Periyar River Research Articles

Multi-metal resistance and antibiotic susceptibility of biofilm forming bacteria isolated from Kuzhikandam Creek in Kochi, southwest part of India

The purpose of this work was to characterize and identify the bacteria isolated from highly polluted locations that could potentially be able to withstand extremely toxic heavy metals. The study area selected for bacterial isolation from sediment samples was Kuzhikandam Creek, a tributary of the Periyar River and one of the world’s most hazardous hotspots, located in Kochi’s Eloor industrial region. Heavy metal analysis of chromium, copper, and lead in sediment samples was performed, and the results showed that the concentrations were greater than permissible limits. Several metal-resistant bacteria were isolated from sediments, which, upon further screening in solid media at different concentrations of chromium, copper, and lead, found three highly resistant species (S1B1, S2B2, and S3B3), one from each site. The phenotypic and biochemical characterization of these bacteria was examined using standard procedures. The ability of these species to generate biofilm was examined using methods like the crystal violet assay (qualitative assessment) and also using the scanning electron microscope. The antibiotic susceptibility of these species was tested with six different antibiotics, which are used in various disease treatments. These isolates, sequenced using the 16S rRNA Sanger dideoxy method, have been identified as Staphylococcus arlettae, Bacillus paramycoides, and Cellulosimicrobium funkei.

Plastic Debris in the Aquatic Environment: An Emerging Substratum for Antimicrobial Resistant (AMR) Biofilms.

Plastic pollution has quadrupled over the past years and has become a global concern due to its direct impact on life forms. The present study analysed whether the plastic debris in aquatic environments could act as the substratum for the antimicrobial-resistant (AMR) bacteria to form biofilm for survival. We have collected various plastic debris (n = 32) from six sites of the Periyar River, the drinking water source for the entire city and one of the most polluted rivers in Kerala (India). The chemical composition of plastics was screened via FTIR analysis and found that they comprised two types, viz., polyethylene and polypropylene. Bacteria isolated from the samples were screened for the AMR characteristics towards eight different classes of antibiotics. All isolates showed 100% resistance towards colistin and obtained the MAR index value of 0.1-0.4 range. Six representative bacterial isolates with high multiple antibiotic resistance (MAR) index were selected and identified by 16sRNA sequencing as Lysinibacillus mangiferihumi, Bacillus pumilus, Bacillus safensis, Bacillus cereus, Bacillus altitudins and Bacillus pumilus. In vitro biofilm formation was experimented on the purchased plastic samples in artificial media and river water using two selected strains, Bacillus pumilus and Bacillus cereus. Significant variations were observed in biofilm growth in different media (P < 0.05) regardless of plastic types (P > 0.05). The extracellular polymeric substances (EPS) and the characteristic holes on the surface morphology were visualized in SEM analysis, thus indicating the conditioning of the plastics by the isolates for biofilm formation.

Analysis of seasonal spatio-temporal variations in river water quality and its influencing factors in the Periyar River Basin, Southern Western Ghats, India

ABSTRACT In this study, an extensive and methodical investigation was carried out to comprehend the different geochemical processes, factors governing the hydrochemical composition and water suitability for drinking, irrigation and industrial usage in the Periyar River Basin (PRB). A total of 300 samples were collected from the mainstream, tributaries and dams of the river during PREM (Pre-Monsoon), POM (Post Monsoon), NEM (North-East Monsoon) and SWM (South-West Monsoon). The results suggested that the cationic composition is chiefly characterized by the predominant presence of Ca2+ and Mg2+ while Cl− dominates the anionic composition followed by HCO3-. The results identified transitional waters. Gibb's diagram revealed that the ionic composition dominance in the study area is influenced by the chemistry of the host rock rather than precipitation and evaporation. A comparatively greater pCO2 (&amp;gt;10−3.5 atm) shows an atmospheric disequilibrium in natural waterbodies due to both anthropogenic activities and input of baseflow to stream discharge. The Water Quality Index showed excellent (0–25) to unsuitable (&amp;gt;300) category during NEM, POM and PREM with significant spatial variation along the river. Integrated irrigational suitability indices illustrated the suitability of the samples for agricultural use, except for a few samples in the lowland region.

