 0.6066 0.3169 14.90 0.0004 0.0090 3.57 0.0661
Residual 0.0009 19.7517 0.0009 0.0213 0.0025

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Fig. 9. – Optimum quantum yield of chlorophyll a fluorescence of the seagrass Cymodocea nodosa (A, B) and the green alga Caulerpa prolifera (C, D) at 5 and 20 m depth in February (A, C) and May 2014 (B, D). Error bars are +SE of means (n=6). Different letters above bars denote significant differences for each macrophyte.

Table 3. – Three-way ANOVAs testing the effect of ‘Time’ (Ti), ‘Depth’ (De) and ‘Origin’ (Or) on the optimum quantum yield of chlorophyll a fluorescence (Fv/Fm), the maximum electron tranposrt rate (ETRmax), the photosynthetic efficiency calculated from ETR-E relationship (αETR), the carotenoid content and the antioxidant activity (EC50) of Caulerpa prolifera at the end of the reciprocal transplants. Significant values are highlighted in bold (P<0.05).

Fv/Fm ETRmax αETR Carotenoids EC50
No transformation, C=0.2621 (n.s.) Ln(x+1), C=0.4585 (P<0.05) No transformation, C=0.3211 (n.s.) No transformation, C=0.2425 (n.s.) Ln(x+1), C=0.5852 (P<0.01)
MS F P MS F P MS F P MS F P MS F P
Ti 0.0018 0.12 0.7319 1.5804 11.03 0.0019 0.0000 0.05 0.8324 0.7868 10.43 0.0025 2.9795 106.67 0.0000
De 0.0103 0.06 0.8520 0.6397 87.29 0.0679 0.0088 9165.25 0.0066 0.4619 8.67 0.2084 1.0153 0.27 0.6955
Or 0.0105 16.65 0.1530 0.0806 0.38 0.6493 0.0002 11.90 0.1796 0.6239 17.36 0.1500 0.0288 1.14 0.4787
Ti×De 0.1833 12.45 0.0011 0.0073 0.05 0.8222 0.0000 0.00 0.9522 0.0533 0.71 0.4058 3.7779 135.26 0.0000
Ti×Or 0.0006 0.04 0.8370 0.2136 1.49 0.2292 0.0000 0.07 0.7927 0.0359 0.48 0.4940 0.0252 0.90 0.3477
De×Or 0.0601 9.67 0.1981 0.0010 0.04 0.8742 0.0010 2.14 0.3816 0.0287 52.54 0.0873 0.0555 0.41 0.6363
Ti×De×Or 0.0062 0.42 0.5196 0.0238 0.17 0.6859 0.0005 1.77 0.1912 0.0005 0.01 0.9327 0.1344 4.81 0.0341
Residual 0.0147 0.1432 0.0003 0.0754 0.0279

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Fig. 10. – The maximum electron transport rate (ETRmax) of the seagrass Cymodocea nodosa (A, B) and the green alga Caulerpa prolifera (C, D) at 5 and 20 m depth in February 2014 (A, C) and May 2014 (B, D). Error bars are +SE of means (n=6). Different letters above bars denote significant differences for each macrophyte.

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Fig. 11. – Photosynthetic efficiency calculated from ETR-E relationship (αETR) of the seagrass Cymodocea nodosa (A, B) and the green alga Caulerpa prolifera (C, D) at 5 and 20 m depth in February 2014 (A, C) and May 2014 (B, D). Error bars are +SE of means (n=6). Different letters above bars denote significant differences for each macrophyte.

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Fig. 12. – Carotenoids content of the seagrass Cymodocea nodosa (A, B) and the green alga Caulerpa prolifera (C, D) at 5 and 20 m depth in February 2014 (A, C) and May 2014 (B, D). Error bars are +SE of means (n=6). Different letters above bars denote significant differences for each macrophyte.

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Fig. 13. – Antioxidant activity (EC50 index) of the seagrass Cymodocea nodosa (A, B) and the green alga Caulerpa prolifera (C, D) at 5 and 20 m depth in February 2014 (A, C) and May 2014 (B, D). Error bars are +SE of means (n=6). The lower the EC50 index, the larger the antioxidant activity. Different letters above bars denote significant differences for each macrophyte.

