{"id":8835,"date":"2024-09-30T19:41:39","date_gmt":"2024-09-30T18:41:39","guid":{"rendered":"https:\/\/icertpublication.com\/?page_id=8835"},"modified":"2026-04-03T09:00:16","modified_gmt":"2026-04-03T03:30:16","slug":"unleashing-the-potential-of-artificial-intelligence-ai-tools-in-phytogeographical-studies","status":"publish","type":"page","link":"https:\/\/icert.org.in\/index.php\/shodh-sari-2\/sodh-sari-vol-3-issue-4\/unleashing-the-potential-of-artificial-intelligence-ai-tools-in-phytogeographical-studies\/","title":{"rendered":"Unleashing the Potential of Artificial Intelligence (AI) Tools in Phytogeographical studies"},"content":{"rendered":"\t\t
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Shodh Sari-An International Multidisciplinary Journal<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Vol-03, Issue-04 (Oct-Dec 2024)<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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An International scholarly\/ academic journal, peer-reviewed\/ refereed journal, ISSN : 2959-1376<\/h5>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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Unleashing the Potential of Artificial Intelligence (AI) Tools in Phytogeographical studies<\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Chauhan, Nisha<\/span>1<\/span><\/span>\u00a0<\/span><\/p>

1<\/span><\/span>Assistant Professor, Department of Geography, S D (P G) College Muzaffarnagar, U.P.<\/span>
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Kumar, Manoj<\/span>2<\/span><\/span>\u00a0<\/span><\/p>

2<\/span><\/span>Lecturer in Biology, Govt. I. College, Kunda, U.S. Nagar, U.K., Ex coordinator in UOU, Haldwani, Nainital, Uttarakhand<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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DOI: <\/span>https:\/\/doi.org\/10.59231\/SARI7746<\/span><\/a><\/p>

Subject: Botany \/ Environmental Science \/ Artificial Intelligence<\/span><\/p>

Page No: 47\u201366<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t

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Received: May 30, 2024<\/span><\/p>

Accepted: Aug 13, 2024<\/span><\/p>

Published: Oct 01, 2024<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Thematic Classification: Phytogeography, Artificial Intelligence in Science, Plant Distribution Modeling, Digital Herbarium, Biodiversity Informatics, AI Tools for Ecology.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Abstract\n<\/h6>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Phytogeography, the study of the geographic distribution of plants, is important for understanding ecosystem dynamics, biodiversity, and ecological processes. Over the past few years, advances in technology, especially artificial intelligence (AI), have revolutionized various scientific fields, including ecology and environmental science. In recent years, AI techniques have been increasingly applied in phytogeography, providing new opportunities to increase our understanding of plant distribution patterns and improve conservation efforts. The study of the role of artificial intelligence in phytogeography focuses on how AI techniques such as machine learning, remote sensing, and spatial analysis are being used to analyse large-scale plant distribution data. By leveraging AI, researchers can gain valuable insights from vast and complex datasets, identify patterns and predict future changes in plant distributions with greater accuracy. Furthermore, AI-driven approaches have the potential to address important challenges in phytogeography, such as species distribution modelling, habitat mapping, and biodiversity conservation. By integrating AI with traditional ecological methods, more effective strategies can be developed to manage and conserve plant species and their habitats. AI-driven phytogeography research, provides an overview of recent progress, discusses potential applications of AI techniques in ecological studies, and the opportunities and challenges associated with the use of AI in understanding and conserving plant biodiversity. Ultimately, the integration of AI with phytogeography has the potential to revolutionize our understanding of plant distributions and inform more sustainable conservation practices in the face of global environmental change.<\/span><\/p>

