Spatio-temporal dynamic of the early life stages of fishassemblagesin the Guadalquivir estuary. Responses to anthropic and natural disturbances

Laboratorio de Biología Marina Universidad de Sevilla Spatio-temporal dynamic of the early life stages of fish assemblages in the Guadalquivir estuary. Responses to anthropic and natural disturbances. Dinámica espacio-temporal de la comunidad de larvas y juveniles de peces del estuario del Guadalquivir. Respuestas ante perturbaciones antrópicas y naturales. Juan Miguel Miró Recio-Mensaque PhD Sevilla 2021 Los directores Dr. César Megina Martínez, profesor titulas del Departamento de Zoología de la Universidad de Sevilla, y Dr. José Carlos García Gómez, catedrático del Departamento de Zoología de la Universidad de Sevilla, INFORMAN: Que la presente memoria de tesis doctoral, titulada “Dinámica espacio-temporal de la comunidad de larvas y juveniles de peces del estuario del Guadalquivir. Respuestas ante perturbaciones antrópicas y naturales” fue realizada por Juan Miguel Miró Recio-Mensaque bajo su dirección en el Departamento de Zoología de la Universidad de Sevilla. Asimismo, consideran que esta memoria de investigación reúne las condiciones necesarias para optar al Título de Doctor con Mención Internacional. Sevilla, a 29 de enero de 2021 V°B° de los directores Fdo.: César Megina Martínez Fdo.: José Carlos García Gómez La presente tesis doctoral ha sido financiada gracias a un contrato predoctoral para personal Investigador en Formación y becas de movilidad otorgados por el V Plan Propio de la Universidad de Sevilla. Parte de la financiación proviene del convenio firmado entre la Universidad de Sevilla, la Autoridad Portuaria de Sevilla y el Acuario de Sevilla en 2013. A mi familia INDEX GENERAL ABSTRACT 11 RESUMEN GENERAL 13 GENERAL INTRODUCTION 15 Objectives and thesis structure 19 References 21 MONITORING PROGRAM OF EARLY LIFE STAGES OF FISH ASSEMBLAGES IN THE GUADALQUIVIR ESTUARY 25 Abstract 25 Resumen 26 Introduction 27 Material and methods 28 Study area 28 Field sampling 28 Data analysis 30 Results 32 Environmental data 32 Biological data 38 Discussion 45 References 51 Supplementary data 57 MECHANISMS FOR HORIZONTAL MOVEMENTS IN A WELL-MIXED ESTUARY FOR BENTHIC AND PELAGIC FISH SPECIES 61 Abstract 61 Resumen 62 Introduction 63 Material and methods 65 Study area 65 Biological sampling 66 Physiochemical data collection 66 Data analysis 67 Results 68 Environmental analysis 68 Biological analysis 70 Discussion 72 Environmental conditions 72 Pomatoschistus spp. 73 Engraulis encrasicolus 75 General patterns 77 References 79 Supplementary data 84 MAINTENANCE DREDGING EFFECTS ON THE MACROFAUNA OF THE WATER COLUMN IN THE GUADALQUIVIR ESTUARY 89 Abstract 89 Resumen 90 Introduction 91 Material and methods 93 Study area 93 Field sampling 94 Data analysis 95 Results 96 Immediate effects 96 Environmental analysis 96 Biological analysis 97 Short- and mediumd-term effects 98 Environmental analysis 98 Biological analysis 100 Discussion 102 References 108 Supplementary data 114 EFFECTS OF FRESHET EVENTS ON THE BIOTIC AND ABIOTIC CONDITIONS IN A WELL-MIXED ESTUARY 121 Abstract 121 Resumen 122 Introduction 123 Material and methods 124 Study area 124 Field sampling 125 Data analysis 126 Results 127 Event 1 (discharge 2015) 127 Event 2 (discharge 2016) 134 Event 3 (discharge 2018) 140 Discussion 147 Physiochemical effects 148 Biological effects 149 References 153 Supplementary data 158 COMPARISON OF EARLY LIFE STAGES OF FISH AND ENVIRONMENTAL CONDITIONS BETWEEN ESTUARIES OF THE GULF OF CÁDIZ 165 Abstract 165 Resumen 166 Introduction 167 Material and methods 169 Study area 169 Field sampling 171 Data analysis 172 Results 173 Assemblage analysis 173 Environmental analysis 178 Discussion 181 References 188 GENERAL DISCUSSION 197 Estuaries as nursery areas 197 High productivity in the Guadalquivir estuary 198 Early life stages of fish assemblages 199 Mechanisms for horizontal movements 199 Anthropic and natural disturbances 200 Perspectives: research and management 202 References 204 GENERAL CONCLUSIONS 207 AGRADECIMIENTOS 209 General introduction 16 by the river inflow supplies them organic matter and nutrients continuously, supporting the bases of their complex trophic web (Hoffman et al., 2008). There are several distinct groups of primary producers as phytoplankton, salt marsh grass, sea grasses, mangrove swamps (in tropical latitudes), macroalgae and benthic algae. They are key drivers of carbon, nutrient and oxygen cycling and play a central role in determining water quality (Leston et al., 2008). Among primary producers, phytoplankton often account for at least half of ecosystem primary production (Cloern, 2001; Harrison and Turpin, 1982), supporting a fundamental link in estuarine food webs. Nonetheless, depending on the estuary type, other groups can play a more important contribution. For example, in shallow estuarine environments, benthic microalgae (known as microphytobenthos) usually form brown or green mats on the surface photic layer of the sediment (1-3 mm), whose densities are often 100–1000 times higher than in the water column (Underwood, 2001; Underwood and Kromkamp, 1999). Thus, benthic microalgae may account higher contributions of the total primary production (Cadée and Hegeman, 1974; De Jonge and Van Beusekom, 1992), and even represent an important proportion of chlorophyll concentration in water column by wind or tidal resuspension (Brito et al., 2012; Irigoien and Castel, 1997; Statham, 2012). Other important organisms which also carry out nutrient recycling, organic matter decomposition and conversion of small indigestible detrital materials to bigger structures for larger consumers are the microbes (Caraco et al., 1998). Suspended particles are able to provide habitats for bacteria, which attract flagellates and ciliates to feed on attached bacteria, forming aggregates of larger particles and flocculated materials. These “flocs” can be consumed directly by metazoan grazers, such as copepods and rotifers, passing materials and energy directly from detritus to higher trophic levels by microbial food web (Carpenter et al., 2005). In fact, in turbid estuaries were the photosynthesis activity in the water column can be limited, this heterotrophic energy pathway can be even more important for the base of the food web than the autotrophic way (Abrantes et al., 2013; Hitchcock et al., 2016; Hoffman et al., 2008). In turn, this extensive autotrophic community in combination with abundant detrital material fuel a planktonic food web which produces abundant zooplankton. Zooplankton, which are small animals that inhabit in the water column but cannot swim against moderate water currents, range from single-celled heterotrophic flagellates to complex metazoans such as copepods, chaetognaths, mysids, ctenophores, cnidarians and early life stages of many fish species (Day et al., 2013). The species that comprise this high biomass vary according to the geographical location of the estuary, temperature, and the salinity regime within each system. General introduction 17 Among the most abundant zooplankters groups in number and biomass are the following crustaceans: copepods (common genera include Acartia, Eurytemora and Pseudodiaptomus) and mysids (common genera include Neomysis, Mysis, Mesopodopsis, and Rhopalophthalmus) (David et al., 2016; Wooldridge, 1999). These small crustaceans have high secondary production and serve as prey for organisms such as zooplanktivorous fishes (Baldó and Drake, 2002), transferring carbon from phytoplankton and detrital pools into higher trophic levels (Vilas et al., 2008). The waters of most estuaries teem early life stages of fish, and often exceed to those found over adjacent continental shelves. For this reason, estuaries are considered as “nursery areas”. Still, not all of them accomplish the conditions of supporting higher densities, enhancing the larval development and growth, increasing their survival rates and stocking juvenile to adult populations (Beck et al., 2001). Estuaries usually contain a high diversity of habitats (i.e. subtidal or intertidal soft substratum, saltmarshes, biogenic reefs, seagrass meadows, shallow zones, etc.) which offer refuge against predators (Elliot and Hemingway, 2002). In addition, most of them present turbid zones which hinder their visual detection by adult piscivorous fish, while these zones can benefit fish larvae (their shorter visual field leaves fewer particles between them and their prey, reducing the interference with detection; Utne-Palm (2002)). On the other hand, the salinity gradient limits the distribution of different species along the estuaries depending on their osmoregulatory abilities. Instead, it attract a wide variety of marine, estuarine, diadromous and freshwater fish species, which can be assigned to distinct guilds (straggler, opportunistic, dependent, migrant, etc.) by their functional use of estuaries (Potter et al., 2015). A fundamental question in oceanography concerns those factors that control the input of larvae and juvenile of marine species to nursery grounds (Robins et al., 2013), as well as the mechanism that they use to remain into them (Forward and Tankersley, 2001). Processes such as pelagic larval delivery into estuaries depend on different biophysical interactions between regional hydrodynamic, offspring period, amount of larval supply and natural behaviour of every individual (Potter et al., 2015). Different hypotheses have been proposed for the recruitment of fish larvae, which can use multiple sensory cues (odor, sound, visual or geomagnetic) to detect estuarine environments and help them to navigate towards these areas (Teodósio et al., 2016). Once they reach estuarine habitats, they have to cope with strong water currents generated by freshwater input and periodical tidal flushing, which could be considered extreme environment for fish larvae (Teodósio and Garel, 2015). Distinct strategies have been reported, applying selective tidal stream transports with vertical and/or lateral migrations to move up or General introduction 18 downstream, or to maintain the position along the estuary, in combination with environmental cues (Forward and Tankersley, 2001). Still, the knowledge of the mechanism used by many species is unknown, especially in well-mixed estuaries whose vertical differences in water physiochemical conditions are scarce. Lots of marine early life stages of different fish species depend on estuaries to complete their life cycle, and many of them present an economical interest (Ray, 2005). The coastal and transitional areas are only a small fraction of the marine and brackish areas worldwide (~5%) but produce approximately half of the global fish catch per year (Palomares and Pauly, 2019). However, despite of the important ecosystem service that offer the estuaries, they are one of the environments most threatened by humans (Lotze et al., 2006). More than 60% of the Earth’s population are living in coastal areas (Ray, 2006) and many anthropic activities in or near aquatic habitats generate alterations in their environmental conditions which could affect the organism that inhabit them (Halpern et al., 2008; Lotze et al., 2006). The rapid urban and agriculture development of the last decades (Lee et al., 2012; Wu et al., 2019) are affecting environmental conditions of rivers, wetlands, floodplains and estuaries by flow alteration and high sediment, nutrient or pollutant inputs (González-Ortegón and Drake, 2012; Rolls and Bond, 2017). Also, dredging of navigation channels in estuaries in order to reclaim land and to allow large ship access to inland waterways is another increasing source of disturbance since the container port industry has experienced an exponential growth transporting 80% of world’s commodities currently (Tsolaki and Diamadopoulos, 2010; Yap and Lam, 2013). Additionally, global climate change is imposing complementary modifications; recent studies, based on 30 years of historical data, have found a significant decrease in precipitations in south-central European and Mediterranean river basins (Xoplaki et al., 2004). This, together with anthropogenic water damming for diverse uses, has resulted in an increase in the number of days with low flow (Lobanova et al., 2018; Papadimitriou et al., 2016). These modifications have been reported to decrease the ecological status of affected ecosystems (Poff and Zimmerman, 2010), with fish being a taxonomic group of major concern (Schinegger et al., 2016). Moreover, climatic predictions in temperate regions indicate increasing temperatures and sea levels, subject to more erratic rainfall and freshwater discharges, and the likelihood of more frequent and severe droughts and storms (Day and Rybczyk, 2019). Under these challenges, interpreting the link between freshwater flows, water physiochemical characteristics and plankton dynamic within estuaries is crucial to its management and conservation as they undergo change due to climate and anthropogenic General introduction 19 development (Bates et al., 2008; Hughes, 2003). EU member states have legislated to manage and protect all running waters under the Water Framework Directive (European Commission, 2000), but the River Basin Management Plans from 2018 indicated that 60% of European water bodies failed to achieve good ecological status (European Environment Agency, 2018). Monitoring programs are necessary to assess and enhance the ecological status of aquatic ecosystems, and in the case of estuaries, which are continually flowing between unstable states, long-term or permanent studies are especially recommended (Henderson et al., 2011). Thus, it would generate a baseline knowledge about the variability of assemblages and the ecological preferences of its constituents which help us to predict effects of the modifications in the ecosystem, whether induced by humans or not (Soetaert and Van Rijswijk, 1993), and propose solutions to different kind of management problems. Objectives and thesis structure The main aim of this thesis was to increase the knowledge of recruitment ecology processes for early life stages of fish in estuaries, using the Guadalquivir as study area. For that general objective, different specifics approaches were performed. We determined the composition, abundance and structure of its assemblages in relation with multiple environmental variables in its estuarine and nearshore zones during three consecutive years. During that period, different short- and medium-term disturbances were observed and analysed, such as natural freseht events that occurred after heavy rainfall or anthropic disturbances due to a maintenance dredging operation. Also, we studied the mechanism for horizontal movements inside of the estuary in the most abundant fish species, Engraulis encrasicolus and Pomatoschistus spp. Finally, we compared the nursery function of the Guadalquivir estuary with other estuaries in the Gulf of Cádiz to contextualize its contribution for the fish populations in the region. In addition to the introduction presented above, this thesis is composed by five chapters, in which the objectives are fully addressed, as well as one final section with a general discussion of the results obtained. Finally, the principal conclusions from this thesis are presented. Specifically: In chapter 1, we generated a baseline study of early life stages of fish assemblages in the Guadalquivir estuary using standard methodology to make the information comparable with other studies. We took samples monthly from October 2015 to September 2018 in its inner and nearshore zones to compare the spatio-temporal patterns of their larvae and juvenile fish General introduction 20 assemblages. At the same time, multiple biotic and abiotic variables were sampled to analyse their relations with the environmental conditions and the interactions of its trophic web. In chapter 2, we analysed the mechanisms for horizontal movements and the use of different zones across the transverse section of the estuary in two kind of fish species, the pelagic Engraulis encrasicolus and the benthic Pomatoschistus spp. Also, we determined the possible environmental cues which could lead the individuals of these species to follow their strategies. In chapter 3, we analysed the effects of a maintenance dredging operation from multiple approaches (immediate, short and medium term) in the physiochemical variables, the early life stages of fish and other macrofauna groups present in the water column of two zones with different salinity ranges. In chapter 4, we investigate the short-term effects of three different kinds (intensity, duration and period) of natural freshet events on the early life stages of fish species, other macrofauna groups and the water physiochemical conditions in the inner and outer zones of the estuary. 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In: Estuaries of South Africa. Cambridge University Press. https://doi.org/10.1017/cbo9780511525490.007 Xoplaki, E., González-Rouco, J.F., Luterbacher, J., Wanner, H., 2004. Wet season Mediterranean precipitation variability: Influence of large-scale dynamics and trends. Clim. Dyn. 23, 63–78. https://doi.org/10.1007/s00382-004-0422-0 Yap, W.Y., Lam, J.S.L., 2013. 80 million-twenty-foot-equivalent-unit container port? Sustainability issues in port and coastal development. Ocean Coast. Manag. 