Search Results (37)

Phytoplankton are key indicators of water quality and low-cost tools for freshwater monitoring, yet their diversity and ecological drivers remain poorly documented in the Tropical Andes. This study provides the first national-scale, multi-ecosystem assessment of net phytoplanktonic communities (including microalgae and cyanobacteria), across Ecuador, integrating physicochemical, multivariate, and geospatial analyses. Eighteen lakes and rivers from three biogeographic regions and a wide altitudinal gradient were surveyed, yielding 129 taxa, 77 identified at species level, the most comprehensive checklist reported to date for Ecuador. Community structure showed a clear lentic–lotic differentiation driven by hydrodynamic contrasts, while the absence of distance–decay patterns indicated high dispersal and environmental filtering pattern rather than spatial structuring. Anthropogenic pressure acted as a secondary gradient: pristine high-Andean lakes were dominated by desmids and diatoms, whereas agricultural and urban basins showed chlorophyte and potentially toxic cyanobacterial assemblages. Palmer’s Index detected organic pollution but underestimated eutrophication in endorheic, geochemically enriched lakes. Land-use effects presented strong basin-scale signals in lakes but weak correlations in rivers due to overriding hydromorphological constraints. These findings establish a robust spatial baseline for freshwater bioassessment in the Andes, demonstrating the value of phytoplankton as effective, low-cost indicators readily applicable to national water-quality assessment programs. Full article

This study evaluated the influence of soil health in riparian and ecotone zones on water quality in four high-Andean rivers (Atillo, Ozogoche, Yasepan, and Cebadas) within the Cebadas River sub-basin, Ecuador. Soil and water samples were collected from 20 sites during three field campaigns (2022–2024). Soil properties included organic carbon concentration, soil organic carbon stock (SOC), bulk density, moisture, and potential microbial activity estimated through laboratory CO₂–C efflux. Water quality parameters were integrated into the National Sanitation Foundation Water Quality Index (NSF-WQI), and riparian condition was assessed using the QBR-And index. Multivariate statistical approaches, including Random Forest and Classification and Regression Trees (CART), were used to identify the most influential predictors of ecosystem quality. Results revealed marked spatial contrasts. Riparian SOC stocks ranged from 22.8 to 32.8 Mg C/ha in the more disturbed Cebadas and Yasepan rivers to 91.4–133.6 Mg C/ha in the better-conserved Atillo and Ozogoche systems. Sites with higher SOC and lower bulk density consistently exhibited better water quality, with NSF-WQI values classified as “good”, whereas more degraded sites showed lower riparian quality and “fair” water quality. Riparian forest quality was strongly correlated with water quality (r = 0.81). Random Forest models identified ammoniacal nitrogen, fecal coliforms, and altitude as the most influential predictors of riparian ecosystem condition. These findings demonstrate that soil health and riparian integrity are tightly linked to water quality patterns in high-Andean fluvial systems and support their integration into ecosystem-based watershed management. Full article

This study evaluated the water supply and regulation of the San Pedro River basin, located in the municipality of Puerto Libertador (Córdoba, Colombia), under climate change scenarios, using the SWAT (Soil and Water Assessment Tool) hydrological model. The model was calibrated and validated in SWAT-CUP using the SUFI-2 algorithm, based on observed streamflow series and sensitive hydrological parameters. Observed and satellite climate data, CHIRPS for precipitation and ERA5-Land for temperature, radiation, humidity, and wind, were employed. Climatic data were integrated along with spatial information on soils, land use, and topography, allowing for an adequate representation of the basin’s heterogeneity. The model showed acceptable performance (NSE > 0.6; PBIAS < ±15%), reproducing the seasonal variability and the average flow behavior. Climate projections under RCP 4.5 and RCP 8.5 scenarios, derived from the MIROC5 model (CMIP5), indicated a slight decrease in mean streamflow and an increase in interannual variability for the period 2040–2070, suggesting a potential reduction in surface water availability and natural hydrological regulation by mid-century. The Water Regulation Index (WRI) exhibited a downward trend in most sub-basins, particularly in areas affected by forest loss and agricultural expansion. The WRI showed a downward trend in most sub-basins, especially those with loss of forest cover and a predominance of agricultural uses. These findings provide basin-specific evidence on how climate change and land-use pressures may jointly affect hydrological regulation in tropical Andean–Caribbean basins. These results highlight the usefulness of the SWAT model as a decision-support tool for integrated water resources management in the San Pedro River basin and similar tropical Andean–Caribbean catchments, supporting basin-scale climate adaptation planning. They also emphasize the importance of conserving headwater ecosystems and forest cover to sustain hydrological regulation, reduce vulnerability to flow extremes, and enhance long-term regional water security. Full article

