Seasonal Bottom-Up and Top-Down Control of Plankton in a Hypereutrophic Macrotidal Lagoon on Brazil’s Equatorial Coast

Seasonal Bottom-Up and Top-Down Control of Plankton in a Hypereutrophic Macrotidal Lagoon on Brazil’s Equatorial Coast | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Seasonal Bottom-Up and Top-Down Control of Plankton in a Hypereutrophic Macrotidal Lagoon on Brazil’s Equatorial Coast Marco Valério Jansen Cutrim, Yago Bruno Silveira Nunes, Ana Karoline Duarte dos Santos Sá, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7546980/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 16 Mar, 2026 Read the published version in Environmental Monitoring and Assessment → Version 1 posted 9 You are reading this latest preprint version Abstract Tropical coastal lagoons often show pronounced seasonal forcing that modulates nutrient supply, light climate, and grazer pressure. We surveyed hypereutrophic Jansen Lagoon (São Luís Island, Brazil) in four campaigns during 2017 (rainy: March–April; dry: September–November) at nine near-surface stations sampled on ebb tide. Phytoplankton were enumerated by the Utermöhl method; mesozooplankton were collected with a 120-µm net; and nutrients and chlorophyll-a were measured by UV–Vis spectrophotometry. Clustering and nMDS revealed clear rainy–dry segregation of communities, and dbRDA linked dry-season samples to higher salinity, turbidity, TP, and silicate, whereas rainy-season samples were associated with higher dissolved oxygen, Secchi depth, ammonium, and DIN. Generalized linear models explained 65% of phytoplankton variance: density increased with DIP and decreased with dissolved oxygen and with the rotifer Filinia longiseta , indicating concurrent bottom-up (nutrients, light/renewal) and top-down (grazing) controls. Microcystis wesenbergii and M. aeruginosa exhibited frequent peaks, underscoring eutrophic risk, though values remained below the bloom threshold applied here. Overall, bottom-up control predominated in the rainy season, whereas grazer pressure intensified in the dry season. Management should couple nutrient-load reductions with measures that shorten residence time, reduce resuspension, and restore macrophytes, with priority to urban margins and semi-enclosed embayments; routine tracking of DO percent saturation, DIN/DIP, Secchi depth, and chlorophyll-a is recommended for long-term assessment. community ordination cyanobacteria bioindicators grazing pressure nutrient enrichment Figures Figure 1 Figure 2 Figure 3 Introduction Coastal lagoons are shallow water bodies separated from the sea by natural or artificial barriers. Their physicochemical conditions, especially salinity, shift quickly over space and time under seasonal forcing and human influence (Sadat-Noori et al., 2016 ; Cruz et al., 2018 ). As interfaces between land and ocean, they support nutrient cycling, carbon processing, and biodiversity (Pérez-Ruzafa et al., 2019 ). Changes in salinity, oxygen, nutrients, and light ripple through food webs, altering community structure and ecosystem function (Paturej et al., 2017 ; Gamito et al., 2019 ). In tropical cities, lagoons face mounting pressure from population growth and insufficient wastewater treatment. Nutrient enrichment drives eutrophication, the accumulation of nitrogen and phosphorus, harmful algal proliferation, and hypoxia (Paerl, 2009 ; Domingues et al., 2017 ; Béjaoui et al., 2018 ). Plankton respond quickly to these shifts and are widely used to diagnose contamination and trophic state (Casé et al., 2008 ; Gamito et al., 2019 ). Zooplankton, the main grazers on algae, are sensitive to food quality and quantity, which shape their composition, growth, and reproduction (Sipaúba-Tavares & Bachion, 2002 ). In eutrophic waters, cyanobacteria often dominate and can suppress grazing through filamentous forms (Fulton & Paerl, 1987 ), toxicity (Fulton & Paerl, 1988 ), and poor nutritional value (Von Elert & Wolffrom, 2001 ). Filaments may even clog filtering structures (DeMott et al., 2001 ), tipping competition toward cyanobacteria and away from edible algae (Gragnani et al., 1999 ). Understanding this zooplankton–phytoplankton interplay is central to understanding how eutrophication unfolds. In Brazil, most lagoon studies still focus on subtropical, heavily impacted systems—e.g., Lagoa Rodrigo de Freitas (Rio de Janeiro)—where eutrophication has reshaped zooplankton (Souza et al., 2011 ). Work in tropical lagoons along the equatorial margin remains scarce. The Mundaú–Manguaba complex has revealed how nutrients and salinity structure zooplankton (Luz et al., 2022 ). Farther north, fewer lagoons and fewer studies exist; at Jansen Lagoon (Maranhão), recent research already points to strong urban and eutrophication signals (Cutrim et al., 2019 ). Worldwide, findings from eutrophic lakes support the value of zooplankton as sensitive indicators of water quality (García-Chicote et al., 2019 ; Muñoz-Colmenares et al., 2021 ). Here, we examine spatial and seasonal plankton dynamics in an urban, hypereutrophic tropical lagoon on Brazil’s equatorial coast. We (i) describe zooplankton and phytoplankton across seasons and stations; (ii) test links between nutrients, salinity, oxygen, light and phytoplankton (bottom-up control); and (iii) evaluate whether grazer groups exert top-down effects. To our knowledge, this is the first comprehensive account of zooplankton in this lagoon and a needed baseline for management in highly pressured tropical urban waters. Materials and methods Study area and sampling stations Jansen Lagoon is a coastal lagoon formed by damming Ana Jansen Creek. It spans ~ 140 ha, averages ~ 1.5 m in depth, and is bordered east by mangrove forest (Cutrim et al., 2019 ). The lagoon is in the northwestern sector of São Luís Island, northern Brazil, near 02°29′08″ S; 044°18′02″ W (Fig. 1 ). It connects to São Marcos Bay via the Ana Jansen stream and is influenced by semidiurnal macrotides that can exceed 4 m ( Dados Maregráficos e Fluviométricos | CHM ). To represent the principal environmental settings, we established nine stations (L1–L9) along gradients of marine influence, urban inputs, hydrodynamic retention, and macrophyte cover (WGS84, DMS). L1 (02°30′03′′S 44°18′18′′W) is in the southwest area of the lagoon, which is influenced by a supply of salt water from the São Marcos Bay. Southern estuarine station L9 (02°30′03″ S; 44°18′18″ W) marks the transition to São Marcos Bay. L2 (02°30′16″ S; 44°18′21″ W), L3 (02°30′23″ S; 44°18′13″ W), and L7 (02°30′08″ S; 44°18′11″ W) lie on urban shores receiving domestic sewage, where the organic load and turbidity are typically relatively high. L4 (02°30′19″ S; 44°18′04″ W) and L6 (02°30′23″ S; 44°18′39″ W) are semienclosed embayments with reduced water exchange and degraded mangrove stands ( Rhizophora mangle , Avicennia germinans ) prone to local stagnation. L5 (02°30′06″ S; 044°18′32″ W) represents the central body of the lagoon near a mangrove islet, and L8 (02°30′23″ S; 044°18′32″ W) lies in a reach dominated by submersed macrophytes ( Ruppia maritima ). Sampling design Sampling was conducted during ebb tide for four months in 2017—March and April (rainy season) and September and November (dry season). All plankton and environmental measurements were taken from the surface layer (~ 0.5 m) to ensure consistency. To standardize tidal influence, we sampled within an ~ 2 h window around mid-ebb, scheduling each campaign with DHN/CHM (Diretoria de Hidrografia e Navegação/Dados Maregráficos e Fluviométricos | CHM) tide tables and noting the local time and tidal stage at every station, and the order of stations was kept constant across campaigns to limit temporal drift. Zooplankton sampling and analysis Zooplankton were collected with horizontal subsurface tows (~ 0.5 m depth) via a 120 µm plankton net coupled to a General Oceanics® flowmeter. At each station, we performed two replicate tows, each lasting 3–5 minutes (adjusted to local hydrodynamics and debris). The samples were immediately preserved in buffered formaldehyde (4% final). We used a flowmeter to compute the filtered volume (m³) and standardized the abundances to ind. m⁻³. If a tow was compromised (air entrainment, net clogging, or flowmeter failure), we discarded it and repeated the process. In the laboratory, we identified organisms to the lowest feasible taxonomic level under compound and stereomicroscopes. Rotifers and nauplii were counted in a Sedgwick–Rafter chamber (400×); copepodites and adults were counted in open chambers under a stereomicroscope. With regard to taxonomic classification, specialized classification systems (identification keys) were used for each organism. Why a 120 µm mesh? The lagoon is eutrophic–hypereutrophic and frequently turbid, especially during ebb, when suspended solids and filamentous/coccoid algae increase the risk of net clogging. A finer mesh (e.g., 64 µm) would markedly reduce the filtered volume and compromise between-station comparability under these conditions. Using 120 µm prioritizes mesozooplankton (copepodites/adults)—key agents of top-down grazing—and yields adequate, reproducible volumes across stations. As a trade-off, microzooplankton and small rotifers are underrepresented; therefore, our consumer–producer inferences refer to top-down pressure by mesozooplankton captured with the 120 µm net, and their magnitude should be considered conservative relative to whole-community grazing. Phytoplankton sampling and analysis For phytoplankton, we collected 250 mL of subsurface water with a Van Dorn bottle and preserved the samples with Lugol’s iodine (~ 1% v/v). Counts followed Utermöhl ( 1958 ) at 400×. We enumerated at least 100 fields per sample and calculated the number of cells L⁻¹ via Villafañe & Reid ( 1995 ). The taxonomy was updated with Guiry & Guiry, 2020. We considered a bloom as ≥ 1×10⁶ cells L⁻¹ for a given taxon (Livingston, 2007 ). Environmental variables, nutrients, and chlorophyll-a The in situ measurements included temperature, salinity, and pH at ~ 0.5 m using a multiparameter probe (HI-9828, Hanna®; calibrated daily), turbidity (NTU) measured with a portable turbidimeter (model 2020), and Secchi depth (20 cm white disk) recorded before any disturbance to the water column. For nutrients, we collected 2 L of surface water (~ 0.5 m), stored the samples on ice, and processed them as soon as possible (typically within 6–8 h). We computed DIN as NH₄⁺-N + NO₂⁻-N + NO₃⁻-N and DIP as PO₄³⁻-P; we also measured TP and dissolved silicate (SiO₂-Si). The methods followed APHA ( 2012 ) and classical colorimetry (Koroleff, 1983 ; Strickland & Parsons, 1972 ; Grasshoff et al., 1983 ), with results in µmol L⁻¹. For chlorophyll-a (Chll-a), we analyzed two technical replicates per station: 250 mL was filtered on GF/F (0.7 µm), extracted in 90% acetone under low light, and read on a UV‒Vis spectrophotometer (Thermo Scientific Evolution™ 201). The concentrations (µg L⁻¹) were determined via the Parsons–Strickland equations, as described by Strickland & Parsons ( 1972 ). Each batch included procedural blanks. Exclusion criteria and QA/QC We excluded samples when (i) the flowmeter malfunctioned or the tow was aborted/clogged, (ii) field metadata were incomplete, or (iii) laboratory QC failed (e.g., replicate divergence beyond acceptance limits). All exclusions and reasons were documented. Before every campaign, the probe underwent calibration and was subsequently checked for drift. Readings outside the acceptable range were taken again. For nutrients, each campaign included field duplicates and reagent blanks; fresh 5-point calibration curves (R² ≥ 0.995) were prepared, with detection limits derived from low-level standards and blanks; and spikes or certified materials confirmed acceptable recoveries. For Chl-a, we compared replicates, handled extracts cold and dark, and applied an acidification step to correct for pheophytin; outliers were re-extracted or flagged. Diversity indices and statistical analyses We computed species richness (Margalef), diversity (Shannon–Wiener) and evenness (Pielou) from relative abundances in PAST v3. Indices were calculated per sample after standardization (zooplankton: ind. m⁻³; phytoplankton: cells L⁻¹). Before hypothesis testing, we assessed distributions with Shapiro–Wilk (normality) and Levene’s tests (homogeneity). When assumptions were not met, we applied log₁₀ transformation. We used two-way ANOVA for normally distributed, homoscedastic data and the Kruskal‒Wallis test otherwise, with α = 0.05. To identify seasonal indicators, we applied the indicator value (IndVal) (Dufrêne & Legendre, 1997 ) to zooplankton abundances grouped by season (rainy vs. dry), considering that p < 0.05 was significant (permutation tests). We explored the relationships between community structure and environmental drivers via distance-based redundancy analysis (dbRDA). The community data were square-root transformed; we used Bray–Curtis dissimilarities and centered and scaled the environmental predictors. We evaluated the canonical model and axes with permutation tests (n = 999). Given the selectivity of the zooplankton gear (120-µm mesh focusing on mesozooplankton), predictors derived from zooplankton were interpreted as mesozooplankton proxies. To assess robustness to collinearity and size-selective sampling, we additionally fit a VIF-filtered GLM (retaining predictors with a VIF ≤ 10) to log₁₀-transformed phytoplankton density (Gaussian, identity link). Results Physical, chemical, and biological variables of Jansen Lagoon The physicochemical summary is shown in Table 1 . The water temperature varied modestly across the campaigns (25.5–26.5°C), differing between seasons (two-way ANOVA, F = 4.26, p < 