71, 13–25. https://doi.org/10.1016/j.ocecoaman.2012.10.011 25 1. MONITORING PROGRAM OF EARLY LIFE STAGES OF FISH ASSEMBLAGES IN THE GUADALQUIVIR ESTUARY Abstract The species composition, abundance and distribution of the early life stages of fishes in the Guadalquivir estuary and adjacent coastal area were studied. Sampling was carried out monthly during three consecutive years (October 2015 to September 2018) with 3 stations in the nearshore zone and 3 stations in the estuarine zone (poly-, meso- and oligohaline water masses). Multiple physiochemical and biological variables (distinct zooplankton groups) were measured to analyse their influences in the fish assemblage structure. Much higher abundances of early fish stages were found in the inner zone, showing a clear nursery function for many marine species of the region. Similar seasonal fluctuations were observed along the year in both zones, being the temperature the most influential factor in the temporal variation of assemblages and secondary production. Biological and physiochemical characteristics were spatially similar in the nearshore zone, while the inner zone showed different environments marked by the salinity, being the poly- and mesohaline waters the most diverse and productive. Hydrologic fluctuations in the region influenced the freshwater inputs into the estuary, which provoked changes between the dry and wet years in the recruitment time and abundance of the dominant fish species (Pomatoschistus spp. and Engraulis encrasicolus). Organic matter, supplied in high concentrations by the freshwater inputs, seemed to be the main food resource for the base of the trophic web in this estuary, which presented a high secondary production of mesozooplankton, macrozooplankton and early fish stages. Also, different trophic interactions were found along the temporal dynamic of these groups. The high biotic and abiotic variability observed in this ecosystem, in short (monthly) and long (annually) term, suggests performing different monitoring programs with multiple approaches to better understand the ecological responses to distinct situations or disturbances. Chapter 1 Monitoring program 32 3. Results 3.1. Environmental data Physiochemical condition of the water column along the whole estuary was plotted in the Figure 2. The estuary showed a horizontal salinity gradient, with a different spatial range of the distinct water masses. The polyhaline water mass (30-18 PSU) extended around 10 Km from Sanlúcar to Salinas; the mesohaline water mass (18-5 PSU) extended around 20 Km from Salinas to Tarfia; and the oligohaline water mass (5 – 0.5 PSU) extended 50 Km upstream, approximately, from Tarfia until the port entrance of Seville (Esclusa). Low vertical stratification was observed only in the polyhaline water mass close to the river mouth at the beginning of the flood tide. The turbidity showed a clear vertical stratification with higher values in the bottom layers. The maximum turbidity zone during this sampling was recorded between the kilometre 30 and 60 Figure 2. Physiochemical variables (salinity, (A), turbidity (B), dissolved oxygen (C), temperature (D), chlorophyll-a (E) and pH (F) recorded in the water column (standardized depth) along the whole estuary from the river mouth to Seville during the flood tide of 15-09-2015. Names on top are local names to different sections along the Guadalquivir estuary. Chapter 1 Monitoring program 33 from the river mouth, with levels up to 1750 NTU. Dissolved oxygen concentration, which showed the same pattern than oxygen saturation, was stable along most of the estuary with levels around 6.5 mg/L, except for the last 10 Km upstream, which reached almost hypoxic conditions (<2 mg/L) in the bottom layers. The temperature showed a soft stratification with Figure 3. Temporal series of: daily mean of freshwater input from Alcalá del Río Dam and local daily accumulated rainfall (A); water turbidity (B), chlorophyll-a (C), pH (D), dissolved oxygen (E), oxygen saturation (F), temperature (G) and salinity (H) in every station (Doñana, Canal, Faro) of the nearshore zone of the Guadalquivir estuary. Chapter 1 Monitoring program 34 higher levels close to the superficial layers, as well as a gradual increment upstream. Chlorophyll concentration was lower in the river mouth, especially in the surface. The inner parts of the estuary showed higher levels despite of high turbidity, which could limit the photosynthesis Figure 4. Temporal series of: daily mean of freshwater input from Alcalá del Río Dam and local daily accumulated rainfall (A); water turbidity (B), chlorophyll-a (C), pH (D), dissolved oxygen (E), oxygen saturation (F), temperature (G) and salinity (H) in every station (25, 15, 5 PSU) of the inner zone of the Guadalquivir estuary. Chapter 1 Monitoring program 35 activity in most of the water column. The pH decreased gradually from the river mouth (8.2) toward upstream (7.6), with a more notable decline in the last 10 Km. Freshwater input into the Guadalquivir estuary and local rainfall were plotted in the Figure 3A. The average of water discharged between 01-10-2015 and 30-09-2018 was 38.07 m3/s. The freshwater input was continued and stable along years, although several high discharge events were observed in autumn and spring seasons due to the rainfalls. Most of the freshets were temporally shorts (1-3 days) and with discharges lower than 300 m3/s (November 2015, May and November 2016 and March 2017). A longer (1 month approx.) and higher discharge (up to 1080 m3/s) was registered in March 2018. Figures 3 and 4 show the temporal series of depth averaged physiochemical profiles in every station, outside and inside the estuary, respectively. Technical problems and weather conditions precluded to collect the data in several months. Turbidity levels, directly correlated with total suspended solids, were different between zones, being the outside (Figure 3B) notably lower than inside (Figure 4B and Figure S.1). Similar levels among nearshore stations were observed, while the inner stations showed a gradual increment in upper water masses (25 < 15 < 5 PSU). Turbidity increase was associate to events of high freshwater inputs, even in the outer stations, being the highest levels recorded in March 2018 in inner stations. In fact, the levels registered in the three inner stations during this event were higher than the maximum quantification limit of the multiprobe (5400 NTU), therefore, real levels would be even higher. Instead, total suspended solids (Figure 5A and Figure S.2), which showed a similar pattern as turbidity, reached a maximum concentration higher than 6000 mg/L in all inner stations. Total suspended solids showed the same pattern as turbidity. Most of the suspended solids was inorganic matter, with more than 70% in all stations during the whole study (Figure 5C). No differences were observed between nearshore stations, but a trend was found in the inner stations, which showed a slight gradual decrease of suspended organic matter proportion from downstream to upstream water masses (Figure 5B). Additionally, the freshet of March 2018 notably decreased the proportion of suspended organic matter in the water column. Chlorophyll concentration did not show a clear pattern in the nearshore stations due to high fluctuation inter months (Figure 3C). Still, a slight tendency of higher concentration in summer and lower in winter arise. This trend was more notable in the inner zone (Figure 4C). Higher concentrations were usually in 5 and 15 PSU stations. Also, a punctual increment was observed during the freshet of March 2018 in 25 and 15 PSU stations, while the Canal station showed the opposite tendency. Similar, temporal pattern was observed in pH levels of outer Chapter 1 Monitoring program 36 zone (Figure 3D). In fact, the increase of pH observed in August 2016 coincided with the chlorophyll increment. Instead, pH levels inside of the estuary were seasonally stable, but with differences between stations (Figure 4D). The pH values increased gradually toward upstream stations. Also, the freshets of November 2016 and March 2018 caused a high decrease of the pH levels. Oxygen saturation was higher in the outer zone with an intermonth fluctuation (Figure 3F), but always with more than 90%. Doñana station usually showed higher levels. Inner stations showed stable values along the whole study, with a gradual decrease toward upstream stations (Figure 4F). The freshets of November 2016 and March 2018 altered the saturation, with a Figure 5. Temporal series of total suspended solids (A), suspended organic (B) and inorganic (C) matter in every station of both zones of the Guadalquivir estuary. Inside Outside 07/16 09/16 11/16 01/17 03/17 05/17 07/17 09/17 11/17 01/18 03/18 05/18 07/18 09/18 30 60 90 120 0 2000 4000 6000 Total Suspended Solids (mg/L) Inside Outside 07/16 09/16 11/16 01/17 03/17 05/17 07/17 09/17 11/17 01/18 03/18 05/18 07/18 09/18 10 15 20 25 30 10 15 20 25 30 Suspended organic matter (%) Inside Outside 07/16 09/16 11/16 01/17 03/17 05/17 07/17 09/17 11/17 01/18 03/18 05/18 07/18 09/18 80 85 90 80 85 90 Suspended inorganic matter (%) A B C Chapter 1 Monitoring program 37 notably decrease in both zones. The dissolved oxygen fluctuated seasonally, with higher concentration in winter and spring, and lower in summer and autumn. In nearshore stations, oxygen concentration (Figure 3E) followed the same pattern than oxygen saturation, while in inner stations, oxygen concentration (Figure 4E) increased upstream, contrary to oxygen saturation. Also, the freshets caused punctual decreases in its concentration in all stations. The temperature showed a seasonal variation with an expected opposite pattern than oxygen concentration, reaching the highest levels in summer and the lowest in winter. Different ranges of temperature were observed between the outer (12-26 ⁰C; Figure 3G) and inner (10-28 ⁰C; Figure 4G) zones, being more extreme in the latter, especially in upstream stations. The nearshore zone presented a riverine influence in the salinity levels with a temporal variation (34-38 PSU), being higher in the summer and lower in the winter (Figure 3H). The inner Figure 6. Temporal series of total NO3 (A), NO2 (B), NH4 (C), PO4 (D) and SiO4 (E) in every station of the Guadalquivir estuary. Chapter 1 Monitoring program 38 stations were selected because of their salinities, hence they do not show a significant variation in salinity, but seasonal variations were reflected in their position. The only station showing some variability was 25 PSU because it showed a higher vertical stratification in autumn and winter (Figure 4H). Temporal series of the nutrients measured in the water samples were plotted in the Figure 6 (technical problems in the analysis methodology caused the data from June 2016 to June 2017 to be rejected). Different temporal and spatial patterns were observed for each nutrient, although the Canal station showed the lower levels in all of them. NO3 showed seasonal oscillations, with lower concentration in autumn, and spatial differences, generally with higher levels in upstream stations (Figure 6A). Similar spatial trend was found for NO2, but the temporal tendency was the opposite, with lower concentration in winter and spring seasons (Figure 6B). No clear spatial pattern was found for NH4 concentration, except for the lowest levels in Canal station, and it showed several punctual increments (Figure 6C). PO4 and SiO4 showed similar spatio-temporal patterns with stable values along the study and a gradual increment of concentrations towards upstream stations (Figure 6D and 6F). 3.2. Biological data In total, 121277 fish individuals in early life stages belonging to 41 species, 32 genera and 23 families were caught in the Guadalquivir estuary during the whole study (Table S.1). Total fish abundance was much higher in the estuarine zone than the nearshore, collecting 112528 individuals of 37 species inside and 8749 individuals of 30 species outside. The nMDS ordination of all samples indicated clear differences in the structure of early fish assemblages between the inner and nearshore zones (Figure 7). Figure 7. nMDS ordination of early life stages of fish samples. Samples coded by zones. Chapter 1 Monitoring program 39 Table 1. PERMANOVA results of the Bray-Curtis similarity matrix based on the fourth-root-transformed assemblage data in every zone. Table 2. Pair-wise analysis of significant terms in PERMANOVA results of assemblages in inner zone. Table 3. PERMANOVA results of the Euclidian similarity matrix based on species richness and Shannon index and total fish abundance data in every zone. Richness df SS MS Pseudo-F P(perm) perms df SS MS Pseudo-F P(perm) perms Station 2 1.7837 0.89186 0.21751 0.7883 9956 2 283.38 141.69 35.844 0.0001 9949 Year 2 14.168 7.0838 0.58955 0.4725 9922 2 43.16 21.58 0.68667 0.515 9956 Month (Year) 29 468.33 16.149 16.846 0.0001 9913 31 985.07 31.777 28.18 0.0001 9896 Station x Year 4 8.3557 2.0889 0.48654 0.7383 9963 4 32.533 8.1332 2.0328 0.109 9952 Station x Month (Year) 33 150.22 4.5521 4.7486 0.0001 9878 62 250.54 4.041 3.5836 0.0001 9868 Res 259 248.28 0.95862 340 383.4 1.1276 Total 329 920.62 441 1977.1 Shannon index df SS MS Pseudo-F P(perm) perms df SS MS Pseudo-F P(perm) perms Station 2 0.18478 0.0924 0.27851 0.7487 9957 2 5.0147 2.5073 9.1581 0.0005 9933 Year 2 0.50654 0.25327 0.31439 0.6083 9926 2 3.4817 1.7408 1.9653 0.1553 9938 Month (Year) 29 31.14 1.0738 12.176 0.0001 9892 31 27.757 0.89539 17.298 0.0001 9883 Station x Year 4 0.79473 0.19868 0.57307 0.6857 9954 4 0.16285 0.0407 0.14668 0.9626 9956 Station x Month (Year) 33 12.103 0.36675 4.1585 0.0001 9886 62 17.404 0.28071 5.423 0.0001 9874 Res 259 22.842 0.0882 340 17.599 0.0518 Total 329 68.745 441 72.363 Total abundance df SS MS Pseudo-F P(perm) perms df SS MS Pseudo-F P(perm) perms Station 249572 24786 0.4224 0.4151 9896 257463000 28732000 15.026 0.0001 9954 Year 2200260 100130 1.0653 0.3439 9946 220276000 10138000 1.4244 0.266 9955 Month (Year) 29 3301900 113860 2.7873 0.0438 9893 31 223070000 7195900 22.272 0.0001 9874 Station x Year 481391 20348 0.34041 0.7245 9945 47904500 1976100 1.0191 0.4019 9954 Station x Month (Year) 33 2021000 61243 1.4993 0.0359 9880 62 121620000 1961700 6.0715 0.0001 9879 Res 259 10580000 40849 340 109850000 323090 Total 329 16497000 441 542910000 Inner zone Nearshore zone Table 4. Pair-wise analysis of significant terms in PERMANOVA results of diversity indices and total fish abundance in inner zone. Richness t P(perm) perms 25 PSU - 15 PSU 0.40297 0.6918 9839 25 PSU - 5 PSU 6.6771 0.0001 9858 15 PSU - 5 PSU 6.8372 0.0001 9835 Shannon index t P(perm) perms 25 PSU - 15 PSU 1.948 0.068 9836 25 PSU - 5 PSU 3.9967 0.0008 9818 15 PSU - 5 PSU 2.4682 0.0238 9844 Total abundance t P(perm) perms 25 PSU - 15 PSU 0.24448 0.8066 9841 25 PSU - 5 PSU 4.0679 0.0004 9850 15 PSU - 5 PSU 4.986 0.0001 9814 Chapter 1 Monitoring program 40 PERMANOVA analysis, separating inner and nearshore zones, revealed different patterns for each one, although the structure varied inter-monthly in all stations of both zones (Table 1). The assemblage was annually and spatially constant in nearshore zone, with no differences between stations and years. Conversely, the inner assemblage showed differences between stations and years. Pair-wise comparison showed that all the assemblages of inner stations were different from each other, and only the first year was different with the third one (Table 2). Total fish abundance, species richness and Shannon index showed similar patterns (Table 3). No diversity and total fish abundance differences were found between years in both zones, although it varied inter-monthly in all stations (Figure 8). Generally, lower diversity was observed in summer season, due to the increment of total fish abundance, which was dominated by a few species. Only the inner zone showed differences between stations, being 5 PSU significantly lower in abundance and diversity than the others (Table 4). SIMPER analysis of zones and stations combined (Table 5) showed that Engraulis encrasicolus, and Sardina pilchardus in a lesser extent, were characteristics species in most stations of both zones. Additionally, Pomatoschistus spp. (Pomatoschistus minutus and Figure 8. Boxplot of species richness (A) and Shannon index (B) per month in every station of both zones during the study period. Chapter 1 Monitoring program 41 Pomatoschistus microps) and Argyrosomus regius contributed to the similarity of the inner zone, while Aphia minuta contributed to the outer zone. Temporal series of fish species that most contributed to the similarity of every zone were plotted in the Figure 9. Pomatoschistus spp. was abundant only inside of the estuary, mainly in spring and summer seasons, being the 25 and 15 PSU stations the densest (Figure 9A). Particular increment was observed in all stations, even in Canal, during and after the freshet of March 2018. Engraulis encrasicolus showed similar tendencies in both zones, although inner stations contained much higher densities, except for 5 PSU (Figure 9B). The recruitment period of anchovy was mainly along the late spring and summer seasons, but the months of its maximum density peaks changed between years (2016: August; 2017: May; 2018: July), as well as the temporal range of the period. In fact, during the last year, its abundance was lower in the inner zone, reducing its recruitment spatial and temporally to only polyhaline water mass in July. Argyrosomus regius was characteristic inside the estuary, although some individuals were caught outside too (Figure 9C). Temporal pattern was found with higher abundances during the summer and early autumn, but no clear differences were observed between stations. Sardina pilchardus started its recruitment period during the end of winter, reaching the highest densities in the spring season (Figure 9D). No spatial differences were observed in nearshore stations, Table 5. Results of SIMPER analysis on the abundance of all larval and juvenile fish species from every zone and their stations. Chapter 1 Monitoring program 48 which maintained similar density levels as other years. Still, the high invasive character and the recurrent demographic blooms of both species should be monitored to assess potential ecological interactions in the Guadalquivir estuary. Most of dominant estuary-dependent fish species showed generally similar catch trends in this study when compared to past investigations in the inner zone of Guadalquivir estuary (Drake et al., 2002; González-Ortegón et al., 2012). Pomatoschistus spp. were one of the most abundant fish species in all inner stations, while their presence in the nearshore zone was negligible. Several studies have documented seaward migration of these gobies during the early spring for reproduction in other areas (Guelinckx et al., 2008; Pampoulie et al., 1999), however no evidences were found in this research. Still, different development stages were found along the whole year. Individuals dominated mainly by early stages were caught during the spring, which grew up to adult stages along the summer and autumn, showing the highest densities, and later, declined in winter. Also, Pomatoschistus spp. showed a high recruitment response after the freshet event of March 2018, whose abundances were the highest of the whole study. Therefore, in the Guadalquivir estuary, it is possible, that this species could migrate to outer and deeper zones than nearshore to reproduce in winter, and the estuarine signals released further by the freshet during the recruitment season provoked a higher attraction of early stages into the estuary. Contrary behaviour has been proposed for the meagre Argyrosomus regius in the Gulf of Cádiz, where adults individuals