Amazon Region Research Articles

A new species of Alipumilio Shannon, 1927 (Diptera: Syrphidae), with the description of the male of A. avispas Vockeroth, 1964 and A. femoratus Shannon, 1927

Alipumilio Shannon, 1927 is a flower fly genus endemic to the New World, comprising five described species. In the present study we describe Alipumulio aureus sp. nov. from the Colombian Amazon region. This is the first record of this genus from Colombia. Additionally, the male of A. avispas Vockeroth, 1964 is described from Peru and the male of A. femoratus Shannon, 1927 is described from new material collected in Ecuador. Moreover, we provide an identification key to all the Alipumilio species and a species distribution map.

Analysis of environmental variables and deforestation in the amazon using logistical regression models.

In this study, we applied a multivariate logistic regression model to identify deforested areas and evaluate the current effects on environmental variables in the Brazilian state of Rondônia, located in the southwestern Amazon region using data from the MODIS/Terra sensor. The variables albedo, temperature, evapotranspiration, vegetation index, and gross primary productivity were analyzed from 2000 to 2022, with surface type data from the PRODES project as the dependent variable. The accuracy of the models was evaluated by the parameters area under the curve (AUC), pseudo R2, and Akaike information criterion, in addition to statistical tests. The results indicated that deforested areas had higher albedo (25%) and higher surface temperatures (3.2°C) compared to forested areas. There was a significant reduction of the EVI (16%), indicating water stress, and a decrease in GPP (18%) and ETr (23%) due to the loss of plant biomass. The most precise model (91.6%) included only surface temperature and albedo, providing important information about the environmental impacts of deforestation in humid tropical regions.

Kinetics of phosphorus release from sedimentary rocks as a potential source of fertilizers in the Amazon region, Brazil

Brazil is the seventh-largest phosphate producer globally, contributing to almost 3% of total production. Approximately 20% of the country's phosphate output comes from sedimentary sources, while the remaining 80% is of magmatic origin. The growing demand for phosphate has sparked increased interest in identifying new deposits. In northwestern Brazil, a phosphate rocks in the São Benedito Formation, part of the Alto Tapajós Group in the Apuí region of Amazonia, has attracted attention.Twelve outcrops were collected for mineral and chemical analysis, solubility testing in aqueous media, standard tests using citric acid, and P2O5 release kinetics. The raw material consists of compacted gray quartz sandstone containing fluorapatite, glauconite, and siderite. The raw samples exhibited total P2O5 content of up to 6%. Additional elements were assessed, with only CaO and Fe2O3 showing total contents reaching 8.05 wt% and 6.65 wt%, respectively. Kinetic extraction in a 2% citric acid solution revealed a positive correlation between soluble and total contents of CaO and P2O5 indicating apatite composition. The elements showed solubility exceeding 60% within the first 30 min and reaching 100% after 180 min. However, as the fluorapatite and siderite dissolved, the citric acid solution became saturated, halting the dissolution process. These results indicate effectiveness in solubilizing phosphate in samples with less than 4 to 5 wt% of P2O5, meeting the minimum requirements established by the Brazilian Ministry of Agriculture. These characteristics suggest that the São Benedito Formation phosphate rocks have agronomic value for use as direct/natural fertilizers in Brazil's tropical acidic soils.

Evaluation of the PM2.5 concentrations in South America: Climatological patterns and trend analysis

This study assessed the concentration of particulate matter with an aerodynamic diameter of 2.5 (PM2.5) over South America (SA) based on climatological patterns and trend analysis. This study used monthly PM2.5 data from the Copernicus Atmosphere Monitoring Service (CAMS) at the European Centre for Medium-range Weather Forecasts from 2003 to 2022. The bilinear interpolation method was applied to the data resampling from 0.75° × 0.75°–0.25° × 0.25° spatial resolution, and subsequently, the climatological analysis was performed on seasonal and annual scales of PM2.5 concentrations for the 20-year series. The assessment comprised three main stages: 1) descriptive statistics, 2) seasonal and annual climatology patterns, and 3) trend analysis (Mann-Kendall - MK and Pettitt tests). Results indicated that the largest annual PM2.5 concentrations were found in the Amazon region and northern Paraguay due the El-Niño South Oscillation events (2003–2005, 2007, 2010, 2020, and 2022). The annual average PM2.5 concentrations exceeded the WHO recommended limit (5 μg m−3), ranging from 15.57 μg m−3 (1999) and 22.74 μg m−3 (2007 and 2010). The highest PM2.5 concentrations were observed in the Amazon and Chile (Santiago), reaching 160.4 μg m−3 annually and 177.8 μg m−3 seasonally (spring). Elevated seasonal PM2.5 concentrations were attributed to increased deforestation and wildfires associated with meteorological systems such as the Bolivian high and subtropical jets during dry periods (winter and spring). The MK test revealed a significant reduction in PM2.5 concentrations between 2003 and 2022, observed in Argentina (north), Brazil (arc of reforestation), Bolivia (south), and Chile (north). Reduction values varied between 0.5 and 10 μg m−3.year−1 annually and during winter, attributed to no-tillage practices in regions cultivating commodities. The Pettitt test also identified significant structural changes occurring in 2006–2008 and 2010–2011, aligning with areas highlighted in the MK test. This study provides valuable insights for air quality and environmental monitoring managers to mitigate PM2.5 pollution in SA.

