Refine your search
Co-Authors
Journals
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Sahu, Sudam Charan
- Bibliometric Analysis of Research Publications of Indian Institute of Technology (IIT’s) Based on Published Literature as Reflected in Scopus
Abstract Views :293 |
PDF Views:14
Authors
Affiliations
1 Central Library, Central University of Orissa, Koraput – Odisha – 764021, IN
2 INFLIBNET Center, Gandhi Nagar - 382421, Gujarat, IN
1 Central Library, Central University of Orissa, Koraput – Odisha – 764021, IN
2 INFLIBNET Center, Gandhi Nagar - 382421, Gujarat, IN
Source
Journal of Information and Knowledge (Formerly SRELS Journal of Information Management), Vol 55, No 5 (2018), Pagination: 292-298Abstract
The Indian Institutes of technology (IITs) in India account for significant research outcomes from the country. This paper is an attempt to analyze the publications of five older IITs during the period 2007 to 2016 as reflected in SCOPUS, multidisciplinary international database. A total of 10583 research publications have been downloaded and analyzed. This paper tries to give an overview of the research output of the five IITs (IIT Bombay, IIT Kanpur, IIT Kharagpur, IIT Delhi, and IIT Madras) on different parameters like growth rate of research publications, authorship pattern, productivity per capita, degree of collaboration, etc.Keywords
Bibliometric Analysis, IITs, Research Output, Research Productivity, Scientometric Analysis, Scopus.References
- Bakri, A., Azura, N. M., Nadzar, M., Ibrahim, R. and Tahira, M. (2017). Publication productivity pattern of Malaysian researchers in scopus from 1995 to 2015. Journal of Scientometric Research, 6(2), 86-101. DOI:10.5530/ jscires.6.2.14. https://doi.org/10.5530/jscires.6.2.14.
- Banshal, S. K., Singh, V. K., Basu, A. and Muhuri, P. K. (2017). Research performance of Indian Institutes of Technology. Current Science, 112(05), 923-32. https://doi.org/10.18520/cs/v112/i05/923-932.
- Baskaran, C. (2013). Research productivity of Alagappa University during 1999-2011: A bibliometric study. DESIDOC Journal of Library and Information Technology, 33(3), 236-42. https://doi.org/10.14429/djlit.33.3.4609.
- Bid, S. (2016). Indian Institute of Technology, Kharagpur: A scientometric study of research output. Scientific Society of Advanced Research and Social Change SSARSC International Journal of Library Information Network and Knowledge, 1(1), 1-15.
- Garg, K.C. and Kumar, S. (2016). Scientometric profile of an Indian state: The case study of Odisha. COLLNET Journal of Scientometrics and Information Management, 10(1), 141-53.
- https://doi.org/10.1080/09737766.2016.1177950.
- Gautam, V. K. and Mishra, R. (2015). Scholarly research trend of Banaras Hindu University during 2004-2013: A scientometric study based on Indian citation index. DESIDOC Journal of Library & Information Technology, 35(2), 75-81. https://doi.org/10.14429/djlit.35.2.8021.
- Gupta, B., Dhawan, S. and Gupta, R. (2015). Highly cited publications output by India in materials science published during 2003–2012: A scientometric assessment. Journal of Scientometric Research, 4(3), 178-94. https://doi.org/10.4103/2320-0057.174859.
- Hadagali, G. S. (2014). Scientific productivity of Karnataka State during 1999-2011. Journal of Advances in Library and Information Science, 3(1), 72-84.
- Hadimani, N and K. R. Mulla and Kumar, N.S. (2015). Bibliometric analysis of research publications of Indian Institute of Science Education and Research, Thiruvananthapuram. Journal of Advancements in Library Sciencess, 02(01), 28-35.
- Hanumappa, A., Desai, A. and Dora, M. A. (2015). Bibliometrics profile of Gujarat University, Ahmedabad during 2004-2013. DESIDOC Journal of Library and Information Technology, 35(1), 9-16. https://doi.org/10.14429/djlit.35.1.7699.
- Kanwal, P. (2017). A Bibliometric study of world research output on free and open source software literature during 1960-2016. International Journal of Advanced Research in Computer Science, 8(3), 1067-72.