could migrate into the estuaries to reproduce between March to August, and early stages could remain inside during the 2-3 first years of life (González- Quirós et al., 2011). Our catches were higher in inner stations, mainly in summer and early autumn, which coincide in space and time with the spawning and hatchery process suggested. However, developing larvae were also found, at the same period in the nearshore zone, which could indicate that estuary mouth could be also a spawning zone, or larvae do not stay so long periods into the estuaries. Further research would be necessary to elucidate the early development process of A. regius. The anchovy Engraulis encrasicolus maintained a high contribution to catches along the whole year, but with higher densities during the summer, especially in poly and mesohaline stations. Its spatio-temporal trend remained similar as the previous work performed by Drake et al. (2007) from 1997 to 2005. Nonetheless, the high freshet event of March 2018 seemed to influence on the high recruitment period with an opposite pattern of Pomatoschistus spp., being shorter and with lower abundance, especially in the mesohaline water mass. The similar abundance (or even higher) as previous years in the nearshore zone suggests that external factors did not influence the approach of early stages toward the estuary. Hence, it indicates Chapter 1 Monitoring program 49 that some internal factors could influence on its recruitment. Among the distinct environmental variables measured, turbidity showed a different pattern in comparison with previous years. Its levels, even though declined quickly after the freshet event, maintained elevated in the following months with a slow recovery until the summer in meso and oligohaline water masses, covering most of the high recruitment period of this species. In fact, De Carvalho-Souza et al. (2018) showed that turbidity levels higher than 100 NTU was negative for the early anchovy in the Guadalquivir estuary, being all the averaged values registered after the freshet higher than this reference in the meso and oligohaline water masses. Anchovy was also the most abundant species in the outside zone, followed by Aphia minuta, which seemed to prefer more saline stations as also reported González-Ortegón et al. (2015). In addition, other species as Sardina pilchardus, Dicologoglossa cuneata and several sparids contributed, in lesser extent, to the assemblage of the nearshore zone, showing a composition comparable to that of other coastal waters in the Gulf of Cádiz (Baldó et al., 2006). Conspicuously, Sardina pilchardus, despite of being also characteristic in poly and mesohaline stations, showed much lower densities in the estuarine zone in comparison with previous records during 1997-1999 by Drake et al. (2002), suggesting a dramatic temporal decline. Similar trend has been reported around the Iberian Peninsula waters for adult stocks during the last decade (ICES, 2019), where the authorities have recently developed a restoration plan to manage the fishery pressure over this species (MAPAMA, 2018). In addition, different studies revealed a possible shift of sardine populations to northwards Atlantic waters during the last years, being the increment of the sea surface temperature in the region the main driver (Alheit et al., 2012; Beare et al., 2004; Montero-Serra et al., 2015). When large dam discharges occur in the estuary, they can cause multiple alterations in its physiochemical and biological conditions, even in long-term. Compression of the longitudinal salinity gradient or extreme turbidity levels have been registered in the Guadalquivir estuary previously (Díez-Minguito et al., 2013; Ruiz et al., 2017). In addition, we also observed an increment of chlorophyll concentration in the inner zone at the same time that total suspended solids and organic matter, which could indicate an import of phytoplankton from the upstream water reservoirs (González-Ortegón and Drake, 2012) and/or a higher resuspension of microphytobenthos from the riversides (Díez-Minguito and de Swart, 2020). On the other hand, depending on the kind of discharge, plankton organisms could be pushed downstream or even flushed out of the estuary (Chícharo et al., 2006), as showed Pomatoschistus spp. in March 2018, but also they could be attracted by the higher spread of estuarine cues (Kingsford and Suthers, 1994). González-Ortegón et al. (2012) also showed that the nekton of the Guadalquivir estuary Chapter 1 Monitoring program 50 could responded to high freshwater inputs with immediate changes in its structure, but the recovery of environmental conditions within the estuary allowed its reestablishment. Estuarine biota is well-adapted to cope with different types of stress and so the areas may be regarded as resilient because of the inherent variability of these ecosystems (Elliott and Quintino, 2007). Notwithstanding, the short-term process of how plankton organisms restore to normal conditions in the outside and inside zones of the estuary is still scarcely known. In conclusion, the Guadalquivir estuary showed a clear nursery function, with much higher abundance of early life stages of fishes and other zooplankton groups in its estuarine zone than the surrounding area. The nearshore zone showed similar environmental conditions, while the inner zone was more diverse, being the poly and mesohaline water masses the most productive. The freshwater inputs, in addition to generate a longitudinal salinity gradient, supplied high amounts of organic matter, which seems to be the main food resource of its complex trophic web. 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Trophic ecology of two non-native hydrozoan medusae in the upper San Francisco Estuary. Mar. Freshw. Res. 62, 952–961. https://doi.org/10.1071/MF10221 Zuur, A.F., Ieno, E.N., Walker, N.J., Saveliev, A.A., Smith, G.M., 2009. Mixed Effects Models and Extensions in Ecology With R. Springer, New York, USA. Zuur, A.F., Saliev, A.A., Ieno, E.N., 2015. A Beginner’s Guide to Generalised Additive Mixed Models With R. Highland Statistics Ltd, Newburgh, UK. Chapter 1 Monitoring program 57 Supplementary data Figure S.1. Zoomed facet of the Figure 4B without extreme values of March 2018. Temporal series of water turbidity in every station (25, 15, 5 PSU) of the inner zone of the Guadalquivir estuary. 0 500 1000 1500 2000 2500 3000 10/15 12/15 02/16 04/16 06/16 08/16 10/16 12/16 02/17 04/17 06/17 08/17 10/17 12/17 02/18 04/18 06/18 08/18 10/18 Turbidity (NTU) Station 25 PSU 15 PSU 5 PSU Figure S.2. Zoomed facet of the Figure 5A without extreme values of March 2018. Temporal series of total suspended solids in every station (25, 15, 5 PSU) of the inner zone of the Guadalquivir estuary. 0 500 1000 1500 2000 2500 3000 3500 07/16 09/16 11/16 01/17 03/17 05/17 07/17 09/17 11/17 01/18 03/18 05/18 07/18 09/18 Total Suspended Solids (mg/L) Station 25 PSU 15 PSU 5 PSU Chapter 2 Mechanisms for horizontal movements 64 have tested the STST in stratified or partially stratified estuaries, where there are notably differences between the upper and lower water layers. However, in mixed estuaries, there are weak differences between water layers (Fortier and Leggett, 1982). Thus, fish larvae may need to adopt alternative strategies for successful ingress into estuarine nursery grounds. Other mechanisms have been proposed: wind forcing, residual bottom inflow and passive ingress via tidal processes (Morgan et al., 2011; Roman and Boicourt, 1999; Simons et al., 2006). Also, lateral movements have been considered as another strategy (Forward Jr et al., 1999) because along river flow can have pronounced lateral variability, depending on bathymetry and water mixing (Valle-Levinson and Lwiza, 1995). The Guadalquivir is a well-mixed mesotidal estuary (Vanney, 1970) in the Gulf of Cadiz (Southwestern Iberian Peninsula). It has suffered an extensive anthropic alteration during the recent history with construction of numerous dams along the river basin, by reducing the natural course with multiple river cuts to facilitate vessel navigation, decreasing of marshes for agriculture fields, isolating of its natural marshes from the main channel and the consequent reduction of the tidal flooding, etc. (Llope, 2017; Ruiz et al., 2015). Hence, the estuary is currently composed of the main river channel with a few tidal creeks, but with a significant reduction of the original intertidal area. Still, this estuary has been considered the most productive in the region (Miró et al., 2020). The early life stages of fish community in Guadalquivir estuary have been widely studied, being the dry-warm season the period with higher densities (Drake et al., 2007). The main species captured are the anchovy Engraulis encrasicolus (Linnaeus, 1758) and the gobies Pomatoschistus spp. [mainly Pomatoschistus minutus (Pallas, 1770) and Pomatoschistus microps (Kroyer, 1838)] (Baldó and Drake, 2002). The anchovy is a marine migrant fish with its larval maximum recruitment period from May to November in Guadalquivir estuary (Drake et al., 2007), and their spawning area have been reported offshore (Baldó et al., 2006). It is a commercial species important in the fishery sector of the region (Ruiz et al., 2017). On the other hand, the gobies are resident estuarine species typical in many estuaries in temperate zone. Their seaward migration during early spring for reproduction has been documented by several authors (Guelinckx et al., 2008; Pampoulie et al., 1999), but not in this estuary. Although STST is widely accepted as the mechanism by which larvae move into estuaries, other mechanisms have been proposed, but are rarely evaluated in combination with other factors. This study aims to analyse the movement strategies and the use of different zones across the transverse section of the estuary of two kind of fish species, the pelagic Engraulis Chapter 2 Mechanisms for horizontal movements 65 encrasicolus and the benthic Pomatoschistus spp., as well as to elucidate the possible environmental cues which could lead the individuals of these species to follow their strategy. For that, we have tested the STST hypothesis combined with lateral migrations, water physiochemical characteristics and wind effects from an Eulerian approach (e. g. over time at a fixed estuary section in space). 2. Material and Methods 2.1. Study area The Guadalquivir estuary is located in South-West of Iberian Peninsula, a warm temperate region with Mediterranean climate conditions, and its waters flow to the Gulf of Cadiz (Atlantic Ocean; Figure 1). The estuary extends 110 km inland from its mouth. It is well-mixed mesotidal system with 3.5 m amplitude range (spring tides) in the river mouth (Díez-Minguito et al., 2012). The estuary is convergent with widths of 800 m near the mouth and 150 m at the head (Díez-Minguito et al., 2012). The morphology of the estuary is a single channel isolated from surrounding natural areas in most of its length, with a main navigable channel of 7.1 m average depth (Ruiz et al., 2015). Figure 1. Sampling station locality and scheme of cross section with the zones and depths (S: surface; B: bottom). Bottom depth and across distance are plotted with a proportion of 1:20 approximately. Chapter 2 Mechanisms for horizontal movements 66 2.2. Biological sampling The sampling was carried out during the summer of 2017, in three different cruises during spring tides. Every sampling cruise was done in two consecutive days during the daylight (12th – 13th June, 11th – 12th July and 9th – 10th August 2017). Samples were collected against main flow direction in a passive haul with an anchored boat along the ebb and flood tides. Three different zones were selected across the section of the estuary, 13 km upstream the river mouth: one in every side of the estuary section with a depth range of 2.2 – 4.2 m, over the shoals, and a third zone in the middle of the channel with 6.8 – 8.8 m (Figure 1). The surface and the bottom were simultaneously sampled to determine whether there were any vertical migration patterns. A plankton net of 60 cm of diameter was used for subsurface sampling, and an epibenthic sledge trawl of 43 x 60 cm for the bottom, both nets with 500 µm of mesh size. Each net was equipped with a flowmeter (2030R General Oceanics) and the volume filtered per tow was 90 ± 27 m3. The trawl deposited in the bottom had a strangulation mechanism, which was released once reaching the bottom, to keep the net closed during the up and down movement of the tow. At these two depths (surface-bottom), four samples were collected in every zone at different times along the flood tide and four along the ebb tide; this was replicated in every cruise. Samples were fixed in ethanol 70% and early stages of E. encrasicolus and Pomatoschistus spp. were sorted. Also, in the case of E. encrasicolus, due to the presence of individuals in different life stages, their total length was measured using an image-analysis system, where individuals were scanned and measured with the software Image J. We did not find differences in sizes and life stages of Pomatoschistus spp., and we did not perform size analysis with these species. 2.3. Physiochemical data collection Simultaneously to every biological sampling, physiochemical and current velocity profiles of the whole water column were recorded in every zone. Physiochemical data were taken with a multiprobe with depth, temperature, salinity, turbidity, dissolved oxygen (DO), chlorophyll-a (Chla) and pH sensors (Eureka Manta2). Current velocity was measured with an Acoustic Doppler Current Profiler (ADCP 1 MHz – Aquadopp Profiler Nortek) from the surface. The ADCP was used in surface-tracking mode, and velocity profiles, per triplicate, were obtained as ensembles averaged over 120 s, in cells of 0.5 m thickness from surface to bottom, during every fishing tow. Wind speed and direction data were recorded every five minutes in the meteorological station Vetalengua (6°22' 55.96381"W – 36°55'21.93697"N) and supported by the Spanish National Research Council (CSIC-EBD-ICTS). Chapter 2 Mechanisms for horizontal movements 67 2.4. Data analysis Physiochemical variables of every profile (temperature, salinity, turbidity, DO, Chla, pH and magnitude velocity current) in each sample tow were averaged in a single value over the first meter, for surface samples, and the last meter, for the bottom samples. Results of all environmental variables were plotted with boxplot grouped by depth, tide and zone using the package ‘ggplot2’ of R 3.5.2 software (R Development Core Team, 2018). Physiochemical variables were organized in a variable/sample matrix and a Euclidian distance similarity matrix was calculated on normalised data. The differences in the multivariate structure of environmental variables were analysed in a distance-based permutational multivariate analysis of variance (PERMANOVA) (Anderson, 2001; Mcardle and Anderson, 2001). When the number of total possible permutations to obtain the p-values were low, we used the estimate obtained by Monte Carlo sampling (Anderson and Robinson, 2003). The experimental design included 3 crossed fixed factors: depth (2 levels, “Surface and Bottom”), tide (2 levels, “Flood and Ebb”) and zone (3 levels, “West side, Channel and East side”); and 2 random factors: cruise (3 levels, “June, July and August”), orthogonal to the three previous factors, and sampling time (4 levels, “1-4”) nested within tide, zone and cruise. This last factor is a random block used to consider the simultaneous samples taken in surface and bottom; in this sense, this is a “randomised block design” and it was analysed following the general consensus of excluding the interaction term between “Depth” and “Sampling time” from the analysis (Anderson et al., 2008). When appropriate, significant terms with more than two levels were analysed using pairwise comparison with the PERMANOVA test. In addition, patterns on environmental variables were graphically represented using a plot of the two first principal axes of a Principal Component Analysis (PCA). Multivariate analyses were performed using the software PRIMER v6.1.11 and PERMANOVA+ v1.0.1 statistical package (Clarke and Gorley, 2006). Data on wind speed and direction of every sampling day were summarized during each tide period using a wind rose plot with the package ‘openair’ in R software (R Core Team, 2018). To investigate what factors drive the strategy used by both species to move across the estuary section, two generalised linear mixed-effects models (GLMM) were run with counts of Engraulis encrasicolus and Pomatoschistus spp. as response variables. The distribution most adequate for these data was the negative binomial, and the model was fitted with the function ‘glmer.nb’ of the package ‘Lme4’ (Bates et al., 2015). Design of categorical factors used was the same as multivariate environmental analysis (fixed factors: depth, tide, zone; random factors: cruise, sample time). Water physiochemical factors (temperature, salinity, turbidity, DO, Chla, Chapter 2 Mechanisms for horizontal movements 68 pH and current velocity) were used as explanatory variables as well, in addition to the filtered volume as an offset variable. The model selection process for determining the best fitting GLMM was to first create a global model with all predictor variables included (Bates et al., 2015). Previously, one of the variables which showed a similar or complementary pattern in PCA were excluded [dissolved oxygen (negatively correlated with temperature) and chlorophyll (positively correlated with turbidity)] from the analysis to avoid collinearity. Multicollinearity of the selected variables was further analysed using variance inflation factors (VIF) with the function ‘vif’ from the package ‘car’ (Fox and Weisberg, 2011); all variables from the global model had a VIF < 3. We performed information theoretic model selection based on Akaike’s information criterion (AIC; Akaike 1974) and Akaike weights (Burnham and Anderson, 2002) using the function ‘dredge’ of the ‘MuMIn’ package (Barton, 2018). The model with the highest adjusted Akaike weight was considered the best-fit model used for the analysis (Burnham and Anderson, 2002). Finally, significant categorical terms in the best-fit model with more than 2 levels, were analysed using the Tukey correction for pairwise comparisons comparison with the package ‘emmeans’ (Lenth, 2018). Total lengths of anchovies were compared to test if individuals with different sizes used distinct strategies. For this analysis, linear mixed-effects models (LMM) were run using the function ‘lmer’ of the package ‘Lme4’ with a Gaussian distribution. In this case, global model had three crossed fixed factors (depth, tide, zone) and one random factor (cruise). The model selection process and post hoc analysis of the best-fit model was similar as explained above. 