Patos Lagoon Estuary and Adjacent Marine Coastal Biodiversity Long-term data

. Estuaries are among the most productive aquatic ecosystems and provide important ecological and economic services in coastal areas. However, estuarine systems have been threatened worldwide by natural and anthropogenic impacts acting on local, regional and global scales. Long-term ecological studies contribute to the understanding and management of estuarine functioning, and 15 provide the baseline information for detection changes and modeling of predictive scenarios. Here, we describe long-term data on the biodiversity and physico-chemical parameters obtained from 1993 to 2016 for the Patos Lagoon estuary and adjacent marine coast-PLEA, in southern Brazil. We report eight datasets containing 6,972 sampling events with the occurrence and abundance records of 275 species (Kingdoms: Bacteria, Protozoa, Chromista, Plantae and Animalia) of functional groups plankton, 20 benthos and nekton. Datasets also include 22,190 abiotic records. The dDatabase is published in the Global Biodiversity Information Facility (GBIF) repository (see Data availability in Sect 3). The present compendium represents one of the most comprehensive and longest datasets from primary producers to top predators in an estuarine-coastal system in South America and their availability will be an important contribution to the understanding and predictability of estuarine dynamics around the 25 world. Thalassiosirales, Triceratiales and Ulotrichales. Diploneidaceae, Entomoneidaceae, Eutreptiaceae, Fragilariaceae, Gloeotilaceae, Gonyaulacaceae, Gymnodiniaceae, Hemiaulaceae, Leptocylindraceae, Leptolyngbyaceae, Lithodesmiaceae, Melosiraceae, Merismopediaceae, Mesodiniidae, Microcystaceae, Naviculaceae, Noctilucaceae, Nostocaceae, Paraliaceae, Peridiniaceae, Pleurosigmataceae, Polykrikaceae, Prorocentraceae, Protoperidiniaceae, Pseudanabaenaceae, Pterospermataceae, Rhizosoleniaceae, Skeletonemaceae, Stephanopyxidaceae, Surirellaceae, Thalassionemataceae, Thalassiosiraceae and Triceratiaceae. Genus: Alexandrium, Amphidinium, Aphanocapsa, Asterionellopsis, Aulacoseira, Bacillaria, Bacteriastrum, Binuclearia, Campylosira, Cerataulina, Ceratoneis, Chaetoceros, Coscinodiscus, Dactyliosolen, Detonula, Dictyocha, Dinophysis, Diploneis, Ditylum, Entomoneis, Guinardia, Gyrodinium, Gyrosigma, Hemiaulus, Leptocylindrus, Leptolyngbya, Lithodesmium, Melosira, Mesodinium, Meuniera, Microcystis, Neocalyptrella, Nitzschia, Noctiluca, Paralia, Peridinium, Planktolyngbya, Pleurosigma, Polykrikos, Proboscia, Prorocentrum, Protoperidinium, Pseudo-nitzschia, Pseudosolenia, Pterosperma, Raphidiopsis, Rhizosolenia, Scrippsiella, Skeletonema, Stephanopyxis, Surirella, Synedra, Thalassionema, Thalassiosira, Torodinium, Trieres and Tripos. Paracalanidae, Podonidae, Scolecitrichidae, Sididae, Biapertura, Boeckella, Bosmina, Bosminopsis, Calanoides, Calanus, Camptocercus, Centropages, Ceriodaphnia, Clytemnestra, Pseudosida, Simocephalus, Subeucalanus, Temora and Undinula. Species: Acanthocyclops , Acartia (Acanthacartia) tonsa , Acartia (Odontacartia) Achiridae, Atherinidae, Atherinopsidae, Blenniidae, Carangidae, Characidae, Clupeidae, Engraulidae, Gerreidae, Gobiesocidae, Gobiidae, Hemiramphidae, Mugilidae, Paralichthyidae, Pimelodidae, Poeciliidae, Sciaenidae, Stromateidae, Syngnathidae and Trichiuridae. Genus: Anchoa, Atherinella, Blennius, Brevoortia, Catathyridium, Cynoscion, Engraulis,

Diversity (CBD) (Dreujou et al., 2020) and several of the U.N. Sustainable Development Goals), and to enable global assessments such as those by the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES) and the UN World Ocean Assessment (Duffy et al., 2013).

