The use of medicinal plants for the therapy of diseases of the digestive system; where the Andean peoples developed various forms of administration. The objective being the identification of medicinal plants used in the therapy of ailments of the digestive system by the Andean inhabitants of Pampas, Tayacaja, Huancavelica, Peru. Methods, non-probabilistic sampling, using the “snowball” technique, carrying out semi-structured surveys, allowing information to be collected on the prevalence of ailments or diseases of the digestive system treated with medicinal plants, with inhabitants over 20 years of age participating and using the medicinal plants in the therapy of your digestive system ailments; and, exclude those inhabitants who do not comply with it. Results, 16 families, 33 genera and 34 species are reported; where the families that present the greatest abundance of species are Asteraceae, Lamiaceae; Likewise, the widely used species are Minthostachys mollis (11.9%), Aloe vera (10.4%), Clinopodium bolivianum (9%), Artemisia absinthium (9%) and Matricaria chamomilla (8.2%). Concluding with the identification of a diversity of medicinal flora, used in the therapy of diseases of the digestive system, such as stomach pain, constipation, gallbladder ailments, gastritis, gastrointestinal and liver diseases.

Flood Early Warning Systems (FEWSs) using Machine Learning (ML) has gained worldwide popularity. However, determining the most efficient ML technique is still a bottleneck. We assessed FEWSs with three river states, No-alert, Pre-alert, and Alert for flooding, for lead times between 1 to 12 hours using the most common ML techniques, such as Multi-Layer Perceptron (MLP), Logistic Regression (LR), K-Nearest Neighbors (KNN), Naive Bayes (NB), and Random Forest (RF). The Tomebamba catchment in the tropical Andes of Ecuador was selected as case study. For all lead times, MLP models achieve the highest performance followed by LR, with f1-macro (log-loss) scores of 0.82 (0.09) and 0.46 (0.20) for the 1- and 12-hour cases, respectively. The ranking was highly variable for the remaining ML techniques. According to the g-mean, LR models correctly forecast and show more stability at all states, while the MLP models perform better in the Pre-alert and Alert states. Future efforts are recommended to enhance the input data representation and develop communication applications to boost the awareness of the society for floods.

Our study analyzes the ecology and distribution of fish communities related to the environmental variables of the Alto Madre de Dios River, an Andean-Amazon watershed of southern Peru, between 300 and 2811 m a.s.l. within the Manu Biosphere Reserve. We provide new ecological and diversity data for these highly unknown rivers and new data for palm swamp habitats. With electric fishing techniques, we collected a total of 1934 fish specimens belonging to 78 species, 42 genera and 15 families. To assess main patterns of diversity we combined SIMPER and ANOSIM with canonical correspondence analysis to obtain an overview of the community structure of fish and their distribution related to aquatic habitats. Our results show an important shift on fish diversity at 700 m a.s.l. separating headwater and middle-lowland communities. Electrofishing was a hindrance due to the depth, flow and low conductivity of the rivers, but also allowed us to capture fish not observed with other techniques. We also compared the use of elevation with slope as an alternative variable for statistical analysis. Our results show that slope offers a solid and equivalent explanation for fish distribution variability, avoids redundance, and instead of giving geographical data offers ecologically solid information.

We present here seven new zircon (U-Th)/He (ZHe) ages and three new zircon fission track ages (ZFT) analyzed from an age-elevation profile (Machu Picchu, Peru). ZFT data present older ages in comparison with the other thermochronological data, whereas the ZHe data interestingly present similar ages than the ones obtained with apatite (U-Th)/He (AHe). It has been proposed that He retention in zircon is linked to the damage dose, with an evolution of the closure-temperature from low values associated to low α-dose (<1016 α/g), subsequently increasing before decreasing again at very high α-dose (>1018 α /g). Studies have been focused on the He diffusion behavior at high α-dose, but little is known at low dose. We propose that the ZHe closure temperature at α-dose ranging from 0.6×1015 to 4×1016 α/g is in the range of ~60-80°C. This value is lower than the one proposed in the current damage model ZRDAAM and demonstrates that the ZHe and AHe methods could have similar closure temperatures at low α-dose (i.e. similar ages). These new data strengthen our previous geological conclusions and even highlight an about twice more important cooling rate than the one deduced from AHe and apatite fission-track data alone registered at Machu Picchu.