This study evaluated the Snowmelt-Runoff Model (SRM) and the Génie Rural à X Paramètres Journalier (GRxJ) model family, analyzing the latter both independently and in combination with the CemaNeige snow module. SRM and GRxJ represent snowmelt-runoff and rainfall-runoff hydrological models, respectively. Accurate streamflow estimation in snow- and rain-dominated basins is crucial for water resource management, especially in the Andes where climate variability and glacier retreat threaten long-term water availability. The analysis was conducted in two Chilean watershed basins with contrasting regimes: the snow-dominated Aconcagua and the mixed rain–snow Duqueco basins. Daily data (2012–2020) of precipitation, temperature, evapotranspiration, snow cover (MODIS), and streamflow were used. Models were calibrated and validated with optimization algorithms and evaluated using $NSE$, $RMSE$, $R^2$, $PBIAS$, $KGE$, $MAE$, $logNSE$ and $APFB$. The results show that SRM effectively reproduces variability and, in the case of the rain–snow regime basin, extreme events, with $NSE$ ranging from $0.70$ to $0.78$ (Aconcagua) and $0.93$ to $0.94$ (Duqueco). Model selection should take into account the dominant hydrological processes. In this study, SRM showed the best performance in both analyzed catchments, although with limitations in reproducing extreme streamflow events. In contrast, the GRxJ models did not adequately capture the hydrological dynamics of the snow-dominated Aconcagua catchment. However, their performance improved considerably when applied to the mixed regime of the Duqueco River. These findings highlight the importance of adapting modeling strategies to local hydrological conditions and limited data availability, offering practical guidance for water management and climate change adaptation in Andean catchments. Full article

This study investigates the relationship between land use and soil organic carbon (SOC) storage in tropical Andean ecosystems, introducing a socio-ecological perspective to assess how community conservation perceptions influence SOC storage and contribute to climate change mitigation strategies. Background and Objectives: Land-use change reduces carbon stocks in tropical ecosystems. Focusing on the Las Piedras River basin (Popayan, Colombia), we evaluated SOC storage under four plant cover types—riparian forests (RFs), ecological restoration (ER), natural regeneration (NR), and livestock pastures (LSs)—and examined its association with local conservation perceptions. Materials and Methods: SOC storage at 30 cm depth, carbon inputs and outputs, and soil physicochemical properties were measured across land-use types. Conservation perceptions were assessed through 65 community surveys. Data analyses included ANOVA, principal component analysis, and multinomial logistic regression. Results: SOC storage was highest in RFs (148.68 Mg ha⁻¹), followed by ER and LSs, and lowest in NR (97.30 Mg ha⁻¹). A positive relationship was observed between high conservation perception and greater SOC content. Conclusions: SOC storage is strongly influenced by land use and community conservation values. Active restoration efforts, coupled with environmental education, are essential for enhancing the socio-ecological resilience of these ecosystems. Full article

Accurate precipitation data are essential for hydrological planning in mountainous regions with sparse opportunities for observation, such as the Ambato River basin in Ecuador. In this study, CHIRPS and IMERG satellite precipitation products were compared against six automatic rain gauges from 2014 to 2023, using both categorical metrics (to assess daily rainfall detection skill) and continuous validation (to evaluate rainfall amount), complemented by bias decomposition and spatiotemporal analysis. Our results show that IMERG demonstrated higher skill in detecting daily rainfall, while CHIRPS delivered a more stable performance during dry conditions, with fewer false alarms. Both products capture the main seasonal precipitation patterns but differ in bias behavior: CHIRPS tends to under-estimate daily rainfall less, whereas IMERG provides more reliable volumetric estimates overall. These findings suggest that IMERG may be best suited for flood risk and hydrological modelling, while CHIRPS could be preferred for drought monitoring and climatological studies in Andean catchments. Full article

