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 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 8 datasets containing 6972 sampling events with the occurrence and abundance records of 275 species (kingdoms: Bacteria, Protozoa, Chromista, Plantae, and Animalia) of functional groups plankton, benthos, and nekton. Datasets also include 22 190 abiotic records. The database is published in the Global Biodiversity Information Facility (GBIF) repository (see Sect. 3 “Data availability” and Table 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 world.
Coastal and marine biodiversity are facing an unprecedented worldwide threat from climate change, pollution, overfishing, habitat destruction, and invasive species (Lotze et al., 2006; Christian and Mazzilli, 2007; Halpern et al., 2008; Kennish and Paerl, 2010; Doney and Schimel, 2015), impairing the ecosystem functions and the delivery of goods and services to society. The comprehension of most of those threats requires knowledge of the long-term variability in both biological and environmental variables, which are the baseline for ecological studies and for the detection of early warning signals of natural and anthropogenic impacts and the modeling of predictive scenarios (Vihervaara et at., 2013; Muelbert et al., 2019). The establishment and maintenance of ecological observations of coastal ecosystems are crucial to support scientists and stakeholders with the necessary information to quantify environmental changes and their impact on the biodiversity and the sustainable use of the seas and coasts (Muelbert et al., 2019). That information is crucial to implement conservation and sustainable development targets (e.g., evaluating progress toward Aichi targets of the Convention on Biological Diversity (CBD; Dreujou et al., 2020) and several of the UN 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).
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 al., 2013; Muelbert et al., 2019), particularly in the Southern Hemisphere (Odebrecht et al., 2017). The scarcity of time 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 they are among the most affected by human activities and climate change (Ruiz et al., 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 in the regional economy (Seeliger, 2001). The favorable natural conditions and strategic position led to 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 (LTER) program since 1998, although oceanographic and ecological studies started in the 1970s (Odebrecht et al., 2017). The LTER-PLEA (PELD-ELPA in Portuguese) is a well-established and consolidated monitoring program, producing some of the longest datasets on estuarine and marine biota and abiotic parameters in the Southern Hemisphere (Odebrecht et al., 2010, 2017). Together with other ILTER coastal and marine sites (about 120 around the globe) (Muelbert et al., 2019), the LTER-PLEA has great potential to contribute to global coastal and ocean observation.
The LTER-PLEA contributes information about the biota composition, distribution, and abundance at seasonal, interannual, and decadal timescales, providing the basis to understand the estuarine ecological processes and their driving forces. Many studies have demonstrated how the variability in climate and hydrology influences the ecology of estuarine and marine biodiversity and production (Seeliger and Odebrecht, 2010; Odebrecht et al., 2010, 2017). PLEA is affected by large-scale and remote phenomena, the most important being the El Niño–Southern Oscillation (ENSO), which strongly influences southern South America precipitation and fluvial discharge (Robertson and Mechoso, 1997; Grimm et al., 1998). The interactions among climate and hydrology directly affect the dynamics of plankton (Muxagata et al., 2012; Haraguchi et al., 2015; Odebrecht et al., 2015; Abreu et al., 2016; Teixeira-Amaral et al., 2017; Salvador and Muelbert, 2019), macroalgae, seagrasses, benthic invertebrates (Colling et al., 2010; Lanari and Copertino, 2017; Lanari et al., 2018), and fish (Garcia et al., 2001, 2003; Vieira et al., 2010; Moraes et al., 2012; Garcia et al., 2017), with implications for species conservation (Costa et al., 2016), including fishing resources (Castello and Möller, 1978; Odebrech and Castello, 2001; Vieira et al., 2008). Impacts of human activities such as overfishing and dredging, combined with the ENSO, have the potential to affect biodiversity and ecological functions. Therefore, the PLEA is an ideal environment to test hypotheses about changes in biodiversity and their functioning at several temporal scales.
Here, we describe a database comprising biological parameters within plankton, benthos, and nekton communities, from primary producers to top predators, and associated water physical–chemical parameters. The compendium represents one of the most robust and longest databases of biological diversity in an estuarine coastal system of South America. The dataset is the framework for understanding the structure and functioning of PLEA and can be an important tool for environmental management and decision-making. Furthermore, the data provide information for the modeling of predictive scenarios of climate change impacts, which are fundamental for local adaptation and mitigation strategies, but also for a better understanding of coastal environment dynamics and functioning.