- Kumbar, M., Gupta, B. M. and Dhawan, S. M. (2008). Growth and impact of research output of University of Mysore, 1996-2006: A case study. Annals of Library and Information Studies, 55(3), 185-195.
- Maharana, R. K. and Das, P. (2013). Research publication trend of Utkal University’s researchers indexed in scopus during 2008 to 2012: A bibliometric analysis. Library Philosophy and Practice (e-Journal), Paper 999.
- Maharana, R. K. and Sethi, B. B. (2013). A bibliometric analysis of the research output of Sambalpur University’s publication in ISI web of science during 2007-11. Library Philosophy and Practice (e-Journal), Paper 926.
- Navaneethakrishnan, S. (2014). Authorship patterns and degree of collaboration of Sri Lankan scientific publications in Social Sciences and Humanities – A picture from SCOPUS. Library Philosophy and Practice (e-journal), Paper 1153.
- Pu, Q., Lyu, Q. and Su, H. (2016). Bibliometric analysis of scientific publications in transplantation journals from mainland China, Japan, South Korea and Taiwan between 2006 and 2015. BMJ Open, 6(8), 01-07. https://doi.org/10.1136/bmjopen-2016-011623.
- Singh, V. K. (2015). Mapping research output of Indian Institute of Technology Bhubaneswar. Indian Journal of Scientific Research, 11(2), 65-68.
- Predicting Potential Distribution, Range Change and Niche Dynamics for Saraca asoca (Roxb.) De Wilde: A Threatened Medicinal Plant under Climatic Change
Abstract Views :55 |
PDF Views:34
Authors
Monalisa Jena
1,
Manas Ranjan Mohanta
1,
Bipin Charles
2,
N. A. Aravind
2,
G. Ravikanth
2,
Sudam Charan Sahu
1
Affiliations
1 Department of Botany, Maharaja Sriram Chandra Bhanja Deo University, Baripada 757 003, IN
2 Ashoka Trust for Research in Ecology and the Environment, Royal Enclave, Srirampura, Jakkur, Bengaluru 560 064, IN
1 Department of Botany, Maharaja Sriram Chandra Bhanja Deo University, Baripada 757 003, IN
2 Ashoka Trust for Research in Ecology and the Environment, Royal Enclave, Srirampura, Jakkur, Bengaluru 560 064, IN
Source
Current Science, Vol 125, No 9 (2023), Pagination: 989-998Abstract
In the Anthropocene era, understanding the impact of climate change on niche shift, species distribution, and habitat change is increasingly important for the conservation of biodiversity. In this respect, species distribution models have been considered an important tool over the last decade. The present study illustrates distributional change, niche dynamics and climatic shifts of Saraca asoca (Roxb.) De Wilde in India, a proven medicinal plant and a listed threatened species by IUCN, under different climate change scenarios using MaxEnt. The robustness of the model was satisfactory (AUC = 0.936), indicating a good fit. There could be a significant gain in suitable habitat between the present and future scenarios, ranging from a minimum of 52,275.17 km2 (RCP 2.6) to a maximum of 95,994.62 km2 (RCP 4.5). In the future, the suitable habitat range would shift towards colder regions of India, where cultivation of S. asoca could be taken up, thus enabling effective management of the natural habitat and population of the species. This study will help understand the effects of climate change on S. asoca and its implications for conservation of the species.Keywords
Climate Change, Distributional Changes, Ecological Niche Models, Niche Overlap, Saraca asoca.References
- Patwardhan, A. et al., Distribution and population status of threatened medicinal tree Saraca asoca (Roxb.) De Wilde from Sahyadri–Konkan ecological corridor. Curr. Sci., 2016, 111(9), 1500–1506.
- Bhalerao, S. A., Verma, D. R., Didwana, V. S. and Teli, N. C., Saraca asoca (Roxb.), De. Wild: an overview. Ann. Plant Sci., 2014, 3(7), 770–775.
- Sabita, Sheel, R. and Kumar, B., Qualitative and quantitative screening of phytochemicals in polar and non-polar solvent extracts of stem bark and leaves of Saraca indica (L.). IOSR JBB, 2018, 4(5), 18–29.