3. Results 3.1. Environmental analysis PERMANOVA showed different physicochemical conditions of samples in the estuary section between depths and tides as well as zones and tides along cruises (Table 1). Pair-wise analysis of significant interactions showed differences between surface and bottom in both tidal conditions, and also between zones during the flood, being the East and West side distinct to the Channel, although only the West side was significant (Table 2). PCA analysis showed a clear pattern between tide cycles: higher water current velocities and DO concentration during the ebb tides; and higher temperature and pH during the flood tides (Figure 2). Also, high levels of turbidity and chlorophyll were associated to both sides. On the other hand, comparisons between depths showed a slight vertical stratification in some Chapter 2 Mechanisms for horizontal movements 69 environmental variables (Figure S.1) with higher relative values of temperature and velocity current in the surface layers; while the bottom depth showed higher values in turbidity, salinity and chlorophyll. In addition, wind data (Figure S.2) showed a dominant direction from West-Southwest to East-Northeast in most of the flood tides, except for the last sampling day. However, no clear patterns were found during the ebb tides, where some sampling days had a direction from East- Northeast to West-Southwest and other days from South-Southwest to North-Northeast. Table 1. PERMANOVA results of the Euclidian similarity matrix based on environmental variables. Source df SS MS Pseudo-F P(perm) Perms Depth 1 60.041 60.041 21.206 0.0876 192 Tide 1 108.87 108.87 5.4735 0.0189 9952 Zone 2 22.847 11.424 1.2642 0.3214 9962 Cruise 2 209.98 104.99 19.559 0.0001 9930 DepthxTide 1 22.221 22.221 11.275 0.0301 9305 DepthxZone 2 1.8788 0.93939 0.73702 0.5997 9963 DepthxCruise 2 5.6739 2.837 2.5216 0.0208 9927 TidexZone 2 44.411 22.206 4.7071 0.0086 9943 TidexCruise 2 39.877 19.938 3.7144 0.0027 9932 ZonexCruise 4 36.2 9.05 1.686 0.0729 9920 DepthxTidexZone 2 7.7155 3.8578 2.5679 0.1281 9953 DepthxTidexCruise 2 3.9475 1.9738 1.7544 0.1018 9934 DepthxZonexCruise 4 5.1005 1.2751 1.1334 0.3214 9932 TidexZonexCruise 4 18.861 4.7151 0.8784 0.5533 9904 Station(ZonexTidexCruise) 48 257.66 5.3678 4.7711 0.0001 9824 DepthxTidexZonexCruise 4 6.0147 1.5037 1.3365 0.2 9921 Res 48 54.003 1.1251 Total 131 917 Table 2. Pair-wise analysis of significant interactions in PERMANOVA results of environmental variables. * p estimation obtained by Monte Carlo. Term 'TidexDepth' Groups t P(perm) perms t P(perm) perms Surface-Bottom 7.0251 0.0002 9942 3.3084 0.0023 9957 Term 'TidexZone' Groups t P(perm) perms t P(perm) perms East, West side 1.5361 0.1245 9952 1.1316 0.3481 9958 East side, Channel 1.308 0.2555 9957 2.151 0.0533 9961 West side, Channel 0.87768 0.5824 9950 2.182 0.0441* 38 Flood Ebb Ebb Flood Chapter 2 Mechanisms for horizontal movements 70 3.2. Biological analysis A total of 144 tows were conducted, 48 every cruise. Several early life stages of fishes were caught, in addition to Engraulis encrasicolus and Pomatoschistus spp. (P. minutus and P. microps), like Umbrina cirrosa, Argirosomus regius, Dicentrarchus punctatus, Solea solea, Halobatrachus didactylus, Hippocampus hippocampus, Diplodus sp., Stromateus fiatola, Mullus surmuletus and Cyprinus carpio. Anchovy and gobies were the most abundant and consistently present with a total of 11.676 (79%) and 2.695 (18%) individuals sampled respectively. Pomatoschistus spp. Figure 3A shows the densities (ind/1000 m3; mean ± SE) of gobies Pomatoschistus complex by tide, depth and zone averaged along all cruises. The best-fit model (Table S.1) showed significant differences with depth: gobies were ever mainly in the bottom, being very scarce in the surface. In fact, in the surface, due to the low general abundances, there were not any clear pattern and not any significant differences between tides or zones. In the bottom, instead, density differences were found between ebb and flood tide in both sides. Also, a different global pattern was found between flood and ebb: during floods, abundances were Figure 2. Plot of the 2 first principal components of a PCA with environmental variables (DO: dissolved oxygen; Chla: chlorophyll-a; W: west side; C: channel; E: east side). Chapter 2 Mechanisms for horizontal movements 71 significantly higher in both sides compared with the Channel; during ebbs, there was a gradient of densities, increasing from West to East, being the density in the West side significantly lower than the rest of zones. The analysis also showed a slightly positive relationship between temperature and the density of gobies (Table S.1). Engraulis encrasicolus Figure 3B shows the densities (ind/1000 m3; mean ± SE) of anchovy Engraulis encrasicolus by depth, tide and zone averaged along all cruises. The best-fit model (Table S.2) showed significant differences with depth: anchovies were mainly in the surface, being very scarce in the bottom, showing a pattern of use of the space virtually inverse to the gobies. In fact, similar to what we found in the gobies but in the opposite depth (in the bottom), there were not any clear pattern and not significant differences were found between zones, although small but significant differences were found between tides. In the surface, instead, significant Figure 3. Density (mean ± SE) of Pomatoschistus spp. (A) and Engraulis encrasicolus (B) in different stations along all cruises. Different letters indicate significant differences (p < 0.05) among stations from post hoc analysis of GLMM. Asterisks (*) indicate significant differences (p < 0.05) among tide factor in the same zone and depth of Engraulis encrasicolus. 0 500 1000 1500 2000 2500 3000 3500 4000 4500 West side Channel East side West side Channel East side SURFACE BOTTOM Density of Engraulis encrasicolus (nº/103m3) Ebb Flood B a* a* b* c* c* c* 0 200 400 600 800 1000 1200 1400 1600 1800 West side Channel East side West side Channel East side SURFACE BOTTOM Density of Pomatoschistus spp. (nº/103m3) Ebb Flood A bc ef de cd e f aab a a a ab Chapter 2 Mechanisms for horizontal movements 72 differences were found with tides and zones: there were higher abundances during the ebb compared with flood and there were higher densities in the East side than in the rest of the zones. The analysis also showed that salinity was the only environmental variable with significant influence in anchovy distribution along samples (Table S.2). A negative relationship was found, being the low salinity range (19-27 PSU) where higher anchovies were caught, mostly in the surface samples. Best-fit LMM (Table S.3) showed that mean total length of anchovies was different between tides, zones and depths (Figure 4). Flood condition showed bigger sizes compared with ebb tide; during the flood, bigger sizes were found in both sides (East and West) compared with the Channel; during the ebb tide in the surface, East side and Channel mean length were slightly but significantly higher than West side. 4. Discussion Different strategies were found in the anchovy and the gobies to move within the estuary, and the differences found in physicochemical variables across the estuary section and along the tidal cycle could work as cues to lead these strategies. 4.1. Environmental conditions Although, since a hydrological point of view, the Guadalquivir estuary is defined as a well-mixed one (Vanney, 1970), since a biological point of view, the differences found in Figure 4. Total length (mean ± SE) of early life stages of Engraulis encrasicolus in different stations along all cruises. Different letters indicate significant differences (p<0.05) among stations from post hoc analysis of LMM. Chapter 2 Mechanisms for horizontal movements 73 physicochemical variables between surface and bottom or among different zones, could be detected by fish larvae guiding them through different pathways into the estuary. The estuary section sampled was located in the diffusion part of the tide propagation process with a strong tidal dominated condition (Díez-Minguito et al., 2012), which could provoke periodic and slight stratifications (Díez-Minguito et al., 2013). Tidal asymmetry has been previously showed in the middle channel, being a flood dominated estuary (Díez-Minguito et al., 2012). However, in our study, higher maximum current velocities were measured during the ebb tide in the surface than the flood tide samples, mainly in the channel zone, probably for the proximity of the samples section to the estuary inlet. DO and temperature were, as expected, negatively related, and played a major role in the differences found, especially between tides. In addition to the tidal asymmetry, irregularities in the section bathymetry could affect the water circulation (Valle- Levinson and Lwiza, 1995). According to Scully and Friedrichs (2007), the reduced friction in the channel at the end of ebb delays the beginning of the flood tide, increasing the duration of ebb. Conversely, over the shoal zones where stratification is more inhibited by tidal mixing, there is greater friction and the transition from ebb to flood occurs more quickly. This phenomenon generates a residual current seaward over the channel and landward over the shoals (Scully and Friedrichs, 2007). Another effect of the different current velocities was a wider salinity range in the channel than in the sides due to advection of the salinity front that was not driven at the same speed at different lateral locations, creating lateral salinity gradients (Nunes and Simpson, 1985). On the other hand, the greater friction in the shoals would enhance both sediment and microphytobenthos resuspension, in agreement with the higher turbidity and chlorophyll concentration observed in these zones (Díez-Minguito and de Swart, 2020; Miró et al., 2020). 4.2. Pomatoschistus spp. The gobies Pomatoschistus spp. (P. minutus and P. microps) are benthic species which showed a clear bottom behaviour, remaining deep in the water column at all times of the tide cycle as other species described [e.g. Micropogonias undulates by Boehlert and Mundy (1988)]. 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Ichthyol. 24, 60–62. https://doi.org/10.1111/j.1439-0426.2007.00868.x Chapter 2 Mechanisms for horizontal movements 84 Supplementary data Table S.1. GLMM results of Pomatoschistus spp. for comparison between depth, tide and zone along cruises in relation to salinity, turbidity, temperature, pH and current velocity: a) global model; b) best-fit model. a) Global model Pomatoschistus spp. ~ (Depth+Tide+Zone)3 + Salinity + Turbidity + Temperature + pH + Current velocity + (1|Cruises) + (1|Sampling time) + offset(log(filtered volume)) b) Best-fit model Pomatoschistus spp. ~ (Depth+Tide+Zone)3 + Temperature + (1|Cruises) + (1|Sampling time) + offset(log(filtered volume)) Estimate SE z P (Intercept) -1.8114 0.3095 -5.852 >0.0001 Depth (Surface) -3.9076 0.3674 -10.637 >0.0001 Tide (Flood) -0.9544 0.4153 -2.298 0.0215 Zone(East) 0.4588 0.4113 1.115 0.2646 Zone(West) -1.5662 0.4472 -3.503 0.0004 Temperature 0.2476 0.1244 1.991 0.0464 Depth(Surface)*Tide(Flood) 0.8263 0.533 1.55 0.121 Depth(Surface)*Zone(East) -0.154 0.5506 -0.28 0.7796 Depth(Surface)*Zone(West) 1.7743 0.5632 3.15 0.0016 Tide(Flood)*Zone(East) 2.2722 0.5764 3.942 >0.0001 Tide(Flood)*Zone(West) 3.422 0.5972 5.73 >0.0001 Depth(Surface)*Tide(Flood)*Zone(East) -1.3142 0.7288 -1.803 0.0713 Depth(Surface)*Tide(Flood)*Zone(West) -2.2623 0.7198 -3.143 0.0016 Table S.2. GLMM results of Engraulis encrasicolus for comparison between depth, tide and zone along cruises in relation to salinity, turbidity, temperature, pH and current velocity: a) global model; b) best-fit model. a) Global model E. encrasicolus ~ (Depth+Tide+Zone)3 + Salinity + Turbidity + Temperature + pH + Current velocity + (1|Cruises) + (1|Sampling time) + offset(log(filtered volume)) b) Best-fit model E. encrasicolus ~ (Depth+Tide)2 + (Depth+Zone)2 + Salinity + (1|Cruises) + (1|Sampling time) + offset(log(filtered volume)) Estimate SE z P (Intercept) -2.0043 0.3907 -5.13 >0.0001 Depth (Surface) 1.9673 0.5318 3.699 0.0002 Tide (Flood) -1.2792 0.3471 -3.685 0.0002 Zone(East side) -0.6224 0.4297 -1.448 0.1475 Zone(West side) -0.951 0.4418 -2.153 0.0313 Salinity -0.4155 0.1371 -3.031 0.0024 Depth(Surface)*Tide(Flood) -0.955 0.4567 -2.091 0.0365 Depth(Surface)*Zone(East side) 2.0926 0.5876 3.561 0.0003 Depth(Surface)*Zone(West side) 1.3747 0.5821 2.361 0.0182 Chapter 2 Mechanisms for horizontal movements 85 Table S.3. LMM results of total length of Engraulis encrasicolus for comparison between depth, tide and zone along cruises: a) global model; b) best-fit model. a) Global model Total length ~ (Depth+Tide+Zone)3 + (1|Cruises) b) Best-fit model Total length ~ (Depth+Tide+Zone)3 + (1|Cruises) Estimate SE t P (Intercept) 15.628 1.1069 14.119 >0.0001 Depth (Surface) 1.5227 0.9074 1.678 0.0933 Tide (Flood) 1.7112 1.338 1.279 0.2010 Zone (East) -0.4793 1.1308 -0.424 0.6720 Zone (West) 2.4397 1.1524 2.117 0.0342 Depth(Surface)*Tide(Flood) -0.909 1.3972 -0.651 0.5150 Depth(Surface)*Zone(East) 0.5264 1.1376 0.463 0.6440 Depth(Surface)*Zone(West) -3.7096 1.162 -3.192 0.0014 Tide(Flood)*Zone(East) 16.8244 2.3475 7.167 >0.0001 Tide(Flood)*Zone(West) 7.6671 2.4424 3.139 0.0017 Depth(Surface)*Tide(Flood)*Zone(East) -12.8 2.3928 -5.349 >0.0001 Depth(Surface)*Tide(Flood)*Zone(West) -0.5908 2.519 -0.235 0.8150 Chapter 2 Mechanisms for horizontal movements 86 Figure S.1. Boxplots of all water physiochemical variables per zone, depth and tide during the three cruises. Chapter 2 Mechanisms for horizontal movements 87 Figure S.2. Wind rose plots with speed and direction data of Vetalengua Station during every sampling day in each tide condition. 89 3. MAINTENANCE DREDGING EFFECTS ON THE MACROFAUNA OF THE WATER COLUMN IN THE GUADALQUIVIR ESTUARY Abstract Many human activities in or near aquatic habitats generate alterations in their environmental conditions which could affect the organisms that inhabit in them. Maintenance dredging of navigation channels in order to allow large ship access to inland ports is one such source of disturbance. In this study, we analysed the effects of a maintenance dredging operation from multiple approaches (immediate, short and medium term) in the physiochemical variables, the early life stages of fish and other macrofauna groups present in two zones of the Guadalquivir estuary with different salinity ranges (poly- and mesohaline). Most physiochemical variables were homogenized in the water column immediately after the water mass passed by the dredger, including sediment resuspension. However, this process seemed to be temporarily short as no significant increments in the depth-averaged levels of turbidity were observed in short- and medium-term. Instead, metals concentration of Cr, Fe y Zn increased in the polyhaline station. Even so, these perturbations did not appear to be severe enough to influence the macrofauna. Still, organisms can suffer direct mechanical impacts by the trailer suction. Epibenthic species, like Pomatoshcistus spp. or decapods, tended to decrease slightly, while pelagic species as Engraulis encrasicolus or mysids did not, indicating that benthic organisms usually are more prone to a high entrainment. Nonetheless, the possible effects of this disturbance were of the same order or less than natural ones, therefore, macrofauna organisms could be well-adapted to cope with them. Chapter 3 Dredging effects 96 Generalized additive models (GAMs) were fitted for depth profiles of physiochemical variables recorded with the multiprobe. As GLMMs uses a single value of every predictor variable for every value of the response variable, predicted values of GAMs were depth averaged obtaining a single value representative of the complete water column. Results of all variables were plotted by zone using the package ‘ggplot2’. Analysis were performed using the R 3.5.2 software (R Core Team, 2018). Additionally, daily mean discharge from Alacalá del Río Dam during the whole study period was observed to analyse the influence of freshwater input (data provided by Confederación Hidrográfica del Guadalquivir, http://www.chguadalquivir.es/saih/DatosHistoricos.aspx) on the environmental variables measured. 3. Results 3.1. Immediate effects 3.1.1. Environmental analysis Profiles of the different environmental variables recorded with the multiprobe were plotted in the Figure 3. A general pattern was found after dredging for chlorophyll, turbidity and Figure 3. Vertical profiles of the environmental variables (A: chlorophyll; B: turbidity; C: Dissolved oxygen; D: Temperature; E: pH; F: Salinity) before (solid line) and after (dash line) the water mass pass through the dredger while it is working in the three different cruises. Chapter 3 Dredging effects 97 salinity variables, which consisted in a homogenization of the whole water column with similar values in the surface than in the bottom. Only the dissolved oxygen showed the inverse tendency, with higher values in the surface after dredging. The pH maintained homogeneous values in both moments, similar as temperature except for the cruise 1. 