Keywords<\/span>: Phytogeography, Ecosystem Dynamics, Remote Sensing, Modelling, Revolutionizing, Machine learning.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Impact Statement\n<\/h6>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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The impact of using Artificial Intelligence (AI) tools in phytogeographical studies, which focus on the distribution of plant species and their relationships to geographical, environmental, and climatic factors, is significant. The introduction of AI has brought several advances and innovations, transforming how researchers approach the subject. There are some potential impacts of AI in various field of phytogeographical studies i.e. Data Analysis and Modelling, Biodiversity Conservation, Handling Big Data in Phytogeography, AI for Climate Change and Habitat Mapping, AI for Climate Change, Habitat Mapping, Automation and Efficiency. AI tools have the potential to revolutionize phytogeographical studies by improving the accuracy, efficiency, and scope of research. By integrating AI for data analysis, predictive modelling, and species identification, researchers can better understand plant distribution patterns and respond to environmental challenges such as climate change and habitat loss. However, ongoing challenges related to data quality, computational resources<\/span>, and model interpretability must be addressed to fully unleash the potential of AI in this field.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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About The Author<\/h6>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Dr Nisha Chauhan is working as Assistant Professor in Geography at S D College Muzaffarnagar UP. She has completed her secondary education from UP Board of secondary education and higher education including Ph.D.in geography from M.J.P. Rohilkhand University Bareilly. She has 10 years teaching and research experience to teach U.G and P.G. classes. She has published 7 Research Paper and a chapter in research book.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Cite this Article\n\n<\/h6>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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APA 7th Style:<\/span> Chauhan, N., & Kumar, M. (2024). Unleashing the potential of artificial intelligence (AI) tools in phytogeographical studies. <\/span>Shodh Sari-An International Multidisciplinary Journal<\/span>, <\/span>3<\/span>(04), 47\u201366. <\/span>https:\/\/doi.org\/10.59231\/SARI7746<\/span><\/a><\/p>

Chicago 17th Style:<\/span> Chauhan, Nisha, and Manoj Kumar. “Unleashing the Potential of Artificial Intelligence (AI) Tools in Phytogeographical Studies.” <\/span>Shodh Sari-An International Multidisciplinary Journal<\/span> 3, no. 4 (2024): 47\u201366. <\/span>https:\/\/doi.org\/10.59231\/SARI7746<\/span><\/a>.<\/span><\/p>

MLA 9th Style:<\/span> Chauhan, Nisha, and Kumar, Manoj. “Unleashing the Potential of Artificial Intelligence (AI) Tools in Phytogeographical Studies.” <\/span>Shodh Sari-An International Multidisciplinary Journal<\/span>, vol. 3, no. 4, 2024, pp. 47-66, <\/span>https:\/\/doi.org\/10.59231\/SARI7746<\/span><\/a>.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Statements & Declarations\n\n<\/h6>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Review Method:<\/span> This article underwent a double-blind peer-review process by two independent external experts in Biogeography and Computational Intelligence to evaluate the integration of AI algorithms in mapping plant distributions and ecological modeling.<\/span><\/p>

Competing Interests:<\/span> The author Nisha Chauhan and the author Manoj Kumar declare that there are no financial, personal, or professional conflicts of interest that could have inappropriately influenced the research findings or the technological assessments presented in this study.<\/span><\/p>

Funding:<\/span> This research was conducted as part of the authors’ academic and professional activities at S D (P G) College Muzaffarnagar and Govt. I. College Kunda. No specific external grants or commercial funding from AI software providers were received for this work.<\/span><\/p>

Data Availability:<\/span> The analysis is based on a synthesis of existing phytogeographical datasets and the application of AI tools such as Machine Learning and GIS-based predictive modeling. Theoretical frameworks and digital tool references are provided within the manuscript.<\/span><\/p>

License:<\/span> Unleashing the Potential of Artificial Intelligence (AI) Tools in Phytogeographical studies<\/span> \u00a9 2024 by Nisha Chauhan and Manoj Kumar is licensed under <\/span>CC BY-NC-ND 4.0<\/span>. This work is published by the International Council for Education Research and Training (ICERT).<\/span><\/p>

Ethics Approval:<\/span> As this study is a theoretical and methodological review of AI applications in plant geography and does not involve direct experimentation on human participants or protected animal species, it was deemed exempt from formal ethical review.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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References<\/h6>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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1.<\/span> Elith, J., and Leathwick, J.R. (2009). Species distribution models: ecological explanation and prediction in space and time. Annual Review of Ecology, Evolution and Systematics, 40, 677\u2013697.<\/span><\/p>

