Amazon River Research Articles

Pelagic cnidarian assemblages show range-edge effect at the boundary of ocean surface, as illustrated in the case of the Amazon River Plume.

The neuston layer represents a complex community inhabiting the interface where oceanographic and atmospheric processes interact. Here, our aim was to compare patterns in the distribution and abundance of cnidarian assemblages observed in the neuston to parallel patterns previously observed in epipelagic waters along the spread of the Amazon River Plume over the Western Equatorial Atlantic, to test if the neuston reflects the patterns of the overall community whose core of distribution is located in epipelagic waters or are shaped by specific surface processes. The results show that both initial hypothesis were false. Instead, the cnidarian assemblages showed range-edge effect at the major ecotone placed at the interface between ocean and atmosphere. I.e., when proximate to the superior limits of their three-dimensional geographic ranges, represented here by the neuston, the population of most observed species occur in lower abundance. Specifically at the portion of the continental shelf with influence of the Amazon River Plume, the range-edge effect seems to be more prominent. Such results suggests the core of the cnidarian populations inhabiting this habit may lie in the deeper hypoxic waters beneath the plume. In conclusion, due the marked vertical structure observed here, proper evaluations of spatial patterns in the structure of pelagic cnidarian communities should preferentially be grounded on stratified sampling.

First record of captive breeding of the ornamental fish L333, King Tiger Pleco, Hypancistrus sp. (Siluriformes – Loricariidae) of the Amazon River basin

First record of captive breeding of the ornamental fish L333, King Tiger Pleco, Hypancistrus sp. (Siluriformes – Loricariidae) of the Amazon River basin

Three new species of Jainus (Monogenoidea: Dactylogyridae) from the gills of Triportheus angulatus (Characiformes: Triportheidae) collected in the Peruvian Amazonia.

Three new species of Jainus Mizelle, Kritzky & Crane, 1968, are described parasitizing the gill filaments of Triportheus angulatus (Spix & Agassiz) (Characiformes: Triportheidae), an omnivorous fish endemic to the Amazon River basin. Jainus iquitensis n. sp. is characterized by the morphology of the vagina, which is bell-shaped, with a canal as a sclerotized tube and the morphology of hook pair VII, which in the new species presents an inflated base, a characteristic not observed in other congeners. Jainus loretoensis n. sp. is unique among Jainus species due to the morphology of its Y-shaped ventral anchors, with an arrow-shaped superficial root and a finger-shaped deep root. Jainus sardinae n. sp. is characterized by presenting a slender, small J-shaped tube with a sigmoid accessory piece and a ventral anchor that is Y-shaped, with inconspicuous finger-shaped deep root and superficial root with rounded ending with a chin-shaped projection. These findings add three new species to the previously reported two Jainus species from Peru.

River suspended-sand flux computation with uncertainty estimation using water samples and high-resolution ADCP measurements

Abstract. Measuring suspended-sand fluxes in rivers remains a scientific challenge due to their high spatial and temporal variability. To capture the vertical and lateral gradients of concentration in the cross-section, measurements with point samples are performed. However, the uncertainty related to these measurements is rarely evaluated, as few studies of the major sources of error exist. Therefore, the aim of this study is to develop a method to determine the cross-sectional sand flux and estimate its uncertainty. This SDC (for sand discharge computing) method combines suspended-sand concentrations from point samples with ADCP (acoustic Doppler current profiler) high-resolution depth and velocity measurements. The MAP (for multitransect averaged profile) method allows obtaining an average of several ADCP transects on a regular grid, including the unmeasured areas. The suspended-sand concentrations are integrated vertically by fitting a theoretical exponential suspended-sand profile to the data using Bayesian modeling. The lateral integration is based on the water depth as a proxy for the local bed shear stress to evaluate the bed concentration and sediment diffusion along the river cross-section. The estimation of uncertainty combines ISO standards and semi-empirical methods with a Bayesian approach to estimate the uncertainty due to the vertical integration. The new method is applied to data collected in four rivers under various hydro-sedimentary conditions: the Colorado, Rhône, Isère, and Amazon rivers, with computed flux uncertainties ranging between 18 % and 32 %. The relative difference between the suspended-sand flux in 21 cases calculated with the proposed SDC method compared to the International Organization for Standardization (ISO) 4363 standard method ranges between −40 % and +23 %. This method that comes with a flexible, open-source code is the first to propose an applicable uncertainty estimation that could be adapted to other flux computation methods.