3.1.1. Biological analysis The fish species found were Engraulis encrasicouls (45.6%), Pomatoschistus spp. (44.9%), Aphia minuta (2.9%), Pomadasys incisus (2.3%), Solea senegalensis (2.2%), Sardina pilchardus (1.1%), Argyrosmus regius (0.5%), Anguilla anguilla (0.3%) and Gobius paganellus (0.2%). Among the rest of macrofauna groups, mysids were the most abundant (77.9%; e.g. Rhopalophthalmus tartessicus, Mesopopdosis slabberi and Neomysis integer), followed by decapods (17.4%; e.g. Palaemon spp. and Crangon crangon) and isopods (4.6%; e.g. Synidotea laticauda and Lekanesphaera rugicauda). Species showed different responses after water mass passed by the dredger, although the variations between moments hindered to find clear patterns (Figure S.1). Only the mysids and Solea senegalensis showed significant differences, increasing in all cruises (Table 1). Also, the anchovy Engraulis encrasicolus tended to increase. Contrary, decapods, Pomatoschistus spp. Aphia minuta and Pomadasys incisus tended to decrease. Isopods maintained stable densities in front and behind the dredge. Table 1. Results of the fixed effect “Moment” for GLMM on main early fish species (count data) and macrofauna groups (biomass data) of the immediate approach. Level “Before” was used as intercept to calculate estimates. Estimate SE z value p value Engraulis encrasicolus 0.328 0.213 1.537 0.124 Pomatoschistus spp. -0.426 0.411 -1.034 0.301 Aphia minuta -0.369 0.492 -0.75 0.453 Pomadasys incisus -0.36 1.195 -0.302 0.763 Solea senegalensis 1.778 0.763 2.329 0.019 Estimate SE t value p value Mysids 41.67 10.14 4.111 >0.001 Decapods -10.01 27.6 -0.362 0.717 Isopodos 0.333 0.981 0.34 0.734 Chapter 3 Dredging effects 98 3.2. Short- and medium-term effects 3.2.1. Environmental analysis The duration of the study was 81 days between the first and the last cruise, showing different temporal patterns between the different physiochemical variables. Statistical differences of the fixed effect “Period” from GLMM on all variables were summarized in the plots by letter codes and extended in Table S.1. Daily mean freshwater input into the estuary (Figure 4A) increased (discharges higher than 50 m3/s) at the end of the dredging period and thereafter. Turbidity did not show any change during dredging, while their values increased during the post-dredging period, being significant in polyhaline zone (Figure 4B). Chlorophyll Figure 4. Daily mean of freshwater inputs in the Guadalquivir estuary (A) and temporal values of physiochemical variables measured in the water column (turbidity (B), chlorophyll (C), temperature (D), dissolved oxygen (E), pH (F), salinity (G)) and biological (Engraulis encrasicolus (H), Pomatoschistus spp. (I), mysids (J), decapods (K), isopods (L)). Dush lines point out the dredging period. Solid lines are smoother models with loess method for polyhaline (Red) and mesohaline (Blue) zones. Grey shades mean standard errors. Different letters indicate significant differences (p<0.05) between levels of Period factor (before, during and after) from GLMM in every zone (Red letters: polyhaline; Blue letters: mesohaline). a b b a a a ab a b a a a a a a a ab b a a a a ab b a a a a a a a a ba a a a b aba b ab a b c a b c a b c a b c a b aba b a a a aa a a AG BH CI J EK FL D Chapter 3 Dredging effects 99 concentration showed a decrease during the dredging period, and thereafter a soft recovery (Figure 4C). Water temperature decreased gradually from 22.5°C to 12.5°C, typical in autumnwinter transition of temperate regions in the north hemisphere, although this decline ceased during the dredging (Figure 4D). Dissolved oxygen showed the inverse trend during the study (Figure 4E), although their values increased more during dredging period despite the fact that temperature was stable during these dates. The pH increased in both zones during dredging, decreasing to pre-dredging values afterwards. Salinity was stable in both zones during the whole study (Figure 4F), although it tended to decrease after dredging associated to the increment of freshwater input in this period. TSS, directly correlated with SIM and SOM (Figures 5A-C), showed the same pattern as turbidity, being the post-dredging period when higher concentrations were found in every zone, although the wide range found in the mesohaline zone did not make this zone significantly different. Silicate and nitrite concentrations did not show differences (Figures 5D-E). Nitrates showed a gradual increment in both zones, with significant differences in the polyhaline zone between all periods (Figure 5F). Similar trend showed the ammonium, but without significant differences (Figure 5G). Phosphates did not show any difference in the mesohaline zone, while values measured in polyhaline zone were higher during dredging, with a partial recovery thereafter (Figure 5H). Figure 5. Boxplot of total suspended solids (A), suspended inorganic matter (B), suspended organic matter (C), SiO4 (D), NO2 (E), NO3 (F), NH4 (G) and PO4 (H) in every zone. Blue: before dredging; red: during dredging; green: after dredging. Different letters indicate significant differences (p<0.05) between levels of Period factor from GLMM in every zone. Chapter 3 Dredging effects 100 Similar trends between zones were found in the concentration of most metals analyzed, although the mesohaline zone did not show significant differences between periods for any of them (Figure 6 and Table S.2). As, Cd, Co, Cu and Pb did not show any clear patterns due to variations between replicates (Figure 6A-D, H). Ni, despite not being significantly different between periods, showed a cumulative trend during the dredging period (Figure 6G). Cr and Fe started to increment gradually during the dredging and continued in post-dredging period (Figure 6D, F). Zn showed the highest relative increment during the dredging, with different trends after dredging for the polyhaline zone, in which it decreased slightly, and the mesohaline zone, in which it was maintained high but with oscillations (Figure 6I). 3.2.2. Biological analysis A total of 16 fish species in early life stages were found with two dominant species that compounded more than 90% of the total abundance of the fish assemblage, the anchovy Engraulis encrasicolus (58.3%) and the goby Pomatoschistus spp. (32.8%). In relation with the rest of macrozooplankton and hyperbenthos groups, similar species as described in the immediate approach were found, with mysids showing the highest biomass (76.6%), followed of decapods (17.6%) and isopods (5.3%). Figure 6. Temporal series of metal concentrations (As, Cd, Co, Cr, Cu, Fe, Ni, Pb, Zn; A-I respectively) in the water column. Dush lines point out the dredging period. Solid lines are smoother models with loess method for polyhaline (Red) and mesohaline (Blue) zones. Different letters indicate significant differences (p<0.05) between levels of Period factor from GLMM in every zone (Red letters: polyhaline; Blue letters: mesohaline). Chapter 3 Dredging effects 101 Temporal series of the densities of most abundant fish species and the rest of macrofauna were plotted by zones in the figure 4. A general pattern was observed for most taxa, which showed a wider density variation before and during dredging cruises, as well as a temporal decreasing along the whole study. Notwithstanding, distinct responses and significant differences were found between periods for every species (Table S.3). Anchovy and mysids showed similar patterns in both zones, with a marked decrease from the beginning of dredging, especially in polyhaline waters, that continued until the last cruise (Figures 4H, J). Isopods, goby and decapods did not show differences between periods due to high cruise variability intraperiods, although different tendencies were observed (Figures 4 I, K, L). Isopod densities were too low in the polyhaline zone to detect any change along periods, while in the mesohaline zone, its biomass showed a notably descend during the dredging in comparison with the last cruise of the period before; also, it showed a partially recovery in the second cruise after dredging, although it did not continue in the next one. Goby and decapods showed a similar trend, but in opposite zones, with a decrease at the end of the dredging which continued also in the period after dredging. Figure 7. Density of Engraulis encrasicolus (A) and Pomatoschistus spp. (B), and biomass of the rest of macrofauna (C) during the dredging study (2017) and on similar dates in previous years (2015 and 2016) in every zone. Dush lines point out the dredging periods: colour green for 2016 and blue for 2017. Solid lines are smoother models with loess method for every year. Polyhaline Mesohaline 17/09 02/10 17/10 01/11 16/11 01/12 16/12 31/12 15/01 17/09 02/10 17/10 01/11 16/11 01/12 16/12 31/12 15/01 0 400 800 1200 Engraulis encrasicolus (n/1000m3) Polyhaline Mesohaline 17/09 02/10 17/10 01/11 16/11 01/12 16/12 31/12 15/01 17/09 02/10 17/10 01/11 16/11 01/12 16/12 31/12 15/01 0 200 400 600 Pomatoschistus spp. (n/1000m3) Polyhaline Mesohaline 17/09 02/10 17/10 01/11 16/11 01/12 16/12 31/12 15/01 17/09 02/10 17/10 01/11 16/11 01/12 16/12 31/12 15/01 0 250 500 750 Macrofauna (g.f.w/1000m3) A B C Chapter 3 Dredging effects 102 Interannual comparison (2015, 2016 and 2017) of E. encrasicolus, Pomatoschistus spp. and the rest of macrofauna groups together (the main component was mysids) in every zone were plotted in Figure 7. Anchovy (Figure 7A) showed stable densities in the polyhaline zone during the whole period in 2015 and 2016, despite the dredging operation carried out in the latter year. Instead, 2017 presented higher anchovy abundances before dredging, but it decreased during dredging until similar levels as previous years in the same dates. The densities of anchovies in the mesohaline zone showed a different trend, with a gradual decrease but with oscillations depending on the year. In fact, the natural inter-month variations found in 2015 where higher than those observed in years with dredging. The trend of the rest of macrofauna (Figure 7C) was similar than anchovy in the polyhaline zone, and a gradual decrease was repeated for all years in the mesohaline zone. The goby (Figure 7B) showed a distinct pattern in both zones all years, except for the mesohaline zone in 2016, with a progressive increment at the beginning of studied period that varied between dates, to finally decrease with different slopes. 4. Discussion Estuaries are ecosystem with wide environmental variations that make difficult to detect anthropic stress from natural changes, unless the human impact is severe, leading to the ‘Estuarine Quality Paradox’ (Elliott and Quintino, 2007). In addition, the impossibility to establish controls replicates per zone, due to the absent of polyhaline or mesohaline waters without dredging in the same estuary, makes it necessary to interpret these results with caution. Notwithstanding, the immediate-, short- and medium-term design applied in this study, in addition with interannual comparisons, helped to discriminate different effects of a dredging operation in biological and physiochemical variables of a high fluctuating estuary as Guadalquivir. Among the physiochemical variables, only DO and pH showed a clear influence by the dredging, increasing their levels. These observations contrast with the general assumption that sediment resuspension releases chemical substances which react with DO, reducing temporally its concentration and acidifying the water (Jones-Lee and Lee, 2005). In this case, observing the stratification of DO in the immediate approach, it is possible that mechanical perturbation as ship-propeller and cavitation, in addition to the action of trailer arm, could mix the water column with atmospheric air (Bowie et al., 1985), balancing the chemical demanding of DO, and even increasing its values. Nonetheless, DO concentration never reached levels lower than 6 mg/L during the whole study at any depth in both zones and the pH increased only 0.1, which did not Chapter 3 Dredging effects 103 seem to have a relevant negative effect in well oxygenated waters with low temperatures as reported by Jabusch et al. (2008). On the other hand, DO depletion is also associated with persistent high turbidity levels which reduce light penetration in the water column and limit photosynthesis activity (Desmit et al., 2005). Still, Guadalquivir estuary is considered a turbid system where the primary production in the water column is scarce and constrained to the surface layer (Ruiz et al., 2015). Hence, oxygen production by phytoplankton would be little influenced in a temporal increment of turbidity. Turbidity increase, directly correlated with TSS, has been widely studied as common effect of dredging operations in coastal areas which may affect to marine biodiversity (Magris and Ban, 2019; Wenger et al., 2017), being able to cause lethal and sublethal impacts in 10–20% of fish species respectively (Wenger et al., 2018). An analysis of surface satellite images showed increments of total suspended solids (1000 mg/L approx.) in plumes during dredging operation in upper zones of the same estuary (Caballero et al., 2018). These observations coincided with the immediate profiles recorded after the water mass passed by the dredger working, when the homogenization of the water column incremented the turbidity levels on the surface. But surprisingly, we did not detect significant changes in the depth-averaged values of turbidity. Dredging operation must have necessarily increased the suspended sediment and, consequently, turbidity; but the effect seems to be spatially very local and its persistence temporally short, and we could not detect significant changes either in the short- and in the medium-term approaches. Nonetheless, turbidity, TSS, SIM and SOM concentration increased after dredging, which seems to be rather associated to higher freshwater inputs in this period. (González-Ortegón et al., 2010) reported similar observations during other freshets in the same estuary (up to 700 NTU approx.), describing adverse effects on the estuarine food web at different levels. Increasing exposure to suspended sediment may causes damage to gill tissue and structure, being more easily to clog the gills and reduce their efficiency in smaller fish and larvae (Au et al., 2004). The Guadalquivir estuary has been considered the most productive and important nursery areas of the region in spite of being the most turbid (Miró et al., 2020). The high flows originated by tides and the high chronic turbidity in the Guadalquivir estuary (Losada et al., 2017) could have overshadow the sediment resuspension effect caused by dredging in our sampling zones, and consequently, we could not observe a clear increase, nor any direct effect on species found. The dynamics of chlorophyll concentration appear to follow a seasonal pattern related with temperature reduction, provided that dredging did not significantly modify turbidity, and consequently light penetration. However, higher values were observed in the latter cruises while Chapter 3 Dredging effects 104 temperature continued decreasing and turbidity increased. These observations could be explained by imports from upstream waters with higher primary production caused by rising freshwater inputs (González-Ortegón and Drake, 2012) and/or a higher resuspension of microphytobenthos from riversides (Díez-Minguito and de Swart, 2020; Miró et al., 2020). Also, nutrients as nitrate and ammonium, which presented similar tendencies as chlorophyll, could be imported due to sewage effluents and nitrification processes from upstream waters close to urban and agriculture areas (Mendiguchía et al., 2007). Different stages of ammonium could be found depending on pH levels, with higher un-ionized [ammonia (NH3)] proportion associated to high pH, which it has been considered toxic for fishes (Brinkman et al., 2009). In our case, the changes of pH observed during the dredging could increase the NH3 proportion around 0.1-0.2% (poly- and mesohaline zones respectively), which means a total concentration found of 0.1 µM NH3 during that period. Therefore, un-ionized ammonia showed levels far from toxicity references [1.16 µM NH3 (Eddy, 2005)]. The concentration of phosphate, whose increment is usually attributed to fertilizers via river flow (Mainstone and Parr, 2002), showed changes during the dredging in polyhaline waters, although concentrations reached were lower than levels found in mesohaline zone. Globally, we could not clearly assign an increase in inorganic nutrients due to dredging operations. In contrast, dredging has been primarily related to remobilize metals associated with sediment particles into the water column, which change its environmental conditions and promotes the shift of metals from the particulate into the dissolved state (Van Den Berg et al., 2001). This phenomena could be even more noticeable in the Guadalquivir estuary given that it received a toxic spill from Aznalcóllar mine in 1998 (Riba et al., 2002) [although ten years afterwards, studies showed that the decline in metal contamination in the area was evident (Tornero et al., 2014, 2011)]. It is known that oxidation of sulfides liberates different heavy metals because the precipitates are degraded (Caille et al., 2003). This phenomenon was observed in our case for Cr, Fe, Ni and Zn, with a cumulative trend during dredging. However, the oxidation of Fe also causes precipitation of iron-(oxo)hydroxides which could form a very strong adsorptive layer in the surface of the new dredged bottom and decrease the release of metals (Goossens and Zwolsman, 1996). On the other hand, a previous study in the Guadalquivir estuary of heavy metals concentration in the sediment of the same zones observed an increment of As, Co and Ni after dredging operations, especially in the polyhaline site (Donázar-Aramendía et al., 2018). In our water samples, higher effects were found in the same zone, where slight differences could be due to the salinity of water, the oxidation-reduction potential of the sediment and the pH of the sediment pore water and overlying water on site (Eggleton and Thomas, 2004). Chapter 3 Dredging effects 105 Maximum values recorded in the field were lower than minimal concentration used in controlled experiments in the laboratory that test lethal effects of trace metals in early life stages of fishes (Jezierska et al., 2009). Experiments in crustacea also show that ranges measured usually do not cause significant effects on individuals (Lavolpe et al., 2004; Martin and Holdich, 1986). Thus, the metal uptake for fish and the rest macrofauna present in both zones is expected to be low in this study. Other than the effect of dredging, also the daily tidal currents, wind energies or storms in estuarine systems can cause periodical remobilization of surface sediments, releasing metals naturally (Eggleton and Thomas, 2004). The higher freshwater inputs observed after dredging, and the associated increment in TSS, could also contribute to maintain the increased values of some metals. On the other hand, some metals can be released and/or re-absorbed more readily than others (Maddock et al., 2007). Faster release and reabsorption could be happening for Ni and Cr, which increased quickly only during the dredging, and slower release and re-absorption for Zn and Fe, which reached higher levels after dredging. Also, fine sediments could remain longer in suspension and consequently liberate more metals after dredging (Maddock et al., 2007). The Guadalquivir estuary have showed high persistent turbidity events in wet years (González-Ortegón et al., 2010), and also is considered one of the estuaries in the region with higher metal fluxes (González-Ortegón et al., 2019) due to urban and agriculture supports (Mendiguchía et al., 2007). As organisms take up and accumulate trace metals during their whole life cycle, which have the potential to cause toxic effects over time (Rainbow, 2007), especial attention should be taken in metal release after higher bottom disturbance situations such as longer dredging periods or torrential freshets. Still, this is more probably a concern with longer living estuarine organisms, such as adult resident fishes, than short living ones, as most species included in this study. Physiochemical alterations of dredging operation appear to be minor in comparison with the natural changes observed, however, other possible effects have been observed in planktonic organisms. The limited swimming capacity of small individuals could make it impossible for them to avoid the water mass affected by dredging. Therefore, the main and direct cause that could decrease densities after water mass passed through the dredger working is the hydraulic entrainment, leading to their death by the mechanical action of the suction arm (Reine and Clarke, 1998). Different tendencies were found for epibenthic and pelagic species in the immediate approach. Epibenthic species, like Pomatoshcistus spp. or decapods, tended to decrease, probably due to the direct impact of physical removal of bottom sediments where epibenthic organisms inhabit (Hoffmann and Dolmer, 2000). In fact, a previous study showed that Chapter 3 Dredging effects 112 Ponti, M., Pasteris, A., Guerra, R., Abbiati, M., 2009. Impacts of maintenance channel dredging in a northern Adriatic coastal lagoon. II: Effects on macrobenthic assemblages in channels and ponds. Estuar. Coast. Shelf Sci. 85, 143–150. https://doi.org/10.1016/j.ecss.2009.06.027 R Core Team, 2018. A language and environment for statistical computing. 