Seasonal variation, spatial distribution and risk assessment of microplastics in surface waters of Periyar River, Kerala, India.

Microplastics, an emerging contaminant, are widespread in oceans around the world, and rivers are the key conveyors of these pollutants into the oceans. There exists a dearth of available data pertaining to seasonal fluctuation, spatial distribution and risk assessment of microplastics in rivers extending from upper reaches to the lower reaches. The collection of such data is of utmost importance for the purpose of formulating beneficial management strategies for riverine microplastics. In order to bridge this research gap, an investigation was made in the Periyar River in Kerala, India, which is exposed to anthropogenic stress and is at risk of microplastic pollution. A total of eighteen sites (six sites each from downstream, midstream and upstream) along the 244km of the river were investigated across three seasons in a year. The study revealed a discernible pattern in the spatial distribution of microplastic concentrations, wherein there was a rise in abundance from the upstream to midstream and then a sudden increase of abundance along the downstream regions towards the lower reaches. The highest mean microplastic abundance of 124.95 items/L was obtained during the monsoon season followed by post-monsoon season i.e. 123.21 items/L and pre-monsoon i.e. 120.50 items/L. The predominant forms of microplastics were found to be fibres, fragments and filaments. Most prevalent polymer types acquired were polyethylene (PE) and polypropylene (PP). Pollution hazard index (PHI) and pollution load index (PLI) were also evaluated to assess the water quality of this river. The findings of this study conclude that the Periyar River is polluted with microplastics throughout its course and offer significant insights into the detection of microplastic origins in river systems and lend support to the implementation of potential measures aimed at mitigating their impact.

Ensemble empirical mode decomposition based deep learning models for forecasting river flow time series

River flow forecasting is important for flood prediction and effective utilization of water resources. This study proposed a comprehensive methodology that simultaneously enables the creation of multiple datasets and a comparison of multiple learning models for forecasting river flows. First, the data characteristics of the river flow time series were assessed based on its nature and pattern characteristics. Second, data decomposition was made for simplifying the complex data into decomposed modes. Ensemble Empirical Mode Decomposition (EEMD) was used for this purpose that provides intrinsic mode functions (IMFs). In addition, as benchmark, traditional time series decomposition was also applied over the complex data. Third, based on their data characteristics, the IMFs were combined into different components. These components along with the traditional time series decomposition create multiple datasets. Then, the components from the different datasets were forecasted using deep learning models, mainly BPNN (Back-Propagation Neural Network), CNN (Convoluted Neural Network) and LSTM (Long-Short Term Memory). Then, ensemble prediction was used to get the final output. For verification and benchmark purpose, we have also used statistical models like SARIMA over the datasets. A comprehensive evaluation and model comparisons were made using Diebold-Mariano (DM) test, k-fold cross validation and with the results of Prophet. In addition, the temporal convolution network (TCN) and the gated recurrent unit (GRU) were also modelled. Finally, all the DL modelling was performed for two data situations: with missing data deleted and missing data imputed. An empirical case study was done considering the average of daily time series data of Neeleswaram Hydrological Observation (HO) station over the Periyar river of South India for the period 2017–2021. The empirical assessment was made using several tests for all the different datasets and different learning models for further insights. Our results indicate that the deep learning-based models offer better predictions for complex time series in comparison to traditional statistical models. The DL models applied on the original time series data provided robust predictions with good performance such as low RMSE and high correlation values. However, the DL models’ performances are not enhanced through integration with time series decomposition and EEMD. Furthermore, the empirical results and the k-fold cross validation-based test indicate that all the DL models show equivalent performances. Interestingly, the DL models show superior performance over Prophet.