45
Our current understanding of marine ecosystem responses to human activities is limited by the availability of data, particularly long-term series of physical, chemical, and biological conditions (Carstensen, 2014). Despite the important global initiatives (e.g. International Long-Term Ecological Research -ILTER) long-term, integrated, ecosystem-level monitoring efforts are still scarce for most coastal and marine ecosystems (Kennish and Paerl, 2010;Duffy et al., 2013;Vihervaara et at., 2013; 50 Muelbert et al., 2019), particularly in the Southern Hemisphere (Odebrecht et al., 2017). The scarcity of time seriestemporal data series from coastal ecosystems hampers the assessment of the impacts and undermines our ability to respond effectively to these threats (Turra and Denadai, 2016).
Estuaries and nearshore coastal regions are some of the most productive ecosystems on earth (McLusky and Elliott, 2004), yet among the most affected by human activities and climate changes (Ruiz et al., 55 2000). In southern Brazil, the Patos Lagoon Estuary and adjacent marine coast (PLEA) have been long recognized (Von Ihering, 1885) by their high biological productivity, together with human interference (Odebrecht et al., 2017). Considered the largest choked lagoon in the world (Kjerfve, 1986), the Patos Lagoon connects the continental waters to the western South Atlantic Ocean and performs a critical role on the regional economy . The favorable natural conditions and strategic position led to 60 the development of local and regional economic activities associated with artisanal and industrial fisheries (Kalikoski and Vasconcellos, 2012;Haimovici et al., 2014;Haimovici and Cardoso, 2017), port activities, industry and tourism (Newton et al., 2018).
The PLEA has been a Site of the Brazilian Long-Term Ecological Research Program (LTER) since 1998, although oceanographic and ecological studies started in the 1970s (Odebrecht et al., 2017). The  Table 1.

125
The data described is a product of the Brazilian Long-Term Ecological Research Program in the Patos Lagoon estuary and adjacent marine coast -LTER-PLEA established in 1998. The program aims to investigate the main natural and anthropic impacts on biotic and abiotic components of this ecosystem.
Distinct areas of the PLEA have been monitored generating a core set of measurements repeated over time across spatial gradients (Fig. 1, Table 1). Eight datasets, covering the biota (phyto-, zoo-, and 130 ichthyoplankton, benthic macrofauna, seagrasses, macroalgae, pink shrimp, fishes and marine mammals -dolphins) and associated physical and chemical water parameters (salinity, temperature, transparency, chlorophyll a, inorganic dissolved nutrients, and seston) was obtained by several research groups and laboratories that systematically and almost simultaneously monitor the estuary PLEA ( Fig.   2a) at different temporal scales (daily, monthly, and seasonal) ( Table 2). Some datasets include 135 sampling since 1993, prior to the start of the LTER-PLEA (Fig. 2a).

Data sources and sampling protocol
The eight datasets was based on the use of distinct sampling strategies and methods, according to the goals and specific characteristics of the biotic and abiotic components investigated. Consistency in data collection was continually emphasized, and was assisted by continued participation of the same researchers over the time period.

Phytoplankton (Dataset -I)
Sampling description: Phytoplankton was sampled monthly at two stations located in the estuary of the Patos Lagoon and one at Cassino BeachPLEA ( Fig. 1, Table 1). Phytoplankton for qualitative analysis was sampled by horizontal tows using a 20 µm-mesh size plankton net and stored in glass bottles fixed 160 with fomaldehyde (4 %) neutralized with hexamethylentetramine. For phytoplankton quantitative (cells counting) analysis, surface water samples were stored in ambar glass bottles and fixed with lugol's solution (2 %). Phytoplankton composition and abundance were obtained using the classical Utermöhl sedimentation method and described elsewhere Haraguchi et al., 2015). Six persons (graduate students, technician, researcher) counted phytoplankton over the whole study period 165 using the same procedure, i.e., screening of half (density of predominant species > 100 units) or the entire sedimentation chamber for organisms larger than 50 μm under low magnification (100 x) using an optical microscope (Inverted microscope Zeiss). Smaller organisms were counted according to the cell density, under magnification of 200 x and/or 400 x, in strips or at least 30 fields.
The routine identification of phytoplankton morpho-species was conducted under optical microscopy 170 (inverted and transmitted light, Zeiss) and followed classical literature (Balech, 1988;Tomas, 1993;  1996; Hoppenrath et al., 2009) and specific taxonomic articles. Electron microscopy was used for the identification of some species, e.g. Skeletonema (Bergesch et al., 2009), Pseudo-nitzschia (Hagström et al., 2011). Thalassiosira, however, was identified and counted to genus level due to identification difficulties using the optical microscope (Garcia and Odebrecht, 2009). Other difficulties to identify 175 species were grouped at higher taxonomic levels (i.e., centric and pennate diatoms, armored or unarmoured gymnodinioid dinoflagellates). Also, small flagellates (< 20 μm) and coccoid cells were grouped and counted in size classes. Molecular biology tools were applied to species of Asterionellopsis (Franco et al., 2016) and Pseudo-nitzschia (Hagström et al., 2011). Non-identifiable or damaged specimens associated with the phytoplankton sample were annotated as NA (not available).