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Center, Vicksburg, MS, Tech. Note DOER-E1 1–14. Riba, I., DelValls, T.A., Forja, J.M., Gómez-Parra, A., 2002. Influence of the Aznalcóllar mining spill on the vertical distribution of heavy metals in sediments from the Guadalquivir estuary (SW Spain). Mar. Pollut. Bull. 44, 39–47. https://doi.org/10.1016/S0025-326X(01)00171-0 Ruiz, J., Polo, M.J., Díez-Minguito, M., Navarro, G., Morris, E.P., Huertas, E., Caballero, I., Contreras, E., Losada, M.A., 2015. The Guadalquivir Estuary: A Hot Spot for Environmental and Human Conflicts, in: Environmental Management and Governance. Coastal Research Library. pp. 199–232. https://doi.org/10.1007/978-3-319-06305-8 Simonini, R., Ansaloni, I., Cavallini, F., Graziosi, F., Iotti, M., Massamba N’Siala, G., Mauri, M., Montanari, G., Preti, M., Prevedelli, D., 2005. Effects of long-term dumping of harbor-dredged material on macrozoobenthos at four disposal sites along the Emilia-Romagna coast (Northern Adriatic Sea, Italy). Mar. Pollut. Bull. 50, 1595–1605. https://doi.org/10.1016/j.marpolbul.2005.06.031 Tornero, V., Arias, A.M., Blasco, J., 2014. Trace element contamination in the Guadalquivir River Estuary ten years after the Aznalcóllar mine spill. Mar. Pollut. Bull. 86, 349–360. https://doi.org/10.1016/j.marpolbul.2014.06.044 Tornero, V., Arias, A.M., Blasco, J., 2011. Following the Aznalcóllar toxic spill. Environ. Res. 111, 1033–1036. https://doi.org/10.1016/j.envres.2011.07.011 Torres, R.J., Abessa, D.M.S., Santos, F.C., Maranho, L.A., Davanso, M.B., do Nascimento, M.R.L., Mozeto, A.A., 2009. Effects of dredging operations on sediment quality: Contaminant mobilization in dredged sediments from the Port of Santos, SP, Brazil. J. Soils Sediments 9, 420– 432. https://doi.org/10.1007/s11368-009-0121-x Tsolaki, E., Diamadopoulos, E., 2010. Technologies for ballast water treatment: A review. J. Chem. Technol. Biotechnol. 85, 19–32. https://doi.org/10.1002/jctb.2276 Chapter 3 Dredging effects 113 Van Den Berg, G.A., Meijers, G.G.A., Van Der Heijdt, L.M., Zwolsman, J.J.G., 2001. Dredgingrelated mobilisation of trace metals: A case study in The Netherlands. Water Res. 35, 1979– 1986. https://doi.org/10.1016/S0043-1354(00)00452-8 Wenger, A.S., Harvey, E., Wilson, S., Rawson, C., Newman, S.J., Clarke, D., Saunders, B.J., Browne, N., Travers, M.J., Mcilwain, J.L., Erftemeijer, P.L.A., Hobbs, J.P.A., Mclean, D., Depczynski, M., Evans, R.D., 2017. A critical analysis of the direct effects of dredging on fish. Fish Fish. 1–19. https://doi.org/10.1111/faf.12218 Wenger, A.S., Rawson, C.A., Wilson, S., Newman, S.J., Travers, M.J., Atkinson, S., Browne, N., Clarke, D., Depczynski, M., Erftemeijer, P.L.A., Evans, R.D., Hobbs, J.P.A., McIlwain, J.L., McLean, D.L., Saunders, B.J., Harvey, E., 2018. Management strategies to minimize the dredging impacts of coastal development on fish and fisheries. Conserv. Lett. 11, 1–10. https://doi.org/10.1111/conl.12572 Wilber, D.H., Clarke, D.G., 2001. Biological Effects of Suspended Sediments: A Review of Suspended Sediment Impacts on Fish and Shellfish with Relation to Dredging Activities in Estuaries. North Am. J. Fish. Manag. 21, 855–875. https://doi.org/10.1577/1548- 8675(2001)021<0855:beossa>2.0.co;2 Winterwerp, J.C., Wang, Z.B., 2013. Man-induced regime shifts in small estuaries - I: Theory. Ocean Dyn. 63, 1279–1292. https://doi.org/10.1007/s10236-013-0662-9 Yap, W.Y., Lam, J.S.L., 2013. 80 million-twenty-foot-equivalent-unit container port? Sustainability issues in port and coastal development. Ocean Coast. Manag. 71, 13–25. https://doi.org/10.1016/j.ocecoaman.2012.10.011 Chapter 3 Dredging effects 114 Supplementary Data Figure S.1. Abundance of main early fish stages and the rest of macrofauna groups captured before and after the water mass passed by the dredger working in every cruise. Chapter 3 Dredging effects 115 Table S.1.1. Pairwise comparisons to evaluate the water physiochemical variables among the different periods of the dredging (Before, During and After) in every zone (polyhaline and mesohaline). Significant terms p ≤ 0.05 are highlighted in bold. Turbity estimate SE df t.ratio p.value Turbity estimate SE df t.ratio p.value Before-During 23 21.4 6.31 1.078 0.5591 Before-During 97.2 59.9 6.66 1.623 0.301 Before-After -124 32.9 8.37 -3.777 0.0124 Before-After -439 265.1 4.93 -1.656 0.3088 During-After -147 27.5 5.51 -5.356 0.0053 During-After -536.2 260.2 4.62 -2.061 0.1999 pH estimate SE df t.ratio p.value pH estimate SE df t.ratio p.value Before-During -0.0869 0.0217 10.75 -4.013 0.0055 Before-During -0.0783 0.0192 9.22 -4.085 0.0066 Before-After -0.0221 0.0249 8.09 -0.886 0.6636 Before-After 0.0303 0.0281 5.66 1.079 0.5617 During-After 0.0649 0.0261 9.9 2.482 0.0766 During-After 0.1086 0.0312 8.43 3.483 0.0188 Temperature estimate SE df t.ratio p.value Temperature estimate SE df t.ratio p.value Before-During 5.28 1.147 1.42E+05 4.604 <.0001 Before-During 5.68 1.18 4.52 4.801 0.0142 Before-After 8.56 1.166 2.90E+03 7.344 <.0001 Before-After 8.96 1.21 4.95 7.393 0.0017 During-After 3.28 0.222 5.12E+00 14.753 0.0001 During-After 3.28 0.27 4.89 12.129 0.0002 Chla (Multi) estimate SE df t.ratio p.value Chla (Multi) estimate SE df t.ratio p.value Before-During 1.192 0.386 6.64 3.084 0.0439 Before-During 1.759 0.247 5.41 7.11 0.0015 Before-After 1.045 0.405 7.11 2.579 0.0817 Before-After 1.446 0.628 6 2.303 0.1314 During-After -0.147 0.253 9.73 -0.58 0.8339 During-After -0.313 0.585 4.68 -0.535 0.8583 DO estimate SE df t.ratio p.value DO estimate SE df t.ratio p.value Before-During -1.052 0.1889 6.04 -5.569 0.0034 Before-During -1.203 0.213 6.28 -5.633 0.0028 Before-After -1.886 0.1859 5.45 -10.144 0.0002 Before-After -2.076 0.21 5.62 -9.902 0.0002 During-After -0.833 0.0894 10.63 -9.321 <.0001 During-After -0.874 0.106 10.62 -8.217 <.0001 Salinity estimate SE df t.ratio p.value Salinity estimate SE df t.ratio p.value Before-During -0.544 0.599 8.47 -0.908 0.6499 Before-During 0.731 0.679 5.48 1.077 0.5636 Before-After 3.089 1.297 6.03 2.381 0.1184 Before-After 1.379 1.848 5.74 0.746 0.7472 During-After 3.632 1.24 5.29 2.928 0.0674 During-After 0.648 1.742 4.64 0.372 0.9276 POLYHALINE ZONE MESOHALINE ZONE Chapter 3 Dredging effects 116 Table S.1.2. Pairwise comparisons to evaluate the water physiochemical variables among the different periods of the dredging (Before, During and After) in every zone (polyhaline and mesohaline). Significant terms p ≤ 0.05 are highlighted in bold. TSS estimate SE df t.ratio p.value TSS estimate SE df t.ratio p.value Before-During 4.39 20.7 9.43 0.212 0.9757 Before-During 100 47.4 6.11 2.12 0.1644 Before-After -114.54 26 8.41 -4.398 0.0051 Before-After -401 218 4.89 -1.839 0.2516 During-After -118.93 23.9 8.19 -4.979 0.0026 During-After -501 214.2 4.57 -2.34 0.1472 SIM estimate SE df t.ratio p.value SIM estimate SE df t.ratio p.value Before-During 0.01752 0.01044 9.45 1.678 0.263 Before-During 0.01463 0.00969 8.48 1.51 0.3341 Before-After 0.00101 0.00987 7.98 0.102 0.9943 Before-After -0.00965 0.01838 5.01 -0.525 0.8629 During-After -0.01651 0.01225 11.14 -1.348 0.3994 During-After -0.02428 0.01995 7.08 -1.217 0.4805 SOM estimate SE df t.ratio p.value SOM estimate SE df t.ratio p.value Before-During -0.01752 0.01044 9.45 -1.678 0.263 Before-During -0.01463 0.00969 8.48 -1.51 0.3341 Before-After -0.00101 0.00987 7.98 -0.102 0.9943 Before-After 0.00965 0.01838 5 0.525 0.8629 During-After 0.01651 0.01225 11.14 1.348 0.3994 During-After 0.02428 0.01994 7.07 1.217 0.4805 NO2 estimate SE df t.ratio p.value NO2 estimate SE df t.ratio p.value Before-During -0.0565 0.158 9.07 -0.357 0.9328 Before-During 0.2068 0.1496 5.74 1.383 0.4088 Before-After 0.1903 0.163 7.84 1.165 0.505 Before-After 0.2193 0.1461 5.01 1.501 0.366 During-After 0.2468 0.127 8.99 1.938 0.1839 During-After 0.0124 0.0607 9.99 0.205 0.9772 NO3 estimate SE df t.ratio p.value NO3 estimate SE df t.ratio p.value Before-During -17.5 4.44 4.69 -3.942 0.0276 Before-During -4.68 9.95 5.37 -0.47 0.8876 Before-After -53.6 9.92 6.19 -5.405 0.0036 Before-After -118.04 43.25 4.88 -2.729 0.091 During-After -36.1 9.59 5.7 -3.767 0.0237 During-After -113.36 42.83 4.73 -2.646 0.1025 NH4 estimate SE df t.ratio p.value NH4 estimate SE df t.ratio p.value Before-During -0.339 1.29 5.35 -0.262 0.9631 Before-During -0.781 0.657 12.69 -1.189 0.4805 Before-After -1.44 2.33 7.65 -0.617 0.8154 Before-After -2.484 0.936 7.82 -2.654 0.0686 During-After -1.1 2 4.83 -0.55 0.8513 During-After -1.703 0.818 6.26 -2.082 0.1708 PO4 estimate SE df t.ratio p.value PO4 estimate SE df t.ratio p.value Before-During -0.347 0.147 7.85 -2.359 0.105 Before-During -0.185 0.381 7.11 -0.486 0.8802 Before-After -0.234 0.151 4.18 -1.547 0.361 Before-After -0.503 0.427 6.9 -1.176 0.5029 During-After 0.113 0.162 6.55 0.699 0.7723 During-After -0.317 0.273 3.62 -1.163 0.5366 SiO4 estimate SE df t.ratio p.value SiO4 estimate SE df t.ratio p.value Before-During -0.968 2.46 6.99 -0.393 0.9192 Before-During -3.569 9.33 10.32 -0.382 0.9231 Before-After -2.392 7.29 5.04 -0.328 0.9431 Before-After -3.316 10.12 4.57 -0.328 0.9433 During-After -1.424 7.34 5.24 -0.194 0.9796 During-After 0.252 9.62 5.07 0.026 0.9996 POLYHALINE ZONE MESOHALINE ZONE Chapter 3 Dredging effects 117 Table S.2.1. Pairwise comparisons to evaluate the trace metal concentration among the different periods of the dredging (Before, During and After) in the polyhaline zone. Significant terms p ≤ 0.05 are highlighted in bold. As estimate SE df t.ratio p.value Before-During 0.00368 0.0157 8.05 0.234 0.9704 Before-After -0.00262 0.0157 4.19 -0.167 0.9849 During-After -0.0063 0.0173 6.83 -0.365 0.9299 Cd estimate SE df t.ratio p.value Before-During 2.23E-04 0.000423 8.69 0.529 0.8596 Before-After 5.25E-05 0.000473 4.88 0.111 0.9932 During-After -1.71E-04 0.000425 4.7 -0.402 0.9163 Cr estimate SE df t.ratio p.value Before-During -0.00231 0.00104 8.12 -2.221 0.1261 Before-After -0.00829 0.00159 5.39 -5.228 0.0064 During-After -0.00598 0.0018 8.58 -3.318 0.0234 Co estimate SE df t.ratio p.value Before-During -0.00133 0.00103 5.01 -1.287 0.4602 Before-After -0.000817 0.0014 6.25 -0.582 0.8344 During-After 0.000513 0.00127 6.99 0.405 0.9147 Cu estimate SE df t.ratio p.value Before-During -3.25E-03 0.00163 5.13 -1.995 0.2064 Before-After -3.18E-03 0.0021 4.32 -1.511 0.3721 During-After 7.03E-05 0.00188 4.01 0.037 0.9992 Fe estimate SE df t.ratio p.value Before-During -0.0154 0.00565 4.75 -2.729 0.0932 Before-After -0.0459 0.01156 5.96 -3.971 0.0175 During-After -0.0305 0.01109 5.45 -2.748 0.081 Ni estimate SE df t.ratio p.value Before-During 0.000288 0.00201 8.13 0.143 0.9888 Before-After -0.005139 0.00276 8.06 -1.862 0.2109 During-After -0.005427 0.00251 7.54 -2.159 0.1425 Pb estimate SE df t.ratio p.value Before-During 0.0059 0.00861 7.68 0.686 0.7785 Before-After 0.00475 0.01002 6.28 0.474 0.8857 During-After -0.00115 0.00725 3.63 -0.159 0.9862 Zn estimate SE df t.ratio p.value Before-During -0.01465 0.00507 7.06 -2.889 0.0535 Before-After -0.01689 0.00288 6.01 -5.861 0.0026 During-After -0.00223 0.00554 8.79 -0.403 0.9152 POLYHALINE ZONE Chapter 3 Dredging effects 118 Table S.2.2. Pairwise comparisons to evaluate the trace metal concentration among the different periods of the dredging (Before, During and After) in the mesohaline zone. Significant terms p ≤ 0.05 are highlighted in bold. As estimate SE df t.ratio p.value Before-During 0.0102 0.0105 5.42 0.972 0.6218 Before-After 0.0115 0.0135 4.4 0.851 0.6932 During-After 0.0013 0.0121 3.98 0.108 0.9936 Cd estimate SE df t.ratio p.value Before-During 4.67E-04 0.000423 7.06 1.103 0.5419 Before-After 5.36E-04 0.000519 4.36 1.033 0.5948 During-After 6.91E-05 0.000459 3.67 0.151 0.9876 Cr estimate SE df t.ratio p.value Before-During -0.00492 0.00345 8.02 -1.428 0.3724 Before-After -0.00811 0.00346 4.2 -2.344 0.1545 During-After -0.00318 0.00378 6.81 -0.842 0.6914 Co estimate SE df t.ratio p.value Before-During -0.000193 0.000868 5.13 -0.223 0.9732 Before-After -0.000797 0.001121 4.32 -0.711 0.7697 During-After -0.000604 0.001005 4.01 -0.601 0.8273 Cu estimate SE df t.ratio p.value Before-During -0.00087 0.00158 4.67 -0.55 0.8513 Before-After -0.00199 0.00281 6.91 -0.708 0.7666 During-After -0.00112 0.00266 6.56 -0.422 0.9079 Fe estimate SE df t.ratio p.value Before-During -0.0139 0.0191 5.6 -0.727 0.7581 Before-After -0.0552 0.0272 6.18 -2.026 0.1846 During-After -0.0412 0.0265 7 -1.558 0.3234 Ni estimate SE df t.ratio p.value Before-During -0.00312 0.00375 5.78 -0.833 0.6987 Before-After -0.00446 0.00457 4.19 -0.977 0.6261 During-After -0.00134 0.00428 4.5 -0.312 0.9483 Pb estimate SE df t.ratio p.value Before-During -0.000326 0.00662 7.46 -0.049 0.9987 Before-After 0.005565 0.00827 4.83 0.673 0.7887 During-After 0.005891 0.00703 3.75 0.838 0.7036 Zn estimate SE df t.ratio p.value Before-During -0.00812 0.0065 8.41 -1.249 0.4582 Before-After -0.03022 0.0103 5.46 -2.941 0.0643 During-After -0.02211 0.0111 7.48 -1.986 0.1818 MESOHALINE ZONE Chapter 3 Dredging effects 119 Table S.3. Pairwise comparisons to evaluate the most abundant early fish stages and macrofauna groups among the different periods of the dredging (Before, During and After) in every zone (polyhaline and mesohaline). Significant terms p ≤ 0.05 are highlighted in bold. Engraulis encrasicolus estimate SE df z.ratio p.value Engraulis encrasicolus estimate SE df z.ratio p.value Before-During 2.53 0.588 Inf 4.301 0.0001 Before-During 0.788 0.348 Inf 2.265 0.0608 Before-After 5.39 1.337 Inf 4.032 0.0002 Before-After 4.66 1.631 Inf 2.857 0.0119 During-After 2.86 1.431 Inf 1.999 0.1124 During-After 3.872 1.653 Inf 2.342 0.0502 Pomatoschistus spp. estimate SE df z.ratio p.value Pomatoschistus spp. estimate SE df z.ratio p.value Before-During 0.7359 0.534 Inf 1.377 0.353 Before-During 0.138 0.479 Inf 0.288 0.9553 Before-After 0.8053 0.609 Inf 1.323 0.3824 Before-After 0.763 0.502 Inf 1.522 0.2807 During-After 0.0694 0.659 Inf 0.105 0.9939 During-After 0.625 0.48 Inf 1.304 0.3932 Mysids estimate SE df z.ratio p.value Mysids estimate SE df z.ratio p.value Before-During 156 62.4 2.52 2.496 0.1915 Before-During 113.5 47 5.91 2.414 0.115 Before-After 273 63.7 2.66 4.28 0.0577 Before-After 159.2 35 3.37 4.55 0.0321 During-After 117 32.6 4.59 3.586 0.0401 During-After 45.7 41.5 5.55 1.1 0.5507 Decapods estimate SE df z.ratio p.value Decapods estimate SE df z.ratio p.value Before-During 40.5 33 3.15 1.229 0.5136 Before-During 13.4 7.21 3.09 1.857 0.2907 Before-After 68.8 30.2 2.27 2.28 0.2407 Before-After 9.48 9.42 3.98 1.006 0.6122 During-After 28.2 17.2 5.48 1.64 0.3071 During-After -3.92 7.66 2.94 -0.512 0.8714 Isopods estimate SE df z.ratio p.value Isopods estimate SE df z.ratio p.value Before-During 2.148 0.808 3.17 2.659 0.1409 Before-During 16.89 6.11 3 2.765 0.1356 Before-After 0.363 1.675 2.83 0.216 0.9747 Before-After 7.05 7.66 3.99 0.92 0.6581 During-After -1.786 1.566 2.26 -1.14 0.5748 During-After -9.84 6 3.04 -1.641 0.356 POLYHALINE ZONE MESOHALINE ZONE 121 4. EFFECTS OF FRESHET EVENTS ON THE BIOTIC AND ABIOTIC CONDITIONS IN A WELL-MIXED ESTUARY Abstract Freshwater input is one of the most important variables to generate elevated productivity in estuaries, influencing over many biogeochemical processes. However, when high discharges happen, it may also affect estuarine biota by altering its water physiochemical variables and displacing the organisms. The present study investigates the short-term effects of three different kind of freshets events on the early life stages of fish species, the rest of macrofauna and the environmental conditions in the Guadalquivir estuary. Freshet events generally produced a strong shift in physiochemical conditions of most the estuary section, compressing salinity gradient and increasing turbidity, and even decreasing oxygen concentration in some cases. This alteration influenced in the abundance and distribution of early life stages of fishes and the rest of macrofauna, reducing its nursery area. Still, the physicochemical conditions showed an almost complete or partial recovery (depending on the intensity, duration and period of the discharge) to the previous state in a short term (one month after the freshet approx.). Instead, different biological responses were found depending on the species and periods, such as displacement downstream, flushing out of the estuary or cueguided attraction. In general, the estuarine species like gobies and other macrofauna groups coped better with the freshets than marine species like anchovies. Nonetheless, despite of the multiple environmental disturbances caused by the distinct natural freshet events, the estuary and their estuarine organisms showed a high resilience. Chapter 4 Effects of freshet events 