Trend Analysis of Rainfall and Temperature of Periyar River Basin

Trend Analysis of Rainfall and Temperature of Periyar River Basin

Tracing the Late Quaternary coastal evolution of Central Kerala, India, around the lost ancient port Muziris using multi-proxy study of the sedimentary archives

The Central Kerala coast in Southwest India serves as a valuable natural archive for studies of the Late Quaternary coastal evolution, palaeoclimate, and maritime trades. The coast is an archeologically and culturally significant region in South India, located in the mouth of the longest river in Kerala, the Periyar River. The riverbank of the Periyar at its mouth is believed to host the ancient port Muziris, whose remnants are found in the areas around where the Periyar River joins the Arabian Sea. Sea level oscillations and climate variabilities in the past have played a pivotal role in the destruction of the Muziris port. Recent excavations unearthed many artifacts from nearby areas of the river confluence; however, the exact location of the port remains unresolved. The present study is an attempt to trace out the coastal evolutionary processes and palaeoclimatic conditions that prevailed in the area during the Late Quaternary period using three drilled cores retrieved from this stretch of the coastal lands. A multi-proxy approach, combining geochemical, mineralogical, palynological, and geochronological tools was used in the study. The Holocene deposit in the study area is composed mainly of sand and clay-dominant sediments that fall within an age range of 1.1–8.1 cal kyr BP, whereas the underlying sedimentary sequence dates to a maximum of 31.5–37.9 cal kyr BP. The inorganic and organic elemental compositions, together with the textural and palynological attributes, indicate that Holocene sedimentation occurred here under fluctuating environmental conditions with significant changes in climate and sea level positions. The upper part of this section bears the signature of the humid depositional environment that prevailed during the Late Holocene when sand-dominated sediments were deposited and brought in under the influence of longshore drift. The sediments from the lower part of the section carry the signature of the Holocene transgression when deposition took place under submerged conditions with considerable marine influence but receiving significant terrestrial inputs. The study highlights the location of the historically significant lost ancient port of Muziris at Kodungallur near the mouth of the Periyar River. A three-fold evolutionary model proposed for the coastal segment revealed that the location of the Muziris port was part of the Periyar River near Kodungallur, as mentioned by the historians, and the settlement near Pattanam may be considered a satellite township of the ancient Muziris port.

Hydraulic modeling of the Periyar River using HEC-RAS: unraveling flow dynamics.

The Periyar River, a vital component of Kerala's ecosystem in India, serves as a lifeline supporting agriculture, hydropower generation, and ecological equilibrium. This study adopts a multifaceted approach to address critical challenges in the Periyar basin, with a primary focus on flood mitigation due to the region's susceptibility to devastating floods. Covering a length of 67.85 km, the study intricately segments the Periyar River into distinct reaches for a comprehensive steady flow analysis, considering factors such as seasonal monsoon fluctuations, diverse catchment topography, and human-induced alterations. Utilizing advanced modeling techniques, particularly HEC-RAS software, the study effectively predicts and simulates shifts in hydraulic behavior. The results, including velocity plots and cross-sectional maps, offer accurate insights into critical parameters, enabling the identification of areas with high velocity occurrence. This information proves instrumental in making informed decisions for the construction of river restoration structures, crucial for mitigating the impact of floods. The study's findings contribute valuable tools for future forecasting and sustainable management of the Periyar River, addressing the complex interplay of natural and anthropogenic factors.

Flood Susceptibility Map of Periyar River Basin Using Geo-spatial Technology and Machine Learning Approach

Flood Susceptibility Map of Periyar River Basin Using Geo-spatial Technology and Machine Learning Approach

Occurrence and distribution of steroid hormones (estrogen) and other contaminants of emerging concern in a south indian water body