- Haridasan, K., Anupam, S., Bhuyan, L. R., Hegde, S. N. and Ahlawat, S. P., SFRI Information Bulletin No. 16 – Field Manual for Propagation and Plantation of Medicinal Plants, State Forest Research Institute, Itanagar, 2003.
- Kumar, M., Bhatt, V. P. and Rajwar, G. S., Plant and soil diversities in a sub-tropical forest of the Garhwal Himalaya. Ghana J. For., 2006, 19, 20, 1–19.
- Warren, D. L., Glor, R. E. and Turelli, M., Environmental niche equivalency versus conservatism: quantitative approaches to niche evolution. Evolution, 2008, 62(11), 2868–2883.
- Brito, J. C., Acosta, A. L., Alvares, F. and Cuzin, F., Biogeography and conservation of taxa from remote regions: an application of ecological-niche based models and GIS to North-African canids. Biol. Conserv., 2009, 142(12), 3020–3029.
- Booth, T. H., Nix, H. A., Busby, J. R., Hutchinson, M. F. and Franklin, J., Bioclim: the first species distribution modelling package, its early applications and relevance to most current MaxEnt studies. Divers. Distrib., 2014, 20(1), 1–9.
- Elith, J. and Leathwick, J. R., Species distribution models: ecological explanation and prediction across space and time. Annu. Rev. Ecol. Evol. Syst., 2009, 40, 677–697.
- Booth, T. H., Why understanding the pioneering and continuing contributions of BIOCLIM to species distribution modelling is important. Austral. Ecol., 2018, 43(8), 852–860.
- Priti, H., Aravind, N. A., Uma Shaanker, R. and Ravikanth, G., Modeling impacts of future climate on the distribution of Myristicaceae species in the Western Ghats, India. Ecol. Eng., 2016, 89, 14–23.
- Miller, J., Species distribution modeling. Geogr. Compass, 2010, 4(6), 490–509.
- Antunez, P., Suarez-Mota, M., Valenzuela-Encinas, C. and Ruiz-Aquino, F., The potential distribution of tree species in three periods of time under a climate change scenario. Forests, 2018, 9(10), 628.
- Sarma, R. R., Munsi, M. and Aravind, N. A., Effect of climate change on invasion risk of giant African snail (Achatina fulica Ferussac, 1821: Achatinidae) in India. PLoS ONE, 2015; doi: https://doi.org/10.1371/journal.pone.0143724.
- Fortunel, C., Paine, C. E. T., Fine, P. V. A., Kraft, N. J. B., Baraloto, C. and De Deyn, G., Environmental factors predict community functional composition in Amazonian forests. J. Ecol., 2014, 102(1), 145–155.
- Jochum, G., Mudge, K. and Thomas, R., Elevated temperatures increase leaf senescence and root secondary metabolite concentrations in the understory herb Panax quinquefolius (Araliaceae). Am. J. Bot., 2007, 94(5), 819–826.
- Bertrand, R. et al., Changes in plant community composition lag behind climate warming in lowland forests. Nature, 2011, 479, 517–520.
- Lenoir, J., Gegout, J. C., Marquet, P. A., De Ruffray, P. and Brisse, H., A significant upward shift in plant species optimum elevation during the 20th century. Science, 2008, 320(5884), 1768–1771.
- Wang, W., Tang, X., Zhu, Q., Pan, K., Hu, Q., He, M. and Li, J., Predicting the impacts of climate change on the potential distribution of major native non-food bioenergy plants in China. PLoS ONE, 2014, 9(11), e111587; doi:10.1371/journal.pone.0111587.
- Barnosky, A. et al., Has the Earth’s sixth mass extinction already arrived? Nature, 2011, 471, 51–57.
- Chaturvedi, R. K., Raghubanshi, A. S. and Singh, J. S., Plant functional traits with particular reference to tropical deciduous forests: a review. J. Biosci., 2011, 36, 963–981.
- Yang, W. Z., Zhang, S. S., Wang, W. B., Kang, H. M. and Ma, N., A sophisticated species conservation strategy for Nyssa yunnanensis, a species with extremely small populations in China. Biodivers. Conserv., 2017, 26, 967–981.