0.001) but not among the stations. Salinity is markedly greater in the dry season than in the rainy season and varies significantly between seasons (ANOVA, F = 13.8, p < 0.001). Dissolved oxygen (DO) also differs seasonally (ANOVA, F = 13.01, p < 0.0001), reaching its lowest values in the dry months. Nutrients display clear seasonality: DIN is dominated by NH₄⁺ (~ 85%), whereas DIP is greater in the dry season. The community indices are consistently greater in the rainy season, zooplankton show greater diversity and richness with high evenness, and phytoplankton follow the same pattern; all the seasonal contrasts are significant (Table 1 ). Table 1 Seasonal means (± SDs) of physicochemical and biological variables in Jansen Lagoon (rainy vs. dry; 2017; surface ≈ 0.5 m; ebb tide). F gives the test statistic from two-way ANOVA; where assumptions were not met, the Kruskal–Wallis result is reported for seasonal contrast (see Methods). Asterisks denote significant seasonal differences (*p < 0.05). Abbreviations: DO = dissolved oxygen; DIN = dissolved inorganic nitrogen (NH₄⁺ + NO₂⁻ + NO₃⁻); DIP = dissolved inorganic phosphorus (PO₄³⁻–P); TP = total phosphorus; SiO₂ = dissolved silicate; Chll-a = chlorophyll-a. Variables Rainy Dry F p Depth (m) 0.93 ± 0.32 0.67 ± 0.41 2.47 < 0.001* Secchi (m) 0.83 ± 0.18 0.44 ± 0.19 41.46 < 0.001* Temperature (°C) 25.50 ± 0.92 26.56 ± 0.49 4.26 < 0.001* pH 8.73 ± 0.25 8.96 ± 0.03 6.63 < 0.001* Salinity 6.11 ± 1.45 31.77 ± 2.52 13.78 < 0.001* Turbidity (NTU) 9.01 ± 2.47 34.03 ± 22.39 23.54 0.011 DO (mg L − 1 ) 2.97 ± 1.28 1.10 ± 0.24 13.01 < 0.001* NO − 2 (µmol L − 1 ) 0.09 ± 0.09 0.15 ± 0.05 7.59 < 0.001* NH + 4 (µmol L − 1 ) 43.92 ± 72.26 9.38 ± 2.78 6.76 < 0.001* NO − 3 (µmol L − 1 ) 2.86 ± 2.50 6.03 ± 6.40 4.67 0.035 DIN (µmol L − 1 ) 44.02 ± 72.25 15.57 ± 7.23 7.89 0.006 DIP (µmol L − 1 ) 0.25 ± 0.28 0.52 ± 0.24 6.62 < 0.001* SiO 2 (µmol L − 1 ) 1.01 ± 0.29 4.05 ± 0.67 16.83 < 0.001* TP (µmol L − 1 ) 4.25 ± 2.44 3.91 ± 1.00 24.83 < 0.001* Chll-a (µg L − 1 ) 80.19 ± 61.63 246.25 ± 40.70 52.03 < 0.001* Phytoplanktonic Diversity (bits cells − 1 ) 0.96 ± 0.46 1.03 ± 0.18 11.12 < 0.001* Phytoplanktonic Richness (bits cells − 1 ) 1.53 ± 0.19 0.92 ± 0.23 3.12 < 0.001* Phytoplanktonic Evenness 0.30 ± 0.16 0.38 ± 0.11 83.15 < 0.001* Zooplankton Diversity (bits cells − 1 ) 0.87 ± 0.05 0.85 ± 0.02 114.9 < 0.001* Zooplankton Richness (bits cells − 1 ) 10.28 ± 7.71 2.12 ± 0.25 98.44 < 0.001* Zooplankton Evenness 0.83 ± 0.76 0.83 ± 0.03 27.51 < 0.001* Planktonic community composition The zooplankton community comprised twenty-five taxa, dominated by rotifers (57.0% of taxa) and copepods (23.8%), with protozoans and tintinnids contributing 9.5% each. During the rainy season, rotifers and tintinnids occur at all stations (100% occurrence). In the dry season, tintinnids were absent, and several rotifer and copepod taxa also dropped out of the assemblage (Table 2 ). IndVal analysis identified a suite of indicators spanning both seasons (e.g., Brachionus plicatilis , B.angularis , Attheyella fuhrmanni , Harpacticoida, Filinia longiseta , Hexarthra mira , Lepadella sp., and Paracalanus crassirostris ), as detailed in Table 2 . Table 2 Abundance, occurrence total, and IndVal values for zooplankton taxa in Jansen Lagoon. Legend : ABU – Abundance; TO – Total Occurrence; * Indicators species according to Indval values (IndVal > 25%). Rainy Dry IndVal p ABU (org m³) TO (%) ABU (org m³) TO (%) TINTINIDAE Favella ehrenbergi 0.07 0.05 - - 11.11 0.0001 Tintinnopsis compressa 0.03 0.05 - - 11.11 0.0001 ROTIFERA Asplanchna sieboldin 1.10 4.25 38.89 0.96 100 0.4229 Brachionus angularis* 3.73 4.89 339.61 6.27 100 0.0401 Brachionus calyciflorus 1.84 2.39 13.89 0.12 66.66 0.2381 Brachionus plicatilis* 13.19 17.10 1,583.53 26.17 100 0.019 Brachionus urceolaris 4.56 4.41 426.39 6.63 100 0.0790 Colurella deflexa 2.11 2.87 107.99 1.48 100 0.3651 Colurella sp* 0.15 0.42 - - 33.33 0.0058 Euchlanis dilatata f. lucksiana 4.81 4.35 568.75 6.83 100 0.3033 Filinia longiseta* 3.78 3.98 0.74 0.08 100 0.0279 Hexarthra mira 9.95 13.12 - - 88.88 0.0982 Leocane lunaris 0.15 4.20 15.63 0.60 88.88 0.0777 Lepadella sp 0.19 2.81 - - 77.77 0.3843 COPEPODA Apocyclops panamensis* 0.65 4.35 379.54 7.27 100 0.0008 Acanthocyclops sp 0.12 2.07 - - 100 0.2356 Atheylla fuhrmanni* 0.49 6.80 696.40 13.03 100 0.0004 Paracalanus crassirostris 0.79 3.08 - - 100 0.0670 Harpacticoida * 1.18 7.59 460.94 9.95 100 0.0038 Copepodites/nauplii 11.72 9.77 894.79 14.27 100 0.8443 PROTOZOA Difflugia sp - 0.53 125.05 2.44 100 0.2245 Arcella sp - - 95.16 2.04 100 0.0716 OTHERS Nematoda 0.02 0.37 87,50 1.08 77.77 0.1224 Polychaeta Larvae* 0.07 0.37 29,94 0.44 55.55 0.0036 Polychaeta (Phyllodocidae) - 0.16 23,26 0.32 55.55 0.2167 TOTAL 60.70 100.00 6,915.89 100.00 - - The phytoplankton community included 74 taxa distributed among Cyanophyta (47.30%), Bacillariophyta (37.84%), Chlorophyta (8.11%), Euglenophyta (1.52%), and Dinophyta (1.35%). The highest densities occurred in the rainy season at L6 (48.66 × 10³ cells L⁻¹) and L5 (42.06 × 10³ cells L⁻¹), and the phytoplankton density varied significantly across seasons and among stations (p < 0.05). Microcystis spp. dominate Cyanobacteria; Cyclotella meneghiniana peaks in the rainy season at L1 (2.56 × 10³ cells L⁻¹) and L6 (1.05 × 10³ cells L⁻¹). M. weisenbergii peaked during the dry season at almost all stations except L9, where it ranged from 1.40 × 10³ cells L⁻¹ (L3) to 23.34 × 10³ cells L⁻¹ (L7) in the rainy season. M.aeruginosa also peaked at most stations in the dry season (absent at L9), from 1.30 × 10³ cells L⁻¹ (L5) to 18.05 × 10³ cells L⁻¹ (L4) and reached relatively high values in the rainy season (up to 46.16 × 10³ cells L⁻¹ at L6, minimum 9.00 × 10³ cells L⁻¹ at L7). Table 3 Mean abundance of zooplankton (org.m 3 ) and density of phytoplankton (cell L − 1 ) communities, respectively, in Jansen Lagoon by sampling point and seasonal period. Zooplankton Community Phytoplankton Community Rainy Dry F p Rainy Dry F p L1 0.97 71.80 0.25 < 0.001 25,823 x 10 3 17,074 x 10 3 3.03 < 0.001 L2 0.52 750.00 0.27 < 0.001 20,995 x 10 3 9,051 x 10 3 2.60 < 0.001 L3 1.19 848.96 4.66 < 0.001 16,535 x 10 3 5,523 x 10 3 2.33 < 0.001 L4 11.37 253.13 3.07 < 0.001 23,784 x 10 3 40,221x 10 3 3.30 < 0.001 L5 1.32 1,038.19 7.14 < 0.001 42,058 x 10 3 4,283 x 10 3 2.41 < 0.001 L6 2.55 264.58 3.85 < 0.001 48,666 x 10 3 35,006 x 10 3 2.65 < 0.001 L7 33.44 2,328.13 8.59 < 0.001 16,899 x 10 3 33,567 x 10 3 3.44 < 0.001 L8 6.92 590.28 6.27 < 0.001 25,847 x 10 3 17,192 x 10 3 2.40 < 0.001 L9 2.42 781.25 6.03 < 0.001 6,738 x 10 3 702.70 x 10 3 3.43 < 0.001 Total 60.70 6,926. 31 - - 241,218 x 10 3 162,63 x10 3 X ± SD 6.74 ± 10.01 769.59 ± 627.94 26,802 ± 15,04x10 3 18,07 ± 14,79x10 3 Factors affecting the planktonic community Modeling phytoplankton density as the response, the stepwise-backward GLM explained 65% of the variance (adjusted R² = 0.65; Table 4 ). Within this model, density decreased with increasing dissolved oxygen content (β = −0.94 ± 0.17, p < 0.001) and with F.longiseta (β = −0.36 ± 0.13, p = 0.017) and increased with DIP (β = 0.46 ± 0.16, p = 0.012). The coefficient for B.plicatilis was also negative (β = −3.58 ± 1.32, p = 0.016), but its tolerance was extremely low (T = 0.0077; VIF ≈ 129), indicating severe collinearity and warranting caution in interpretation. The other predictors were not significant (p > 0.05). Table 4 Generalized linear model (GLM) for phytoplankton density in Jansen Lagoon via stepwise backward selection. Reported are standardized coefficients (β), standard error (SE), t = β/SE, (T), p values, the variance inflation factor (VIF), and significance. The final model (adjusted R² = 0.65) identified dissolved oxygen (DO), DIP (PO₄³⁻–P), Brachionus plicatilis and Filinia longiseta as significant predictors (α = 0.05). Predictors with a VIF > 10 are flagged for collinearity. Significance : ***p < 0.001, * p 10) Dissolved oxygen (DO) -0.943 0.172 -5.483 0.000064 2.214 *** No Salinity -0.067 0.257 -0.261 0.798961 4.925 No DIP (PO 4 3− -P) 0.458 0.160 2.863 0.011936 1.908 * No Brachionus angularis 0.407 0.647 0.629 0.538675 31.152 Yes Brachionus plicatilis -3.575 1.319 -2.710 0.016086 129.514 * Yes Filinia longiseta -0.356 0.132 -2.697 0.016592 1.296 * No Polychaeta larvae 0.822 0.446 1.843 0.085109 14.814 Yes Colurella sp. -0.153 0.125 -1.224 0.237561 1.159 No Harpacticoida -1.028 0.555 -1.852 0.083711 22.942 Yes Attheyella fuhrmanni 0.651 0.536 1.215 0.243252 21.414 Yes Total zooplankton abundance 2.132 1.358 1.570 0.137425 137.418 Yes For Synechococcus sp., the abundance increased with Attheyella fuhrmani (β = 0.65, p = 0.007) and Polychaeta larvae (β = 0.82, p = 0.06) and with DO (β = 1.06, p = 0.004), yielding an adjusted R² = 0.69. For Chroococcus turgidus , the best-fitting model (adjusted R² = 0.75) included Colurella sp. (β = −0.15, p = 0.86), DO (β = −0.94, p = 0.45), salinity (β = −0.06, p = 0.20) and a negative association with chlorophyll-a (β = −0.51, p = 0.03); among these, only Chl-a was statistically supported at α = 0.05. Seasonal structure and indicator patterns Hierarchical clustering (Bray–Curtis on square–root–transformed data, group-average linkage) and nMDS both reveal a clear seasonal separation of communities (Fig. 2 a, b). The dendrogram (Fig. 2 a) resolves two coherent clusters, with all rainy-season samples in GI and all dry-season samples in GII. The nMDS (Fig. 2 b; stress = 0.01) corroborates this split, with rainy samples forming a tight cluster on the left and dry samples a compact cluster on the right. Notably, L1Dry plots at the edge of the dry cluster, and L8Rainy lies farthest from the rainy centroid, indicating modest within-season heterogeneity. This multivariate pattern is consistent with the univariate contrasts and with the environmental gradients highlighted by the dbRDA. Indicator patterns mirrored this seasonal partitioning. Dry-season dominance was observed for B.plicatilis , B.angularis , A.fuhrmanni , Polychaeta larvae, Harpacticoida, and A. panamensis , with a marked peak at L7. In contrast, F. longiseta , H. mira , Lepadella sp., and P.crassirostris were more common and achieved higher IndVal—during the rainy season (Fig. 3 ). The bubble overlays on the nMDS (stress = 0.01; panel-specific abundance scales) reinforce the seasonal split seen in the dendrogram. The dry-season samples contained the largest bubbles for B.plicatilis , B.angularis , A.fuhrmanni , Polychaeta larvae, Harpacticoida and A.panamensis , with a clear maximum at L7Dry and secondary peaks around L3–L5Dry. In contrast, F. longiseta is primarily associated with the rainy-season cluster—most notably at L8Rainy, with a single high value at L1Dry; Colurella sp. was consistently rare in both seasons. Overall, taxa with higher abundances in the dry cluster track the conditions identified for the dry period (higher salinity and DIP/SiO₂), whereas those concentrated in the rainy cluster align with higher DO and DIN, which is consistent with the dbRDA patterns. (Fig. 3 ) The dbRDA captured 38.68% of the adjusted variation, with axis 1 = 26.54% and axis 2 = 12.14% (Fig. 3 ). The dry-season side of the gradient was associated with relatively high salinity, temperature, pH, turbidity, TP, and silicate contents, grouping taxa such as B.plicatilis , B.angularis , B.urceolaris , E.dilatata f. lucksiana , Difflugia sp., Protozoa sp., and Phyllodocidae. Conversely, the rainy season side was associated with greater DO, Secchi depth, ammonium, and DIN concentrations, and Lepadella sp., F.longiseta , and P.crassirostris were associated with these conditions. Top-down and bottom-up controls on plankton. Across stations and seasons, phytoplankton responded to the resource supply, which was consistent with bottom-up control. In the GLM, DIP is a positive predictor of phytoplankton density (β = 0.46, p = 0.012; GLM table), and the rainy season side of the ordinations aligns with DIN (NH₄⁺, DIN vector) and greater water transparency (Secchi) (Fig. 2 b; Fig. 3 ). Although DIP tends to be greater in the dry period (Table 1 ), peak phytoplankton densities occur in the rainy season (e.g., L5–L6), suggesting that light availability and reduced salinity modulate nutrient signals. Concurrently, several lines of evidence indicate top-down grazing. The GLM retained the negative partial effects of F.longiseta (β = −0.36, p = 0.017) and B.plicatilis (β = −3.58, p = 0.016; severe collinearity for the latter), which was consistent with rotifer grazing pressure on phytoplankton (GLM table). Indicator analyses and bubble overlays revealed dry-season dominance of grazing taxa, B.plicatilis, B.angularis, A.fuhrmanni , Harpacticoida, and Polychaeta larvae, with maxima at L7Dry (Fig. 3 ), which coincided with the dry cluster characterized by higher salinity and DIP/SiO₂ (Fig. 2 a, b). Together, these patterns are consistent with a seasonally shifting balance in which bottom-up drivers (nutrients/light) favor phytoplankton in the rainy season, whereas top-down pressure by zooplankton (and potentially light limitation via turbidity) constrains phytoplankton in the dry season. Collectively, these results indicate that top-down pressure is exerted by mesozooplankton captured with the 120-µm net. Because microzooplankton are undersampled, the magnitude of consumer effects reported here should be considered conservative. Discussion 1. Seasonal context in a hypereutrophic lagoon Seasonality structured the system sharply. The dry-season waters presented higher salinity and DIP from evaporation and reduced freshwater input, whereas the rainy-season waters presented higher DO and DIN (NH₄⁺) and greater water renewal (Table 1 ). Despite the DIP peak in the dry period, the phytoplankton density and diversity were greater in the rainy season than in the dry period, which was consistent with the higher Secchi and lower salinity in the dry period (Fig. 2 a, b). Similar seasonal forcings have been reported for tropical coastal lagoons (e.g., Branco et al., 2008 ; Delgadillo-Hinojosa et al., 2008 ; Maia-Barbosa et al., 2014 ). More broadly, coastal lagoons exhibit pronounced spatiotemporal gradients, especially in terms of salinity and nutrients, under strong anthropogenic pressure; these gradients are primary vectors shaping plankton distributions and indicator species selection (Hemraj et al., 2017 ), a rationale fully consistent with our results. In macrotidal settings, tidal pumping can further reorganize zooplankton structure across the tidal cycle, reinforcing the seasonal signal (Krumme & Liang, 2004 ). 