Aude Nguyen
email: audeliennguyen@gmail.com

Laurence Solovei
email: l-solovei@chu-montpellier.fr

Charles Marty-Ané

Arnaud Bourdin

Ludovic Canaud

Pierre Alric

Kheira Hireche
email: kheira.hireche@yahoo.fr

Arterial Sleeve Lobectomy: Does Pulmonary Artery Reconstruction Type Impact Lung Function?

Keywords: non-small-cell lung cancer, pulmonary artery, sleeve lobectomy, lung perfusion, lung function Simple

Lung cancer is the second most frequent tumor worldwide. In cases of pulmonary artery invasion, arterial sleeve lobectomy has progressively gained acceptance as an advantageous alternative to pneumonectomy, but few studies have considered lung perfusion and respiratory function. This singlecenter retrospective cohort study aimed to assess the impact of arterial reconstruction techniques on lung perfusion and respiratory function. Between January 2001 and December 2020, a comparative analysis of 48 patients' preoperative and postoperative functional outcomes (FEV 1 ) and 28 patients' preoperative and postoperative lung perfusion results was conducted. Regardless of the type of vascular reconstruction, the study revealed no significant difference between the perfusion ratio of the remaining parenchyma before and after surgery. Moreover, arterial reconstruction did not negatively affect the expected postoperative respiratory function. Arterial sleeve lobectomy is a valid parenchymal-sparing technique in terms of perfusion and respiratory function.

Introduction

Despite the evolution of medical and multimodal treatment, non-small-cell lung cancer remains the leading cause of cancer deaths worldwide [START_REF] Barta | Global Epidemiology of Lung Cancer[END_REF], with surgery being the only curative option [START_REF] Brunelli | ERS/ESTS clinical guidelines on fitness for radical therapy in lung cancer patients (surgery and chemoradiotherapy)[END_REF]. Historically, pneumonectomy was the standard of care of central lung tumors with bronchus and/or pulmonary artery (PA) invasion. In recent years, sleeve lobectomy with PA reconstruction has progressively gained acceptance as an advantageous alternative to pneumonectomy. Initially performed on patients with impaired cardiopulmonary reserves [START_REF] Chunwei | Evaluations of bronchoplasty and pulmonary artery reconstruction for bronchogenic carcinoma[END_REF], this parenchymal-sparing technique is now performed on all patients where anatomical conditions allow complete resection [START_REF] Shrager | Lobectomy with tangential pulmonary artery resection without regard to pulmonary function[END_REF]. Growing evidence suggests that arterial sleeve lobectomy is associated with lower postoperative complications, long term morbimortality [START_REF] Ma | Does sleeve lobectomy concomitant with or without pulmonary artery reconstruction (double sleeve) have favorable results for non-small cell lung cancer compared with pneumonectomy? A meta-analysis[END_REF][START_REF] Ferguson | Sleeve lobectomy or pneumonectomy: Optimal management strategy using decision analysis techniques[END_REF][START_REF] Schiavon | Lobectomy With Artery Reconstruction and Pneumonectomy for Non-Small Cell Lung Cancer: A Propensity Score Weighting Study[END_REF], and better quality of life [START_REF] Yang | Comparison of Bronchial Sleeve LobectomyWith Pulmonary Arterioplasty Versus Pneumonectomy[END_REF] when compared to pneumonectomy, even after neoadjuvant therapy [START_REF] Maurizi | Sleeve Lobectomy Compared with Pneumonectomy after Induction Therapy for Non-Small-Cell Lung Cancer[END_REF]. However, few studies have considered the lung perfusion, respiratory function, and patency outcomes of sleeve procedures. Therefore, our aim was to investigate whether the type of arterial reconstruction has an impact on lung perfusion. This investigation involved comparing and analyzing the preoperative and postoperative perfusion of the preserved lobes using ventilation/perfusion lung scintigraphy, while considering the specific reconstruction technique employed. Our secondary aim was to evaluate postoperative lung function: we compared measured postoperative FEV 1 (MPO FEV 1 ) with predicted postoperative FEV 1 (PPO FEV 1 ).

Materials and Methods

Study Design and Preoperative Evaluation

We performed a retrospective analysis of the perfusion and respiratory function data of patients who underwent sleeve resection for lung tumors with PAinvasion, requiring partial or complete arterial reconstruction at Montpellier University Hospital, between January 2001 and December 2020. Complete preoperative and postoperative functional results were available for 48 patients, of which complete preoperative and postoperative perfusion data were available for 28. We excluded patients having undergone only bronchial sleeve resection, patients with incomplete preoperative and postoperative pulmonary function tests (PFTs), and patients with tumors other than NSCLC. Preoperative assessment included a contrast-enhanced thoracic-abdominal and pelvic computed tomography, brain imaging, and whole-body fluorodeoxyglucose positron emission tomography (PET/CTFDG), the latter having replaced bone scintigraphy since 2007. Preoperative pulmonary function studies were performed on all patients to assess first-second forced expiratory volume (FEV 1 ) and diffusing capacity of the lung for carbon monoxide (DLCO). Direct measurement of wholebody maximal oxygen consumption (VO2-max test) and TC 99mperfusion lung scintigraphy were performed when needed according to European guidelines [START_REF] Postmus | Early and Locally Advanced Non-Small-Cell Lung Cancer (NSCLC): ESMO Clinical Practice Guidelines for Diagnosis, Treatment and Follow-up[END_REF]. PPO FEV 1 was estimated using the formula described by Brunelli: [START_REF] Brunelli | Physiologic Evaluation of the Patient With Lung Cancer Being Considered for Resectional Surgery: Diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines[END_REF] Predicted postoperative FEV 1 = Preoperative FEV 1 x (1 -number of functional segments resected/number of total functional segments).

Tumor stage was determined according to the eighth edition TNM Staging classification [START_REF] Goldstraw | The IASLC Lung Cancer Staging Project: Proposals for Revision of the TNM Stage Groupings in the Forthcoming (Eighth) Edition of the TNM Classification for Lung Cancer[END_REF]. Invasive nodal staging using endobronchial ultrasound biopsy or mediastinoscopy was performed in cases of N2 clinical stages with mediastinal uptake on PET/CTFDG. All patients with clinical stage IIIA-N2 and higher received neoadjuvant therapy mediastinal restaging after induction therapy and prior to resection. Data were obtained from patient case notes and electronic patient records, then entered into a dedicated anonymized database (Excel, Microsoft Corp, Redmond, WA, USA). The study was approved by the local ethics committee and Institutional Review Board (N_IRBMTP_ 2021_07_202100888) with a waiver of individual patient consent.

Surgical Procedure

Four experienced surgeons were in charge of the patients. The cause of arterial invasion was either hilar tumors or lymph node disease. The procedure was performed under general anesthesia with double-lumen endotracheal intubation. Lung lobectomy with radical lymph node dissection was performed in all patients via a posterolateral thoracotomy. Oncologic and technical feasibility of the arterial sleeve lobectomy was assessed by the surgeon after proximal and distal control of the PA. Systemic heparin sodium (0.5 mg_kg -1 ) was intravenously administered. Then, vascular clamps were placed at the proximal and distal disease-free PA segment. The tumor was resected en bloc with the involved portion of the PA and other adjacent structures if required. All resection margins were ascertained by frozen section analysis. The modality of PA reconstruction was assessed after resection. Thus, we considered 4 types of PA reconstruction: direct angioplasty, patch angioplasty using either prosthetic (HemaCarotid patch, Maquet® Gentige Group, Rastatt, Germany) or biological bovine pericardium patches (XenoSure Biological Patch; LeMaitre Vascular, Burlington, MA, USA), end-to-end anastomosis, and bypass using prosthetic conduits (GORE-TEX®, WL Gore&Associates, Flagstaff, AZ, USA) or cryopreserved allograft (PA or thoracic aorta) in cases of extensive PA involvement precluding direct reconstruction. Vascular anastomoses were performed with 5-0 or 6-0 polypropylene thread. At the end of the vascular procedure, the distal clamp was removed before tying the suture in order to purge and to check the congruence of the reconstruction (absence of kinking and twisting). When a double sleeve was needed, the bronchial anastomosis was performed first, through separate PDS 4.0 stitches. All patients received 6000 UI subcutaneous low-molecular-weight heparin for 15 days after surgery. [START_REF] Maurizi | Reconstruction of the bronchus and pulmonary artery[END_REF]

Follow Up

Postoperative follow up data were collected from several sources: consultation and hospitalization reports and personal contact with patients and/or their families. The national death registry was also consulted. We collected the most recent PFT for all patients. When pre-and postoperative lung scintigraphy results were available, perfusion and ventilation assessments were recorded for each lobe. Patency PA reconstruction was assessed on the most recent contrast-enhanced thoracic CT.

Statistical Analysis

Statistical analyses were performed using RStudio version 4.0.1. (R Foundation, Vienna, Austria) and ExcelStat (Microsoft Corp, Redmond, WA, USA). Scintigraphic assessments of lung perfusion were compared using the Wilcoxon signed rank test for paired data. We additionally performed a subgroup analysis according to the type of PA reconstruction technique. The difference between predicted and measured postoperative FEV 1 is represented by DFEV 1 (= MPO FEV 1 -PPO FEV 1 ). Comparison of MPO FEV 1 and PPO FEV 1 was performed using a linear regression model. Univariate and multivariate analysis was also performed to identify confounding factors of lower FEV 1 . The Kaplan-Meier method was used to perform survival analysis. A p-value less than 0.05 was considered significant, without correction for multiple statistical tests.

Results

Patient Characteristics and Overall Survival

Patient characteristics and surgical details are described in Table 1. 69% were men with a median age at surgery of 67 years. Left upper lobectomy was the most common surgical procedure (68%), and squamous cell carcinoma was the predominant pathological subtype. The types of PA reconstruction included 9 direct angioplasties (19%), 14 patch angioplasties (29%), 7 end-to-end anastomoses (15%) and 18 bypass reconstructions (37%). Seventeen patients (35%) had double arterial and bronchial sleeve lobectomy. The median follow up period was 34 months (0.5-153 months). The 5-year overall survival was 49%. Lung scintigraphy results were available for 28 patients.