The Patos Lagoon estuary is part of the Patos–Mirim lagoon system located in
the subtropical coastal plain of southern Brazil (Fig. 1). The geographical
coverage of the dataset ranges from
Study area.
Interannual variability in hydrological patterns is largely associated with
ENSO remote effects on regional precipitation, with anomalous high and low
freshwater run-off occurring during El Niño and La Niña years,
respectively (Odebrecht et al., 2010). Overall, high levels of nutrients in
the water column (up to 40
The data described are 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 and
Table 1). Eight datasets, covering the biota (phyto-, zoo-, and
ichthyoplankton; benthic macrofauna; seagrasses; macroalgae; pink shrimp;
fish and marine mammals such as dolphins) and associated physical and chemical
water parameters (salinity, temperature, transparency, chlorophyll
Geographic locations at sampling stations of the Brazilian Long-Term Ecological Research program in the Patos Lagoon estuary and adjacent marine coast, LTER-PLEA.
Dataset I: phytoplankton and water quality parameters in the Patos Lagoon estuary and adjacent marine coast; dataset II: continuous monitoring of the micro- and mesozooplankton of the Patos Lagoon estuary and adjacent coastal area; dataset III: interannual variability in ichthyoplankton diversity in the Patos Lagoon estuary in southern Brazil; dataset IV: dynamics of submerged aquatic vegetation in the Patos Lagoon estuary; dataset V: temporal data series of benthic macrofauna abundance and composition from the Patos Lagoon estuary; dataset VI: ecology of the pink shrimp
Stages of the LTER-PLEA's database life cycle: from data
collection to integration in the Global Biodiversity
Information Facility (GBIF).
Temporal coverage of the LTER-PLEA's datasets.
Dataset I: phytoplankton and water quality parameters in the Patos Lagoon estuary and adjacent marine coast; dataset II: continuous monitoring of the micro- and mesozooplankton of the Patos Lagoon estuary and adjacent coastal area; dataset III: interannual variability in ichthyoplankton diversity in the Patos Lagoon estuary in southern Brazil; dataset IV: dynamics of submerged aquatic vegetation in the Patos Lagoon estuary; dataset V: temporal data series of benthic macrofauna abundance and composition from the Patos Lagoon estuary; dataset VI: ecology of the pink shrimp
The eight datasets were 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.
The routine identification of phytoplankton morpho-species was conducted
under optical microscopy (inverted and transmitted light, Zeiss) and
followed the classical literature (Balech, 1988; Tomas, 1996, 1997; Hoppenrath
et al., 2009) and specific taxonomic articles. Electron microscopy was used
for the identification of some species, e.g.,
The physical water parameters were obtained in situ: temperature (mercury
thermometer), salinity (optical refractometer or conductivity meter, YSI model 33 SCT – salinity, conductivity, temperature), and water transparency (Secchi disk). Surface water
samples were obtained using a bucket, stored in plastic bottles and
maintained in the dark for the analysis of dissolved inorganic nutrients and
chlorophyll
All zooplankton organisms present in subsamples of 1.25 % to 50 % of the
200
At 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
In the laboratory, the material was screened and identified. Fish eggs and
larvae were identified at 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 of 100
Temperature and salinity were registered with a YSI thermosalinometer with
precision of 0.01
In the laboratory, the biomass samples were washed and cleaned from
sediments, debris, and associated fauna. The plant biomass was split into
functional groups: rooted plants, macroalgae, and epiphyte algae. The rooted
plants were divided into belowground and aboveground fractions. Plant
development and phenology were recorded. Epiphyte algae were removed by
scraping the leaves with a surgical blade. Demographic parameters were
obtained for the rooted plants such as hast length, leaf length, number of
shoots, total rhizome length, and number of nodes along the rhizome. The dry
weight (48 h at 60
The macrofauna specimens were identified at the lowest taxonomic level
(Amaral and Nonato, 1996; Buckup and Bond-Buckup, 1999; Rios, 2009) and
quantified with the aid of stereomicroscopes (
Water temperature (mercury thermometer), salinity (refractometer), and transparency (Secchi disk) data were collected at each sampling occasion.
Concomitant with fish sampling, the water temperature (mercury thermometer), salinity (refractometer), and transparency (Secchi disk) data were collected at each station. Datasets VI and VII are subsets of the same sampling scheme, and the associated environmental variables are exactly the same.
