Field study on natural phytoplankton throughout “Bizerte City” oil spill on the south-western coast of the Mediterranean Sea

Field study on natural phytoplankton throughout “Bizerte City” oil spill on the south-western coast of the Mediterranean Sea | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Field study on natural phytoplankton throughout “Bizerte City” oil spill on the south-western coast of the Mediterranean Sea Boutheina Grami, Oumayma Chkili, Sondes Melliti Ben Garali, Kaouther Mejri Kousri, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4019976/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 Jul, 2024 Read the published version in Aquatic Sciences → Version 1 posted 12 You are reading this latest preprint version Abstract Oil spills are recurrent worldwide. Assessing the response of phytoplankton – the basis of marine food webs – at the early stages of an oil spill and throughout its evolution is crucial to improve our understanding of the impact of oil spills on the marine environment. Field data collected 1, 4, 8 and 18 days after the “Bizerte City” oil spill showed that phytoplankton responded differentially over time. In the short term (1–8 days), picophytoplankton biomass and abundance increased, possibly due to reduced grazing. In contrast, nano- and microphytoplankton biomass decreased, probably owing to inhibited growth of species sensitive to polycyclic aromatic hydrocarbons (PAHs) – the most toxic components of oil. After 18 days, the dispersal of oil and its decreasing negative effect were accompanied by outbreaks of all size fractions. Accordingly, the phytoplankton size structure shifted throughout the oil exposure level from a prevalence of microphytoplankton after a few days toward picophytoplankton dominance. Oil pollution influenced the species composition and significantly decreased diversity indexes. In the first days, nanophytoplankton was dominated by cryptophyceae (mainly Hillea fusiformis and H. marina ), while microphytoplankton was mostly represented by the pennate diatoms Pseudo-nitzschia and Nitzschia , suggesting a better resistance of these genera to oil. Algal recovery after 18 days was associated with high proliferation of nano-sized Chaetoceros and micro-sized Astrionellopsis glacialis diatoms. These results improve our knowledge of the impact of oil pollution on coastal phytoplankton communities and reinforce the idea of using them as bio-indicators. oil spill phytoplankton diatoms diversity Coastal waters Mediterranean Sea Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Oil spills are unintentional releases of petroleum oil or derived oils into the marine ecosystem (Li et al. 2016 ). They have serious environmental and socio-economic impacts on marine ecosystems (Nwipie et al. 2019 ; Soares et al. 2022 ) and are a persistent threat to human health because of their impact on aquatic food resources (Wirtz and Liu 2006 ; Penela-Arenaz et al. 2009 ; El-Fadel et al. 2012 ; Arùjo et al. 2023). To understand the impact of oil pollution on marine environments, numerous studies have used phytoplankton because it represents the basis of marine ecosystem productivity and plays key roles in the nutrient and carbon cycles and as a biological carbon pump (Zehr and Kudela 2011 ; Tréguer et al. 2018 ). Therefore, the effects of toxic oil compounds on these primary producers can be cascaded to higher trophic levels and impact the food web dynamics as well as the biogeochemical cycles of marine ecosystems. Furthermore, phytoplanktonic species can respond quickly to marine contamination and environmental conditions, and are considered as an indicator of anthropogenic pressure and water quality (Verlecar et al. 2006 ; Marshall et al. 2006 ; Paches et al. 2019 ; Parsons et al. 2021 ; Song et al. 2022 ). Much effort has been dedicated to studying the response of marine phytoplankton to different oil spills, such as the “Volgoneft-248” spill in the Sea of Marmara (1999), the “Prestige” spill along the Spanish coast (2002), the “Montara” spill in the Northwest Shelf of Australia (2009), the “Deepwater Horizon” spill in the Gulf of Mexico (2010) and the “Texas City Y” spill (2014) (Varela et al. 2006 ; Taş et al. 2011 ; Sheng et al. 2011 ; González et al. 2009 ; Gemmell et al. 2018 ; Bretherton et al. 2019a , 2020 ). Nevertheless, current knowledge on the effect of petroleum and its most toxic components – polycyclic aromatic hydrocarbons (PAHs) (Jiang et al. 2010 ) – on marine phytoplankton is still contradictory. After an oil spill, decreased phytoplankton photosynthesis can be observed as a direct response to the toxic impacts of petroleum compounds or as an indirect effect of less light penetrating into the water column caused by the presence of oil on the sea surface (Goutz et al. 1984 ; Tomajka 1985 ; González et al. 2009 ; Paul et al. 2013 ). Different negative effects have been observed after oil exposure, such as reduced phytoplankton growth, DNA damage, and inhibition of photosystem II (Aksmann and Tukaj 2008 ; Deasi et al. 2010 ; Bretherton et al. 2019a ). In contrast, other studies have reported a stimulation of phytoplankton growth (González et al. 2009 ; Taş et al. 2011 ; Bretherton et al. 2019a ). Ozhan et al. ( 2014 ), reported that crude oil at a low concentration ( 100 mg L − 1 ). The response of phytoplankton to oil pollution may also vary when considering short- or long-term effects (Lee et al. 2009 ; Tang et al. 2019 ). The phytoplankton community can also be impacted indirectly by such incidents via the effects of oil on the zooplankton community (González et al. 2009 ; Almeda et al. 2014 ; Van Dinh et al. 2019 ). The increase in phytoplankton biomass following an oil spill can be caused by a decrease in grazing due to PAH toxicity to zooplankton (Hjorth et al. 2007 ; Van Dinh et al. 2019 ; Tang and Buskey 2022 ). Contrasting effects of oil spills on taxonomic groups have also been reported. A decline in diatom biomass and an increase in phytoflagellates have been observed after laboratory or in situ oil exposure (Harrison et al. 1986 ; Mishamandani et al. 2015; Fiori et al. 2016 ), while an opposite impact has been reported in other cases (González et al. 2009 ; Gilde and Pinckney 2012 ; Parsons et al. 2015 ). Diatoms better tolerated high oil concentrations according to Ozhan et al. ( 2014 ), but dinoflagellates better tolerated oil pollution according to Jung et al. ( 2010 ), Taş et al. ( 2011 ) and Gemmell et al. ( 2018 ). These results highlight that the response of marine phytoplankton to the hydrocarbon components of oil depends on several factors, e.g., the amount and type of oil and the sensitivity of taxonomic groups, since oil toxicity to phytoplankton is widely species dependent (Ozhan et al. 2014 ). Oil exposure can be lethal for some species, but others can survive and grow at an unaffected or reduced rate. The oil-resisting ability of some phytoplankton species is related to the plasticity of their core metabolism, i.e., reduced extracellular carbohydrate secretion and enhanced flux through the Krebs cycle to conserve and increase energy production and counteract the oxidative stress caused by oil exposure (Kamalanathan et al. 2021 , 2022 ). Physiological traits such as cell size, motility and mixotrophy, are also important in determining the ability of species to survive oil exposure (Bretherton et al. 2020 ). Most data on the responses of marine phytoplankton to oil spills have been collected from experimental approaches. These include single species cultures or natural communities in microcosms and mesocosms (Varela et al. 2006 ; González et al. 2009 ; Gemmell et al. 2018 ; Bretherton et al. 2019a , 2020 ; Putzeys et al. 2022 ). However, field monitoring data from the early stages of an oil spill and throughout its evolution are rare because i) this requires heavy logistics, and ii) being on site and collecting samples rapidly is a challenge. Data on the early and late responses of natural phytoplankton following an oil spill are crucial to better understand how this event can affect marine communities. An oil spill incident occurred in the Bay of Bizerte (south-western Mediterranean Sea, northern Tunisia) on 4 October 2018 as a result of a crack in a tank of the Tunisian Company of Refining Industries. The government of Tunisia announced a leak of 7 tons of crude oil. The climatic and hydrodynamic features of the region extended the impact of the spill up to five km away from the source of the leak. The dykes/breakwaters built at the entrance of the Bizerte Channel reduce the sea current intensity, which prevented the oil spreading offshore. Therefore, the oil slick was directed towards the western coasts (Sidi Salem beach) and especially towards the Lagoon of Bizerte via the Channel (Fig. 1 ). The Lagoon supports intense fisheries and is considered as the main shellfish farming site in Tunisia. Therefore, incidents of this kind have an ecological impact leading also to economic and societal consequences as well. The goal of the present study was to follow the responses of the natural phytoplankton community to an oil spill from the early stages up to a few weeks after the oil release, called “short-term response” and “long-term response” hereafter, respectively. The results will provide valuable information on the dynamics of phytoplankton in response to the oil spill and contribute to a better understanding of the ecological aspects of oil pollution in coastal marine ecosystems. Materials and Methods Sampling Sampling was carried out at one station (maximum depth 7 m) near the northern mouth of the Channel of Bizerte affected by the oil spill (Fig. 1 ) on 5, 8, 12 and 22 October 2018. These dates corresponded to 1, 4, 8 and 18 days after the oil leak, respectively. The wind was blowing strongly (24–60 km h − 1 ) during the oil incident, with a dominant easterly direction (Weather Spark 2018 ) propitious to a rapid dispersal of the oil slick towards the coast of the City of Bizerte and the Channel of Bizerte, where the sampling station was located. Each day (D01, D04, D08 and D18), three replicate water samples were collected with a plastic water sampler (Hydro-Bios) at three depths (0.5 m, 2.5 m and 5 m), filtered through a 200µm-mesh sieve and placed in a cooler until analyses within 2–3 h after sampling. Subsamples for nutrient determination (PO 4 3− NO 3 − , NO 2 − , NH 4 + and Si(OH) 4 ) were filtered through 0.2-µm sterile cellulose acetate filters and stored in microvials at -20°C. Nutrients were analysed following spectrophotometric methods (Parsons et al. 1984). Other samples were taken to analyse the phytoplankton community, i.e., biomass (expressed as Chl a ), abundance, and species composition. Water temperature and salinity were recorded in situ at each sampling depth with a microprocessor conductivity meter (LF 196), the pH was estimated using a pH meter (Accumet Basic AB15, Fisher Scientific), while water turbidity was measured with a turbidimeter (WTW, Turb 350 IR). Phytoplankton community analysis Subsamples for Chl a measurements were sequentially filtered through 10-µm, 2-µm and 0.2-µm pore-size polycarbonate filters to measure Chl a in three phytoplankton size fractions ( 10 µm). Concentrations were estimated after overnight dark extraction at 4°C in 90% acetone, using the standard spectrophotometric method (Parsons et al. 1984). Total Chl a was estimated as the sum of the Chl a concentrations in the three size fractions. The Chl a percentage in each size fraction was calculated as the Chl a concentration of each size fraction divided by the total Chl a concentration. Picophytoplankton (< 2 µm cells) was counted based on its autofluorescent pigments (MacIsaac and Stockner 1993 ). Subsamples were fixed with formaldehyde (2% final concentration) and placed in the dark at 4 o C for 10 min. They were filtered through black polycarbonate filters (Nucleopore, 0.22 µm) and laid over 0.45-mm nitrocellulose backing filters. The filters were mounted on slides using low-fluorescence immersion oil, and immediately stored at -20 o C. Picophytoplankton was counted under a CETI Topic-T epifluorescence microscope (100×Fluotarobjective), using blue and green excitation and counting at least 200 cells from 30 random squares. For phytoplankton count and identification (i.e. nano-sized cells: 2–10 µm; micro-sized cells: 10–200 µm), subsamples were fixed with acid Lugol’s solution (3% final concentration) and stored at 4°C in the dark. Prior to analysis, 50 mL of each subsample were settled for at least 24 h and analysed under an inverted microscope (100× oil immersion objective, CETI) (Utermöhl 1958 ). At least 500 cells were counted in each subsample. Hydrocarbon analysis PAHs – the most toxic oil components (Jiang et al. 2010 ) – were analysed 8 days after the oil spill. Seawater samples were collected manually approximately 0.5m below the surface using pre-cleaned and sterile glass bottles. Sediment were sampled using a Van Veen grab (Hydrobios). Analysis of PAHs in water and sediment were performed according to the technique proposed by UNEP/FAO/IAEA/IOC.1996. Appropriate blanks were analyzed with each set of analyses, internal standards and in addition reference material (IAEA 408) with certified concentrations of hydrocarbons was analyzed for quality control purposes. Recoveries ranged from 72–89% for 226 IAEA 408 and the method detection limits ranged from 0.05 to 0.25 ng g − 1 for PAH. Further quality control was assured through participation in the hydrocarbons intercomparison exercises of IAEA (International Atomic Energy Agency). Quantification was performed by calculation of response factors of individual AH and PAH external standards. Data analyses One-way analysis of variance (ANOVA) was performed to test the significance of the variation in physicochemical and phytoplanktonic variables over time. The normality of data distribution and the homogeneity of variance were tested using Shapiro-Wilk’s test and Levene's test, respectively. A principal component analysis (PCA) was applied on the environmental variables to assess variability over time and the relevant factors responsible for the differences. Spearman’s correlations were calculated to test for a linear relationship between phytoplankton parameters (Chl a concentration and phytoplankton abundance) and physicochemical factors. The ANOVA, PCA and correlation analyses were performed using XLSAT program (XLSTAT 2022 Trial version). Phytoplankton diversity indices (species richness, S; Shannon-Wiener’s diversity index, H’; evenness, J) were calculated for the phytoplankton community sampled each day. A multidimensional scaling ordination (MDS) was performed on phytoplankton species abundances to detect changes in the phytoplankton community composition over time. A Euclidean distance dissimilarity analysis was used to determine the dispersal between communities at different sampling times. The diversity index and MDS analyses were performed using PRIMER program (PRIMER 6). Results Hydrocarbon contamination Visual observation showed the presence of oil on the top layer of the sampling station (foam and oil aggregates) on