Patency and Perfusion Results

CT scan follow up was performed 6 to 24 months after surgery (mean 14 months). Patency rate was 96%. Three patients (6.3%) had a complete or partial PA thrombosis. For these patients, the type of PA reconstruction was prosthetic bypass in the left upper lobectomy. Twenty-eight patients had complete data on preoperative and postoperative ventilation/perfusion lung scintigraphy. Median time between surgery and postoperative lung scintigraphy was 32 months (13-48 months). For those patients, the type of PA reconstructions used were 3 direct angioplasties (11%), 3 end-to-end anastomosis (11%), 10 patch angioplasties (36%), 4 prosthetic bypasses (14%), 7 cryopreserved arterial allograft bypasses (25%), and 1 custom-made xenopericardial patch bypass (3%). There was no significant difference between the preoperative and postoperative perfusion ratio of the remaining parenchyma on the operated side (29.5% (25-36) vs. 32.5% [START_REF] Schirren | Prospective Study on Perioperative Risks and Functional Results in Bronchial and Bronchovascular Sleeve Resections[END_REF][START_REF] Ibrahim | Glutaraldehyde Preserved Autologous Pericardium for Patch Reconstruction of the Pulmonary Artery and Superior Vena Cava[END_REF][START_REF] Maurizi | Long-segment pulmonary artery resection to avoid pneumonectomy: Long-term results after prosthetic replacement[END_REF][START_REF] Galetta | Pulmonary artery reconstruction by a custom-made heterologous pericardial conduit in the treatment of lung cancer[END_REF][START_REF] Shiraishi | Pulmonary artery "conduit" reconstruction using bovine pericardium following long-segment sleeve resection: A unique "in situ tailor-made" sewing method[END_REF][START_REF] Goldhaber | Pulmonary embolism[END_REF][START_REF] Danielsbacka | Lung function, functional capacity, and respiratory symptoms at discharge from hospital in patients with acute pulmonary embolism: A cross-sectional study[END_REF][START_REF] Miyoshi | Exercise Capacity of Thoracotomy Patients in the Early Postoperative Period[END_REF][START_REF] Nagamatsu | Long-term recovery of exercise capacity and pulmonary function after lobectomy[END_REF][START_REF] Wang | Effect of Lung Resection on Exercise Capacity and on Carbon Monoxide Diffusing Capacity During Exercise[END_REF][START_REF] Brunelli | Evaluation of Expiratory Volume, Diffusion Capacity, and Exercise Tolerance Following Major Lung Resection[END_REF][START_REF] Bolliger | Pulmonary function and exercise capacity after lung resection[END_REF][START_REF] Deslauriers | Adjustments in cardiorespiratory function after pneumonectomy: Results of the pneumonectomy project[END_REF](35)(36)(37)(38), p = 0.47). However, the postoperative perfusion of the contralateral lung increased significantly (61.5% (52-64) vs. 66% (62-77), p < 0.001) (Figure 1), while the lowest perfusion values were observed in patients with partial or complete thrombosis (n = 3). No perfusion defects were observed on lung scintigraphy, except in one patient with complete prosthetic bypass thrombosis (Figure 2). Perfusion analysis according to the type of reconstruction did not show any statistically significant difference for each type of arterial reconstruction (Figure 3).

Functional Results

PFTs were performed 7 to 26 months after surgery (median 12 months). Table 1 shows the preoperative and postoperative pulmonary function tests. FEV 1 was significatively reduced by 400 mL (15% of the preoperative value, p < 0.001). The preoperative and postoperative DLCO values were 63% (53-79) and 52 % (62-71) (p < 0.01), respectively, also showing significant loss.

It should be noted that the comparison of pre-and postoperative FEV 1 in the 17 patients who underwent a double sleeve procedure yielded non-significant results.

Median MPO FEV 1 was 75 % (63-81%). There was a statistically significant linear correlation between MPO and PPO FEV 1 (r = 0.66, p < 0.001) (Figure 4). However, median MPO FEV 1 was 260 mL (11.4% of the preoperative value) higher than PPO FEV 1 . In univariate analysis, PA reconstruction technique did not affect DFEV 1 . However, multivariate analysis revealed prosthetic bypass to be a predictive factor of worse DFEV 1 (p = 0.03) (Table 2).

Discussion

In this study, we report further evidence regarding the functional validity of PA reconstruction during parenchymal-sparing lung cancer surgery whatever the type of arterial reconstruction. Arterial sleeve lobectomy has been widely accepted in our center since the early 2000s, with the combination of vascular and thoracic surgery in the same department being a determining factor in the development of this complex procedure in routine practice [START_REF] Berthet | Extended Sleeve Lobectomy: One More Step Toward Avoiding Pneumonectomy in Centrally Located Lung Cancer[END_REF][START_REF] Berthet | Pulmonary sleeve resection in locally advanced lung cancer using cryopreserved allograft for pulmonary artery replacement[END_REF].

The incidence of arterial sleeve resection remains low, with reported rates ranging from 1.5% to 3.7% [START_REF] Alifano | Lobectomy with pulmonary artery resection: Morbidity, mortality, and long-term survival[END_REF][START_REF] Cerfolio | Surgical Techniques and Results for Partial or Circumferential Sleeve Resection of the Pulmonary Artery for Patients with Non-Small Cell Lung Cancer[END_REF], which are generally related to the more technically demanding procedure rather than to bronchial sleeve lobectomy and pneumonectomy. The choice of reconstruction techniques and materials remains a major issue. While several descriptions of the different options exist, no definite recommendations on this subject have been made [START_REF] Venuta | Reconstruction of the Pulmonary Artery[END_REF][START_REF] Vannucci | Lobectomy with angioplasty: Which is the best technique for pulmonary artery reconstruction?[END_REF][START_REF] Galetta | Surgical Techniques and Long-Term Results of Pulmonary Artery Reconstruction in Patients With Lung Cancer[END_REF].

It should also be highlighted that even the definition of sleeve lobectomy remains fuzzy. According to Vannucci et al. [START_REF] Vannucci | Lobectomy with angioplasty: Which is the best technique for pulmonary artery reconstruction?[END_REF], "PA reconstruction could be defined as any kind of arterial wall resection, repaired by a hand suture requiring a proximal clamp, placed after systemic heparinization", whereas some surgeons may consider tangential excisions of the arterial wall with primary closure as part of an anatomic pulmonary resection for lung cancer. However, previous studies reported high rates of thrombosis and pulmonary embolism when performing tangential primary repair of the PA. In our series, none of the nine patients who underwent direct angioplasty developed perfusion defects or pulmonary embolism.

Despite the growing acceptance and the confirmed safety and oncologic reliability of this reconstructive procedure [START_REF] Ma | Does sleeve lobectomy concomitant with or without pulmonary artery reconstruction (double sleeve) have favorable results for non-small cell lung cancer compared with pneumonectomy? A meta-analysis[END_REF][START_REF] Alifano | Lobectomy with pulmonary artery resection: Morbidity, mortality, and long-term survival[END_REF], only two studies have paid attention to the impact of PA reconstruction on postoperative pulmonary perfusion. The first postoperative perfusion data were reported by Rendina et al. in 1999 [21], and demonstrated normal perfusion of the preserved lobe of 24-42% of total lung perfusion. However, this study included only three cases (5.8%) of PA replacement. In 2009, Schirren et al. [START_REF] Schirren | Prospective Study on Perioperative Risks and Functional Results in Bronchial and Bronchovascular Sleeve Resections[END_REF] conducted a prospective study of 100 consecutive patients undergoing bronchial or bronchovascular sleeve resection. The authors reported 26% and 33% lung perfusion of the residual lobe on the left and the right side, respectively, and showed that the proportion of perfusion of the preserved lobe gradually improved and stabilized at 6 months. However, the authors did not provide details regarding the type of PA reconstruction. With a median postoperative perfusion of 32.5% (22-38%) and median time from surgery to postoperative scintigraphy of 32 months, our findings are in line with the latest reports [START_REF] Rendina | Sleeve resection and prosthetic reconstruction of the pulmonary artery for lung cancer[END_REF][START_REF] Schirren | Prospective Study on Perioperative Risks and Functional Results in Bronchial and Bronchovascular Sleeve Resections[END_REF]. Moreover, our study is the first to provide pre-and postoperative comparative results of the preserved parenchyma perfusion according to the type of PA reconstruction, including 18 PA replacements (38%). Subgroup analysis did not show any perfusion difference for each type of PA reconstruction. However, it should be noted that three cases of thrombosis occurred in prosthetic bypass grafts, resulting in a major defect on postoperative lung scintigraphy. This finding supports previous observations advocating the use of biological materials in order to decrease thrombotic risk [START_REF] Ibrahim | Glutaraldehyde Preserved Autologous Pericardium for Patch Reconstruction of the Pulmonary Artery and Superior Vena Cava[END_REF][START_REF] Maurizi | Long-segment pulmonary artery resection to avoid pneumonectomy: Long-term results after prosthetic replacement[END_REF][START_REF] Galetta | Pulmonary artery reconstruction by a custom-made heterologous pericardial conduit in the treatment of lung cancer[END_REF][START_REF] Shiraishi | Pulmonary artery "conduit" reconstruction using bovine pericardium following long-segment sleeve resection: A unique "in situ tailor-made" sewing method[END_REF]. The type of substitute is not the only factor of perfusion defects; PA bypass repositioning during pulmonary re-expansion can be a source of twist or kink and must be carefully assessed. Also, PA resection without combined bronchial sleeve resection may result in thrombosis by excessive tensing of an end-to-end anastomosis. Considering the encouraging perfusion results over a median follow up of 34 months, we believe that bypass reconstruction should be considered whenever uncertainty persists as to unsatisfactory PA reconstruction by a tensioned end-to-end anastomosis.