2. Bottom-up control: nutrients, light, and flushing Two lines of evidence point to bottom-up forcing. First, the GLM identified DIP as a positive predictor of phytoplankton (β = 0.46, p = 0.012; Table 3 ). Second, the rainy season samples plotted toward higher DIN and a better light climate (greater Secchi) in the ordinations (Fig. 2 b). Together, these results explain why phytoplankton increased in the rainy months even with lower DIP: light availability, nitrogen supply, and flushing appear to unlock growth under better-oxygenated conditions, a pattern consistent with lagoon studies using plankton as bioindicators (Hemraj et al., 2017 ). Although tropical Brazil does not experience a classical monsoon, the ITCZ-driven rainy season delivers comparable freshwater and nutrient pulses that reorganize salinity, turbidity, and residence time. In a monsoon-forced tropical bay (Marudu Bay, Malaysia), increases in nitrate triggered centric-diatom blooms ( Chaetoceros , Bacteriastrum ), whereas high ammonium suppressed them; high silica favored pennate diatoms, and silica depletion rapidly terminated blooms; additionally, high zooplankton abundance limited bloom development toward the end of the wet phase. These mechanisms provide a useful analogue for our system, helping to explain why rainy-season nutrient inputs and flushing structure phytoplankton composition and bloom dynamics here. (Tan & Ransangan, 2017 ) 3. Top-down control: grazer pressure and consumer structure Evidence for top-down regulation has also emerged. The GLM revealed negative partial effects of F.longiseta (β = −0.36, p = 0.017) and B.plicatilis (β = −3.58, p = 0.016; high collinearity noted) on phytoplankton (Table 3 ), which was consistent with rotifer grazing. The nMDS results highlighted the dry-season dominance of grazing taxa, B.plicatilis , B.angularis , A.fuhrmanni , Harpacticoida, and Polychaeta larvae, with a clear maximum at L7 (Fig. 3 ). This consumer–producer coupling aligns with evidence that zooplankton can modulate phytoplankton, water transparence, and nutrients (Bess et al., 2021). Ecologically, B.plicatilis is well known for its tolerance to eutrophic conditions and broad salinity range (Arcifa et al., 1994 ; Sládeček, 1983 ; Castilho Noll et al., 2023 ), supporting its ecological success here. Collectively, these results indicate that top-down pressure is exerted by mesozooplankton captured with the 120-µm net. Because microzooplankton were undersampled, the magnitude of consumer effects reported here should be considered conservative. Seasonal dilution experiments in the monsoon-driven Chilika Lagoon (India) demonstrate that microzooplankton frequently remove a large share of phytoplankton standing stock and production (often g/k > 1). These findings indicate strong top-down regulation in eutrophic–mesohaline waters (Singh et al., 2025 ). 4. Cyanobacteria, oxygen stress and feedback Frequent peaks of M.wesenbergii and M.aeruginosa fit the lagoon’s eutrophic status (Imai et al., 2008; Li & Xiao, 2016 ). Although counts remained below the bloom threshold defined in Methods (≥ 10⁶ cells L⁻¹), such density peaks can depress DO through respiration and decay, reinforcing hypoxia and favoring smaller grazers over larger zooplankton, feedback widely reported for eutrophic systems (Guenther et al., 2015 ). These conditions, together with cyanobacterial interference, are known to disadvantage larger crustacean grazers while favoring rotifers (Ghadouani et al., 2003 ; Jiang et al., 2017 ). 5. Community–environment coupling across seasons Multivariate analyses converge on the same mechanism. Clusters and nMDS separated the samples cleanly into rainy and dry seasons (Fig. 2 a, b). The dbRDA linked the dry side to salinity, temperature, pH, turbidity, TP and silicate, grouping rotifers ( Brachionus spp.), harpacticoids and protozoans; the rainy side aligned with DO, Secchi, NH₄⁺ and DIN, associating Lepadella sp., F.longiseta and P.crassirostris (Fig. 3 ). This mirrors lagoon bioindicator literature that links environmental gradients to predictable community responses (Hemraj et al., 2017 ). Land-use signals likely reinforce these patterns at urban margins, as shown for functional zooplankton guilds in Amazon streams (Bomfim et al., 2023 ). 6. Management implications Mitigation should act on both sides of this balance. Nutrient load reduction (DIP and DIN from domestic sewage) is necessary but insufficient if the residence time and turbidity remain high. Actions that improve hydrological connectivity and reduce resuspension, combined with macrophyte restoration to increase nutrient uptake and habitat complexity, are likely to yield greater, more durable improvements (Branco et al., 2008 ; Derolez et al., 2019 ; Martín et al., 2020 ; Derolez et al., 2020 ). Spatial priorities include urban margins (L2, L3, L7) and semienclosed embayments (L4, L6), where loading and retention are strongest. In macrotidal systems, management should also consider tide-driven community shifts that can amplify or dampen intervention outcomes (Krumme & Liang, 2004 ). For urban lagoon monitoring, we recommend a network of fixed stations at priority sites (urban margins and semi-enclosed embayments) plus a downstream reference, instrumented with high-frequency sondes (DO, temperature, EC/salinity, turbidity, chlorophyll-a fluorescence) at 10–60 min intervals. Monthly baseline sampling should be complemented by event-triggered campaigns after major rainfall, and by tide-stratified sampling (neap/spring) to capture mixing effects. A core indicator set—DIN, DIP, Secchi depth, chlorophyll-a, DO percent saturation—and plankton bioindicators (e.g., Brachionus spp., F. longiseta ) can provide early-warning signals of eutrophication risk. Intervention performance should be tested with BACI designs against pre-defined thresholds (e.g., DO < 2 mg L⁻¹; cyanotoxins above WHO guidance), under a documented QA/QC protocol (sensor calibration, fouling control, uncertainty). Publishing near-real-time data to a public dashboard supports adaptive management and stakeholder accountability. 7. Methodological considerations and future work Interpretation is bounded by (i) collinearity in parts of the GLM (notably for B.plicatilis ; VIF > 10), (ii) the 120-µm mesh, which undersamples microzooplankton and small rotifers, and (iii) temporal resolution (four campaigns). A reduced model excluding predictors with a VIF > 10 retained the core effects (DO−, DIP+, − F.longiseta ), suggesting robustness. Future work should include multimesh sampling and explicit microzooplankton/protistan grazing assays, given the growing evidence that microzooplankton can exert strong top-down control on phytoplankton size-structure and productivity, together with higher-frequency time series to resolve short-term pulses of mixing, light, and nutrients. Where feasible, coupling to hydrodynamic/tidal sampling designs can clarify renewal effects (Krumme & Liang, 2004 ). Conclusion Jansen Lagoon clearly features rainy–dry partitioning of plankton communities typical of hypereutrophic, tidally influenced systems. Across analyses, phytoplankton responded to bottom-up drivers (DIP, DIN, light/clarity, flushing), whereas top-down pressure from small grazers, especially rotifers, intensified in the dry season. The higher phytoplankton density and diversity in the rainy months, together with the negative partial effects of key grazers in the GLM and the seasonal separation in the ordinations, indicate a seasonally shifting balance: bottom-up control predominates during the rainy period, whereas top-down control predominates during the dry period. The peaks of Microcystis spp. (below the bloom threshold used here) and low DO at times underscore the system’s sensitivity to nutrient pulses and residence time. Management should therefore couple nutrient load reductions (DIP and DIN from domestic sewage) with measures that affect hydrodynamics and the light climate, improving water renewal, reducing turbidity/resuspension, and restoring macrophytes to increase nutrient uptake and habitat complexity. Spatial priorities include urban margins (e.g., L2, L3, and L7) and semienclosed embayments (L4 and L6), where loading and retention are strongest. Routine tracking of DIP/DIN, Secchi, and DO, paired with indicator taxa (e.g., Brachionus spp., F.longiseta ), can serve as an early warning framework for ecological risk. Declarations Author contribution All authors contributed to the conception and design of the study. Data collection and research design were carried out by Marco Cutrim, Yago B. S. Nunes and Jordana A. Furtado. Data analysis and interpretations were performed by Yago B. S. Nunes and Jordana A. Furtado. The first draft of the manuscript was written by Yago B. S. Nunes, Ana K.D. dos Santos-Sá, Quedyane Cruz, and Marco V.J. Cutrim, and all authors provided comments on previous versions of the manuscript. The final version was reviewed by Marco V.J. Cutrim and Andrea C.G. Azevedo-Cutrim, with additional intellectual contributions to improve the final version of the manuscript. Funding No funding was received to assist with the preparation of this manuscript. 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Limnology and Oceanography , 46 , 1552–1558. https://doi.org/10.4319/lo.2001.46.6.1552 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 16 Mar, 2026 Read the published version in Environmental Monitoring and Assessment → Version 1 posted Editorial decision: Revision requested 14 Oct, 2025 Reviews received at journal 14 Oct, 2025 Reviews received at journal 02 Oct, 2025 Reviewers agreed at journal 25 Sep, 2025 Reviewers agreed at journal 25 Sep, 2025 Reviewers invited by journal 24 Sep, 2025 Editor assigned by journal 12 Sep, 2025 Submission checks completed at journal 12 Sep, 2025 First submitted to journal 05 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Cutrim","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyklEQVRIiWNgGAWjYHADxgaGDwxyQAYPkRp4gFoYZzAYk6SFgYGZhxgtuu1nH374wGCXuF/6cOtm2zaDaP4G3mMf8GkxO5NuLDmDITmxhy+x7XZum0HujAN8yTPwajmQxgZ0z4HEHh5GkJY/uQ0HeIzxOszs/DMkLZZAW+YT1HID2RZGoJYNhLU8Y5acYZBs3HOGse1mzzmD3I2H+ZIJOCyN8cOHCjvZ9h72Zzd+lBnkzjveexivFggwQOYwE6FhFIyCUTAKRgF+AACFBEXur/y08QAAAABJRU5ErkJggg==","orcid":"","institution":"Federal University of Maranhão (UFMA) – São Luís","correspondingAuthor":true,"prefix":"","firstName":"Marco","middleName":"Valério Jansen","lastName":"Cutrim","suffix":""},{"id":523850682,"identity":"465823ee-8cfc-4f50-82a3-b6f61a56c0ee","order_by":1,"name":"Yago Bruno Silveira Nunes","email":"","orcid":"","institution":"State University of Maranhão (UEMA) - São Luís","correspondingAuthor":false,"prefix":"","firstName":"Yago","middleName":"Bruno 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Gomes","lastName":"Azevedo-Cutrim","suffix":""},{"id":523850686,"identity":"05d864a9-ea7b-4919-8c47-b0b1842e2ee5","order_by":5,"name":"Jordana Adorno Furtado","email":"","orcid":"","institution":"Federal University of Maranhão (UFMA) – São Luís","correspondingAuthor":false,"prefix":"","firstName":"Jordana","middleName":"Adorno","lastName":"Furtado","suffix":""}],"badges":[],"createdAt":"2025-09-05 20:23:05","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7546980/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7546980/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10661-026-15162-y","type":"published","date":"2026-03-16T15:58:32+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":92935339,"identity":"1ca96c38-91e7-4a6c-b38a-36b0408e2568","added_by":"auto","created_at":"2025-10-07 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10:05:23","extension":"html","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":183109,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7546980/v1/db080b6f704895eb55d0ac9c.html"},{"id":92935332,"identity":"ab3862bd-a6b9-4fb8-872e-ae39c7347985","added_by":"auto","created_at":"2025-10-07 10:05:22","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":146446,"visible":true,"origin":"","legend":"\u003cp\u003eLocation of the study area with sampling points (L1–L9), Jansen Lagoon, São Luís Island - Maranhão, Brazil.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-7546980/v1/6ee2564d9579a09e1a9355af.png"},{"id":92935995,"identity":"63860435-71cf-4486-873b-dd2253f452dc","added_by":"auto","created_at":"2025-10-07 10:13:22","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":145493,"visible":true,"origin":"","legend":"\u003cp\u003eSeasonal structure of the planktonic community. (a) Cluster analysis (Bray–Curtis, square-root, UPGMA) resolves two groups—GI (rainy) and GII (dry); the red dashed line marks the ~12.86% cutoff. (b) nMDS of the same data (stress = 0.01) with the rainy season (green triangles) and dry season (blue inverted triangles); shaded hulls outline the two clusters.