DISCUSSIONTop

Our results have suggested a connection between the patterns of vertical distribution of the seagrass C. nodosa (i.e. decreased biomass with depth) and the green alga C. prolifera (i.e. increased biomass with depth) with their respective photochemical adaptations at the study site in Gran Canaria Island. Overall, C. nodosa behaves as a ‘light-plant’ relative to C. prolifera, which follows a ‘shade-plant’ pattern. This result is similar to that of a study comparing the photo-physiology of both macrophytes within a Mediterranean coastal lagoon (García-Sánchez et al. 2012García-Sánchez S., Korbee N., Pérez-Ruzafa I.M., et al. 2012. Physiological response and photoacclimation capacity of Caulerpa prolifera (Forsskål) J.V. Lamouroux and Cymodocea nodosa (Ucria) Ascherson meadows in the Mar Menor lagoon (SE Spain). Mar. Environ. Res. 79: 37-47.). This outcome has implications in the way light is absorbed by both macrophytes, as well as in the quantity and quality of pigment contents, and in ways to ameliorate/dissipate the excess of light energy reaching photosynthetic tissues (Malta et al. 2005Malta E.J., Ferreira D.G., Vergara J.J., et al. 2005. Nitrogen load and irradiance affect morphology, photosynthesis and growth of Caulerpa prolifera (Bryopsidales, Chlorophyta). Mar. Ecol. Prog. Ser. 298: 101-114., García-Sánchez et al. 2012García-Sánchez S., Korbee N., Pérez-Ruzafa I.M., et al. 2012. Physiological response and photoacclimation capacity of Caulerpa prolifera (Forsskål) J.V. Lamouroux and Cymodocea nodosa (Ucria) Ascherson meadows in the Mar Menor lagoon (SE Spain). Mar. Environ. Res. 79: 37-47.).

Our results demonstrated that the seagrass C. nodosa has a consistently larger optimum quantum yield (Fv/Fm), ETRmax and photosynthetic efficiency than the green alga C. prolifera, particularly when PAR values are larger (May in comparison with February 2014). Evidence for this, moreover, was provided by direct measurements from collected thalli and at the end of the reciprocal transplants. This outcome is a clear indication of adaptation of the seagrass to larger irradiances and therefore optimization of light absorption in this time (May). Not surprisingly, this is particularly pertinent in this season, as this seagrass experiences rapid growth in spring-summer in the study region (Tuya et al. 2006Tuya F., Martín J.A., Luque A. 2006. Seasonal cycle of a Cymodocea nodosa seagrass meadow and of the associated ichthyofauna at Playa Dorada (Lanzarote, Canary Islands, eastern Atlantic). Cien. Mar. 32: 695-704.), as well as in a range of sites across the Mediterranean Sea (e.g. Terrados and Ros 1992Terrados J., Ros J.D. 1992. Growth and primary production of Cymodocea nodosa (Ucria) Ascherson in a Mediterranean coastal lagoon: The Mar Menor (SE Spain). Aquat. Bot. 43: 63-74.). Biomass accumulation (e.g. seagrass leaf growth and rhizome production) is metabolically based on increased photosynthetic rates and therefore high C demands. For C. nodosa, there is a positive correlation between gross primary production and ETR at the PSII, except under stressful conditions (e.g. low nutrients levels and very high PAR), as usually occurs for C4 plants, including C. nodosa (Cabello-Pasini et al. 2015Cabello-Pasini A., Abdala-Díaz R., Macías-Carranza V., et al. 2015. Effect of irradiance and nitrate levels on the relationship between gross photosynthesis and electron transport rate in the seagrass Cymodocea nodosa. Cienc. Mar. 41: 93-105.). In turn, decreased irradiances reaching the photosynthetic apparatus of C. nodosa, for example during fertilization events, negatively affect the production of photochemical energy by C. nodosa (Tuya et al. 2015Tuya F., Betancor S., Viera-Rodríguez M.A., et al. 2015. Effect of chronic versus pulse perturbations on a marine ecosystem: integration of functional responses across organization levels. Ecosystems 18: 1455-1471.). This seagrass showed increased photosynthetic potential (ETRmax) and photochemical energy conversion efficiency (α) under increased irradiances, i.e. at 5 in comparison with 20 m, and in May in comparison with February (2014). Under decreased irradiances (e.g. at 20 in comparison with 5 m depth), this seagrass shows increased photochemical energy conversion efficiency (α); this is a common strategy of marine angiosperms when they are subjected to chronic light deprivation (Collier et al. 2012Collier C.J., Waycott M., Giraldo Ospina A. 2012. Responses of four Indo-West Pacific seagrass species to shading. Mar. Poll. Bull. 65: 342-354.), including C. nodosa (Silva et al. 2013Silva J., Barrote J., Costa M.M., et al. 2013. Physiological responses of Zostera marina and Cymodocea nodosa to light-limitation stress. PLoS ONE 8(11): e81058.).

