The Longleaf Tree-Ring Network: Reviewing and expanding the utility of Pinus palustris Mill. Dendrochronological data

The longleaf pine (Pinus palustris Mill.) and related ecosystem is an icon of the southeastern United States (US). Once covering an estimated 37 million ha from Texas to Florida to Virginia, the near-extirpation of, and subsequent restoration efforts for, the species has been well-documented over the past ca. 100 years. Although longleaf pine is one of the longest-lived tree species in the southeastern US—with documented ages of over 400 years—its use has not been reviewed in the field of dendrochronology. In this paper, we review the utility of longleaf pine tree-ring data within the applications of four primary, topical research areas: climatology and paleoclimate reconstruction, fire history, ecology, and archeology/cultural studies. Further, we highlight knowledge gaps in these topical areas, for which we introduce the Longleaf Tree-Ring Network (LTRN). The overarching purpose of the LTRN is to coalesce partners and data to expand the scientific use of longleaf pine tree-ring data across the southeastern US. As a first example of LTRN analytics, we show that the development of seasonwood chronologies (earlywood width, latewood width, and total width) enhances the utility of longleaf pine tree-ring data, indicating the value of these seasonwood metrics for future studies. We find that at 21 sites distributed across the species’ range, latewood width chronologies outperform both their earlywood and total width counterparts in mean correlation coefficient (RBAR = 0.55, 0.46, 0.52, respectively). Strategic plans for increasing the utility of longleaf pine dendrochronology in the southeastern US include [1] saving remnant material (e.g., stumps, logs, and building construction timbers) from decay, extraction, and fire consumption to help extend tree-ring records, and [2] developing new chronologies in LTRN spatial gaps to facilitate broad-scale analyses of longleaf pine ecosystems within the context of the topical groups presented

Heavy metal pollution in groundwater of urban Delhi environs: Pollution indices and health risk assessment

The excess presence of heavy metals in water resources deteriorates the quality and has a high potential for bioaccumulation and environmental contamination. The study of heavy metals in water is essential because of their integration in the food chain and the potential for sublethal effects on aquatic and human life. To understand the extent of heavy metal pollution, a total of 64 groundwater samples (32 in each pre-and post-monsoon season) were collected around the Yamuna River's flood plains in the Delhi region. In this study, pollution indices and health risk assessment methodologies were used to estimate the significant threat to humans. In examined seasons, the sequence of heavy metal content in groundwater is Fe > Mn > Zn > B > As>Ni > Pb. The heavy metal pollution index (HPI) revealed that in the pre-and post-monsoon seasons, 53% and 44% (HPI >100), of groundwater samples are at high-risk zone respectively. 53% of pre-monsoon and 56% of post-monsoon samples were found highly polluted, according to the degree of contamination (Cd). Moreover, health risk assessment shows that hazard index (HI) values for heavy metals were found significantly high (HI >1) in groundwater samples inferring increased non-cancerous risk to the local community. The results imply that continuous exposure can lead to chronic diseases in the population residing in the study region. In both carcinogenic and non-carcinogenic assessments, children's hazard index and carcinogenic risk assessment (CR) scores were found higher. As a result, compared to adults in the study region, children are more vulnerable to potential health threats. The principal component analysis (PCA) method was used to figure out the origin of heavy metals, and it was found that As, Fe, Mn, and Zn come from non-anthropogenic sources, whereas mixed sources (natural and anthropogenic) may be responsible for B, Ni, and Pb presence. The results of the study will help to develop an effective strategy for environmental assessment and monitoring to control groundwater pollution of the Delhi urban environs

Study of Micro-structures and their Relation with Occurrence of Mineral Matter in Ramagundam Coals, Godavari Basin, India: Implications on Coal and Hydrocarbon Industries