Evaluation and Ranking of Energy Alternatives for Implementation in Different Geographic Scenarios using Decision Methods: Case Study of Colombia

In this research, several crucial aspects have been explored in the evaluation and ranking of energy alternatives in Colombia using advanced decision methods such as TOPSIS and Diffuse TOPSIS. The study analyzed how these techniques allow to effectively compare different renewable energy sources in various regions of the country, highlighting the importance of considering multiple approaches due to the unique geographical and energy characteristics of each region. Specifically, five regions were evaluated: Caribbean 1 and 2, Pacific 1 and 2, Andean, Amazonian and Orinoquia, observing significant differences in the evaluation of technologies between the models. In the evaluation of energy sources for each region, the potential of photovoltaic solar energy in the Caribbean and Orinoquia regions was emphasized due to the high solar radiation, wind energy in the Caribbean and Pacific regions due to its strong winds, and biomass in the Amazon and Andean regions thanks to the abundance of organic resources. These technologies not only contribute to the reduction of carbon emissions and the diversification of the energy matrix, but also promote a just energy transition by generating employment and improving the quality of life in local communities. The TOPSIS method and its diffuse variant make it possible to weigh criteria with different degrees of importance and manage uncertainty in decision-making, resulting in more precise evaluations adapted to specific contexts. This type of research is vital for decision-making in the Colombian electricity sector, as it provides a solid and replicable methodology for evaluating energy alternatives in an integral way. The results not only contribute to environmental sustainability, but also boost the socio-economic development of the regions, fostering an equitable and fair energy transition.

Tree mortality by ecological groups in the amazon region: Influence of forest structure, soil characteristics, and extreme climatic events after logging

Mortality of remaining trees tends to increase after logging, and adapting forest management to climate change is another significant challenge to ensure the sustainability of forests, timber production, and provision of ecosystem services. This study investigated mortality in remaining trees (DBH ≥ 20 cm) in different ecological groups (pioneer, light-demanding, and shade-tolerant) during different phases of forest monitoring (initial, intermediate, and final), as well as their relationship with structural, climatic, and environmental characteristics. The research was conducted in five managed areas in the Brazilian Amazon (Jari, Km114, Km67, Peteco, and Moju) with continuous monitoring over six to 33 years. We analyzed a total of 212 permanent plots containing 62 pioneer species, 250 light-demanding species, and 304 shade-tolerant species. The mortality rate for the three monitoring phases in logged forests was 1.27 %, 1.49 %, and 0.75 % year−1, respectively, while the rate in unlogged forests was 1.04 %, 1.33 %, and 0.50 % year−1. In post-logging forests, mortality was high for pioneer and light-demanding species, especially in the initial phase. For shade-tolerant species, mortality rate was influenced by soil silt and sand content, presence of phosphorus, and total carbon content. In unlogged forests, forest structure variables such as average height and total basal area, soil characteristics like phosphorus content, and climate factors such as intensity of dry months were most important for pioneer and light-demanding species. In the intermediate and final monitoring phases in logged forests, tree mortality was related to soil characteristics like sand and clay content, total carbon, and cation exchange capacity. Extreme climatic events such as severe drought, El Niño, and extreme temperatures also influenced tree mortality, along with time elapsed after logging. These findings highlight the complex interaction between soil characteristics, climate, and forest structure and tree mortality and ecology. These correlations are crucial to understand mortality processes in logged and unlogged forests, underscoring the importance of these factors for managing and conserving these ecosystems in the face of extreme climatic events and forest management practices.