The green alga C. prolifera has adapted its photosynthetic apparatus to prevailing light regimes, e.g. a larger photosynthetic efficiency at 20 than at 5 m depth. A similar pattern has been described for other Caulerpa species, such as Caulerpa racemosa in the Mediterranean Sea (Raniello et al. 2006Raniello R., Lorenti M., Brunet C., et al. 2006. Photoacclimation of the invasive alga Caulerpa racemosa var. cylindracea to depth and daylight patterns and a putative new role for siphonoxanthin. Mar. Ecol. 27: 20-30., Bernardeau-Esteller et al. 2011Bernardeau-Esteller J., Marín-Guirao L., Sandoval-Gil J.M., et al. 2011. Photosynthesis and daily metabolic carbon balance of the invasive Caulerpa racemosa var. cylindracea (Chlorophyta: Caulerpales) along a depth gradient. Sci. Mar. 75: 803-810.). Not only deep-water (20 m depth) thalli of C. prolifera are more adapted to low irradiances: this alga also showed short-term acclimation under varying light regimes, i.e. when reciprocal transplants of vegetative fragments were carried out. When fragments from 5 m were relocated at 20 m depth, these fragment became more photo-chemically efficient (i.e. larger Fv/Fm and αETR), while the opposite occurred for deep-water fragments (20 m) relocated at 5 m. This photo-physiological versatility of C. prolifera provides an additional, short-term advantage of this alga under varying environmental scenarios. Due to their lateral (clonal) growth, Caulerpa spp. often experience spatial variation in a range of environmental conditions and resources (Collado-Vides 2002Collado-Vides L. 2002. Morphological plasticity of Caulerpa prolifera (Caulerpales, Chlorophyta) in relation to growth form in a coral reef lagoon. Bot. Mar. 45: 123-129.). As a result, species within the genus Caulerpa show morphological plasticity, including varying patterns of internode production and length of fronds, e.g. for a more efficient light use, which affect the overall appearance of the plant (Collado-Vides 2002Collado-Vides L. 2002. Morphological plasticity of Caulerpa prolifera (Caulerpales, Chlorophyta) in relation to growth form in a coral reef lagoon. Bot. Mar. 45: 123-129.).