D01 (Fig. 1 ), D04 and D08. At the end of sampling (D18), the water at the station had regained its pre-incident colour and smell. Eight days after the oil leak, the station contained toxic oil hydrocarbons, with ∼130 ng PAHs L − 1 measured in seawater and high concentrations in sediment (ΣPAHs: 1222 ng g − 1 dry sediment). Chrysene was the main hydrocarbon in seawater (89 ng L − 1 ) and sediment (189 ng g − 1 dry sediment), followed by naphthalene, phenanthrene and fluoranthene. Benzo(b)fluoranthene, benzo(k)fluoranthene and pyrene were only detected in sediment (Table 1 ). Table 1 Concentrations of the main PAHs detected in the seawater and the sediment of the sampling station (Channel of Bizerte) 8 days after the oil spill incident. PAH compound Water solubility (mg L − 1 )** Water (ng L − 1 ) Sediment (ng g − 1 dry sediment) Naphthalene 31.0 18.9 33.17 Acenaphthene 3.9 nd nd Fluorene 1.69 nd nd Phenanthrene 1.15 13.59 43.26 Anthracene 0.43 nd nd Fluoranthene 0.26 7.38 151.52 Pyrene 0.13 nd 144.44 Chrysene* 0.002 87.88 188.85 Benzo(b)fluoranthene* 0.0015 nd 32.15 Benzo(k)fluoranthene* 0.0008 nd 40.27 Benzo(a)pyrene* 0.0016 nd nd nd: non detected *: Considered probable human carcinogens by the US EPA, the European Union, and/or the International Agency for Research on Cancer (IARC) (EFSA, 2008) **: water solubility values are reported from the literature (Ben Othman et al. 2023 ) Environmental data The sampling station had a shallow ( 0.05, N = 12), and the data are presented as depth-averaged values (Table 2 ). Table 2 Environmental factors recorded 1, 4, 8 and 18 days after the oil spill (Depth-averaged values ± SD, N = 12). Sampling day after the oil spill incident D01 D04 D08 D18 Temperature (°C) 22.00 ± 0.45 24.37 ± 0.31 24.57 ± 0.25 23.27 ± 0.31 Salinity (PSU) 37.20 ± 0.02 37.33 ± 0.05 37.47 ± 0.05 37.30 ± 0.1 pH 8.20 ± 0.10 8.27 ± 0.12 8.26 ± 0.15 8.83 ± 0.11 Turbidity (NTU) 4.22 ± 0.04 3.64 ± 0.04 3.28 ± 0.08 2.27 ± 0.08 NO 2 − (µM) 0.19 ± 0.02 0.12 ± 0.03 0.10 ± 0.01 0.09 ± 0.02 NO 3 − (µM) 0.98 ± 0.02 0.24 ± 0.01 0.35 ± 0.03 0.18 ± 0.01 NH 4 + (µM) 59.59 ± 5.00 33.12 ± 6.23 33.12 ± 6.00 27.43 ± 4.89 PO 4 3− (µM) 0.76 ± 0.04 0.67 ± 0.04 0.47 ± 0.04 0.36 ± 0.03 Si(OH) 4 (µM) 8.41 ± 1.25 5.75 ± 1.31 5.42 ± 1.30 3.30 ± 1.18 Total Chl a (µg L − 1 ) 3.01 ± 0.79 3.24 ± 0.41 2.48 ± 0.09 6.61 ± 1.21 Water temperature (22.6-24.57°C), salinity (37.2-37.47) and pH (8.2–8.83) varied little over time, while nutrient and Chl a concentrations as well as water turbidity varied significantly (ANOVA, p < 0.05, N = 12). The temporal variability of environmental data was confirmed by the PCA, whose axes 1 and 2 explained 65.1% and 26.1% of total variation, respectively. Axis 1 was positively correlated with all inorganic nutrients (r = 0.793–0.957, p < 0.01, N = 12) and water turbidity (r = 0.957, p < 0.01, N = 12), but negatively correlated with the total Chl a concentration (r = -0.804, p < 0.01, N = 12). Axis 2 was positively correlated with temperature and salinity (r = 0.792–0.841, p < 0.01, N = 12). The sampling days were mainly discriminated on axis 1. The first day was characterised by the highest value of turbidity and dissolved nitrogen, phosphorous and Si(OH) 4 , while the highest total Chl a concentration was recorded on the last day, associated to the lowest turbidity and nutrient levels. A cluster including D04 and D08 was distinguished in the middle of the PCA plot and was depicted by intermediate environmental data between D01 and D18 (Table 2 , Fig. 2 ). Phytoplankton size-fractioned biomass and abundance The Chl a concentrations of the three size fractions showed different responses over time after the oil spill (Fig. 3 a). In the pico-sized fraction (< 2 µm), Chl a was very low on D01 (< 0.2 µg L − 1 ), increased by 4-5-fold on D04 and D08, and strongly increased on D18 (6fold relative to D08). Conversely, Chl a decreased gradually from D01 to D08 in nano- and microphytoplankton (from 0.93 to 0.53 µg L − 1 and from 1.84 to 1.37 µg L − 1 , respectively). However, the biomass of both size fractions significantly increased on D18 (2-fold relative to D08) (ANOVA, p < 0.01, N = 12). The size structure of Chl a biomass distinctly varied over time. Picophytoplankton, which formed only 7% of total Chl a on D01, contributed 32% on D04 and D08, and dominated the biomass (∼60%) on D18. On D01, the abundance of picophytoplankton amounted to 11 x 10 5 cells L − 1 , versus 0.91 and 1.7 x 10 5 cells L − 1 for nano- and microphytoplankton, respectively. The evolution of the abundances of the three size fractions was almost similar to that of size-fractioned Chl a (Fig. 3 b). The abundance of nano- and microphytoplankton significantly decreased in the shortterm (from D01 to D08), while the abundance of picophytoplankton increased. In the long-term (on D18), all size fractions bloomed: the cell concentrations reached 3 x 10 7 cells L − 1 for picophytoplankton and 2.5 and 4 x 10 5 cells L − 1 for nano- and microphytoplankton, respectively (ANOVA, p < 0.01, N = 12). The abundances and Chl a concentrations of the nano- and micro-sized fractions were negatively correlated with nitrogen nutrients (r s = -0.56 – -0.64, p < 0.05), phosphorous (r s = - 0.80 – - 0.95, p < 0.01) and silicates (r s = - 0.75 – - 0.86, p < 0.01), while the abundance and biomass of picophytoplankton were not correlated with any nutrient. Phytoplankton community composition Throughout the sampling period, microphytoplankton was dominated by diatoms (98–99%), but its composition changed over days following the oil spill. Centric diatoms formed 34% of microphytoplankton on D01, but their contribution decreased until D08, when pennate diatoms formed almost all micro-sized cells (91% of microphytoplankton abundance). Centric diatoms became an important component again (40%) on D18 (Fig. 4 a). Furthermore, the species composition of each diatom group changed remarkably over time. The pennate diatom community on D01 was mainly represented by Pseudo-nitzschi a (42%) and Nitzschia (25%) species, and Asterionellopsis glacialis and Thalassionema spp to a lesser extent (∼ 10% each). Nitzschia and Pseudo-nitzschia species remained important taxa on D04, and the Nitzschia genus was dominant on D08 (82%). In contrast, A. glacialis bloomed on D18 (2 10 5 cells L − 1 ) and largely dominated the community (87%) (Fig. 4 b). The abundance of this species was negatively correlated with the N and Si nutrient concentrations (r s = -0.643 – -0.699, p < 0.05). For centric diatoms, Leptocylindrus and Dactyliosolen formed 66% and 24% of the community on D01, respectively. Then, Leptocylindrus grew more and more abundant until they formed almost the entire centric group on D18 (96%) (Fig. 4 c). The community composition of nanophytoplankton also changed over time (Fig. 5 ). From D01 to D08, the community was dominated by phytoflagellates (86–92% of nanophytoplankton abundance) – mainly Cryptophyceae, mostly represented by H. fusiformis and H. marina. Chrysophyceae (mainly Micromonas pusilla ) and Prymnesiophyceae (mainly Imantonia rotunda ) had a relatively high contribution on D01 (12–20%), but decreased to only 1–5% of nanophytoplankton on D08. The 2–10 µm diatoms, represented by centric Chaetoceros species, only represented 8–13% of nanophytoplankton from D01 to D08. On D18, these species bloomed (1.3 10 5 cells L − 1 ) and co-dominated the nanophytoplankton community (52%) along with phytoflagellates. MDS analysis The changes in nanophytoplankton (Fig. 6 a) and microphytoplankton (Fig. 6 b) communities following the oil spill were confirmed by the NMDS analysis. Three clusters were observed for each community. The first cluster grouped all D01 replicates, the second was represented by all D04 and D08 replicates, and the last one was composed of the D18 replicates. Moreover, the dissimilarity of communities was low between D04 and D08 (41–44%), but high between D01, D04/D08 and D18 (Table S1 ). Diversity indexes Oil pollution had a marked effect on all diversity indexes 18 days after the incident. The species richness index (S) marked a significant decrease on D18 relatively to the other days (ANOVA, p < 0.01, N = 12) (Fig. 7 a). The Shannon-Wiener index (H’: commonly called the Shannon diversity Index, a way to measure the diversity of species in a community) and the evenness (J: a measure of the relative abundances of a specie within a community) recorded on D01 and D04 were not significantly different, decreased on D08 and were lowest on D18 (ANOVA, p < 0.01, N = 12) (Fig. 7 b, c). Discussion Several oil spills have occurred in different marine ecosystems around the world in the last 30 years (Varela et al. 2006 ; Soto et al. 2014 ; Duda and Wawruch 2017 ; Tang et al. 2019 ). Assessing the effects of these accidents on marine phytoplankton is crucial, considering its basic status in marine food webs and its determining role in material and energy fluxes. Reports on in situ phytoplankton community changes at the early stages of an oil spill and throughout its evolution are rare, even if abundant data from experiments with single species or natural communities are available (Varela et al. 2006 ; González et al. 2009 ; Bretherton et al. 2019a , 2020 ; Putzeys et al. 2022 ). Microbial communities are rapidly altered after an oil spill incident (Gemmell et al. 2018 ), so that early monitoring is efficient when in-situ responses to oil pollution are targeted. Therefore, to improve knowledge on the effects of oil spills, it is important to consider rapid and longer responses of in situ phytoplankton following an oil leak. This work presents first field data on the responses of a coastal phytoplankton community to an oil spill from the early stage (the first days) up to a few weeks in the south-western Mediterranean Sea. The oil leak site was located in the Bay of Bizerte, while the sampling station was located in the Channel of Bizerte (Fig. 1 ). The wind direction and speed moved the oil slick towards the Bizerte City coast and to the Channel. This was reflected by the presence of PAHs in the sampling station 8 days after the spill. Referring to the WHO 1997 standard (700 ng L − 1 ), seawater was moderately contaminated (ΣPAHs ≈130 ng L − 1 ). Some of the measured PAHs (chrysene, fluoranthene, naphthalene, phenanthrene) could have a toxic effect on phytoplankton even at low concentrations (Echeveste et al. 2010a , 2010b ; Ben Othman et al. 2017 ). The PAH water concentrations measured on D08 had certainly been diluted. Therefore, higher levels would have been measured on D01 and D04 if sampled, and phytoplankton was most probably exposed to higher concentrations on D01 and D04 than those measured on D08. PAH levels were much higher in sediment (ΣPAHs = 1222 ng g − 1 dry sediment, Table 1 ) than in seawater. As a result of their hydrophobic nature, PAHs are known to be sequestered within sediment (Mille et al. 2007 ; Bradshaw et al. 2012 ), where it could be degraded partially by bacteria (Acosta-Gonzàlez et al. 2015). Historical data showed that the sediment of Bizerte Channel had been exposed to PAH contamination, but at levels much lower than those recorded after this oil spill (394.1 ng g − 1 dry sediment, Barhoumi et al. 2014 ). Impact of oil on the growth of size-fractioned phytoplankton Phytoplankton can respond rapidly to oil pollution and to the most toxic components of oil – PAHs (Ohwada et al. 2003 ; González et al. 2009 ; Gemmell et al. 2018 ). Our results also showed that phytoplankton displayed significant changes in biomass and abundance following the oil spill. However, the three size fractions exhibited different responses, confirming that cell size is important in determining the reaction of phytoplankton to oil and PAH pollution (Echeveste et al. 2010a , 2010b ; Ben Othman et al. 2012 ; Bretherthon et al. 2020). Moreover, the observed changes in biomass and abundance varied over time after the oil spill. The biomasses and abundances of nano- and micro-phytoplankton significantly decreased on D04 and D08 relatively to D01 (Fig. 3 a, b). Short-term negative effects of oil and PAHs on large phytoplankton have been reported, and their toxicity on the photosynthetic activity, growth and biomass of phytoplankton is well documented (Djomo et al. 2004 ; González et al. 2009 ; Paul et al. 2013 ; Ben Othman et al. 2018 ). PAHs can alter photosystem II functioning and reduce the fluorescence yield in several marine phytoplankton species (Aksmann and Tukaj 2008 ; Ben Othman et al. 2023 ). In addition to the toxicity of petroleum hydrocarbons, the presence of an oil slick on the water surface during the first week of sampling (Fig. 1 ) reduced light penetration and indirectly inhibited phytoplankton growth. Conversely, nearly three weeks after the oil spill (D18), a positive effect was observed on large phytoplankton (> 2 µm), which bloomed and reached high concentrations (2.5-4 10 5 cells L − 1 , Fig. 3 a, b). Our results are in agreement with previous studies reporting a reduced phytoplankton concentration in the short term, but phytoplankton outbreaks (particularly for large species such as diatoms) in the long term (Taş et al. 2011 ; Sheng et al. 2011 ; Pan et al. 2012 ; Ozhan et al. 2014 ). On D18, the oil in the sampled station had been easily dispersed by the hydrological conditions encountered in mid-autumn (wind, water mass movements), and its negative effect on phytoplankton was ultimately reduced. Therefore, the regrowth of nano- and microphytoplankton on D18 could be mainly due to the return of a long-term favourable situation in the station, particularly light conditions. D18 was indeed characterised by the lowest turbidity (Table 2 , Fig. 2 ) and by seawater that recovered the same colour and smell as before the incident. D18 also coincided with the lowest nutrient concentrations (Table 2 , Fig. 2 ), which may reflect their absorption during phytoplankton regrowth. Moreover, nano- and microphytoplankton biomasses and abundances were negatively correlated with all nutrients. Ben Othman et al. ( 2018 ) have shown that resumption of phytoplankton growth under PAH contamination coincided with significant change in community composition. Smaller phytoplankton species are traditionally reported to be more sensitive than large ones to pollutants like oil compounds because of their higher surface-to-volume ratio (Echeveste et al. 2011 ; Ben Othman et al. 2012 ), and significant decreases in their abundance and growth are generally reported after PAH exposure (Kottuparambil and Augusti 2018; Ashok et Augusti 2022). On the contrary, the biomass and abundance of picophytoplankton was stimulated after the oil pollution event of Bizerte, even when an oil film covered the surface water of the station (on D04 and D08, Fig. 3 ). Our results are in agreement with other studies showing proliferation of small phytoplankton after an oil spill incident (González et al. 2009 ; Huang et al. 2011 ; Kottuparambil et al. 2023 ). Quigg et al ( 2021 ) argued that the dominance of small phytoplankton following an oil spill is related to their higher growth rate than that of large cells. However, the increase of picophytoplankton could result