The 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 as “findable” by the
integration and dissemination of data and metadata through the Global
Biodiversity Information Facility (GBIF; Data holders supplied their datasets to the database manager in digital
format (e.g., spreadsheets, csv files). Data were checked by the researchers responsible for data and by the data
manager for automatic and manual corrections (see quality assurance and
quality control in Sect. 2.3 for more details). Datasets were formatted according to the Darwin Core (DwC) standard
(TDWG, 2015) and the OBIS-ENV-DATA format (De Pooter et al., 2017). Technical validation was performed (taxonomic and structural validation). The metadata were described and verified by the responsible researchers. The resulting database was published in the GBIF platform through the
Integrated Publishing Toolkit (IPT) provided by the Information System on
Brazilian Biodiversity (SiBBr;
Description of the LTER-PLEA's datasets.
All datasets are available as a Darwin Core Archive (DwC-A), and all fields were named compliant with Darwin Core (DwC) standards (TDWG, 2015). The DwC offers a stable and flexible framework to store all fields available in original data sources. Each dataset is published as sampling event data, formatted using a star scheme based on the OBIS-ENV-DATA format (De Pooter et al., 2017), which includes an event core (event sampling data), occurrence (taxonomic data), and extended measurement or fact (environmental variables and taxa abundances) (Fig. 3).
The LTER-PLEA's dataset structure.
The LTER-PLEA's dataset structure based on the OBIS-ENV-DATA
format. Darwin Core terms (
Each sampling event formed one row in the event core data table and was identified by an event ID code that is a unique identifier of each sampling event (something that occurs at a place and time) (TDWG, 2015) and that was built according to the following information: (1) the standard code for the country (Brazil: Br), (2) project name (i.e., the source organization; in Portuguese: PELD-ELPA), (3) the identifier for the institution with 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 the sampling station.
The LTER-PLEA's database contains a total of 6972 sampling event records unequally distributed across the research groups during the monitoring period (Fig. 4). The sampling events encompassed 106 155 taxa occurrences and 22 190 abiotic measurements (Fig. 5) in the Patos Lagoon estuary and adjacent marine coast.
Number of sampling events for datasets (biota monitoring) in the
Patos Lagoon estuary and adjacent marine coast from 1993 to 2016. The plot shows the number of sampling events collected for each year and for each dataset.
Dataset I: phytoplankton and water quality parameters in the Patos Lagoon
estuary and adjacent marine coast; dataset II: continuous monitoring of the micro-
and mesozooplankton of the Patos Lagoon estuary and adjacent coastal area;
dataset III: interannual variability in ichthyoplankton diversity in the Patos
Lagoon estuary in southern Brazil; dataset IV: dynamics of submerged aquatic vegetation
in the Patos Lagoon estuary; dataset V: temporal data series of benthic macrofauna
abundance and composition from the Patos Lagoon estuary; dataset VI: ecology of the
pink shrimp
Abiotic records from the LTER-PLEA's database. Sampling events to
measure water salinity, water temperature, water transparency, suspended
particulate matter, chlorophyll
Kingdoms: Bacteria, Chromista, Plantae, and Protozoa.
Phyla: Charophyta, Chlorophyta, Ciliophora, Cryptophyta, Cyanobacteria, Euglenozoa, Myzozoa, and Ochrophyta.
Class: Bacillariophyceae, Chlorophyceae, Conjugatophyceae, Cryptophyceae, Cyanophyceae, Dictyochophyceae, Dinophyceae, Euglenoidea, Litostomatea, Prasinophyceae, Pyramimonadophyceae, Raphidophyceae, Trebouxiophyceae, and Ulvophyceae.
Orders: Aulacoseirales, Bacillariales, Chaetocerotanae incertae sedis, Chattonellales, Chroococcales, Coscinodiscales, Cyclotrichiida, Cymatosirales, Dictyochales, Dinophysiales, Eutreptiida, Fragilariales, Gonyaulacales, Gymnodiniales, Halosphaerales, Hemiaulales, Leptocylindrales, Lithodesmiales, Melosirales, Naviculales, Noctilucales, Nostocales, Oscillatoriales, Paraliales, Peridiniales, Prorocentrales, Rhizosoleniales, Surirellales, Synechococcales, Thalassionematales, Thalassiosirales, Triceratiales, and Ulotrichales.
Families: Aphanizomenonaceae, Aphanothecaceae, Aulacoseiraceae, Bacillariaceae, Ceratiaceae, Chaetocerotaceae, Coscinodiscaceae, Cymatosiraceae, Dictyochaceae, Dinophysiaceae, 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.
Genera:
Subgenera:
Species:
Kingdom: Animalia.