The results of our study show that arterial reconstruction does not negatively affect the expected postoperative FEV 1 value. By comparing FEV 1 PPO and FEV 1 MPO, we considered the volume of lung resected. Furthermore, we found that PPO FEV 1 significantly underestimates MPO FEV 1 by about 260 mL (11.4% of the preoperative value). This underestimation should be factored in when offering lung resection to patients who might be excluded from any surgical program because of impaired preoperative lung functions. Multivariate analysis revealed that prosthetic bypass was a significant factor associated with lower MPO FEV 1 . One might wonder about the relationship between arterial reconstruction and respiratory function; we answer that the understanding of hypoxic vasoconstriction and bronchoconstriction, especially in COPD patients, along with the disparities in viscoelastic properties between native tissue and vascular substitutes, has raised questions regarding the potential impact of arterial clamping and the patency of arterial reconstruction on postoperative respiratory function following such surgical procedures. Furthermore, the direct influence of pulmonary embolism on bronchoconstriction, increased airway resistance, and decreased pulmonary compliance has been well established [START_REF] Goldhaber | Pulmonary embolism[END_REF]. In 2017, Danielsbacka and colleagues [START_REF] Danielsbacka | Lung function, functional capacity, and respiratory symptoms at discharge from hospital in patients with acute pulmonary embolism: A cross-sectional study[END_REF] demonstrated that patients with acute pulmonary embolism experience reduced lung function and functional capacity, highlighting how a perfusion defect can impair respiratory function. Consistent with Danielsbacka's findings, postoperative lung scintigraphy in the three cases of arterial thromboses reported in this study revealed that the perfusion defect closely resembled the ventilation defect (Figure 2). Previous studies have examined the permanent PFT loss following lung resection and reported that the percentage differences in FEV 1 and DLCO at 6 to 12 months after standard lobectomy compared with the preoperative values were to be 8.8% to 17.6% and 3.6 to 11.5%, respectively [START_REF] Miyoshi | Exercise Capacity of Thoracotomy Patients in the Early Postoperative Period[END_REF][START_REF] Nagamatsu | Long-term recovery of exercise capacity and pulmonary function after lobectomy[END_REF][START_REF] Wang | Effect of Lung Resection on Exercise Capacity and on Carbon Monoxide Diffusing Capacity During Exercise[END_REF][START_REF] Brunelli | Evaluation of Expiratory Volume, Diffusion Capacity, and Exercise Tolerance Following Major Lung Resection[END_REF][START_REF] Bolliger | Pulmonary function and exercise capacity after lung resection[END_REF]. The historical series by Deslauriers et al. [START_REF] Deslauriers | Adjustments in cardiorespiratory function after pneumonectomy: Results of the pneumonectomy project[END_REF] evaluating the long-term cardiopulmonary function in 100 pneumonectomy patients reported a worsening of FEV 1 by approximately 30% and a reduction of DLCO by 33%. In the present study, the losses of FEV 1 and DLCO were similar to those of previous reports on PFT following standard lobectomy and significantly less in comparison with that after pneumonectomy.

Limitations

First, this study is limited by a selection bias related to the retrospective design. Second, the small number of patients who had pre-and postoperative scintigraphic evaluation drastically reduced the verification effectiveness of our study. Third, because CT scanning is not a dynamic examination, a more accurate analysis of the position and angulation of the PA reconstruction during respiratory movements could not be performed. Fourth, there is an obvious bias related to the disparity in the postoperative evaluation time among patients. In future, prospective studies which employ systematic pre-and postoperative perfusion scans and dynamic MRI would allow a precise analysis of the perfusion results according to the congruence of the PA reconstruction.

Conclusions

Lobectomy with arterial reconstruction is a valid parenchymal-sparing technique in terms of perfusion and respiratory function. Priority must be given to the use of biological materials for arterial reconstruction.

Funding:

This research received no external funding.

Institutional Review Board Statement:

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of Montpellier University Hospital (IRB number: IRB-MTP_2021_07_202100888). Clinical Trial Registry Number: NCT04981938.

Informed Consent Statement:

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement:

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Conflicts of Interest:

The authors declare no conflict of interest.

Abbreviations


domain: sde sdv

text:
Dimitra-Ioli Skouroliakou
email: dimitra-ioli.skouroliakou@univ-littoral.fr.

Elsa Breton

Solène Irion

Felipe Artigas

Editor Konstantinos

Aristomenis Kormas

Stochastic and Deterministic Processes Regulate Phytoplankton Assemblages in a Temperate Coastal Ecosystem

Keywords: community assembly, phytoplankton, seasonality, ecological processes, coastal ecosystem, community ecology

Assessing the relative contributions of the interacting deterministic and stochastic ecological processes for phytoplankton community assembly is crucial in understanding and predicting community organization and succession at different temporal and spatial scales. In this study, we hypothesized that deterministic and stochastic ecological processes regulating phytoplankton, present seasonal and repeating patterns. This hypothesis was explored during a 5-year survey (287 samples) conducted at a small spatial scale (;15km) in a temperate coastal ecosystem (eastern English Channel). Microscopy and flow cytometry quantified phytoplankton abundance and biomass, while metabarcoding data allowed an extended evaluation of diversity and the exploration of the ecological processes regulating phytoplankton using null model analysis. Alpha diversity of phytoplankton was governed by the effect of environmental conditions (environmental filtering). Temporal community turnover (beta diversity) evidenced a consistent interannual pattern that determined the phytoplankton seasonal structure. In winter and early spring (from January to March), determinism (homogeneous selection) was the major process in the phytoplankton community assembly. The overall mean in the year was 38%. Stochastic processes (ecological drift) prevailed during the rest of the year from April to December, where the overall mean for the year was 55%. The maximum values were recorded in late spring and summer, which often presented recurrent and transient monospecific phytoplankton peaks. Overall, the prevalence of stochastic processes rendered less predictable seasonal dynamics of phytoplankton communities to future environmental change.

IMPORTANCE While ecological deterministic processes are conducive to modeling, stochastic ones are far less predictable. Understanding the overall assembly processes of phytoplankton is critical in tracking and predicting future changes. The novelty of this study was that it addressed a long-posed question, on a pluriannual scale. Was seasonal phytoplankton succession influenced by deterministic processes (e.g., abiotic environment) or by stochastic ones (e.g., dispersal, or ecological drift)? Our results provided strong support for a seasonal and repeating pattern with stochastic processes (drift) prevailing during most of the year and periods with monospecific phytoplankton peaks.

with these perspectives, Vellend's conceptual framework [START_REF] Vellend | Conceptual synthesis in community ecology[END_REF] grouped four major ecological processes that drive species composition and diversity: selection, dispersal, speciation, and ecological drift. Selection refers to deterministic fitness differences between individuals of the same or different species, including environmental filtering and interactions among species (competition, predation, and facilitation). Dispersal is the movement of species across space, speciation is the generation of new genetic variation, and ecological drift represents random changes in species' relative abundance over time due to the inherent stochastic processes.

Assessing the relative importance of these processes has recently attracted the attention of microbial ecologists mostly in soil and freshwater environments by using concepts developed in terrestrial ecology (e.g., references [START_REF] Stegen | Stochastic and deterministic assembly processes in subsurface microbial communities[END_REF][START_REF] Wang | Phylogenetic beta diversity in bacterial assemblages across ecosystems: deterministic versus stochastic processes[END_REF][START_REF] Liu | Long-term nitrogen addition affects the phylogenetic turnover of soil microbial community responding to moisture pulse[END_REF][START_REF] Wu | Contrasting the relative importance of species sorting and dispersal limitation in shaping marine bacterial versus protist communities. 2[END_REF][START_REF] Aguilar | The balance between deterministic and stochastic processes in structuring lake bacterioplankton community over time[END_REF]). These studies revealed the concomitant action of deterministic and stochastic processes in shaping communities. Deterministic processes are related to environmental conditions such as nutrient availability [START_REF] Liu | Long-term nitrogen addition affects the phylogenetic turnover of soil microbial community responding to moisture pulse[END_REF], species traits or interactions (reference [START_REF] Zhou | Stochastic community assembly: does it matter in microbial ecology?[END_REF] and references therein), while stochastic processes that include inherent randomness are less predictable and related to dispersal mechanisms, drift, and speciation [START_REF] Vellend | Conceptual synthesis in community ecology[END_REF]. Most of the literature developing ecological theories (such as Hubbel et al. [START_REF] Hubbell | The Unified Neutral Theory of Biodiversity and Biogeography (MPB-32)[END_REF]) and the respective methodology derive from terrestrial ecology.

Historically, phytoplankton assemblages have been studied from a deterministic perspective based on their traits (e.g., [START_REF] Tilman | Phytoplankton community ecology: the role of limiting nutrients[END_REF][START_REF] Violle | Let the concept of trait be functional![END_REF]), and their environment [START_REF] Longobardi | Photoperiod-driven rhythms reveal multi-decadal stability of phytoplankton Phytoplankton Community Assembly Processes Microbiology Spectrum[END_REF]. However, deterministic processes in structuring phytoplankton communities [START_REF] Litchman | Trait-based community ecology of phytoplankton[END_REF] are insufficient to explain overall community structure and diversity patterns [START_REF] Behrenfeld | Phytoplankton biodiversity and the inverted paradox[END_REF]. Marine phytoplankton studies have been partly focused on stochastic (e.g., [START_REF] Chust | Latitudinal phytoplankton distribution and the neutral theory of biodiversity[END_REF] or dispersal processes (e.g., [START_REF] Spatharis | Everything is not everywhere: can marine compartments shape phytoplankton assemblages?[END_REF]). Yet, there is a need to understand how deterministic and stochastic processes potentially change in one ecosystem at different time scales [START_REF] Aguilar | The balance between deterministic and stochastic processes in structuring lake bacterioplankton community over time[END_REF][START_REF] Jia | Community assembly processes of the microbial rare biosphere[END_REF]. Two existing phytoplankton studies have quantified the relative contribution of both deterministic and stochastic processes focused on the large spatial scale [START_REF] Xu | Disentangling the ecological processes shaping the latitudinal pattern of phytoplankton communities in the Pacific Ocean[END_REF] or short periods (less than a year) [START_REF] Ramond | Phytoplankton taxonomic and functional diversity patterns across a coastal tidal front[END_REF]. However, the present study was the first to quantify both deterministic and stochastic phytoplankton assembly processes at a seasonal scale over a pluriannual sampling period.

Given the annual emergence of Phaeocystis globosa blooms and the high seasonal turnover in environmental conditions and phytoplankton, the eastern English Channel is a very suitable natural ecosystem to explore these ecological processes. It is a constantly mixed mesoeutrophic epicontinental sea, which has been undergoing anthropogenic disturbances since the last century [START_REF] Mclean | Functional reorganization of marine fish nurseries under climate warming[END_REF]. The nitrate enrichment with parallel silicate depletion in late winter promotes annual spring blooms of the Haptophyte Phaeocystis globosa [START_REF] Egge | Silicate as regulating nutrient in phytoplankton competition[END_REF][START_REF] Breton | Hydroclimatic modulation of diatom/Phaeocystis blooms in nutrient-enriched Belgian coastal waters (North Sea)[END_REF]. Yet, after the wane of the P. globosa bloom, the seasonal succession is also marked by the increase in abundance and biomass of other planktonic taxa, such as heterotrophic bacteria, reaching high abundances [START_REF] Lamy | Temporal changes of major bacterial groups and bacterial heterotrophic activity during a Phaeocystis globosa bloom in the eastern English Channel[END_REF], peaks of parasitic Syndiniales [START_REF] Christaki | Parasitic eukaryotes in a meso-eutrophic coastal system with marked phaeocystis globosa blooms[END_REF], diatoms [START_REF] Breton | Functional trait variation and nitrogen use efficiency in temperate coastal phytoplankton[END_REF], and dinoflagellates [START_REF] Gómez | The distribution and life cycle of the dinoflagellate Spatulodinium pseudonoctiluca (Dinophyceae, Noctilucales) in the northeastern English Channel[END_REF][START_REF] Gómez | The impact of the 2003 summer heat wave and the 2005 late cold wave on the phytoplankton in the north-eastern English Channel[END_REF].

