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Pandit, R.

Publications and source records attributed to Pandit, R..

3 recordsLinked to original sources

Testing a theoretical framework for the environment-species abundance paradigm: a new approach to the Abundant Centre Hypothesis

The linkage between environment, a species fitness and its abundance is central to the theory of evolution. So far, all studies of this linkage have been heuristic and empirical due to an inability to determine fitness either experimentally (independent of abundance) or theoretically (from species-environment interaction). One category of such studies involves the Abundant Centre Hypothesis which posits that a species abundance rises to a maximum at the centre of its range. We argue that the confusing mix of results from ACH studies arises from ignoring the central premise that the abundance distribution cannot be independent of the environment. First, we employed a theoretical framework to identify an environmental context (an elevational transect; 200-2800 m in the eastern Himalayas) likely to favour ACH. We then improved upon some previously identified conceptual and methodological shortcomings of ACH studies. Using systematically collected bird data (245 species; 15867 records) from that transect we found that the community average abundance profile is symmetric, as expected by ACH. Notwithstanding which, the abundance profiles of individual species showed a small degree of asymmetry which was correlated with elevation. This elevational dependence may be due to the hard elevational limits at the lower and upper ends of the mountain, as expected from theoretical considerations. We also showed that the average abundance profile shape is close to gaussian, while ruling out uniform and inverted-quadratic shapes. This work demonstrates that selecting a particular category of environmental contexts can help in integrating theoretical tools into a field dominated by empirical studies. Such a union should spur the development of more detailed and testable theoretical models for better insights in an important field.

ecology↗

Comparative analysis of two NGS platforms and different databases for analysis of AMR genes

The use of antibiotics in human medicine and livestock production has contributed to the widespread occurrence of antimicrobial resistance (AMR). Recognizing the relevance of AMR to human and livestock health, it is important to assess the occurrence of genetic determinants of resistance in medical, veterinary, and public health settings in order to understand risks of transmission and treatment failure. Advances in Next Generation Sequencing (NGS) technologies have had a significant impact on research in microbial genetics and microbiome analyses. Now, strategies for high throughput sequencing from panels of PCR amplicons representing known AMR genes offer opportunities for targeted characterization of complex microbial populations. Aim of the present study was to compare the Illumina MiSeq and Ion Torrent S5 Plus sequencing platforms for use with the Ion AmpliSeq AMR Research Panel in a veterinary/public health setting. All samples were processed in parallel for the two sequencing technologies, subsequently following a common bioinformatics workflow to define the occurrence and abundance of AMR gene sequences. Regardless of sequencing platform, the results were closely comparable with minor differences. The Comprehensive Antibiotic Resistance Database (CARD), QIAGEN Microbial Insight - Antimicrobial Resistance (QMI-AR), Antimicrobial resistance database (AR), and CARD-CLC databases were compared for analysis, with the most genes identified using CARD. Drawing on these results we describe an end-to-end workflow for AMR gene analysis using NGS.

bioinformatics↗

Taxonomic scale dependency of Bergmann's patterns: A cross-scale comparison of hawkmoths and birds along a tropical elevational gradient

Bergmanns rule predicts a larger body size for endothermic organisms in colder environments. The multiplicity of patterns and processes is expected because body size and temperature are two most fundamental factors on which many physiological, ecological and evolutionary processes depend, affecting all levels of biological organization, from individuals to communities. The confounding results from previous studies may be due to the differences in taxonomic (intraspecific, interspecific and community) and spatial (latitudinal vs elevational) scales. We compared Bergmanns patterns for endotherms (Aves) and ectotherms (Lepidoptera: Sphingidae) along a same 2.6 km elevational transect in the eastern Himalayas. Using a large data spanning 3,302 hawkmoths (76 morpho-species) and 15,746 birds (245 species), we compared the patterns at the intraspecific (hawkmoths only), interspecific and community scales. At the interspecific scale, we account for phylogenetic non-independence in body mass by using a heirarchical linear mixed effects model for hawkmoths, and a phylogenetic generalised least squares model for birds. We assess the importance of using abundance-weighted metrics at the community scales, after accounting for spatial auto-correlation in communities. Hawkmoths exhibited positive Bergmanns pattern at the intraspecific and abundance-weighted community scale. Intraspecific variation accounted for a substantial 33% variation at the community level. Contrary to this, birds exhibited a strong converse-Bergmanns pattern at interspecific and community scales, both with- and without-abundance. Overall, all metrics which incorporate local traits and/or species abundances show stronger correlations than when this information is lacking. The multiplicity of patterns at a single location provides the opportunity to disentangle the relative contribution of individual- and species-level processes by integrating data across multiple nested taxonomic scales for the same taxa. We suggest that future studies of Bergmanns patterns should explicitly address taxonomic- and spatial-scale dependency, with species relative abundance and intraspecific trait variation as essential ingredients especially at short elevational scales.

ecology↗