The seagrass and the green alga seem to have different physiological mechanisms to achieve photo-protection. The exposition of C. nodosa to high PAR seems to explain the larger antioxidant activity of the seagrass in comparison with C. prolifera, as a way to dissipate excess light energy. This has been described in the Mediterranean Sea, where C. nodosa typically live in shallow water (García-Sánchez et al. 2012García-Sánchez S., Korbee N., Pérez-Ruzafa I.M., et al. 2012. Physiological response and photoacclimation capacity of Caulerpa prolifera (Forsskål) J.V. Lamouroux and Cymodocea nodosa (Ucria) Ascherson meadows in the Mar Menor lagoon (SE Spain). Mar. Environ. Res. 79: 37-47.). The green alga showed a larger content of carotenes than the seagrass, particularly in shallow water (i.e. under high irradiances), most likely to protect its photosynthetic machinery from light excess. In turn, when vegetative fragments of C. prolifera from 5 m were relocated at 20 m, the alga decreased its carotene content. In the particular case of the seagrass, however, the carotene content increased with depth; this is most likely a response to increase light harvesting by photosynthetic antennas under scenarios of low PAR. In turn, leaves of flowering plants have the capacity to adapt the carotene content either to improve light harvesting or to protect the photosynthetic machinery from light excess (Matsubara et al. 2009Matsubara S., Krause G.H., Aranda J., et al. 2009. Sun-shade patterns of leaf carotenoid composition in 86 species of neotropical forest plants. Funct. Plant Biol. 36: 20-36.). These results, however, should be taken with caution, as we have not analysed the specific carotenes associated with each macrophyte. Moreover, we cannot link differences in antioxidant activity with varying quality and quantity of carotenes (e.g. b-carotene and lutein) and other chemical ways of excess light dissipation.

A range of human-induced perturbations may reduce the transparency of coastal waters, including sedimentation (e.g. associated with construction of infrastructures and coastal runoff) and fertilization (Burkholder et al. 2007Burkholder J.M., Tomasko D., Touchette B.W. 2007. Seagrasses and eutrophication. J. Exp. Mar. Biol. Ecol. 350: 46-72.). Decreased light regimes, where C. nodosa and C. prolifera coexist in subtidal soft bottoms, seem to clearly favour the alga in comparison with the seagrass, at least from a physiological point of view. The results of this study are therefore added to a body of literature that demonstrates the need to maintain coastal waters with a good quality status to promote seagrass conservation.

ACKNOWLEDGEMENTSTop

This study was partially supported by the EU project ECOSERVEG, within the BEST initiative (Voluntary Scheme for Biodiversity and Ecosystem Services in Territories of the EU Outermost Regions and Oversees Countries and Territories, Grant nº 07.032700/2012/635752/SUB/B2). F. Tuya was supported by the MINECO ‘Ramón y Cajal’ programme. We thank T. Sánchez for his help during fieldwork. Two anonymous reviewers provided positive feedback on a previous draft of this paper.

REFERENCESTop

Barberá C., Tuya F., Boyra A., et al. 2005. Spatial variation in the structural parameters of Cymodocea nodosa seagrass meadows in the Canary Islands: a multiscaled approach. Bot. Mar. 48: 122-126.
http://dx.doi.org/10.1515/BOT.2005.021

Bernardeau-Esteller J., Marín-Guirao L., Sandoval-Gil J.M., et al. 2011. Photosynthesis and daily metabolic carbon balance of the invasive Caulerpa racemosa var. cylindracea (Chlorophyta: Caulerpales) along a depth gradient. Sci. Mar. 75: 803-810.
http://dx.doi.org/10.3989/scimar.2011.75n4803

Betancor S., Domínguez B., Tuya F., et al. 2015. Photosynthetic performance and photoprotection of Cystoseira humilis (Phaeophyceae) and Digenea simplex (Rhodophyceae) in an intertidal rock pool. Aquat. Bot. 121: 16-25.
http://dx.doi.org/10.1016/j.aquabot.2014.10.008

Blois M. 1958. Antioxidant determinations by the use of a stable free radical. Nature 181: 1199-1200.

Bradstreet R.B. 1965. The Kjeldahl method for organic Nitrogen. Academic Press, New York, 239 pp.

Burkholder J.M., Tomasko D., Touchette B.W. 2007. Seagrasses and eutrophication. J. Exp. Mar. Biol. Ecol. 350: 46-72.
http://dx.doi.org/10.1016/j.jembe.2007.06.024

Cabello-Pasini A., Abdala-Díaz R., Macías-Carranza V., et al. 2015. Effect of irradiance and nitrate levels on the relationship between gross photosynthesis and electron transport rate in the seagrass Cymodocea nodosa. Cienc. Mar. 41: 93-105.
http://dx.doi.org/10.7773/cm.v41i2.2499