from the release from grazing by sensitive grazers like heterotrophic nanoflagellates (Johansson et al. 1980 ; Almeda et al. 2018 ; Gemmell et al. 2018 ). Additionally, correlations between picophytoplankton and abiotic factors (nutrients) were absent, suggesting that pico-sized biomass may be more controlled by biotic factors such as zooplankton grazing. Concomitantly with our work, Chkili et al. (submitted) investigated the protozooplanktonic community and its grazing rate, and reported a net decrease in grazing mortality rate of picophytoplankton starting from D08, with the absence of their potential heterotrophic nanoflagellate grazers. The different responses of small and large phytoplankton to the oil spill were followed by a shift in the phytoplankton size structure from dominant micro-sized cells on D01 (61% of Chl a ) to pico-sized cells on D18 (∼60% of Chl a ). This change could influence the grazer community and ultimately the food web structure. Impact of oil on the phytoplankton community composition The oil spill had a clear effect on the community composition of nano- and microphytoplankton, which changed differentially in the short and long terms (Figs. 4 , 5 , 6 ). Short-term impact . In the short term, the compositions of the two communities showed high dissimilarity on D01 relative to D04 and D08 (Table S1 ). During this short period, the presence of petroleum slick in the station (Fig. 1 ) was accompanied by a decrease in the abundance and biomass of nano- and micro-sized cells, but some species maintained their growth. This indicates a growth inhibition of sensitive species and a possible selection of pollutant-tolerant species following the oil spill in the short term. As regards microphytoplankton, diatoms were the main species on D01 and remained dominant on D04 and D08 despite the presence of oil in the station. The ability of diatoms to resist oil spills is documented. The presence of the silica frustule can protect them from the lethal effect of oil and confer them a better chance to survive than the naked phytoplankton cells do (Ikavalko 2005; Varela et al. 2006 ; Hallare et al. 2011 ; Ozhan et al. 2014 ; Parsons et al. 2015 ). Genes involved in the formation of the silica shell of diatoms (e.g., sil3) are downregulated after exposure to PAH mixtures (Bopp and Lettieri 2007 ). However, other researchers showed that diatoms are more affected by oil than phytoflagellates and dinoflagellates (Mishamandani et al. 2015; Taş et al. 2011 ; Fiori et al. 2016 ), and the response of coastal diatoms to oil is clearly size-dependent. Small diatoms ( 20 µm) are negatively affected by high oil concentrations (González et al. 2009 ). Furthermore, when Bretherton et al. ( 2020 ) assessed the role of different physiological traits in the response of various phytoplankton taxa to oil, cell size was most important in determining the biomass response to oil. In our study, the abundance of centric diatoms decreased from D01 to D08, dominated by small (mean length/width ratio 35 µm / 3 µm) Leptocylindrus species (Fig. 4 c), at the expense of pennate diatoms whose contribution increased gradually to form almost all microphytoplankton on D08 (∼90%; Fig. 4 a). Large Pseudo-nitzschia and Nitzschia species (length/width ratio ranges 45–108 µm / 3–13 µm) were the main taxa on D01 and D04, and Nitzschia spp. formed 91% of pennate diatoms on D08 (Fig. 4 b). Our results are in line with those of Bretherton et al. ( 2019a ) showing the dominance of the Pseudo-nitzschia genus after 3 days of oil exposure. The tolerance of pennate diatoms to toxic petroleum products may be explained genetically, since they are known to be more tolerant than other diatoms to oil compounds (Ozhan and Bargu 2014 ; Bretherton et al. 2019b ). Furthermore, Melliti Ben Garali et al. ( 2021 ) provided the first evidence that two Pseudo-nitzschia species isolated from the Channel and Lagoon of Bizerte could tolerate a 15-PAH mixture by enhancing their biovolume, and were even able to bioconcentrate PAHs and degrade them, probably in synergy with their associated bacteria. Phytoplankton (including diatoms) can release extracellular polymeric substances (EPS) during environmental stress, e.g., oil exposure (Sun et al. 2018 ; Kamalanathan et al. 2019 ). The bacteria associated to phytoplankton can influence EPS production, and phytoplankton can in turn alter the bacterial community (Kamalanathan et al. 2019 ). Therefore, the phytoplankton-bacteria association can undoubtedly play an important role in phytoplankton resistance to oil. A benthic diatom and its associated bacteria isolated from a station close to Bizerte Channel have been found efficient in removing benzo(a)pyrene and fluoranthene (Kahla et al. 2021 ). All these findings clearly suggest that Nitzschia and Pseudo-nitzschia species from Bizerte, where previous PAH contamination has been reported (Lafabrie et al. 2013 ; Bancon-Montigny et al. 2019 ), have developed tolerance to PAHs through adaptation mechanisms that make them physiologically able to resist oil pollution. The trophic mode might also influence the sensitivity of phytoplankton to contaminants, including oil compounds. Conversely to autotrophic species, mixotrophic or heterotrophic diatoms can rely on sources of organic carbon to grow and to decrease their dependence on photosynthesis, so that they can better withstand contaminant toxicity (Debenest et al. 2009 ; Larras et al. 2012 ; Brethertron et al. 2021). Interestingly, heterotrophy has been reported for some Peudo-nitzschia species (Mengelt and Prezelin 2005; Loureiro et al. 2009 ), including species from our study site (Melliti Ben Garali et al. 2016 ). Our results suggest that diatoms are resistant to hydrocarbons and that certain species – e.g., members of the Pseudo-nitzschia and Nitzschia genera – may grow under oil contamination conditions. This is of particular interest given the fact that several species within these genera are known to produce the neurotoxin domoïc acid, including strains from the Bizerte waters (Bouchouicha Smida et al. 2014a ; Sakka Halili et al. 2016 ). Blooms of Pseudo-nitzschia and Nitzschia are a known fact in the Lagoon and Channel of Bizerte (Sahraoui et al. 2012 ; Bouchouicha Smida et al. 2014b ; Melliti Ben Garali et al. 2020 ). Oil hydrocarbon pollution can promote the growth of these diatoms and could increase the frequency of toxic blooms in these coastal waters, which are chronically prone to this kind of pollution. As regards nanophytoplankton, cryptophyceae (dominated by H. fusiformis and H. marina) were the main taxa from D01 to D08 (Fig. 5 ). This is not in agreement with the observation of Brussaard et al. ( 2016 ), who reported the disappearance of this phytoplankton group after short-term exposure to oil. The major short-term change within nanophytoplankton observed in our study was the decrease of chrysophyceae (mainly M. pusilla ) and prymnesiophyceae (mainly Imantonia rotunda ) (Fig. 5 ). M. pusilla has been found sensitive to oil (Bretherton et al. 2020 ), or not (Brussaard et al. 2016 ), and a beneficial effect of oil exposure on chrysophyceae has even been found (Finkel et al. 2020 ). However, prymnesiophyceae can be a dominant group after an oil spill (Brussaard et al. 2016 ). In fact, the sensitivity of phytoplankton to oil is largely species dependent, since toxic oil compounds can affect different cellular and molecular targets (Ozhan et al, 2014 ; Kamalanathan et al. 2021 , 2022 ). Furthermore, species can have differential core metabolism plasticity to counteract oil-induced oxidative stress and can modulate their tolerance to oil exposure (Kamalanathan et al. 2021 , 2022 ). Long-term impact. The community compositions of micro- and nanophytoplankton on D18 greatly differed from those of the other days (Table S1 , Figs. 4 , 5 , 6 ). On D18, the wide regrowth of both size fractions (Fig. 3 ) coincided with significant changes in the community composition, as speculated. Centric diatoms (microphytoplankton) were more abundant after 18 days and formed ∼40% of the community, although the community structure did not change that much since Leptocylindrus spp. remained the dominant taxon (Fig. 4 c). Centric diatoms have been reported to be faster growing species than pennate diatoms after a long post-spill period (Verlecar et al. 2006 ; Hallare et al. 2011 ). In the present study, pennate diatoms remained an important component of microphytoplankton, but the community changed deeply: A. glacialis had a low contribution from D01 to D08 (8–11%), but proliferated (2 10 5 cells L − 1 ) and became dominant on D18 (87%) (Fig. 4 b). Gallo et al. (2016) reported a dominance of A. glacialis under increased levels of CO 2 in seawater, while Sahu et al. ( 2022 ) found that its development can be supported by salinity and a high nitrogen concentration. The return of favourable environmental factors in our study site in the longer term may be responsible for A. glacialis development. The species abundance was negatively correlated with the N and Si concentrations, indicating their utilization during the A. glacialis increase. As regards nanophytoplankton, the Chaetoceros spp. bloom (1.3 10 5 cells L − 1 ) was the most significant change observed after 18 days (Fig. 5 ). The growth of these red tide organisms was recently found stimulated after 10 and 14 days of oil exposure (Lv et al. 2023 ). Nutrients – phosphorous in particular – are considered the main regulating factors of Chaetoceros species growth (Shevchenko et al. 2006 ; Silkin et al. 2011 ). During our study, phosphorous seemed to support the proliferation of Chaetoceros spp., since the abundance of these organisms was negatively correlated with P concentrations (rs = -0.699, P < 0.05). Species succession after an oil spill might also be related to different sensitivity levels to hydrocarbons (Sargian et al. 2007 ; Huang et al. 2011 ; Hemmer et al. 2011 ). Dominant species after several days of oil exposure can be considered more sensitive than species growing in the presence of high amounts of oil. In our study, A. glacialis and Chaetoceros spp, which can be sensitive to oil pollutants, dominated on D18 and took the place of Nitzschia and Pseudonitzschia species, which can resist to hydrocarbons as discussed above. Another reason might be that A. glacialis and Chaetoceros spp could outcompete and eliminate other species via allelopathic mechanisms, and become more competitive for resources (nutrients, light) and hence grow better. Allelopathy plays a significant role in the dominance, succession, and formation of natural diatom communities (Leflaive and Ten Hage, 2009 ; Zhang et al. 2019). Additionally, the difference in the diatom community composition after long-term oil pollution could be partially due to indirect trophic interactions because herbivorous zooplankton is sensitive to oil compounds (Hjorth et al. 2007 ; González et al. 2009 ; Almeda et al. 2014 ; Van Dinh et al. 2019 ). For one reason or another, our results clearly show that the oil spill was followed by a profound change in the phytoplankton community composition after 18 days. This modification was accompanied by significantly lower diversity indexes (S, H’ and J, Fig. 7 ), which reinforces the fact that oil spillage has deep effects on the structure of primary producers. Huang et al. (2010) also observed a drop in biodiversity and in the number and evenness of phytoplankton species after 15 days of crude oil exposure during different seasons. Conclusion This study highlights the importance of phytoplankton sampling at different stages of an oil spill because it displays various responses throughout the evolution of an oil incident. The size structure and species composition of phytoplankton observed in the days following initial oil exposure were quite different from those in the longer term. Picophytoplankton proliferated, possibly thanks to decreased grazing due to oil poisoning of its potential consumers like heterotrophic nanoflagellates. In contrast, large phytoplankton decreased in the short term and bloomed after 18 days. The dominance of pennate diatoms of the genera Pseudo-nitschia and Nitzschia in the presence of the oil slick could be related to the high tolerance of these species to oil hydrocarbon components. This re-confirms previous observations in the study area that hydrocarbon pollution could increase the likelihood of blooms of toxic diatoms. Our results demonstrate that even small oil spills may have short- and long-term effects on phytoplankton, and their recurrent nature in coastal waters may affect ecosystem functioning. Further research is needed to investigate the chronic impact of oil on coastal ecosystems. Declarations Statements and Declarations Competing Interests The authors have no competing interests to declare that are relevant to the content of this article. Financial/ non-financial interests The authors have no relevant financial or non-financial interests to disclose. Ethical Approval Not applicable Consent to Participate Not applicable Consent to Publish The authors have given their consent to publish the manuscript. Author Contributions Boutheina Grami: Conceptualization, Investigation, Writing-original draft. Oumayma Chkili: Data collection and analysis, Editing. Sondes Melliti Ben Garali, Kaouther Mejri Kousri, Marouen Meddeb: Material preparation, Methodology, data collection, Editing. Lassad Chouba: Editing, HAP analysis. Nathalie Niquil: review and editing. Asma Sakka Hlaili: Project Conceptualization, Supervision, Review-writing. As supervisors of this work the final authorship positions were awarded to Sakka Hlaili A. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Data availability statement Collected in situ data, photos and analysis that support the findings of this study are not openly available but are available from the corresponding author upon reasonable request. References Acosta-González A, Martirani-von Abercron SM, Rosselló-Móra R, Wittich RM, Marqués S (2015) The effect of oil spills on the bacterial diversity and catabolic function in coastal sediments: a case study on the Prestige oil spill. 