Understanding the structural concordance between taxonomic and functional diversity (FD) metrics is essential for improving the ecological interpretation of community patterns in biomonitoring programs. This study evaluated the concordance between taxonomic and FD metrics of benthic macroinvertebrates along a fluvial habitat quality gradient in the Paute River Basin, Ecuador. Macroinvertebrate communities were sampled over six years at twelve sampling points and assessed using four taxonomic metrics: Shannon diversity (H), the Margalef index (D_Mg), family richness (N), and the Andean Biotic Index (ABI). Functional diversity was evaluated using four metrics: weighted functional dendrogram-based diversity (wFDc), Rao’s quadratic entropy (Rao), functional dispersion (FDis), and functional richness (FRic). The fluvial habitat index (FHI) was used as an environmental reference to evaluate diversity metric responses. K-means clustering was independently applied to each metric, and pairwise concordance was quantified using the Measure of Concordance (MoC) and overlap in sampling points groupings across replicates. Most metrics (except FRic and N) showed clear responsiveness to the FHI gradient, confirming their ecological relevance. Strong structural concordance was observed between H and D_Mg and the FD metrics Rao, FDis, and wFDc, showing that these metrics captured similar yet complementary aspects of community organization. In contrast, ABI showed marked sensitivity to the FHI gradient but low concordance with functional metrics, suggesting distinct dimensions of biological integrity not encompassed by trait-based metrics. These findings highlight the value of combining taxonomic and functional metrics to detect both broad and subtle ecological changes. Integrating metrics with differing structural properties and environmental sensitivities can enhance the robustness of freshwater biomonitoring frameworks, especially in systems undergoing ecological transition or habitat degradation. Full article

The Andean river basins of central–southern Chile face multiple anthropogenic disturbances, including water extraction, hydropower, mining, and industrial discharges, which affect their ability to adapt to new disturbances. Disturbance intensity forms a gradient from high (Maipo, Rapel, Biobío, Maule) through medium (Mataquito, Itata) to low (Imperial, Toltén). This study evaluated resilience in these eight river basins based on fish assemblages, using taxonomic and functional trait indices within the framework of the three Rs of resilience: resources, recruitment, and refugia. Taxonomic indices captured changes in species richness, abundance, diversity, evenness, and beta diversity, while functional traits reflected the fish species characteristics promoting resilience. Statistical tests revealed significant differences in resilience indices among basins. Recruitment was the most impacted resilience mechanism, with beta diversity revealing effects from river fragmentation in the Maipo, Rapel, and Biobío basins. The resources mechanism was also affected, primarily by land-use changes and water pollution, leading to low species richness in the Maipo, Rapel, Mataquito, and Maule river basins. Interestingly, basins with medium disturbance levels showed high resilience, indicating adaptive responses to moderate impacts. This study emphasizes the importance of multiple indicators to assess ecosystem resilience and calls for integrated strategies to address the complex challenges impacting freshwater biodiversity. Full article

Understanding how land use and climate change jointly affect water availability is essential for sustainable planning in tropical Andean–Amazonian basins. This study focuses on the Utcubamba River Basin in northeastern Peru, a data-scarce and socioecologically strategic watershed where land transformation and climate variability converge. A multi-temporal land use/land cover (LULC) analysis (1990–2024) was conducted, coupled with hydrological modeling using the SWAT model under historical and future climate scenarios (SSP2–4.5 and SSP5–8.5), including the spatial overlay of the LULC change concentration with key hydrological indicators. LULC classifications revealed forest loss and the expansion of pasture, agriculture, and shrubland areas, particularly in the upper basin. Hydrological projections showed significant changes in water flow, including reductions in minimum monthly flows by up to 73.9% and increases in peak flows by 14.8% under the SSP5–8.5 scenario. The water balance is expected to shift, with increased percolation and reduced lateral flow, suggesting decreased storage capacity. By identifying critical sub-basins where land degradation and water insecurity converge, the study supports adaptive strategies for land restoration, aquifer recharge planning, and ecosystem conservation. Despite limited hydrological infrastructure, the SWAT model effectively simulated water dynamics, aiding climate resilience and water security efforts in the Amazonian Andes. Full article