180
The autotrophic ciliate Mesodinium was included in the present dataset.
The physical water parameters were obtained in situ: temperature (mercury thermometer), salinity (optical refractometer or conductivity meter Yellow Spring, mod. 33 SCT) and water transparency (Secchi disk). Surface water samples were obtained using a bucket, stored in plastic bottles and maintained in dark, for the analysis of dissolved inorganic nutrients and chlorophyll a (Abreu et al., 185 2010;. In the laboratory, 50-100 mL water aliquots were filtered (Whatman GF/F glass fibre filters) and frozen (-40° C) for the analysis of dissolved inorganic silicate, phosphate and nitrite + nitrate, while ammonium and chlorophyll a (material retained on the filters) analysis were conducted right away. The concentration of the former nutrients was measured according to the methods described by Strickland and Parsons (Strickland and Parsons, 1972), and that of ammonium followed the method 190 of UNESCO (1983). For the chlorophyll a concentration analysis, pigments were extracted (acetone solution 90 % v/v) in the dark and cold for 24 h, and measured using a calibrated Turner Design fluorometer with correction for degradation products (Strickland and Parsons, 1972;Welschmeyer, 1994).

Micro and mesozooplankton (Dataset -II)
Sampling description: Zooplankton samples were collected monthly at three stations located in the PLEA estuary of the Patos Lagoon and Cassino Beach (Fig. 1 All zooplankton organisms present on subsamples of 1.25 to 50 % of the 200 µm-mesh samples, were counted on a stereoscopic microscope and identified to the lowest taxonomic level possible. All results are expressed in numbers of organisms.m -3 . Copepod species were identified according to Rose (1933), Björnberg (1981) and Bradford-Grieve (1999), barnacle nauplii according to Lang (1979;1980), and 220 the remaining species and/or groups using specific references on Boltovskoy (1981;. Nonidentifiable or damaged specimens were recorded as NA (not available).
On each station water samples of 20 to 100 mL were collected and filtered through 2.5 cm glass microfiber filters (Whatman GF/F) using a syringe with a filter holder attachment (Swinnex). Each filter paper was then folded in half, wrapped in foil and frozen until processing. Chlorophyll a was 225 extracted with 90 % acetone and readings were made on a calibrated Turner Designs Fluorometer (TD 700) according to Welschmeyer (1994). Temperature and salinity were also measured on each station using a thermosalinometer (Hanna HI 9828), refractometers and a mercury thermometer depending on availability.
Quality Assurance and Control (QA/QC): All samples were collected under the supervision of 230 planktologists or graduate students of the zooplankton laboratory, and the taxonomic quality of the data was checked before uploading to the database.

Ichthyoplankton (Dataset -III)
Sampling description: Ichthyoplankton samples were collected monthly at seven stations located in the 235 PLEA estuarine margins of the Patos Lagoon and adjacent marine coast of Cassino Beach (Fig. 1, Table   1). Sampling of fish eggs and larvae was made with a 50 cm diameter 300 µm-mesh conical net equipped with a flowmeter. The net was manually hauled on the beach area by two people during two minutes at the seven stations. In the laboratory, samples were concentrated in 300 ml jars and all fish eggs and larvae were sorted from the remainder zooplankton. All the collected material was preserved 240 in formaldehyde 4 %.
In the laboratory, the material was screened and identified. Fish eggs and larvae were identified to the lowest taxonomic level possible according to Weiss (1981), Fahay (1983), Moser (1996), Olivar et al. (1999) and Richards (2005). Non-identifiable or damaged specimens were recorded as NA (not available). Total abundance was recorded by taxa as an absolute number and standardized to a volume 245 of 100 m 3 .
Temperature and salinity were registered with a YSI Thermosalinometer with precision of 0.01° C and of 0.01 salinity units.
Quality Assurance and Control (QA/QC): Sampling and laboratory procedure was were conducted under the same supervision and with the same standardized technique during this period. Taxonomic determination was were done by the same qualified technical expert for the entire period so far. Data was were double checked for typing errors and inadequate values.