Geochemical Dynamics and Evolutionary Implications of Sediments at the Xingu–Amazon Rivers’ Confluence: Proxies for Mixing, Mobility and Weathering

This study investigates the geochemical characteristics and evolutionary implications of sediments at the confluence of the Xingu and Amazon Rivers. The main objective is to understand sediment mixing, mobility, and weathering processes through geochemical proxies. Samples were collected from various sections of the lower Xingu River, focusing on its interaction with the Amazon River. Analytical techniques such as X-ray diffraction (XRD), X-ray fluorescence (XRF), and inductively coupled plasma mass spectrometry (ICP-MS) were employed to analyze major and trace elements. The results reveal significant spatial variations in mineralogical and textural patterns, with sediments forming distinct groupings based on their location. The data suggest that the lower Xingu River is strongly influenced by sediment inputs from the Amazon River, particularly affecting sediment composition and chemical weathering processes. This research highlights the critical interactions between river systems and their implications for the evolution of the Amazon basin, especially regarding sediment contributions from various geological sources. Even though the Xingu River drains cratonic regions at higher elevations, the geochemistry of the bottom sediments confirms that the bedload is derived from heterogeneous sources with primarily intermediate igneous compositions and has undergone substantial recycling during river transport.

Divergent dynamics of coastal wetlands in the world’s major river deltas during 1990–2019

Coastal wetlands provide vital dynamic ecosystem services. They have become increasingly important after being linked to several sustainable developmental goals, resulting in a focus on their protection, management, and restoration. Therefore, there is an increasing need to detect and compare coastal wetland spatiotemporal dynamics in deltas at a global scale. In this study, we mapped and characterized coastal wetland spatiotemporal patterns for 1990–2019 in the world’s major river deltas using pixel frequency algorithms and Landsat-4/5 (TM), −7 (ETM + ), −8 (OLI), and Sentinel-2 (MSI) time-series imagery obtained from Google Earth Engine (GEE). Our map had a high overall accuracy (91.84 %) for 2019. Tidal flats were primarily distributed in North America (∼6.87 %) and Asia (∼5.91 %), whereas salt marshes were more commonly found in North America (∼45.39 %) and South America (∼10.61 %). Mangroves are more common in South America (∼11.86 %) and Asia (∼5.83 %), primarily because of the Amazon River Delta and tropical and subtropical regions of Asia, which host several large river deltas. South America had the largest coastal delta wetland area (798,569 km2), followed by Asia (640,251 km2), North America (581,977 km2), Africa (181,977 km2), Europe (140,759 km2), and Oceania (15,915 km2). There was a minor difference in the distribution of wetland vegetation and tidal flats in Asian coastal deltas, and the wetland vegetation area in Asia was greater than that in tidal flats on other continents. We found that the coastal wetland areas increased during 1990–2001, decreased during 2001–2012, and steadily increased during 2012–2019. Our study provides a baseline for monitoring the area, status, and health of the coastal wetlands in these river deltas.