Previous studies investigating drivers structuring planktonic communities in the eastern English Channel focused only on deterministic processes, such as intertaxon relations [START_REF] Genitsaris | Small-scale variability of protistan planktonic communities relative to environmental pressures and biotic interactions at two adjacent coastal stations[END_REF], environmental filtering [START_REF] Breton | Seasonal variations in the biodiversity, ecological strategy, and specialization of diatoms and copepods in a coastal system with phaeocystis blooms: the key role of trait trade-offs[END_REF], and predation [START_REF] Grattepanche | Succession of primary producers and micrograzers in a coastal ecosystem dominated by Phaeocystis globosa blooms[END_REF]. The present study aimed to explore the stochastic and deterministic ecological processes driving the seasonal organization of phytoplankton assemblages, and how these processes varied across seasons. We hypothesized that deterministic and stochastic ecological processes regulating phytoplankton, present seasonal and repeating patterns. For this, the seasonal diversity patterns combining morphological (i.e., counts by microscopy and flow cytometry) and metabarcoding (18S rRNA gene amplicon sequencing) data of phytoplankton obtained at five neighboring coastal stations in the eastern English Channel from 2016 to 2020 were investigated. Second, the phylogenetic structure (alpha diversity) and the phylogenetic turnover (beta diversity) in metabarcoding data using null models according to Stegen et al. [START_REF] Stegen | Stochastic and deterministic assembly processes in subsurface microbial communities[END_REF][START_REF] Stegen | Quantifying community assembly processes and identifying features that impose them[END_REF] were explored. Finally, considering the theoretical framework of Vellend [START_REF] Vellend | Conceptual synthesis in community ecology[END_REF], the relative importance of stochastic and deterministic ecological processes across seasons was quantified.

RESULTS

Seasonality of the environmental variables and phytoplankton communities. Before the quantification of ecological processes regulating the phytoplankton communities across seasons, the seasonal variations of the environment and the phytoplankton communities were investigated. The environmental variables and phytoplankton community composition measured in the eastern English Channel at the Service d9Observation en Milieu Littoral (SOMLIT) and DYnamique PHYtoplanctonique le long de la RADiale (DYPHYRAD) stations evidenced clear seasonal patterns from December 2016 to October 2020 that were typical of temperate marine waters. Wind stress, nutrients, and chlorophyll showed great variability across seasons (Table S4 in Supplemental File 1). Nutrient inputs originated mainly from local rivers and reached relatively high values during fall and winter (Fig. S2A in Supplemental File 1). For example, silicate concentrations recorded in winter were high (e.g., on average 5.9 6 1.9 mM in January), whereas values in spring and summer were low on average (e.g., 0.9 6 0.9 mM in June; Table S4 and Fig. S2A in Supplemental File 1). The N/P molar ratio varied greatly across seasons (from 0.4 to 316), and most of the time strongly deviated from the Redfield ratio ( 35), (N/P = 16; Table S4 in Supplemental File 1). A comparison of the mean ranks (Kruskal Wallis and Nemenyi post hoc test) of environmental variables between the different stations revealed significant differences in salinity, phosphate, silicate, and Chl-a between the stations (Fig. S2B in Supplemental File 1). However, the environmental variables were of the same range and showed the same seasonal variation at all stations (Fig. S2B in Supplemental File 1). Principal component analysis (PCA) performed on the environmental data set showed that the first two principal components contributed to 58% of the total variance (Fig. 1A). The first principal component (PC1, 39.2%) was mainly formed, in decreasing order, by phosphate, PAR, nitrite and nitrate, silicate, temperature, and wind stress, opposing winter and summer conditions (Fig. 1A; Fig. S2A in Supplemental File 1). The second principal component (PC2, 18.8%) was mainly formed by decreasing order by Chl-a, salinity, and temperature associated with spring and autumn. Overall, summer and autumn samples formed tighter groups on the PCA biplot than spring and winter samples, which were more dispersed (Fig. 2A).

The distance-based redundancy analysis (db-RDA) was applied to metabarcoding data of phytoplankton communities. The environmental variables showed that the first two axes explained 45% of the total variation in phytoplankton composition data (23% and 22% of the total variability for db-RDA1 and db-RDA2, respectively; Fig. 1B) with db-RDA1 and db-RDA2, highlighting a seasonal succession similar the PCA. The permutation test showed that PAR and temperature mainly contributed to the overall variability by 21% (P = 0.001) and 18% (P = 0.001), respectively, followed by nutrients (nearly 10%, P = 0.01; Table S5 in Supplemental File 1). Our study was one of the rare ones considering both morphological and metabarcoding data using a relatively large data set (287 samples). Accordingly, it was important to confront the two data sets and see if they showed similar trends because metabarcoding data were subjected to PCR biases and were always expressed in relative abundances while morphological data were absolute abundances. For this, the db-RDA was also applied to the microscopy data, which revealed similar seasonal trends (Fig. S3 in Supplemental File 1). The first two axes showed that the selected environmental variables explained nearly 37% of the total variation (db-RDA1, 24%; db-RDA2, 13%) in phytoplankton data. The permutation test showed that PAR (24%, P = 0.001), temperature (10%, P = 0.001), and nutrients (10%, P , 0.05) mainly contributed to the overall variability (Table S6 in Supplemental File 1).

Phytoplankton community inferred with metabarcoding and morphological data. Phytoplankton communities showed high variability in alpha diversity (Fig. 2A to D). The overall trend observed was decreasing richness, phylogenetic Faith's diversity (PD), and Shannon index from winter to spring, with the lowest observed values during the P. globosa spring bloom (April, May) and highest observed values in summer and autumn. Accordingly, the Simpson diversity index (1-D) showed the lowest values during the P. globosa spring bloom and relatively high values during the rest of the year (Fig. 2A to D). Based on morphological data (i.e., microscopy and cytometry counts), diatoms dominated the phytoplankton biomass (mean 55%) across all seasons except April to May, when the haptophyte P. globosa increased in biomass (42% and 28%, respectively, Fig. 3A). pico-nanophytoplankton (PicoNano) contributed 32% of the total biomass, while cryptophytes and dinoflagellates accounted for only 4% and 3% of the total phytoplankton biomass, respectively (Fig. 3A). Metabarcoding data also reflected the dominance of diatoms as relative read abundance (mean 60%) in the community and the Phaeocystis bloom in April and May (43% and 41%, respectively). PicoNano, cryptophytes, and dinoflagellates contributed 20%, 0.5%, and 6% of the mean relative read abundance, respectively (Fig. 3B). Furthermore, no significant differences were found among the stations for the number of reads, cell counts, and biomass of the different phytoplankton groups recorded in this study (Fig. S4 in Supplemental File 1).

Besides the P. globosa bloom in April and May (Fig. 4A), several important peaks belonging to different groups were observed in spring, summer, and autumn, in both data sets. In July 2016, the planktonic diatom Chaetoceros socialis reached a maximum value of 3.1 Â 10 6 cells L 21 (Fig. 4B, Fig. S5 in Supplemental File 1), which coincided with a relatively high number of Chaetoceros reads (32%, Fig. S5 in Supplemental File 1). In July 2017, Guinardia showed a relatively high number of reads (69%, Fig. S6 in Supplemental File 1) in contrast to low abundance (18 Â 10 3 cells L 21 ) in microscopy data. In June 2018, a peak of the pennate diatom Pseudonitzschia pungens, reached 4.8 Â 10 6 cells L 21 (Fig. 4B). The transient P. pungens peak was also clearly observed in metabarcoding data, reaching 73% of relative read abundance (Fig. S7 in Supplemental File 1). In addition, the centric diatom Leptocylindrus danicus marked diatom community structure also in June with a maximum concentration of 1.5 Â 10 6 cells L 21 in 2018 (Fig. 4B; S3 in Supplemental File 1 for biomass calculation). (B) From rarefied metabarcoding data (relative abundance as the percentage of reads of the ASVs).

Fig. S7 in Supplemental File 1) and was also abundant in June of 2019 and 2020 (Fig. 4A, Fig. S8 and S9 in Supplemental File 1). Dinoflagellates showed a peak in June 2018 (13.5 Â 10 3 cells L 21 , Fig. 4C) attributed to Prorocentrum minimum, which contributed up to 9% of the total relative abundance of reads (Fig. S7 in Supplemental File 1). PicoNano showed peaks of abundance generally in spring and summer, while the maximum abundance was recorded in September 2020 (35.4 Â 10 6 cells L 21 , Fig. 4D). According to metabarcoding, PicoNano was dominated by the coccolithophorid Emiliania and the nanoplanktonic diatom Minidiscus. Several peaks were observed in cryptophyte abundance in July 2016, 2018, and 2020. In 2016, peaks were also observed in April and September (Fig. 4E). Based on metabarcoding, the dominant cryptophyte was assigned to Plagioselmis.

Phylogenetic structure, temporal turnover, and ecological processes driving the phylogenetic phytoplankton community structure. Mantel correlograms correlating the phylogenetic distances to the niche distances at different distance classes detected significant positive correlations across short phylogenetic distances (,0.4 phylogenetic distance; Fig. S10 in Supplemental File 1). Except for salinity, all the evaluated environmental variables showed significant negative correlations over intermediate phylogenetic distances. These results supported that phylogenetic metrics can be applied to infer ecological assembly processes. Significant positive correlations across long phylogenetic distances were observed for PAR (nearly 0.8 phylogenetic distance; Fig. S10 in Supplemental File 1). Ecological processes governed the alpha diversity of phytoplankton (i.e., phylogenetic structure) were investigated using the net relatedness index (NRI). It showed that phylogenetic clustering prevailed during all seasons suggesting environmental filtering (NRI . 0, Table 1). The strongest values of phylogenetic clustering were detected from January to March (NRI . 3, Fig. 5). From April to July, NRI values showed a decreasing trend, indicating a tendency toward a weaker phylogenetic clustering at this time of the year. From September to December, NRI values showed again an increasing trend (Fig. 5).