Submerged aquatic vegetation (Dataset -IV)
Sampling description: The submerged aquatic vegetation (SAV) was monitored monthly monitored in a shallow area historically occupied by Ruppia maritima meadows and drift green macroalgae, at an inner and protected shoal within the mesomixohaline region of Patos Lagoon Estuary (Fig. 1, Table 1).
The Within each quadrat, the plant biomass was sampled by using cylindrical cores, buried into the sediment (ø 10 cm, 15 cm depth) (N=3 per plot; total N=18). The samples previously washed in the field with the help of sieves, were packed and transported to the laboratory with ice.

265
In the laboratory, the biomass samples were washed and cleaned from sediments, debris, and associated sites within Patos Lagoon estuary, exposed to different environmental conditions (salinity, transparency, nutrient input, anthropogenic impacts). In addition to percentage cover, biomass and 285 demographic parameters recorded across three transects (in each site), the ReBentos protocol includes information about sediment and water parameters, and seagrass meadow area.  Table 1). Data have been acquired twice a year, comprising winter (August) and summer (March) samplings. The samples were taken with a 10 cm diameter PVC corer (0.0078 m 2 ) buried 20 cm into the substrate and sieved through a 300 µm-mesh (Gray and Elliott, 2009). All collected material was fixed in formaldehyde 4 % and preserved in ethanol (70 %).

Benthic macrofauna (Dataset -V)
The macrofauna specimens were identified to the lowest taxonomic level (Amaral and Nonato, 1996; 295 Buckup and Bond-Buckup, 1999;Rios, 2009) and quantified with the aid of stereomicroscopes (40 x) in the Laboratorylaboratory. The abundance data for each point represent the number of organisms for each species collected by the PVC corer.
Quality Assurance and Control (QA/QC): Sampling was done by qualified technical experts continuously trained to use the same techniques and methods. The quality of data was checked monthly 300 before the uploading in the data bankto the database. Data is were checked for typing errors under supervision of experienced researchers.

Pink-shrimp Penaeus paulensis (Dataset -VI)
Sampling description: The pink-shrimp samples were collected monthly at eight stations ( Fig. 1, Table   305 1) located in the estuary of the Patos Lagoon and Cassino BeachPLEA with five replicates each. The gear used to obtain biological samples was a beach seine (9 m in length, 13 mm (adjacent knots) and 5 mm in the center), an active net designed to operate in shallow regions (average depth lower than 1.5 m). The pink-shrimp samples were preserved in 10 % formalin and later identified in the laboratory according to Buckup and Bond-Buckup (1999).
Quality Assurance and Control (QA/QC): Researchers and the classical methods were the same employed since the beginning of the time series. Thus, the methodology influence is minimal. Sampling 315 was always performed under supervision of experienced researchers.

Fish assemblages (Dataset -VII)
Sampling description: The ichthyofauna samples were collected monthly at eight stations located in the estuary of the Patos Lagoon and the adjacent marine coast (Cassino Beach)PLEA (Fig. 1, Table 1).

320
Fishes were sampled using a 9 m beach seine (13 mm bar mesh in the wings and 0.5 mm mesh adjacent knots in the 3 m center section) that was pulled to cover an area of about 60 m 2 during each haul. Five hauls were made monthly (usually in the first week of each month) at each sampling station. After sampling, fishes were euthanized using Eugenol (CONCEA, 2013) and stored in plastic bags with 10 % formalin. In the laboratory, fishes were transferred to 70 % alcohol. Fishes were then identified to the lowest taxonomic level possible according to specialized literature, such as Figueiredo (1977), Menezes and Figueiredo (1980;1985), Figueiredo and Menezes (1978;1980;2000), Fischer et al. (2004), and Fishbase (Froese and Pauly, 2019).
Concomitant with fish sampling, the water temperature (mercury thermometer), salinity (refractometer) and transparency (Secchi disk) data were collected at each station. The datasets VI and VII are subsets 330 of the same sampling scheme and the associated environmental variables are exactly the same.
Quality Assurance and Control (QA/QC): Principal investigators and fishing gears were the same since the beginning of the time series. Fish sampling in one of the sampling stations (Marambaia) had to be discontinued in 2013 due to physical changes in the site that prevented beach seining. Sampling and species identification methods were consistent across the years of the study and occurred under the 335 supervision of the same principal investigators.