Ceccherelli G., Cinelli F. 1997. Short-term effects of nutrient enrichment of the sediment and interactions between the seagrass Cymodocea nodosa and the introduced green alga Caulerpa taxifolia in a Mediterranean bay. J. Exp. Mar. Biol. Ecol. 217: 165-177.
http://dx.doi.org/10.1016/S0022-0981(97)00050-6

Collado-Vides L. 2002. Morphological plasticity of Caulerpa prolifera (Caulerpales, Chlorophyta) in relation to growth form in a coral reef lagoon. Bot. Mar. 45: 123-129.
http://dx.doi.org/10.1515/BOT.2002.013

Collier C.J., Waycott M., Giraldo Ospina A. 2012. Responses of four Indo-West Pacific seagrass species to shading. Mar. Poll. Bull. 65: 342-354.
http://dx.doi.org/10.1016/j.marpolbul.2011.06.017

Duarte C.M., Dennison W.C., Orth R.J., et al. 2008. The charisma of coastal ecosystems. Estuar. Coasts 31: 233-238.
http://dx.doi.org/10.1007/s12237-008-9038-7

García-Sánchez S., Korbee N., Pérez-Ruzafa I.M., et al. 2012. Physiological response and photoacclimation capacity of Caulerpa prolifera (Forsskål) J.V. Lamouroux and Cymodocea nodosa (Ucria) Ascherson meadows in the Mar Menor lagoon (SE Spain). Mar. Environ. Res. 79: 37-47.
http://dx.doi.org/10.1016/j.marenvres.2012.05.001

Gardner A., Tuya F., Lavery P.S., et al. 2013. Habitat preferences of macroinvertebrate fauna among seagrasses with varying structural forms. J. Exp. Mar. Biol. Ecol. 439: 143–151.
http://dx.doi.org/10.1016/j.jembe.2012.11.009

Grzymski J., Johnsen G., Sakshaug E. 1997. The significance of intracellular self-shading on the bio-optical properties of brown, red and green macroalgae. J. Phycol. 33: 408-414.
http://dx.doi.org/10.1111/j.0022-3646.1997.00408.x

Häder D.P., Porst M., Herrmann H., et al. 1997. Photosynthesis of Mediterranean green alga Caulerpa prolifera measured in the field under solar irradiation. J. Photoch. Photobio. B 37: 66-73.
http://dx.doi.org/10.1016/S1011-1344(96)07338-1

Hanelt D. 1998. The capability for dynamic photoinhibition in Arctic macroalgae is related to their depth distribution. Mar. Biol. 131: 361-369.
http://dx.doi.org/10.1007/s002270050329

Jassby A., Platt T. 1976. Mathematical formulation of the relationship between photosynthesis and light for phytoplankton. Limnol. Oceanogr. 21: 540-547.
http://dx.doi.org/10.4319/lo.1976.21.4.0540

Lapointe B.E., Barile P.J., Littler M.M., et al. 2005. Macroalgal blooms on southeast Florida coral reefs: II. Cross-shelf discrimination of nitrogen sources indicates widespread assimilation of sewage nitrogen. Harmful Algae 4: 1106-1122.
http://dx.doi.org/10.1016/j.hal.2005.06.002

Lloret J., Marin A., Marin-Guirao L., et al. 2005. Changes in macrophytes distribution in a hypersaline coastal lagoon associated with the development of intensively irrigated agriculture. Ocean. Coast. Manage. 48: 828-842.
http://dx.doi.org/10.1016/j.ocecoaman.2005.07.002

Lüning K. 1990. Seaweeds: their environment, biogeography, and ecophysiology. Wiley-Interscience, New York, NY.