A novel analytical approach in Amazon fish chain: Using infrared-spectroscopy with chemometric tools to identify non-typhoid Salmonella

The tambaqui (Colossoma macropomum) is one of the main native fish species in the Amazon region of Brazil, with economic, nutritional, cultural and environmental importance for the country. However, the presence of pathogens such as Salmonella in this matrix poses a threat to the safety and potential of this food chain. In response, this study aimed to develop a rapid, non-destructive approach to detecting Salmonella enterica serovar Schwarzengrund in tambaqui samples, using Fourier Transform Mid-Infrared Spectroscopy (FT-MIR) spectral data combined with the Data-Driven - Soft Independent Modeling of Class Analogy (DD-SIMCA) method. For this purpose, seventy-two samples of tambaqui ribs were purchased from supermarkets. Two groups of samples were used to build the model: control and contaminated with Salmonella. FT-MIR spectra were checked and four relevant regions were analyzed: all spectrum (4000–550 cm-1), region 1 (1490–500 cm-1), region 2 (1500–1730 cm-1), and region 3 (2835–4000 cm-1). The results revealed that region 1 proved to be the best for classifying contaminated samples from those not contaminated with Salmonella, with the best predictive performance with an accuracy of 94.2%. Our model exhibited the potential to be applied to the identification of Salmonella in tambaqui and to be a valuable tool for guaranteeing the safety and authenticity of fish products in the Brazilian Amazon region and, potentially, beyond. However, the use of FT-MIR combined with DD-SIMCA could be further explored in the future with a larger sample database, in order to verify the model's performance when the entire spectrum, regions 2 and 3 are used.

A Genome-Focused Investigation Reveals the Emergence of a Mycobacterium tuberculosis Strain Related to Multidrug-Resistant Tuberculosis in the Amazon Region of Brazil.

A previous study in Pará, Northern Brazil, described a strain of Mycobacterium tuberculosis with a unique genotype (SIT2517/T1) associated with multidrug-resistant tuberculosis (MDR-TB). To improve our understanding of MDR-TB transmission dynamics of these strains within this region, we performed phenotypic and genotypic drug susceptibility testing (pDST/gDST), 24-loci mycobacterial interspersed repetitive units (MIRU-VNTR) genotyping, whole-genome sequencing (WGS) and geo-epidemiology analysis. Of the 28 SIT2517/T1 isolates, 19 (67.9%) could be genotyped by 24-loci MIRU-VNTR and 15 by WGS. All belonged to sublineage 4.1.1.3, distinct from other representative Lineage 4 isolates identified in Brazil. The MDR phenotype determined by pDST was confirmed by gDST, the latter also demonstrating the presence of additional mutations conferring pre-extensively drug-resistance (pre-XDR). Discrepancies between gDST and pDST were observed for pyrazinamide and fluoroquinolones. Thirteen out of 15 isolates analyzed by WGS were clustered when applying a 12 single nucleotide polymorphisms (SNPs) cutoff. The SIT2517/T1 isolates were distributed across the metropolitan regions of Belém and Collares municipalities, showing no geographic clustering. WGS-transmission network analysis revealed a high likelihood of direct transmission and the formation of two closely linked transmission chains. This study highlights the need to implement TB genomic surveillance in the Brazilian Amazon region.

PROPOSAL FOR AN EMBRYONIC MODEL TO PROMOTE SMART CITIES, IMPLEMENTED IN A BOTTOM-UP FORMAT, APPLIED TO THE AMAZON REGION

Environmental changes, many of which result from human negligence, have driven managers to adopt sustainable practices that adhere to the concept of Smart Cities, a concept that is becoming popular among administrators of Brazilian metropolises. This movement has been corroborated by ABNT standards and the federal government. However, in less developed regions such as Northern Brazil, where challenges are greater and resources are limited, traditional top-down urban development strategies such as BRTs have proven inefficient as initial solutions. This article investigates the feasibility of implementing projects for Smart Cities in the Amazon region given the scarcity of resources. It proposes an alternative bottom-up model titled Smart Launch, which is shown to be more viable for sustainable development in regions with these characteristics. The model recommends starting with smaller and more manageable projects that can be easily implemented without extensive bureaucracy or significant investments. Once established, the model can be quickly replicated and adapted in other locations. The case of the UsiPaz (Peace Plants) in Pará exemplifies the success of this approach and has been taken as a case study, showing significant reduction in violence rates and an increase in the sense of community belonging, as evidenced by qualitative research through semi-structured interviews with managers from three plants in different neighborhoods of the metropolitan region of Belém.