Lahille's bottlenose dolphin Tursiops truncatus gephyreus (Dataset -VIII)
Sampling description: The area sampled is 140 km 2 and encompasses the lower portion of the Patos Lagoon estuary (40 km 2 ) and adjacent marine coast (50 km 2 south and 50 km 2 north of Patos Lagoon 340 estuary in the coastal zone) (Fig. 1, Table 1).
Distribution patterns and habitat use: All field work was carried out onboard a 5.6 m-long inflatable boat equipped with a 90 hp outboard engine, VHF radio, echo sounder and GPS. Boat-based surveys were conducted year-round on the core area of Patos Lagoon estuary dolphin community. Surveys in estuarine waters were conducted following predefined zigzag transects whereas in the adjacent marine 345 coast either zigzag or parallel-to-shore transects up to 20 km north and south of the estuary mouth were run, depending on the sea conditions and objective of the sampling occasion. This variation, however, does not interfere in the nature and quality of data inserted in the database. Surveys were was halted when the sea state (Beaufort scale) were > 3. Transects were run at speeds between 18 and 22 km/h. Two observers positioned in the bow searched for dolphins visually. Whenever a dolphin group was 350 sighted, the survey route was abandoned to approach the animals for photo-identification, for skin/blubber biopsy sampling and to obtain data of group size and composition, sighting depth and geographical position. After a sufficient number of good-quality digital photographs of the dorsal fins of presumably all animals were taken, the survey was resumed.
Quality Assurance and Control (QA/QC): Principal investigators and major sampling protocols 355 remained the same since the beginning of the study. Adaptations to sampling procedures were eventually made for specific research questions but do not interfere in the content and quality of the dataset presented in this compendium.

360
LTER-PLEA´s database sharing was performed based on the FAIR principles, which ensures that all data are easily findable, accessible, interoperable and reusable (Wilkinson et al., 2016;Tanhua et al., 2019). Thus, the potential of these data is summarized in: Findable, by the integration and dissemination of data and metadata through Global Biodiversity Information Facility (GBIF; www.gbif.org) with unique and persistent identifiers assigned (Table 3); Accessible, by open and free providing a complete description of the dataset in GBIF metadata sections and in the presented data descriptor. Data management followed the steps below ( Fig. 2b and 2c): 1. Data holders supplied their datasets to database manager in digital format (e.g., spreadsheets, csv files); 2. Data were checked by the researchers responsible for data and by the data manager for The long-term information enabled the monitor seasonal and interannual changes in the composition, distribution, abundance and production of zooplanktonic species related to climatic events and antropogenic causes.

III
Interannual variability of ichthyoplankton diversity in the Patos Lagoon estuary Southern Brazil (https://doi.org/10.15468/noeqwa) (Muelbert, 2020) Fish eggs and larvae were sampled to study temporal variability of the dynamics of recruitment and diversity of ichthyoplankton in the PLEA.

IV
Dynamics of Submerged Aquatic Vegetation in the Patos Lagoon estuary (https://doi.org/10.15468/bjzlnb) (Copertino, 2020) The annual and interannual variability of the biomass, demographic parameters and composition of submerged aquatic vegetation was analyzed in relation to the regional climate, hydrology and physical chemical parameters obtained by LTER -PLEA.
V Temporal data series of Benthic macrofauna abundance and composition from the Patos Lagoon estuary (https://doi.org/10.15468/lsoc2v) (Colling and Cavalca Bom, 2020) Species composition and densities of benthic macrofauna were seasonally recorded in mudflats, aiming to evaluate the relationship between the biota and hydrological scenarios of the Patos Lagoon estuary.

VI
Ecology of the pink-shrimp Penaeus paulensis in Patos Lagoon estuary (https://doi.org/10.15468/ovayhc) (Dumont, 2020) This data provides unique long-term information enabling the evaluation of natural and anthropic impacts in the estuarine and coastal region in southern Brazil, for an intensively exploited fishery resource, such as the pink-shrimp Penaeus paulensis .

VII
Species composition and abundance patterns of fish assemblages at shallow waters of Patos Lagoon estuary (https://doi.org/10.15468/kci8zb) (Vieira et al., 2020) Species composition, size structure, relative abundance and diversity patterns of fish have been monitored in shallow waters (< 2 m) aiming to evaluate the relationship between the biota and hydrological scenarios, climatic events and antropogenic causes.