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-7546980/v1/651dcaa13dbee42e81a8639e.png"},{"id":92935337,"identity":"9172d838-426c-4a06-8ad4-cea4da13347e","added_by":"auto","created_at":"2025-10-07 10:05:23","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":200885,"visible":true,"origin":"","legend":"\u003cp\u003eTaxon-specific abundance overlays the nMDS. nMDS ordination via Bray‒Curtis on square-root–transformed data (2D stress = 0.01). Each panel shows one taxon (\u003cem\u003eB.plicatilis\u003c/em\u003e, \u003cem\u003eB.angularis\u003c/em\u003e, \u003cem\u003eA.fuhrmanni\u003c/em\u003e, Polychaeta larvae, Harpacticoida, \u003cem\u003eA.panamensis\u003c/em\u003e, \u003cem\u003eColurella\u003c/em\u003esp., \u003cem\u003eF.longiseta\u003c/em\u003e) as bubbles plotted at the sample scores; bubble diameter scales with abundance (ind. m⁻³) with panel-specific scales are shown at the bottom-right.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-7546980/v1/6ba592eff11f902d26d33f60.png"},{"id":105224208,"identity":"ace78f77-005a-4c3e-b45b-dfa318063ab1","added_by":"auto","created_at":"2026-03-23 16:13:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1918302,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7546980/v1/c9109149-068f-4c89-a981-65964789dfb4.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Seasonal Bottom-Up and Top-Down Control of Plankton in a Hypereutrophic Macrotidal Lagoon on Brazil’s Equatorial Coast","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCoastal lagoons are shallow water bodies separated from the sea by natural or artificial barriers. Their physicochemical conditions, especially salinity, shift quickly over space and time under seasonal forcing and human influence (Sadat-Noori et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Cruz et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). As interfaces between land and ocean, they support nutrient cycling, carbon processing, and biodiversity (P\u0026eacute;rez-Ruzafa et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Changes in salinity, oxygen, nutrients, and light ripple through food webs, altering community structure and ecosystem function (Paturej et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Gamito et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn tropical cities, lagoons face mounting pressure from population growth and insufficient wastewater treatment. Nutrient enrichment drives eutrophication, the accumulation of nitrogen and phosphorus, harmful algal proliferation, and hypoxia (Paerl, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Domingues et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; B\u0026eacute;jaoui et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Plankton respond quickly to these shifts and are widely used to diagnose contamination and trophic state (Cas\u0026eacute; et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Gamito et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eZooplankton, the main grazers on algae, are sensitive to food quality and quantity, which shape their composition, growth, and reproduction (Sipa\u0026uacute;ba-Tavares \u0026amp; Bachion, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). In eutrophic waters, cyanobacteria often dominate and can suppress grazing through filamentous forms (Fulton \u0026amp; Paerl, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1987\u003c/span\u003e), toxicity (Fulton \u0026amp; Paerl, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1988\u003c/span\u003e), and poor nutritional value (Von Elert \u0026amp; Wolffrom, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Filaments may even clog filtering structures (DeMott et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), tipping competition toward cyanobacteria and away from edible algae (Gragnani et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Understanding this zooplankton\u0026ndash;phytoplankton interplay is central to understanding how eutrophication unfolds.\u003c/p\u003e\u003cp\u003eIn Brazil, most lagoon studies still focus on subtropical, heavily impacted systems\u0026mdash;e.g., Lagoa Rodrigo de Freitas (Rio de Janeiro)\u0026mdash;where eutrophication has reshaped zooplankton (Souza et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Work in tropical lagoons along the equatorial margin remains scarce. The Munda\u0026uacute;\u0026ndash;Manguaba complex has revealed how nutrients and salinity structure zooplankton (Luz et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Farther north, fewer lagoons and fewer studies exist; at Jansen Lagoon (Maranh\u0026atilde;o), recent research already points to strong urban and eutrophication signals (Cutrim et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Worldwide, findings from eutrophic lakes support the value of zooplankton as sensitive indicators of water quality (Garc\u0026iacute;a-Chicote et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Mu\u0026ntilde;oz-Colmenares et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHere, we examine spatial and seasonal plankton dynamics in an urban, hypereutrophic tropical lagoon on Brazil\u0026rsquo;s equatorial coast. We (i) describe zooplankton and phytoplankton across seasons and stations; (ii) test links between nutrients, salinity, oxygen, light and phytoplankton (bottom-up control); and (iii) evaluate whether grazer groups exert top-down effects. To our knowledge, this is the first comprehensive account of zooplankton in this lagoon and a needed baseline for management in highly pressured tropical urban waters.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy area and sampling stations\u003c/h2\u003e\u003cp\u003eJansen Lagoon is a coastal lagoon formed by damming Ana Jansen Creek. It spans\u0026thinsp;~\u0026thinsp;140 ha, averages\u0026thinsp;~\u0026thinsp;1.5 m in depth, and is bordered east by mangrove forest (Cutrim et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The lagoon is in the northwestern sector of S\u0026atilde;o Lu\u0026iacute;s Island, northern Brazil, near 02\u0026deg;29\u0026prime;08\u0026Prime; S; 044\u0026deg;18\u0026prime;02\u0026Prime; W (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). It connects to S\u0026atilde;o Marcos Bay via the Ana Jansen stream and is influenced by semidiurnal macrotides that can exceed 4 m (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eDados Maregr\u0026aacute;ficos e Fluviom\u0026eacute;tricos | CHM\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo represent the principal environmental settings, we established nine stations (L1\u0026ndash;L9) along gradients of marine influence, urban inputs, hydrodynamic retention, and macrophyte cover (WGS84, DMS). L1 (02\u0026deg;30\u0026prime;03\u0026prime;\u0026prime;S 44\u0026deg;18\u0026prime;18\u0026prime;\u0026prime;W) is in the southwest area of the lagoon, which is influenced by a supply of salt water from the S\u0026atilde;o Marcos Bay. Southern estuarine station L9 (02\u0026deg;30\u0026prime;03\u0026Prime; S; 44\u0026deg;18\u0026prime;18\u0026Prime; W) marks the transition to S\u0026atilde;o Marcos Bay. L2 (02\u0026deg;30\u0026prime;16\u0026Prime; S; 44\u0026deg;18\u0026prime;21\u0026Prime; W), L3 (02\u0026deg;30\u0026prime;23\u0026Prime; S; 44\u0026deg;18\u0026prime;13\u0026Prime; W), and L7 (02\u0026deg;30\u0026prime;08\u0026Prime; S; 44\u0026deg;18\u0026prime;11\u0026Prime; W) lie on urban shores receiving domestic sewage, where the organic load and turbidity are typically relatively high. L4 (02\u0026deg;30\u0026prime;19\u0026Prime; S; 44\u0026deg;18\u0026prime;04\u0026Prime; W) and L6 (02\u0026deg;30\u0026prime;23\u0026Prime; S; 44\u0026deg;18\u0026prime;39\u0026Prime; W) are semienclosed embayments with reduced water exchange and degraded mangrove stands (\u003cem\u003eRhizophora mangle\u003c/em\u003e, \u003cem\u003eAvicennia germinans\u003c/em\u003e) prone to local stagnation. L5 (02\u0026deg;30\u0026prime;06\u0026Prime; S; 044\u0026deg;18\u0026prime;32\u0026Prime; W) represents the central body of the lagoon near a mangrove islet, and L8 (02\u0026deg;30\u0026prime;23\u0026Prime; S; 044\u0026deg;18\u0026prime;32\u0026Prime; W) lies in a reach dominated by submersed macrophytes (\u003cem\u003eRuppia maritima\u003c/em\u003e).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSampling design\u003c/h3\u003e\n\u003cp\u003eSampling was conducted during ebb tide for four months in 2017\u0026mdash;March and April (rainy season) and September and November (dry season). All plankton and environmental measurements were taken from the surface layer (~\u0026thinsp;0.5 m) to ensure consistency. To standardize tidal influence, we sampled within an ~\u0026thinsp;2 h window around mid-ebb, scheduling each campaign with DHN/CHM (Diretoria de Hidrografia e Navega\u0026ccedil;\u0026atilde;o/Dados Maregr\u0026aacute;ficos e Fluviom\u0026eacute;tricos | CHM) tide tables and noting the local time and tidal stage at every station, and the order of stations was kept constant across campaigns to limit temporal drift.\u003c/p\u003e\n\u003ch3\u003eZooplankton sampling and analysis\u003c/h3\u003e\n\u003cp\u003eZooplankton were collected with horizontal subsurface tows (~\u0026thinsp;0.5 m depth) via a 120 \u0026micro;m plankton net coupled to a General Oceanics\u0026reg; flowmeter. At each station, we performed two replicate tows, each lasting 3\u0026ndash;5 minutes (adjusted to local hydrodynamics and debris). The samples were immediately preserved in buffered formaldehyde (4% final). We used a flowmeter to compute the filtered volume (m\u0026sup3;) and standardized the abundances to ind. m⁻\u0026sup3;. If a tow was compromised (air entrainment, net clogging, or flowmeter failure), we discarded it and repeated the process.\u003c/p\u003e\u003cp\u003eIn the laboratory, we identified organisms to the lowest feasible taxonomic level under compound and stereomicroscopes. Rotifers and nauplii were counted in a Sedgwick\u0026ndash;Rafter chamber (400\u0026times;); copepodites and adults were counted in open chambers under a stereomicroscope. With regard to taxonomic classification, specialized classification systems (identification keys) were used for each organism.\u003c/p\u003e\u003cp\u003eWhy a 120 \u0026micro;m mesh? The lagoon is eutrophic\u0026ndash;hypereutrophic and frequently turbid, especially during ebb, when suspended solids and filamentous/coccoid algae increase the risk of net clogging. A finer mesh (e.g., 64 \u0026micro;m) would markedly reduce the filtered volume and compromise between-station comparability under these conditions. Using 120 \u0026micro;m prioritizes mesozooplankton (copepodites/adults)\u0026mdash;key agents of top-down grazing\u0026mdash;and yields adequate, reproducible volumes across stations. As a trade-off, microzooplankton and small rotifers are underrepresented; therefore, our consumer\u0026ndash;producer inferences refer to top-down pressure by mesozooplankton captured with the 120 \u0026micro;m net, and their magnitude should be considered conservative relative to whole-community grazing.\u003c/p\u003e\n\u003ch3\u003ePhytoplankton sampling and analysis\u003c/h3\u003e\n\u003cp\u003eFor phytoplankton, we collected 250 mL of subsurface water with a Van Dorn bottle and preserved the samples with Lugol\u0026rsquo;s iodine (~\u0026thinsp;1% v/v). Counts followed Uterm\u0026ouml;hl (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1958\u003c/span\u003e) at 400\u0026times;. We enumerated at least 100 fields per sample and calculated the number of cells L⁻\u0026sup1; via Villafa\u0026ntilde;e \u0026amp; Reid (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). The taxonomy was updated with Guiry \u0026amp; Guiry, 2020. We considered a bloom as \u0026ge;\u0026thinsp;1\u0026times;10⁶ cells L⁻\u0026sup1; for a given taxon (Livingston, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eEnvironmental variables, nutrients, and chlorophyll-a\u003c/h3\u003e\n\u003cp\u003eThe in situ measurements included temperature, salinity, and pH at ~\u0026thinsp;0.5 m using a multiparameter probe (HI-9828, Hanna\u0026reg;; calibrated daily), turbidity (NTU) measured with a portable turbidimeter (model 2020), and Secchi depth (20 cm white disk) recorded before any disturbance to the water column.\u003c/p\u003e\u003cp\u003eFor nutrients, we collected 2 L of surface water (~\u0026thinsp;0.5 m), stored the samples on ice, and processed them as soon as possible (typically within 6\u0026ndash;8 h). We computed DIN as NH₄⁺-N\u0026thinsp;+\u0026thinsp;NO₂⁻-N\u0026thinsp;+\u0026thinsp;NO₃⁻-N and DIP as PO₄\u0026sup3;⁻-P; we also measured TP and dissolved silicate (SiO₂-Si). The methods followed APHA (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) and classical colorimetry (Koroleff, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e1983\u003c/span\u003e; Strickland \u0026amp; Parsons, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1972\u003c/span\u003e; Grasshoff et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1983\u003c/span\u003e), with results in \u0026micro;mol L⁻\u0026sup1;.\u003c/p\u003e\u003cp\u003eFor chlorophyll-a (Chll-a), we analyzed two technical replicates per station: 250 mL was filtered on GF/F (0.7 \u0026micro;m), extracted in 90% acetone under low light, and read on a UV‒Vis spectrophotometer (Thermo Scientific Evolution\u0026trade; 201). The concentrations (\u0026micro;g L⁻\u0026sup1;) were determined via the Parsons\u0026ndash;Strickland equations, as described by Strickland \u0026amp; Parsons (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1972\u003c/span\u003e). Each batch included procedural blanks.