Steroid hormones (SHs) are among the important classes of Contaminants of Emerging Concern (CECs) whose detection in aquatic environments is vital due to their potential adverse health impacts. Their detection is challenging because of their lower stability in natural conditions and low concentrations. This study reports the presence of steroid hormones in a major river system, the Periyar River, in Kerala (India). Water samples were collected from thirty different river locations in the case of SHs and five locations within these in the case of other CECs. These were subjected to LC-MS/MS and LC-Q-ToF/MS analyses. Five SHs, estriol, estrone, 17 β estradiol, progesterone, and hydroxy progesterone, were separated and targeted using MS techniques. The studies of the water samples confirmed the presence of the first three estrogens in different sampling sites, with estrone present in all the sampling sites. The concentration of estrone was detected in the range from 2 to 15 ng/L. Estriol and estradiol concentrations ranged from 1.0 to 5 ng/L and 1–6 ng/L, respectively. The hormones at some selected sites were continuously monitored for seven months. The chosen areas include the feed water sites for the drinking water treatment plants across the river. The monthly data revealed that estrone is the only SHs detected in all the samples in the selected months. The highest concentration of SH was found in August. Twelve CECs belonging to pharmaceuticals and personal care products were identified and quantified. In addition, 31 other CECs were also identified using non-target analysis. A detailed study of the hormone mapping reported here is the first from any South Indian River.

Assessment of Hydro-Geochemical Indices of Periyar River in Eloor Industrial Belt (Kerala), India to Identify Potential Environmental Impacts

The study investigated the role of hydrogeochemical parameters that act as indicators of environmental pollution in industrial areas of Periyar River, Kerala India. A total of 20 water/sediment samples collected along the industrial stretch of Eloor-Vypin area during the premonsoon season of the year 2020. Among the hydrochemical parameters, extent of pollution was imparted by the assessment of nutrients and heavy metals concentration. The micro nutrients such as silicate (640-3440μg/L), ammonia (4.42-894.2μg/L), phosphate (28.65-132.41μg/L), nitrite (3.12-30.14μg/L), and nitrate (50.13-851.97μg/L) were found to have higher enrichment at locations near the industrial areas of the study. The identified heavy metals, Zn, Mn, Pb, Cr, Cd, and Th having concentrations ranging from 1.0-152.4, 1.2-49.2, 1.2-31.7, 3.0-26.2, 1.1-13.3, 0.1-3.2μg/L, respectively. Various pollution indices suggest that the sediments having low to moderate level heavy metal contamination. The conditions may be worsen in the future if the industrial activities are continued in an unregulated manner. Keywords: Industrial Pollution; Heavy Metals; WQI; Hydrochemical Studies; Contamination Factor

Complete mitogenome of Lepidopygopsis typus, an evolutionarily-distinct, endangered cyprinid fish from the Western Ghats Biodiversity Hotspot: Phylogenetic relationships and implications for conservation

The mitogenome of Lepidopygopsis typus, an evolutionarily distinct, endangered, cyprinid fish from the Western Ghats Biodiversity Hotspot, was characterized. Total length of the mitogenome was 16,729 bp, and comprised of 13 protein coding, 22 tRNA and two rRNA genes. Thirteen protein coding genes contributed a total nucleotide length of 11,408 bp, which coded for a total of 3794 amino acids and accounting for 68.2 % of the mitogenome. A maximum likelihood phylogenetic tree based on mitogenomes of members of cyprinid subfamilies Torinae, Schizothoracinae and Schizopygopsinae, recovered L. typus in a well-resolved clade of Torinae with members of the Western Ghats endemic genus Hypselobarbus as sister taxa. Selection analysis suggested that the branch of L. typus and Hypselobarbus spp. was under intensified selection with reference to other members of Torinae. There were 19 codons under diversifying selection in L. typus, which could be the result of positive selection for adapting to high-altitude, upstream tributaries of Periyar River, where the species has a restricted distribution. With respect to Hypselobarbus spp., L. typus was under relaxed selection with about 68 % of codons experiencing neutral evolution. Restricted distribution, low population size and relaxation in selection can likely trigger extinction in L. typus, and therefore urgent conservation and monitoring plans are required to secure the future of this evolutionary distinct, and globally endangered species.