The High Andean region of Peru, characterized by a complex orography, has unique and highly biodiverse ecosystems. This region has several headwater basins that play a critical role in the hydrological cycle, providing diverse ecosystem services essential to sustain biodiversity and supply water to human communities. Despite the importance of this region, it faces significant human intervention, particularly mining activities, which affect basin headwaters and jeopardize water security. This study aimed to calibrate the Biological Monitoring Working Party (BMWP) index to evaluate water quality in High Andean rivers in Peru affected by mining activities, using aquatic macroinvertebrates as bioindicators. We used a 15-year dataset (2008 to 2023) from three headwater basins in the High Andean region; this dataset included physicochemical water quality parameters, trace metals, and aquatic macroinvertebrates. The BMWP was calibrated for the High Andean region of Peru with this dataset (BMWP/PeIAZIM); afterward, it was validated to assess water quality in an area influenced by mining activities in this region. The results allowed us to differentiate between aquatic macroinvertebrate families tolerant to mining pollution and highly sensitive families. The sites heavily affected by mining activity returned very low BMWP/PeIAZIM scores; sites with no mining impact had the highest scores. These findings indicate that the calibrated index can be used for water resource management in the High Andean region, contributing to the conservation of its ecosystems. Full article

Glaciers worldwide are in retreat, and their meltwater can modulate mountain aquifers. We examined whether mass loss of the Juncal Norte Glacier (central Chile) has affected groundwater storage in the Juncal River basin between 1990 and 2022. Recession-curve modeling of daily streamflow shows no statistically significant trend in basin-scale groundwater reserves (τ = 0.06, p > 0.05). In contrast, glacier volume declined significantly (−3.8 hm³/yr, p < 0.05), and precipitation at the nearby Riecillos station fell sharply during the 2008–2017 megadrought (p < 0.05) but exhibited no significant change beforehand. Given the simultaneous decreases in meteoric inputs (rain + snow) and glacier mass, one would expect groundwater storage to decline; its observed stability therefore suggests that enhanced glacier-melt recharge may be temporarily offsetting drier conditions. Isotopic evidence from comparable Andean catchments supports such glacio-groundwater coupling, although time lags of months to years complicate detection with recession models alone. Hence, while our results do not yet demonstrate a direct glacier–groundwater link, they are consistent with the hypothesis that ongoing ice loss is buffering aquifer storage. Longer records and tracer studies are required to verify this mechanism and to inform sustainable water resources planning. Full article

Climate change has a significant impact on river flows, leading to overflows and floods that affect populations, especially in Andean regions. This study examines flood scenarios in the Cunas River Basin (Junín, Peru) through hydrological and hydraulic simulations under various climate projections. A Reliability Ensemble Averaging (REA) approach was employed using CMIP6 climate models. In this analysis, precipitation data were processed, basin parameters were calculated, and peak flows and the extent of flood-prone areas were estimated. HEC-HMS software was used to simulate peak flows corresponding to return periods of 25, 50, 100, 139, and 200 years, while HEC-RAS was employed to determine flood zones. Model calibration and validation relied on historical precipitation data from nearby stations. The results indicate a considerable increase in peak flows and flood-prone areas due to climate change. A 3.32% increase in peak flow, a 55.35% expansion in flood-prone areas, and a 34.12% rise in flood depth are observed. These findings highlight the importance of implementing riverine protection structures. This study provides key information for flood risk management in the Peruvian highlands, using widely accepted tools to understand the hydrological response to climate change. Full article