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Supplementary Files SupplementaryMaterialGramietal.docx Cite Share Download PDF Status: Published Journal Publication published 30 Jul, 2024 Read the published version in Aquatic Sciences → Version 1 posted Editorial decision: Revision requested 21 May, 2024 Reviews received at journal 12 May, 2024 Reviews received at journal 11 May, 2024 Reviewers agreed at journal 08 May, 2024 Reviewers agreed at journal 08 May, 2024 Reviewers agreed at journal 23 Mar, 2024 Reviewers agreed at journal 12 Mar, 2024 Reviewers agreed at journal 11 Mar, 2024 Reviewers invited by journal 11 Mar, 2024 Editor assigned by journal 08 Mar, 2024 Submission checks completed at journal 07 Mar, 2024 First submitted to journal 06 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4019976","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":277854363,"identity":"eb1048b6-fdb6-4de9-b831-b9838d830594","order_by":0,"name":"Boutheina Grami","email":"","orcid":"","institution":"Université de Monastir, Institut Supérieur de Biotechnologie de Monastir","correspondingAuthor":false,"prefix":"","firstName":"Boutheina","middleName":"","lastName":"Grami","suffix":""},{"id":277854366,"identity":"1d2f0a68-0191-465e-94e5-61ba5af5b1e9","order_by":1,"name":"Oumayma Chkili","email":"","orcid":"","institution":"Université de Carthage","correspondingAuthor":false,"prefix":"","firstName":"Oumayma","middleName":"","lastName":"Chkili","suffix":""},{"id":277854367,"identity":"9abe7dab-9186-46b0-a806-890d3e4ee4ed","order_by":2,"name":"Sondes Melliti Ben Garali","email":"","orcid":"","institution":"Université de Carthage","correspondingAuthor":false,"prefix":"","firstName":"Sondes","middleName":"Melliti Ben","lastName":"Garali","suffix":""},{"id":277854371,"identity":"2109714d-19fa-4c7a-8c84-c96ead8feee3","order_by":3,"name":"Kaouther Mejri Kousri","email":"","orcid":"","institution":"Université de Carthage","correspondingAuthor":false,"prefix":"","firstName":"Kaouther","middleName":"Mejri","lastName":"Kousri","suffix":""},{"id":277854375,"identity":"779a646e-a4e8-42b6-a689-36cc8638872f","order_by":4,"name":"Marouan Meddeb","email":"","orcid":"","institution":"Université de Carthage","correspondingAuthor":false,"prefix":"","firstName":"Marouan","middleName":"","lastName":"Meddeb","suffix":""},{"id":277854377,"identity":"d11e0058-c5b3-4dc0-87bd-94bd60ce0a9d","order_by":5,"name":"Lassaad Chouba","email":"","orcid":"","institution":"Institut National des Sciences et Technologies de la Mer","correspondingAuthor":false,"prefix":"","firstName":"Lassaad","middleName":"","lastName":"Chouba","suffix":""},{"id":277854379,"identity":"688fce8f-b2c6-4b99-8400-de8c134558ce","order_by":6,"name":"Nathalie Niquil","email":"","orcid":"","institution":"CNRS, Normandie Université, UNICAEN, UMR BOREA (MNHN, Sorbonne Universités, Université Caen Normandie, Université des Antilles)","correspondingAuthor":false,"prefix":"","firstName":"Nathalie","middleName":"","lastName":"Niquil","suffix":""},{"id":277854381,"identity":"42f036a9-e9c9-4239-bbe7-f81e1490203c","order_by":7,"name":"Asma Sakka Hlaili","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEUlEQVRIie2PsWqEQBCGRwKpPLYLIx76CiOCWEjyKkpaDVcGUtxVl+bCtYY8QpoDwXoPixRBbDekSXoDlhYWWe1C9Lh0B9mvm935+P8BUChOGELQNQ7k66wfw8VxCkgFdWPVK3S0AgjEh3l6lW1fowa6S9e4LzlvFzh3q+eo+SCw2QUfVVAkGWrra8/Ub8L9RhbzxFeGspjz+BSOx4jZDrXVWWBBTFwflHLXKyG9jyt2VWYtdMvAYjXtO6m4qXw5pBBPcoTzwjMxpqJPIfaQH0xxRJL70frFNdKairlUUMxyPyScvMWSxUTT3TlpFTufdRdcsW2ZvbW3gc3MifN7fn7hMOL0+m8Y/8u2QqFQ/AO+Af65Xjmz/LUnAAAAAElFTkSuQmCC","orcid":"","institution":"Université de Carthage","correspondingAuthor":true,"prefix":"","firstName":"Asma","middleName":"Sakka","lastName":"Hlaili","suffix":""}],"badges":[],"createdAt":"2024-03-06 08:19:52","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4019976/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4019976/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00027-024-01113-7","type":"published","date":"2024-07-30T15:57:38+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":52457663,"identity":"8ba0844c-0e9e-4c4d-a9c9-0f6175df7fcb","added_by":"auto","created_at":"2024-03-11 21:02:35","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":547449,"visible":true,"origin":"","legend":"\u003cp\u003eSite sampled during the oil spill in the Bay of Bizerte. Sampling stations in relation to the oil leak location and photographs of the polluted coasts of Sidi Salem beach (1: https://www.webdo.tn/2018/10/05/bizerte-7-tonnes-de-petrole-ont-fuite-dans-la-mer-de-zarzouna/) and of the Channel of Bizerte (2: https://directinfo.webmanagercenter.com/2018/10/10/tunisie-les-plages-polluees-par-une-vaste-couche-de-petrole-video/). White arrows, trajectory of oil dispersal.\u003c/p\u003e","description":"","filename":"FigsGramietal2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4019976/v1/6848d7f93dca0e7957104bdd.jpg"},{"id":52457659,"identity":"8b179691-b92e-42a5-b24f-ee7d8243b95d","added_by":"auto","created_at":"2024-03-11 21:02:35","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":290984,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal component analysis of environmental data and individual factors collected from D01 to D18 after the oil spill incident.\u003c/p\u003e","description":"","filename":"FigsGramietal3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4019976/v1/65ad05895bd15f1a7d813b84.jpg"},{"id":52457660,"identity":"78b1260c-382f-4caa-9701-ad593c55aa7a","added_by":"auto","created_at":"2024-03-11 21:02:35","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":183609,"visible":true,"origin":"","legend":"\u003cp\u003eEvolution of the biomass (a) and abundance (b) of three phytoplankton size fractions following the oil spill incident (depth-averaged values ± SD, N = 12).\u003c/p\u003e","description":"","filename":"FigsGramietal4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4019976/v1/b7b8912d36f36b81d5f768c6.jpg"},{"id":52457658,"identity":"8dbf69d8-a9ee-44cd-b446-eceedab7e41c","added_by":"auto","created_at":"2024-03-11 21:02:35","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":322108,"visible":true,"origin":"","legend":"\u003cp\u003eComposition of micro-sized diatoms (a), pennate diatoms (b) and centric diatoms (c) in the days following the oil spill.\u003c/p\u003e","description":"","filename":"FigsGramietal5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4019976/v1/1fd21db9cb8c009742940d5f.jpg"},{"id":52457661,"identity":"7db0392d-ee02-4778-b20d-090c8c577a17","added_by":"auto","created_at":"2024-03-11 21:02:35","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":233038,"visible":true,"origin":"","legend":"\u003cp\u003eComposition of nanophytoplankton in the days following the oil spill.\u003c/p\u003e","description":"","filename":"FigsGramietal6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4019976/v1/b005632d7dfb8f42fb7d89f4.jpg"},{"id":52457664,"identity":"62875433-14fa-49df-b282-a7875ad92440","added_by":"auto","created_at":"2024-03-11 21:02:35","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":259355,"visible":true,"origin":"","legend":"\u003cp\u003eNon-metric MDS ordination of nanophytoplankton (a) and microphytoplankton (b) species abundance, data collected from D01 to D18 after the oil spill incident.\u003c/p\u003e","description":"","filename":"FigsGramietal7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4019976/v1/ec9ba932bd87c9f30bd3cc8d.jpg"},{"id":52457732,"identity":"f83b7c01-2fe2-4fa4-94d3-99d803e2a6d8","added_by":"auto","created_at":"2024-03-11 21:10:35","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":147244,"visible":true,"origin":"","legend":"\u003cp\u003eEvolution of diversity indexes (a: species richness, S; b: Shannon-Wiener’s diversity index, H’; c: evenness, J) calculated for the \u0026gt; 2 µm phytoplankton community from D01 to D18 after the oil spill incident (means ± SD, N=12).\u003c/p\u003e","description":"","filename":"FigsGramietal8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4019976/v1/7a1fd95780c61484071c8a73.jpg"},{"id":61793935,"identity":"b33fd2e3-5a05-47fd-8648-0f18c6f62d4b","added_by":"auto","created_at":"2024-08-05 16:16:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2814526,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4019976/v1/6493c0c7-ed19-47f8-8715-6009cdd49434.pdf"},{"id":52457665,"identity":"ecd4d6c6-b7bf-4c82-8084-1e7e7df7cc5e","added_by":"auto","created_at":"2024-03-11 21:02:35","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":14186,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterialGramietal.docx","url":"https://assets-eu.researchsquare.com/files/rs-4019976/v1/bb101d2a5cab68c9202e0f22.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Field study on natural phytoplankton throughout “Bizerte City” oil spill on the south-western coast of the Mediterranean Sea","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOil spills are unintentional releases of petroleum oil or derived oils into the marine ecosystem (Li et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). They have serious environmental and socio-economic impacts on marine ecosystems (Nwipie et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Soares et al. \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and are a persistent threat to human health because of their impact on aquatic food resources (Wirtz and Liu \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Penela-Arenaz et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; El-Fadel et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Ar\u0026ugrave;jo et al. 2023). To understand the impact of oil pollution on marine environments, numerous studies have used phytoplankton because it represents the basis of marine ecosystem productivity and plays key roles in the nutrient and carbon cycles and as a biological carbon pump (Zehr and Kudela \u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Tr\u0026eacute;guer et al. \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Therefore, the effects of toxic oil compounds on these primary producers can be cascaded to higher trophic levels and impact the food web dynamics as well as the biogeochemical cycles of marine ecosystems. Furthermore, phytoplanktonic species can respond quickly to marine contamination and environmental conditions, and are considered as an indicator of anthropogenic pressure and water quality (Verlecar et al. \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Marshall et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Paches et al. \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Parsons et al. \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Song et al. \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMuch effort has been dedicated to studying the response of marine phytoplankton to different oil spills, such as the \u0026ldquo;Volgoneft-248\u0026rdquo; spill in the Sea of Marmara (1999), the \u0026ldquo;Prestige\u0026rdquo; spill along the Spanish coast (2002), the \u0026ldquo;Montara\u0026rdquo; spill in the Northwest Shelf of Australia (2009), the \u0026ldquo;Deepwater Horizon\u0026rdquo; spill in the Gulf of Mexico (2010) and the \u0026ldquo;Texas City Y\u0026rdquo; spill (2014) (Varela et al. \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Taş et al. \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Sheng et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Gonz\u0026aacute;lez et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Gemmell et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Bretherton et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019a\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Nevertheless, current knowledge on the effect of petroleum and its most toxic components \u0026ndash; polycyclic aromatic hydrocarbons (PAHs) (Jiang et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) \u0026ndash; on marine phytoplankton is still contradictory. After an oil spill, decreased phytoplankton photosynthesis can be observed as a direct response to the toxic impacts of petroleum compounds or as an indirect effect of less light penetrating into the water column caused by the presence of oil on the sea surface (Goutz et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e1984\u003c/span\u003e; Tomajka \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e1985\u003c/span\u003e; Gonz\u0026aacute;lez et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Paul et al. \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Different negative effects have been observed after oil exposure, such as reduced phytoplankton growth, DNA damage, and inhibition of photosystem II (Aksmann and Tukaj \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Deasi et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Bretherton et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019a\u003c/span\u003e). In contrast, other studies have reported a stimulation of phytoplankton growth (Gonz\u0026aacute;lez et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Taş et al. \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Bretherton et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019a\u003c/span\u003e). Ozhan et al. (\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), reported that crude oil at a low concentration (\u0026lt;\u0026thinsp;1 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) can stimulate phytoplankton growth, but inhibit it at higher concentrations (\u0026gt;\u0026thinsp;100 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). The response of phytoplankton to oil pollution may also vary when considering short- or long-term effects (Lee et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Tang et al. \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The phytoplankton community can also be impacted indirectly by such incidents \u003cem\u003evia\u003c/em\u003e the effects of oil on the zooplankton community (Gonz\u0026aacute;lez et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Almeda et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Van Dinh et al. \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The increase in phytoplankton biomass following an oil spill can be caused by a decrease in grazing due to PAH toxicity to zooplankton (Hjorth et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Van Dinh et al. \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Tang and Buskey \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eContrasting effects of oil spills on taxonomic groups have also been reported. A decline in diatom biomass and an increase in phytoflagellates have been observed after laboratory or \u003cem\u003ein situ\u003c/em\u003e oil exposure (Harrison et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1986\u003c/span\u003e; Mishamandani et al. 2015; Fiori et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), while an opposite impact has been reported in other cases (Gonz\u0026aacute;lez et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Gilde and Pinckney \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Parsons et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Diatoms better tolerated high oil concentrations according to Ozhan et al. (\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), but dinoflagellates better tolerated oil pollution according to Jung et al. (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), Taş et al. (\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) and Gemmell et al. (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). These results highlight that the response of marine phytoplankton to the hydrocarbon components of oil depends on several factors, e.g., the amount and type of oil and the sensitivity of taxonomic groups, since oil toxicity to phytoplankton is widely species dependent (Ozhan et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Oil exposure can be lethal for some species, but others can survive and grow at an unaffected or reduced rate. The oil-resisting ability of some phytoplankton species is related to the plasticity of their core metabolism, i.e., reduced extracellular carbohydrate secretion and enhanced flux through the Krebs cycle to conserve and increase energy production and counteract the oxidative stress caused by oil exposure (Kamalanathan et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Physiological traits such as cell size, motility and mixotrophy, are also important in determining the ability of species to survive oil exposure (Bretherton et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMost data on the responses of marine phytoplankton to oil spills have been collected from experimental approaches. These include single species cultures or natural communities in microcosms and mesocosms (Varela et al. \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Gonz\u0026aacute;lez et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Gemmell et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Bretherton et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019a\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Putzeys et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, field monitoring data from the early stages of an oil spill and throughout its evolution are rare because i) this requires heavy logistics, and ii) being on site and collecting samples rapidly is a challenge. Data on the early and late responses of natural phytoplankton following an oil spill are crucial to better understand how this event can affect marine communities.