Influence of indole-butyric acid and substrate type on vegetative propagation of native Peruvian blueberry (Vaccinium sp.)

In the Amazon region of Peru, native blueberries are found in high Andean areas, where they are associated with small shrubs and mosses. These blueberries prefer shallow soils with a sandy-clay texture and low fertility. However, their population is threatened by their limited regenerative capacity and various anthropogenic factors. The aim of this study was to evaluate the influence of indole butyric acid and substrate type on the vegetative propagation of native Peruvian blueberry (Vaccinium sp.) grown in microtunnel. The experiment was conducted under a complete randomized design with the factorial arrangement; A: substrate (sand 100%, sand + coconut fiber 1:1 v/v and coconut fiber 100%) and B: AIB concentrations (1, 2 and 3 g L-1) and control (0 g L-1), giving 12 treatments, three replicates and 36 experimental plots. In the field, apical shoots of blueberry with semi-lignified and vigorous stems were collected. In the laboratory, they were disinfected with fungicide and cut to a size of 7 cm. Subsequently, they were treated with AIB and planted in prepared substrates. After 120 days in the microtunnel, it was observed that blueberry cuttings showed higher survival in sand + coconut fiber (94.7%), rooting (73.8%), root number (6.9), and root growth (9.2). AIB concentrations at 2 and 3 g L-1 had a greater effect on rooting, with values above 60%. The use of suitable substrates and auxin concentrations significantly favors the vegetative propagation of native blueberries. This propagation technique is postulated as a promising alternative for the mass propagation of this species for the conservation and rehabilitation of degraded ecosystems.

Lower Microscopy Sensitivity with Decreasing Malaria Prevalence in the Urban Amazon Region, Brazil, 2018-2021.

Malaria is increasingly diagnosed in urban centers across the Amazon Basin. In this study, we combined repeated prevalence surveys over a 4-year period of a household-based random sample of 2,774 persons with parasite genotyping to investigate the epidemiology of malaria in Mâncio Lima, the main urban transmission hotspot in Amazonian Brazil. We found that most malarial infections were asymptomatic and undetected by point-of-care microscopy. Our findings indicate that as malaria transmission decreases, the detection threshold of microscopy rises, resulting in more missed infections despite similar parasite densities estimated by molecular methods. We identified genetically highly diverse populations of Plasmodium vivax and P. falciparum in the region; occasional shared lineages between urban and rural residents suggest cross-boundary propagation. The prevalence of low-density and asymptomatic infections poses a significant challenge for routine surveillance and the effectiveness of malaria control and elimination strategies in urbanized areas with readily accessible laboratory facilities.

Production and toxicological analysis of a powdered beverage based on Brazil nut milk and acai

Considered one of the main seeds in the Amazon region, the Brazil nut (Bertholletia excelsa) has a very high nutritional and economic potential, being rich in minerals and serving as an alternative source of proteins. Allied to it, there is açaí (Euterpe oleracea), an extremely energetic Amazonian fruit, rich in anthocyanins with antioxidant power and with several benefits for the body. In this context, the project aimed to combine these beneficial characteristics of these two foods to create a healthy product with high energy potential, also carrying out its toxicological analysis, measuring the level of selenium and the presence of aflatoxins at the end of the process. It was then observed that the produced product showed potentially positive results, however, specific legislation for these functional beverages is necessary .

Stratified sampling for roots biomass quantification in shifting cultivation in Amazon Brazil