This paper is an attempt to study the relationship between coal microstructures and mineral matter in Ramagundam Gondwana coal of Godavari basin. For this purpose, the occurrence and distribution of mineral matter in different lithotypes and microlithotypes have been investigated and their association with organic matter has been studied. The work has been accomplished through detailed petrography, SEM-EDS and XRD studies. Presence of clay minerals and pyrite, along with trace amounts of apatite, ankerite, hematite, calcite, dolomite and quartz has been revealed from the study. The lithotypes and bands have variable concentrations of mineral matter which occurs associated with different microstructures in coal. Optical microscopy reveals that mineral matter occurs maximum in dull-coal but it is almost equally distributed in dull-banded coal and banded-bright coal. The study also incorporates the nature of fracture and phyteral pores and their association with mineral matter. Vitrain is characterized by cleats, micropores and microfractures which are often filled up partially or completely with mineral matter; fusain has well preserved tracheids with open pits and partially homogenized cell structure filled with mineral matter. In durain and clarain lithotypes, the minerals are intimately intergrown with the organic constituents

Morphometric Analysis of Baner, Neogal and Awa River Basins, Himachal Pradesh, India

The present study aims at evaluating the morphometric parameters of Baner, Neogal and Awa river basins in Himachal Pradesh, India for making important assessments about the morphometric characteristics and geo-hydrological conditions of these watersheds. Georeferenced Survey of India toposheets, Cartosat-DEM are the datasets used in ArcGIS software for the delineation of watersheds and calculating important morphometric parameters along with the preparation of relief, slope, aspect and drainage basin asymmetry maps. The results show that the Neogal and Awa rivers are of 6th order whereas Baner river is of 7th order. The basins are of elongated shape and the drainage is mainly of sub-dendritic to dendritic type. In the northern regions of these river basins, the slopes are very steep and the relief is very high that results in rapid runoff and increases the intensity of erosion. High drainage density (>2.8) and fine drainage texture (>9) indicate moderately permeable subsurface material that causes groundwater deficit. These watersheds have developed asymmetrical drainage and their high ruggedness values (>12) refers to the rejuvenated stage of their geomorphic development. The study concludes that erosion-prone areas with rapid runoff are present in the area and adequate measures will assist in the sustainable management of land and water resources

CHANNEL MIGRATION AND CONSEQUENTIAL LAND USE LAND COVER CHANGES OF SUBANSIRI RIVER, ASSAM, NORTH-EASTERN INDIA

Subansiri River is the largest tributary of the Brahmaputra River running through the Indian states of Assam and Arunachal Pradesh, and Tibet, the Autonomous Region of China. The Subansiri River is 442 km long with a drainage basin of 32,640 km2 and it contributes approximately 7.92% of the Brahmaputra's total flow. Sequential Channel shifting has been witnessed as the most important characteristic of the Subansiri River of Assam. The detailed study on channel migration of the present course of the Subansiri River through the upper floodplain of Brahmaputra valley indicates that the area is under active erosion for a long time. Therefore, an attempt has been made to understand the relationship between the rate of channel migration and successive land use/land cover changes in its surrounding floodplain area. The Support Vector Machine (SVM) and the Artificial Neural Network (ANN) algorithms are applied on Landsat images of the years 1973, 1988, 2001, and 2017 for generating land use/land cover maps through supervised classification technique. The overall accuracy of the land use/land cover classification ranges between 81% (for the year 1988) and 84% (for the year 2017). The land use/land cover maps show an increase in the built-up area and a decrease in the agricultural area. The change has been observed vis-a-vis channel migration indicating that the migration directly affects the floodplain habitats which in turn affects the land use, Findings of this study highlight geomorphological instabilities of the study area and the vulnerability of the habitations residing near the Subansiri river

Assessment of active tectonics in the Siwalik basin around the Subansiri river, NE India.