The state of Acre, located in the Western Amazon, has been more intensely affected in recent years by extreme weather events, especially those of a hydrological nature. These are rainy seasons with major floods and record water levels and, later in the same year, severe droughts that last for more months than is normal for the dry season. In this sense, remote sensing acts as an important tool for monitoring the meteorological variables involved in this dynamic, and for predicting future climate trends. Different temporal lengths reflect the availability of reliable data for each variable, and statistical methods were applied separately to ensure robust analyses despite these differences. Our research used data on rainfall (1982–2023), air temperature (2001–2020), fire foci, vegetation, and snow cover (2001–2023) for these purposes. Snow cover data were obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) product MOD10CM (MODIS/Terra Snow Cover Monthly L3 Global Climate Modeling Grid). The MOD10CM product was used to quantify snow cover in an area close to the state, connected to one of the main river basins in Acre. The results showed an increase in the amount of rainfall for the month of February and a reduction in the amount for months of the dry season, as well as an extension of the same. A reduction in the percentage of snow cover was also observed in the region, which may have a direct impact on water availability for several populations, including the city of Rio Branco. The Mann–Kendall test reinforced this reduction, with a Z index of −1.98 for the month of June. Principal Component Analysis (PCA) highlighted key relationships among variables. For the first principal component (PC1), rainfall, snow cover, maximum temperature, and minimum temperature had the strongest contributions, capturing over 56% of the total variance across all datasets. A negative relationship was observed between rainfall and minimum temperature, indicating that higher minimum temperatures are associated with reduced rainfall in the region. Conversely, the second principal component (PC2), which explained approximately 29% of the variance, revealed a strong positive relationship between fire foci and maximum temperature, suggesting that higher maximum temperatures significantly increase the number of fire foci. These results reinforce the role of climatic extremes in shaping environmental dynamics in Acre. The level of statistical significance (p-value) adopted for the data was up to 0.10. Full article

The Amuyo Ponds (APs) are a group of three brackish hydrothermal lagoons located at 3700 m above sea level in a pre-Andean setting in the Atacama Desert. Each pond shows a conspicuous green (GP), red (RP), or yellow (YP) coloration, and discharges water rich in arsenic and boron into the Caritaya River (Camarones Basin, northern Chile). Microorganisms are subjected to harsh environmental conditions in these ponds, and the microbial composition and diversity in the Amuyo Ponds’ sediments are unknown. The microbial life colonizing AP sediments was explored by metagenomics analyses, showing a diverse microbial life dominated by members of the bacterial domain, with nearly 800 bacterial genome sequences, and sequences associated with Archaea, Eukarya, and viruses. The genus Pseudomonas was more abundant in GP and YP sediments, while the genera Pseudomonas, Aeromonas, and Shewanella were enriched in RP sediments. Archaeal composition was similar in all sediments, and enriched with methanogens sequences from the Archaeoglobi and Halobacteria classes. Abundant fungi sequences were detected in all sediments from the phyla Blastocladiomycota and Ascomycota. We also report putative functional capabilities related to virulence and defense genes, the biosynthesis of secondary metabolites, and tolerance to arsenic. Thirteen bacterial and fourteen viral metagenome-assembled genomes were reconstructed and informed here. This work expands our knowledge on the richness of the microorganisms in the APs and open further studies on the ecology and genomics of this striking Andean geosite. Full article

Extreme rainfall events in Andean basins frequently trigger landslides, obstructing river channels and causing flash flows, loss of lives, and economic damage. This study focused on improving the modeling of these events to enhance risk management, specifically in the La Liboriana basin in Salgar (Colombia). A cascading modeling methodology was developed, integrating the spatially distributed rainfall intensities, hazard zoning with the SLIDE model, propagation modeling with RAMMS using calibrated soil rheological parameters, the distributed hydrological model TETIS, and flood mapping with IBER. Return periods of 2.33, 5, 10, 25, 50, and 100 years were defined and applied throughout the methodology. A specific extreme event (18 May 2015) was modeled for calibration and comparison. The spatial rainfall intensities indicated maximum concentrations in the northwestern upper basin and southeastern lower basin. Six landslide hazard maps were generated, predicting landslide-prone areas with a slightly above random prediction rate for the 2015 event. The RAMMS debris flow modeling involved 30 simulations, indicating significant deposition within the river channel and modifying the terrain. Hydraulic modeling with the IBER model revealed water heights ranging from 0.23 to 7 m and velocities from 0.34 m/s to 6.98 m/s, with urban areas showing higher values, indicating increased erosion and infrastructure damage potential. Full article