Several countries have been paying attention to carbon stocks and balances in the soil, a characteristic related to land management and use. Among the biomes that have great participation in the maintenance of these stocks, the Amazon biome stands out, which has great diversity by area. With the advances in markets aimed at buying carbon credits, estimates of the values of these stocks are highly susceptible to the intrinsic characteristics of the location. In order to solve these problems, several soil sampling techniques have been used to estimate these values. However, soil sampling techniques vary greatly in the amount of soil sampled, directly impacting the values of these estimates. In this sense, the present work aims to evaluate the point and interval estimates of carbon stocks in the soil in a peripheral region of the Brazilian Amazon, in the state of Maranhão. For this, three soil sampling techniques were compared, the large monolith (LM), the small monolith (SM) and the auger (RA). Considering a stratified sampling plan (STR), in which the different sampled depths are considered as strata, its efficiency was compared to a simple random sampling (SRS) and its amplitudes with the simulation through the Bootstrap technique. The samples were obtained by washing the samples and separating them into < 2mm and > 2mm for two biological groups (babassu roots and other roots). For interval estimates with the LM collection method, roots larger than 2 mm have a total of 2.56 to 4.62 t ha–1, and for smaller roots, 1.67 to 4.33 t ha–1. As for babassu roots, these values ranged from 0.38 to 1.44 t ha–1 and those smaller than 2 mm from 0.86 to 2.43. In contrast, the LM collection method can be replaced by SM and RA only for thick roots (> 2 mm). Regarding the STR sampling plan, the variance of the total was reduced in relation to the SRS. The bootstrap technique managed to reduce the amplitude of the intervals to the total, showing an improvement in accuracy. Therefore, estimates of carbon stocks can be made for the RA method for stored carbon, but the method for carbon that will return to the atmosphere the LM method is the most suitable.

New insights into Oropouche: expanding geographic spread, mortality, vertical transmission, and birth defects.

Oropouche virus (OROV) is an arbovirus transmitted by midges that is now emerging outside the Amazon region. For the first time, fatal cases were reported, and possible vertical transmission of OROV is under investigation. Knowledge gaps remain concerning the natural history of OROV infection, host immune response and vector competence.

New Records of Sharpshooters (Hemiptera, Cicadellidae, Cicadellinae) in Citrus Orchards in Amazonas State, Brazil.

This research study reports new records of eight species of Cicadellini (Hemiptera, Cicadellidae, Cicadellinae) across seven municipalities in Amazonas State, Brazil. Among these species, one is known as a vector of CVC (Provancherana corniculata). Additionally, five species are being reported for the first time in citrus for the State (Erythrogonia sexguttata, Hortensia similis, Provancherana corniculata, Scopogonalia amazonensis, and Scoposcartula oculata), and three species (Diedrocephala variegata, Macugonalia moesta and Xyphon reticulatum) are reported for the first time in the northern region. This research highlights the lack of information on sharpshooter occurrence in the Amazonas region, emphasizing the need for further investigations in this area.

Physiological and biochemical responses of the achachairu tree (Garcinia humilis) to prolonged flooding

Flooding and waterlogging create hypoxic or anoxic soil conditions that negatively affect the physiology of wild and cultivated tropical fruit trees. The achachairu (Garcinia humilis) is a slow-growing tropical fruit tree endemic to the Bolivian Amazon region. Like many tropical trees, G. humilis is increasingly affected by flooding events that may threaten its natural and cultivated areas, but its physiological and biochemical responses to prolonged flooding have not been reported. This study assessed the physiological, biochemical, and morphological responses of G. humilis to prolonged flooding of different durations for up to 30 d Physiological variables measured included leaf gas exchange [net CO2 assimilation (A), stomatal conductance of H2O (gs), and intercellular CO2 concentration (Ci)], leaf chlorophyll index (LCI), and the ratio of variable to maximum chlorophyll fluorescence (Fv/Fm). Antioxidant responses, such as superoxide dismutase (SOD), peroxidase (POD), catalase (CAT), ascorbate peroxidase (APX), glutathione (GSH), glutathione reductase (GTR), dehydroascorbate reductase (DHAR), monodehydroascorbate reductase (MDAR), ascorbic acid (AsA), and glutathione (GSH); reactive oxygen species (ROS); and lipid peroxidation indicated by malondialdehyde (MDA) were also measured. Results indicate that G. humilis is very tolerant of flooding periods of at least 30 d, which causes approximately a 50 % reduction in net A but no measurable negative impact on other physiological variables, including LCI and Fv/Fm. Flooding caused an increase in ROS and malonaldehyde (MDA), which were countered by a robust antioxidant response that possibly contributed to improved flooding tolerance. Plants continued to grow during the flooding period, and A recovered to nearly pre-flooding levels 90 d after plants were unflooded.

Marine catfishes (Ariidae-Siluriformes) from the Coastal Amazon: mitochondrial DNA barcode for a recent diversification group?