\u003c/p\u003e \u003cp\u003eAn oil spill incident occurred in the Bay of Bizerte (south-western Mediterranean Sea, northern Tunisia) on 4 October 2018 as a result of a crack in a tank of the Tunisian Company of Refining Industries. The government of Tunisia announced a leak of 7 tons of crude oil. The climatic and hydrodynamic features of the region extended the impact of the spill up to five km away from the source of the leak. The dykes/breakwaters built at the entrance of the Bizerte Channel reduce the sea current intensity, which prevented the oil spreading offshore. Therefore, the oil slick was directed towards the western coasts (Sidi Salem beach) and especially towards the Lagoon of Bizerte \u003cem\u003evia\u003c/em\u003e the Channel (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The Lagoon supports intense fisheries and is considered as the main shellfish farming site in Tunisia. Therefore, incidents of this kind have an ecological impact leading also to economic and societal consequences as well. The goal of the present study was to follow the responses of the natural phytoplankton community to an oil spill from the early stages up to a few weeks after the oil release, called \u0026ldquo;short-term response\u0026rdquo; and \u0026ldquo;long-term response\u0026rdquo; hereafter, respectively. The results will provide valuable information on the dynamics of phytoplankton in response to the oil spill and contribute to a better understanding of the ecological aspects of oil pollution in coastal marine ecosystems.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSampling\u003c/h2\u003e \u003cp\u003eSampling was carried out at one station (maximum depth 7 m) near the northern mouth of the Channel of Bizerte affected by the oil spill (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003e) on 5, 8, 12 and 22 October 2018. These dates corresponded to 1, 4, 8 and 18 days after the oil leak, respectively. The wind was blowing strongly (24\u0026ndash;60 km h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) during the oil incident, with a dominant easterly direction (Weather Spark \u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) propitious to a rapid dispersal of the oil slick towards the coast of the City of Bizerte and the Channel of Bizerte, where the sampling station was located. Each day (D01, D04, D08 and D18), three replicate water samples were collected with a plastic water sampler (Hydro-Bios) at three depths (0.5 m, 2.5 m and 5 m), filtered through a 200\u0026micro;m-mesh sieve and placed in a cooler until analyses within 2\u0026ndash;3 h after sampling. Subsamples for nutrient determination (PO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e3\u0026minus;\u003c/sup\u003e NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e, NO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e, NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e and Si(OH)\u003csub\u003e4\u003c/sub\u003e) were filtered through 0.2-\u0026micro;m sterile cellulose acetate filters and stored in microvials at -20\u0026deg;C. Nutrients were analysed following spectrophotometric methods (Parsons et al. 1984). Other samples were taken to analyse the phytoplankton community, i.e., biomass (expressed as Chl \u003cem\u003ea\u003c/em\u003e), abundance, and species composition. Water temperature and salinity were recorded \u003cem\u003ein situ\u003c/em\u003e at each sampling depth with a microprocessor conductivity meter (LF 196), the pH was estimated using a pH meter (Accumet Basic AB15, Fisher Scientific), while water turbidity was measured with a turbidimeter (WTW, Turb 350 IR).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003ePhytoplankton community analysis\u003c/h2\u003e \u003cp\u003eSubsamples for Chl \u003cem\u003ea\u003c/em\u003e measurements were sequentially filtered through 10-\u0026micro;m, 2-\u0026micro;m and 0.2-\u0026micro;m pore-size polycarbonate filters to measure Chl \u003cem\u003ea\u003c/em\u003e in three phytoplankton size fractions (\u0026lt;\u0026thinsp;2 \u0026micro;m, 2\u0026ndash;10 \u0026micro;m and \u0026gt;\u0026thinsp;10 \u0026micro;m). Concentrations were estimated after overnight dark extraction at 4\u0026deg;C in 90% acetone, using the standard spectrophotometric method (Parsons et al. 1984). Total Chl \u003cem\u003ea\u003c/em\u003e was estimated as the sum of the Chl \u003cem\u003ea\u003c/em\u003e concentrations in the three size fractions. The Chl \u003cem\u003ea\u003c/em\u003e percentage in each size fraction was calculated as the Chl \u003cem\u003ea\u003c/em\u003e concentration of each size fraction divided by the total Chl \u003cem\u003ea\u003c/em\u003e concentration.\u003c/p\u003e \u003cp\u003ePicophytoplankton (\u0026lt;\u0026thinsp;2 \u0026micro;m cells) was counted based on its autofluorescent pigments (MacIsaac and Stockner \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). Subsamples were fixed with formaldehyde (2% final concentration) and placed in the dark at 4 \u003csup\u003eo\u003c/sup\u003eC for 10 min. They were filtered through black polycarbonate filters (Nucleopore, 0.22 \u0026micro;m) and laid over 0.45-mm nitrocellulose backing filters. The filters were mounted on slides using low-fluorescence immersion oil, and immediately stored at -20 \u003csup\u003eo\u003c/sup\u003eC. Picophytoplankton was counted under a CETI Topic-T epifluorescence microscope (100\u0026times;Fluotarobjective), using blue and green excitation and counting at least 200 cells from 30 random squares.\u003c/p\u003e \u003cp\u003eFor phytoplankton count and identification (i.e. nano-sized cells: 2\u0026ndash;10 \u0026micro;m; micro-sized cells: 10\u0026ndash;200 \u0026micro;m), subsamples were fixed with acid Lugol\u0026rsquo;s solution (3% final concentration) and stored at 4\u0026deg;C in the dark. Prior to analysis, 50 mL of each subsample were settled for at least 24 h and analysed under an inverted microscope (100\u0026times; oil immersion objective, CETI) (Uterm\u0026ouml;hl \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e1958\u003c/span\u003e). At least 500 cells were counted in each subsample.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eHydrocarbon analysis\u003c/h2\u003e \u003cp\u003ePAHs \u0026ndash; the most toxic oil components (Jiang et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) \u0026ndash; were analysed 8 days after the oil spill. Seawater samples were collected manually approximately 0.5m below the surface using pre-cleaned and sterile glass bottles. Sediment were sampled using a Van Veen grab (Hydrobios). Analysis of PAHs in water and sediment were performed according to the technique proposed by UNEP/FAO/IAEA/IOC.1996. Appropriate blanks were analyzed with each set of analyses, internal standards and in addition reference material (IAEA 408) with certified concentrations of hydrocarbons was analyzed for quality control purposes.\u003c/p\u003e \u003cp\u003eRecoveries ranged from 72\u0026ndash;89% for 226 IAEA 408 and the method detection limits ranged from 0.05 to 0.25 ng g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for PAH. Further quality control was assured through participation in the hydrocarbons intercomparison exercises of IAEA (International Atomic Energy Agency). Quantification was performed by calculation of response factors of individual AH and PAH external standards.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eData analyses\u003c/h2\u003e \u003cp\u003eOne-way analysis of variance (ANOVA) was performed to test the significance of the variation in physicochemical and phytoplanktonic variables over time. The normality of data distribution and the homogeneity of variance were tested using Shapiro-Wilk\u0026rsquo;s test and Levene's test, respectively.\u003c/p\u003e \u003cp\u003eA principal component analysis (PCA) was applied on the environmental variables to assess variability over time and the relevant factors responsible for the differences. Spearman\u0026rsquo;s correlations were calculated to test for a linear relationship between phytoplankton parameters (Chl \u003cem\u003ea\u003c/em\u003e concentration and phytoplankton abundance) and physicochemical factors. The ANOVA, PCA and correlation analyses were performed using XLSAT program (XLSTAT 2022 Trial version).\u003c/p\u003e \u003cp\u003ePhytoplankton diversity indices (species richness, S; Shannon-Wiener\u0026rsquo;s diversity index, H\u0026rsquo;; evenness, J) were calculated for the phytoplankton community sampled each day. A multidimensional scaling ordination (MDS) was performed on phytoplankton species abundances to detect changes in the phytoplankton community composition over time. A Euclidean distance dissimilarity analysis was used to determine the dispersal between communities at different sampling times. The diversity index and MDS analyses were performed using PRIMER program (PRIMER 6).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eHydrocarbon contamination\u003c/h2\u003e \u003cp\u003eVisual observation showed the presence of oil on the top layer of the sampling station (foam and oil aggregates) on D01 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003e), D04 and D08. At the end of sampling (D18), the water at the station had regained its pre-incident colour and smell. Eight days after the oil leak, the station contained toxic oil hydrocarbons, with \u0026sim;130 ng PAHs L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e measured in seawater and high concentrations in sediment (ΣPAHs: 1222 ng g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e dry sediment). Chrysene was the main hydrocarbon in seawater (89 ng L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and sediment (189 ng g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e dry sediment), followed by naphthalene, phenanthrene and fluoranthene. Benzo(b)fluoranthene, benzo(k)fluoranthene and pyrene were only detected in sediment (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eConcentrations of the main PAHs detected in the seawater and the sediment of the sampling station (Channel of Bizerte) 8 days after the oil spill incident.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAH compound\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWater solubility\u003c/p\u003e \u003cp\u003e(mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)**\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWater\u003c/p\u003e \u003cp\u003e(ng L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSediment\u003c/p\u003e \u003cp\u003e(ng g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e dry sediment)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNaphthalene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcenaphthene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFluorene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhenanthrene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnthracene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFluoranthene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e151.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePyrene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e144.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChrysene*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e188.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBenzo(b)fluoranthene*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBenzo(k)fluoranthene*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBenzo(a)pyrene*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003end: non detected\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e*: Considered probable human carcinogens by the US EPA, the European Union, and/or the International Agency for Research on Cancer (IARC) (EFSA, 2008)\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e**: water solubility values are reported from the literature (Ben Othman et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eEnvironmental data\u003c/h2\u003e \u003cp\u003eThe sampling station had a shallow (\u0026lt;\u0026thinsp;7 m) well-mixed water column. Consequently, the environmental and phytoplankton showed no significant variations with depth (ANOVA p\u0026thinsp;\u0026gt;\u0026thinsp;0.05, N\u0026thinsp;=\u0026thinsp;12), and the data are presented as depth-averaged values (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEnvironmental factors recorded 1, 4, 8 and 18 days after the oil spill (Depth-averaged values\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, N\u0026thinsp;=\u0026thinsp;12).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSampling day after the oil spill incident\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD01\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eD04\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eD08\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eD18\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTemperature (\u0026deg;C)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e22.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e24.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e24.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e23.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSalinity (PSU)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e37.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e37.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e37.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e37.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e8.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e8.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e8.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e8.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTurbidity (NTU)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e4.