Monitoring the Amazon River plume from satellite observations

ABSTRACT Most of our knowledge about the Amazon River plume is limited from the field experiments or modeling due to various challenges for satellite remote sensing, i.e., constant cloud coverage, atmospheric correction, and difficulties to differentiate the Amazon River plume from normal Atlantic Ocean water. In this study, observations of ocean properties from the Visible Infrared Imaging Radiometer Suite (VIIRS) and sea surface salinity (SSS) from the Soil Moisture Active Passive (SMAP) missions in 2021 are used as an example to demonstrate the capability to monitor the Amazon River plume on daily basis and characterize the change of the ocean environment driven by the offshoots and migration of the plume in the western tropical Atlantic Ocean. The start, development, evolvement, dispersion, and dissipation of the Amazon River plume in 2021 in the western tropical Atlantic Ocean were effectively monitored. The extensive influence of the Amazon River runoff mostly occurred between June and November. The water diffuse attenuation coefficient at 490 nm (K d (490)) and SSS were significantly impacted by the Amazon River plume in the vast region of the western tropical Atlantic Ocean. The routes of the Amazon River plume that flowed into the Atlantic Ocean were highly variable. High turbidity, low salinity plume water with K d (490) reaching ~1.0 m−1 and SSS ~25 practical salinity unit (psu) was found in a region over 500 km from the Amazon River Estuary. The comparison of the Amazon River plume in 2020 and 2022 further shows the complication of the driving forcing and inter-annual variability of the Amazon River plume. The combination of gap-free satellite ocean color and SSS observations provided a new tool to monitor the short-term variability of the Amazon River plume and assess its seasonal and interannual impact on the ocean environment in the western tropical Atlantic Ocean.

Seasonally flooded landscape connectivity and implications for fish in the Napo Moist Forest: A high-resolution mapping approach

The Amazon River Basin's fish diversity is shaped by its dynamic flood-pulse system, critical for hydrological and ecological connectivity. This study examines the Napo Moist Forest (NMF) ecoregion, mapping permanent and seasonally flooded areas from 2018 to 2021 using remote sensing and deep learning models. We aimed to map these areas at a high spatial resolution (10-m pixels) and analyse their role in maintaining lateral connectivity essential for fish diversity. Using synthetic aperture radar data from Sentinel-1 combined with deep learning algorithms, we produced high-accuracy flood maps to assess landscape connectivity between rivers and floodplains. Our methodology included creating a ground truth dataset with the Normalized Difference Water Index and integrating high-resolution optical data for model training, overcoming challenges of cloud coverage and dense vegetation. Our predictive model achieved high accuracy (mean pixel accuracy = 97 %) and consistently predicted 4801 km² of surface water, with only 3 % (130 km²) being seasonally flooded areas over four years. The Caquetá, Bajo Marañón, Napo, and Pastaza watersheds accounted for nearly 60 % of the flooded areas, highlighting their ecological importance. Connectivity analysis in three areas of interest within the NMF ecoregion revealed important seasonal and interannual fluctuations in hydrological connectivity due to changes in flooded patch characteristics. Reductions in the number and flooded patch area during low water seasons increased the distance between patches, leading to a disconnection between flooded areas, channels and rivers. Despite hydrological fluctuations, certain patches maintained consistent flooding, critical for lateral connectivity and sustaining aquatic biodiversity. These seasonally flooded areas act as connectors, influencing patch dynamics and connectivity with tributaries. Seasonal and interannual variations in hydrological connectivity are crucial for sustaining fish diversity. Conserving dynamic floodplains supports migratory fish life cycles and biodiversity. This study underscores the importance of high-resolution temporal and spatial data in conservation planning for aquatic ecosystems.

Monitoring terrestrial water storage changes using GNSS vertical coordinate time series in Amazon River basin