Ariidae species play a significant role as fishing resources in the Amazon region. However, the family's systematic classification is notably challenging, particularly regarding species delimitation within certain genera. This difficulty arises from pronounced morphological similarities among species, posing obstacles to accurate species recognition. Following morphological identification, mitochondrial markers (COI and Cytb) were employed to assess the diversity of Ariidae species in the Amazon. Our sampling efforts yielded 12 species, representing 92% of the coastal Amazon region's diversity. Morphological identification findings were largely corroborated by molecular data, particularly for species within the Sciades and Bagre genera. Nonetheless, despite morphological support, Cathorops agassizii and Cathorops spixii displayed minimal genetic divergence (0.010). Similarly, Notarius quadriscutis and Notarius phrygiatus formed a single clade with no genetic divergence, indicating mitochondrial introgression. For the majority of taxa examined, both COI and Cytb demonstrated efficacy as DNA barcodes, with Cytb exhibiting greater polymorphism and resolution. Consequently, the molecular tools utilized proved highly effective for species discrimination and identification.

Acceptability and Feasibility of Provision of COVID-19 Services by Community Health Workers to Remote Gold Mining Communities in Suriname.

Gold mining communities in the Amazon region typically have limited access to public health services. In Suriname, the Ministry of Health Malaria Program (MoH-MP) works with community health workers (CHWs), people from mining communities without a formal medical degree, to provide malaria diagnostic and treatment services. During the COVID-19 pandemic, the MoH-MP trained 21 of these CHWs in COVID-19 outreach and testing, using rapid antigen tests for symptomatic persons in their communities; afterward, a mixed methods research approach was used to investigate whether including COVID-19 services in the tasks of the CHWs was feasible and accepted among gold mining populations. Also, CHWs took part in active case detection missions to proactively offer COVID-19 testing to all inhabitants of specific mining areas, regardless of symptoms. In the 6 months of field implementation (May-October 2022), 1,300 persons were tested for COVID-19, among whom 28.7% were women. Eight percent tested positive. Of the 312 asymptomatic persons tested, 2.2% tested positive. Qualitative semi-structured interviews with the CHWs and quantitative pre- and postintervention surveys revealed that the communities appreciated the nearby and free COVID-19 testing opportunity. The intervention motivated individuals who otherwise would not have been tested to test for COVID-19. Twenty-nine percent of those who had tested at least once for COVID-19 reported that their most recent test was conducted through the services of the CHWs. The results suggest that integrating COVID-19 testing into other CHW services can lower health access barriers in difficult-to-reach populations in remote communities.

A Machine Learning Predictive Model for Ship Fuel Consumption

Water navigation is crucial for the movement of people and goods in many locations, including the Amazon region. It is essential for the flow of inputs and outputs, and for certain Amazon cities, boat access is the only option. Fuel consumption accounts for over 25% of a vessel’s total operational costs. Shipping companies are therefore seeking procedures and technologies to reduce energy consumption. This research aimed to develop a fuel consumption prediction model for vessels operating in the Amazon region. Machine learning techniques such as Decision Tree, Random Forest, Extra Tree, Gradient Boosting, Extreme Gradient Boosting, and CatBoost can be used for this purpose. The input variables were based on the main design characteristics of the vessels, such as length and draft. Through metrics like mean, median, and coefficient of determination (R2), six different algorithms were assessed. CatBoost was identified as the model with the best performance and suitability for the data. Indeed, it achieved an R2 value higher than 91% in predicting and optimizing fuel consumption for vessels operating in the Amazon and similar regions.

On a new species of ostracod from the Brazilian Amazon and its potential for experimental studies in laboratory culture

Ostracods are taxonomically and ecologically diverse small crustaceans that have recently gained prominence in laboratory studies and environmental impact assessment. In this context, the present study aims to assess the applicability of a new freshwater ostracod for experimental studies in the laboratory, and we provide the formal description of Strandesia rondoniensisn. sp. The original specimens for setting the laboratory cultures originated from the Natural Park of Porto Velho, in the Amazon region (Rondônia State, Brazil). The growth and reproductive rates of eleven adult individuals of S. rondoniensisn. sp. were analyzed. The results showed a high morphological resemblance with Neostrandesia striata and Bradleytriebella lineata, even though the new species belongs to Strandesia, indicating evolutionary convergence. The life cycle analysis showed that individuals of S. rondoniensisn. sp. have fast growth and high reproductive rates, which favour their use in laboratory studies. Besides contributing to the knowledge about ostracods in the Amazon region, which has been poorly studied, the life cycle experiment characterizations provided here should promote the use of this new species as a model organism for laboratory studies.