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e3.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e2.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e (\u0026micro;M)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e (\u0026micro;M)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e (\u0026micro;M)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e59.59\u0026thinsp;\u0026plusmn;\u0026thinsp;5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e33.12\u0026thinsp;\u0026plusmn;\u0026thinsp;6.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e33.12\u0026thinsp;\u0026plusmn;\u0026thinsp;6.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e27.43\u0026thinsp;\u0026plusmn;\u0026thinsp;4.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e3\u0026minus;\u003c/sup\u003e (\u0026micro;M)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSi(OH)\u003csub\u003e4\u003c/sub\u003e (\u0026micro;M)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e8.41\u0026thinsp;\u0026plusmn;\u0026thinsp;1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e5.75\u0026thinsp;\u0026plusmn;\u0026thinsp;1.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e5.42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e3.30\u0026thinsp;\u0026plusmn;\u0026thinsp;1.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Chl \u003cem\u003ea\u003c/em\u003e (\u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e3.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e6.61\u0026thinsp;\u0026plusmn;\u0026thinsp;1.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWater temperature (22.6-24.57\u0026deg;C), salinity (37.2-37.47) and pH (8.2\u0026ndash;8.83) varied little over time, while nutrient and Chl \u003cem\u003ea\u003c/em\u003e concentrations as well as water turbidity varied significantly (ANOVA, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, N\u0026thinsp;=\u0026thinsp;12). The temporal variability of environmental data was confirmed by the PCA, whose axes 1 and 2 explained 65.1% and 26.1% of total variation, respectively. Axis 1 was positively correlated with all inorganic nutrients (r\u0026thinsp;=\u0026thinsp;0.793\u0026ndash;0.957, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, N\u0026thinsp;=\u0026thinsp;12) and water turbidity (r\u0026thinsp;=\u0026thinsp;0.957, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, N\u0026thinsp;=\u0026thinsp;12), but negatively correlated with the total Chl \u003cem\u003ea\u003c/em\u003e concentration (r = -0.804, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, N\u0026thinsp;=\u0026thinsp;12). Axis 2 was positively correlated with temperature and salinity (r\u0026thinsp;=\u0026thinsp;0.792\u0026ndash;0.841, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, N\u0026thinsp;=\u0026thinsp;12). The sampling days were mainly discriminated on axis 1. The first day was characterised by the highest value of turbidity and dissolved nitrogen, phosphorous and Si(OH)\u003csub\u003e4\u003c/sub\u003e, while the highest total Chl \u003cem\u003ea\u003c/em\u003e concentration was recorded on the last day, associated to the lowest turbidity and nutrient levels. A cluster including D04 and D08 was distinguished in the middle of the PCA plot and was depicted by intermediate environmental data between D01 and D18 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003ePhytoplankton size-fractioned biomass and abundance\u003c/h2\u003e \u003cp\u003eThe Chl \u003cem\u003ea\u003c/em\u003e concentrations of the three size fractions showed different responses over time after the oil spill (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). In the pico-sized fraction (\u0026lt;\u0026thinsp;2 \u0026micro;m), Chl \u003cem\u003ea\u003c/em\u003e was very low on D01 (\u0026lt;\u0026thinsp;0.2 \u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), increased by 4-5-fold on D04 and D08, and strongly increased on D18 (6fold relative to D08). Conversely, Chl \u003cem\u003ea\u003c/em\u003e decreased gradually from D01 to D08 in nano- and microphytoplankton (from 0.93 to 0.53 \u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and from 1.84 to 1.37 \u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, respectively). However, the biomass of both size fractions significantly increased on D18 (2-fold relative to D08) (ANOVA, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, N\u0026thinsp;=\u0026thinsp;12). The size structure of Chl \u003cem\u003ea\u003c/em\u003e biomass distinctly varied over time. Picophytoplankton, which formed only 7% of total Chl \u003cem\u003ea\u003c/em\u003e on D01, contributed 32% on D04 and D08, and dominated the biomass (\u0026sim;60%) on D18.\u003c/p\u003e \u003cp\u003eOn D01, the abundance of picophytoplankton amounted to 11 x 10\u003csup\u003e5\u003c/sup\u003e cells L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, \u003cem\u003eversus\u003c/em\u003e 0.91 and 1.7 x 10\u003csup\u003e5\u003c/sup\u003e cells L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for nano- and microphytoplankton, respectively. The evolution of the abundances of the three size fractions was almost similar to that of size-fractioned Chl \u003cem\u003ea\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). The abundance of nano- and microphytoplankton significantly decreased in the shortterm (from D01 to D08), while the abundance of picophytoplankton increased. In the long-term (on D18), all size fractions bloomed: the cell concentrations reached 3 x 10\u003csup\u003e7\u003c/sup\u003e cells L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for picophytoplankton and 2.5 and 4 x 10\u003csup\u003e5\u003c/sup\u003e cells L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for nano- and microphytoplankton, respectively (ANOVA, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, N\u0026thinsp;=\u0026thinsp;12). The abundances and Chl \u003cem\u003ea\u003c/em\u003e concentrations of the nano- and micro-sized fractions were negatively correlated with nitrogen nutrients (r\u003csub\u003es\u003c/sub\u003e = -0.56 \u0026ndash; -0.64, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), phosphorous (r\u003csub\u003es\u003c/sub\u003e = \u003cb\u003e-\u003c/b\u003e0.80 \u0026ndash; \u003cb\u003e-\u003c/b\u003e0.95, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and silicates (r\u003csub\u003es\u003c/sub\u003e = \u003cb\u003e-\u003c/b\u003e0.75 \u003cb\u003e\u0026ndash; -\u003c/b\u003e0.86, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), while the abundance and biomass of picophytoplankton were not correlated with any nutrient.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePhytoplankton community composition\u003c/h2\u003e \u003cp\u003eThroughout the sampling period, microphytoplankton was dominated by diatoms (98\u0026ndash;99%), but its composition changed over days following the oil spill. Centric diatoms formed 34% of microphytoplankton on D01, but their contribution decreased until D08, when pennate diatoms formed almost all micro-sized cells (91% of microphytoplankton abundance). Centric diatoms became an important component again (40%) on D18 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). Furthermore, the species composition of each diatom group changed remarkably over time. The pennate diatom community on D01 was mainly represented by \u003cem\u003ePseudo-nitzschi\u003c/em\u003ea (42%) and \u003cem\u003eNitzschia\u003c/em\u003e (25%) species, and \u003cem\u003eAsterionellopsis glacialis\u003c/em\u003e and \u003cem\u003eThalassionema\u003c/em\u003e spp to a lesser extent (\u0026sim; 10% each). \u003cem\u003eNitzschia\u003c/em\u003e and \u003cem\u003ePseudo-nitzschia\u003c/em\u003e species remained important taxa on D04, and the \u003cem\u003eNitzschia\u003c/em\u003e genus was dominant on D08 (82%). In contrast, \u003cem\u003eA. glacialis\u003c/em\u003e bloomed on D18 (2 10\u003csup\u003e5\u003c/sup\u003e cells L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and largely dominated the community (87%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). The abundance of this species was negatively correlated with the N and Si nutrient concentrations (r\u003csub\u003es\u003c/sub\u003e = -0.643 \u0026ndash; -0.699, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). For centric diatoms, \u003cem\u003eLeptocylindrus\u003c/em\u003e and \u003cem\u003eDactyliosolen\u003c/em\u003e formed 66% and 24% of the community on D01, respectively. Then, \u003cem\u003eLeptocylindrus\u003c/em\u003e grew more and more abundant until they formed almost the entire centric group on D18 (96%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003ec).\u003c/p\u003e \u003cp\u003eThe community composition of nanophytoplankton also changed over time (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e5\u003c/span\u003e). From D01 to D08, the community was dominated by phytoflagellates (86\u0026ndash;92% of nanophytoplankton abundance) \u0026ndash; mainly Cryptophyceae, mostly represented by \u003cem\u003eH. fusiformis\u003c/em\u003e and \u003cem\u003eH. marina.\u003c/em\u003e Chrysophyceae (mainly \u003cem\u003eMicromonas pusilla\u003c/em\u003e) and Prymnesiophyceae (mainly \u003cem\u003eImantonia rotunda\u003c/em\u003e) had a relatively high contribution on D01 (12\u0026ndash;20%), but decreased to only 1\u0026ndash;5% of nanophytoplankton on D08. The 2\u0026ndash;10 \u0026micro;m diatoms, represented by centric \u003cem\u003eChaetoceros\u003c/em\u003e species, only represented 8\u0026ndash;13% of nanophytoplankton from D01 to D08. On D18, these species bloomed (1.3 10\u003csup\u003e5\u003c/sup\u003e cells L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and co-dominated the nanophytoplankton community (52%) along with phytoflagellates.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eMDS analysis\u003c/h2\u003e \u003cp\u003eThe changes in nanophytoplankton (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e6\u003c/span\u003ea) and microphytoplankton (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e6\u003c/span\u003eb) communities following the oil spill were confirmed by the NMDS analysis. Three clusters were observed for each community. The first cluster grouped all D01 replicates, the second was represented by all D04 and D08 replicates, and the last one was composed of the D18 replicates. Moreover, the dissimilarity of communities was low between D04 and D08 (41\u0026ndash;44%), but high between D01, D04/D08 and D18 (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eDiversity indexes\u003c/h2\u003e \u003cp\u003eOil pollution had a marked effect on all diversity indexes 18 days after the incident. The species richness index (S) marked a significant decrease on D18 relatively to the other days (ANOVA, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, N\u0026thinsp;=\u0026thinsp;12) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e7\u003c/span\u003ea). The Shannon-Wiener index (H\u0026rsquo;: commonly called the Shannon diversity Index, a way to measure the diversity of species in a community) and the evenness (J: a measure of the relative abundances of a specie within a community) recorded on D01 and D04 were not significantly different, decreased on D08 and were lowest on D18 (ANOVA, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, N\u0026thinsp;=\u0026thinsp;12) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e7\u003c/span\u003eb, c).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eSeveral oil spills have occurred in different marine ecosystems around the world in the last 30 years (Varela et al. \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Soto et al. \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Duda and Wawruch \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Tang et al. \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Assessing the effects of these accidents on marine phytoplankton is crucial, considering its basic status in marine food webs and its determining role in material and energy fluxes. Reports on \u003cem\u003ein situ\u003c/em\u003e phytoplankton community changes at the early stages of an oil spill and throughout its evolution are rare, even if abundant data from experiments with single species or natural communities are available (Varela et al. \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Gonz\u0026aacute;lez et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Bretherton et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019a\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Putzeys et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Microbial communities are rapidly altered after an oil spill incident (Gemmell et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), so that early monitoring is efficient when \u003cem\u003ein-situ\u003c/em\u003e responses to oil pollution are targeted. Therefore, to improve knowledge on the effects of oil spills, it is important to consider rapid and longer responses of \u003cem\u003ein situ\u003c/em\u003e phytoplankton following an oil leak. This work presents first field data on the responses of a coastal phytoplankton community to an oil spill from the early stage (the first days) up to a few weeks in the south-western Mediterranean Sea.