Malta E.J., Ferreira D.G., Vergara J.J., et al. 2005. Nitrogen load and irradiance affect morphology, photosynthesis and growth of Caulerpa prolifera (Bryopsidales, Chlorophyta). Mar. Ecol. Prog. Ser. 298: 101-114.
http://dx.doi.org/10.3354/meps298101

Matsubara S., Krause G.H., Aranda J., et al. 2009. Sun-shade patterns of leaf carotenoid composition in 86 species of neotropical forest plants. Funct. Plant Biol. 36: 20-36.
http://dx.doi.org/10.1071/FP08214

Maxwell K., Johnson G. 2000. Chlorophyll fluorescence—a practical guide. J. Exp. Bot. 51: 659-668.
http://dx.doi.org/10.1093/jexbot/51.345.659

Murphy J., Riley J.P. 1962. A modified single solution method for the determination of phosphate in natural waters. Anal. Chem. Acta 27: 31-36.
http://dx.doi.org/10.1016/S0003-2670(00)88444-5

Olesen B., Enríquez S., Duarte C.M., et al. 2002. Depth-acclimation of photosynthesis, morphology and demography of Posidonia oceanica and Cymodocea nodosa in the Spanish Mediterranean Sea. Mar. Ecol. Prog. Ser. 236: 89-97.
http://dx.doi.org/10.3354/meps236089

Parsons T.R., Strickland J.D.H. 1963. Discussion of spectrophometric determination of marine-plant pigments, with revised equations for ascertaining chlorophyll-a and carotenois. J. Mar. Res. 21: 105-156.

Platt T., Gallegos I. 1980. Modelling primary production. In: Falkowski P.G. (ed.), Primary productivity in the sea. Plenum, pp. 339-351.
http://dx.doi.org/10.1007/978-1-4684-3890-1_19

Raniello R., Lorenti M., Brunet C., et al. 2006. Photoacclimation of the invasive alga Caulerpa racemosa var. cylindracea to depth and daylight patterns and a putative new role for siphonoxanthin. Mar. Ecol. 27: 20-30.
http://dx.doi.org/10.1111/j.1439-0485.2006.00080.x

Silva J., Barrote J., Costa M.M., et al. 2013. Physiological responses of Zostera marina and Cymodocea nodosa to light-limitation stress. PLoS ONE 8(11): e81058.
http://dx.doi.org/10.1371/journal.pone.0081058

Terrados J., Ros J.D. 1992. Growth and primary production of Cymodocea nodosa (Ucria) Ascherson in a Mediterranean coastal lagoon: The Mar Menor (SE Spain). Aquat. Bot. 43: 63-74.
http://dx.doi.org/10.1016/0304-3770(92)90014-A

Tuya F., Martín J.A., Luque A. 2006. Seasonal cycle of a Cymodocea nodosa seagrass meadow and of the associated ichthyofauna at Playa Dorada (Lanzarote, Canary Islands, eastern Atlantic). Cien. Mar. 32: 695-704.

Tuya F., Hernández-Zerpa H., Espino F., et al. 2013a. Drastic decadal decline of the seagrass Cymodocea nodosa at Gran Canaria (Eastern Atlantic): interactions with the green alga Caulerpa prolifera. Aquat. Bot. 105: 1-6.
http://dx.doi.org/10.1016/j.aquabot.2012.10.006

Tuya F., Viera-Rodríguez M.A., Guedes R., et al. 2013b. Seagrass responses to nutrient enrichment depend on clonal integration, but not flow-on effects on associated biota. Mar. Ecol. Prog. Ser. 490: 23-35.
http://dx.doi.org/10.3354/meps10448

Tuya F., Ribeiro-Leite L., Arto-Cuesta N., et al. 2014. Decadal changes in the structure of Cymodocea nodosa seagrass meadows: Natural vs. human influences. Estuar. Coast. Shelf Sci. 137: 41-49.
http://dx.doi.org/10.1016/j.ecss.2013.11.026

Tuya F., Betancor S., Viera-Rodríguez M.A., et al. 2015. Effect of chronic versus pulse perturbations on a marine ecosystem: integration of functional responses across organization levels. Ecosystems 18: 1455-1471.
http://dx.doi.org/10.1007/s10021-015-9911-8

Underwood A.J. 1997. Experiments in Ecology: their logical design and interpretation using Analysis of Variance. Cambridge Univ. Press., Cambridge, UK.

Walkley A., Black J.A. 1934. An examination of the Degtjareff method for determining soil organic matter and a proposed modification of the chromic titration method. Soil Sci. 37: 29-38.
http://dx.doi.org/10.1097/00010694-193401000-00003

APPENDICESTop

Appendix 1. – Sediment characteristics across depth at Gando Bay (Gran Canaria Island). Only the Ptotal showed a significant change with depth.