VIII
Ecology of Lahille's bottlenose dolphin Tursiops truncatus gephyreus in the Patos Lagoon estuary and adjacent marine coast (https://doi.org/10.15468/4nh9ng) (Secchi et al., 2020) Tursiops truncatus gephyreus have been systematically and intensively monitored in the PLEA. This long-term surveys allowed estimating on the distribution, abundance, reproductive and survival rates, genetic and social structures, contamination load and detecting temporal and gender-related variation in diet of the Lahille's bottlenose dolphin. Measurement-or-Fact (environmental variables and taxa abundances) (Fig. 3).

405
Each sampling event formed one row in the Event Core data table and was identified by an eventID code that is an unique identifier of each sampling event (something that occurs at a place and time) (TDWG, 2015) and was built according to the following information: (1) The standard code for the country (Brazil-Br), (2) project name, i.e., the source organization (i.e., in Portuguese: PELD-ELPA), (3) the identifier for the institution having custody of the information referred to in the record (Universidade Federal de Rio Grande -FURG), (4) locality name (Patos Lagoon), (5) dataset name, (6) year, (7) month and (8) identifier of sampling station.
The LTER-PLEA´s database contains a total of 6,972 sampling event records unequally distributed across the research groups during the monitoring period (Fig. 4). Sampling events encompassed 106,155 taxa occurrences and 22,190 abiotic measurements (Fig. 5) in the Patos Lagoon estuary and 415 adjacent marine coast.

690
LTER-PLEA's is the first publicly available long-term database describing the abundance and composition of several components of planktonic, benthic, and pelagic biota from protists to mammals, associated with environmental data in an estuarine-coastal system of South America. The LTER-PLEA's database has been the basis for several studies that investigate estuarine and coastal dynamics over time and has provided insights on the impacts of major anthropogenic and natural drivers, 695 particularly the remote climate phenomena ENSO, across distinct taxonomic groups and trophic levels 2017).
ILTER datasets have subsidized meta-analyses of multidecadal biodiversity trends, hence corroborating the importance of long-term monitoring programmes to offer insights on changes in natural systems 720 (e.g., Pilotto et al., 2020). In general, long-term biodiversity data have been biased towards few taxonomic groups and lacking associate environmental data, hindering the understanding of the drivers of detected changes (Pilotto et al., 2020). Our database thus provides a comprehensive view on the biota´s spatio-temporal dynamics and its environmental drivers in a subtropical coastal marine system in the Southwestern Atlantic Ocean. Considering the over-representation of temperate regions in 725 estuarine biodiversity and functioning studies (e.g., Vieillard et al., 2020), it allows to test for generalizations of previous findings across distinct biogeographical areas.
LTER-PLEA is one of the 115 globally distributed Coastal and Marine ILTER Sites (ILTER-CMS), a network that provides several opportunities to the study and monitoring of these ecosystems. ILTER-
Comparisons of our datasets obtained in the southern hemisphere with other estuaries worldwide, would contribute to broaden our understanding on the role of the distinct signals (human versus climatic) in the biodiversity and functioning of these ecosystems (Paerl et al., 2015).
Our datasets can also contribute to analyses of emergent environmental issues over large temporal scale 735 and geographic areas such as harmful algal blooms (Lyons et al., 2014) and overfishing (Brett et al., 2020). On a global scale, LTER-PLEA´s long-term data have already supplied data to analyses of range-shifts in species distributions and abundance driven by climate changes (Hastings et al., 2020).
Despite the wide range of variables monitored, we acknowledge that several components that are key to assess ecosystem quality are missing from our dataset. We have plans to monitor contaminants and heterotrophic prokaryotes in the near future. The environmental data such as water temperature and nutrient concentration time series may foster assessments of global warming and nutrient pollution in coastal marine systems. Despite the coastal nutrient pollution reported worldwide, little data is available for tropical and subtropical estuarine systems (Vieillard et al., 2020) and our data may help to fulfill this knowledge gap.

745
The sustainable use of ecosystem services can only be devised on a solid scientific basis (Carstensen, 2014). Thus, the information about the biological and physical properties of the system could be also used towards integrative, interdisciplinary, and transversal approach, which may better link estuary, coastal zone, and the ocean to its ecosystem services. Furthermore, such high-quality information adds to conservation, management and restoration efforts of coastal and estuarine ecosystems (Costa et al., 750 2016), contributing to recommendations for public policies, at local, national and global levels.

Competing interests
The authors declare that they have no conflict of interest.