In soil erosion estimation models, the variable with the greatest impact is rainfall erosivity (RE), which is the measurement of precipitation energy and its potential capacity to cause erosion, and erosivity density (ED), which relates RE to precipitation. The RE requires high temporal resolution records for its estimation. However, due to the limited observed information and the increasing availability of rainfall estimates based on remote sensing, recent research has shown the usefulness of using observed-corrected satellite data for RE estimation. This study evaluates the performance of a new gridded dataset of RE and ED in Peru (PISCO_reed) by merging data from the IMERG v06 product, through a new calibration approach with hourly records of automatic weather stations, during the period of 2000-2020. By using this method, a correlation of 0.7 was found between the PISCO\_reed and RE obtained by the observed data. An average annual RE for Peru of 4831 MJ·mm·ha-1·h-1 was estimated with a general increase towards the lowland Amazon regions and high values are found on the north-coast Pacific area of Peru. The spatial identification of the most risk areas of erosion, was carried out through a relationship between the ED and rainfall. Both erosivity data sets will allow us to expand our fundamental understanding and quantify soil erosion with greater precision.

The research presents the inter-comparison of atmospheric variables measured by 9 automatic meteorological stations. This set of data was compared with the measurements of other meteorological stations in order to standardize the values that must be adjusted when taken to different areas. The data of a set of a total of 9 GMX500, which measures conventional meteorological variables, and 10 WS100 sensors, which measures precipitation parameters. The automatic stations were set up at the Huancayo Observatory (Geophysical Institute of Peru) for a period of 5 months. The data set of GMX500 were evaluated comparing with the average of the 9 sensors and the WS100 was compared with a optical disdrometer Parsivel2. The temperature, pressure, relative humidity, wind speed, rainfall rate, and drop size distribution was evaluated. A pair of GMX500 sensors presented high data dispersion, it was found found that the errors came from a bad configuration; once this problem was solved, good agreement was archived, with low RMSE and high correlation. I was found that the WS100 sensors overestimate the precipitation with a percent bias close to 100% and the differences increase with the greater intensity of rain. The DSD retrieved by WS100 have unrealistic behavior with higher concentrations in diameters of 1 mm and 5 mm, in addition to a flattened curve.

Flood modeling and forecasting are key to managing and preparing for extreme flood events. Hydrological flood forecasting aims to predict the system response to different input changes with minimum uncertainties. In that sense, streamflow Data Assimilation (DA) seeks to combine errors between hydrological model and water discharge observations through the update of model states. This paper aims to assess a sub-daily flood forecast system in a basin of the Peruvian Tropical Andes using two sequential data assimilation algorithms called the Ensemble Kalman Filter (EnKF) and the Particle Filter (PF). The study was conducted in the Vilcanota River basin during the rainiest months in 2022 to assess recent potential river floods. This basin is in the southern Peruvian Andes and was selected because it is continually affected by river floods such as occurred in 2010. For this purpose, the lumped GR4H rainfall-runoff model was run forward with 100 ensemble members using two different Satellite Precipitation sources (IMERG-E' and GSMaP-NRT'). Also, four DA experiments (IMERG-E'+EnKF, IMERG-E'+PF, GSMaP-NRT'+EnKF, and GSMaP-NRT'+PF) were conducted by assimilating real-time hourly discharges at the Pisac stream gauge station to examine the improvement of forecast accuracy for lead times of 1—24 hours. Results display good forecast performances during the first 10 hours, especially for the GSMaP'+EnKF scheme. Finally, this work benchmarks the application of streamflow DA in and Andean basin of Peru with sparse data availability and will support the development of more accurate climate services in Peru through hydrologic ensemble predictions.