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eExclusion criteria and QA/QC\u003c/h2\u003e\u003cp\u003eWe excluded samples when (i) the flowmeter malfunctioned or the tow was aborted/clogged, (ii) field metadata were incomplete, or (iii) laboratory QC failed (e.g., replicate divergence beyond acceptance limits). All exclusions and reasons were documented.\u003c/p\u003e\u003cp\u003eBefore every campaign, the probe underwent calibration and was subsequently checked for drift. Readings outside the acceptable range were taken again. For nutrients, each campaign included field duplicates and reagent blanks; fresh 5-point calibration curves (R\u0026sup2; \u0026ge; 0.995) were prepared, with detection limits derived from low-level standards and blanks; and spikes or certified materials confirmed acceptable recoveries. For Chl-a, we compared replicates, handled extracts cold and dark, and applied an acidification step to correct for pheophytin; outliers were re-extracted or flagged.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eDiversity indices and statistical analyses\u003c/h3\u003e\n\u003cp\u003eWe computed species richness (Margalef), diversity (Shannon\u0026ndash;Wiener) and evenness (Pielou) from relative abundances in PAST v3. Indices were calculated per sample after standardization (zooplankton: ind. m⁻\u0026sup3;; phytoplankton: cells L⁻\u0026sup1;).\u003c/p\u003e\u003cp\u003eBefore hypothesis testing, we assessed distributions with Shapiro\u0026ndash;Wilk (normality) and Levene\u0026rsquo;s tests (homogeneity). When assumptions were not met, we applied log₁₀ transformation. We used two-way ANOVA for normally distributed, homoscedastic data and the Kruskal‒Wallis test otherwise, with α\u0026thinsp;=\u0026thinsp;0.05.\u003c/p\u003e\u003cp\u003eTo identify seasonal indicators, we applied the indicator value (IndVal) (Dufr\u0026ecirc;ne \u0026amp; Legendre, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1997\u003c/span\u003e) to zooplankton abundances grouped by season (rainy vs. dry), considering that p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was significant (permutation tests). We explored the relationships between community structure and environmental drivers via distance-based redundancy analysis (dbRDA). The community data were square-root transformed; we used Bray\u0026ndash;Curtis dissimilarities and centered and scaled the environmental predictors. We evaluated the canonical model and axes with permutation tests (n\u0026thinsp;=\u0026thinsp;999).\u003c/p\u003e\u003cp\u003eGiven the selectivity of the zooplankton gear (120-\u0026micro;m mesh focusing on mesozooplankton), predictors derived from zooplankton were interpreted as mesozooplankton proxies. To assess robustness to collinearity and size-selective sampling, we additionally fit a VIF-filtered GLM (retaining predictors with a VIF\u0026thinsp;\u0026le;\u0026thinsp;10) to log₁₀-transformed phytoplankton density (Gaussian, identity link).\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003ePhysical, chemical, and biological variables of Jansen Lagoon\u003c/h2\u003e\u003cp\u003eThe physicochemical summary is shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The water temperature varied modestly across the campaigns (25.5\u0026ndash;26.5\u0026deg;C), differing between seasons (two-way ANOVA, F\u0026thinsp;=\u0026thinsp;4.26, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) but not among the stations. Salinity is markedly greater in the dry season than in the rainy season and varies significantly between seasons (ANOVA, F\u0026thinsp;=\u0026thinsp;13.8, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Dissolved oxygen (DO) also differs seasonally (ANOVA, F\u0026thinsp;=\u0026thinsp;13.01, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), reaching its lowest values in the dry months. Nutrients display clear seasonality: DIN is dominated by NH₄⁺ (~\u0026thinsp;85%), whereas DIP is greater in the dry season. The community indices are consistently greater in the rainy season, zooplankton show greater diversity and richness with high evenness, and phytoplankton follow the same pattern; all the seasonal contrasts are significant (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSeasonal means (\u0026plusmn;\u0026thinsp;SDs) of physicochemical and biological variables in Jansen Lagoon (rainy vs. dry; 2017; surface\u0026thinsp;\u0026asymp;\u0026thinsp;0.5 m; ebb tide). F gives the test statistic from two-way ANOVA; where assumptions were not met, the Kruskal\u0026ndash;Wallis result is reported for seasonal contrast (see Methods). Asterisks denote significant seasonal differences (*p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Abbreviations: DO\u0026thinsp;=\u0026thinsp;dissolved oxygen; DIN\u0026thinsp;=\u0026thinsp;dissolved inorganic nitrogen (NH₄⁺ + NO₂⁻ + NO₃⁻); DIP\u0026thinsp;=\u0026thinsp;dissolved inorganic phosphorus (PO₄\u0026sup3;⁻\u0026ndash;P); TP\u0026thinsp;=\u0026thinsp;total phosphorus; SiO₂ = dissolved silicate; Chll-a\u0026thinsp;=\u0026thinsp;chlorophyll-a.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRainy\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDry\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDepth (m)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e0.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSecchi (m)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e0.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e41.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTemperature (\u0026deg;C)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e25.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e26.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003epH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e8.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e8.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSalinity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e6.11\u0026thinsp;\u0026plusmn;\u0026thinsp;1.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e31.77\u0026thinsp;\u0026plusmn;\u0026thinsp;2.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e13.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTurbidity (NTU)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e9.01\u0026thinsp;\u0026plusmn;\u0026thinsp;2.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e34.03\u0026thinsp;\u0026plusmn;\u0026thinsp;22.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e23.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.011\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDO (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e2.97\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e1.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e13.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNO\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026thinsp;\u003csub\u003e2\u003c/sub\u003e (\u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e0.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNH\u003csup\u003e+\u003c/sup\u003e\u0026thinsp;\u003csub\u003e4\u003c/sub\u003e (\u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e43.92\u0026thinsp;\u0026plusmn;\u0026thinsp;72.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e9.38\u0026thinsp;\u0026plusmn;\u0026thinsp;2.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNO\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026thinsp;\u003csub\u003e3\u003c/sub\u003e (\u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e2.86\u0026thinsp;\u0026plusmn;\u0026thinsp;2.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e6.03\u0026thinsp;\u0026plusmn;\u0026thinsp;6.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.035\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDIN (\u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e44.02\u0026thinsp;\u0026plusmn;\u0026thinsp;72.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e15.57\u0026thinsp;\u0026plusmn;\u0026thinsp;7.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDIP (\u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e0.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSiO\u003csub\u003e2\u003c/sub\u003e (\u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e1.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e4.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e16.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTP (\u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e4.25\u0026thinsp;\u0026plusmn;\u0026thinsp;2.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e3.91\u0026thinsp;\u0026plusmn;\u0026thinsp;1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e24.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChll-a (\u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e80.19\u0026thinsp;\u0026plusmn;\u0026thinsp;61.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e246.25\u0026thinsp;\u0026plusmn;\u0026thinsp;40.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e52.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhytoplanktonic Diversity (bits cells \u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e0.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e1.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e11.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhytoplanktonic Richness (bits cells \u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e1.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhytoplanktonic Evenness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e0.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e83.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZooplankton Diversity (bits cells \u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e0.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e114.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZooplankton Richness (bits cells \u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e10.28\u0026thinsp;\u0026plusmn;\u0026thinsp;7.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e2.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e98.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZooplankton Evenness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e0.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e0.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e27.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003ePlanktonic community composition\u003c/h2\u003e\u003cp\u003eThe zooplankton community comprised twenty-five taxa, dominated by rotifers (57.0% of taxa) and copepods (23.8%), with protozoans and tintinnids contributing 9.5% each. During the rainy season, rotifers and tintinnids occur at all stations (100% occurrence). In the dry season, tintinnids were absent, and several rotifer and copepod taxa also dropped out of the assemblage (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). IndVal analysis identified a suite of indicators spanning both seasons (e.g., \u003cem\u003eBrachionus plicatilis\u003c/em\u003e, \u003cem\u003eB.angularis\u003c/em\u003e, \u003cem\u003eAttheyella fuhrmanni\u003c/em\u003e, Harpacticoida, \u003cem\u003eFilinia longiseta\u003c/em\u003e, \u003cem\u003eHexarthra mira\u003c/em\u003e, \u003cem\u003eLepadella\u003c/em\u003e sp., and \u003cem\u003eParacalanus crassirostris\u003c/em\u003e), as detailed in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAbundance, occurrence total, and IndVal values for zooplankton taxa in Jansen Lagoon. \u003cb\u003eLegend\u003c/b\u003e: ABU \u0026ndash; Abundance; TO \u0026ndash; Total Occurrence; * Indicators species according to Indval values (IndVal\u0026thinsp;\u0026gt;\u0026thinsp;25%).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eRainy\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eDry\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eIndVal\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eABU (org m\u0026sup3;)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTO (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eABU (org m\u0026sup3;)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTO (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTINTINIDAE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eFavella ehrenbergi\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e11.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eTintinnopsis compressa\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e11.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eROTIFERA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAsplanchna sieboldin\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e38.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.4229\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eBrachionus angularis*\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e339.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0401\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eBrachionus calyciflorus\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e66.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.2381\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eBrachionus plicatilis*\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1,583.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e26.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.019\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eBrachionus urceolaris\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e426.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0790\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eColurella deflexa\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e107.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.3651\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eColurella\u003c/em\u003e sp*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e33.