- Xu, W. et al., Strengthening protected areas for biodiversity and ecosystem services in China. Proc. Natl. Acad. Sci. USA, 2017, 114(7), 1601–1606.
- Sumangala, R. C., Charles, B., Ganesh, D. and Ravikanth, G., Identifying conservation priority sites for Saraca asoca: an important medicinal plant using ecological niche models. Indian For., 2017, 143(6), 531–536.
- Chakraborty, R., Sen, S., Deka, M. K., Rekha, B. and Sachan, S., Anti-microbial evaluation of Saraca indica leaves extracts by disk diffusion method. Res. J. Pharm. Biol. Chem., 2014, 1(1), 1–5.
- Athiralakshmy, T. R., Divyamol, A. S. and Nisha, P., Phytochemical screening of Saraca asoca and antimicrobial activity against bacterial species. Asian J. Plant Sci., 2016, 6(2), 30–36.
- Smitha, G. R. and Thondaiman, V., Reproductive biology and breeding system of Saraca asoca (Roxb.) De Wilde: a vulnerable medicinal plant. Springer Plus, 2016, 5(1), 2025.
- Radosavljevic, A. and Anderson, R. P., Making better MaxEnt models of species distributions: complexity, over fitting and evaluation. J. Biogeogr., 2013, 41(4), 629–643.
- Aiello-Lammens, M. E., Boria, R. A., Radosavljevic, A., Vilela, B. and Anderson, R. P., Sp Thin: an R package for spatial thinning of species occurrence records for use in ecological niche models. Ecography, 2015, 38(5), 541–545.
- Anderson, R. P., Harnessing the world’s biodiversity data: promise and peril in ecological niche modeling of species distributions. Ann. N.Y. Acad. Sci., 2012, 1260, 66–80.
- Kramer‐Schadt, S., Niedballa, J., Pilgrim, J. D., Schroder, B., Lindenborn, J., Reinfelder, V. and Wilting, A., The importance of correcting for sampling bias in MaxEnt species distribution models. Divers. Distrib., 2013, 19, 1366–1379.
- Boria, R. A., Olson, L. E., Goodman, S. M. and Anderson, R. P., Spatial filtering to reduce sampling bias can improve the performance of ecological niche models. Ecol. Model., 2014, 275, 73–77.
- Moss, R. H., Edmonds, J. A., Hibbard, K. A., Manning, M. R., Rose, S. K. and Van Vuuren, D. P., The next generation of scenarios for climate change research and assessment. Nature, 2010, 463, 747–756.
- Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. and Jarvis, A., Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol., 2005, 25, 1965–1978.
- Oke, T. A. and Hager, H. A., Assessing environmental attributes and effects of climate change on Sphagnum peat land distributions in North America using single- and multi-species models. PLoS ONE, 2017; https://doi.org/10.1371/journal.pone.0175978.
- Mamgain, A. and Uniyal, P. L., Species distribution modelling of Rhododendron arboreum Sm. A keystone species in India and adjoining regions. Int. J. Ecol. Environ. Sci., 2018, 44(3), 251–259.
- Dormann, C. F. et al., Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography, 2013, 36(1), 27–46.
- Joshi, M., Charles, B., Ravikanth, G. and Aravind, N. A., Assigning conservation value and identifying hotspots of endemic rattan diversity in the Western Ghats, India. Plant Divers., 2017, 39(5), 263–272.
- Hamid, M., Khuroo, A. A., Charles, B., Ahmad, R., Singh, C. P. and Aravind, N. A., Impact of climate change on the distribution range and niche dynamics of Himalayan birch, a typical treeline species in Himalayas. Biodivers. Conserv., 2018, 28, 2345–2370.
- Phillips, S. J., Anderson, R. P. and Schapire, R. E., Maximum entropy modeling of species geographic distributions. Ecol. Modell., 2006, 190(3–4), 231–259.
- Phillips, S. J., Anderson, R. P., Dudik, M., Schapire, R. E. and Blair, M. E., Opening the black box: an open-source release of MaxEnt. Ecography, 2017, 40(7), 887–893.