Hantavirus cardiopulmonary syndrome (HCPS) is characterized by capillary leak, pulmonary edema (PE) and shock that leads to death in up to 40% of patients. Treatment is supportive, including mechanical ventilation (MV) and extracorporeal membrane oxygenation (ECMO). Hemodynamic monitoring is critical to titrate therapy and to decide ECMO support. Transpulmonary thermodilution (TPTD) provides hemodynamic and PE data that has not been systematically used to understand HCPS pathophysiology. We identified 11 HCPS patients monitored with TPTD; 5 on MV, 3 on ECMO. We analyzed 133 measurements to describe the hemodynamic pattern and its association to PE. The main findings were reduced stroke volume, global ejection fraction (GEF) and preload parameters associated to increased extravascular lung water and pulmonary vascular permeability compatible with hypovolemia, myocardial dysfunction and increased permeability PE. Lung water correlated positively with heart rate (HR, r=0.20) and negatively with mean arterial pressure (r=-0.27) and GEF (r=-0.36), suggesting that PE is linked to hemodynamic impairment. Pulmonary vascular permeability correlated positively with HR (r=0.31) and negatively with cardiac index (r=-0.49), end-diastolic volume (r=-0.48) and GEF (r=-0.40), suggesting that capillary leak contributes to hypovolemia and systolic dysfunction. In conclusion, TPTD data suggests that in HCPS patients, increased permeability leads to PE, hypovolemia and circulatory impairment.

Accurate detection and quantification of regional vegetation trends is essential for understanding the dynamics of landscape ecology and vegetation distribution. We applied a comprehensive trend analysis to satellite data to describe geo-spatial changes in vegetation along the Pacific slope of Peru and northern Chile, from sea level to the continental divide, a region characterised by biologically unique and highly sensitive arid and semi-arid environments. Our statistical analyses show broad regional patterns of positive trends in EVI, called “greening” alongside patterns of “browning” where trends are negative between 2000 and 2020. The coastal plain and foothills, up 1000m, contain notable greening of the coastal Lomas and newly irrigated agricultural lands occurring alongside browning trends related to changes in land use practices and urban development. Strikingly, the precordilleras show a distinct ’greening strip’ which extends from approximately 6°S to 22°S, with an altitudinal trend; ascending from the tropical lowlands (170-780 m) in northern Peru, to the subtropics (1000-2800 m) in central Peru, and temperate zone (2600-4300 m) in southern Peru and northern Chile. We find that the geographical characteristics of the greening strip do not match climate zones previously established by Köppen and Geiger. Greening and browning trends in the coastal deserts and the high Andes lie within well defined climatic and life zones, producing variable but identifiable trends. However, the distinct Pacific slope greening presents an unexpected distribution with respect to the regional Köppen-Geiger climate and life zones. This work provides insights on understanding the effects of climate change on Peru’s diverse ecosystems in highly sensitive, biologically rich arid and semi-arid environments on the Pacific slope.

Little is known about how differences in water availability within the “super humid” tropics can influence the distribution of understory plant species and the composition of understory plant communities. We investigated variation in the physiological drought tolerances of understory plants and plant communities across a large elevation and precipitation gradient. We established 58 understory plots along a gradient of 400 – 3600 m asl elevation and 1000 – 6000 mm yr-1 rainfall in and around Manu National Park in southeastern Peru. Within the plots, we sampled all understory woody plants and measured three metrics of physiological leaf drought tolerance - turgor loss point (TLP), cuticular conductance (Gmin), and solute leakage (SL) - and assessed how the community-level means of these traits related to mean annual precipitation (MAP) and elevation (in the study gradient temperature decreases linearly and vapor pressure deficit increases monotonically with elevation). We did not find any correlations between the three metrics of leaf drought tolerance, suggesting that they represent independent strategies for coping with low water availability. Despite being widely used metrics of leaf drought tolerance, neither TLP nor Gmin showed any significant relationships with elevation or MAP. In contrast, SL, which has only recently been developed for use in ecological field studies, increased significantly at higher precipitations and at lower elevations (i.e., plants in colder and drier habitats have lower SL, indicating greater drought tolerances). Our results illustrate that differences in water availability may play a strong role in structuring plant communities even in in the wet tropics and highlight the potential for SL assays to be an efficient and effective tool for measuring drought tolerances in the field.