128 discharges higher than 200 m3/s. This event was a “pulse” with a short temporal freshet of 2 days. Physiochemical variables showed spatio-temporal variations during the whole event (Figure 3). No results were obtained in the sampling day of After 2 due to technical problems with the multiprobe. Salinity gradient was compressed longitudinally close to the river mouth just after the high discharge. The isohaline of 1 PSU was registered 30 Km upstream. Salinity showed a strong vertical stratification with more than 15 PSU of differences between the surface and bottom layers in some zones. The isohaline of 5 PSU (and hence the practical space available for nursery function) almost recovered its position 6 days afterwards. However, the longitudinal and vertical structure of the salinity gradient maintained altered, mostly in downstream zones. Turbidity was gradually higher in upstream zones, where the discharge provoked a notable increase in the bottom, reaching values of 3500 NTU, although they restored partially in After 1. Before the high discharge pulse, pH was gradually lower downstream. During the elevated discharge, pH decreased and was homogenized along the longitudinal section. This lower pH was still held in the estuarine zone thereafter. The oxygen showed higher concentrations in upstream zones before the freshet. The concentration increased during the discharge in the whole sampling section, especially in the surface layers of the middle zone (5 and 30 Km). The oxygen saturation, which was homogeneous along the longitudinal section before the freshet, also changed afterwards, showing a gradual increment towards the estuary inlet. The temperature showed a temporal decline, with softer changes in the outer zone. A total of 21 species of early life stages of fish were found, 15 in the freshet event and 17 in the control period. SIMPER analysis showed the characteristics species for both study Figure 2. Temporal series of freshwater inputs in the Guadalquivir estuary and local rainfall from Alcalá del Río station during the event 1 in 2015. Vertical dashed lines indicate sampling dates [Blue: Before (08/10/15); Red: During (05/11/15); Green: After 1 (11/11/15); Orange: After 2 (11/12/15)]. Chapter 4 Effects of freshet events 129 Figure 3.1. Physiochemical variables (salinity, turbidity and pH) recorded in the water column (normalize depth) along the longitudinal section of the estuary from the river mouth to the most upstream sampling station during the different sampling dates [A (Before: 08/10/15), B (During: 05/11/15), C (After 1: 11/11/15)] of the high discharge event 1 in 2015. A B C Chapter 4 Effects of freshet events 130 Figure 3.2. Physiochemical variables (dissolved oxygen, oxygen saturation and temperature) recorded in the water column (normalize depth) along the longitudinal section of the estuary from the river mouth to the most upstream sampling station during the different sampling dates [A (Before: 08/10/15), B (During: 05/11/15), C (After 1: 11/11/15)] of the high discharge event 1 in 2015. A B C Chapter 4 Effects of freshet events 131 periods, being Pomatoschistus spp., Engraulis encrasicolus, Aphia minuta and Sardina pilchardus the common species that more contributed to the similarity (Table 1). The spatial distribution of most organisms in the freshet event was displaced 10-15 downstream during the high discharge (Figure 4). Statistical differences of the fixed effect “Time” for GAM on all variables were summarized in the plots by letter code and extended in Table S.1. The total abundance of early fish stages decreased significantly during the high discharge, although it almost recovered the density one week later (After 1), and also the distribution one month thereafter (After 2) (Figure 4.1.A). On the other hand, the analysis of the control period (Oct-Dec 2017) showed no changes in spatial distribution and a gradual temporal decrease, reaching significantly lower values in December. Macrofauna biomass did not show significant differences during the high discharge event, but it showed a temporal decrease in the control period (Figure 4.1.B). The spatiotemporal abundance of Pomatoschistus spp. fluctuated along the different periods showing a high increase in the lower zone (15-25 km) after the high discharge (Figure 4.1.C). The anchovy Engraulis encrasicolus was the species with highest density during the event. Its abundance declined significantly during the freshet and the sampling day After 1 (Figure 4.2.D). The density and distribution recovered completely, showing the same pattern as before the event in After 2. Instead, it showed a gradual decrease during those months in the control period. Aphia minuta was found mainly in the outer zone of the estuary during and after the freshet period (where no data were obtained before the high discharge due to technical problems) (Figure 4.2.E). Still, low abundance was found in the outer zone during October in the control period, whose density oscillated between sampling times. The spatio-temporal abundance of Sardina pilchardus did not show a significant variation in the freshet event, although their levels increased slightly in upstream zones thereafter. In the control groups, it was absent in October, and the abundance fluctuated significantly during the next months (Figure 4.2.F). Table 1. Results of SIMPER analysis on the abundance of all larval and juvenile fish species from every period (freshet and control) of the high discharge event 1. Average similarity: 49.16 Species Av.Abund Av.Sim Sim/SD Contrib% Cum.% Engraulis encrasicolus 2.9 23.6 2.17 48.01 48.01 Pomatoschistus spp. 2.42 14.65 0.98 29.79 77.8 Aphia minuta 0.96 5.03 0.48 10.23 88.04 Sardina pilchardus 0.74 2.69 0.45 5.48 93.51 Average similarity: 34.65 Species Av.Abund Av.Sim Sim/SD Contrib% Cum.% Engraulis encrasicolus 2.59 15.44 1.15 44.54 44.54 Pomatoschistus spp. 1.87 8.85 0.78 25.53 70.07 Aphia minuta 1.09 3.85 0.55 11.1 81.16 Anguilla anguilla 0.59 2.18 0.33 6.3 87.47 Sardina pilchardus 0.67 1.46 0.33 4.22 91.69 Freshet Event 1 Control Event 1 Chapter 4 Effects of freshet events 132 Figure 4.1. Spatial distribution of total early fish abundance (A), macrofauna biomass (B) and Pomatoschistus spp. (C) along the longitudinal section of the Guadalquivir estuary in the different sampling days during the high discharge (Before: 08/10/15; During: 05/11/15; After 1: 11/11/15; After 2: 11/12/15) and the control (October: 21/10/17; November: 30/11/2017; December: 13/12/17) periods of the freshet event 1. Different letters mean significant differences (p<0.05) between the levels of Time factor for GAM in every period. 0 500 1000 1500 2000 010 20 30 40 Distance (Km) Early fish stages (n/1000m3) Discharge 2015 Before (October) During (November) After1 (November) After2 (December) 0 500 1000 1500 2000 010 20 30 40 Distance (Km) Early fish stages (n/1000m3) Control 2017 October November December 0 500 1000 1500 2000 010 20 30 40 Distance (Km) Macrofauna (g.f.w./1000m3) Discharge 2015 Before (October) During (November) After1 (November) After2 (December) 0 500 1000 1500 2000 010 20 30 40 Distance (Km) Macrofauna (g.f.w./1000m3) Control 2017 October November December 0 200 400 600 010 20 30 40 Distance (Km) Pomatoschistus spp. (n/1000m3) Discharge 2015 Before (October) During (November) After1 (November) After2 (December) 0 200 400 600 010 20 30 40 Distance (Km) Pomatoschistus spp. (n/1000m3) Control 2017 October November December A B C a b a a a a a a ab a b ab a a b a b b a a a Chapter 4 Effects of freshet events 133 Figure 4.2. Spatial distribution of Engraulis encrasicolus (D), Aphia minuta (E) and Sardina pilchardus (F) along the longitudinal section of the Guadalquivir estuary in the different sampling days during the high discharge (Before: 08/10/15; During: 05/11/15; After 1: 11/11/15; After 2: 11/12/15) and the control (October: 21/10/17; November: 30/11/2017; December: 13/12/17) periods of the freshet event 1. Different letters mean significant differences (p<0.05) between the levels of Time factor for GAM in every period. 0 500 1000 1500 2000 010 20 30 40 Distance (Km) Engraulis encrasicolus (n/1000m3) Discharge 2015 Before (October) During (November) After1 (November) After2 (December) 0 500 1000 1500 2000 010 20 30 40 Distance (Km) Engraulis encrasicolus (n/1000m3) Control 2017 October November December 0 50 100 150 200 010 20 30 40 Distance (Km) Aphia minuta (n/1000m3) Discharge 2015 Before (October) During (November) After1 (November) After2 (December) 0 50 100 150 200 010 20 30 40 Distance (Km) Aphia minuta (n/1000m3) Control 2017 October November December 0 50 100 150 010 20 30 40 Distance (Km) Sardina pilchardus (n/1000m3) Discharge 2015 Before (October) During (November) After1 (November) After2 (December) 0 50 100 150 010 20 30 40 Distance (Km) Sardina pilchardus (n/1000m3) Control 2017 October November December D E F a b b a a b b b a a a a a b c ab a b a a b Chapter 4 Effects of freshet events 134 3.2. Event 2 (discharge 2016) The event 2 happened in the same season as event 1, autumn, but with different characteristics. Precipitations were high and frequent during the month of November 2016, reaching values higher than 30 mm/day on several occasions (Figure 5). Increments in freshwater input were associated to rainfalls. The flow increased during one day to 150 m3/s, before the first sampling day; afterwards, an event of high discharge happened at the end of November, with almost 250 m3/s; finally, there were several low and temporally short discharges around 100 m3/s during the first fortnight of December (Figure 5). Physiochemical variables showed spatio-temporal variations during the whole event (Figure 6), with a slight vertical stratification in some variables (mainly salinity and DO) in the Before sampling day, probably for the previous increment of freshwater input. Salinity gradient was reduced longitudinally, displacing the isohaline of 5 PSU from 30 Km upstream in Before to 10 Km during the high discharge. It was similar as event 1 but with a higher spatial reduction; the isohaline of 1 PSU was registered 20 Km upstream. Also, it provoked a strong vertical stratification with more than 15 PSU of difference between the surface and bottom layers in some zones. The longitudinal and vertical alteration was almost recovered 14 days after (After 1) the high discharge. Turbidity showed the same pattern as in the event 1, although the maximum values recorded were lower, with 2500 NTU, and they were observed more downstream. The pH was always stable in the outer zone with a value of 8. Instead, inner estuarine zone showed fluctuations. The higher values (8.1) registered in upstream zones in the first sampling, were then observed in the middle of the studied section during the high discharge with even higher values in the surface layers. Afterwards, the pH levels decreased to 7.8, and Figure 5. Temporal series of freshwater inputs in the Guadalquivir estuary and local rainfall from Alcalá del Río station during the event 2 in 2016. Vertical dashed lines indicate sampling dates [Blue: Before (24/11/16); Red: During (28/11/16); Green: After 1 (12/12/16); Orange: After 2 (10/01/17)]. Chapter 4 Effects of freshet events 135 Figure 6.1. Physiochemical variables (salinity, turbidity and pH) recorded in the water column (normalize depth) along the longitudinal section of the estuary from the river mouth to the most upstream sampling station during the different sampling dates [A (Before: 24/11/16), B (During: 28/11/16), C (After 1: 12/12/16), D (After 2: 10/01/17)] of the high discharge event 2 in 2016. A B C D Chapter 4 Effects of freshet events 136 Figure 6.2. Physiochemical variables (dissolved oxygen, oxygen saturation and temperature) recorded in the water column (normalize depth) along the longitudinal section of the estuary from the river mouth to the most upstream sampling station during the different sampling dates [A (Before: 24/11/16), B (During: 28/11/16), C (After 1: 12/12/16), D (After 2: 10/01/17)] of the high discharge event 2 in 2016. A B C D Chapter 4 Effects of freshet events 137 only showed a partial recovery one month later (7.9). The dissolved oxygen showed a similar pattern as the pH, with a displacement of the highest values (9 mg/L approx.) to the middle section during the high discharge. The levels decreased in the whole section in After 1 (never lower than 6 mg/L), but they almost recovered the same levels and distribution as before the event in the last sampling. A soft stratification with lower values in the bottom were observed in most samplings. Instead, oxygen saturation decreased during the high discharge, especially in the upstream zones, although it reached the previous percentages at the end. The temperature showed a slight and gradual increment downstream, while it declined temporally. A total of 22 species of early life stages of fish were found, 21 in the freshet event and 17 in the control period. SIMPER analysis showed the characteristics species, being Pomatoschistus spp., Engraulis encrasicolus, Aphia minuta, Sardina pilchardus and Solea senegalensis the species that more contributed to the similarity in both periods (Table 2). The spatial distribution of most organisms in the freshet event was displaced to downstream zones during the high discharge, occupying only the first 15-20 Km (Figure 7). Statistical differences of the fixed effect “Time” for GAM on all variables were summarized in the plots by letter code and extended in Table S.2. The abundance of early fish stages showed a significant reduction during the high discharge, at the same time as compressed their distribution to the first 15 Km from estuary mouth (Figure 7.1.A). Afterwards, its abundance recovered partially, with distinct patterns in the distribution, which was elongated upstream a Table 4. Results of SIMPER analysis on the abundance of all larval and juvenile fish species from every period (freshet and control) of the high discharge event 2. Average similarity: 34.38 Species Av.Abund Av.Sim Sim/SD Contrib% Cum.% Pomatoschistus spp. 2.07 14 0.9 40.71 40.71 Engraulis encrasicolus 1.54 9.37 0.97 27.26 67.97 Aphia minuta 0.85 3.53 0.4 10.26 78.23 Sardina pilchardus 0.54 1.87 0.39 5.43 83.66 Solea senegalensis 0.73 1.64 0.33 4.78 88.45 Dicologoglossa cuneata 0.54 1.1 0.21 3.2 91.65 Average similarity: 39.85 Species Av.Abund Av.Sim Sim/SD Contrib% Cum.% Pomatoschistus spp. 2 13.5 1.02 33.87 33.87 Aphia minuta 1.29 6.49 0.64 16.29 50.16 Engraulis encrasicolus 1.51 6.42 0.73 16.12 66.28 Sardina pilchardus 1.09 5.2 0.67 13.06 79.34 Solea senegalensis 0.72 2.5 0.46 6.27 85.6 Anguilla anguilla 0.62 2.29 0.47 5.74 91.35 Freshet Event 2 Control Event 2 Chapter 4 Effects of freshet events 144 A total of 24 species of early life stages of fish were found, 21 in the freshet event and 20 in the control period. SIMPER analysis showed the characteristics species for both study periods, sharing Pomatoschistus spp., Sardina pilchardus, Solea senegalensis and Diplodus vulgaris (Table 3). The spatial distribution of most organisms in the freshet event was displaced to downstream zones during the high discharge, relegate them to the first 15 Km (Figure 10). The outer station could not be sampled in February and March of control period due to inclement weather in that zone. Statistical differences of the fixed effect “Time” for GAM on all variables were summarized in the plots by letter code and extended in Table S.3. Total abundance of early fish stages did not change significantly in the estuary section during the freshet, but its distribution was compressed downstream (Figure 10.1.A). In the two sampling times after the freshet, its density showed a notable and significant increment, and the distribution was elongated until 30 Km upstream. In the control period, the abundance increased temporally, but with much lower densities than the freshet period. Macrofauna biomass fluctuated between sampling times, showing a significant increment in the last cruise to compare with during the freshet (Figure 10.1.B). The distribution was compressed during the high discharge in the first 10 km from the estuary mouth. The distribution extended upstream two weeks later (After 1), and the densities incremented one month thereafter following the seasonal trend in this period. Also, control period showed a temporal increment of density, but with a more elongated Table 3. Results of SIMPER analysis on the abundance of all larval and juvenile fish species from every period (freshet and control) of the high discharge event 3. Average similarity: 44.30 Species Av.Abund Av.Sim Sim/SD Contrib% Cum.% Pomatoschistus spp. 4.44 22 1.82 49.65 49.65 Aphia minuta 1.42 3.99 0.64 9 58.65 Sardina pilchardus 1.23 3.63 0.67 8.19 66.84 Solea senegalensis 0.96 3.24 0.66 7.31 74.15 Gobius paganellus 1.2 2.88 0.58 6.49 80.65 Sparus aurata 0.89 2.86 0.52 6.46 87.11 Diplodus vulgaris 0.69 1.53 0.43 3.45 90.55 Average similarity: 51.35 Species Av.Abund Av.Sim Sim/SD Contrib% Cum.% Pomatoschistus spp. 3.05 16.35 1.77 31.85 31.85 Engraulis encrasicolus 2.22 13.68 2.16 26.63 58.48 Sardina pilchardus 1.8 7.21 1.02 14.04 72.52 Diplodus vulgaris 1.11 3.81 0.72 7.42 79.94 Solea senegalensis 0.95 3.04 0.7 5.92 85.86 Dicentrarchus labrax 1.1 2.39 0.51 4.65 90.5 Freshet Event 3 Control Event 3 Chapter 4 Effects of freshet events 145 Figure 10.1. Spatial distribution of total early fish abundance (A), macrofauna biomass (B), Pomatoschistus spp. (C) and Gobius paganellus (D) along the longitudinal section of the Guadalquivir estuary in the different sampling days during the high discharge (Before: 14/02/18; During: 22/03/18; After 1: 28/03/18; After 2: 26/04/18) and the control (February: 22/02/16; March: 21/03/16; April: 21/04/16) periods of the freshet event 3. Different letters indicate significant differences (p<0.05) between the levels of Time factor for GAM in every period. “*” for species absent during the period. 