- Swets, J. A., Measuring the accuracy of diagnostic systems. Science, 1988, 240, 1285–1293.
- Brown, J. L., SDM toolbox: a python-based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses. Methods Ecol. Evol., 2014, 5(7), 694–700.
- Brown, J. L., Bennett, J. R. and French, C. M., SDMtoolbox 2.0: the next generation Python-based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses. Peer J., 2017, 5, e4095; doi:https://doi.org/10.7717/peerj.4095.
- Broennimann, O. et al., Measuring ecological niche overlap from occurrence and spatial environmental data. Global Ecol. Biogeogr., 2012, 21(12), 481–497.
- Petitpierre, B., Kueffer, C., Broennimann, O., Randin, C., Daehler, C. and Guisan, A., Climatic niche shifts are rare among terrestrial plant invaders. Science, 2012, 335(6074), 1344–1348; doi:https://doi.org/10.1126/science.1215933.
- Li, Y., Liu, X., Li, X., Petitpierre, B. and Guisan, A., Residence time, expansion toward the equator in the invaded range and native range size matter to climatic niche shifts in non-native species. Global Ecol. Biogeogr., 2014, 23(10), 1094–1104.
- Di Cola, V. et al., Ecospat: an R package to support spatial analyses and modeling of species niches and distributions. Ecography, 2017, 40(6), 774–787.
- Schiaffini, M. I., Niche overlap and shared distributional patterns between two South American small carnivorans: Galictis cuja and Lyncodon patagonicus (Carnivora: Mustelidae). Mammalia, 2017, 81(5), 455–463.
- Franklin, J., Species distribution models in conservation biogeography: developments and challenges. Divers. Distrib., 2013, 19, 1217–1223.
- Ahmad, R., Khuroo, A. A., Hamid, M., Charles, B. and Rashid, I., Predicting invasion potential and niche dynamics of Parthenium hysterophorus (Congress grass) in India under projected climate change. Biodivers. Conserv., 2019, 28, 2319–2344.
- Slater, H. and Michael, E., Predicting the current and future potential distributions of lymphatic filariasis in Africa using maximum entropy ecological niche modelling. PLoS ONE, 2012, 7(2), e32202; doi:10.1371/journal.pone.0032202.
- Guisan, A. et al., Predicting species distributions for conservation decisions. Ecol. Lett., 2013, 16(12), 1424–1435.
- Chitale, V. S. and Behera, M. D., Can the distribution of sal (Shorea robusta Gaertn. f.) shift in the northeastern direction in India due to changing climate? Curr. Sci., 2012, 102(8), 1126–1135.
- Islam, K., Rahman, M. F., Islam, K. N., Nath, T. K. and Jashimuddin, M., Modeling spatiotemporal distribution of Dipterocarpus turbinatus Gaertn. f. in Bangladesh under climate change scenarios. J. Sustain. For., 2019, 39(3), 1–21.
- Ksiksi, T. S. et al., Climate change-induced species distribution modeling in hyper-arid ecosystems. F1000Research, 2019, 8, 978.
- Harrison, S., Spasojevic, M. J. and Li, D., Climate and plant community diversity in space and time. Proc. Natl. Acad. Sci. USA, 2020, 117(9), 4464–4470.
- IPCC, Climate Change, Synthesis Report, Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Geneva, Switzerland, 2014, p. 151.
- Reddy, M. T., Begum, H., Sunil, N., Pandravada, S. R., Sivaraj, N. and Kumar, S., Mapping the climate suitability using MaxEnt modeling approach for Ceylon spinach (Basella alba L.) cultivation in India. J. Agric. Sci., 2015, 10(2), 87–97.
- Zhang, K., Yao, L., Meng, J. and Tao, J., MaxEnt modeling for predicting the potential geographical distribution of two peony species under climate change. Sci. Total Environ., 2018, 634, 1326–1334.
- Gebrewahid, Y. et al., Current and future predicting potential areas of Oxytenanthera abyssinica (A. Richard) using MaxEnt model under climate change in northern Ethiopia. Ecol. Process., 2020 9, 6; https://doi.org/10.1186/s13717-019-0210-8.