Phyla: Annelida, Arthropoda, Chaetognatha, Chordata, Cnidaria, Ctenophora, Echinodermata, Mollusca, Phoronida, and Rotifera.
Class: Appendicularia, Bivalvia, Branchiopoda, Gastropoda, Hexanauplia, Hydrozoa, Ichthyostraca, Malacostraca, Ostracoda, Polychaeta, Sagittoidea, and Thaliacea.
Orders: Amphipoda, Anomopoda, Aphragmophora, Arguloida, Calanoida, Copelata, Ctenopoda, Cumacea, Cyclopoida, Decapoda, Euphausiacea, Harpacticoida, Isopoda, Mysida, Onychopoda, Salpida, Sessilia, Siphonophorae, Siphonostomatoida, and Tanaidacea.
Families: Acartiidae, Balanidae, Bosminidae, Calanidae, Centropagidae, Chydoridae, Clausocalanidae, Corycaeidae, Cyclopidae, Daphniidae, Diaptomidae, Ditrichocorycaeus, Ectinosomatidae, Ergasilidae, Eurycercidae, Heterorhabdidae, Ilyocryptidae, Kalliapseudidae, Lubbockiidae, Luciferidae, Macrothricidae, Miraciidae, Moinidae, Oikopleuridae, Oithonidae, Oncaeidae, Onychocorycaeus, Paracalanidae, Peltidiidae, Podonidae, Pontellidae, Pseudodiaptomidae, Sagittidae, Sapphirinidae, Scolecitrichidae, Sididae, Subeucalanidae, Tachidiidae, and Temoridae.
Genera:
Species:
Kingdom: Animalia.
Phylum: Chordata.
Class: Actinopterygii.
Orders: Anguilliformes, Atheriniformes, Beloniformes, Characiformes, Clupeiformes, Cyprinodontiformes, Elopiformes, Gobiesociformes, Perciformes, Pleuronectiformes, Siluriformes, and Syngnathiformes.
Families: Achiridae, Anablepidae, Atherinidae, Atherinopsidae, Blenniidae, Carangidae, Characidae, Clupeidae, Engraulidae, Gerreidae, Gobiesocidae, Gobiidae, Hemiramphidae, Mugilidae, Paralichthyidae, Pimelodidae, Poeciliidae, Sciaenidae, Stromateidae, Syngnathidae, and Trichiuridae.
Genera:
Species:
Kingdom: Plantae.
Subkingdoms: Biliphyta and Viridiplantae.
Division: Chlorophyta, Rhodophyta, and Tracheophyta.
Class: Florideophyceae, Magnoliopsida, and Ulvophyceae.
Orders: Acrochaetiales, Alismatales, Ceramiales, Cladophorales, and Ulvales.
Families: Acrochaetiaceae, Cladophoraceae, Rhodomelaceae, Ruppiaceae, and Ulvaceae.
Genera:
Species:
Kingdom: Animalia.
Phyla: Annelida, Arthropoda, and Mollusca.
Class: Bivalvia, Gastropoda, Malacostraca, and Polychaeta.
Orders: Cumacea, Isopoda, Littorinimorpha, Myida, Phyllodocida, and Tanaidacea.
Families: Capitellidae, Cochliopidae, Corbulidae, Diastylidae, Hyssuridae, Kalliapseudidae, Munnidae, Nephtyidae, Nereididae, Sphaeromatidae, and Tanaididae.
Genera:
Species:
Kingdom: Animalia.
Phylum: Arthropoda.
Class: Malacostraca.
Order: Decapoda.
Family: Penaeidae.
Genus:
Species:
Common name: pink shrimp.
Kingdom: Animalia.
Phylum: Chordata.
Class: Actinopterygii.
Orders: Albuliformes, Anguilliformes, Atheriniformes, Batrachoidiformes, Beloniformes, Characiformes, Clupeiformes, Cyprinodontiformes, Elopiformes, Gobiesociformes, Perciformes, Pleuronectiformes, Scorpaeniformes, Siluriformes, Syngnathiformes, and Tetraodontiformes.
Families: Achiridae, Albulidae, Anablepidae, Ariidae, Atherinidae, Atherinopsidae, Batrachoididae, Callichthyidae, Carangidae, Characidae, Cichlidae, Clupeidae, Curimatidae, Cynoglossidae, Elopidae, Engraulidae, Erythrinidae, Gerreidae, Gobiesocidae, Gobiidae, Haemulidae, Hemiramphidae, Heptapteridae, Loricariidae, Monacanthidae, Mugilidae, Ophichthidae, Paralichthyidae, Percophidae, Pimelodidae, Pleuronectidae, Poeciliidae, Pomacentridae, Pomatomidae, Sciaenidae, Serranidae, Syngnathidae, Tetraodontidae, Trichiuridae, and Triglidae.