\u003c/p\u003e \u003cp\u003eThe oil leak site was located in the Bay of Bizerte, while the sampling station was located in the Channel of Bizerte (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The wind direction and speed moved the oil slick towards the Bizerte City coast and to the Channel. This was reflected by the presence of PAHs in the sampling station 8 days after the spill. Referring to the WHO 1997 standard (700 ng L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), seawater was moderately contaminated (ΣPAHs \u0026asymp;130 ng L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). Some of the measured PAHs (chrysene, fluoranthene, naphthalene, phenanthrene) could have a toxic effect on phytoplankton even at low concentrations (Echeveste et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2010a\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2010b\u003c/span\u003e; Ben Othman et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The PAH water concentrations measured on D08 had certainly been diluted. Therefore, higher levels would have been measured on D01 and D04 if sampled, and phytoplankton was most probably exposed to higher concentrations on D01 and D04 than those measured on D08. PAH levels were much higher in sediment (ΣPAHs\u0026thinsp;=\u0026thinsp;1222 ng g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e dry sediment, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) than in seawater. As a result of their hydrophobic nature, PAHs are known to be sequestered within sediment (Mille et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Bradshaw et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), where it could be degraded partially by bacteria (Acosta-Gonz\u0026agrave;lez et al. 2015). Historical data showed that the sediment of Bizerte Channel had been exposed to PAH contamination, but at levels much lower than those recorded after this oil spill (394.1 ng g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e dry sediment, Barhoumi et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eImpact of oil on the growth of size-fractioned phytoplankton\u003c/h2\u003e \u003cp\u003ePhytoplankton can respond rapidly to oil pollution and to the most toxic components of oil \u0026ndash; PAHs (Ohwada et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Gonz\u0026aacute;lez et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Gemmell et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Our results also showed that phytoplankton displayed significant changes in biomass and abundance following the oil spill. However, the three size fractions exhibited different responses, confirming that cell size is important in determining the reaction of phytoplankton to oil and PAH pollution (Echeveste et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2010a\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2010b\u003c/span\u003e; Ben Othman et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Bretherthon et al. 2020). Moreover, the observed changes in biomass and abundance varied over time after the oil spill. The biomasses and abundances of nano- and micro-phytoplankton significantly decreased on D04 and D08 relatively to D01 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003ea, b). Short-term negative effects of oil and PAHs on large phytoplankton have been reported, and their toxicity on the photosynthetic activity, growth and biomass of phytoplankton is well documented (Djomo et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Gonz\u0026aacute;lez et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Paul et al. \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Ben Othman et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). PAHs can alter photosystem II functioning and reduce the fluorescence yield in several marine phytoplankton species (Aksmann and Tukaj \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Ben Othman et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In addition to the toxicity of petroleum hydrocarbons, the presence of an oil slick on the water surface during the first week of sampling (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003e) reduced light penetration and indirectly inhibited phytoplankton growth. Conversely, nearly three weeks after the oil spill (D18), a positive effect was observed on large phytoplankton (\u0026gt;\u0026thinsp;2 \u0026micro;m), which bloomed and reached high concentrations (2.5-4 10\u003csup\u003e5\u003c/sup\u003e cells L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003ea, b). Our results are in agreement with previous studies reporting a reduced phytoplankton concentration in the short term, but phytoplankton outbreaks (particularly for large species such as diatoms) in the long term (Taş et al. \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Sheng et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Pan et al. \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Ozhan et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). On D18, the oil in the sampled station had been easily dispersed by the hydrological conditions encountered in mid-autumn (wind, water mass movements), and its negative effect on phytoplankton was ultimately reduced. Therefore, the regrowth of nano- and microphytoplankton on D18 could be mainly due to the return of a long-term favourable situation in the station, particularly light conditions. D18 was indeed characterised by the lowest turbidity (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003e) and by seawater that recovered the same colour and smell as before the incident. D18 also coincided with the lowest nutrient concentrations (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003e), which may reflect their absorption during phytoplankton regrowth. Moreover, nano- and microphytoplankton biomasses and abundances were negatively correlated with all nutrients. Ben Othman et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) have shown that resumption of phytoplankton growth under PAH contamination coincided with significant change in community composition.\u003c/p\u003e \u003cp\u003eSmaller phytoplankton species are traditionally reported to be more sensitive than large ones to pollutants like oil compounds because of their higher surface-to-volume ratio (Echeveste et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Ben Othman et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), and significant decreases in their abundance and growth are generally reported after PAH exposure (Kottuparambil and Augusti 2018; Ashok et Augusti 2022). On the contrary, the biomass and abundance of picophytoplankton was stimulated after the oil pollution event of Bizerte, even when an oil film covered the surface water of the station (on D04 and D08, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Our results are in agreement with other studies showing proliferation of small phytoplankton after an oil spill incident (Gonz\u0026aacute;lez et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Huang et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Kottuparambil et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Quigg et al (\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) argued that the dominance of small phytoplankton following an oil spill is related to their higher growth rate than that of large cells. However, the increase of picophytoplankton could result from the release from grazing by sensitive grazers like heterotrophic nanoflagellates (Johansson et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1980\u003c/span\u003e; Almeda et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Gemmell et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Additionally, correlations between picophytoplankton and abiotic factors (nutrients) were absent, suggesting that pico-sized biomass may be more controlled by biotic factors such as zooplankton grazing. Concomitantly with our work, Chkili et al. (submitted) investigated the protozooplanktonic community and its grazing rate, and reported a net decrease in grazing mortality rate of picophytoplankton starting from D08, with the absence of their potential heterotrophic nanoflagellate grazers.\u003c/p\u003e \u003cp\u003eThe different responses of small and large phytoplankton to the oil spill were followed by a shift in the phytoplankton size structure from dominant micro-sized cells on D01 (61% of Chl \u003cem\u003ea\u003c/em\u003e) to pico-sized cells on D18 (\u0026sim;60% of Chl \u003cem\u003ea\u003c/em\u003e). This change could influence the grazer community and ultimately the food web structure.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eImpact of oil on the phytoplankton community composition\u003c/h2\u003e \u003cp\u003eThe oil spill had a clear effect on the community composition of nano- and microphytoplankton, which changed differentially in the short and long terms (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003e, \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e5\u003c/span\u003e, \u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eShort-term impact\u003c/b\u003e. In the short term, the compositions of the two communities showed high dissimilarity on D01 relative to D04 and D08 (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). During this short period, the presence of petroleum slick in the station (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003e) was accompanied by a decrease in the abundance and biomass of nano- and micro-sized cells, but some species maintained their growth. This indicates a growth inhibition of sensitive species and a possible selection of pollutant-tolerant species following the oil spill in the short term.\u003c/p\u003e \u003cp\u003eAs regards microphytoplankton, diatoms were the main species on D01 and remained dominant on D04 and D08 despite the presence of oil in the station. The ability of diatoms to resist oil spills is documented. The presence of the silica frustule can protect them from the lethal effect of oil and confer them a better chance to survive than the naked phytoplankton cells do (Ikavalko 2005; Varela et al. \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Hallare et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Ozhan et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Parsons et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Genes involved in the formation of the silica shell of diatoms (e.g., sil3) are downregulated after exposure to PAH mixtures (Bopp and Lettieri \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). However, other researchers showed that diatoms are more affected by oil than phytoflagellates and dinoflagellates (Mishamandani et al. 2015; Taş et al. \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Fiori et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), and the response of coastal diatoms to oil is clearly size-dependent. Small diatoms (\u0026lt;\u0026thinsp;20 mm) are apparently stimulated by oil, whereas large diatoms (\u0026gt;\u0026thinsp;20 \u0026micro;m) are negatively affected by high oil concentrations (Gonz\u0026aacute;lez et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Furthermore, when Bretherton et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) assessed the role of different physiological traits in the response of various phytoplankton taxa to oil, cell size was most important in determining the biomass response to oil. In our study, the abundance of centric diatoms decreased from D01 to D08, dominated by small (mean length/width ratio 35 \u0026micro;m / 3 \u0026micro;m) \u003cem\u003eLeptocylindrus\u003c/em\u003e species (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003ec), at the expense of pennate diatoms whose contribution increased gradually to form almost all microphytoplankton on D08 (\u0026sim;90%; Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). Large \u003cem\u003ePseudo-nitzschia\u003c/em\u003e and \u003cem\u003eNitzschia\u003c/em\u003e species (length/width ratio ranges 45\u0026ndash;108 \u0026micro;m / 3\u0026ndash;13 \u0026micro;m) were the main taxa on D01 and D04, and \u003cem\u003eNitzschia\u003c/em\u003e spp. formed 91% of pennate diatoms on D08 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). Our results are in line with those of Bretherton et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019a\u003c/span\u003e) showing the dominance of the \u003cem\u003ePseudo-nitzschia\u003c/em\u003e genus after 3 days of oil exposure. The tolerance of pennate diatoms to toxic petroleum products may be explained genetically, since they are known to be more tolerant than other diatoms to oil compounds (Ozhan and Bargu \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Bretherton et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019b\u003c/span\u003e). Furthermore, Melliti Ben Garali et al. (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) provided the first evidence that two \u003cem\u003ePseudo-nitzschia\u003c/em\u003e species isolated from the Channel and Lagoon of Bizerte could tolerate a 15-PAH mixture by enhancing their biovolume, and were even able to bioconcentrate PAHs and degrade them, probably in synergy with their associated bacteria. Phytoplankton (including diatoms) can release extracellular polymeric substances (EPS) during environmental stress, e.g., oil exposure (Sun et al. \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Kamalanathan et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The bacteria associated to phytoplankton can influence EPS production, and phytoplankton can in turn alter the bacterial community (Kamalanathan et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Therefore, the phytoplankton-bacteria association can undoubtedly play an important role in phytoplankton resistance to oil. A benthic diatom and its associated bacteria isolated from a station close to Bizerte Channel have been found efficient in removing benzo(a)pyrene and fluoranthene (Kahla et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). All these findings clearly suggest that \u003cem\u003eNitzschia\u003c/em\u003e and \u003cem\u003ePseudo-nitzschia\u003c/em\u003e species from Bizerte, where previous PAH contamination has been reported (Lafabrie et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Bancon-Montigny et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), have developed tolerance to PAHs through adaptation mechanisms that make them physiologically able to resist oil pollution. The trophic mode might also influence the sensitivity of phytoplankton to contaminants, including oil compounds. Conversely to autotrophic species, mixotrophic or heterotrophic diatoms can rely on sources of organic carbon to grow and to decrease their dependence on photosynthesis, so that they can better withstand contaminant toxicity (Debenest et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Larras et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Brethertron et al. 2021). Interestingly, heterotrophy has been reported for some \u003cem\u003ePeudo-nitzschia\u003c/em\u003e species (Mengelt and Prezelin 2005; Loureiro et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), including species from our study site (Melliti Ben Garali et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Our results suggest that diatoms are resistant to hydrocarbons and that certain species \u0026ndash; e.g., members of the \u003cem\u003ePseudo-nitzschia\u003c/em\u003e and \u003cem\u003eNitzschia\u003c/em\u003e genera \u0026ndash; may grow under oil contamination conditions. This is of particular interest given the fact that several species within these genera are known to produce the neurotoxin domo\u0026iuml;c acid, including strains from the Bizerte waters (Bouchouicha Smida et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2014a\u003c/span\u003e; Sakka Halili et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Blooms of \u003cem\u003ePseudo-nitzschia\u003c/em\u003e and \u003cem\u003eNitzschia\u003c/em\u003e are a known fact in the Lagoon and Channel of Bizerte (Sahraoui et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Bouchouicha Smida et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2014b\u003c/span\u003e; Melliti Ben Garali et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Oil hydrocarbon pollution can promote the growth of these diatoms and could increase the frequency of toxic blooms in these coastal waters, which are chronically prone to this kind of pollution.