To test if a phylogenetic structure (i.e., NRI) and turnover (i.e., bNRI) were attributed to different environmental variables a permutational multivariate analysis of variance (PERMANOVA) was applied. PAR and temperature were the only variables significantly linked with phytoplankton phylogenetic structure and phylogenetic turnover (Table S8 and S9 in Supplemental File 1; P , 0.001), although they explained a very small amount of the variance of the data set. Most of the variance remained unexplained with residuals presenting 67% and 87% for the phylogenetic structure and phylogenetic turnover (Table S8 and S9 in Supplemental File 1). 1). Solid black lines represent the median and black dots the mean. The different ecological processes, selection, dispersal, and drift were quantified using the null model analysis. The analysis applied to the entire data set showed that drift and homogeneous selection were the dominant ecological processes driving the seasonal succession of the phytoplankton community, contributing to 55% and 38%, respectively, over the entire period of study (Fig. 6A). Heterogeneous selection contributed weakly to the seasonal succession of the phytoplankton community (6%), and dispersal did not have any significant influence. The null model analysis applied additionally at the monthly scales showed three distinct patterns. First, phytoplankton succession in winterearly spring was dominated by homogeneous selection, contributing to 83%, 52%, and 54% of the assembly processes in January, February, and March, respectively. Second, spring and summer periods were mostly dominated by drift mechanisms (contributing from 69% to 87%, depending on the month). Third, autumn was dominated primarily by drift, contributing from 52% to 65% to the assembly processes with homogeneous selection accounting from 25% to 38% (Fig. 6B; Table S7 in Supplemental File 1).

DISCUSSION

Here, microscopy and flow cytometry allowed phytoplankton biomass to be quantified, while metabarcoding data provided an extended evaluation of its diversity. Alpha diversity of phytoplankton communities was regulated by environmental filtering. Drift, followed by homogeneous selection, were the major mechanisms regulating the temporal turnover in community composition (beta diversity) and prevailed across seasons. Three periods were evidenced, including (i) winter-early spring, with homogeneous selection as the major process regulating the phytoplankton communities, composed mainly of diatoms communities (e.g., Thalassiosira); (ii) spring-summer, with drift as the major process in community assembly during the bloom of P. globosa and during the transient peaks of various taxa (diatoms, dinoflagellates, and pico-nanophytoplankton); and (iii) autumn, with a combination of drift and homogeneous selection as a major ecological process in phytoplankton community assembly dominated by diatoms (Table 2). Overall, we evidenced that deterministic and stochastic ecological processes varied across seasons in alpha and beta diversity.

Seasonal diversity patterns. Overall, the relative abundance of the major phytoplankton groups inferred by metabarcoding was in good accordance with the relative carbon biomass inferred by morphological approaches for PicoNano and cryptophytes and to a lesser degree for diatoms (36) (Fig. 3). Moreover, the distance-based RDA analysis showed similar seasonal patterns in both data sets (Fig. 1B, Fig. S3 in Supplemental File 1).

The most abundant diatom taxa were common in both data sets. Three diatom taxa showed transient blooms in summer (June-July). The chain-forming centric diatom L. danicus had been previously reported in high abundances in the sampling area during summer [START_REF] Breton | Functional trait variation and nitrogen use efficiency in temperate coastal phytoplankton[END_REF][START_REF] Genitsaris | Seasonal variations of marine protist community structure based on taxon-specific traits using the eastern English Channel as a model coastal system[END_REF]. A good correspondence between a high number of reads and cell counts of Leptocylindrus has been reported also in the Gulf of Naples [START_REF] Piredda | Diatom diversity through HTS-metabarcoding in coastal European seas[END_REF]. The chain-forming diatom Pseudonitzschia is known to form dense blooms along the French coast of the eastern English Channel and is often a co-occurring species of the P. globose (reference [START_REF] Losos | Phylogenetic niche conservatism, phylogenetic signal and the relationship between phylogenetic relatedness and ecological similarity among species[END_REF] and references therein). The colony-forming diatom C. socialis observed in July has been reported in the English Channel in spring and summer [START_REF] Breton | Functional trait variation and nitrogen use efficiency in temperate coastal phytoplankton[END_REF][START_REF] Napoléon | Dynamics of phytoplankton diversity structure and primary productivity in the English Channel[END_REF].

Dinoflagellates are known to be overrepresented in sequencing data, and their use in numerical analysis can lead to important biases (e.g., references [START_REF] Medinger | Diversity in a hidden world: potential and limitation of next-generation sequencing for surveys of molecular diversity of eukaryotic microorganisms[END_REF][START_REF] Christaki | Microzooplankton diversity and potential role in carbon cycling of contrasting Southern Ocean productivity regimes[END_REF]). In this study, two small mixotrophic dinoflagellates (Gymnodinium and Prorocentrum) were included in the analysis because they were the only dinoflagellates to exhibit relatively high abundances in microscopy data, while they did not represent an exaggerated number of reads in metabarcoding data (Fig. 3,S4). Gymnodinium and Prorocentrum were prominent members of the protist community in previous studies in the eastern English Channel [START_REF] Grattepanche | Succession of primary producers and micrograzers in a coastal ecosystem dominated by Phaeocystis globosa blooms[END_REF][START_REF] Widdicombe | Longterm phytoplankton community dynamics in the Western English Channel[END_REF]. The genus Gymnodinium showed relatively stable cell numbers across seasons, while the species P. minimum showed a peak in 2018. Intense but brief blooms of P. minimum have been previously reported during the summer months in the Western English Channel [START_REF] Widdicombe | Longterm phytoplankton community dynamics in the Western English Channel[END_REF]. The P. globosa bloom in April and May was clear in both data sets. However, metabarcoding data evidenced the presence of low relative abundances of P. globosa all year long (Fig. 3B), which were not recorded by microscopy and cytometry because of its very low abundance. Piconanophytoplankton showed maximum concentrations also in summer reaching 2 Â 10 7 cells L 21 , and one in fall 3.5 Â 10 7 cells L 21 (43) (Fig. 4D).

Ecological processes shaping phytoplankton seasonal organization. The NRI index calculated for the whole phytoplankton community evidenced that the alpha diversity of phytoplankton communities was governed by environmental filtering (44) (Table 1 and4; Fig. 5). Environmental filtering was the effect of environmental conditions selecting those species capable of survival and persistence in a local environment [START_REF] Emerson | Phylogenetic analysis of community assembly and structure over space and time[END_REF][START_REF] Kraft | Community assembly, coexistence and the environmental filtering metaphor[END_REF], and it is known to play a major role in structuring marine phytoplankton communities [START_REF] Segura | Competition drives clumpy species coexistence in estuarine phytoplankton[END_REF][START_REF] Bottin | Diatom cooccurrence shows less segregation than predicted from niche modeling[END_REF][START_REF] Klais | Community assembly and drivers of phytoplankton functional structure[END_REF][START_REF] Burson | Stable coexistence of equivalent nutrient competitors through niche differentiation in the light spectrum[END_REF]. Phytoplankton communities, based on the phylogenetic temporal turnover (beta diversity), were assembled across seasons through a concomitant action of deterministic and stochastic processes. However, stochastic processes (i.e., drift) contributed far more than ecological selection to community assembly, except for winter and early spring (from January to March), when homogeneous selection regulated phytoplankton communities (Fig. 5 and6).

The dominance of homogeneous selection in winter and early spring was coherent with the strong environmental filtering conditions, such as the high nutrient concentration values, and low light availability recorded during this period (NRI . 4; Fig. 5A, see also Table 1 and2). Hence, homogenous selection has been seen as the selection of species with common and appropriate genomic architecture and metabolic strategies for surviving and persisting in a local environment (e.g., 51, 52) implying an increase in community similarity [START_REF] Stegen | Estimating and mapping ecological processes influencing microbial community assembly[END_REF]. This process dominated community assembly when environmental conditions were spatially homogenous (Fig. S2B in Supplemental File 1) [START_REF] Jia | Community assembly processes of the microbial rare biosphere[END_REF][START_REF] Stegen | Estimating and mapping ecological processes influencing microbial community assembly[END_REF]. In the geographic scale of our study (ca 15 km), the coastal waters of the eastern English Channel represented a homogeneous pool of phytoplankton taxa undergoing similar selection processes (Fig. 6,S4). The dominance of diatoms at this time of the year, mainly of the genus Thalassiosira, was coherent with the worldwide observations of diatoms thriving in light-limited, nutrient-enriched, and colder waters submitted to relatively high wind-driven turbulence [START_REF] Schapira | Temporal patterns of phytoplankton assemblages, size spectra and diversity during the wane of a Phaeocystis globosa spring bloom in hydrologically contrasted coastal waters[END_REF][START_REF] Armbrust | The life of diatoms in the world's oceans[END_REF]. Silica frustule and large centric vacuole are considered key traits for diatom success in winter and early spring for protecting against mechanical and haline shocks [START_REF] Logares | Infrequent marine-freshwater transitions in the microbial world[END_REF][START_REF] Hoef-Emden | Osmotolerance in the Cryptophyceae: jacks-of-alltrades in the Chroomonas clade[END_REF] and optimizing light affinity [START_REF] Hansen | The seasonal succession of optimal diatom traits[END_REF].

The prevalence of stochastic processes in phytoplankton community assembly in beta diversity was observed during the rest of the year (from April to December; Fig. 6 and Table 2). Maximum drift values were recorded in late spring and summer periods that presented monospecific phytoplankton peaks. This was coherent with the large quantity of unexplained variance between environmental variables and the phytoplankton community in terms of abundance, phylogenetic structure, and turnover (db-RDA and PERMANOVA, respectively). The dominance of drift was in accordance with a previous study quantifying the ecological processes in natural ecosystems using the same analytical approaches as the present study [START_REF] Logares | Contrasting prevalence of selection and drift in the community structuring of bacteria and microbial eukaryotes[END_REF]. These authors found that microeukaryotic communities were governed by drift (72%), while the relative contribution of selection and dispersal was low.

However, identifying the underlying mechanisms and factors favoring stochasticity was challenging. Hence, studies are still scarce, and detecting stochastic processes may suggest the lack of consideration of unmeasured environmental variables [START_REF] Zhou | Stochastic community assembly: does it matter in microbial ecology?[END_REF], as well as from a mixture of antagonistic processes [START_REF] Powell | Deterministic processes vary during community assembly for ecologically dissimilar taxa[END_REF]. Moreover, multiple factors may influence the relative importance of stochastic versus deterministic processes in community assembly, including predation [START_REF] Chase | Predators temper the relative importance of stochastic processes in the assembly of prey metacommunities[END_REF], productivity [START_REF] Chase | Stochastic community assembly causes higher biodiversity in more productive environments[END_REF], community size [START_REF] Orrock | Local community size mediates ecological drift and competition in metacommunities[END_REF], resource availability [START_REF] Kardol | Resource availability mediates the importance of priority effects in plant community assembly and ecosystem function[END_REF], as well as a disturbance [START_REF] Dini-Andreote | Disentangling mechanisms that mediate the balance between stochastic and deterministic processes in microbial succession[END_REF]. For example, predators can increase the importance of stochastic processes by reducing the number of individuals that can live in each environment and, thus, the community size by increasing the probability of species going extinct locally [START_REF] Chase | Predators temper the relative importance of stochastic processes in the assembly of prey metacommunities[END_REF]. Nonetheless, the minor role played by dispersal in shaping phytoplankton communities in this study area (Fig. 6) was coherent with the small spatial scale investigated (;15 km) (e.g., references [START_REF] Heino | Metacommunity organisation, spatial extent and dispersal in aquatic systems: patterns, processes and prospects[END_REF][START_REF] Logares | Disentangling the mechanisms shaping the surface ocean microbiota[END_REF]).