2. Franklin, J. (2010). Mapping and spatial estimation and prediction of species distribution. Cambridge University Press.<\/span><\/p>

3. He, K., Zhang, X., Ren, S., and Sun, J. (2016). Deep residual learning for image recognition. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 770\u2013778).<\/span><\/p>

4. Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G., and Jarvis, A. (2005). Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25(15), 1965\u20131978.<\/span><\/p>

5. Phillips, S.J., Anderson, R.P., and Shapire, R.E. (2006). Maximum entropy modeling of the geographic distribution of species. Ecological Modeling, 190(3-4), 231-259.<\/span><\/p>

5. Phillips, S.J., Anderson, R.P., and Shapire, R.E. (2006). Maximum entropy modeling of the geographic distribution of species. Ecological Modeling, 190(3-4), 231-259.<\/span><\/p>

6. Potapov, P., Turubanova, S., Hansen, M.C., Addussi, B., Broich, M., Altstadt, A., … and Justice, C.O. (2012). Quantifying forest cover loss in the Democratic Republic of the Congo, 2000\u20132010, with Landsat ETM data. Remote Sensing of the Environment, 122, 106-116.<\/span><\/p>

7. Ren, J., Zhang, H., and Ruan, S. (2020). A review of species distribution modeling and its applications in bioinformatics. Current Bioinformatics, 15(4), 309-320.<\/span><\/p>

8. Schroeter, M., Diaz, S., Setele, J., and Bellmaker, J. (2019). Mapping the global distribution of local plant diversity: past progress and future perspectives. Proceedings of the Royal Society B, 286(1910), 20182732.<\/span><\/p>

9. Swets, J.A. (1988). Measuring the accuracy of diagnostic systems. Science, 240(4857), 1285-1293.<\/span><\/p>

10. Thissen, A.E., and Patterson, D.J. (2011). Data issues in life sciences. Jukies, 150, 15-51.<\/span><\/p>

11. Veloz, S.D., Williams, J.W., Blois, J.L., He, F., Otto-Bliesner, B., and Liu, Z. (2012). No-analog climate and implications for 21st-century predictions of realized changes during the late Quaternary by species distribution models. Global Change Biology, 18(5), 1698\u20131713.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Shodh Sari-An International Multidisciplinary Journal Vol-03, Issue-04 (Oct-Dec 2024) An International scholarly\/ academic journal, peer-reviewed\/ refereed journal, ISSN : 2959-1376 Unleashing the Potential of Artificial Intelligence (AI) Tools in Phytogeographical studies Chauhan, Nisha1\u00a0 1Assistant Professor, Department of Geography, S D (P G) College Muzaffarnagar, U.P. Kumar, Manoj2\u00a0 2Lecturer in Biology, Govt. I. College, Kunda, U.S. […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":8763,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"postBodyCss":"","postBodyMargin":[],"postBodyPadding":[],"postBodyBackground":{"backgroundType":"classic","gradient":""},"site-sidebar-layout":"no-sidebar","site-content-layout":"page-builder","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"disabled","ast-breadcrumbs-content":"","ast-featured-img":"disabled","footer-sml-layout":"","theme-transparent-header-meta":"default","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"class_list":["post-8835","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/icert.org.in\/index.php\/wp-json\/wp\/v2\/pages\/8835","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/icert.org.in\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/icert.org.in\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/icert.org.in\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/icert.org.in\/index.php\/wp-json\/wp\/v2\/comments?post=8835"}],"version-history":[{"count":12,"href":"https:\/\/icert.org.in\/index.php\/wp-json\/wp\/v2\/pages\/8835\/revisions"}],"predecessor-version":[{"id":31579,"href":"https:\/\/icert.org.in\/index.php\/wp-json\/wp\/v2\/pages\/8835\/revisions\/31579"}],"up":[{"embeddable":true,"href":"https:\/\/icert.org.in\/index.php\/wp-json\/wp\/v2\/pages\/8763"}],"wp:attachment":[{"href":"https:\/\/icert.org.in\/index.php\/wp-json\/wp\/v2\/media?parent=8835"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}