Estimating Land Subsidence and Gravimetric Anomaly Induced by Aquifer Overexploitation in the Chandigarh Tri-City Region, India by Coupling Remote Sensing with a Deep Learning Neural Network Model

This study utilizes surface displacement data from Persistent Scatterer SAR Interferometry (PSInSAR) of Sentinel-1 satellite and groundwater storage change data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission to understand land subsidence in the Chandigarh tri-city region. The satellite datasets are used along with the groundwater level data obtained from wells over the study area. Since the GRACE data are available at a much coarser spatial resolution of 1o by 1o, challenges remain in correlating the dataset with PSInSAR displacement that has been multi-looked at 14 m by 14 m resolution. Therefore, multiple sources of data (i.e., the monthly average of GRACE data, groundwater storage change and monthly average PSInSAR displacement per pixel, and interpolated groundwater level data from wells for 2017 to 2022) have been deployed into a deep learning multi-layer perceptron (DLMLP) model to estimate the groundwater storage change at the urban level. This has an indirect downscaling method that is carried out successfully using the DLMLP model for the estimation of groundwater storage changes at the urban level, which is usually complicated by applying direct downscaling methods on the GRACE data. Thus, the DLMLP model developed here is a distinctive approach considered for estimating the changes in groundwater storage using PSInSAR displacement, groundwater data from wells, and GRACE data. The DLMLP model gives an R2-statistics value of 0.91 and 0.89 in the training and testing phases, respectively, and has a mean absolute error (MAE) of 1.23 and root mean square error (RMSE) of 0.87

Distribution of Some Macrophytes in relation to Water Depth in Three Lakes of Kashmir Valley, India

N

Think globally, measure locally: The MIREN standardized protocol for monitoring plant species distributions along elevation gradients

Climate change and other global change drivers threaten plant diversity in mountains worldwide. A widely documented response to such environmental modifications is for plant species to change their elevational ranges. Range shifts are often idiosyncratic and difficult to generalize, partly due to variation in sampling methods. There is thus a need for a standardized monitoring strategy that can be applied across mountain regions to assess distribution changes and community turnover of native and non-native plant species over space and time. Here, we present a conceptually intuitive and standardized protocol developed by the Mountain Invasion Research Network (MIREN) to systematically quantify global patterns of native and non-native species distributions along elevation gradients and shifts arising from interactive effects of climate change and human disturbance. Usually repeated every five years, surveys consist of 20 sample sites located at equal elevation increments along three replicate roads per sampling region. At each site, three plots extend from the side of a mountain road into surrounding natural vegetation. The protocol has been successfully used in 18 regions worldwide from 2007 to present. Analyses of one point in time already generated some salient results, and revealed region-specific elevational patterns of native plant species richness, but a globally consistent elevational decline in non-native species richness. Non-native plants were also more abundant directly adjacent to road edges, suggesting that disturbed roadsides serve as a vector for invasions into mountains. From the upcoming analyses of time series, even more exciting results can be expected, especially about range shifts. Implementing the protocol in more mountain regions globally would help to generate a more complete picture of how global change alters species distributions. This would inform conservation policy in mountain ecosystems, where some conservation policies remain poorly implemented

Azolla cristata in the Kashmir Himalaya

Volume: 102Start Page: 224End Page: 22

cpDNA Microsatellite Markers for <i>Lemna minor</i> (Araceae): Phylogeographic Implications

Premise of the study: A lack of genetic markers impedes our understanding of the population biology of Lemna minor. Thus, the development of appropriate genetic markers for L. minor promises to be highly useful for population genetic studies and for addressing other life history questions regarding the species. Methods and Results: For the first time, we characterized nine polymorphic and 24 monomorphic chloroplast microsatellite markers in L. minor using DNA samples of 26 individuals sampled from five populations in Kashmir and of 17 individuals from three populations in Quebec. Initially, we designed 33 primer pairs, which were tested on genomic DNA from natural populations. Nine loci provided markers with two alleles. Based on genotyping of the chloroplast DNA fragments from 43 sampled individuals, we identified one haplotype in Quebec and 11 haplotypes in Kashmir, of which one occurs in 56% of the genotypes, one in 8%, and nine in 4%, respectively. There was a maximum of two alleles per locus. Conclusions: These new chloroplast microsatellite markers for L. minor and haplotype distribution patterns indicate a complex phylogeographic history that merits further investigation

Phenotypic Variability and Genetic Diversity of Phragmites australis in Quebec and Kashmir Reveal Contrasting Population Structure

The origin of differences in traits influencing competitive success between invasive and native wild populations of alien species is subject of debate. Herbarium-based information sources from 2005 onwards about nativity and distributional range of Phragmites australis were used to survey putative native populations of the species in Quebec, and chloroplast DNA (cpDNA) PCR-RFLP analyses identified only one native population, whereas the same analyses revealed that the Kashmir populations are invasive. We compared the native population of P. australis in Quebec (QN), ten populations invasive to Quebec (QE), and five populations invasive in Kashmir, India (KE) using morphometric traits. Using nine cpDNA microsatellite loci, we also compared nine KE populations, ten QE populations, and the QN population. Phenotypic variation was observed among and within populations. Only dry mass of flowers varied across regions. Characterization of morphotypes defined three distinct haplotypes. A bimodal distribution of stem diameter (SD), internode length (IL), leaf length (LL), and leaf width (LW) suggests that a major gene may control growth traits or occurrence of co-selection. High genetic differentiation was observed between populations (RST = 0.353) and haplotypes (RST = 0.133 to 0.418), indicating limited gene flow and probable local adaptation. Principal coordinates analysis and the neighbor-joining phylogenetic tree clearly distinguished the three haplotypes. Among-populations phenotypic difference (PST) was lower than overall RST for plant height, SD, and fresh and dry mass of flowers and seeds, whereas PST estimates for LL and LW exceeded among-populations RST, suggesting divergent selection, while local adaptation might have occurred in IL, LL, and flower masses. Genetic drift probably influenced among-populations IL differences