In this study, the continuous decrease in species richness observed from February to May (Fig. 2A) potentially suggests intense stress for the diatom community which, despite increasing light, faces silicate limitations during this period (Fig. S2A in Supplemental File 1) [START_REF] Breton | Hydroclimatic modulation of diatom/Phaeocystis blooms in nutrient-enriched Belgian coastal waters (North Sea)[END_REF]. This presumption of stress was reinforced by the low degree of silicification, and the decrease of the functional evenness observed by Breton et al. [START_REF] Breton | Seasonal variations in the biodiversity, ecological strategy, and specialization of diatoms and copepods in a coastal system with phaeocystis blooms: the key role of trait trade-offs[END_REF] in May. Note that functional evenness describes the evenness of abundance distribution in functional trait space [START_REF] Mason | Functional richness, functional evenness and functional divergence: the primary components of functional diversity[END_REF]. A decrease in functional evenness, which reflects underused parts of the niche [START_REF] Mason | Functional richness, functional evenness and functional divergence: the primary components of functional diversity[END_REF], is considered a fingerprint of disturbance [START_REF] Mouillot | A functional approach reveals community responses to disturbances[END_REF]. P. globosa, although it is a poor competitor for nitrate and has a lower maximum growth rate than diatoms [START_REF] Breton | Functional trait variation and nitrogen use efficiency in temperate coastal phytoplankton[END_REF] does not require silicate and thus it blooms under limiting silicate and excess nitrate in spring [START_REF] Lancelot | Autoecology of the Marine Haptophyte Phaeocystis sp[END_REF]. Phaeocystis has also a strong protection against grazing by forming colonies and may further benefit from the increased grazing of mesozooplankton on the microzooplankton, potential predators of Phaeocystis [START_REF] Grattepanche | Microzooplankton herbivory during the diatom-Phaeocystis spring succession in the eastern English Channel[END_REF].

Despite the relatively low nutrient levels after the P. globosa bloom, phytoplankton richness and PD values increased (Table 2) and several transient peaks belonging to different phylogenetic groups (diatoms, dinoflagellates, and PicoNano) appeared in summer (Fig. 4) [START_REF] Christaki | Parasitic eukaryotes in a meso-eutrophic coastal system with marked phaeocystis globosa blooms[END_REF]. This suggests that other mechanisms lowered the competitive exclusion in shaping phytoplankton communities at this time of the year. One plausible explanation is that the new niche opportunities that might have resulted from intense bacteria activity remineralizing the organic resource derived from P. globosa. This resource is recurrently released in May in the seawater [START_REF] Lamy | Temporal changes of major bacterial groups and bacterial heterotrophic activity during a Phaeocystis globosa bloom in the eastern English Channel[END_REF], and/or from the underused and vacant niches left open after the species loss at the end of the Phaeocystis bloom. Such a large input of dissolved organic material may be compared to large inputs of nutrients, which is typically considered a perturbation that favors ecological drift (5) through the enhanced growth of a variety of species and by reducing competition. Jurburg et al. [START_REF] Jurburg | Autogenic succession and deterministic recovery following disturbance in soil bacterial communities[END_REF] stated that ecological drift in soil microbial communities was due to niche enlargement after a perturbation. Mixotrophy typically reflects such a possibility [START_REF] Xu | Disentangling the ecological processes shaping the latitudinal pattern of phytoplankton communities in the Pacific Ocean[END_REF]. The dinoflagellate P. minimum showed that the peak in abundance in June was mixotrophic (Fig. 4B) [START_REF] Fan | Characterization of the affinity for nitrogen, uptake kinetics, and environmental relationships for Prorocentrum minimum in natural blooms and laboratory cultures[END_REF]. This species grows photosynthetically on inorganic nutrients but compensates for low concentrations of inorganic nitrogen by mixotrophic utilization of organic nitrogen and other compounds released at the end of P. globosa bloom. Other alternative strategies also exist, such as adaptation to high light levels. Indeed, the diatoms L. danicus and P. pungens are considered adapted to high light conditions [START_REF] Widdicombe | Longterm phytoplankton community dynamics in the Western English Channel[END_REF][START_REF] Polimene | Modelling a light-driven phytoplankton succession[END_REF], whereas PicoNano and cryptophytes, can acquire nutrients in low concentration; outcompeting larger cells for nutrient uptake [START_REF] Reynolds | Phytoplankton periodicity: the interactions of form, function and environmental variability[END_REF] due to the high surface/volume ratio reducing the "package effect" [START_REF] Finkel | Light absorption and size scaling of light-limited metabolism in marine diatoms[END_REF], and increasing nutrient diffusion (77), compared to larger cells. Overall, these specific adaptations provide a better efficiency for growth that is necessary for maintenance and ecological success during seasons with low nutrient and high light levels.

Autumn phytoplankton communities were subjected to the combined action of drift and selection processes. The local environment progressively increased the action of environmental filtering and, consequently, the contribution of homogeneous selection to community assembly increased (Fig. 5 and6, and Table 2). Nutrients became progressively available again, light and temperature diminished, while high turbulence values (wind stress as a proxy) enhanced physical mixing (Fig. S2 in Supplemental File 1). This could explain the high richness, diversity, and community characterized by large diatoms such as Thalassiosira sp. and Ditylium sp. (e.g., Fig. S7 in Supplemental File 1). Drift remained a major mechanism in autumn, potentially related to high grazing pressure in late summer-autumn [START_REF] Grattepanche | Succession of primary producers and micrograzers in a coastal ecosystem dominated by Phaeocystis globosa blooms[END_REF]. External forces such as wind stress and salinity showed high variability and extreme values particularly in September (Fig. S2 in Supplemental File 1), which seemed to be a transitional period between summer and autumn conditions (Fig. 1A; Fig. S2 andS3 in Supplemental File 1).

We acknowledge that there are several limitations to discuss. Inferring ecological processes based on phylogenetic metrics was challenging. The phylogenetic signal was required, which was detected in our study (Fig. S10 in Supplemental File 1). The phylogenetic signal has been confirmed in natural phytoplankton communities and based on evolutionary models ( 78), but the opposite has been demonstrated in an experimental study focused on eight species of freshwater green algae [START_REF] Narwani | Experimental evidence that evolutionary relatedness does not affect the ecological mechanisms of coexistence in freshwater green algae[END_REF]. However, our results present the overall action of ecological processes at the whole community level, and not on a particular taxonomic group. Different taxonomic classes may be structured by different processes [START_REF] Xu | Disentangling the ecological processes shaping the latitudinal pattern of phytoplankton communities in the Pacific Ocean[END_REF]. The sampling effort was also important. For example, in this study, only three samples were available for August. Thus, the results could not be interpreted (Fig. 6). Finally, the biases derived from PCR and sequencing may add bias in calculating the importance of the ecological processes in community assembly. Nonetheless, in this study, there was, which was discussed above. a relatively good correspondence between morphological and metabarcoding data. Molecular and morphological data are complementary but unfortunately are rarely considered together in actual marine planktonic studies, and this was one of the strong points of our work.

Concluding this study, null modeling based on phytoplankton metabarcoding data revealed that stochastic and deterministic processes present seasonal and repeating patterns. Our results provided strong support that, except for winter and early spring, the ecological drift prevailed during the rest of the year and the periods presented by recurrent and transient monospecific phytoplankton peaks. The prevalence of stochastic processes renders a priori the seasonal dynamics of phytoplankton communities less predictable. In this context, the exploration of ecological processes driving phytoplankton communities in the long term is critical in our understanding of pelagic ecosystems' response relative to environmental variability.

MATERIALS AND METHODS

Sampling strategy. Subsurface seawater (2 m depth) of five coastal stations along a ca. 15 km transect was sampled from March 2016 to October 2020 in the eastern English Channel (Fig. S1 in Supplemental File 1). During, the first 2 years, the S1 inshore station and the S2 offshore station of the SOMLIT monitoring network (https://www.somlit.fr/) were sampled on a bi-weekly basis. From 2018 to 2020 three stations were added: the coastal stations R1, R2, and the offshore station R4 from the local monitory transect DYPHYRAD. The sampling was carried out weekly and more intensively for some periods between 2018 and 2020. A total of 322 samples were gathered during 169 sampling campaigns at these five stations (Table S1 and S2 in Supplemental File 1).

Environmental variables. Sea surface temperature (T, °C) and salinity (S, PSU) were measured in situ with a CTD Seabird profiler. The average subsurface daily PAR experienced by phytoplankton in the water column for 6 days before sampling was obtained from global solar radiation (GSR, Wh m 22 ) as described in Breton et al., [START_REF] Breton | Seasonal variations in the biodiversity, ecological strategy, and specialization of diatoms and copepods in a coastal system with phaeocystis blooms: the key role of trait trade-offs[END_REF]. Wind stress (Pa) was calculated as described in Smith [START_REF] Smith | Coefficients for sea surface wind stress, heat flux, and wind profiles as a function of wind speed and temperature[END_REF]. In addition, seawater macronutrient concentrations were analyzed according to Aminot and Kérouel [START_REF] Aminot | Dissolved organic carbon, nitrogen and phosphorus in the N-E Atlantic and the N-W Mediterranean with particular reference to non-refractory fractions and degradation[END_REF]. Chlorophyll-a (Chl-a) concentration was measured by fluorometry as described in [START_REF] Lorenzen | A method for the continuous measurement of in vivo chlorophyll concentration[END_REF]. Additional details on environmental data acquisition and sample analysis can be found at https://www.somlit.fr/en/ and in Supplemental File 1.