5 m 10 m 15 m 20 m
Mean SD Mean SD Mean SD Mean SD
Ntotal (mg kg–1) 405.50 19.09 251.00 39.60 307.50 60.10 403.50 177.48
Ptotal (mg kg–1), R2=0.58, P<0.01 1375.20 1669.20 29.95 9.12 57.20 11.46 55.25 41.65
Organic matter (%) 1.05 0.07 0.90 0.14 0.75 0.07 0.95 0.07
D50 0.14 0.00 0.33 0.25 0.19 0.02 0.14 0.00
Type of sediment Fine sands Fine sands Fine sands Fine sands Fine sands Fine sands Fine sands Fine sands

Appendix 2. – Photosynthetic parameters of Cymodocea nodosa and Caulerpa prolifera at the start of transplants (means and SE are included, n=6).

Time Species Depth Fv/Fm SE ETRmax SE αETR SE Ek SE
February (2014) C. nodosa 5 m 0.824 0.003 16.490 1.760 0.097 0.009 173.156 24.342
February (2014) C. prolifera 5 m 0.683 0.021 11.972 1.354 0.061 0.009 196.070 13.459
February (2014) C. nodosa 20 m 0.823 0.007 16.583 1.956 0.112 0.006 150.331 25.888
February (2014) C. prolifera 20 m 0.807 0.009 13.278 1.509 0.084 0.008 157.577 7.494
May (2014) C. nodosa 5 m 0.747 0.007 21.394 1.826 0.118 0.016 183.970 17.979
May (2014) C. prolifera 5 m 0.484 0.111 10.298 1.828 0.041 0.002 244.082 37.737
May (2014) C. nodosa 20 m 0.772 0.011 24.361 1.711 0.141 0.006 171.441 5.138
May (2014) C. prolifera 20 m 0.507 0.155 8.554 0.703 0.048 0.009 184.985 25.912

Appendix 3. – Photosynthetic parameters of Cymodocea nodosa and Caulerpa prolifera at the end of transplants (means and SE are included, n=6).

Time Depth Species Origin ETRmax SE αETR SE Ek SE
February (2014) 5 m C. nodosa autochthonous 11.9955 0.971 0.093 0.008 132.525 14.813
February (2014) 5 m C. nodosa allochthonous 9.497 1.348 0.074 0.009 130.358 13.305
February (2014) 5 m C. prolifera autochthonous 2.0471 0.302 0.034 0.005 62.445 9.523
February (2014) 5 m C. prolifera allochthonous 2.331 0.355 0.028 0.005 88.765 11.059
February (2014) 20 m C. nodosa autochthonous 12.372 1.886 0.083 0.011 144.726 13.221
February (2014) 20 m C. nodosa allochthonous 12.160 2.077 0.089 0.018 145.925 19.438
February (2014) 20 m C. prolifera autochthonous 2.944 0.545 0.058 0.004 49.609 7.402
February (2014) 20 m C. prolifera allochthonous 3.003 0.478 0.058 0.010 53.016 2.876
May (2014) 5 m C. nodosa autochthonous 21.693 0.815 0.152 0.018 166.486 11.494
May (2014) 5 m C. nodosa allochthonous 24.528 2.617 0.104 0.010 245.268 40.441
May (2014) 5 m C. prolifera autochthonous 4.034 0.348 0.042 0.002 93.517 3.504
May (2014) 5 m C. prolifera allochthonous 3.102 0.748 0.021 0.007 163.744 25.198
May (2014) 20 m C. nodosa autochthonous 26.498 1.530 0.139 0.009 192.115 12.080
May (2014) 20 m C. nodosa allochthonous 23.191 2.415 0.134 0.008 172.505 16.907
May (2014) 20 m C. prolifera autochthonous 6.390 1.997 0.054 0.010 106.208 20.512
May (2014) 20 m C. prolifera allochthonous 4.419 0.768 0.064 0.002 66.974 9.551


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