Genera:
Species:
Kingdom: Animalia.
Phylum: Chordata.
Class: Mammalia.
Order: Cetartiodactyla.
Family: Delphinidae.
Genus:
Species:
Common name: Lahille's bottlenose dolphins.
All datasets have reliable sampling properties (same sampling methodology
over time), have been thoroughly checked, have broad temporal and taxonomic
coverage, and are ready to use for analyses (accompanied with metadata
information). The data management, including the data validation process,
consisted of (i) data acquisition and ecological validation, (ii) taxonomic
validation, and (iii) structural validation:
All data collection and ecological validation steps were carried out by
the researchers responsible for the datasets (see quality assurance and
control in Sect. 2.3). Taxonomic nomenclature control was performed
through the taxon match tool of the World Register of Marine Species (WoRMS,
2021), an authoritative and comprehensive list of marine organisms' taxonomy
edited and reviewed by an international team of more than 240 taxonomic
editors worldwide. Every species has a unique identifier known as a life
sciences identifier (LSID), a persistent and globally unique identifier. This
identifier links the species name to an internationally accepted
standardized name and associated taxonomic information and also redirects
to the most accurate information on the species taxonomy (e.g., accepted
names and synonyms). Prior to publication, all datasets' technical
information has been individually reviewed regarding the use of the DwC
terms and taxonomic validity during upload in the Integrated Publishing
Toolkit (IPT) provided by the SiBBr and subsequent GBIF registration
(datasets were validated by the Data Validator tool available from the GBIF).
The Darwin Core was standardized according to the practices recommended by
the TDWG guidelines (
The LTER-PLEA's database policy follows the best practices of open data principles by releasing validated datasets on primary biodiversity and associated environmental data. The datasets were published in the GBIF repository through the Integrated Publishing Toolkit (IPT) provided by the Brazilian node SiBBr and can be accessed in the GBIF repository (Table 3). This publication refers to the most recent dataset published in the IPT. Monitoring is currently still being carried out, and the database will be updated and published every 4 years. All datasets presented here are identified by unique persistent identifiers such as digital object identifiers (DOIs) and are published under the Creative Commons Attribution-NonCommercial 4.0 International License (CC-BY-NC). Therefore, all datasets must be cited when used in scientific papers, presentations, reports, or any other by-product generated by researchers, governmental agencies, and the general public. Furthermore, it is desirable that the LTER-PLEA be included in the acknowledgements. When referring to the LTER-PLEA's database or sampling strategies and methodologies, please cite the present paper. The custodian of all the information collected is the Oceanography Institute of the Federal University of Rio Grande.
The LTER-PLEA's database 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, particularly the remote climate phenomena ENSO, across distinct taxonomic groups and trophic levels (Odebrecht et al., 2010, 2017).
The LTER-PLEA's database enabled the comprehension of the magnitude and drivers of short- and long-term changes in the abundance and composition of phytoplankton (Haraguchi et al., 2015), submerged aquatic vegetation (Copertino and Seeliger, 2010; Lanari and Copertino, 2017), benthic macrofauna (Collin et al., 2007, 2010), micro- and mesozooplankton assemblages (Muxagata et al., 2012; Teixeira-Amaral et al., 2017), the most relevant ichthyoplankton species (Bruno and Muelbert, 2009; Costa et al., 2013), fish fauna (Garcia et al., 2001, 2003, 2004), pink shrimp, and Lahille's bottlenose dolphin population parameters (Fruet et al., 2011, 2015; Genoves et al., 2018, 2020). All this information has enabled the understanding of the dynamics of ichthyoplankton transport and recruitment into the estuary (Costa and Muelbert, 2016; Franzen et al., 2019) and the influence of environmental dynamics on the health of fish larvae (Gouveia et al., 2015; Salvador and Muelbert, 2019); the influence of climatic and local factors on fish abundance, diversity, and trophic organization (Garcia et al., 2003, 2012, 2017; Possamai et al., 2018); the evaluation of the secondary production of copepods and its main contributors (Muxagata et al., 2012; Teixeira-Amaral et al., 2017); occurrence of potentially harmful microalgae groups (e.g., cyanobacteria and dinoflagellates) (Haraguchi et al., 2015); diatom accumulation in surf zone influenced by drastic events like mud deposition freshwater output (Odebrecht et al., 2010, 2013); phase shifts in the SAV (Copertino and Seeliger, 2010; Lanari and Copertino, 2017); the importance of the main nursery grounds for commercial species (D'Incao, 1991; Haimovici and Cardoso, 2017); overfishing impacts through analysis of Lahille's bottlenose dolphin (Fruet et al., 2011, 2014; Secchi et al., 2017); assessments of the conservation status and adaptive capacity and resilience of estuarine and marine organisms to anthropogenic changes and global warming (Bernardino et al., 2015; Copertino et al., 2016); among other relevant ecological processes.