Aiming at the Terrestrial Water Storage(TWS) changes in the Amazon River basin, this article uses the coordinate time series data of the Global Navigation Satellite System (GNSS), adopts the Variational Mode Decomposition and Bidirectional Long and Short Term Memory(VMD-BiLSTM) method to extract the vertical crustal deformation series, and then adopts the Principal Component Analysis(PCA) method to invert the changes of terrestrial water storage in the Amazon Basin from July 15, 2012 to July 25, 2018. Then, the GNSS inversion results were compared with the equivalent water height retrieved from Gravity Recovery and Climate Experiment (GRACE) data. The results show that (1) the extraction method proposed in this article has better denoising effect than the traditional method; (2) the surface hydrological load deformation can be well calculated using GNSS coordinate vertical time series, and then the regional TWS changes can be inverted, which has a good consistency with the result of GRACE inversion of water storage, and has almost the same seasonal variation characteristics; (3) There is a strong correlation between TWS changes retrieved by GNSS based on surface deformation characteristics and water mass changes calculated by GRACE based on gravitational field changes, but GNSS satellite’s all-weather measurement results in a finer time scale compared with GRACE inversion results. In summary, GNSS can be used as a supplementary technology for monitoring terrestrial water storage changes, and can complement the advantages of GRACE technology.

A new Multivariate Drought Severity Index to identify short-term hydrological signals: case study of the Amazon River basin

The Earth's climate is changing rapidly and unexpectedly, causing more frequent, longer and more severe droughts, with lasting impacts on plants, ecosystems, communities and people. Consequently, this is leading to an increased importance of monitoring the climate and water storage trends in different regions. This information on a global scale is already commonly derived using satellite-based geodetic techniques such as the Global Positioning System (GPS) and the Gravity Recovery and Climate Experiment (GRACE). The use of both techniques has significant advantages, especially in regions where changes in the hydrosphere are notable, such as the Amazon basin, where 25 GPS stations were lately classified as benchmarks for hydrogeodesy. We show that the vertical displacements obtained from GPS and GRACE have good spatio-temporal agreement with the Standardized Precipitation and Standardized Precipitation Evapotranspiration indices, abbreviated respectively as SPI and SPEI, for all these stations. Drought severity index (DSI) estimated separately from GPS-observed and GRACE-derived vertical displacements on a station-by-station basis is capable to identify dry and wet events previously reported for the Amazon basin. However, due to the weaknesses of both techniques, such as technique-related systematic errors or coarse spatial resolution, a few extreme hydrological events may not be properly captured by GPS-DSI and/or GRACE-DSI. To take full advantage of both techniques and overcome their weaknesses, we introduce a completely new methodology to combine individual GPS-DSI and GRACE-DSI indices. As a novelty, both indices are estimated using short-term changes (<9 months) of monthly vertical displacements observed by GPS permanent stations and those derived by GRACE for GPS locations. Then, to capture and detect drought events that either both geodetic techniques metrics missed or incorrectly depicted, the Multivariate Drought Severity Index (MDSI) is estimated through the concept of Frank copulas. We demonstrate that the MDSI captures more hydroclimatic events reported in previous studies, which are not identified by individual series of GPS-DSI or GRACE-DSI indices, and is temporally consistent with Standardized Streamflow Index (SSI) based on the in-situ river discharge changes.

Low-degree gravity field coefficients based on inverse GNSS method: insights into hydrological and ice mass change studies

The relative displacements of stations from a global network of Global Navigation Satellite System (GNSS) sites provide information on global mass transport. In this study, we use 19 years of global GNSS station displacements from the 3rd International GNSS Service reprocessing campaign to estimate the coefficients of the spherical harmonics of the Earth’s gravity field up to degree and order 8 using the inverse GNSS method based on elastic loading theory. The results indicate that the C30 coefficient can be derived based on GNSS station displacements as an alternative to solutions provided by Satellite Laser Ranging (SLR) and Gravity Recovery and Climate Experiment (GRACE). GNSS may support GRACE solutions that face the problems of deriving C30, which has fundamental meaning in estimating ice mass changes in polar regions. The recovery of Antarctic ice sheet mass change from January 2007 to December 2020 based on coefficients replaced by GNSS estimates results in a linear trend of − 152 ± 4 Gt/year, in comparison to − 149 ± 2 Gt/year for the replacement based on SLR from GRACE Technical Note #14. The results indicate that the spatial and seasonal patterns of terrestrial water storage changes derived from GNSS are consistent with those estimated using GRACE/GRACE Follow-On and SLR at a few-millimeter level in the Amazon and Brahmaputra River basin regions.