Phytoplankton microscopic and cytometric counts (morphological data). For diatoms and P. globosa counting, 110 mL water samples were collected and fixed with Lugol's-glutaraldehyde solution (1% vol/vol). For dinoflagellates, another 110 mL was fixed with acid Lugol's solution (1% vol/vol) (data for dinoflagellates were available from February 16, 2018; Table S2 in Supplemental File 1). Phytoplankton was examined, when possible, to the species or genus level using an inverted Downloaded from https://journals.asm.org/journal/spectrum on 29 October 2023 by 2a01:e0a:402:41f0:3c48:d2da:1f6d:5951.

microscope (Nikon Eclipse TE2000-S) at Â400 magnification after sedimentation in a 10, 50, or 100 mL Hydrobios chamber, as described previously in Breton et al. [START_REF] Breton | Seasonal variations in the biodiversity, ecological strategy, and specialization of diatoms and copepods in a coastal system with phaeocystis blooms: the key role of trait trade-offs[END_REF]. The abundance of picophytoplankton and nanophytoplankton (PicoNano,0.2 to 20 mm) and cryptophytes were enumerated by flow cytometry with a CytoFlex cytometer (Beckman Coulter). For all samples, 4.5 mL was fixed with paraformaldehyde (PFA) at a final concentration of 1% and stored at 280°C until analysis [START_REF] Marie | Enumeration of Marine viruses in culture and natural samples by flow cytometry[END_REF]. Phytoplankton cells were detected according to the autofluorescence of their pigments (Chl-a, Phycoerythrin). P. globosa was discriminated from the PicoNano group based on orange fluorescence (Phycoerythrin, 496 nm).

Biovolumes for diatoms and cryptophytes, dinoflagellates, and P. globosa were estimated using an image analyzer system and standard geometric forms according to [START_REF] Hillebrand | Biovolume calculation for pelagic and benthic microalgae[END_REF]. Then, the carbon-biovolume relationships were estimated following prior studies (85-87) (see Table S3 in Supplemental File 1 for details).

DNA barcoding. For DNA extraction 4 to 7 L of seawater was filtered on 0.2 mm polyethersulfone (PES) membrane filters (142 mm, Millipore, U.S.A.) after a prefiltration step through 150 mm nylon mesh (Millipore, U.S.A.) to remove metazoans. All filters were stored at 280°C for 18S rRNA genes amplicon Illumina MiSeq sequencing. A quarter of the PES filter was used for DNA extraction following the DNAeasy PowerSoil Pro kit (Qiagen, Germany) manufacturer's protocol. The 18S rRNA gene V4 region was amplified using EK-565F (50-GCAGTTAAAAAGCTCGTAGT) and UNonMet (50-TTTAA GTTTCAGCCTTGCG) primers [START_REF] Bower | Preferential PCR amplification of parasitic protistan small Subunit rDNA from metazoan tissues[END_REF]. Pooled purified amplicons were then paired-end sequenced on an Illumina MiSeq 2 Â 300 platform. Quality filtering of reads, identification of amplicon sequencing variants (ASV), and taxonomic affiliation based on the PR2 database were done in the R-package DADA2 [START_REF] Guillou | The Protist Ribosomal Reference database (PR2): a catalog of unicellular eukaryote small sub-unit rRNA sequences with curated taxonomy[END_REF][START_REF] Callahan | DADA2: high-resolution sample inference from Illumina amplicon data. 7[END_REF].

A total number of 41,179 ASVs were identified from 6,366,087 reads in 287 samples, containing Metazoa, Streptophyta, Excavata, Alveolata, Amoebozoa, Apusozoa, Archaeoplastida, Hacrobia, Opisthokonta, Rhizaria, and Stramenopiles. For this study, only ASVs affiliated with Hacrobia, Stramenopiles, and Archaeoplastida were kept. In addition, mixotrophic dinoflagellates ASVs related to Gymnodinium and Prorocentrum were considered for their ecological importance. Gymnodinium is known to dominate dinoflagellate abundance and biomass in the eastern English Channel (33), while Prorocentrum showed a momentary increase in this study. Unaffiliated eukaryotic ASVs, singletons, and doubletons were removed, obtaining a final phyloseq object containing 6,471 ASVs corresponding to 2,448,955 reads, in 287 samples. The data set was rarefied to the lowest number of reads (1,020), resulting in 274,380 reads corresponding to 4,141 ASVs from 269 samples.

Diversity, statistical, and community assembly analyses. To describe the phytoplankton communities, the alpha diversity and Faith's phylogenetic diversity indices were calculated. Kruskal-Wallis and the post hoc Nemenyi test were used to test if phytoplankton groups significantly differ among stations. To explore and summarize seasonal variations in the abiotic environment the multivariate principal component analysis (PCA) was performed. Distance-based RDA analysis was applied considering morphological and metabarcoding data. All analysis was performed in R [START_REF] Team | R: a language and environment for statistical computing[END_REF].

To infer ecological assembly processes governing alpha and beta diversity, null models based on metabarcoding data were applied according to the framework by Stegen et al. [START_REF] Stegen | Stochastic and deterministic assembly processes in subsurface microbial communities[END_REF][START_REF] Stegen | Quantifying community assembly processes and identifying features that impose them[END_REF] and reviewed by Zhou and Ning [START_REF] Zhou | Stochastic community assembly: does it matter in microbial ecology?[END_REF]. All tests presented here were applied according to this framework. Briefly, the community assembly analysis was based on the comparison of observed community turnovers (shifts in composition across samples), phylogenetic turnovers (shifts in composition weighted by the phylogenetic similarity between taxa), and turnovers expected by chance (in null models), to estimate whether the differences between pairs of communities were explained by dispersal, selection, or ecological drift. According to phylogenetic community composition (alpha diversity) within each sample, the phylogenetic structure was divided into environmental filtering and overdispersion, which were deterministic processes (Table 1). Based on phylogenetic turnover in community composition (beta diversity), deterministic processes were divided into homogeneous selection (i.e., consistent environmental factors cause low compositional turnover) and heterogeneous selection (i.e., high compositional turnover caused by shifts in environmental factors). However, stochastic processes were divided into homogeneous dispersal (i.e., low compositional turnover caused by high dispersal rates), dispersal limitation (i.e., high compositional turnover caused by a low rate of dispersal), and ecological drift that can result from fluctuations in population sizes due to chance events (7, 34, and 47; Table 1). The implicit hypothesis was that phylogenetic conservatism exists, which means that ecological similarity between taxa was related to their phylogenetic similarity (i.e., phylogenetic signal) [START_REF] Losos | Phylogenetic niche conservatism, phylogenetic signal and the relationship between phylogenetic relatedness and ecological similarity among species[END_REF]. Mantel correlograms were applied to detect phylogenetic signals, which correlate the phylogenetic distances to the niche distances at different distance classes (e.g., references [START_REF] Liu | Long-term nitrogen addition affects the phylogenetic turnover of soil microbial community responding to moisture pulse[END_REF][START_REF] Doherty | The transition from stochastic to deterministic bacterial community assembly during permafrost thaw succession[END_REF]; further information in Supplemental File 1). Significant positive correlations indicate that ecological similarity among ASVs was higher than expected by chance within the distance class. Alternatively, significant negative correlations indicated that ASVs were more ecologically dissimilar than expected by chance. Here, the cal_mantel_corr function in the microeco package was used [START_REF] Liu | microeco: an R package for data mining in microbial community ecology[END_REF].

To characterize if alpha diversity (i.e., phylogenetic structure) of phytoplankton was governed by environmental filtering or overdispersion we used the NRI index (nearest related index, see also Table 1). For this, first, the phylogenetic metric MPD (mean pairwise distance) was calculated as it considers the mean phylogenetic distance among all pairs of species within a community [START_REF] Webb | Phylogenies and Community Ecology[END_REF]. Phylogenetic structure (alpha diversity) was then assessed by the NRI for each community with null models based on 999 randomizations with the random shuffling of the phylogenetic tree labels with MicrobiotaProcess package v.1.5.4.990 (i.e., the get_NRI_NTI function). The NRI index was obtained by multiplying the standardized effect size of the mean pairwise phylogenetic distance by 21.

The phylogenetic temporal turnover between pairwise communities among sampling dates (beta diversity) was quantified to investigate the action of deterministic and stochastic ecological processes with microeco R package v.0.6.0 (93), using the trans_nullmodel function. The phylogenetic distance Downloaded from https://journals.asm.org/journal/spectrum on 29 October 2023 by 2a01:e0a:402:41f0:3c48:d2da:1f6d:5951.

between pairwise communities (beta mean pairwise distance [bMPD]) was computed with null models based on 999 randomizations with the random shuffling of the phylogenetic tree labels as in Stegen et al. [START_REF] Stegen | Quantifying community assembly processes and identifying features that impose them[END_REF]. The bNRI was calculated via the z score, as the difference between the observed bMPD and the mean of the bMPD null models divided by the standard deviation of the null models. bNRI scores less than 22 indicate that the observed phylogenetic turnover was significantly lower than ;95% of the null values and thus that homogeneous selection between the compared communities causes higher than expected phylogenetic similarity. Similarly, bNRI scores greater than 12 indicate the dominance of heterogeneous selection. The Raup-Crick distances based on the Bray-Curtis similarity (RC bray ) were also calculated to further differentiate the stochastic processes structuring the community assembly when bNRI scores varied between 22 and 12 [START_REF] Stegen | Quantifying community assembly processes and identifying features that impose them[END_REF][START_REF] Chase | Using null models to disentangle variation in community dissimilarity from variation in a-diversity[END_REF]. Values, of RC bray less than 20.95 or greater than 0.95 indicate less and more compositional turnover, respectively, than the null expectation and that was attributed to homogeneous dispersal in the former case and dispersal limitation in the latter. All definitions of the different assembly processes corresponding to the values of NRI and bNRI were shown in Table 1. Nonweighted metrics were used as metabarcoding data were semiquantitative and the rarefied data set was considered to prevent any bias due to potential under-sampling [START_REF] Ramond | Phytoplankton taxonomic and functional diversity patterns across a coastal tidal front[END_REF]. The analysis in August has not been considered for further discussion in the present study because of insufficient sampling (i.e., only three samples).

To evaluate whether a phylogenetic structure (i.e., NRI) and turnover (i.e., bNRI) were attributed to different environmental variables a permutational multivariate analysis of variance (PERMANOVA) was performed based on the Bray-Curtis distance.