\u003c/p\u003e \u003cp\u003eAs regards nanophytoplankton, cryptophyceae (dominated by \u003cem\u003eH. fusiformis\u003c/em\u003e and \u003cem\u003eH. marina)\u003c/em\u003e were the main taxa from D01 to D08 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e5\u003c/span\u003e). This is not in agreement with the observation of Brussaard et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), who reported the disappearance of this phytoplankton group after short-term exposure to oil. The major short-term change within nanophytoplankton observed in our study was the decrease of chrysophyceae (mainly \u003cem\u003eM. pusilla\u003c/em\u003e) and prymnesiophyceae (mainly \u003cem\u003eImantonia rotunda\u003c/em\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e5\u003c/span\u003e). \u003cem\u003eM. pusilla\u003c/em\u003e has been found sensitive to oil (Bretherton et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), or not (Brussaard et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), and a beneficial effect of oil exposure on chrysophyceae has even been found (Finkel et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, prymnesiophyceae can be a dominant group after an oil spill (Brussaard et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). In fact, the sensitivity of phytoplankton to oil is largely species dependent, since toxic oil compounds can affect different cellular and molecular targets (Ozhan et al, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Kamalanathan et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Furthermore, species can have differential core metabolism plasticity to counteract oil-induced oxidative stress and can modulate their tolerance to oil exposure (Kamalanathan et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eLong-term impact.\u003c/b\u003e The community compositions of micro- and nanophytoplankton on D18 greatly differed from those of the other days (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e, Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003e, \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e5\u003c/span\u003e, \u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e6\u003c/span\u003e). On D18, the wide regrowth of both size fractions (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003e) coincided with significant changes in the community composition, as speculated. Centric diatoms (microphytoplankton) were more abundant after 18 days and formed \u0026sim;40% of the community, although the community structure did not change that much since \u003cem\u003eLeptocylindrus\u003c/em\u003e spp. remained the dominant taxon (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). Centric diatoms have been reported to be faster growing species than pennate diatoms after a long post-spill period (Verlecar et al. \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Hallare et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). In the present study, pennate diatoms remained an important component of microphytoplankton, but the community changed deeply: \u003cem\u003eA. glacialis\u003c/em\u003e had a low contribution from D01 to D08 (8\u0026ndash;11%), but proliferated (2 10\u003csup\u003e5\u003c/sup\u003e cells L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and became dominant on D18 (87%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). Gallo et al. (2016) reported a dominance of \u003cem\u003eA. glacialis\u003c/em\u003e under increased levels of CO\u003csub\u003e2\u003c/sub\u003e in seawater, while Sahu et al. (\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) found that its development can be supported by salinity and a high nitrogen concentration. The return of favourable environmental factors in our study site in the longer term may be responsible for \u003cem\u003eA. glacialis\u003c/em\u003e development. The species abundance was negatively correlated with the N and Si concentrations, indicating their utilization during the \u003cem\u003eA. glacialis\u003c/em\u003e increase.\u003c/p\u003e \u003cp\u003eAs regards nanophytoplankton, the \u003cem\u003eChaetoceros\u003c/em\u003e spp. bloom (1.3 10\u003csup\u003e5\u003c/sup\u003e cells L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) was the most significant change observed after 18 days (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The growth of these red tide organisms was recently found stimulated after 10 and 14 days of oil exposure (Lv et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Nutrients \u0026ndash; phosphorous in particular \u0026ndash; are considered the main regulating factors of \u003cem\u003eChaetoceros\u003c/em\u003e species growth (Shevchenko et al. \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Silkin et al. \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). During our study, phosphorous seemed to support the proliferation of \u003cem\u003eChaetoceros\u003c/em\u003e spp., since the abundance of these organisms was negatively correlated with P concentrations (rs = -0.699, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eSpecies succession after an oil spill might also be related to different sensitivity levels to hydrocarbons (Sargian et al. \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Huang et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Hemmer et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Dominant species after several days of oil exposure can be considered more sensitive than species growing in the presence of high amounts of oil. In our study, \u003cem\u003eA. glacialis\u003c/em\u003e and \u003cem\u003eChaetoceros\u003c/em\u003e spp, which can be sensitive to oil pollutants, dominated on D18 and took the place of \u003cem\u003eNitzschia\u003c/em\u003e and \u003cem\u003ePseudonitzschia\u003c/em\u003e species, which can resist to hydrocarbons as discussed above. Another reason might be that \u003cem\u003eA. glacialis\u003c/em\u003e and \u003cem\u003eChaetoceros\u003c/em\u003e spp could outcompete and eliminate other species \u003cem\u003evia\u003c/em\u003e allelopathic mechanisms, and become more competitive for resources (nutrients, light) and hence grow better. Allelopathy plays a significant role in the dominance, succession, and formation of natural diatom communities (Leflaive and Ten Hage, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Zhang et al. 2019). Additionally, the difference in the diatom community composition after long-term oil pollution could be partially due to indirect trophic interactions because herbivorous zooplankton is sensitive to oil compounds (Hjorth et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Gonz\u0026aacute;lez et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Almeda et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Van Dinh et al. \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). For one reason or another, our results clearly show that the oil spill was followed by a profound change in the phytoplankton community composition after 18 days. This modification was accompanied by significantly lower diversity indexes (S, H\u0026rsquo; and J, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e7\u003c/span\u003e), which reinforces the fact that oil spillage has deep effects on the structure of primary producers. Huang et al. (2010) also observed a drop in biodiversity and in the number and evenness of phytoplankton species after 15 days of crude oil exposure during different seasons.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study highlights the importance of phytoplankton sampling at different stages of an oil spill because it displays various responses throughout the evolution of an oil incident. The size structure and species composition of phytoplankton observed in the days following initial oil exposure were quite different from those in the longer term. Picophytoplankton proliferated, possibly thanks to decreased grazing due to oil poisoning of its potential consumers like heterotrophic nanoflagellates. In contrast, large phytoplankton decreased in the short term and bloomed after 18 days. The dominance of pennate diatoms of the genera \u003cem\u003ePseudo-nitschia\u003c/em\u003e and \u003cem\u003eNitzschia\u003c/em\u003e in the presence of the oil slick could be related to the high tolerance of these species to oil hydrocarbon components. This re-confirms previous observations in the study area that hydrocarbon pollution could increase the likelihood of blooms of toxic diatoms. Our results demonstrate that even small oil spills may have short- and long-term effects on phytoplankton, and their recurrent nature in coastal waters may affect ecosystem functioning. Further research is needed to investigate the chronic impact of oil on coastal ecosystems.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eStatements and Declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u0026nbsp;\u003c/strong\u003eThe authors have no competing interests to declare that are relevant to the content of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFinancial/ non-financial interests\u0026nbsp;\u003c/strong\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish\u0026nbsp;\u003c/strong\u003eThe\u0026nbsp;authors have given their consent to publish the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u0026nbsp;\u003c/strong\u003eBoutheina Grami: Conceptualization, Investigation, Writing-original draft. Oumayma Chkili: Data collection and analysis, Editing. Sondes Melliti Ben Garali, Kaouther Mejri Kousri, Marouen Meddeb: Material preparation, Methodology, data collection, Editing. Lassad Chouba: Editing, HAP analysis. Nathalie Niquil: review and editing. Asma Sakka Hlaili: Project Conceptualization, Supervision, Review-writing. As supervisors of this work the final authorship positions were awarded to Sakka Hlaili A.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u0026nbsp;\u003c/strong\u003eCollected \u003cem\u003ein situ\u003c/em\u003e data, photos and analysis that support the findings of this study are not openly available but are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAcosta-Gonz\u0026aacute;lez A, Martirani-von Abercron SM, Rossell\u0026oacute;-M\u0026oacute;ra R, Wittich RM, Marqu\u0026eacute;s S (2015) The effect of oil spills on the bacterial diversity and catabolic function in coastal sediments: a case study on the Prestige oil spill. 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Ann Rev Mar Sci 3:197\u0026ndash;225. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1146/annurev-marine-120709-142819\u003c/span\u003e\u003cspan address=\"10.1146/annurev-marine-120709-142819\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"aquatic-sciences","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aqsc","sideBox":"Learn more about [Aquatic Sciences](http://link.springer.com/journal/27)","snPcode":"27","submissionUrl":"https://submission.nature.com/new-submission/27/3","title":"Aquatic Sciences","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"oil spill, phytoplankton, diatoms, diversity, Coastal waters, Mediterranean Sea","lastPublishedDoi":"10.21203/rs.3.rs-4019976/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4019976/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eOil spills are recurrent worldwide. Assessing the response of phytoplankton \u0026ndash; the basis of marine food webs \u0026ndash; at the early stages of an oil spill and throughout its evolution is crucial to improve our understanding of the impact of oil spills on the marine environment. Field data collected 1, 4, 8 and 18 days after the \u0026ldquo;Bizerte City\u0026rdquo; oil spill showed that phytoplankton responded differentially over time. In the short term (1\u0026ndash;8 days), picophytoplankton biomass and abundance increased, possibly due to reduced grazing. In contrast, nano- and microphytoplankton biomass decreased, probably owing to inhibited growth of species sensitive to polycyclic aromatic hydrocarbons (PAHs) \u0026ndash; the most toxic components of oil. After 18 days, the dispersal of oil and its decreasing negative effect were accompanied by outbreaks of all size fractions. Accordingly, the phytoplankton size structure shifted throughout the oil exposure level from a prevalence of microphytoplankton after a few days toward picophytoplankton dominance. Oil pollution influenced the species composition and significantly decreased diversity indexes. In the first days, nanophytoplankton was dominated by cryptophyceae (mainly \u003cem\u003eHillea fusiformis\u003c/em\u003e and \u003cem\u003eH. marina\u003c/em\u003e), while microphytoplankton was mostly represented by the pennate diatoms \u003cem\u003ePseudo-nitzschia\u003c/em\u003e and \u003cem\u003eNitzschia\u003c/em\u003e, suggesting a better resistance of these genera to oil. Algal recovery after 18 days was associated with high proliferation of nano-sized \u003cem\u003eChaetoceros\u003c/em\u003e and micro-sized \u003cem\u003eAstrionellopsis glacialis\u003c/em\u003e diatoms. These results improve our knowledge of the impact of oil pollution on coastal phytoplankton communities and reinforce the idea of using them as bio-indicators.\u003c/p\u003e","manuscriptTitle":"Field study on natural phytoplankton throughout “Bizerte City” oil spill on the south-western coast of the Mediterranean Sea","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-11 21:02:30","doi":"10.21203/rs.3.rs-4019976/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-05-21T20:13:08+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-12T11:41:17+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-12T02:37:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"141515597172838752815757406838419760285","date":"2024-05-08T11:59:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"262407932851717308684976185465112756371","date":"2024-05-08T07:07:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"d086555d-416a-4657-9bd6-a249075e8317","date":"2024-03-23T11:58:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"cb8bba68-4b63-4fb9-9668-eb82511fe63e","date":"2024-03-12T07:58:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"df94651c-61be-4760-897c-686cf31b7e26","date":"2024-03-11T16:08:48+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-03-11T15:58:23+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-08T09:33:52+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-03-07T09:56:37+00:00","index":"","fulltext":""},{"type":"submitted","content":"Aquatic Sciences","date":"2024-03-06T08:14:13+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"aquatic-sciences","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aqsc","sideBox":"Learn more about [Aquatic Sciences](http://link.springer.com/journal/27)","snPcode":"27","submissionUrl":"https://submission.nature.com/new-submission/27/3","title":"Aquatic Sciences","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"e7424809-c1ee-4af1-901d-c3d7393e99c8","owner":[],"postedDate":"March 11th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-08-05T16:09:31+00:00","versionOfRecord":{"articleIdentity":"rs-4019976","link":"https://doi.org/10.1007/s00027-024-01113-7","journal":{"identity":"aquatic-sciences","isVorOnly":false,"title":"Aquatic Sciences"},"publishedOn":"2024-07-30 15:57:38","publishedOnDateReadable":"July 30th, 2024"},"versionCreatedAt":"2024-03-11 21:02:30","video":"","vorDoi":"10.1007/s00027-024-01113-7","vorDoiUrl":"https://doi.org/10.1007/s00027-024-01113-7","workflowStages":[]},"version":"v1","identity":"rs-4019976","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4019976","identity":"rs-4019976","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}