Wildlife Ecotourism in Protected Areas of the Lower Negro River, Brazilian Amazon: characterization, challenges, and potentials

In the last few decades, tourist interactions involving wildlife, one of the activities that distinguishes ecotourism, have attracted many fans in various regions of the world. This article maps, characterizes, and presents the challenges and potentials of wildlife ecotourism in protected areas of the Lower Negro River, in the Brazilian Amazon. Through data collection in the field, seven enterprises were visited and tourist interactions with twelve different species of wildlife were recorded. The activities that visitors engage in vary according to the species they are interacting with, but include watching the animals, offering food, physical contact (petting or holding the animals), and getting into the water with them. The recorded species include the Amazon River dolphin (Inia geoffrensis), the Woolly monkey (Lagothrix lagotricha), and the Bald uakari (Cacajao calvus), which are on the International Union for Conservation of Nature (IUCN) Red List of Threatened Species. Despite the negative impacts of these activities, they help create income for the host communities, increase the public use of protected areas, and raise awareness among visitors regarding the conservation of species and their habitats.

Amazon severe drought in 2023 triggered surface water loss

Abstract The Amazon underwent a severe austral springtime drought attributed to the onset of El Niño in 2023 and the warmer North Atlantic, Indian, and North Pacific Oceans. The Amazon rivers, lakes, small streams, wetlands, and reservoirs quickly lowered their water level below historical records due to decreased rainfall and warmth in the region. Based on satellite imagery, this study presents the first estimate of the water loss extent in the 4.2 million km2 of the Brazilian Amazon biome (∼62% of the Amazon total biome) in 2023. We estimated the loss of 3.3 million hectares of surface water relative to 2022, with an overall accuracy of 92%. The surface water losses were concentrated in the states of Amazonas (59.4%) and Pará (25.5), adding up to 2.8 million hectares. The warmer and drier climate in the region affected the main rivers in the Amazon. Among them, the Solimões, Negro, Purus, Acre, and Branco suffered extreme drops in their levels in some regions, resulting in a high negative impact on the aquatic biodiversity, yet estimated only in local areas. A total of 1.14 million hectares of surface water loss (i.e. 35%) was detected within protected areas territories, affecting extractivist, indegenous, African-Brazilian, and fishing and traditional communities. Proximity analysis revealed that 75% of the 2023 surface water loss was within 25 km of small towns, 48% and 65.8% at 50 km from indigenous villages and urban areas, respectively. Our results reinforce people’s vulnerability to climate change, anticipating a plausible adverse impact scenario in the Amazon region and urging solutions to adaptation and mitigation. Therefore, an integrated monitoring system based on climate and water dynamics from satellite and ground stations is necessary to improve understanding of the problem for timing response of climatic change negative impacts.

Soil greenhouse gas fluxes partially reduce the net gains in carbon sequestration in mangroves of the Brazilian Amazon

There is interest in assessing the potential climate mitigation benefit of coastal wetlands based on the balance between their greenhouse gas (GHG) emissions and carbon sequestration. Here we investigated soil GHG fluxes (CO2 and CH4) on mangroves of the Brazilian Amazon coast, and across common land use impacts including shrimp farms and a pasture. We found greater methane fluxes near the Amazon River mouth (1439 to 3312 μg C m−2 h−1), which on average are equivalent to 37% of mangrove C sequestration in the region. Soil CO2 fluxes were predominant in mangrove forests to the East of the Amazon Delta. Land use change shifted mangroves from C sinks (mean sequestration of 12.2 ± 1.4 Mg CO2e ha−1 yr-1) to net GHG sources (mean loss of 8.0 ± 3.3 Mg CO2e ha−1 yr−1). Our data suggests that mangrove forests in the Amazon can aid decreasing the net annual emissions in the Brazilian forest sector in 9.7 ± 0.8 Tg CO2e yr−1 through forest conservation and avoided deforestation.