ILTER datasets have subsidized meta-analyses of multidecadal biodiversity trends, hence corroborating the importance of long-term monitoring programs to offer insights on changes in natural systems (e.g., Pilotto et al., 2020). In general, long-term biodiversity data have been biased towards few taxonomic groups, and there is a lack of associated environmental data, hindering the understanding of the drivers of detected changes (Pilotto et al., 2020). Our database thus provides a comprehensive view of 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 estuarine biodiversity and functioning studies (e.g., Vieillard et al., 2020), it allows for testing for generalizations of previous findings across distinct biogeographical areas.
The LTER-PLEA is one of the 115 globally distributed coastal and marine ILTER sites (ILTER-CMS), a network that provides several opportunities to study and monitor these ecosystems. ILTER-CMS constitutes an observation platform for the Global Ocean Observing System (GOOS)-defined essential ocean variables (EOVs) and several regional and global programs (Muelbert et al., 2019). Comparisons of our datasets obtained in the Southern Hemisphere with other estuaries worldwide would contribute to broaden our understanding of 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 scales and geographic areas such as harmful algal blooms (Lyons et al., 2014) and overfishing (Brett et al., 2020). On a global scale, the LTER-PLEA's long-term data have already been supplied to analyses of range shifts in species distributions and abundance driven by climate change (Hastings et al., 2020). Despite the wide range of variables monitored, we acknowledge that several components that are key to assessing 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, few data are available for tropical and subtropical estuarine systems (Vieillard et al., 2020), and our data may help to fulfill this knowledge gap.
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 an integrative, interdisciplinary, and transversal approach, which may better link the estuary, coastal zone, and the ocean to their ecosystem services. Furthermore, such high-quality information adds to conservation, management, and restoration efforts of coastal and estuarine ecosystems (Costa et al., 2016), contributing to recommendations for public policies at local, national, and global levels.
Taxonomic coverage of the LTER-PLEA's database.
Continued.
Continued.
Continued.
Continued.
MC and ML conceived the data paper. VML, ML, and MC wrote the manuscript. MC, EM, PCOVdA, JHM, FCD, ERS, JPV, AMG, AC, and CO coordinated the monitoring studies; provided metadata and data; and reviewed the information on occurrence, abundance, and taxonomic status of the species and abiotic data. VML formatted the data and published the LTER-PLEA's database in GBIF. All authors commented on the paper and contributed to the quality check.
The contact author has declared that neither they nor their co-authors have any competing interests.
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We would like to thank Ulrich Seeliger, who was the creator of LTER-PLEA and coordinated the program from 1999 to 2010. The Brazilian Long-Term Ecological Research Program has been supported by the MCTI (Ministério de Ciência, Tecnologia e Inovação) and the Brazilian governmental funding agencies. The program also thanks the many laboratory technicians and undergraduate and graduate students who contributed to data sampling and organization.
This research has been supported by the Brazilian governmental funding agencies CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico; CNPq Proc. 520188/98-5, CNPq Proc. 558230/2009-1, CNPq Proc. 403805/2012-0, CNPq/CAPES/FAPs/BC – Fundo Newton/PELD no. 15/2016, CNPq/MCTI/CONFAP-FAPs/PELD no. 21/2020, Proc. 442206/2020-8), CAPES (Coordenação de Aperfeiçoamento Pessoal de Nivel Superior), and FAPERGS (Fundação de Amparo à Pesquisa do Rio Grande do Sul) as well as the Newton Fund (British Council) and the Organization for the Conservation of South American Aquatic Mammals (YAQUPACHA e.V., Nuremberg Zoo).
This paper was edited by François G. Schmitt and reviewed by Jacob Carstensen and one anonymous referee.