In this paper we evaluate the morphotectonics of the area around the Subansiri river in north-eastern India. Research focuses on understanding the impacts on areas experiencing active tectonic deformation. It also explains the variety of kinematics observed in the area from the Miocene to the present. The tectonics can explain some structures related to the extensional tectonics predominant in the region and the development of the minor and major morph structures driven by faults with different kinematics. We developed a morphotectonic evolutionary model for the area based on the morphotectonic analysis and geological mapping. Morphotectonic indices used to evaluate the tectonic activeness in this study are Mountain Front sinuosity Index, Valley Floor Width to Valley Height Ratio, Asymmetry Factor, Transverse Topographic Symmetry Factor, Mountain Front Steepness Index, Basin Shape Index and Stream Length Gradient Index. There are numerous lineaments present in the study area which are trending in NW-SE and NE-SW directio

Evaluation of a Preliminary Support Design of Railway Tunnel Adit in Inner Lesser Himalaya India: An Empirical Analysis

This article addresses the excavation method and support design for the adit tunnel in the Rudraprayag District, Lesser Himalayas of India, using Rock Mass Rating (RMR), Tunneling Quality Index (Q), and New Austrian Tunneling Method (NATM). Based on ONORM B 2203 correlations with RMR and Q systems, the New Austrian Tunneling Method rock structure classes were developed. Because the geology was constantly changing, NATM concepts were applied. The RMR-based rock mass estimates were overestimated, but the qualitative investigation was correct. The NATM method is more appropriate for a Garhwal Himalayan rock with varying rock mass uncertainty. The present adit research reveals several outstanding questions about rock mass quality, tunnel behavior during construction, and use. The analysis results might be used to build new tunnels in comparable terrain in other parts of the world

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Not AvailableSnow cover is an important feature for the supply of freshwater and influences climatic hydrology at various altitudes, especially in mountain regions. Snow is a significant component of the environmental threat. In order to map and realize the extent of snow cover at high altitudes, continuous monitoring is therefore necessary. Data from satellite remote sensing helps to capture land cover and changes in land cover. The major intricacies in the snow cover mapping in the Leh region are the underlying vegetation, debris, and sparse snow. The Landsat OLI satellite data base methodology was developed to map the snow cover in the Leh region of the Indian Himalayas through NDSI (normalized difference snow index) to overcome such area specific issues. NDSI encompasses a reasonably good accuracy and can be used extensively because topographic shadows, water bodies and clouds can easily be misinterpreted as snow. It is capable of differentiating pixels of snow from pixels of cloud, debris, vegetation, and water. The NDSI was generated for snow mapping using Landsat OLI satellite images. Using the high reflectance of the snow in the blue band, misinterpreted water bodies were removed. NDSI was subsequently used month-wise to estimate the snow cover of the Leh region (Ladakh Union Territory of India). The findings of present study clearly indicate that the accuracy of the NDSI is reasonably appropriate for the estimation of the snow cover distribution over a wider area. It has been also observed that the snow cover in the study region has decreased over the years.Not Availabl

Development of correlations between various engineering rockmass classification systems using railway tunnel data in Garhwal Himalaya, India

Abstract Engineering rockmass classifications are an integral part of design, support and excavation procedures of tunnels, mines, and other underground structures. These classifications are directly linked to ground reaction and support requirements. Various classification systems are in practice and are still evolving. As different classifications serve different purposes, it is imperative to establish inter-correlatability between them. The rating systems and engineering judgements influence the assignment of ratings owing to cognition. To understand the existing correlation between different classification systems, the existing correlations were evaluated with the help of data of 34 locations along a 618-m-long railway tunnel in the Garhwal Himalaya of India and new correlations were developed between different rock classifications. The analysis indicates that certain correlations, such as RMR-Q, RMR-RMi, RMi-Q, and RSR-Q, are comparable to the previously established relationships, while others, such as RSR-RMR, RCR-Qn, and GSI-RMR, show weak correlations. These deviations in published correlations may be due to individual parameters of estimation or measurement errors. Further, incompatible classification systems exhibited low correlations. Thus, the study highlights a need to revisit existing correlations, particularly for rockmass conditions that are extremely complex, and the predictability of existing correlations exhibit high variations. In addition to augmenting the existing database, new correlations for metamorphic rocks in the Himalayan region have been developed and presented that can serve as a guide for future rock engineering projects in such formations and aid in developing appropriate excavation and rock support methodologies