The biogeography of the Amazonian tree flora

We describe the geographical variation in tree species composition across Amazonian forests and show how environmental conditions are associated with species turnover. Our analyses are based on 2023 forest inventory plots (1 ha) that provide abundance data for a total of 5188 tree species. Within-plot species composition reflected both local environmental conditions (especially soil nutrients and hydrology) and geographical regions. A broader-scale view of species turnover was obtained by interpolating the relative tree species abundances over Amazonia into 47,441 0.1-degree grid cells. Two main dimensions of spatial change in tree species composition were identified. The first was a gradient between western Amazonia at the Andean forelands (with young geology and relatively nutrient-rich soils) and central–eastern Amazonia associated with the Guiana and Brazilian Shields (with more ancient geology and poor soils). The second gradient was between the wet forests of the northwest and the drier forests in southern Amazonia. Isolines linking cells of similar composition crossed major Amazonian rivers, suggesting that tree species distributions are not limited by rivers. Even though some areas of relatively sharp species turnover were identified, mostly the tree species composition changed gradually over large extents, which does not support delimiting clear discrete biogeographic regions within Amazonia.

Amazonian amphibians: diversity, spatial distribution patterns, conservation and sampling deficits.

The Amazon biome is home to the largest tropical forest on the planet and has the greatest global biodiversity on Earth. Despite this, several less charismatic taxonomic groups, such as amphibians, lack comprehensive studies on their species richness and spatial distribution in the Amazon Region. In this study, we investigated: i) patterns of richness and endemism of Amazonian amphibians across geopolitical and biogeographic divisions, ii) similarities between different Amazonian bioregions, iii) temporal trends in amphibian sampling, iv) conservation status of amphibians according to assessments of the IUCN and v) the importance of diverse data sources in building a robust database of amphibian occurrences. We aggregated data from four different sources: publicly accessible platforms, peer-reviewed articles, grey literature and fieldwork inventories spanning 15 years (2007-2021), ultimately compiling 160,643 records of 947 species across 7,418 sampled sites. The greatest diversity of species was found in Peru, Brazil and Ecuador, with notable amphibian diversity and endemism in regions such as the western basins and the Tapajós River Basin in the central-southern Amazon. Geographical analysis of species diversity revealed four distinct groups defined by latitudinal (the Amazon River) and longitudinal (the Juruá, Madeira and Tapajós Rivers) gradients, with low species similarity (< 40%), particularly in the basins of north-western Amazonia. Amphibian sampling in the Amazon has intensified since the 1950s with the establishment of important research centres such as INPA and the GOELD Museum in the Brazilian Amazon. Approximately 18% of Amazonian amphibian species face extinction risk, according to IUCN assessments, highlighting the need for comprehensive data sources to understand and conserve species in this megadiverse region. Our findings suggest that river systems likely influence Amazonian amphibian species composition due to biogeographic history, emphasising the need for robust taxonomic and spatial databases. This study, therefore, contributes a valuable large-scale dataset for Amazonian amphibians, guiding future research and strategies for amphibian conservation.

Population dynamics and reproductive features of the Amazon River prawn Macrobrachium amazonicum (Heller, 1862) in Neotropical reservoirs under drought events