Urban Growth and Transformation of Port City – A Case of Kochi

In the year 1109 AD, the princely state of Cochin was established, marking the beginning of Kochi's historical journey. Over the centuries, Kochi has undergone significant metamorphosis and transformation, experiencing changes in its historical narrative, spatial layout, and environmental context. Particularly noteworthy is Fort Kochi, characterized by its charming ambience and colonial buildings that vividly narrate the tales of centuries-old cultural and commercial interactions with Western colonial powers. This area has left a lasting impression, contributing to Kochi's identity as the commercial capital of Kerala. Studying Kochi becomes a means to comprehend the city's growth patterns and its physical expansion over time. The evolution of Kochi reflects not only its historical roots but also the dynamic shifts in its spatial and environmental dynamics, providing insights into the multifaceted development of this significant urban centre. Fuelled by rapid urbanization and an influx of entrepreneurs, Kochi has emerged as the thriving commercial epicentre of Kerala. Key Words: Kochi, Periyar River, Urbanization, Cosmopolitan Industrial Parks, Economic Landscape

Screening of Pharmaceutical Pollutants Along with Emerging Contaminants in the Sediments of the Periyar River, Located in Kerala (India) by Using High-Resolution Mass Spectrometry (UPLC-Q-ToF-MS).

In this study, ultra-performance liquid chromatography coupled with a quadruple time-of-flight mass spectrometry (UPLC-Q-ToF-MS) was employed to screen and identify pharmaceutical pollutants and emerging contaminants (ECs) in the Periyar River near Aster Medicity hospital, the dumping yard of Amrutha hospital, and the Vaduthala bridge regions in Kerala, India. The analysis was conducted in both positive and negative ionization modes using electrospray ionization (ESI). The QuEChERS method was employed for initial sediment sample preparation. Among the twenty-five identified ECs, four compounds were identified as pharmaceutical pollutants. This study have great significance as it represents the first comprehensive investigation of pharmaceutical pollutants in these hospital regions, highlighting the urgent need for further analysis and understanding of the situation. The presence of ECs poses an urgent need for attention due to the irreversible harm caused to the riverine ecosystem by the degradation of water quality resulting from industrial and domestic discharge.

On the role of climate change in the 2018 flooding event in Kerala

The extreme precipitation during August 2018 in Kerala, India was catastrophic, triggering one of the worst floods in history. There is growing evidence of human-induced climate change in driving hydroclimatic extremes across the globe. However, whether and to what degree the 2018 flooding event in Kerala was influenced by climate change has yet to be fully understood. To this end, we present the first formal attribution analysis of the event, using the probabilistic event attribution (PEA) framework. Three methods using (i) Historical and HistoricalNat runs from CMIP6 (general circulation models-based method), (ii) observed records from 1901–2018 for two periods, split at 1950 (time-slice method) and (iii) observations that are scaled to 1901 and 2018 climates (scaling method), are considered for quantifying the risk ratio (RR) of the event. Using an objective approach, the 2018 precipitation event is defined by the return period of the 4 day cumulative precipitation over the Periyar River Basin (PRB), during 15–18 August, 2018. The subsequent flood event is characterized by the return period of the 1 day maximum streamflow at one of the outlets of the PRB, where maximum impact during the event was reported. The results from multiple methods are consistent, suggesting that the event is exceptionally less likely to have been caused by anthropogenic climate change, with RR for the precipitation and flood events ranging from 0.31 to 0.82 and 0.55 to 0.8, respectively. The role of wet antecedent soil moisture conditions, which is found to be the primary driving factor of floods in the PRB, is also found to be unchanged between simulations with and without climate change. Our results highlight the challenges in unequivocal discerning of the climate change signal on regional hydrological events and emphasize the importance of better consideration of local confounding interventions in PEA studies.