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0058\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eEuchlanis dilatata\u003c/em\u003e f. \u003cem\u003elucksiana\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e568.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.3033\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eFilinia longiseta*\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0279\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eHexarthra mira\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e88.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0982\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLeocane lunaris\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e88.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0777\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLepadella\u003c/em\u003e sp\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e77.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.3843\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCOPEPODA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eApocyclops panamensis*\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e379.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0008\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAcanthocyclops\u003c/em\u003e sp\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.2356\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAtheylla fuhrmanni*\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e696.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e13.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0004\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eParacalanus crassirostris\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0670\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHarpacticoida *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e460.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0038\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCopepodites/nauplii\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e894.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e14.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.8443\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePROTOZOA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eDifflugia\u003c/em\u003e sp\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e125.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.2245\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eArcella\u003c/em\u003e sp\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e95.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0716\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOTHERS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNematoda\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e87,50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e77.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.1224\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePolychaeta Larvae*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e29,94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e55.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.0036\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePolychaeta (Phyllodocidae)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23,26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e55.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.2167\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTOTAL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e60.70\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e100.00\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e6,915.89\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e100.00\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe phytoplankton community included 74 taxa distributed among Cyanophyta (47.30%), Bacillariophyta (37.84%), Chlorophyta (8.11%), Euglenophyta (1.52%), and Dinophyta (1.35%). The highest densities occurred in the rainy season at L6 (48.66 \u0026times; 10\u0026sup3; cells L⁻\u0026sup1;) and L5 (42.06 \u0026times; 10\u0026sup3; cells L⁻\u0026sup1;), and the phytoplankton density varied significantly across seasons and among stations (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). \u003cem\u003eMicrocystis\u003c/em\u003e spp. dominate Cyanobacteria; \u003cem\u003eCyclotella meneghiniana\u003c/em\u003e peaks in the rainy season at L1 (2.56 \u0026times; 10\u0026sup3; cells L⁻\u0026sup1;) and L6 (1.05 \u0026times; 10\u0026sup3; cells L⁻\u0026sup1;). \u003cem\u003eM. weisenbergii\u003c/em\u003e peaked during the dry season at almost all stations except L9, where it ranged from 1.40 \u0026times; 10\u0026sup3; cells L⁻\u0026sup1; (L3) to 23.34 \u0026times; 10\u0026sup3; cells L⁻\u0026sup1; (L7) in the rainy season. \u003cem\u003eM.aeruginosa\u003c/em\u003e also peaked at most stations in the dry season (absent at L9), from 1.30 \u0026times; 10\u0026sup3; cells L⁻\u0026sup1; (L5) to 18.05 \u0026times; 10\u0026sup3; cells L⁻\u0026sup1; (L4) and reached relatively high values in the rainy season (up to 46.16 \u0026times; 10\u0026sup3; cells L⁻\u0026sup1; at L6, minimum 9.00 \u0026times; 10\u0026sup3; cells L⁻\u0026sup1; at L7).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMean abundance of zooplankton (org.m\u003csup\u003e3\u003c/sup\u003e) and density of phytoplankton (cell L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) communities, respectively, in Jansen Lagoon by sampling point and seasonal period.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"10\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003eZooplankton Community\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"5\" nameend=\"c10\" namest=\"c6\"\u003e\u003cp\u003ePhytoplankton Community\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRainy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDry\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRainy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDry\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e71.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e25,823 x 10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e17,074 x 10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e750.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e20,995 x 10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e9,051 x 10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e848.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e16,535 x 10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5,523 x 10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e253.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e23,784 x 10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e40,221x 10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,038.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e42,058 x 10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4,283 x 10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e264.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e48,666 x 10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e35,006 x 10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2,328.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e16,899 x 10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e33,567 x 10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e590.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e25,847 x 10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e17,192 x 10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e781.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6,738 x 10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e702.70 x 10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6,926. 31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e241,218 x 10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e162,63 x10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eX\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.74\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;10.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e769.59\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;627.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e26,802\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;15,04x10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e18,07\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;14,79x10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eFactors affecting the planktonic community\u003c/h2\u003e\u003cp\u003eModeling phytoplankton density as the response, the stepwise-backward GLM explained 65% of the variance (adjusted R\u0026sup2; = 0.65; Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Within this model, density decreased with increasing dissolved oxygen content (β = \u0026minus;0.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and with \u003cem\u003eF.longiseta\u003c/em\u003e (β = \u0026minus;0.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13, p\u0026thinsp;=\u0026thinsp;0.017) and increased with DIP (β\u0026thinsp;=\u0026thinsp;0.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16, p\u0026thinsp;=\u0026thinsp;0.012). The coefficient for \u003cem\u003eB.plicatilis\u003c/em\u003e was also negative (β = \u0026minus;3.58\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32, p\u0026thinsp;=\u0026thinsp;0.016), but its tolerance was extremely low (T\u0026thinsp;=\u0026thinsp;0.0077; VIF\u0026thinsp;\u0026asymp;\u0026thinsp;129), indicating severe collinearity and warranting caution in interpretation. The other predictors were not significant (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eGeneralized linear model (GLM) for phytoplankton density in Jansen Lagoon via stepwise backward selection. Reported are standardized coefficients (β), standard error (SE), t\u0026thinsp;=\u0026thinsp;β/SE, (T), p values, the variance inflation factor (VIF), and significance. The final model (adjusted R\u0026sup2; = 0.65) identified dissolved oxygen (DO), DIP (PO₄\u0026sup3;⁻\u0026ndash;P), \u003cem\u003eBrachionus plicatilis\u003c/em\u003e and \u003cem\u003eFilinia longiseta\u003c/em\u003e as significant predictors (α\u0026thinsp;=\u0026thinsp;0.05). Predictors with a VIF\u0026thinsp;\u0026gt;\u0026thinsp;10 are flagged for collinearity. \u003cem\u003eSignificance\u003c/em\u003e: ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, * \u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePredictor\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eβ (std)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSE(β)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eT\u0026thinsp;=\u0026thinsp;β\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eVIF\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eSignif.\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eCollinearity flag (VIF\u0026thinsp;\u0026gt;\u0026thinsp;10)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDissolved oxygen (DO)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.943\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.172\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-5.483\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.000064\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.214\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSalinity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.067\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.257\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.261\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.798961\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4.925\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDIP (PO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e3\u0026minus;\u003c/sup\u003e-P)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.458\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.160\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.863\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.011936\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.908\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eBrachionus angularis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.407\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.647\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.629\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.538675\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e31.152\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eBrachionus plicatilis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-3.575\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.319\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-2.710\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.016086\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e129.514\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eFilinia longiseta\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.356\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.132\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-2.697\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.016592\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.296\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePolychaeta larvae\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.822\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.446\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.843\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.085109\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e14.814\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eColurella\u003c/em\u003e sp.