0 500 1000 1500 2000 2500 010 20 30 40 Distance (Km) Macrofauna (g.f.w./1000m3) Discharge 2018 Before (February) During (March) After1 (March) After2 (April) 0 500 1000 1500 2000 2500 010 20 30 40 Distance (Km) Macrofauna (g.f.w./1000m3) Control 2016 February March April 0 1000 2000 3000 4000 010 20 30 40 Distance (Km) Pomatoschistus spp. (n/1000m3) Discharge 2018 Before (February) During (March) After1 (March) After2 (April) 0 1000 2000 3000 4000 010 20 30 40 Distance (Km) Pomatoschistus spp. (n/1000m3) Control 2016 February March April 0 50 100 150 200 010 20 30 40 Distance (Km) Gobious paganellus (n/1000m3) Discharge 2018 Before (February) During (March) After1 (March) After2 (April) 0 50 100 150 200 010 20 30 40 Distance (Km) Gobious paganellus (n/1000m3) Control 2016 February March April 0 1000 2000 3000 4000 010 20 30 40 Distance (Km) Early fish stages (n/1000m3) Discharge 2018 Before (February) During (March) After1 (March) After2 (April) 0 1000 2000 3000 4000 010 20 30 40 Distance (Km) Early fish stages (n/1000m3) Control 2016 February March April A B C D a a b b a b c ab a ab b a b c a a b b a b c a ab b ab * * * Chapter 4 Effects of freshet events 146 Figure 10.2. Spatial distribution of Sardina pilchardus (E), Aphia minuta (F), Sparus aurata (G) and Solea senegalensis (H) along the longitudinal section of the Guadalquivir estuary in the different sampling days during the high discharge (Before: 14/02/18; During: 22/03/18; After 1: 28/03/18; After 2: 26/04/18) and the control (February: 22/02/16; March: 21/03/16; April: 21/04/16) periods of the freshet event 3. Different letters indicate significant differences (p<0.05) between the levels of Time factor for GAM in every period. “*” for species absent during the period. 0 100 200 300 400 010 20 30 40 Distance (Km) Sardina pilchardus (n/1000m3) Discharge 2018 Before (February) During (March) After1 (March) After2 (April) 0 100 200 300 400 010 20 30 40 Distance (Km) Sardina pilchardus (n/1000m3) Control 2016 February March April 0 250 500 750 1000 010 20 30 40 Distance (Km) Aphia minuta (n/1000m3) Discharge 2018 Before (February) During (March) After1 (March) After2 (April) 0 250 500 750 1000 010 20 30 40 Distance (Km) Aphia minuta (n/1000m3) Control 2016 February March April 0 10 20 30 40 50 010 20 30 40 Distance (Km) Sparus aurata (n/1000m3) Discharge 2018 Before (February) During (March) After1 (March) After2 (April) 0 10 20 30 40 50 010 20 30 40 Distance (Km) Sparus aurata (n/1000m3) Control 2016 February March April 0 20 40 60 010 20 30 40 Distance (Km) Solea senegalensis (n/1000m3) Discharge 2018 Before (February) During (March) After1 (March) After2 (April) 0 20 40 60 010 20 30 40 Distance (Km) Solea senegalensis (n/1000m3) Control 2016 February March April E F G H a ab b b ab a b ab a b ab * * * a ab ab b a a b a ab a b a b a Chapter 4 Effects of freshet events 147 abundance upstream in April. The goby Pomatoschistus spp. was the fish species most dominant during this event, with the 80% of abundance. Therefore, it determined the observed pattern of total early fish abundance described previously (Figure 10.1.C). Another species of goby, Gobius paganellus, was absent before the freshet, showing an increment in the abundance during the freshet, mainly in downstream zone (Figure 10.1.D). Thereafter, its abundance and distribution continued increasing upstream, although its density decreased in all estuary section one month later (After 2). This species was not present during the control period. Sardina pilchardus was also not present in the estuary before the freshet (Figure 10.2.E). Individuals were found in the outer zone during the high discharge, but with low densities. Afterwards, it showed a slight but significant increase in the middle estuary section. The control period showed temporal fluctuations, being the month of April the most abundant. Aphia minuta was present in the outer zone with high densities before the freshet, but it disappeared during the high discharge in this case (Figure 10.2.F). Thereafter, it showed a low increment in downstream zone (After 1). This species was not found in the estuary during the control period, as happened with Gobius paganellus. The seabream Sparus aurata reduced its density gradually, being not present in the last sampling time (Figure 10.2.G). Instead, the distribution during the high discharge was reduced from upstream (40 Km) to downstream (5 Km) zones. Afterwards, it recovered partially the distribution but with lower densities as before, mainly in upstream zone. The control period showed a similar temporal decline for this species, but with a different distribution pattern. Solea senegalensis was almost absent before the high discharge (Figure 10.2.H). During the freshet, some individuals were found in downstream zones. Thereafter, it returned to previous conditions (After 1), but later, the density increased significantly in the middle estuary section (After 2). It showed a similar spatial distribution in the control period, with different density fluctuations between months, although its maximum abundances were lower than those found in April of the freshet period. The other contributor species caught presented too low densities to find patterns. 4. Discussion This study was conducted to characterize the short response times and spatial distribution pattern of early life stage of fish and the rest of the macrofauna following high discharge events in a well-mixed estuary and its nearshore area. The differences in the intensity, duration and period of the year of every discharge were an opportunity to better understand the plankton dynamic in estuaries under distinct runoff scenarios. A shift on physiochemical conditions were observed in all cases, but the degree of biological response varied among Chapter 4 Effects of freshet events 148 events. Still, distribution of organisms showed a compression downstream during the high discharge similar as did the longitudinal salinity gradient in all studied freshets. 4.1. Physiochemical effects High discharges sampled in the Guadalquivir estuary were associated to an increment of the precipitations in the region, which were more abundant and frequent in autumn and spring seasons during this study. Still, rainfalls do not always provoke an increment in the freshwater input due to the damming and water reservoir management of the watershed (González-Ortegón and Drake, 2011). This estuary is characterized by freshwater inputs lower than 40 m3/s during 75% of the year (Díez-Minguito et al., 2012), hence all the freshet events sampled were in high river inflow conditions. In fact, among the different freshets, the event 3 changed the water current regime of the estuary from tidally-dominated to fluvially-dominated, as the monthly mean flow discharged was higher than 400 m3/s (Díez-Minguito et al., 2012). Under low freshwater input conditions, this estuary is considered, hydrologically, a wellmixed system (Vanney, 1970) with a longitudinal salinity gradient from seawater (≈36 PSU) in the estuary mouth to freshwater (≈0 PSU) 80 km upstream approximately (Díez-Minguito et al., 2013). The salinity was vertically stratified and longitudinally compressed in the downstream zone during all events, although its degree of change depended on the kind of freshet. The more intense and lasting was the discharge, the higher the compression of the salinity gradient. When freshwater inflow diminished, salt wedge intruded gradually further up the estuary, although with distinct recovery times. It depends on the spring-neap tidal cycle during which the discharge occurs, the magnitude of the freshwater discharge, and the atmospheric and oceanographic conditions at the mouth and the inner shelf (Díez-Minguito et al., 2013). While the event 1 and 2 took a few days, the event 3 spent more than one month, especially in the upstream zone. The advance of the salt wedge during the flood tide was associated with a decrease in turbidity due to the advection of (less turbid) seawater, similar as other authors reported in a freshet event in the Guadiana estuary (Garel et al., 2009). Still, the recovery time of this variable was slower than the salinity. In the Guadalquivir estuary it has been reported two estuarine turbidity maximum (ETM) in low freshwater input conditions: at 35 km and 58 km (from estuary mouth; equivalent to 42 Km and 64 Km in our longitudinal section scale) approximately (Díez- Minguito et al., 2014). Although not all the estuarine section has been sampled in this study, the higher turbidity found near-bed during the high discharges could indicate a resuspension of sediment, including the displacement downstream, at least, of the lower ETM (Garel et al., 2009). Also, the high values registered in the whole water column in most of the estuarine Chapter 4 Effects of freshet events 149 section suggest elevated inputs of TSS load from the drainage basin. In fact, the supply was so high in the event 3 that it formed a turbid plume which spread several kilometres offshore from estuary mouth (Figure S.2). Previous studies in the Guadalquivir also have reported high concentrations of TSS during freshet events [e.g. 3500 mg/L in Navarro et al. (2012) or 5000 mg/L in Ruiz et al. (2017)], although in this case, the values were much higher (13774 mg/L), even than other estuaries [e.g. (Garel and Ferreira, 2015; Jalón-Rojas et al., 2015)]. For this reason, the Guadalquivir estuary has been characterized as a high turbidity system, especially in wet years (González-Ortegón et al., 2010; Losada et al., 2017). On the other hand, high turbidity levels have been related with hypoxic conditions (Schmidt et al., 2019). The light penetration in the water column can be limited for the high turbidity, reducing the photosynthetic activity by phytoplankton (Ruiz et al., 2017), while the increment of organic and inorganic nutrients could increase the oxygen consumption by oxidation (Henrichs, 1992) or heterotrophic bacteria respiration (Atwood et al., 2012), which in its turn, it would increase CO2 and reduce the pH. Therefore, the generalized decline of pH levels and oxygen concentration observed in the whole estuary section after the freshets could indicate a high bacteria proliferation. Still, only the event 3 showed hypoxic conditions. The extreme turbidity and the extended period of this discharge (1 month approx.) would have further increased photosynthesis limitation and oxygen consumption. Also, Navarro et al. (2012) observed similar effects during some freshet events during 2008-2010 in the Guadalquivir estuary, although in their case, the oxygen concentration reached even lower values (0.52 mg/L). 4.2. Biological effects Freshets not only controlled the circulation of water masses and their physiochemical conditions, but also modify the structure and distribution of small organism populations. In general, the distribution of early life stages of fish and macrofauna species were associate to the salinity gradient, being almost absent in the freshwater masses during the high discharges despite of being located closer to the estuary mouth. Young recruits of marine species seemed to be pulled by freshwater flow, moving with the mass of estuarine water. They were almost absent in water masses lower than 5 PSU in the Guadalquivir estuary, even in low inflow conditions (Fernández-Delgado et al., 2007). On the other hand, no increments of densities were found in the outer station during the high discharge of any freshet despite the total abundance of organisms decreased generally in the inner estuarine zone. This suggest several possibilities for individuals not found, unless for a part of the community: i) they could have been flushed Chapter 4 Effects of freshet events 150 out further of the sampling area, as some studies found high abundance of early fish stages in the front of the plumes (Kingsford and Suthers, 1994; Sabatés, 1990), ii) they could have been predated in the nearshore areas and/or clearer zones downstream (Utne-Palm, 2002) or die by osmotic shocks (Serafy et al., 1997) and/or iii) they could have been used shelter zones as shoals, rocks or even submerged channels in the estuary mouth as reported Ueda et al. (2004) for some zooplankton species. Different biological effects were found for the events 1 and 2 that for the event 3. In addition to the intensity of freshwater discharged, these events happened in different seasons. The events 1 and 2 took place during the autumn, when the temperature and the density of the macrofauna in the Guadalquivir estuary usually declines, while the event 3 was during the spring, when the temperature, the biological activity and recruitment start to increase (Drake et al., 2002). Still, the species Pomatoschistus spp., Aphia minuta and Sardina pilchardus were characteristics in all of them. The fish species which better cope with the different freshet events was the goby Pomatoschistus spp. Although it showed different patterns during the high discharge in every event, its abundance and distribution recovered quickly or even increased notably in all of them. This goby is a benthic estuarine species whose bottom behaviour and the pectoral fin adduction may help them to deal with strong water currents settling in the bottom (Dolbeth et al., 2007), or even burrowing in the sediment (Magnhagen and Forsgren, 1991), being displaced downstream but no flushed out. These strategies would help to recover the distribution rapidly following the advance of salinity wedge formed by the flood tide. In addition, the pattern found during the event 3 suggests a strong call effect, because it coincided with its recruitment period, the early spring (González-Ortegón et al., 2012; Pampoulie et al., 1999), and its density increased remarkably in comparison with previous sampling day and also with the control period. Similar pattern was observed for the rock goby, Gobius paganellus, which is a species predominantly marine but can enter brackish waters (Azevedo and Simas, 2000), likely attracted by the concentration of prey downstream as small invertebrates observed in the macrofauna. The distribution of both gobies in high densities in the middle section of the estuary in the sampling day just after the high discharge showed their tolerance to high turbidity levels. In fact, we did not find many other organisms in this part of the section after the freshet; these turbid zones were also characterized by a low oxygen concentration (hypoxia in some instances), what could make them unsuitable (Schmidt et al., 2019). The transparent goby, Aphia minuta, showed variable responses depending on the period of the event. It increased in the estuary mouth during the freshets of autumn, while it disappeared during the high discharge of spring. Chapter 4 Effects of freshet events 151 Differences could be doubt to the settlement periods of early life stages (La Mesa et al., 2005). Still, this species seems to be lured, showing increments of their abundances when environmental conditions were more variable, as González-Ortegón et al. (2010) found during high persistent turbidity events in the inner zone. In contrast, most pelagic species which were abundant in inner zones did not recover the densities after the discharge. This was the case of the seabream Sparus aurata, which was displaced to lower zones and even flushed out. Its natural trend is to decrease during the spring, as showed the control period, but the freshet could have reduced its recruitment period, which can fluctuate in the region along the winter and early spring (Arias and Drake, 1990). Similar pattern was found for the anchovy Engraulis encrasicolus, although its negligible presence during the discharges suggest that it was completely flushed out of the estuary. Still, the event 1 showed a late recovery, while event 2 did not. The different recoveries could be because the discharge of event 1 was lower in intensity and duration, so individuals could be expelled closer to the estuary mouth, and therefore, return later. However, no density increments were found in the outer zone. Alternatively, high recruitment period of anchovy has been registered from May to November mainly, although this can oscillate interannually (Drake et al., 2007), enabling that a new recruitment stock from offshore could have been attracted and the previous estuarine population could have been predated in the nearshore area. The event 3 happened during the high larval recruitment period offshore of two important commercial fish in the Gulf of Cádiz, Sardina pilchardus and Solea senegalensis (Baldó et al., 2006). While S. pilchardus showed similar patterns during the event and control periods, S. senegalensis increased their densities in the freshet period one month after the discharge, which could suggest an attraction effect in this species due to the extent of estuarine cues by the large river plume (Kingsford and Suthers, 1994; Teodósio et al., 2016). Also, the resto of macrofauna, as important food resource for many early fish stages (Baldó and Drake, 2002), can influence in their distribution (Drake et al., 2007). In fact, the spatial distribution along the section of the total abundance of early fishes and the rest of the macrofauna were very similar in most of the sampling days in all events. Macrofauna, when it was relative abundant before the freshet (event 2 and 3), tended to decrease slightly during the high discharge. But later, it recovered previous conditions quickly and its total abundance tended to increase (although the differences were not found to be significant), even when its normal trend was to decrease (event 2). This response, similar to that of gobies, shows the adaptation of estuarine species to these ecosystems, which better cope with this type of situation, probably avoiding being expelled from the estuary using shelter zones as a Chapter 4 Effects of freshet events 152 mechanism. Different studies have reported the benefits of freshet events in the lower trophic levels of estuaries by the nutrients and organic matter inputs, increasing the phytoplankton diversity and abundance, which in its turn, increase the secondary production as zooplankton (Chícharo et al., 2006; Hoover et al., 2006). However, the high turbidity levels found could difficult the photosynthetic activity and primary production in most of the water column of the estuary section (Ruiz et al., 2017), at least in the short-term studied. Instead, allochthonous carbon supplied by freshwater input can directly support zooplankton taxa with a more heterotrophic energy pathway (Abrantes et al., 2013; Hitchcock et al., 2016; Hoffman et al., 2008). Therefore, frequent high discharges in the Guadalquivir estuary can change in resource utilisation at the base of the food chain, making it one of the most productive systems of the region (Miró et al., 2020). In summary, high freshet events generally generated a strong shift in physiochemical conditions of most estuary section, compressing salinity gradient, increasing turbidity and decreasing oxygen concentration. This alteration influenced in the abundance and distribution of early life stages of fishes and the rest of macrofauna, reducing its nursery area. 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