Assessing the Vulnerability of Water Balance to Climate Change at River Basin Scale in Humid Tropics: Implications for a Sustainable Water Future

Sustainability in hydrology aims at maintaining a high likelihood of meeting future water demands without compromising hydrologic, environmental, or physical integrity. Therefore, understanding the local-scale impact of global climate change on hydrology and water balance is crucial. This study focuses on assessing the impact of climate change on water balance components (precipitation, surface runoff, groundwater flow, percolation, etc.) at the river basin scale in a humid tropical region. The Periyar river basin (PRB) in Kerala in India is considered as a case study and the SWAT hydrological model is adopted to obtain the water balance components. Three general circulation models are considered under two shared socioeconomic pathways (SSP 245 and SSP 585) emission scenarios assess the impact of climate change until 2100. For the PRB, the results demonstrate a significant increase in streamflow (&gt;65%) and runoff (&gt;40%) in the mid (2041–2070) and far (2071–2100) future under both the SSP scenarios, indicating a potential vulnerability to future floods. Conversely, in the near future under SSP 585, a decrease in runoff (−15%) and nominal changes in streamflow (−5%) are observed. Spatially, the eastern sub-basins and the west coast of the Periyar river basin are projected to experience higher precipitation events, while the central region faces reduced precipitation and low flow rates. The findings emphasize the need for proactive and sustainable management of water resources, considering irrigation requirements, groundwater discharge, and flood control measures, to mitigate the negative effects of climate change and prevent water stress/surplus situations in specific sub-basins. This study enhances our understanding of climate change impacts on water balance and emphasizes the significance of sustainable water resource management for an effective response. By integrating scientific knowledge into policy and management decisions, we can strive towards a resilient water future within a changing climate.

Influence of COVID-19 lockdown on river water quality and assessment of environmental health in an industrialized belt of southern Western Ghats, India.

The COVID-19 pandemic and sudden lockdown have severely hampered the country's economic growth and socio-cultural activities while imparting a positive effect on the overall fitness of the environment especially air and water resources. Increased urbanization and rapid industrialization have led to rising pollution and deterioration of rivers and associated sectors such as agriculture, domestic and commercial needs. However, various available studies in different parts of the country indicate that the COVID-19 pandemic has changed the entire ecosystem. But it is noted that studies are lacking in the southern Western Ghats region of India. Therefore, the present study attempts to investigate how the continuous lockdowns affect the River Water Quality (RWQ) during lockdown (October 2020) and post-lockdown (January 2021) periods in the lower catchments (Eloor-Edayar industrialized belt) of Periyar river, Kerala state, South India. A total of thirty samples (15 samples each) were analyzed based on drinking water quality, irrigational suitability, and multivariate statistical methods to evaluate the physical and chemical status of RWQ. The results of theWater Quality Index (WQI) for assessing the drinking water suitability showed a total of 93% of samples in the excellent and good category during the lockdown, while only 47% of samples were found fit for drinking during the post-lockdown period. Irrigational suitability indices like Mg hazard, KR, PI, SAR, and Wilcox diagram revealed lockdown period samples as more suitable for irrigational activities compared to post-lockdown samples with site-specific changes. Spearman rank correlation analysis indicated EC and TDS with a strong positive correlation to Ca2+, Mg2+, Na+, K+, TH, SO42-, and Cl- during both periods as well as strong positive correlations within the alkaline earth elements (Ca2+ and Mg 2+) and alkalis (Na+ and K+). Three significant components were extracted from principal component analysis (PCA), explaining 88.89% and 96.03% of the total variance for lockdown and post-lockdown periods, respectively. Variables like DO, BOD, Ca2+, NO3-, and Cl- remained in the same component loading during both periods elucidating their natural origin in the basin. The results of health risk assessment based on US EPA represented hazard quotient and hazard index values below the acceptable limit signifying no potential noncarcinogenic risk via oral exposure except As, suggesting children as more vulnerable to the negative effects than adults. Furthermore, this study also shows rejuvenation of river health during lockdown offers ample scope to policymakers, administrators and environmentalists for deriving appropriate plans for the restoration of river health from anthropogenic stress.