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.153\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.125\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-1.224\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.237561\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.159\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHarpacticoida\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-1.028\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.555\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-1.852\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.083711\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e22.942\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAttheyella fuhrmanni\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.651\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.536\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.215\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.243252\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e21.414\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal zooplankton abundance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.132\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.358\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.570\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.137425\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e137.418\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFor \u003cem\u003eSynechococcus\u003c/em\u003e sp., the abundance increased with \u003cem\u003eAttheyella fuhrmani\u003c/em\u003e (β\u0026thinsp;=\u0026thinsp;0.65, p\u0026thinsp;=\u0026thinsp;0.007) and Polychaeta larvae (β\u0026thinsp;=\u0026thinsp;0.82, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.06) and with DO (β\u0026thinsp;=\u0026thinsp;1.06, p\u0026thinsp;=\u0026thinsp;0.004), yielding an adjusted R\u0026sup2; = 0.69. For \u003cem\u003eChroococcus turgidus\u003c/em\u003e, the best-fitting model (adjusted R\u0026sup2; = 0.75) included \u003cem\u003eColurella\u003c/em\u003e sp. (β = \u0026minus;0.15, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.86), DO (β = \u0026minus;0.94, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.45), salinity (β = \u0026minus;0.06, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.20) and a negative association with chlorophyll-a (β = \u0026minus;0.51, p\u0026thinsp;=\u0026thinsp;0.03); among these, only Chl-a was statistically supported at α\u0026thinsp;=\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eSeasonal structure and indicator patterns\u003c/h2\u003e\u003cp\u003eHierarchical clustering (Bray\u0026ndash;Curtis on square\u0026ndash;root\u0026ndash;transformed data, group-average linkage) and nMDS both reveal a clear seasonal separation of communities (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea, b). The dendrogram (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea) resolves two coherent clusters, with all rainy-season samples in GI and all dry-season samples in GII. The nMDS (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb; stress\u0026thinsp;=\u0026thinsp;0.01) corroborates this split, with rainy samples forming a tight cluster on the left and dry samples a compact cluster on the right. Notably, L1Dry plots at the edge of the dry cluster, and L8Rainy lies farthest from the rainy centroid, indicating modest within-season heterogeneity. This multivariate pattern is consistent with the univariate contrasts and with the environmental gradients highlighted by the dbRDA.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIndicator patterns mirrored this seasonal partitioning. Dry-season dominance was observed for \u003cem\u003eB.plicatilis\u003c/em\u003e, \u003cem\u003eB.angularis\u003c/em\u003e, \u003cem\u003eA.fuhrmanni\u003c/em\u003e, Polychaeta larvae, Harpacticoida, and \u003cem\u003eA. panamensis\u003c/em\u003e, with a marked peak at L7. In contrast, \u003cem\u003eF. longiseta\u003c/em\u003e, \u003cem\u003eH. mira\u003c/em\u003e, \u003cem\u003eLepadella\u003c/em\u003e sp., and \u003cem\u003eP.crassirostris\u003c/em\u003e were more common and achieved higher IndVal\u0026mdash;during the rainy season (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe bubble overlays on the nMDS (stress\u0026thinsp;=\u0026thinsp;0.01; panel-specific abundance scales) reinforce the seasonal split seen in the dendrogram. The dry-season samples contained the largest bubbles for \u003cem\u003eB.plicatilis\u003c/em\u003e, \u003cem\u003eB.angularis\u003c/em\u003e, \u003cem\u003eA.fuhrmanni\u003c/em\u003e, Polychaeta larvae, Harpacticoida and \u003cem\u003eA.panamensis\u003c/em\u003e, with a clear maximum at L7Dry and secondary peaks around L3\u0026ndash;L5Dry. In contrast, \u003cem\u003eF. longiseta\u003c/em\u003e is primarily associated with the rainy-season cluster\u0026mdash;most notably at L8Rainy, with a single high value at L1Dry; \u003cem\u003eColurella\u003c/em\u003e sp. was consistently rare in both seasons. Overall, taxa with higher abundances in the dry cluster track the conditions identified for the dry period (higher salinity and DIP/SiO₂), whereas those concentrated in the rainy cluster align with higher DO and DIN, which is consistent with the dbRDA patterns. (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eThe dbRDA captured 38.68% of the adjusted variation, with axis 1\u0026thinsp;=\u0026thinsp;26.54% and axis 2\u0026thinsp;=\u0026thinsp;12.14% (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The dry-season side of the gradient was associated with relatively high salinity, temperature, pH, turbidity, TP, and silicate contents, grouping taxa such as \u003cem\u003eB.plicatilis\u003c/em\u003e, \u003cem\u003eB.angularis\u003c/em\u003e, \u003cem\u003eB.urceolaris\u003c/em\u003e, \u003cem\u003eE.dilatata\u003c/em\u003e f. \u003cem\u003elucksiana\u003c/em\u003e, \u003cem\u003eDifflugia\u003c/em\u003e sp., Protozoa sp., and Phyllodocidae. Conversely, the rainy season side was associated with greater DO, Secchi depth, ammonium, and DIN concentrations, and \u003cem\u003eLepadella\u003c/em\u003e sp., \u003cem\u003eF.longiseta\u003c/em\u003e, and \u003cem\u003eP.crassirostris\u003c/em\u003e were associated with these conditions.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eTop-down and bottom-up controls on plankton.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAcross stations and seasons, phytoplankton responded to the resource supply, which was consistent with bottom-up control. In the GLM, DIP is a positive predictor of phytoplankton density (β\u0026thinsp;=\u0026thinsp;0.46, p\u0026thinsp;=\u0026thinsp;0.012; GLM table), and the rainy season side of the ordinations aligns with DIN (NH₄⁺, DIN vector) and greater water transparency (Secchi) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Although DIP tends to be greater in the dry period (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), peak phytoplankton densities occur in the rainy season (e.g., L5\u0026ndash;L6), suggesting that light availability and reduced salinity modulate nutrient signals.\u003c/p\u003e\u003cp\u003eConcurrently, several lines of evidence indicate top-down grazing. The GLM retained the negative partial effects of \u003cem\u003eF.longiseta\u003c/em\u003e (β = \u0026minus;0.36, p\u0026thinsp;=\u0026thinsp;0.017) and \u003cem\u003eB.plicatilis\u003c/em\u003e (β = \u0026minus;3.58, p\u0026thinsp;=\u0026thinsp;0.016; severe collinearity for the latter), which was consistent with rotifer grazing pressure on phytoplankton (GLM table). Indicator analyses and bubble overlays revealed dry-season dominance of grazing taxa, \u003cem\u003eB.plicatilis, B.angularis, A.fuhrmanni\u003c/em\u003e, Harpacticoida, and Polychaeta larvae, with maxima at L7Dry (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), which coincided with the dry cluster characterized by higher salinity and DIP/SiO₂ (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea, b). Together, these patterns are consistent with a seasonally shifting balance in which bottom-up drivers (nutrients/light) favor phytoplankton in the rainy season, whereas top-down pressure by zooplankton (and potentially light limitation via turbidity) constrains phytoplankton in the dry season. Collectively, these results indicate that top-down pressure is exerted by mesozooplankton captured with the 120-\u0026micro;m net. Because microzooplankton are undersampled, the magnitude of consumer effects reported here should be considered conservative.\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cb\u003e1. Seasonal context in a hypereutrophic lagoon\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSeasonality structured the system sharply. The dry-season waters presented higher salinity and DIP from evaporation and reduced freshwater input, whereas the rainy-season waters presented higher DO and DIN (NH₄⁺) and greater water renewal (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Despite the DIP peak in the dry period, the phytoplankton density and diversity were greater in the rainy season than in the dry period, which was consistent with the higher Secchi and lower salinity in the dry period (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea, b). Similar seasonal forcings have been reported for tropical coastal lagoons (e.g., Branco et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Delgadillo-Hinojosa et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Maia-Barbosa et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). More broadly, coastal lagoons exhibit pronounced spatiotemporal gradients, especially in terms of salinity and nutrients, under strong anthropogenic pressure; these gradients are primary vectors shaping plankton distributions and indicator species selection (Hemraj et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), a rationale fully consistent with our results. In macrotidal settings, tidal pumping can further reorganize zooplankton structure across the tidal cycle, reinforcing the seasonal signal (Krumme \u0026amp; Liang, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003e2. Bottom-up control: nutrients, light, and flushing\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTwo lines of evidence point to bottom-up forcing. First, the GLM identified DIP as a positive predictor of phytoplankton (β\u0026thinsp;=\u0026thinsp;0.46, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.012; Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Second, the rainy season samples plotted toward higher DIN and a better light climate (greater Secchi) in the ordinations (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). Together, these results explain why phytoplankton increased in the rainy months even with lower DIP: light availability, nitrogen supply, and flushing appear to unlock growth under better-oxygenated conditions, a pattern consistent with lagoon studies using plankton as bioindicators (Hemraj et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAlthough tropical Brazil does not experience a classical monsoon, the ITCZ-driven rainy season delivers comparable freshwater and nutrient pulses that reorganize salinity, turbidity, and residence time. In a monsoon-forced tropical bay (Marudu Bay, Malaysia), increases in nitrate triggered centric-diatom blooms (\u003cem\u003eChaetoceros\u003c/em\u003e, \u003cem\u003eBacteriastrum\u003c/em\u003e), whereas high ammonium suppressed them; high silica favored pennate diatoms, and silica depletion rapidly terminated blooms; additionally, high zooplankton abundance limited bloom development toward the end of the wet phase. These mechanisms provide a useful analogue for our system, helping to explain why rainy-season nutrient inputs and flushing structure phytoplankton composition and bloom dynamics here. (Tan \u0026amp; Ransangan, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)\u003c/p\u003e\u003cp\u003e\u003cb\u003e3. Top-down control: grazer pressure and consumer structure\u003c/b\u003e\u003c/p\u003e\u003cp\u003eEvidence for top-down regulation has also emerged. The GLM revealed negative partial effects of \u003cem\u003eF.longiseta\u003c/em\u003e (β = \u0026minus;0.36, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.017) and \u003cem\u003eB.plicatilis\u003c/em\u003e (β = \u0026minus;3.58, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.016; high collinearity noted) on phytoplankton (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), which was consistent with rotifer grazing. The nMDS results highlighted the dry-season dominance of grazing taxa, \u003cem\u003eB.plicatilis\u003c/em\u003e, \u003cem\u003eB.angularis\u003c/em\u003e, \u003cem\u003eA.fuhrmanni\u003c/em\u003e, Harpacticoida, and Polychaeta larvae, with a clear maximum at L7 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This consumer\u0026ndash;producer coupling aligns with evidence that zooplankton can modulate phytoplankton, water transparence, and nutrients (Bess et al., 2021). Ecologically, \u003cem\u003eB.plicatilis\u003c/em\u003e is well known for its tolerance to eutrophic conditions and broad salinity range (Arcifa et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Sl\u0026aacute;deček, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e1983\u003c/span\u003e; Castilho Noll et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), supporting its ecological success here. Collectively, these results indicate that top-down pressure is exerted by mesozooplankton captured with the 120-\u0026micro;m net. Because microzooplankton were undersampled, the magnitude of consumer effects reported here should be considered conservative.