Here, we describe population and reproductive dynamics of four populations of Macrobrachium amazonicum in reservoirs during drought events. Additionally, we analyze possible phenotypic changes in this species promoted by fish predation. Two populations had a large-size phenotype (with large body proportions and morphotypes in males) while a small-size phenotype (with reduced sizes and no morphotypes) was found in the two other populations. Overall, females were larger than males and there were varying sex ratios among the four studied populations. All populations had bimodal or polymodal patterns in their monthly size-class frequency, suggesting a seasonal influence and a potentially great capacity of these populations to adapt to adverse environmental conditions. No major changes were found in the patterns of sex ratio, recruitment, frequency of (larger) male morphotypes and female ovarian development stages during drought events. Macrobrachium amazonicum is a resilient species and undergoes continuous reproduction. Females with immature ovaries were predominant in all populations, performing multiple spawns and exhibiting rapid ovarian development cycles. In males, the initial morphotype (TC - translucent claw) was predominant in populations with a social hierarchy. Males of dominant morphotypes (GC1 and GC2 - green claw 1 and 2) use more energy to carry out and maintain metabolic processes, which could probably one of the explanations why their number in populations are limited. We did not find any clear evidence that fish predation affected phenotypes, suggesting that phenotypic plasticity could be more related to intrinsic factors, which would have to be further investigated.

Machine Learning for the Sustainable Management of Depth Prediction and Load Optimization in River Convoys: An Amazon Basin Case Study

The seasonal fluctuation of river depths is a critical factor in designing cargo capacity for river convoys and logistics processes used for grain transportation in northern Brazil. Water level variations directly impact the load capacities of pusher convoys navigating the Amazon rivers. This paper presents a machine learning model based on a multilayer perceptron artificial neural network developed with the aim of estimating the cargo capacities of river convoys one year in advance, which is essential for determining load capacities during dry periods. The prediction model was applied to the Tapajós River in the Amazon Basin, Brazil, where grain transportation is significant and relies on inland waterways. Navigability conditions were evaluated in terms of depth and geometric parameters. The results of this case study were satisfactory, validating the computational tool and enabling the assessment of capacity losses during dry periods and the identification of navigation bottlenecks. The main contributions of this work include optimizing river logistics, reducing costs, minimizing environmental impacts, and promoting the sustainable management of water resources in the Amazon. Conclusions drawn from the study indicate that the developed model is highly effective, with an R2 of 0.954 and RMSE of 0.095, demonstrating its potential to significantly enhance river convoy operations and support sustainable development in the region.

Ecological index analysis in the coastal and estuarine waters of the tropical Amazon Region

The Brazilian Amazon Coastal Zone holds the largest estuarine area in the world, located in the Amazon Continental Shelf (ACS). Additionally, it encompasses numerous estuaries and channels, such as Furo do Muriá (FM) and Furo da Laura (FL), which make up the local landscape and favor the primary productivity of water. The objective of this study was using the trophic index (TRIX) and O'Boyle index to determine the trophic state in the ACS area, FL, and FM, compare the results, and relate them to seasonality and river discharge in the sites. In the three estuaries, the applied methodology was the same: temperature, salinity, pH, dissolved oxygen, and saturation rate of dissolved oxygen data were obtained in situ, and the samples were filtered for the analysis of nitrite, nitrate, ammonia, phosphate, and chlorophyll a. The highest TRIX values were found in FL (3.89–3.12) and ACS (4.43–4.44), while for the O'Boyle index, the highest values were found in FL (16.73–100) and FM (43.3–100). Comparing the indices, it was observed that their classification was similar only in the ACS during the period of maximum discharge of the Amazon River (eutrophic), varying slightly in the minimum discharge period (potentially eutrophic for O'Boyle and eutrophicated for TRIX). This difference can be explained by the additional variables considered by the TRIX, such as nutrients and chlorophyll a. The scenario was completely different for FM and FL, where the TRIX showed greater variation owing to the presence of dissolved inorganic nutrients. Both indices can be used to simply and directly reflect the eutrophication conditions of estuarine areas: the joint and multiparametric approach of the indices provides complementary information regarding the dynamics of studied environments through their trophic status.

The seasonal rate of discharge change as the primary trigger synchronizing freshwater fish reproduction in an Amazonian River

The seasonal rate of discharge change as the primary trigger synchronizing freshwater fish reproduction in an Amazonian River