A Framework for Assessment of Flood Conditions Using Hydrological and Hydrodynamic Modeling Approach

River flooding has been triggering significant damage to lives and infrastructure and is a major worry all around the globe. To lessen these losses, proper planning and management methods need to be deployed. The purpose of this research is to fill a knowledge gap on the effects of reservoirs operation of the Idukki and Idamalyar to Periyar River Basin massive flooding. The proposed methodology is implemented on the Periyar River Basin located in Kerala, India, where severe flooding occurred during monsoon season in the year 2018. In this study, modelling technique has been used in two-step: (1) development of 1D physically based, distributed-parameter model (Soil and Water Assessment Tool, SWAT) to compute the stream flow and estimate the stream discharge at different outlet points; and (2) hybrid model is developed by linking SWAT with a well-known 2D hydrodynamic model (International River Interface Cooperative, iRIC) to display flood scenarios and to identify the flood-prone areas. The ArcSWAT user interface employed in the ArcGIS software was utilized to delineate the river basin. The SWAT model was calibrated and validated on daily and monthly basis at two gauge discharge stations, i.e., Neeleeswaram and Kalady. The statistical coefficients result obtained from SWAT model was in good agreement with the measured values for calibration and validation. The hybrid model simulation results compared with observed flood depth and remote sensing data demonstrated good capability of the model. Agreeable performances of computed results were observed in both flow fields and flood propagations. The result was compared with 2018 flood to check model accuracy and found to be satisfactory. The proposed framework can be utilized as an effective tool for efficient planning and management of natural disasters, such as flash floods.

Macrosporophycos sahyadricus (Batrachospermales, Rhodophyta), a new genus and species of freshwater red algae from the Western Ghats of India

ABSTRACT A new genus of freshwater red algae, Macrosporophycos, and a new species, M. sahyadricus, are described from the Periyar River in the southern part of the Western Ghats, Kerala, India. Macrosporophycos shares distinctive characteristics with Montagnia, such as straight carpogonial branches having involucral filaments forming a rosette around the carpogonia, and pedunculate carposporophytes. However, the two genera have a raw genetic distance of 16.4%–17.0% for rbcL, and 24%–26.7% for COI-5P genes. The new species, Macrosporophycos sahyadricus, also possesses large, elongated, pear-shaped carposporangia. Phylogenetic analyses based on the concatenated rbcL and COI-5P recovered M. sahyadricus as a distinct lineage, sister to Acarposporophycos from South America. However, these genera are distinct from each other in their morphology. The morphological similarity, coupled with the high levels of genetic difference between Macrosporophycos and Montagnia, suggest convergent evolution in morphology. The recent records of new red algal taxa, including the discovery of this new genus, suggest that the Indian subcontinent continues to be under-explored and is in need of integrative taxonomic research supported by large-scale sampling.

Establishment of Baseline Reference Geochemical Values in Tropical Soils of Western Ghats: Assessment of Periyar Basin with Special Reference to Contaminant Geochemistry

AbstractBased on the detailed geochemical studies of 184 soil samples from Periyar River Basin (PRB), a tropical monsoon dominated river basin (5398 km2) in the southern western Ghats (WGs) of India, a baseline reference data is established. The soils are mildly acidic with sandy loam and silt loam facies in non‐monsoon to sandy loam and sandy clay loam in monsoon. The mean metal concentrations follow the upper continental crust and world shale values. The Geoaccumulation index (Igeo) shows unpolluted to moderately polluted category, except for Cu, Zn, and Ba, while Enrichment Factor (EF) indicates no to minor enrichment for all elements. Contamination factor (Cf) indicates low to considerable contamination for V, Rb, Sr, Ni, and low to very high contamination for Cu, Zn, and Ba. Three significant components are extracted by Principal Component Analysis (PCA), explaining 78.09% and 74.10% of the total variance for monsoon and non‐monsoon seasons. Ti, Al, Fe, Ca, Na, K, V, Cr, Ni, Sr, and Ba exhibited common source of origin while anthropogenic origin is identified for Zn and Cu. The study will provide valuable information into the pedological characteristics of WGs river basins.