\u003c/p\u003e\u003cp\u003eSeasonal dilution experiments in the monsoon-driven Chilika Lagoon (India) demonstrate that microzooplankton frequently remove a large share of phytoplankton standing stock and production (often g/k\u0026thinsp;\u0026gt;\u0026thinsp;1). These findings indicate strong top-down regulation in eutrophic\u0026ndash;mesohaline waters (Singh et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003e4. Cyanobacteria, oxygen stress and feedback\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFrequent peaks of \u003cem\u003eM.wesenbergii\u003c/em\u003e and \u003cem\u003eM.aeruginosa\u003c/em\u003e fit the lagoon\u0026rsquo;s eutrophic status (Imai et al., 2008; Li \u0026amp; Xiao, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Although counts remained below the bloom threshold defined in Methods (\u0026ge;\u0026thinsp;10⁶ cells L⁻\u0026sup1;), such density peaks can depress DO through respiration and decay, reinforcing hypoxia and favoring smaller grazers over larger zooplankton, feedback widely reported for eutrophic systems (Guenther et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). These conditions, together with cyanobacterial interference, are known to disadvantage larger crustacean grazers while favoring rotifers (Ghadouani et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Jiang et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003e5. Community\u0026ndash;environment coupling across seasons\u003c/b\u003e\u003c/p\u003e\u003cp\u003eMultivariate analyses converge on the same mechanism. Clusters and nMDS separated the samples cleanly into rainy and dry seasons (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea, b). The dbRDA linked the dry side to salinity, temperature, pH, turbidity, TP and silicate, grouping rotifers (\u003cem\u003eBrachionus\u003c/em\u003e spp.), harpacticoids and protozoans; the rainy side aligned with DO, Secchi, NH₄⁺ and DIN, associating \u003cem\u003eLepadella\u003c/em\u003e sp., \u003cem\u003eF.longiseta\u003c/em\u003e and \u003cem\u003eP.crassirostris\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This mirrors lagoon bioindicator literature that links environmental gradients to predictable community responses (Hemraj et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Land-use signals likely reinforce these patterns at urban margins, as shown for functional zooplankton guilds in Amazon streams (Bomfim et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003e6. Management implications\u003c/b\u003e\u003c/p\u003e\u003cp\u003eMitigation should act on both sides of this balance. Nutrient load reduction (DIP and DIN from domestic sewage) is necessary but insufficient if the residence time and turbidity remain high. Actions that improve hydrological connectivity and reduce resuspension, combined with macrophyte restoration to increase nutrient uptake and habitat complexity, are likely to yield greater, more durable improvements (Branco et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Derolez et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Mart\u0026iacute;n et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Derolez et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Spatial priorities include urban margins (L2, L3, L7) and semienclosed embayments (L4, L6), where loading and retention are strongest. In macrotidal systems, management should also consider tide-driven community shifts that can amplify or dampen intervention outcomes (Krumme \u0026amp; Liang, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFor urban lagoon monitoring, we recommend a network of fixed stations at priority sites (urban margins and semi-enclosed embayments) plus a downstream reference, instrumented with high-frequency sondes (DO, temperature, EC/salinity, turbidity, chlorophyll-a fluorescence) at 10\u0026ndash;60 min intervals. Monthly baseline sampling should be complemented by event-triggered campaigns after major rainfall, and by tide-stratified sampling (neap/spring) to capture mixing effects. A core indicator set\u0026mdash;DIN, DIP, Secchi depth, chlorophyll-a, DO percent saturation\u0026mdash;and plankton bioindicators (e.g., \u003cem\u003eBrachionus\u003c/em\u003e spp., \u003cem\u003eF. longiseta\u003c/em\u003e) can provide early-warning signals of eutrophication risk. Intervention performance should be tested with BACI designs against pre-defined thresholds (e.g., DO\u0026thinsp;\u0026lt;\u0026thinsp;2 mg L⁻\u0026sup1;; cyanotoxins above WHO guidance), under a documented QA/QC protocol (sensor calibration, fouling control, uncertainty). Publishing near-real-time data to a public dashboard supports adaptive management and stakeholder accountability.\u003c/p\u003e\u003cp\u003e\u003cb\u003e7. Methodological considerations and future work\u003c/b\u003e\u003c/p\u003e\u003cp\u003eInterpretation is bounded by (i) collinearity in parts of the GLM (notably for \u003cem\u003eB.plicatilis\u003c/em\u003e; VIF\u0026thinsp;\u0026gt;\u0026thinsp;10), (ii) the 120-\u0026micro;m mesh, which undersamples microzooplankton and small rotifers, and (iii) temporal resolution (four campaigns). A reduced model excluding predictors with a VIF\u0026thinsp;\u0026gt;\u0026thinsp;10 retained the core effects (DO\u0026minus;, DIP+, \u0026minus;\u003cem\u003eF.longiseta\u003c/em\u003e), suggesting robustness. Future work should include multimesh sampling and explicit microzooplankton/protistan grazing assays, given the growing evidence that microzooplankton can exert strong top-down control on phytoplankton size-structure and productivity, together with higher-frequency time series to resolve short-term pulses of mixing, light, and nutrients. Where feasible, coupling to hydrodynamic/tidal sampling designs can clarify renewal effects (Krumme \u0026amp; Liang, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eJansen Lagoon clearly features rainy\u0026ndash;dry partitioning of plankton communities typical of hypereutrophic, tidally influenced systems. Across analyses, phytoplankton responded to bottom-up drivers (DIP, DIN, light/clarity, flushing), whereas top-down pressure from small grazers, especially rotifers, intensified in the dry season. The higher phytoplankton density and diversity in the rainy months, together with the negative partial effects of key grazers in the GLM and the seasonal separation in the ordinations, indicate a seasonally shifting balance: bottom-up control predominates during the rainy period, whereas top-down control predominates during the dry period. The peaks of \u003cem\u003eMicrocystis\u003c/em\u003e spp. (below the bloom threshold used here) and low DO at times underscore the system\u0026rsquo;s sensitivity to nutrient pulses and residence time.\u003c/p\u003e\u003cp\u003eManagement should therefore couple nutrient load reductions (DIP and DIN from domestic sewage) with measures that affect hydrodynamics and the light climate, improving water renewal, reducing turbidity/resuspension, and restoring macrophytes to increase nutrient uptake and habitat complexity. Spatial priorities include urban margins (e.g., L2, L3, and L7) and semienclosed embayments (L4 and L6), where loading and retention are strongest. Routine tracking of DIP/DIN, Secchi, and DO, paired with indicator taxa (e.g., \u003cem\u003eBrachionus\u003c/em\u003e spp., \u003cem\u003eF.longiseta\u003c/em\u003e), can serve as an early warning framework for ecological risk.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contribution\u0026nbsp;\u003c/strong\u003eAll authors contributed to the conception and design of the study. Data collection and research design were carried out by Marco Cutrim, Yago B. S. Nunes and Jordana A. Furtado. Data analysis and interpretations were performed by Yago B. S. Nunes and Jordana A. Furtado. The first draft of the manuscript was written by Yago B. S. Nunes, Ana K.D. dos Santos-S\u0026aacute;, Quedyane Cruz, and \u0026nbsp;Marco V.J. Cutrim, and all authors provided comments on previous versions of the manuscript. The final version was reviewed by Marco V.J. Cutrim and Andrea C.G. Azevedo-Cutrim, with additional intellectual contributions to improve the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e No funding was received to assist with the preparation of this manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e No datasets were generated or analyzed during the current study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e All authors have read, understood, and have complied as applicable with the statement on \u0026lsquo;Ethical responsibilities of Authors\u0026rsquo; as found in the Instructions for Authors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e The authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e: not applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAPHA. 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Supplementation of cyanobacterial food with polyunsaturated fatty acids does not improve growth of \u003cem\u003eDaphnia\u003c/em\u003e. \u003cem\u003eLimnology and Oceanography\u003c/em\u003e, \u003cem\u003e46\u003c/em\u003e, 1552\u0026ndash;1558. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4319/lo.2001.46.6.1552\u003c/span\u003e\u003cspan address=\"10.4319/lo.2001.46.6.1552\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"environmental-monitoring-and-assessment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"emas","sideBox":"Learn more about [Environmental Monitoring and Assessment](http://link.springer.com/journal/10661)","snPcode":"10661","submissionUrl":"https://submission.nature.com/new-submission/10661/3","title":"Environmental Monitoring and Assessment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"community ordination, cyanobacteria, bioindicators, grazing pressure, nutrient enrichment","lastPublishedDoi":"10.21203/rs.3.rs-7546980/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7546980/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTropical coastal lagoons often show pronounced seasonal forcing that modulates nutrient supply, light climate, and grazer pressure. We surveyed hypereutrophic Jansen Lagoon (S\u0026atilde;o Lu\u0026iacute;s Island, Brazil) in four campaigns during 2017 (rainy: March\u0026ndash;April; dry: September\u0026ndash;November) at nine near-surface stations sampled on ebb tide. Phytoplankton were enumerated by the Uterm\u0026ouml;hl method; mesozooplankton were collected with a 120-\u0026micro;m net; and nutrients and chlorophyll-a were measured by UV\u0026ndash;Vis spectrophotometry. Clustering and nMDS revealed clear rainy\u0026ndash;dry segregation of communities, and dbRDA linked dry-season samples to higher salinity, turbidity, TP, and silicate, whereas rainy-season samples were associated with higher dissolved oxygen, Secchi depth, ammonium, and DIN. Generalized linear models explained 65% of phytoplankton variance: density increased with DIP and decreased with dissolved oxygen and with the rotifer \u003cem\u003eFilinia longiseta\u003c/em\u003e, indicating concurrent bottom-up (nutrients, light/renewal) and top-down (grazing) controls. \u003cem\u003eMicrocystis wesenbergii\u003c/em\u003e and \u003cem\u003eM. aeruginosa\u003c/em\u003e exhibited frequent peaks, underscoring eutrophic risk, though values remained below the bloom threshold applied here. Overall, bottom-up control predominated in the rainy season, whereas grazer pressure intensified in the dry season. Management should couple nutrient-load reductions with measures that shorten residence time, reduce resuspension, and restore macrophytes, with priority to urban margins and semi-enclosed embayments; routine tracking of DO percent saturation, DIN/DIP, Secchi depth, and chlorophyll-a is recommended for long-term assessment.\u003c/p\u003e","manuscriptTitle":"Seasonal Bottom-Up and Top-Down Control of Plankton in a Hypereutrophic Macrotidal Lagoon on Brazil’s Equatorial Coast","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-07 10:05:18","doi":"10.21203/rs.3.rs-7546980/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-15T01:42:30+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-14T22:47:13+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-02T14:27:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"321717318537758284157028290678263289351","date":"2025-09-25T13:49:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"44485299067870054398731975235836898150","date":"2025-09-25T12:55:25+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-25T03:15:41+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-12T09:15:12+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-12T09:14:11+00:00","index":"","fulltext":""},{"type":"submitted","content":"Environmental Monitoring and Assessment","date":"2025-09-05T20:08:42+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"environmental-monitoring-and-assessment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"emas","sideBox":"Learn more about [Environmental Monitoring and Assessment](http://link.springer.com/journal/10661)","snPcode":"10661","submissionUrl":"https://submission.nature.com/new-submission/10661/3","title":"Environmental Monitoring and Assessment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"eb18bf3c-1289-40af-9b0e-8bcc4414fb09","owner":[],"postedDate":"October 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-23T16:09:58+00:00","versionOfRecord":{"articleIdentity":"rs-7546980","link":"https://doi.org/10.1007/s10661-026-15162-y","journal":{"identity":"environmental-monitoring-and-assessment","isVorOnly":false,"title":"Environmental Monitoring and Assessment"},"publishedOn":"2026-03-16 15:58:32","publishedOnDateReadable":"March 16th, 2026"},"versionCreatedAt":"2025-10-07 10:05:18","video":"","vorDoi":"10.1007/s10661-026-15162-y","vorDoiUrl":"https://doi.org/10.1007/s10661-026-15162-y","workflowStages":[]},"version":"v1","identity":"rs-7546980","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7546980","identity":"rs-7546980","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}