FIG 1 (

 1 FIG 1 (A) Principal-component analysis (PCA) illustrating the variations of the environmental variables (arrows) at all sampling dates (colored points with the size corresponding to the cos2 values of the PCA); photosynthetic active radiation (PAR, E m 22 d 21 ), temperature (T, o C), salinity (S, PSU), nitrite and nitrate (NO 2 1NO 3 mM), silicate (Si[OH] 4 , mM), phosphate (PO 4 , mM), chlorophyll-a (Chl-a, mg L 21 ), rainfall (Kg m 22 ), wind stress (Pa). The table on the bottom left represents the percentage of the contribution of the different environmental variables in the building of the PCA axis. The most important contributors are in bold. (B) Distance-based redundancy (db-RDA) ordination illustrating the variations of the phytoplankton communities, based on metabarcoding data, (samples, colored dots) in relation to the environmental variables (black arrows) in the eastern English Channel at the DYPHYRAD and SOMLIT stations from March 2016 to October 2020.

FIG 2

 2 FIG 2 Alpha diversity of the phytoplankton communities based on metabarcoding data collected in the eastern English Channel at the DYPHYRAD and SOMLIT stations from March 2016 to October 2020. (A) Richness, (B) PD, Faith's phylogenetic diversity, and the (C) Shannon and (D) Simpson (1-D) indices. Solid black lines represent the median, black dots the mean, colored dots the samples according to stations, and the black stars the outliers.

FIG 3

 3 FIG 3 Phytoplankton community structure in the eastern English Channel at the DYPHYRAD and SOMLIT stations from March 2016 to October 2020. (A) From microscopy and cytometry (relative biomass as a percentage of carbon, see TableS3in Supplemental File 1 for biomass calculation). (B) From rarefied metabarcoding data (relative abundance as the percentage of reads of the ASVs).

FIG 4 6

 46 FIG 4 Abundance (cells L 21 ) of the phytoplankton groups identified in the eastern English Channel at the SOMLIT and DYPHYRAD stations from March 2016 to October 2020 based on microscopy and flow cytometry data. (A) P. globosa, (B) diatoms, (C) dinoflagellates (Gymnodinium and Prorocentrum), (D) PicoNano, and (D) cryptophytes. No data were available from 2016 to 2017 for dinoflagellates and all phytoplankton from February 14, 2020 to May 20, 2020 because of the sanitary crisis). Solid black lines represent the median, black dots the mean, and the black stars the outliers.

FIG 5

 5 FIG 5 Phylogenetic structure (alpha diversity) of the phytoplankton community in the eastern English Channel at the DYPHYRAD and SOMLIT stations from March 2016 to October 2020 based on metabarcoding data. Phylogenetic structure based on the net relatedness index (NRI) with NRI . 0 and NRI , 0 suggested phylogenetic clustering and overdispersion, respectively (see Table1). Solid black lines represent the median and black dots the mean.

FIG 6

 6 FIG 6 The relative importance of the ecological processes (beta diversity) driving phytoplankton communities in the eastern English Channel at the DYPHYRAD and SOMLIT stations from March 2016 to October 2020. A: considering the whole data set, B: data discriminated per month. *, only three samples were available for August, so the data was not interpretable.

TABLE 1

 1 Definitions of the different assembly processes, and respective model conditions referenced from Webb et al.[START_REF] Webb | Phylogenies and Community Ecology[END_REF], Stegen et al.[START_REF] Stegen | Stochastic and deterministic assembly processes in subsurface microbial communities[END_REF][START_REF] Stegen | Quantifying community assembly processes and identifying features that impose them[END_REF], and Zhou and Ning[START_REF] Zhou | Stochastic community assembly: does it matter in microbial ecology?[END_REF]

	Phytoplankton Community Assembly Processes									Microbiology Spectrum
											Drift	Population size fluctuates due to	chance events			20.95 , RC bray , 0.95
											Homogeneous dispersal	High rate of movement of	an individual from one	location to another		RC bray , 20.95
	Stochastic processes										Dispersal limitation	Movement of an individual	was restricted		22 , bNRI , 2	RC bray . 0.95
			Phylogenetic overdispersion	Competitive exclusion,	resulting in limiting	similarity (overdispersion)			NRI , 0		Heterogeneous selection	Shifts in environmental	factors cause a high	compositional turnover	bNRI . 2	-
	Deterministic processes	Alpha diversity	Phylogenetic clustering	Environmental conditions, selecting	those species capable of survival	and persistence in a local	environment (environmental	filtering)	NRI . 0	Beta diversity	Homogeneous selection	Consistent environmental factors	cause a low compositional	turnover	bNRI , 22	-
	Process	Diversity	Clustering	Definition					Phylogenetic structure index	Diversity	Selection, Dispersal, Drift	Definition			Phylogenetic turnover index	Taxonomic turnover index

November/December 2022 Volume 10 Issue 6 10.1128/spectrum.02427-22 7

TABLE 2

 2 Summary of the seasonal characteristics of the phytoplankton community in coastal waters of the eastern English Channel a

		Median in entire
		dataset	January-March	April-July	September-December
	Dominant phytoplankton		Thalassiosira sp.	Phaeocystis globosa, Chaetoceros	Thalasiossira sp.,
	(morphological and			socialis, Leptocilyndrus danicus,	Ditylum sp.,
	metabarcoding)			Pseudonitzschia pungens,	piconanophyto-
				Prorocentrum minimum,	plankton
				PicoNano
	PAR (E m 22 d 21 )	60.8	Low (35.5)	High (84.9)	Low (41.7)
	T (°C)	15	Low (7.7)	Moderate (15.2)	Moderate (16.5)
	NO 2 1NO 3	1.0	High (4.3)	Low (0.5)	Moderate (1.3)
	Si(OH) 4	1.3	High (2.9)	Low (0.8)	Moderate (1.8)
	PO 4	0.2	High (0.4)	Low (0.1)	Moderate (0.2)
	Wind stress (Pa)	0.04	High (0.1)	Moderate (0.04)	High (0.1)
	Rainfall (Kg m 2 )	1.3	Moderate (1.1)	Low (0.8)	High (2.0)
	Richness	272	Low (213)	Low (218)	High (361)
	Taxonomic alpha diversity (Shannon)	3.4	High (3.5)	Low (2.5)	High (3.8)
	Ecological processes (Alpha diversity)	1.4	Environmental filtering (3.1) Environmental filtering (0.8)	Environmental
					filtering (1.5)
	Ecological processes (Beta diversity)		Homogeneous selection	Drift	Drift1Homogeneous
					selection

a The median values are given in parentheses. The relative terms "High," "Moderate," and "Low" refer to the median of the entire data set. Phytoplankton Community Assembly Processes Microbiology Spectrum November/December 2022 Volume 10 Issue 6 10.1128/spectrum.02427-22 9

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November/December 2022 Volume 10 Issue 6 10.1128/spectrum.02427-22

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ACKNOWLEDGMENTS

We thank the captain and the crew of the RV 'Sepia II'; M. Crouvoisier for nutrient analysis; V. Cornille and E. Lecuyer for help with the fieldwork; E. Goberville for meteorological data; and P. Magee for English proofing. We thank the SCoSI/ULCO (Service COmmun du Système d'Information de l'Université du Littoral Côte d'Opale) for providing us with the computational resources to run all the bioinformatic analyses via the CALCULCO computing platform (https://www-calculco.univ-littoral.fr/). We also thank the reviewers for their comments and suggestions that helped to improve our manuscript.

This work was logistically supported by the national monitoring network SOMLIT (https://www.somlit.fr/) and funded by the CPER MARCO (https://marco.univ-littoral.fr/) and the French Research program of INSU-CNRS via the LEFE-EC2CO 'PLANKTON PARTY' and the OFB through the INDIGENE project. DIS was funded via a PhD grant by the 'Region des Hauts de France' and the 'Pôle métropolitain de la Côte d'Opale (PMCO)'.

We declare that all authors of the manuscript do not have any conflict of interest.

Data availability. Raw sequencing data have been submitted to the Short Read Archive under BioProject number PRJNA851611.

SUPPLEMENTAL MATERIAL

Supplemental material is available online only. SUPPLEMENTAL FILE 1, PDF file, 1.3 MB.


Simon Manceau

Andrea Fanesi

Julia Mougin

Julien Deschamps

Filipa Lopez

Romain Briandet

Introduction Motility caracterisation:

-Position -Swimming parameters (speed, length, duration…) -Mean square displacement -Straightness index CLSM Acquisitions 30 minutes after inoculation:

Cylindrotheca closterium

Growth medium : f/2 3 days adhesion

Materials and Methods

Culture of microalgae biofilms

Culture of swimming bacteria:

Bacillus thuringiensis Bt407-GFP Growth medium : TSB DO 600nm = 0,4

Bacteria tracking at the bottom of the wells

Biofilm biovolume extraction

Biovolume over time

Results

Conclusion

Some Bacillus biofilms have been shown to spontaneously contain a subpopulation of motile bacteria capable of navigating through the matrix in three dimensions (Houry et al., 2012). These swimming bacteria vascularize the biofilms and facilitate the penetration of specific substances to the deeper layers. Microalgae are rich in molecules of interest, and are at the heart of the challenges of the 21st century. Their biofilm culture is attracting growing interest due to their high productivity potential. In this innovative study, the aim is to characterize Bacillus swimming in a Cylindrotheca closterium biofilm using swimming bacilli to further increase biomass productivity.

The swimmers criss-cross a biofilm of bacteria, but are they capable of vascularizing a biofilm of microalgae, given that these microorganisms are at least three times larger? Using confocal microscopy (CLSM), an experimental method was developed to study the swimming of these bacilli. Although the microalgae biofilm becomes thicker with increasing matrix production (Fanesi et al., 2019), Bacillus swimming is still observable. Precise characterization of the swimmers requires further optimization and trajectory analyses. Control mean speed (16 μm.s -1 ) > Biofilm mean speed (13 μm.s -1 ) There is a decrease in the number of bacteria over time.

Normalized Mean Speed Time (days)

1 2 3 1 2 3 4 5
Track Length (μm)

1 2 3 4 5 Time (days)
There is no decrease in mean speed over time.

Track Length in control < Track Length in biofilm This project, at the convergence of the fields of biofilms, microalgae and bacterial motility, has demonstrated the remarkable ability of bacilli to move within the matrix of a microalgal biofilm. However, the swimmers used have a reduced average speed of movement, more confined trajectories and a reduced number of swimmers observed at the bottom of the well. This is consistent with the increased biovolume of the C. closterium biofilm and its substantial thickening. This groundbreaking study highlights the heterogeneity of this phenomenon in a complex biofilm. The impact of biofilm vascularization by bacteria swimming through the matrix has not yet been assessed. Exploring these vascularization phenomena could encourage the entry of nutrients or the release of molecules such as O 2 trapped in biofilms, and thus promote their growth.

  (> 5 days) C. closterium(> 3 weeks)