Background: Hantavirus cardiopulmonary syndrome (HCPS) has a high lethality. About two-thirds of the severe cases may be rescued by extracorporeal membrane oxygenation (ECMO). However, about half of the patients supported by ECMO suffer major complications. High volume hemofiltration (HVHF) is a depurative extracorporeal support that provides homeostatic balance allowing hemodynamic stabilization in some critically ill patients. Methods: We implemented HVHF prior to ECMO consideration in the last five severe HCPS patients requiring mechanical ventilation and vasoactive drugs admitted to our intensive care unit. Patients were considered HVHF-responders if ECMO was avoided and nonresponders if ECMO support was needed. Results: The first two patients required ECMO, while the last three did not. Patients had a maximum serum lactate of 8.4 [4.3-14] mMol/L and a lowest cardiac index of 1.76 [1.45-2.9] L/min/m2. Nonresponders were connected later to HVHF, displayed progressive tachycardia and decreasing stroke volume. The opposite was true for HVHF-responders who also received targeted-HVHF compounded by aggressive hyperoncotic albumin, sodium bicarbonate and calcium supplementation plus ultrafiltration to avoid fluid overload. All patients survived, but one of the ECMO patients suffered a vascular complication. Conclusion: HVHF may contribute to support severe HCPS patients avoiding the need for ECMO in some of them. Early connection and targeted-HVHF may increase the chance of success.

Snow-covered regions are the main source of reflection of incident shortwave radiation (ISR) on Earth’s surface. The deposition of light-absorbing particles (LAPs) on these regions increases the capacity of snow to absorb ISR and decreases surface snow albedo (SSA), which intensifies the radiative forcing leading to accelerated snowmelt and modifications of the hydrologic cycle. In this work we investigate changes in SSA and radiative forcing (RF) induced by LAPs in the Upper Aconcagua River Basin (Chilean central Andes) using remote sensing satellite data (MODIS), in-situ spectral SSA measurements, and the ISR (Chilean Solar Explorer platform) during the austral-winter months (May to August) for the 2004-2016 period. To estimate the changes in SSA and RF, we define two spectral ranges: i) an enclosed range (Ecr) between 841-876 nm, which isolates effects of Black-Carbon, an important LAP derived from anthropogenic activities, and ii) a broadband range (Bbr) between 300-2500 nm. Our results show that percent variations in SSA in the Ecr are higher than in the Bbr, regardless of the total amount of radiation received, which may be attributed to the presence of LAPs as these particles have a greater impact on SSA at wavelengths in the Ecr band than in the Bbr band.

The Environmental interactions contributed to the processes of settlement and development of the first settlers at southern Peru 15,000 BC. The determination of this process is based on paleoclimatic studies at southern Peru and ethnoarchaeological evidence. The determination of this process is based on paleoclimatic studies of southern Peru and ethnoarchaeological evidence; establishing as a result of this analysis the hypothesis of environmental interaction and territorial occupation of the first hunter-gatherer populations until their consolidation, dominating the geographical space from Tacna. The Disruptive disaster events and their effects on climate during the Peruvian Paleolithic resulted in the origin of local societies that shaped the Tiawanaku societies of the early horizon at Southern Peru and Northern Chile.